Agricultural subsurface drainage systems are commonly installed on farmland to remove the excess water from poorly drained soils. Conventional methods for drainage mapping such as tile probes and trenching equipment are laborious, cause pipe damage, and are often inefficient to apply at large spatial scales. Knowledge of locations of an existing drainage network is crucial to understand the increased leaching and offsite release of drainage discharge and to retrofit the new drain lines within the existing drainage system. Recent technological developments in non-destructive techniques might provide a potential alternative solution. The objective of this study was to determine the suitability of unmanned aerial vehicle (UAV) imagery collected using three different cameras  and ground penetrating radar (GPR) for subsurface drainage mapping. Both the techniques are complementary in terms of their usage, applicability, and the properties they measure and were applied at four different sites in the Midwest USA. At Site-1, both the UAV imagery and GPR were equally successful across the entire field, while at Site-2, the UAV imagery was successful in one section of the field, and GPR proved to be useful in the other section where the UAV imagery failed to capture the drainage pipes’ location. At Site-3, less to no success was observed in finding the drain lines using UAV imagery captured on bare ground conditions, whereas good success was achieved using GPR. Conversely, at Site-4, the UAV imagery was successful and GPR failed to capture the drainage pipes’ location. Although UAV imagery seems to be an attractive solution for mapping agricultural subsurface drainage systems as it is cost-effective and can cover large field areas, the results suggest the usefulness of GPR to complement the former as both a mapping and validation technique. Hence, this case study compares and contrasts the suitability of both the methods, provides guidance on the optimal survey timing, and recommends their combined usage given both the technologies are available to deploy for drainage mapping purposes. Subsurface drainage systems are installed in agricultural areas to remove excess water and convert poorly drained soils into productive cropland. Some of the most productive agricultural regions in the world are a result of subsurface drainage practices . SubsurfIn addition, the installation of a new set of drain lines to enhance soil water removal efficiency or for sub-irrigation requires accurate knowledge of the existing drainage system as the new drain lines are typically installed between the old drain lines ,15. ThisThe traditional methods of drainage mapping involve the use of tile probes and trenching equipment. While the tile probes are time-consuming, tedious, and hard to employ across large spatial scales, the use of trenching equipment, though effective, is extremely invasive and severs the drainage pipes, thus requiring costly repairs . Non-desIn relation to remote sensing techniques, most of the previous studies analyzed satellite imagery or aerial imagery from manned aircraft or helicopters to study subsurface drainage systems ,36,37,38GPR works in a frequency range of 10 MHz to 1 GHz and consists of transmitter and receiver antennas. The transmitter antenna transmits electromagnetic (EM) energy into the ground and a receiver antenna records the earth’s impulse response, i.e., the reflected and scattered energy. Two electrical properties—relative dielectric permittivity (RDP) and electrical conductivity (EC)—mainly control the GPR wave propagation in the subsurface as the magnetic permeability is generally assumed a constant . The degIn the case of drainage pipe mapping, the detectability arises because of the contrast in RDP between the material inside the drainage pipe (air/water) and the material surrounding the drainage pipe (soil). The material of the pipe itself (clay/ceramic/polyvinyl chloride/polyethylene) has no effect on the GPR drainage pipe response ,16,50. MDrainage pipes at their usual depth of installation (0.6–1.5 m) can be regarded as a point size object and therefore show up as hyperbolas in vertical profiles obtained along a perpendicular traverse relative to the drainage pipe orientation. If the GPR transect is over the top and along the trend of a drain line, it will show up as a banded linear feature in the vertical profile ,26,31. TThe detectability of drain line signatures in UAV imagery is possible due to the greater water removal and soil drying directly above a drain line after a significant rainfall event in comparison to the soil between the drain lines ,37,43. CFurthermore, early into the growing season, the crops tend to establish first directly above the drain lines and are in better health compared to in between the drain lines as optimal soil–water–air conditions are established for proper aeration ,40,45. TTherefore, on the one hand, we have GPR that responds to subsurface variation in soil electrical properties, provides depth information, and has showed significant success in drainage pipe detection. At the same time, it is expensive to employ across large farm field areas and has limited PD in high-EC soils. On the other hand, we have the newly emerging UAV-based sensory technology which measures the surface variation in soil and plant properties, is more feasible, and has showed promise for drainage pipe mapping across large field areas. However, it comes with its own set of drawbacks such as the inability to detect or demarcate the drain lines’ location under certain conditions. Given the complementary nature of their usage, applicability, and the information they provide concerning drainage pipe mapping, further investigation is needed regarding their combined use.In this study, we evaluate the potential of UAV imagery in combination with GPR across four study sites in the Midwest USA for mapping agricultural subsurface drainage systems. The UAV imagery and GPR surveys were performed flexibly when an opportunity arose and without adhering to any specific criteria concerning the prior rainfall and site surface conditions. The UAV imagery data were collected using three different cameras  and the GPR data were collected across a limited spatial extent, preferably in the direction perpendicular to the expected drain line orientation or in a random fashion when the orientation was unknown, by using parallel, spiral, and serpentine transects. The hypotheses tested were as follows: (1) the UAV imagery might not be able to capture the drain line signature on all the different soil types due to non-existent ideal conditions concerning prior rainfall, ground wetness level, crop residue, time of day the imagery was captured, etc., (2) the drainage pipe response can vary between different bandwidths of imagery, and (3) the use of GPR in combination is useful at least on a limited spatial extent as it acts as validation by confirming the drainage pipe signature depicted in the UAV imagery, providing information on drainage pipes’ depth and possibly ascertaining whether the farm field is subsurface drained or not. Overall, the case study presented here explores the suitability of both technologies, comparing and contrasting their abilities, and provides insight into their complementary use. Further, an attempt was made to develop guidelines on the optimal survey timing concerning prior rainfall  and site surface  conditions for employing these sensors to derive maximal success in subsurface drainage mapping.Two sites in Ohio (OH) and two sites in Michigan (MI), all within the Midwest USA, were visited as a part of this study. Site-1, OH:Site-1 is located in Morrow County of central OH. According to SoilWeb-Earth , the soiSite-2, MI:Site-2 is located in Lenawee County of MI. The soils at this site include Blount loam , Glynwood loam , Griffin and Genesee loams , Pewamo clay and mucky clay loam , Griffin and Sloan sandy loams , and Morley loam . The area of interest is around 100 ha b. The siSite-3, MI:Site-3 is located in Lenawee County of MI. The soils at this site are mostly Brady and Macomb loams  and Brady sandy loam . The area of interest is around 45 ha c, and thSite-4, OH:Site-4 is located in Seneca County of OH. The soils here are mainly Blount silt loam  and Pandora silt loam . The area of interest is around 33 ha d, and thA fixed-wing UAV, eBee Plus  is a 20 Mpx camera with a 28 mm focal lens and was used to collect high-resolution (2.8 cm/px) panchromatic VIS-C (400–700 nm wavelengths) photos. The UAV, when configured with the S.O.D.A. camera, had RTK/GNSS functionality and provided survey-grade positional accuracy (0.7 cm) for the VIS-C imagery obtained. To use RTK/GNSS functionality with the UAV S.O.D.A. configuration, onsite connection via the internet was achieved with state (OH and MI) Department of Transportation virtual reference station networks. A lateral photo overlap of 70% between the adjacent flight lines and a longitudinal photo overlap of 60% along the flight line was maintained while flying with the S.O.D.A. camera.The Sequoia  MS camera captured 16 Mpx photos in VIS-C and 1.2 Mpx photos in four narrow bands of green (530–570 nm), red (640–680 nm), red edge (730–740 nm), and NIR (770–810 nm) wavelengths, respectively. The UAV, when configured with the Sequoia camera, did not have RTK/GNSS functionality. Hence, the positional accuracy was approximately 4 m for the imagery obtained. A lateral photo overlap of 60% and a longitudinal overlap of 80% were maintained while flying with the Sequoia camera. The senseFly SA thermoMAP TIR camera captured 0.3 Mpx photos in a wavelength range of 8.5–11.5 μm. Again, the UAV, when configured with the thermoMAP camera, did not have RTK/GNSS functionality, and the positional accuracy of the photos was approximately 4 m. A lateral photo overlap of 70% and a longitudinal photo overlap of 90% were maintained while flying with the thermoMAP camera. It is worth a mention that for the UAV flights carried out at a similar height, both the spatial and spectral resolutions of a TIR camera are, in general, coarser when compared to the VIS-C and MS cameras see . This isCloud-connected, high-precision AeroPoints  were used as ground control points (GCPs) to confirm the positional accuracy of the UAV S.O.D.A. surveys and to greatly improve the positional accuracy of the UAV Sequoia surveys. For the TIR imagery, the AeroPoints did not show up well, and hence a 61-cm (24 in.)