Many techniques for atlantoaxial fixation have been developed. However, the biomechanical differences among various atlantoaxial fixation methods remain unclear. This study aimed to evaluate the biomechanical influence of anterior and posterior atlantoaxial fixation techniques on fixed and nonfixed segments.An occiput-C7 cervical finite element model was used to construct 6 surgical models including a Harms plate, a transoral atlantoaxial reduction plate (TARP), an anterior transarticular screw (ATS), a Magerl screw, a posterior screw-plate, and a screw-rod system. Range of motion (ROM), facet joint force (FJF), disc stress, screw stress, and bone-screw interface stress were calculated.The C1/2 ROMs were relatively small in the ATS and Magerl screw models under all loading directions except for extension (0.1°–1.0°). The posterior screw-plate system and screw-rod system generated greater stresses on the screws (77.6–1018.1 MPa) and bone-screw interfaces (58.3–499.0 MPa). The Harms plate and TARP models had relatively small ROMs (3.2°–17.6°), disc stress (1.3–7.6 MPa), and FJF (3.3–106.8 N) at the nonfixed segments. Changes in disc stress and FJF of the cervical segments were not consistent with changes in ROM.ATS and Magerl screws may provide good atlantoaxial stability. The posterior screw-rod system and screw-plate system may have higher risks of screw loosening and breakage. The Harms plate and TARP model may more effectively relieve nonfixed segment degeneration than other techniques. The C0/1 or C2/3 segment may not be more susceptible to degeneration than other nonfixed segments after C1/2 fixation. The atlantoaxial complex is the most mobile segment of the spine, and its range of motion (ROM) in rotation accounts for approximately 50% of the entire cervical spine rotation . AtlantoCurrently, studies have demonstrated that posterior surgery represented by C1 lateral mass-C2 pedicle screw fixation achieves reliable stability and has high fusion rates and excellent clinical outcomes, so it has become the commonly used method for atlantoaxial fixation –8. HowevIn addition, it is well known that nonfixed segment degeneration, especially adjacent segment degeneration, is one of the most common long-term complications of cervical arthrodesis, which can provoke typical neck pain , 16. NumFinite element analysis based on numerical models is widely used in biomechanical research since it allows us to easily investigate joint mobility and stress distribution. To evaluate the biomechanical influence of various atlantoaxial fixation techniques on fixed and nonfixed segments, an occiput (C0)–C7 cervical finite element model was constructed, and six surgical models were developed . The ROM, FJF, and maximum stresses on the screws, bone-screw interfaces, and intervertebral discs were calculated and analysed.In this study, a finite element model of the C0–C7 cervical spine was constructed. Informed consent for the use of individual data was obtained from the participant. First, the cervical computed tomography scans (1.0 mm thickness) of a healthy male  without any cervical spine deformity or related diseases were imported into Mimics 21.0 software . Then, the rough geometric model of the cervical vertebrae was generated by executing a series of software commands, such as threshold segmentation and regional growth. For further correction, surface tuning and optimization with 3-Matic 11.0  was used to build a geometric solid model of the bone, cartilage, and intervertebral discs. Next, HyperMesh 2019  was used to mesh the model and construct the major ligaments. Finally, model assembly, material property definitions, and finite element analysis were performed using Abaqus 6.13 .The intact model consisted of the occiput, 7 cervical vertebrae, 5 intervertebral discs, and ligaments Fig. . The thiThe spinal ligaments included the tectorial membrane, transverse ligament, apical ligament, alar ligament, anterior atlantooccipital membrane, anterior atlantoaxial ligament, posterior atlantooccipital membrane, posterior atlantoaxial ligament, anterior longitudinal ligament, posterior longitudinal ligament, ligamentum flavum, interspinous ligament, and capsular ligament. The tectorial membrane and transverse ligament were modelled using 4-node membrane elements. All other ligaments were represented with nonlinear tension-only spring elements Fig. .Fig. 2LiHyperelastic materials were applied to the cartilage, nucleus pulposus, and annulus ground substance. The annulus fibres were defined as hypoelastic material properties. Frictionless soft contact was applied to simulate all the contact interactions, including the facet joints, atlantooccipital joint, atlantoaxial joint, and odontoid joint. The cortical bone and cancellous bone were simulated as isotropic elastic materials. The occiput was simulated as a rigid body. A convergence analysis was performed to ensure that the maximum changes in the strain energy were < 5%. The element types and material properties