-diameter aluminum pizza pan was placed next to each AeroPoint in the field. The aluminum pizza pans showed up well on both S.O.D.A. and thermoMap images. Consequently, the S.O.D.A. survey was used to obtain accurate positional coordinates for the pizza pans, thereby allowing the pizza pans to be employed as precision GCPs for the thermoMap survey. This approach greatly improved the locational accuracy of the thermoMap imagery.At Site-1, the UAV flights were performed on 6 May 2019, using all three camera payloads. At Sites-2 and -3, the UAV flights were initially performed on 7 May 2018, with two cameras (S.O.D.A. and thermoMAP), and the recent surveys with all three cameras were performed, respectively, on 21 May 2019, and 12 July 2018. At Site-4, two sets of UAV surveys at different times during the day were performed on 21 June 2019, with all three cameras. The flights were carried out at approximately 117 m height above the ground as 122 m was the maximum height allowed by the U.S. Federal Aviation Administration (FAA) regulations. The UAV imagery obtained for this research was processed using Pix4Dmapper Pro software . The orthomosaics were generated by “stitching” all the overlapping images together obtained with a particular camera during a UAV survey. The end product was a set of orthomosaic image maps of the complete site survey area from the VIS-C, MS, and TIR cameras. While the VIS-C imagery was the bird’s-eye view of the survey area, as can be seen by the human eye in true color, the MS and TIR imagery was generated in grayscale with the lighter shaded areas representing either a greater reflection of green, red, red edge, or NIR EM radiation or a greater emission of TIR radiation, respectively. The orthomosaic images were post-processed using ArcMap 10.6 desktop software , where annotations were added and the images were then saved in a manageable format. Further processing was accomplished using the free public access GNU Image Manipulation Program (GIMP) 2.10.12 image editor. This software allowed for adjustment and enhancement of exposure, color levels, saturation, contrast, sharpness, image size, and resolution.The GPR used in this study was a time-domain SmartCart Noggin 250 MHz system . The processing steps involved: (1) application of a signal saturation correction filter  to remove slowly decaying low-frequency noise, (2) application of a background removal filter to remove the background noise, especially ground clutter which is a laterally continuous signal caused by cross-talk between antennas , and (3)Additionally, to further interpret the GPR data, average trace amplitude (ATA) plots were generated at each site using the EKKO Project software. The ATA plot represents the decay of the average signal amplitude with time. It is created by averaging all the GPR traces collected in each line of the lineset after rectification, i.e., by considering the absolute valued signal. As the receiver of the Noggin GPR system starts recording the data a few nanoseconds before the transmitter fires, it is possible to assess the background radio frequency noise floor and quantify the GPR PD with the help of ATA plots. Furthermore, they also provide important information on coherent system noise, flat-lying reflectors, clipped GPR signals, signal attenuation, and the choice of appropriate gain function ,69,70.Towards the western part of the entire field, as evident from the TIR orthomosaic b, the drThe VIS-C and TIR orthomosaics generated from the older surveys  when theAt Site-3 , the morAt Site-4, the VIS-C imagery captured at 10:30 in the morning on extensive bare ground conditions after a large rainfall event (4.2 cm) the previous night did not reveal any indications of the drainage pipe signature a. Howeve−1 at Site-1, 0.070 m ns−1 at Site-2, 0.080 and 0.075 m ns−1, respectively, in the preliminary (12 July 2018) and recent (10 December 2019) surveys at Site-3, and 0.052 m ns−1 at Site-4 using the reflection hyperbola curve fitting procedure in the EKKO Project software. Based on the velocity estimates, the soil at Site-3 during the GPR surveys in both instances was drier than the soil at Sites-1, -2, and -4. The GPR wave velocity was estimated to be 0.057 m nsIn relation to the drainage pipes, the hyperbolas are horizontally compressed when the angle is closer to 90° and become horizontally spread out as the angle deviates from 90° and is closer to 15° . MoreoveNevertheless, it is still possible to differentiate between the drainage pipes filled with air and those partially filled with water as a polarity flip is observed in the single hyperbolic responses caused by them. In Single hyperbolic responses were mostly observed at Sites-1, -2, -3 (preliminary survey), and -4, while the dual hyperbolic responses were observed only at a few locations in the recent surveys at Site-3. Hence, this shows even though Site-3 was drier in both instances when compared to Sites-1, -2, and -4, there were a few locations in the recent surveys at Site-3 where the drain lines were undrained and completely filled with water. In the scenario when the angle is smaller  between the GPR traverse and the drain line orientation , and the GPR traverse happens to occur right above the drainage pipe location, the response of the drainage pipe shows up as a banded linear feature with the top of this feature corresponding to the top of the drainage pipe . Figure To further explore the GPR PD at different sites, At Site-2 b, drainaAt Site-3 c, the prAt Site-4 d, the feA combined interpretation was made to understand the complementary nature of the UAV imagery and GPR for subsurface drainage mapping by overlaying the GPR transects and the potential drainage pipe locations marked on the UAV VIS-C imagery acquired at the four sites . The VISAt Site-2 b, the GPAt Site-3 c, prior At Site-4 d, thoughTherefore, the site survey examples presented here depict both the extreme scenarios, comparing and contrasting the suitability of the two techniques. Overall, the UAV imagery proved to be a feasible and cost-effective technique, and GPR, when used appropriately in combination, proved to be a suitable complementary technique at three among four sites. When successful, GPR was useful as both a mapping and validation technique for drainage pipe detection and provided valuable information on their depth and orientation.At the four study sites visited, we were mainly successful at two sites and were only partially able to locate the drain line patterns at the other two sites using the UAV imagery. Except for one site (Site-3), the drainage pipe signature was also located in the historical Google Earth imagery at the other sites. Therefore, viewing all the historical imagery acquired to date could be a good starting point when planning to visit a new site. Moreover, as stated earlier, previous research recommends a rainfall event equal to or greater than 2.5cm  or 5.0 cGiven bare soil conditions, the drain lines’ signature shows up in the VIS-C and MS imagery because of the variation in spectral reflectance between wet and dry soil, while this relates to the differences in thermal inertia and emissivity in the TIR imagery. Contrarily, given the field is covered with a crop, the drain lines’ signature shows up as early crop establishment in the initial stages and due to differences in crop health or stress at the later stages. In particular, this could be important in soils as in Site-3 as no success was observed in locating the drainage pipes in the historical Google Earth imagery or the UAV imagery captured on bare ground conditions. Hence, concerning the prior rainfall and site surface conditions, the timing can be quite flexible for carrying out the UAV surveys depending on the soil type. However, when permissible, the UAV imagery surveys should be performed within two to five days after a significant (2.5 cm and greater) rainfall event on bare ground conditions (outside the growing season) or preferably with an early crop establishment to derive maximum success concerning drainage mapping purposes. Within the growing season, the timing could be flexible based on convenience and without an overriding consideration of the field wetness from prior rainfall. It is worth a mention that high relative humidity (RH > 60%) can, at times, adversely impact the TIR image quality due to atmospheric absorption and re-emission of the TIR radiation and hamper the generation of their orthomosaics ,74,75.In relation to the use of GPR, performing a few survey transects across a limited spatial extent proved useful for both mapping and validation purposes at three study sites. At the same time, the use of GPR can give valuable information on the depth of the drainage pipes. Hence, we recommend carrying out a few GPR transects in the direction perpendicular to the expected drain line orientation given this information is known in advance either from the historical Google Earth imagery or from the pre-existing drain maps acquired from the farmers/landowners/site managers. In this way, the GPR data can be acquired simultaneously along with the UAV flights. At the field sites where this a priori knowledge is unavailable, it is advisable to first carry out the UAV flights and do a rapid/low-resolution processing of the data using the Pix4Dmapper Pro software in order to check if any hints of the drain lines’ signature and trends show up in the UAV imagery. The GPR transects should then be performed accordingly. Moreover, performing rapid/low-resolution processing is always recommended as it acts as a field check quality control measure to ascertain if the UAV imagery collected is of good quality. This should also ensure a sufficient overlap during the flight plan to guarantee proper stitching later on while generating high-quality orthomosaics using full processing .−1 is preferred, permitting the expected GPR signal PD to be greater than 2 m in the best-case scenario, i.e., by considering that the decrease in the GPR signal strength is only due to ohmic signal attenuation [In case no traces of the drainage pipes are observed in the UAV imagery (stitched together with rapid/low-resolution processing), we advise carrying out a few parallel GPR transects spaced few meters apart or in mutually orthogonal directions to get a sense of whether the field is subsurface drained. Moreover, this would facilitate the generation of ATA plots to determine the GPR PD and comprehend if GPR would work for drainage pipe detection at a given field site ,31. Thisenuation ,79.Otherwise, some handheld soil moisture probes (such as TDR or a frequency-domain reflectometer) used to estimate RDP, e.g., CS655, SoilVUE10 , also facilitate the simultaneous measurement of the temperature and soil EC. Hence, the use of these handheld probes is recommended just before or at least concurrently with the GPR surveys at a few random locations spread over the entire field area for the preliminary EM wave velocity estimation and to discern the soil EC. Additionally, it can be difficult to traverse with GPR on a field covered with crop cover and achieve good antenna to ground coupling. Therefore, a general recommendation about the optimal timing concerning the prior rainfall and site surface conditions could be to conduct the GPR surveys two to three days after a rainfall event on moderately wet soil and bare ground conditions. This is because moist soils with air-filled drainage pipes provide a suitable RDP contrast and pose the best-case scenario for the drainage pipes’ detectability ,55. NeveWhen required to be operated in combination, visiting a site within two to five days after a significant rainfall on bare soil conditions is more likely an optimal timing for performing the drainage mapping surveys. However, it should be noted that soils such as Site-3 do exist where it is optimal to perform the UAV imagery and GPR surveys on surface conditions with the early establishment of crop cover for easier mobility of GPR. To summarize the above recommendations, guidelines are presented as a flow chart diagram in Therefore, rigorous theoretical and practical studies are certainly warranted to fully comprehend the complex subsurface processes that affect the drainage pipes’ detectability. Hence, in efforts moving forward, future research should focus on understanding the dependence of these non-destructive techniques on soil type, crop residue, tillage practice, ground wetness level, and rainfall event prior to the surveys with the aim of developing more robust guidelines on the optimal timing for subsurface drainage mapping. More specifically, concerning the UAV imagery, this will be achieved by visiting a number of sites with different soil types multiple times both within and outside the growing season, as proposed by Allred et al. . In relaUAV imagery proved to be a feasible and cost-effective solution for subsurface drainage mapping as large agricultural areas can be surveyed in a limited time. However, its inability to find the linear patterns  under certain circumstances and lack of distinction with other similar linear features  remain caveats for this technique. While GPR was proven effective in previous studies, the technique can be inefficient and cost-intensive to cover large farm field areas and has limited applicability in high-EC soils. Thereby, given the constraints, when used appropriately, collecting GPR data along a limited spatial extent in combination with UAV imagery not only provided the depth information of the drainage pipes but was also helpful to set apart the linear signatures caused by drain lines from those caused due to field operations. At the study sites, where the UAV imagery was unsuccessful or only partly successful, a few parallel GPR transects along the edge and in the center of the field, randomly fashioned transects, and the use of spiral and serpentine transects assisted in mapping the drain lines’ location, to determine their orientation, and to guesstimate the drainage network pattern. Moreover, this was particularly helpful to know for certain if the field is subsurface drained or not, which by itself is a very important piece of information for hydrological modeling. In this relation, GPR provided complementary information and proved suitable both as a mapping and validation technique. Hence, the use of UAV imagery in combination with GPR across limited transects proved to be a more optimal approach for subsurface drainage mapping.