referred to previous studies, as shown in Table Six surgical models were developed based on the intact model to simulate anterior and posterior atlantoaxial fixation. Anterior fixation techniques were performed using the Harms plate, TARP, and ATS. Specifically, the anterior arch of C1, the odontoid process, and the ligaments associated with them were removed to allow placement of the TARP and Harms plate. A butterfly shaped TARP with a thickness of 2 mm was fixed with bilateral anterior C1 lateral mass screws and C2 vertebral body screws Fig. A. A HarmThe surgical models were performed as reported previously in the literature –29. The The lower surface of the C7 vertebra was constrained in all directions. To validate the intact model, a pure moment of 1.5 Nm was applied on the superior surface of the C0 to produce flexion, extension, lateral bending, and axial rotation. The C0–C7 ROMs and load‒deflection curves were compared with previously reported data. Then, a 1.5 Nm moment and 73.6 N follower load were applied to the intact model to determine the C0–C7 ROMs. The 73.6 N follower load was used along the physiological curvature of the cervical spine to simulate the head weight and muscle force . DisplacUnder flexion–extension, lateral bending, and axial rotation, the ROM of each segment was compared with the previous finite element study by Zhang et al. in 2006 and in vitro experimental study by Panjabi et al. in 2001 , 31. TheIn general, the C1/2 ROMs of all the surgical models 0.1°–2.5°) were significantly lower than that of the intact model (7.2°–19.4°) under all loading conditions  were higher than those obtained for the intact model (2.4°–12.9°), especially during axial rotation , all the implants increased the maximum disc stresses at nonfixed levels during all motions (1.2–8.9 MPa), especially during axial rotation Fig. . In the FJF was not detected in each segment of the intact or surgical models during flexion except for the C0/1 segment. Compared with the intact model (16.4–55.9 N), the FJF at each level in all surgical models (34.6–127.4 N) increased substantially during axial rotation Fig. . In the The results of the ROM, disc stress, and FJF were normalized with respect to the intact model Fig. . At the Due to the deep anatomical position and frequent variation of the vertebral artery, atlantoaxial fixation is challenging, risky and was once avoided in spinal surgery. Since sublaminar wires were first proposed for atlantoaxial fixation by Gallie et al. in 1939, researchers have continuously improved posterior fixation techniques by using Magerl transarticular screws, C1 lateral mass screws, C2 pedicle screws, and C2 translaminar screws to meet the needs of individual patients. In addition, anterior atlantoaxial fixation with the Harms plate, ATS, and TARP that was developed in the 1980s has improved surgical strategies. Despite this, when planning atlantoaxial fixation, particularly anterior fixation, decisions must be made carefully to avoid problems with internal fixation stability, including screw breakage or loosening, and nonfixed segment degeneration. To this end, six typical anterior and posterior surgical models were constructed in this study to comprehensively evaluate the biomechanical differences between different models.One of the primary objectives of surgery is to achieve rigid fixation of the atlantoaxial articulation, and ROM is the most important index for evaluation of segmental stability. In this study, all surgical models significantly limited the ROMs of the C1/2 segment in all directions when compared with the intact model. Interestingly, there are only slight differences among surgical models. In particular, there was almost no difference between the ATS and Magerl screws, between the Harms plate and TARP, and between the posterior screw-rod system and screw-plate system. This may be because their design concepts based on biomechanical mechanisms were similar. Moreover, studies have shown that the C1/2 segment is responsible for 63%-73% of the rotational movement of the cervical spine, while only 12% contributes to flexion–extension, so limiting atlantoaxial rotation is essential . Here, iWhen evaluating structural stability, not only the ROM of the segment but also the stress concentration effect of the implants should be considered because of extensive cyclic loading imposed on the highly mobile upper cervical region. Under sustained mechanical loading, instrumentation failure due to screw loosening or breakage is likely to occur, which seriously affects the long-term stability of surgical segments. Our study investigated the maximum von Mises stresses of the screws and bone-screw interfaces in each surgical model. The findings revealed that the posterior screw-rod system and the screw-plate system generated greater stresses on screws and bone-screw interfaces during all movements except for extension, suggesting that they may have higher risks of screw loosening and breakage. We speculated that this may be attributed to the load distribution of the cervical spine, with 36% in the anterior column and 64% in the posterior columns . Kim et Until now, the origin of nonfixed segment degeneration has remained controversial. However, overwhelming evidence suggests that it is associated with abnormal alterations in mechanical loading and a compensatory increase in ROM. Consistently, it was noticed that the ROMs and disc stresses of nonfixed segments increased in surgical models under all loading directions compared to the intact model. After atlantoaxial fixation, the FJF of each nonfixed segment mainly increased during rotation. Among the six surgical models, a relatively small ROM, disc stress, and FJF were observed in the models with Harms plate and TARP, indicating that they may delay the progression of degeneration. Harms plates are seldom used in clinical applications because they are prone to screw loosening and other adverse events. Yin et al. developed the TARP system in 2002, which allowed operators to perform decompression, reduction, internal fixation, and fusion through the single transoral approach in a one-stage operation without an additional posterior procedure . To dateThis study has some limitations. First, the screws, ligaments, and loading conditions were simplified, and the impacts from surrounding muscles were ignored in the model. Thus, a gap may exist between the finite element model and a real spine system, and the results need to be further evaluated and verified by more high-quality studies in the future. Second, six classic techniques of atlantoaxial fixation were simulated in this study, and more investigations are required to explore the other techniques. Finally, finite element models were constructed based on the CT data of a healthy male subject. The effect of anatomic structure, osteoporosis, and other factors on biomechanical properties was overlooked.In this study, the ATS and Magerl screws may provide good atlantoaxial stability under all loading directions except for extension. Compared to the other fixation techniques, the posterior screw-rod system and screw-plate system generated greater stresses on screws and bone-screw interfaces, suggesting that they may have higher risks of screw loosening and breakage. The Harms plate and TARP resulted in a relatively small ROM, disc stress, and FJF at the nonfixed segments, which indicated that they may delay the progression of segment degeneration. The C0/1 or C2/3 segment may not be more susceptible to degeneration than other nonfixed segments after C1/2 fixation.


Guided by computational modeling using ligand docking and molecular dynamics simulations, we selected two residues involved in UCPH-101/EAAT1 interaction, which were mutated in ASCT2  in the corresponding positions. We show that in the F136Y/I237M double-mutant transporter, 100% of the inhibitory effect of UCPH-101 could be restored, and the apparent affinity was increased (Ki = 4.3 μM), much closer to the EAAT1 value of 0.6 μM. Finally, we identify a novel non-competitive ASCT2 inhibitor, through virtual screening and experimental testing against the allosteric site, further supporting its localization. Together, these data indicate that the mechanism of allosteric modulation is conserved between EAAT1 and ASCT2. Due to the difference in binding site residues between ASCT2 and EAAT1, these results raise the possibility that more potent, and potentially selective ASCT2 allosteric inhibitors can be designed .Excitatory amino acid transporter 1 (EAAT1) is a glutamate transporter belonging to the SLC1 family of solute carriers. It plays a key role in the regulation of the extracellular glutamate concentration in the mammalian brain. The structure of EAAT1 was determined in complex with UCPH-101, apotent, non-competitive inhibitor of EAAT1. Alanine serine cysteine transporter 2 (ASCT2) is a neutral amino acid transporter, which regulates pools of amino acids such as glutamine between intracellular and extracellular compartments . ASCT2 also belongs to the SLC1 family and shares 58% sequence similarity with EAAT1. However, allosteric modulation of ASCT2 via non-competitive inhibitors is unknown. Here, we explore the UCPH-101 inhibitory mechanisms of EAAT1 and ASCT2 by using rapid kinetic experiments. Our results show that UCPH-101 slows substrate translocation rather than substrate or Na EAATs are responsible for the transport of glutamate across neuronal and astrocytic membranes in the CNS. Glutamate transporters are secondary active transporters, which utilize energy from the sodium concentration gradient between the extra- and intracellular sides of the membrane to take up glutamate into cells against a large concentration gradient . In addinsported . This glnsported .The SLC1 family contains five glutamate transporters (EAATs1–5), as well as two neutral amino acid transporters, the alanine serine cysteine transporters alanine serine cysteine transporter 1 and 2 (ASCT1 and -2) . ASCT2 hthreo-beta-benzyloxyaspartate)   