O-[(2-benzyloxyphenyl-3-fluorophenyl)methyl]-l-serine (ALX1393) and N-[[1-(dimethylamino)cyclopentyl]methyl]-3,5-dimethoxy-4-(phenylmethoxy)benzamide(ORG25543) are two selective GlyT2 inhibitors with nanomolar affinityfor the transporter and analgesic effects in pain animal models, althoughwith deficiencies which preclude further clinical development. Inthis report, we performed a comparative ligand docking of ALX1393and ORG25543 on a validated GlyT2 structural model including all ligandsites constructed by homology with the crystallized dopamine transporterfrom Drosophila melanogaster. Molecular dynamicssimulations and energy analysis of the complex and functional analysisof a series of point mutants permitted to determine the structuraldeterminants of ALX1393 and ORG25543 discrimination by GlyT2. Theligands establish simultaneous contacts with residues present in transmembranedomains 1, 3, 6, and 8 and block the transporter in outward-facingconformation and hence inhibit glycine transport. In addition, differentialinteractions of ALX1393 with the cation bound at Na1 site and ORG25543with TM10 define the differential sites of the inhibitors and explainsome of their individual features. Structural information about theinteractions with GlyT2 may provide useful tools for new drug discovery.Theneuronal glycine transporter GlyT2 modulates inhibitory glycinergicneurotransmission by controlling the extracellular concentration ofsynaptic glycine and the supply of neurotransmitter to the presynapticterminal. Spinal cord glycinergic neurons present in the dorsal horndiminish their activity in pathological pain conditions and behaveas gate keepers of the touch-pain circuitry. The pharmacological blockadeof GlyT2 reduces the progression of the painful signal to rostralareas of the central nervous system by increasing glycine extracellularlevels, so it has analgesic action.  Inhibitory glycinergicinterneurons in the dorsal spinal cord regulate the transmission ofpain signals to the brain by operating through glycine receptors (GlyR)containing the α3 subunit at spinal cord synapses.6 GlyT1 cotransports glycine, 2 Na+ ions, and 1 Cl– ion into glial cells, exerting key control over extracellularglycine concentrations at glycinergic and glutamatergic pathways.GlyT2, exclusively expressed in presynaptic glycinergic neurons, takesup glycine together with 3 Na+ ions and 1 Cl– ion and generates steeper glycine concentration gradients.8 GlyT2 supplies neurotransmitter to the presynaptic terminal forsynaptic vesicle refilling, facilitating synaptic glycine recycling.9 Deletion of the GlyT2 gene in mice10 and loss-of-function mutations in the humanGlyT2 gene, SLC6A5, abolish glycinergic neurotransmission.In humans, this causes a rare sensorimotor disorder called hyperekplexiaor startle disease.12 Trivial touch or sounds triggerexaggerated startle responses and hypertonia in hyperekplexia patients,which can produce apnea episodes in newborns and even sudden infantdeath.14 Therefore,the total absence of GlyT2 function is pathological. In addition,complete inhibition of GlyT2 results in a severe facilitation of painsensation most likely due to a complete breakdown in glycinergic inhibitionin the dorsal horn. However, the local inhibition of GlyT2 can raisethe extracellular glycine levels and enhance glycinergic neurotransmissionin the dorsal spinal cord, which effectively suppresses pain transmission.1 GlyT2 is, thus, a potential target for controllingchronic pain states in humans, and the design of GlyT2 inhibitorsis currently considered a challenging endeavor.15Released glycine is cleared from the synaptic cleft by two plasmamembrane glycine transporters GlyT1 and GlyT2.O-[(2-benzyloxyphenyl-3-fluorophenyl)methyl]-l-serine (ALX1393)and N-[[1-(dimethylamino)cyclopentyl]methyl]-3,5-dimethoxy-4-(phenylmethoxy)benzamide(ORG25543) with nanomolar affinity for the transporter have analgesiceffects in pain animal models.16 ALX1393has an antinociceptive effect on thermal, mechanical, and chemicalstimulations in a rat acute pain model17 and also in several animal models of chronic pain.17 Although minimal side effects have been reported on locomotor activityin these reports,19 one study showed ALX1393 alleviatesthe bladder hypersensitive disorder but elicited significant increasein intercontraction interval and micturition pressure threshold.21 On the other hand, the pharmacokinetics propertiesof ALX1393 are improvable since it has been reported that only 5%of the drug crosses the blood–brain barrier.18 Moreover, ALX1393 is not fully selective for GlyT2, andit inhibits GlyT1 at concentrations above 0.5–1 μM inneuronal cultures and brain preparations.22 Nevertheless,a valuable feature of ALX1393 is its reversibility, an aspect thatmay minimize motor and respiratory side effects due to a low targetresidence time or fast dissociation kinetics.Two selective GlyT2 inhibitors 19 ORG25543 is more selective than ALX1393 forGlyT2 over GlyT1, and it seems to be an irreversible GlyT2 inhibitor.18 ORG25543 generates toxicity in animals due toits physiological irreversibility by affecting glycinergic neurotransmissionin mouse spinal cord slices.23 It initiallyprolongs the glycinergic synaptic transmission, but at longer times,it reduces glycine neurotransmission by completely blocking GlyT2.If ALX1393 and ORG25543 display a competitive behavior, they may allowmodulating GlyT2 inhibition by synaptic glycine concentrations.24 Overall, these inhibitors may have interestingproperties as parental compounds for the development of more specificreversible GlyT2 inhibitors with short residence times at their bindingsites and with the ability to pass the blood–brain barrier,which could be applied in pain therapy. Structural information aboutGlyT2 drug interactions is important for understanding their molecularmechanisms of action and will provide useful tools for new drug discovery.ORG25543 alsoreduces allodynia in different pain models such asnerve ligation injury, streptozotocin-induced diabetic pain model,and complete Freund’s adjuvant-induced inflammatory pain.25 The family encompasses membrane proteins with12 transmembrane domains (TM) arranged in two topologically invertedstructural repeats of 5 TMs each (TM1–5 and TM6–10).The repeats intertwine to form two bundles: a scaffold bundle includingTMs 3, 4, 8, and 9 and a core bundle comprising TMs 1, 2, 6, and 7.The transport mechanism involves the rocking of the core bundle relativeto the more rigid scaffold bundle to make accessible the central bindingpocket alternatively to one side of the membrane or the other .25 During the translocation cycle,the transporters undergo conformational changes that drive the proteinto at least three conformational states: outward-open, occluded, andinward-open. The three of them have been crystallized in the prokaryotichomologue LeuTAa in the presence of substrates or inhibitors.29 Later, the eukaryotic Drosophila melanogaster dopaminetransporter (dDAT)32 and the human serotonintransporter (hSERT)36 have been crystallized in inhibitor-boundforms.GlyTs belong to the SLC6 family of neurotransmitter:sodium symporters(NSS), which includes the GABA and the monoamine transporters.Aa as a template, we predictedthe conservation of the substrate and two sodium binding sites.37 We, additionally, identified a transient sodiumsite in GlyT2 external vestibule, which confers isoform-specific propertiesto the transporter.38 Lately, a new refinedGlyT2 model constructed by homology with the dDATcrystal32 permitted us to experimentallyvalidate the location of the third sodium site in GlyT2 whose positionremained obscure.8 We also verified thatthe region surrounding Na3 site has robust allosteric properties involvedin the sensitivity to different cations. A model based in DAT alsopermitted others the analysis of the molecular determinants for substrateinteractions at the glycine-binding site.39 Following preliminary experimental data of the inhibitor potencyon different GlyT2 mutants, we profited the availability of our experimentallyverified new GlyT2 modeled structure based on dDAT,which includes all the substrate-binding sites ,8 and we carried out the molecular docking of ALX1393 and ORG25543.We performed MD simulations and energy analysis of the docking complexesand systematic functional assays of a series of point mutants thatallowed us to predict some amino acids involved in the binding. Ourapproach revealed structural determinants for the selective inhibitorsALX1393 and ORG25543.Through molecular dynamics (MD) simulations on a validatedGlyT2structure modeled using LeuT50 = 31 ± 2.7 nM and displays about 2 orders of magnitude selectivityfor GlyT2 over GlyT1 (IC50 in the low μM range).This is in agreement with previous reports of an IC50 forGlyT2 in the nM range and with the reported selectivity of the compoundin heterologous and brain-derived experimental systems.19 The chemical structure of ALX1393 is shown in O-[(2-benzyloxyphenyl-3-fluorophenyl)methyl]-l-serine) contains an amino acid core, derivative of l-serine with α-amino, and carboxyl moieties and a three aromaticring groups O-substituted in the hydroxyl side chain. For the easeof description, the three aromatic rings in the structure have beennamed R1 (benzyl ring), R2 (oxyphenyl ring), and R3 (fluorophenylring). According to the presence of the amino acid moieties, ALX1393is predicted to exert a competitive inhibition of GlyT2 function.In order to establish the inhibition type, we measured glycine transportsensitivity to three concentrations of the inhibitor that span atleast an order of magnitude using a wide range of glycine concentrations(0.5–500 μM), and we obtained Eadie–Hofstee plots. The EC50 for ALX1393 at every glycineconcentration differed in no more than 30% of its value at 10 μMglycine. In addition, the inhibition could be eliminated by cell washing,confirming the reversibility of the inhibition cyclopentyl]methyl]-3,5-dimethoxy-4-(phenylmethoxy)benzamide)also contains three rings that were named R4 (benzyl ring), R5 (phenylmethoxyring), and R6 (cyclopentyl ring) . The EC50 for ORG25543 at every glycine concentrationwas slightly different, reaching values that even doubled its valueat 10 μM glycine  2A, and iyl ring) 2B. The E glycine 2C. UnlikORG25543 2D makes 8 We chose placing thedocking box in the transporter pore for the two ligands because wewanted to know whether the binding site was common or different forthe two inhibitors. We used two independent computational dockingmethodologies of reasonable flexibility of ligand and protein to comparethe interactions of the two inhibitors within the same system: AutodockVina and Glide (Schrödinger). ALX1393 and ORG25543 were placedat a coordinate in the GlyT2 model equivalent to the substrate-bindingsite in dDAT and allowed to randomly translate. Amongthe several docking poses obtained from the interaction between theligand and the target protein, the ones exhibiting the best dockingscore, which estimates the strength of the interaction, were chosen.In addition, we compared the ligand–protein interactions ofthe obtained ligand-docked poses with the interactions shown by dDAT crystals bound to the tricyclic antidepressants (TCA)nortryptilin (PDB: 4M48)32 and reboxetine (PDB: 4XNX).33dDAT or hSERT structures.34 The inhibitors were anchoredto the bottom of the transporter channel, by important van der Waalsand electrostatic interactions including multiple hydrogen bonds.The ligands established simultaneous contacts with residues presentin TMs 1, 3, 6, and 8 and, in the case of ALX1393, with the cationbound at Na1 site. Instead, ORG25543 interacts with the TM10 in additionto TMs 1, 3, 6, and 8. Since these residues were located in both thecore  and the scaffold  bundles,42 the binding of any of the two inhibitors may block the rocking ofthe core bundle relative to the scaffold and hence inhibit glycinetransport.Preliminary experimental analysis based on thepotency of the inhibitorson different GlyT2 mutants suggested several candidate residues asmolecular determinants for inhibitor interactions. To validate ourpredictions, we performed the molecular docking of ALX1393 or ORG25543to the GlyT2 model.dDAT Phe-76, whose carbonylgroup of the main chain forms a hydrogen bond with the amine groupof the dDAT-bound antidepressant ligand.31 In SERT, a residue equivalent to Tyr-209 (Tyr-95) is also necessaryfor interactions with bound antidepressants.39 Besides, the ligand amino group interactswith the side chain of Ser-481 through hydrogen. The carboxyl groupof ALX1393 establishes electrostatic interactions with the backboneof residues forming the glycine substrate site and, importantly, with the sodium ion located in Na1 site. In a similarway, TCAs coordinate with the sodium ion in the Na1 site through awater molecule. However, the interactions predicted to have a keyrole in the stabilization of the pose are those affecting the ligandaromatic rings. ALX1393 rings were locked by van der Waals interactionswith aliphatic chains and π–π type stacking witharomatic side chains of the transporter. Main interactions occurredwith the side chains of Ser-481, Thr-580, Tyr-289, Trp-484, Ile-285,Thr-584, and Phe-478. It is worth noting that three of the above residuesinteract with more than one ligand ring: Thr-580 (R1 and R3), Tyr-289(R1 and R2), and Trp-484 (R2 and R3).N-dimethylamino groupby van der Waals contacts. This moiety also interacts with the backboneof Ala-639 and the side chains of two other residues in TM10: Asp-635and Ser-640 through hydrogen bonding and electrostatic interactions.It is worth noting that Asp-635 is involved in the formation of theextracellular gate through a salt bridge with Arg-218. The interactionsinvolving TM10 residues are unique features of ORG25543, not foundin the interaction of ALX1393 with GlyT2 or in additional inhibitorsof other members of the SLC6 family of transporters. The side chainof Ala-639 additionally holds the R6 through van der Waals interactions.Furthermore, the moieties substituting R4 interact with TM1 residues(Gly-212 and the backbone of Leu-213 and Gly-214). ORG25543 ringsare held by the side chains of Tyr-289 (R4 and R5), Trp-484 , Thr-580 (R4), and Tyr-288 (R6). A comparative view of themain GlyT2 residues predicted to be involved in ALX1393 and ORG25543coordination is shown on ORG25543 is bound to the transporterby multiple van der Waalsinteractions and hydrogen bonds 2. The maSupplementary Figure S1A,B). Global RMSD values of the transporter were lower than2 Å, as expected for a stable protein model. In addition, Na1,Na2, Na3, and Cl– ions were very stable along thedynamics with RMSD values lower than 1.5 Å. Regarding the ligands,after the first 2 ns of simulation corresponding to the equilibrationstep, they changed the pose with respect to the docked structure,reaching values of 3.5 Å RMSD and everyone reached its bindingsite. The new pose was stable, and no changes were observed in RMSDvalues along the MD, which means that during the rest of the simulation,the ligands remained at their position. The potential fluctuationsin the ligand binding region were also monitored by the shown root-mean-squarefluctuation (RMSF) values. As expected for a membrane protein surroundedby lipids, the main structural movements corresponded to regions incontact with the solvent such as terminal ends and TM-connecting loops. Supplementary Figure S2A,B shows that, besidesthe terminal ends which are charged regions with greater freedom ofmovement, the main fluctuations were observed in the extracellularloops EL2 , protein regions thatare expected to respond to substrate binding. However, besides EL2,none of the rest of the RMSF values exceeded 3 Å. In addition,there were no remarkable fluctuations affecting the ligand bindingsite. Furthermore, protein–ligand interaction energies measuredduring the simulations remained nearly constant, indicating the posesof the ligands in the protein were energetically favorable . Although we obtainedhigh interaction energy values ,probably due to the fact that the system does not include all theconformational changes that are coordinately required for binding,the values were comparable for the two ligands. In order to know whetherthese interactions underwent time-dependent changes during the MD,we analyzed the evolution of the interaction energy of every key residueduring the simulation. The obtained results are shown in Figure S4A and indicate that the major interactionsof the ligand with the protein were stable over time.Thebest fit docking poses obtained were further refined by 50 ns MD simulationsperformed with AMBER to ascertain whether the complexes were structurallyand energetically stable over time. To assess convergence, the root-mean-squaredeviation (RMSD) values of the inhibitor-GlyT2 complexes were calculatedover the simulation time  or in the stabilization of the transporter structure,and for this reason, some of the mutants were inactive. For example,the different substitutions made in the Tyr-289 and Tyr-209 resultedin inactive transporters. These two residues are preserved throughoutthe NSS family, and Tyr-289 has proven to have an important structuralrole in stabilizing the unwound portion of the TM1 helix, whereasTyr-209 has a key role in S1 site formation through its interactionwith Ser-481.33 Other residues such as Leu-213 or Ser-479 are involved in the formationof the glycine-binding site and Na+-binding site, respectively.So, their substitutions yielded inactive transporters as well.To validate thepredicted interactions between the inhibitors andGlyT2, we used systematic site-directed mutagenesis to construct substitutionmutants of the potential residues involved in ligand binding. Themutants were expressed in COS7 cells, and the inhibitory action ofALX1393 or ORG25543 on the glycine transport by the mutants was assessed.The GlyT2 residues predicted to interact with the inhibitors throughits side chain were replaced by amino acids expected to force theloss of the interaction. In the cases where the interaction occurredthrough the backbone, the inserted amino acid sought to alter thedisposition of the substituted residue to lose the coordination. 3H]-glycine transport by the relevantactive mutants in the presence of fully inhibitory concentrations(1 μM) of ALX1393 or ORG25543. Some of the mutations did notinterfere with the inhibitory potency of the inhibitors. These includedmutations on residues predicted to bind the ligand with the backbone, mutations where the substitution failedto prevent the binding (I285F and F478Y), and mutations on residuespredicted to have a nonsignificant interaction with the ligand (I292C).T580C mutation impaired the inhibitory action of both compounds toa similar extent since this residue has a key role in the S1 glycine-bindingsite.8 Our experimental evidence pointedto some common residues important for the binding of both ALX1393and ORG2554. Those are Thr-580 and Thr-584 to which we probably haveto add some of the residues that yielded inactive transporters uponnonconservative substitution such as Tyr-289, Phe-478, and Ser-479,involved in the binding of substrate(s) or in the stabilization ofthe active center of the transporter.43 Regarding Thr-584 mutations, the insertion of the voluminous Leuor Phe was not tolerated by the two ligands, although Thr-584 doesnot directly bind ORG25543. The natural nonconservative substitutionpresent in GlyT1  showed a reduced inhibitionpotency for both ligands. However, the other nonconservative substitutionS481G showed more reduced inhibition potency for ALX1393 than forORG25543, according to the data in 37 and indirectlyaffects Na1, prevented the inhibition by ALX1393 to a greater extentthan that of ORG25543. Finally, mutations in the two TM10 residuespredicted to interact with their side chain with ORG25543, but notwith ALX1393, selectively impaired ORG25543 inhibition.On the other hand, there are mutationsthat exerted differentialeffects on the inhibitory potency of ALX1393 and ORG25543 , and these effects are in agreementwith the docking predictions. The substitution of Trp-217, which isone helix turn above Leu-213, selectively reduced ORG25543 inhibitionaccording to the stronger binding energy measured as compared to ALX1393.Mutations on Trp-484 probably interfere with the access and accommodationof both ligands when substituted by Phe, but only with ALX1393 whenTrp-484 is substituted by Cys. This agrees with a position for ALX1393located below within the channel as compared to ORG25543. Nonetheless,the most interesting mutations affected residues predicted by thedocking as exclusive for each ligand. In contrast to ORG25543, ALX1393binds to the sodium bound in Na1. For this reason, mutant L576I, whichdisrupts the Na2 site50 value was estimatedfor the different mutants (Supplementary Table S1). As expected, the determined IC50 was in goodagreement with the magnitude of the inhibition at 1 μM shownin 50 values comparable to wild-type. Conversely,the group of mutants with the lowest maximum inhibition at 1 μMcompound showed resistance to inhibition and yielded IC50 values at least 10 times higher than that of GlyT2 wild type.In orderto better quantify the alterations of the inhibitory potencyof ALX1393 and ORG25543 on the relevant mutants, dose–responsecurves were performed at increasing inhibitor concentrations reachinghigh μM values 5. From t38 introduced in TM10 (at positions A639 or S640) were protected fromexternal MTSEA-biotin labeling by the inhibitors, although this approachwas not sensitive enough to reach significance (not shown). Besides,the maximal protection was exerted in the presence of the substrates, a condition thatpromotes the transition of the transporter to the occluded conformationand masks the target cysteine.45 For thisreason, we questioned the maintenance of the outward-open conformationduring inhibitor binding and tried an alternative approach to answerthis inquiry. We generated a double GlyT2 mutant (Y289C/F478C) byintroducing two cysteines replacing the two amino acids that formthe inner external gate. As depicted in +, and Cl–. As expected, in this condition,the label was lost, indicating the substrates