and TFB-partate) . In addipartate) . Charactpartate) . Subsequpartate) . UCPH-10partate) .vmax increase in EAAT2, without altering the substrate affinity. The report also suggested that the allosteric binding site is located between the transport and the trimerization domains . However, when F136 and I273 are remodeled to tyrosine and methionine respectively, UCPH-101 can be successfully docked into ASCT2 with a pose similar to that seen in the EAAT1 structures (see below). This result added further support to our hypothesis that Y127 and M271 are key residues impacting binding of UCPH-101 in EAAT1 and explains why inhibition is only partial in wild-type ASCT2 (see below). Next, our goal was to experimentally test predictions from docking with respect to interaction of UCPH-101 with the SLC1 family member ASCT2, contrasting them with results from EAAT1. To validate our experimental system and to compare inhibitor effects on pre-steady-state currents, which had not been investigated in the past, we first briefly summarize UCPH-101 effects on EAAT1.Ki was essentially independent of the glutamate concentration  and Ki(S) are the Ki values (inhibition constants) in absence and presence of glutamate. Km(substrate) is the apparent Michaelis-Menten constant for glutamate, and [S] is the substrate concentration. Furthermore, we determined the voltage dependence of the UCPH-101 inhibitory effect. As expected, anion currents were fully inhibited at all membrane potentials . The reduction of the decay rate of the transient current indicates a slowing of the translocation reaction in the presence of UCPH-101. In contrast to competitive inhibitors, UCPH-101 application in the absence of glutamate did not induce any currents, as expected for non-competitive inhibitors, which are not known to be able to block the glutamate transporter leak anion conductance  form of the transporter. This question was raised from the crystal structures of EAAT1 in the presence of UCPH-101 , in the absence of glutamate. Non-specific currents were subtracted by applying 200 μM TBOA. In the presence of UCPH-101, the charge movement was still present (+ affinity) was not significantly changed (+ binding (most likely to the Na1 and Na3 sites) is not inhibited by bound UCPH-101 and occurs with similar affinity as in the absence of the inhibitor.Finally, we tested whether UCPH-101 binding affects how NaUCPH-101 . The strposition . However and Na3 . As repotrogenic , generatcurrents , which d present , and the changed . These rIn the next paragraphs, we describe electrophysiological measurements on ASCT2 in the presence of UCPH-101, to test whether the inhibition mechanism is conserved between the EAAT1 and ASCT2 members of the SLC1 family. To corroborate the residues directly contributing to the UCPH-101-bound state in EAAT1 suggested by docking, we used molecular dynamics (MD) simulations, to investigate the stability of UCPH-101 in its EAAT1 binding pocket . From the EAAT1 structure bound to the substrate aspartate and UCPH-101 in the allosteric site (5LLM), we generated a model of EAAT1 inserted into a lipid bilayer in a water box. After equilibration, UCPH-101 remained stable in the original binding pocket in six 100 ns simulations   . Typicalductance . As expeCPH-101] . In addiCPH-101]  demonstr77±20 μM . Althoug77±20 μM . Further[serine] . From thcis-BPE was used to determine the specific component of L-serine uptake  uptake. The competitive inhibitor L-e uptake . We obsee uptake ; howeverWT, anion current could not be observed after application of glutamine (Km of 280±40 μM (ASCT2WT) to 790±130 μM , that residues F136 and I237 contribute to UCPH-101 binding, four mutant ASCT2s were generated based on EAAT1, F135Y, F136Y, I237M, and the F136Y/I237M double mutant , the current was activated immediately , which is a sum of the rate constants for forward (kf) and reverse (kr) translocation. [S]o and [S]i are the external and internal substrate concentrations, respectively, [I] is the UCPH-101 concentration and Km and Ki have their regular meaning. When amino acid substrate is rapidly removed, [S]o becomes 0 and it is possible to isolate the reverse translocation rate constant.Here, +] and [amino acid] on the intracellular side of the membrane). Because ASCT2 amino acid exchange is electroneutral at equilibrium , no steady-state current was observed under these conditions , which decay within 20 ms back to baseline  in the anditions . Howevernditions , due to m < 1 mM ). Therefin ASCT2 . Consistin ASCT2 , with a in ASCT2 .