permitted the closureof the external gate and thereby the transition to an occluded conformation.It is worth noting that the two cysteines introduced in the doublemutant substituted two amino acids which were predicted to have arole in the binding of the two inhibitors, but more prominent in thatof ORG25543 . This behavior could not be tested for the externalgate residues R218/D635, since ORG25543 interacts with D635 by electrostaticinteractions and its substitution by a cysteine prevents inhibitorbinding and, therefore, protection (not shown).3H]-glycine transport inhibition after 1–4 washes ina medium containing NaCl or choline chloride. As depicted in 44 As reportedpreviously, the MTSEA-biotin labeling of the A223C mutant is protectedby glycine in a buffer containing NaCl but not in a medium containingcholine chloride, indicating the accessibility of the cysteine isreduced when sodium is bound  as compared to regular sodiumconcentrations (150 mM NaCl). For the two inhibitors, lowering theexternal Na+ resulted in a reduction of the inhibitorypotency measured as an increase in the IC50 (50 showed a higher increase in low sodium for ALX1393 (122.0 ±20.9 vs 21.8 ± 4.1 nM) than for ORG25543 (51.2 ± 12.3 vs23.8 ± 7.1 nM), reinforcing the sodium dependence of ALX1393binding.The docking predictedthat, in contrast to ORG25543, ALX1393 bindsto the sodium bound in Na1 site. Several pieces of evidence were obtainedto confirm this prediction 7. First,is bound 7B,C. Intthe IC50 7D,E. How+.25 We found the contacts of ALX1393 withTM1 are mediated by many interactions of slightly lower energy ascompared to ORG25543 and seem to be influenced by the presence ofthe cation. The latter binds directly to a reduced number of TM1 residues,and the binding is not mediated by a Na+ ion. The highestenergy interaction of ORG25543 with TM1 is Leu-213, a position thatcould not be tested since its substitution abolishes the activity.However, the reduction of the inhibition by the TM1 mutant W217F exclusivelyby ORG25543 reflects the higher energy interaction of this compoundwith TM1. We suggest this is probably the cause of the irreversiblebinding of ORG25543 to GlyT2. In fact, a chemical derivative of ORG25543recently generated, compound 118 lackingthe −OCH3 substituent of ring R5, the main groupinteracting with TM1 residues, becomes a reversible inhibitor of GlyT2transport. Interestingly, a photoswitchable derivative of this compoundmade by substituting the benzyl phenyl ether moiety (that substitutesR6 in ORG25543) by an azobenzene in the trans configuration,to which it is structurally homologous, still maintains the reversibilityand the noncompetitive inhibition.44The differential interaction of the two inhibitorswith GlyT2 TM1is remarkable. ALX1393 interacts with the cation bound at Na1, andconsequently it requires the correct structure of the Na1 site thatis importantly contributed by TM1 residues . For this reason, the L576I mutant that disrupts thestructural Na2 site, in allosteric connection with the Na1 site, preventedthe binding of ALX1393 to a much higher extent than that of ORG25543and was partially resistant to ALX1393 inhibition. This suggests thatthe basis of the reversible behavior of ALX1393 is its binding toa region that is only structured in the presence of Na39 This would explain the selectivereduction of ORG25543 potency on the W217F mutant as one of the S2residues is Trp-217. In addition, our docking predictions and experimentaldata indicate that ORG25543, in contrast to ALX1393, interacts withTM10 residues (Asp-635 and Ser-640) and probably with Ala-639 backbone,an aspect that could not be confirmed using mutagenesis. Consideringthat some of these residues are included in the S2 site (Asp-635),it is very likely that the ORG25543 site partially overlaps the allostericS2 site present in GlyT2. Therefore, although the present experimentalapproach may not reveal all the interactions of the inhibitors withGlyT2 and perhaps not the complete nature of the binding sites, undoubtedlyit allowed us to identify differential structural determinants ofGlyT2 for the selective inhibitors ALX1393 and ORG25543. The recentlyreported structure of GlyT1 in an inward open conformation will certainlyassist to get closer to the real GlyT2 structure.46On the other hand, our data suggest the interaction of ORG25543may at least partially involve residues belonging to the S2 allostericsite.Drosophila melanogaster that includes all GlyT2 ligand sites. Through binding energy calculationson the simulated transporter-ligand complexes and functional analysisof a series of point mutants and cysteine labeling assays, we haverevealed some structural determinants of ALX1393 and ORG25543 discriminationby GlyT2. The ligands establish simultaneous contacts with residuespresent in transmembrane domains 1, 3, 6, and 8 and block the transporterin outward-facing conformation and hence inhibit glycine transport.The dissimilar nature of the interactions with TM1 of ORG25543 andALX1393 is probably responsible of the irreversible/reversible behaviorof the inhibitors. The binding of ORG25543 to TM10 residues suggestsa partial overlap of the ligand site with the S2 allosteric site ofGlyT2. The differential requirements for the docking and the structuraldeterminants of the inhibitor binding explain some of their individualfeatures and are crucial pieces of information for the design of newreversible inhibitory compounds with suitable pharmacokinetic andpharmacodynamics properties that might be used in pain treatment.In this study, we performedthe comparative ligand docking of theselective GlyT2 inhibitors ALX1393 and ORG25543 on a validated GlyT2model based on the dopamine transporter from 47 The completecoding region of all of the constructs was sequenced to verify thatonly the desired mutation had been introduced. Plasmids from two independent Escherichia coli colonies were expressed in eukaryotic cellsas indicated below, and [3H]glycine transport and/or immunodetectionwas performed for verification. COS7 cells were grown and transfectedusing Turbofect Transfection Reagent , following the manufacturer’s protocol (2 μLreagent/μg of DNA). Cells were incubated for 48 h at 37 °Cuntil used.Substitutionmutants were generated with the QuikChange II Site-Directed Mutagenesiskit , using rGlyT2 orrGlyT1 subcloned in pCDNA3.2, 5 KCl, 1 MgSO4, 10 glucose)containing 2 μCi/mL [2-3H]glycine , at 10 μM final glycine concentrationif not otherwise stated.48 At the end ofthe desired time , reactions were washed and terminatedby aspiration. Protein concentration (Bradford) and [2-3H]glycine levels  were determined.Glycine accumulation measured in mock-transfected cells was subtractedfrom that of the transporter-transfected cells and normalized by theprotein concentration. Kinetic analyses were performed by varyingglycine concentration in the uptake medium between 0.5 and 500 μM.In inhibition experiments, ALX1393  or ORG25543  was added to the transportsolution at the indicated concentrations, and the vehicle  was added to the control reactions. The determinationsof the IC50 were performed initially by diluting compoundsby log steps with the vehicle from 1 nM to 1 μM. Then, exactIC50 values were determined by means of 8-point concentrationcurves performed over a suitable range using half log dilutions withthe vehicle. A nonlinear curve fitting method was used to obtain IC50 values using Graphpad Prism software, version 6.0, Graphpad,San Diego, CA, USA.COS7 cells werewashed and incubatedat 37 °C in HEPES-buffered saline , reagent-reactive transporter proteins were elutedfrom the beads with Laemmli buffer  for 10 min at 70 °C and then analyzed by Western blotting(SDS/7.5% PAGE) with GlyT2-specific antibody.49 Protein bands were visualized by enhanced chemiluminescence andquantified on a GS-900 Calibrated Imaging Densitometer using ImageLab software  and film exposureswithin the linear range. In MTSEA-biotin labeling after cysteine oxidation,COS7 cells expressing the cysteine mutant were treated for 5 min at22 °C with the preincubation solution containing 100 μMCu(II)3 (CuPh).50 The CuPh stock solution (150 mM) was prepared for eachexperiment by mixing 0.4 mL of 1.25 M 1,10-phenanthroline in water:ethanol(1:1) and 0.6 mL of 250 mM CuSO4. Then, the cells werewashed and subjected to MTSEA-biotin staining as described above.Thiol-specific biotinylation and total surface biotinylation wereperformed using 2-aminoethylmethanethiosulfonate (MTSEA)-biotin  and sulfosuccinimidyl-2-(biotinamido)ethyl-1,3-dithiopropionate(sulfo-NHS-SS)-biotin , respectively, at 4 °Con transfected COS7 cells as described.8 constructed based on the crystallized dopamine transporterfrom Drosophila melanogaster (dDAT)(PDB code 4M48)32 as the homology model template, wasused. Our published GlyT2 homology model was further refined by meansof MD simulations8 .The experimentallyvalidated equilibrated homology model of GlyT2,dDAT homology model atglycine binding site (S1 site): Autodock Vina51 (http://vina.scripps.edu) and Glide.52 Ligands preparation anddocking methodology are described in Supporting Information.ALX1393 and ORG25543 found in theSigma-Aldrich catalogue were obtained as a structure data file (sdf).Two docking softwares were used to ascertain the binding mode of ALX1393and ORG25543 on the GlyT2 54 .Thestability of the complexes(GlyT2-ALX1393 and GlyT2-ORG25543) was evaluated by calculating theRMSD of the Cα atoms along the trajectories, using their startingstructures as reference, the RMSF of each residue, and the effectivebinding free energies between the ligands. The more relevant residuesin the binding site were qualitatively estimated using the MM/GBSANonlinear regressionfits of experimentaltransport data and statistical analysis were performed with GraphPadPrism 6.01 . Bars represent SEM of at least triplicatedeterminations. The representative experiments shown were repeatedat least three times with equivalent results.


With the negative impact of COVID-19, the continuous recession of economic globalization, and the increasing market competition, enterprise transformation gradually becomes the theme of enterprise management. Although more and more scholars and companies have paid attention to the importance of enterprise transformation, most of the research on it is still at the qualitative level of theoretical descriptions and lacks a comprehensive consideration and empirical research on its motivation and performance. In view of this, this study analyzes the overall driving effect of technological innovation and the internal and external environment on enterprise transformation from the perspective of its drivers and analyzes in depth its causes and consequences for different industries . The study also analyzes the antecedents and consequences of enterprise transformation and its differences in different industries . In this study, a sample of middle and senior management of 10 companies with a valid sample of 401 is collected. Structural equation modeling results indicate that competitive advantage, technological innovation, and market pressure significantly affect enterprise transformation, which is an antecedent of corporate performance. Further, the results of the multiple-group analysis also reveal some significant differences between the theoretical models of the construction and real estate communities. Finally, suggestions are made based on the findings. In recent years, scholars have proposed many research themes and frontier hotspots in the field of enterprise transformation research, including transformation motives , global First, enterprise transformation helps to alleviate the pressure of upgrading. The timely choice of transformation by firms helps firms avoid the pressure that the original industry has become difficult to provide sufficient growth space for firms , helps iSecond, enterprise transformation helps to enhance core competitiveness . EnterprThird, enterprises transformation helps increase value-added. Enterprises actively engage in transformation activities can make enterprises restructure production factors, influence the improvement of input-output efficiency, and realize process upgrading; drive enterprises to introduce advanced production lines, influence the improvement of existing products and the launch of new products, and realize product upgrading; enable enterprises to increase the added value of products, influence the trade-off of existing functions and the acquisition of new functions, and realize function upgrading; then promote the transfer of industrial knowledge, which acts on related industries, and then realizes industrial upgrading . TherefoThus, although the importance of enterprise transformation has been recognized by many enterprises and academics, and a series of valuable results have been obtained from related researches, the existing literature on the drivers of enterprise transformation still has several shortcomings in the following aspects. The existing literature focuses on the driving effect of independent variables on enterprise transformation, but there is no research on the driving mechanism of technological innovation under the combined effect of internal and external conditions. Enterprise transformation is influenced by the external environment, especially the competitive market pressure faced by technological innovation, and is also constrained by the competitive advantage in the internal environment. A comprehensive analysis of technological innovation and its internal and external influencing factors is beneficial for a deeper understanding of the driving effect of enterprise transformation. Studies have considered technological innovation as an important antecedent driver of enterprise transformation, ignoring the evaluation of the acquisition of sustainable competitiveness and the improvement of the added value of products and services, that is, the evaluation of the corporate performance of enterprise transformation. In addition, research has neglected the evaluation of the acquisition of sustainable competitiveness and the improvement of added value of products and services, that is, the measurement of corporate performance as a result of enterprise transformation. The existing studies mainly focus on samples from developed countries, and there is a lack of research on the construction of the theoretical system of enterprise transformation in China.Based on the above discussion, this study takes COVID-19 as the research background, constructs a theoretical model of internal and external conditions affecting enterprise transformation, takes local real estate enterprises as the research object, and takes middle and senior managers of enterprises as effective samples, uses structural equation modeling to verify the explanatory power of the mechanism of action of enterprise transformation and upgrading, analyzes how technological innovation has a driving effect on enterprise transformation and upgrading under the overall market pressure and competitive advantage, so as to understand the important influencing factors affecting enterprise transformation and upgrading and their antecedents and consequences. This study provides practical guidance on the role mechanism of enterprise transformation under COVID-19 and theoretical support for improving the mechanism of enterprise transformation by deeply exploring its inherent theoretical logic and influence mechanism.As an important driver of enterprise transformation, technological innovation is conducive to the continuous improvement of product or service quality, which helps enterprises to meet the consumer’s consumption intention and demand well, thus enhancing the market share and enterprise market competitiveness. In addition, technological innovation contributes to the renewal of production processes and procedures, the improvement of production efficiency and the reduction of production costs, and ultimately the improvement of business performance . CorporaIt has been shown that technological innovation can enhance corporate performance . Xu et aBased on this, we propose the following hypothesis.H1: Technological innovation is positively related to corporate performance.Technological innovation has a driving role in enterprise transformation. To meet the continuous challenges of transformation, companies are required to improve their existing products, technologies, and market services through technological innovation in order to optimize their organizational structure, reduce production costs and increase operational efficiency . By relyThe high correlation that exists between technological innovation and transformation has been argued by prior studies. For example, in studying the factors influencing enterprise transformation in manufacturing industries of China, H2: Technological innovation is positively related to enterprise transformation.Technological innovation enables a company to provide more attractive products or services than its competitors, and to gain a sustainable competitive advantage in a highly competitive industry. Compared with competitors, technological innovation enables companies to gain economies of scale and learning curve effects in the market competition, which helps companies to provide products or services that are acceptable to customers at the lowest production cost and keep the cost of products or services at the leading level in the industry. Equally important, technological innovation is used by firms to provide unique products or services to customers in certain segments of the value chain and win their favor. As an important source of low-cost competitive advantage or differentiated competitive advantage, technological innovation has a great impact on the competitive advantage of a company.It has been shown that technological innovation has a significant role in determining the relative cost position or differentiation of products. H3: Technological innovation is positively related to competitive advantage.Enterprise transformation helps enterprises to enhance their competitive advantage and obtain great economic benefits. Through transformation, enterprises can participate in social division of labor in the capital and technology-intensive economy at the higher end of the value chain , enhanceThe existing literature has pointed out the relationship between enterprise transformation and corporate performance. H4: Enterprise transformation is positively related to corporate performance.In the competitive modern market, enterprises integrate internal conditions and external environmental resources and need to balance the interests of stakeholders’ needs in order to seek long-term survival and development.Therefore, enterprises bring a huge market pressure for meeting the stakeholder’s interest needs, which forces them to actively respond to innovation and pay attention to scientific and technological issues in the market competition. By further research, In view of this, the following hypotheses are proposed in this study:H5: Market pressure is positively related to technological innovation.H6: Market pressure is positively related to corporate performance.In addition, the continued intensification of competition will also have technology or products that are difficult to create long-term revenue for the company, which will lead to the further expansion of the market pressure faced by the company. As the pressure continues to increase, firms, in order to gain great revenue and sustained competitive advantage, will then make enterprise transformation or upgrade through technological innovation, thus successfully avoid market pressure . Under tMany scholars have conducted research on this subject, expecting to help companies to survive the crisis and transform successfully. Based on this, we propose the following hypothesis.H7: Market pressure is positively related to enterprise transformation.Resource-based theory suggests that the optimal combination and reallocation of a firm’s valuable, scarce, and inimitable resources is an important source of gaining competitive advantage . The keyCompetitive advantage can continuously create added value for customers, win customer satisfaction and loyalty, and obtain superior corporate performance over competitors. H8: Competitive advantage is positively related to enterprise transformation.H9: Competitive advantage is positively related to corporate performance.In summary, this study proposes a research model as shown in In this study, real estate companies and construction companies are selected as the research samples. The reasons are as follows, First, because the construction industry is currently facing the bottleneck of rising energy efficiency in buildings, and the in-depth promotion of transformation has become an important way for it to break through the bottleneck and achieve green and high-quality development. Second, due to the significant structural changes in the real estate market and the adjustment of relevant national policies, transformation has become a new development direction being explored by the real estate industry. Therefore, it is of more practical value to study the industry and enterprises where transformation is imperative. The questionnaires of this study are targeted at middle and senior managers of enterprises. The data collection of this study is completed through two rounds of questionnaire survey.The first round of research, which started at the end of March and lasted until the end of June 2021, selected five real estate enterprises, and a total of 230 middle and senior managers in the real estate industry participated in the questionnaire survey, and a total of 208 valid questionnaires were obtained. The second round of research, which started from the beginning of July and lasted until the end of August 2021, selected five construction enterprises, and a total of 220 middle and senior managers of the construction industry participated in the questionnaire survey, and a total of 193 valid questionnaires were obtained. A total of 401 valid samples were obtained in the two rounds of research. Among them, 75.56% was male, 89.56% under 45 years old, 2.89% over 60 years old, 13.78% of master’s degree and above, 52.22% of bachelor’s degree, and 34% of specialist and below. Middle-level managers accounted for 66% and senior managers accounted for 34%; in terms of years of work in the positions held, 44.23% was below 5 years, 30.66% above 5 years and within 10 years, and 25.11% above 10 years.First, to ensure the reliability and validity of the measurement scales, the measurement questions in this study are all based on existing established scales, which are organized according to the research objectives through literature analysis. Among them, the scales from SSCI journals are translated and validated according to the recommendations of the back-translation method to ensure the quality of the questionnaire and its applicability in Chinese context. Second, to ensure the expert validity of the measurement questionnaire, five scholars in the field of transformation research and three corporate executives engaged in enterprise transformation are invited to review the questionnaire, which is finally formed through the joint suggestions from the academic and corporate practice communities. Third, the measurement questionnaire of this study consists of 23 items, and the measurement items are all measured using a Likert 7-point scale. The variables are measured as follows.Technological innovation: this study refers to the technological