+ binding to the amino acid-bound transporter, and/or substrate translocation across the membrane, in other words, the steps needed for amino acid transport by ASCT2.When the same paired-pulse serine solution exchange protocol was applied to ASCT2 in the presence of UCPH-101, similar transient currents were observed , but the amplitude of the transient currents was significantly reduced . HoweverF136Y/I237M  to identify potential binders . We analyzed the top scoring compounds for closer inspection and selected compounds that made predicted hydrogen bonding interactions to side chains of the allosteric binding site. From the best compounds found in the virtual screening, 11 were tested experimentally. We tested the inhibitory effect at 100 µΜ of serine. One of these compounds #302,  inhibite current . In cont6Y/I237M  as 90±306Y/I237M . Finally6Y/I237M  Notably,+ binding. Second, the general location of the allosteric binding site of UCPH-101 is conserved between the SLC1 family members EAAT1 (glutamate transporter) and ASCT2 , and possibly ASCT1, while the transporter side chains contributing to the binding pocket are not fully conserved. Third, occupancy of the allosteric binding site does not necessarily result in full inhibition of substrate transport, it can also lead to a partially active state, as seen for ASCT2WT’s interaction with UCPH-101. Our results are therefore in agreement with previous mutagenesis studies . Therefore, it is likely that the UCPH-101-free and -bound states interconvert slowly on the time scale of transport. Thus, UCPH-101 reduces the amplitude of glutamate-induced anion and transport current, without a significant effect on the observed kinetics associated with these reactions.The effect of UCPH-101 on the glutamate-induced anion current of EAAT1 fits with this interpretation. It was shown previously that UCPH-101 exhibits very slow binding and dissociation kinetics , much slower than the partial reactions of the glutamate-induced transport process and the turnover rate , no inhibition was observed, unless EAAT1/EAAT2 chimeras were generated that contained the EAAT1 N-terminal six transmembrane domains . In contWT, however, for the double-mutant transporter a mixed inhibition mechanism was observed, pointing to higher affinity of the apo-transporter for UCPH-101, compared to the substrate-bound form. The reason for this is not known, but somehow the UCPH-101 binding site in this mutant transporter must communicate with the substrate binding site. A proposed kinetic mechanism for inhibition of EAAT1/ASCT2 by UCPH-101 is shown in +-bound states. The reaction that is affected by occupation of the allosteric site is the translocation reaction, or reactions closely associated with it, such as Na+ binding to the substrate-bound transporter. In EAAT1, due to the high affinity of the compound, equilibration of the UCPH-101-bound and -unbound states is slow, thus, UCPH-101 inhibits the transient and steady-state currents, with little effect on apparent transport kinetics. In essence, UCPH-101 acts by removing active EAAT1 transporters from the pool, thus inhibiting the overall transport rate. On the other hand, equilibration of the UCPH-101-bound and -unbound states is fast in ASCT2, therefore, kinetics of substrate-induced current activation and recovery are slowed in the presence of inhibitor. Thus, the kinetic mechanism shown in As expected, UCPH-101 shows the hallmarks of a non-competitive inhibitor for ASCT2One limitation with current compounds targeting ASCT2 for cancer therapy is that they are amino acid-like compounds targeting the substrate binding site, and thus have poor pharmacokinetics. Interestingly, we were able to identify a compound with a structure unrelated to UCPH-101, compound #302, which inhibited wild-type ASCT2 in a non-competitive manner, although at relatively high concentrations and, like UCPH-101, showing only partial inhibition of the transient transport current elicited by substrate application. This compound was found from virtual screening against the putative allosteric binding site. Interestingly compound #302 also inhibited ASCT1, in which the critical residues in the allosteric binding site are similar to ASCT2. Like UCPH-101, compound #302 is relatively hydrophobic and harbors an amino function. However, it also has a OH group, suggesting that additional hydrophilic interaction may be important in the allosteric binding site. These results further support the presence of the allosteric binding site in ASCT2 and suggest that it may be possible to identify allosteric inhibitors of ASCT2 with novel scaffolds, opening new avenues for future structure-activity relationship studies, to improve affinity and specificity.ASCT2 has recently received attention due to its involvement in neutral amino acid homeostasis in cells, in particular cancer cells. It was shown that down-regulation of ASCT2 function either by siRNA or by competitive inhibitors, can block the growth of cancer cells in cell-line models, as well as in vivo tumor transplants . Competi+ binding can still take place, although the electrogenicity of Na+ binding is reduced, pointing to a slight conformational change of the substrate-free transporter state induced by UCPH-101. While UCPH-101 is a partial and weak inhibitor of wild-type ASCT2, complete inhibition could be restored by mutating the UCPH-101 binding site to one that resembles EAAT1. Therefore, our results suggest