innovation research scale of Corporate performance: this paper draws on the studies of Enterprise transformation: In this paper, drawing on the studies of Market pressure: this article draws on the studies of Competitive advantage: in this study, the scale consists of five questions, as studied by Control variables: in this study, the subjects’ gender, age, education, and years of job tenure are selected as control variables.Common method variance (CMV) is an overestimation of inter-construal correlations due to self-reported scales and is also influenced by the same measurement method, which reduces the variance between different constructs . Thus, Cpost hoc detection can be handled by applying SEM, where different conformational variables are analyzed using a single CFA model, where a good correlation between conformations means that there is CMV and CFA yields a good fitness . The research hypothesis of SEM is sample covariance matrix = model covariance matrix. However, SEM is a large sample analysis method, so the value of p is very easy to be less than 0.05 and often wrongly reject the hypothesis and get the conclusion that the model is not good, so p, but to report a variety of different fit indicators to determine whether the model fit is good.The structural model analysis is performed by the method of great likelihood estimation, and the analysis results include model fit, significance test of the research hypotheses, and interpretable variance , RMSEA, SRMR, TLI (NNFI), CFI, GFI, and AGFI. The results of the Bollen-Stine Bootstrap corrected model fit, and the Bollen-Stine Bootstrap corrected model fit are shown in The fit metrics in this study apply the 194 international academic journal (SSCI) papers explored in the study of b = 0.581, p < 0.001) significantly affects technological innovation (TI), technological innovation  significantly affects competitive advantage (CA). Competitive advantage , technological innovation  and market pressure  significantly affect enterprise transformation (ET), technological innovation , market pressure , competitive advantage  and enterprise transformation  significantly affect corporate performance (CP). Therefore, all hypotheses are established.In this research model  also plays a positive role in enterprise transformation. Meanwhile, the positive driving effect of technological innovation on enterprise transformation is more significant than that of competitive advantage and market pressure. Internal and external antecedents have a significant positive effect on corporate performance.First, Validated the role of internal and external factors in influencing firm transformation. This study shows that technological innovation and its internal and external environment have significant theoretical explanatory power for China’s enterprise transformation. Although theoretical studies on enterprise transformation in developed countries are abundant and have become a hot topic of social concern, research on enterprise transformation in China, especially empirical studies, is extremely limited. In view of the differences in enterprise management in terms of market operating environment, management philosophy, and business practices, it is necessary to examine the drivers of enterprise transformation and its performance in China from a theoretical perspective. Based on the theoretical foundation and literature review, this study examines the effects of market pressure, technological innovation, and competitive advantage on enterprise transformation in the Chinese context. Overall, market pressure, technological innovation, and competitive advantage are important antecedent influences on enterprise transformation and have positive effect on enterprise transformation. Among them, technological innovation is a very important predictor and main path of enterprise transformation. It is also found that technological innovation positively influences the competitive advantage of the firm and is also positively influenced by market pressure, which together affects the transformation. In addition, market pressure , technological innovation  and market pressure  had significant effects on enterprise transformation (ET). The results show that competitive advantage  is a significant external antecedent influence on enterprise transformation and has a significant contribution to enterprise transformation. On the other hand, the path analysis through structural equation modeling shows that there are differences in the driving effects of the antecedent influences of corporate performance. Specifically, the situation is as follows. First, market pressure , and competitive advantage  are important external influences on corporate performance, but market pressure has a greater impact on corporate performance than competitive advantage and is the main external source of corporate performance growth. Second, enterprise transformation , technological innovation  are important internal influences on corporate performance, but enterprise transformation has a greater positive effect on corporate performance than technological innovation and is an important internal source of corporate performance growth. Internal and external antecedents have a significant positive effect on corporate performance. Internal and external important antecedents jointly drive the growth of corporate performance.Second, Validated the mechanism of the impact of enterprise transformation on corporate performance. This study shows that corporate transformation has a significant effect on corporate performance, however, the driving effect of enterprise transformation motivation and its performance overall consideration varies significantly. On the one hand, there are differences in the driving effects of antecedent influences of enterprise transformation. The structural equation modeling analysis revealed that competitive advantage (Third, revealed the significant differences of transformation mechanism between real estate and construction industries in terms of transformation. The multiple-group analysis reveals that the overall mechanism of action based on technological innovation has different effects on real estate and construction industries. Specifically, there are five groups of regression coefficients with significant differences between real estate and construction firms, namely, the driving effect of competitive advantage on transformation, the driving effect of technological innovation on enterprise transformation, the driving effect of technological innovation on corporate performance, market pressure on corporate performance, and competitive advantage on corporate performance; the remaining four groups, namely, the effect of market pressure on technological innovation, the effect of technological innovation on competitive advantage, the effect of market pressure on transformation, and the effect of enterprise transformation on corporate performance. The effect of transformation on corporate performance is not significant. This shows that there are significant differences in the effects of market pressure, technological innovation, and competitive advantage on corporate performance. Among them, the significance of competitive advantage on corporate performance is significantly stronger in the real estate industry than in the construction industry, while the effects of technological innovation and market pressure on corporate performance are stronger in the construction industry than those in the real estate industry. The effects of technological innovation and market pressure on corporate performance in the construction industry are stronger than those in the real estate industry. Meanwhile, there are significant differences in the effects of competitive advantage and technological innovation on enterprise transformation. Among them, the driving effect of technological innovation on enterprise transformation is stronger in construction than that in real estate industry, while the driving effect of competitive advantage on enterprise transformation is stronger in real estate industry than that in construction industry.First, it promotes the overall study of the antecedents and consequences of the mechanism of enterprise transformation. This study analyzes the core factors driving enterprise transformation from the perspective of enterprise transformation drivers, and proposes the overall influence of market pressure, technological innovation and competitive advantage on enterprise transformation, while technological innovation is driven by market pressure and transformed into competitive advantage. In particular, technological innovation is considered as an important antecedent driver of enterprise transformation under the constraints of market pressure and driven by competitive advantage, and the outcome of enterprise transformation, that is, corporate performance, is considered. The findings of this study help to better understand the root causes of enterprise transformation and evaluate the results and provide guidance for companies to further understand and transform their business practices to improve corporate performance and market competitiveness.Second, it promotes the contribution to enterprise transformation theory. This study examines the mechanism of transformation through empirical research from a holistic perspective of enterprise transformation motivation and performance. Whether enterprises can make full use of technological innovation and turn it into opportunities and drivers of enterprise transformation requires the overall driving force of market pressure, technological innovation, and competitive advantage. When making transformation decisions, enterprises should consider the positive impact of technological innovation, market pressure on technological innovation, and the competitive advantage brought by technological innovation. In order to realize the synergistic effect of the overall driving factors and to lay a solid foundation for enterprise transformation to achieve superior performance, we should consider the three aspects as a whole.The issue of China’s local enterprise transformation needs urgent attention. The details are as follows.First, the most important thing is that, with the transformation of China’s economic structure and the increasingly difficult environment for enterprises to survive, more and more enterprises are seeking survival and development through transformation, and the number of enterprises undergoing transformation is bound to increase. Although China’s enterprise transformation space is huge, the causes and consequences of transformation have not received due attention, if not timely enterprise transformation of the important antecedent factors and their driving effect of all-round, multi-level research, it is very likely to ignore the pressure of transformation, and thus produce the negative impact of transformation, which is the failure of enterprises aspiring to obtain excellent performance through transformation practice. In addition, enterprise managers should pay attention to the role of internal and external factors on enterprise transformation. This study finds that technological innovation, actively driven by market pressure, has the greatest effect on enterprise transformation, and is also the greatest factor affecting corporate performance. Since technological innovation is the heavy source driving enterprise transformation, companies should break through the bottlenecks affecting technological innovation, enhance their core competitiveness by developing core technologies, and promote enterprise. More importantly, the enterprise transformation in different industries is the most important factor in the value chain.Second, there are significant differences in the driving effect of enterprise transformation in different industries. We should not simply base on the driving effect of enterprise transformation, but should guide the practice of enterprise transformation for different industries by combining their own industry characteristics and market conditions.For the construction industry, the positive impact of technological innovation on enterprise transformation and corporate performance is more significant, and enterprise transformation should take advantage of it. We should focus on using technological innovation to drive enterprise transformation. In other words, the success of corporate transformation is caused by increasing the investment in technological innovation, thus reducing the pressure of corporate transformation and obtaining greater corporate performance. At the same time, the positive effect of market pressure on corporate performance should be properly utilized, that is, the market pressure faced by the company should be turned into the motivation for corporate transformation, which will lead to the growth of corporate performance instead of the decline of performance.For the real estate industry, the driving effect of competitive advantage on enterprise transformation and corporate performance is more significant than that of the construction industry, and enterprise transformation should take advantage of this. Therefore, enterprises in the real estate industry should pay more attention to the positive influence of competitive advantage while giving full play to the advantages of technological innovation and transforming the disadvantages of market pressure. In the increasingly competitive real estate industry under the market economy, companies with competitive advantage often become the winners. This is because when a company undergoes transformation, the more prominent competitive advantage can help the company reduce the pressure of upgrading and gain the ability to cope with environmental challenges. If a real estate company implements a competitive strategy that is difficult or too costly for its competitors to imitate, it gains a sustainable competitive advantage. For example, Wanda Commercial Real Estate’s business model innovation based on the smile curve theory is representative of a company that gains long-term competitive advantage and earns above-average profits. A real estate company with a competitive advantage can win the market and achieve above-average profits with good growth prospects, while a company without a competitive advantage will be outperformed by its competitors and suffer from mediocre corporate performance.Although this study strictly follows the requirements of the questionnaire and empirical research to conduct multi-group analysis, the research perspective and ideas have certain advantages over existing studies and have practical significance for enterprise transformation activities, there are still some limitations for improvement. First, there are limitations in the sample source of this study. The questionnaire survey of middle and senior managers around “enterprise transformation” is in itself a complex and difficult topic. However, future research can expand the scope of data collection and conduct structural equation modeling with larger samples to enhance the generalizability of the research results.Second, there are limitations in the sample sources of clusters in this study. Although this study is an advanced paradigm of cluster comparison analysis, which has significant superiority over general empirical studies, the cohort of this study is limited to the construction and real estate industries only, and future studies can collect data in a wider range of industries, such as small and medium-sized enterprises, private technology-based enterprises, manufacturing and other representative industries of transformation, and conduct hierarchical linear modeling studies in a larger industry cluster to enhance the generalizability of the study results.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Informed consent was obtained from all subjects involved in the study.HS and TH: conceptualization. HS and ZD: data curation, formal analysis, and investigation. HS, TH, and SK: writing original draft and writing – review and editing. All authors have read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In this review, we provide recent data on the role of mTOR kinase in the brain under physiological conditions and after damage, with a particular focus on cerebral ischemia. We cover the upstream and downstream pathways that regulate the activation state of mTOR complexes. Furthermore, we summarize recent advances in our understanding of mTORC1 and mTORC2 status in ischemia–hypoxia at tissue and cellular levels and analyze the existing evidence related to two types of neural cells, namely glia and neurons. Finally, we discuss the potential use of mTORC1 and mTORC2 as therapeutic targets after stroke. Mammalian/mechanistic target of rapamycin (mTOR) is a 289 kDa serine–threonine kinase and a key element of two mTOR complexes called mTORC1 and mTORC2 (mTORCs) ,4. FurthStreptomyces hygroscopicus. This kinase comprises several functional domains, including C-terminal small FAT domain (FATC), C-terminal kinase domain (KD), FKBP12 rapamycin-binding domain (FRB), transactivation/transformation-associated domain (FAT), and an N-terminal domain containing at least 20 HEAT (Huntingtin elongation factor 3 A subunit of PP2A TOR1) repeats. The latter provide sites for the interaction of regulatory proteins to form mTORC1 and mTORC2. The KD domain of mTOR, with conserved sequences homologous to the catalytic domain of the phosphoinositide 3-kinase (PI3K) family, contains phosphorylation sites that regulate the activity of this kinase . Am. AmGTP) -C/DGDP) . At thisCerebral ischemia is followed by a reduction in blood flow to the brain. This disruption causes the dysregulation of all upstream pathways that regulate mTORC1 see . HoweverThe strategic position of mTORC1, downstream of three important signaling pathways, makes this complex an essential convergence center to check cell energy status. In this section, we describe the signaling pathways downstream of mTORC1, their principal targets, and the main cellular processes that they regulate. In addition, we provide the scarce details available for the downstream pathways of mTORC2 in the CNS.37/46 and Ser65. It has been proposed that hierarchical phosphorylation of 4EBPs may be crucial in the fine regulation of translational processes mediated by mTORC1 . Th. Th99]. The blockage of or reduction in blood flow to a brain region causes a drastic depletion of energy supply , thereby leading to “energy failure” . All ups473  . In addiThe release of distinct inflammatory factors by ischemic neurons and reactive microglia induces astrocytes to switch to a reactive status, which can have a negative or positive effect on ischemic damage depending on the phenotype they acquire. Like microglia see , astrocySome studies show the beneficial effects of mTOR activation on astrocytes after OGD . This upHowever, a beneficial effect of astrocytic mTOR inhibition under ischemic conditions has been demonstrated . The redThere are limited data regarding the role of astrocytic mTORC2 after ischemia. The increase in ROS after acute prenatal hypoxia triggers the inhibition of mTORC2 activity by ubiquitination and degradation of Rictor. This inhibition then leads to the inefficient differentiation of astrocytes, thereby affecting their response to ischemia and worsening damage to the brain . After OMicroglia are the first line of defense against cerebral damage and infection by pathogens. These cells are uniformly distributed throughout the brain  and theyAfter 2 days of pMCAo, the inflammatory stage is established. Ischemia-induced cell death results in the release of damage-associated molecular patterns (DAMPs), thereby activating microglia to acquire a reactive phenotype ,136,155.Two phenotypes of active microglia, namely M1 and M2, have been identified. The M1 phenotype presents a pro-inflammatory profile and can release inflammatory cytokines such as IL-1 and TNFα. As a general concept, this phenotype exacerbates the inflammatory response and ischemic damage . AccordiThe mTORC1 pathway has recently been reported to be involved in microglial activation and their polarization towards the M1/M2 phenotype after ischemia. Furthermore, mTORC1 is a known regulator of immune responses. Some studies addressing mTORC1 inhibition after ischemia reveal promising results, including the reduction in the ischemic area and the amelioration of neurological deficits in animals. The direct inhibition of mTORC1, using pharmacological (sirolimus and everolimus treatment for 6 h after tMCAo induction) and genetic (Raptor-KO mice) approaches, leads to a reduction in pro-inflammatory cytokine expression, in parallel to an increase in the M2 phenotype . Indeed,Oligodendrocytes (OLGs) are responsible for axonal myelination in the CNS. Myelination, which occurs during embryonic development and continues into adulthood, determines the speed of nerve impulse conduction and supports axons . Myelina473 [−/− and -Rictor−/− mutants [Like other cell types, in OLGs, mTORC1 regulates protein and lipid synthesis, both necessary processes for correct myelin synthesis. The inhibition of mTORC1 induces a reduction in the synthesis of myelin proteins by OLGs, thereby impairing myelination . Convers473 ,181. Fur473  and spec473 . This ob mutants .In addition to their participation in myelination, mTORCs have significant involvement in the differentiation and maturation of OLGs. Using in vitro models, it has been demonstrated that an increase in mTORC1 activity induces the differentiation of OLGs from OPCs. Conversely, the inhibition of mTORC1 using rapamycin prevents OLG differentiation ,183. In Cerebral ischemia induces a dual response in the OLG population. During the acute phase, a loss of OLGs occurs in the damaged area, since these cells are highly sensitive to oxidative stress, which occurs in this early stage of injury . Some auThe “oligovascular unit”, which defines a dynamic structural complex composed of OPCs and endothelial cells (ECs), is gaining relevance. Interactions between OPCs and ECs play a pivotal role in angiogenesis in both physiological and pathological conditions . After iIt is known that mTOR plays a pivotal role in coordinating antagonist cellular processes such as viability–apoptosis and anabolism–catabolism. Given the relevance of this kinase, its activation levels must be finely regulated. Furthermore, mTOR acts as a catalytic subunit of two complexes, named mTORC1 and mTORC2, regulated by multiple signaling pathways by the presence of energetic factors. Various lines of evidence highlight that post-translational modifications (mainly phosphorylation) of protein-binding partners of mTOR have a crucial impact on the final activity of these two complexes. In an ischemic situation, the loss of oxygen, glucose, amino acids, and survival factors triggers the dysregulation of all upstream pathways that modulate mTORCs, promoting marked reductions in mTORC2 and mTORC1 activities . Thus, pAlthough animal models reveal the positive effects of rescuing the activity of mTORCs on damaged tissue, the inhibition of mTOR activity by rapamycin is also beneficial . This apIn astrocytes, there is consensus about the positive effect of mTORC2 activation after ischemia. In contrast, there are contradictory data about the precise role of mTORC1 in this cell population . These dThus, after cerebral ischemia, the upregulation or downregulation of mTORC1 activity has beneficial effects, which probably depend on the temporal evolution of injury . In the