that ASCT2 also harbors the allosteric binding site, however, with differences in the amino acid side chains contributing to the site. These results raise the possibility that this allosteric binding site can be exploited by future compounds specifically targeting ASCT2. Our results involving the novel inhibitor compound #302 further confirm the location of the allosteric binding site in ASCT and suggest that compounds with varying chemical scaffolds could be found that modulate or completely inhibit SLC1 activity. In light of the emerging role of ASCT2 as an anti-cancer drug target, the future characterization of this allosteric site appears promising.The results presented in this report reveal a conserved allosteric inhibition mechanism for SLC1 members for the first time. The results suggest that the major effect of the compound, once bound to the binding site at the interface between the transport and trimerization domain, is to block reactions associated with substrate translocation and anion conductance activation. In contrast, other partial reactions, such as substrate and NaHEK293 cells  were cultured as described previously . The cel2, 2 mM CaMes2, 10 mM 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES), with additional amino acid substrate (Glu or Ser) pH 7.3 (extracellular), and 130 mM NaSCN , 2 mM MgGluconate2, 5 mM ethylene glycol-bis(2-aminoethylether)-N,N,N',N'-tetraacetic acid (EGTA), 10 mM HEPES, pH 7.3 (intracellular), as published previously  under voltage-clamp conditions. The resistance of the recording electrode was 3–6 MΩ. Series resistance was not compensated because of the small whole-cell currents carried out by EAAT1, ASCTs. The composition of the solutions for measuring amino acid exchange currents in the anion conducting mode was: 140 mM NaMes (Mes = methanesulfonate), 2 mM MgGluconateeviously . For theVoltage jumps (–100 to +60 mV) were applied to perturb the translocation equilibrium and to determine the voltage dependence of the anion conductance . To deteFast solution exchanges were performed using the SF-77B  piezo-based solution exchanger, allowing a time resolution in the 10 ms range. Amino acid substrate was applied through a theta capillary glass tubing , with the tip of the theta tubing pulled to a diameter of 350 μm and positioned at 0.5 mm to the cell . For pai5 cells/well) in Dulbecco’s modified Eagle’s medium containing 10% fetal bovine serum, penicillin/streptomycin (100 units/ml), 4.5 g/l glucose, sodium pyruvate, and glutamine (4 mM). Forty-eight hr post transfection with hASCT2 (see above), the cells were washed with uptake buffer  two times and pre-incubated in the same buffer for 10 min. Subsequently, buffer was replaced with fresh buffer containing unlabeled L-serine and 0.1 μCi of [14C] L-serine . After 5 min of incubation at room temperature, uptake was terminated by washing twice with 0.1 ml of uptake buffer on ice . The cells were then solubilized in 0.2 ml of 1% SDS, and radioactivity was measured by scintillation counting in 3 ml of scintillation fluid. Unspecific L-serine uptake was determined using the ASCT2 competitive inhibitor L-cis-BPE  and I237(CD) for ASCT2WT and (N1) and (O2) for UCPH-101. In ASCT2F136Y/I237M distance calculation, we selected atoms Y136(OH) and M237(SD) from the transporter, and (N1) and (O2) from UCPH-101 as reference. We also selected S601(CA) and S353(CA) for ASCT2WT and ASCT2F136Y/I237M to evaluate the distance changes of substrate. The UCPH1-101 force field parameters were generated by SWISSPARAM. The parameter file is attached to the original data submitted with this manuscript.The model system for MD simulations was generated with VMD software  using anKi) were obtained by fitting the dose-response curve of the current (I) with the following equation:The data analysis was performed in Microsoft Excel and Microcal Origin software. Apparent inhibition constants  + I2·exp(−t/τdecay). Here, I is the current amplitude, τ the time constant, and t the time.Transient signals of piezo-based solution-exchange results were analyzed in Clampfit software (Axon Instruments) by fitting with a sum of two exponential components. All docking calculations were conducted with the Schrödinger package . ASCT2 (We remodeled the side chains of two residues in ASCT2 (i.e. F136Y and I273M) on a fixed backbone to mimic the UCPH-101 binding site in EAAT1, using SCWRL4 . Grid prThe ZINC20 Lead-Like library  was virtually screened against the WT ASCT2 allosteric site using Glide, as described above. The 1000 top-scoring compounds from the docking screen were further analyzed. In particular, because errors in docking can occur in large virtual screens, we inspected the docking poses of the top-ranking compounds to remove molecules with problematic pose or strained conformations, and prioritized them for experimental testing . We focu The goal of this study is to identify allosteric modulators of an SLC-1 amino acid transporter, ASCT2, which has been implicated in cancer progression. By combining computational and docking methods with functional measurements, this study provides convincing evidence for a conserved allosteric SLC-1 inhibition mechanism. The findings are important to the fields of transporter mechanism and SLC-1 pharmacology. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, including Randy B Stockbridge as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Richard Aldrich as the Senior Editor.Thank you for submitting your article "Conserved allosteric inhibition mechanism in SLC1 transporters" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:The following revisions are essential to support the central claims of the manuscript regarding the conservation of an allosteric inhibition site in SLC1 transporters:1. The MD simulations should include detailed convergence analyses to support the conclusions. According the X-ray crystal structure, the UCPH-101 binding pocket is only accessible via the lipid membrane. It seems unlikely that the 100-ns timescales of the simulations is sufficiently long to permit conclusions to be drawn. The minimum length of the MD replicas should be chosen such that complete dissociation of UCPH-101 is observed in all the ASCT2 replicas. The authors should also comment on how independence of the simulation replicas is ensured.2. A major conclusion of the paper is that ASCT2 and EAAT1 share a conserved allosteric inhibition mechanism. However, the reviewers are not convinced that an allosteric inhibition mechanism has been established for ASCT2. The data for UPC101 suggests a mixed inhibition mechanism . The authors should comment on why the mechanism of UPC101 inhibition differs for the two SLC1 subtypes. Likewise, the evidence that #302 acts as an allosteric inhibitor  is quite sparse, since inhibition was only tested at two substrate concentrations, and different inhibitor concentrations were used at these two substrate concentrations. An experiment with constant #302 concentration and varying substrate concentration should be performed to establish the allosteric inhibition mechanism.3. The only evidence that #302 binds to the same binding pocket as UPC101 is from docking studies. The authors should provide data that #302 binds in the same pocket in ASCT-2 as UCPH-101, for example by testing the same point mutations that were used for the UCPH-101 experiments.eLife's broad readership. In addition, the studies of UPC101 inhibition of EAAT1 largely confirm previous studies that established the allosteric inhibition mechanism . In the text, the authors should clearly explain how their studies of UPC101/EAAT1 inhibition are significant advances beyond what is already known about the inhibition mechanism, or consider shifting the emphasis of the paper towards the more novel studies involving ASCT2 mutagenesis and inhibition.4. The manuscript is written in a very technical manner. The reviewers recommend that the authors revise the manuscript for readability, taking into consideration Reviewer #2 (Recommendations for the authors):eLife community.The manuscript is written in a very technical way and should be edited to improve readership by a broader Throughout, 'trimerization' and 'scaffold' domain are used interchangeably. One term to describe this domain should be selected and used throughout the manuscript.Line 24: the EAAT1 structure was solved by X-ray crystallography, not cryo-EM.+ and co-transport of H+ that also occur with glutamate transport are not mentioned.Line 53: the counter-transport of KLine 63-64: the description of the TMD making up the transport domain and the scaffold domain is incorrect.+ ion binding sites.Figure 1. in panel B, TFB-TBOA and UCPH-101 should be indicated clearly with labels and different colors. Line 233 states that UCHP-101 binding pocket is over 15A away from the substrate and cation bindings sites, but these are not indicated in the figure and it is not correct that the compound is 15A away from the substrate and all three of the NaWhat is the compound bound in Figure 2A? it would be useful to indicate the membrane in all structure figures as well as 'outside' and 'inside' the cell to orient the reader.Figure 3, panel B – it is difficult to see the data in this panel, a logarithmic scale would be better.Line 358: the word significantly is used but I can see no statistical analysis and the effect does not seem overly large.The section (lines 362-379) is confusing, and I am not sure what these experiments are trying to show, the data in Figure S4 does not look different at all with error bars overlapping.Table 1 shows the Km for various substrates for the ASCT2 mutants. There is no discussion or explanation offered as to why residues distant from the substrate binding site are impacting affinity and selectivity.Figure 7D. Lines 460-465 state that the Ki for the single mutant does change as a function of serine concentration, and a mixed mode of inhibition is suggested. Why would the mode of inhibition change if UCPH-101 is binding in the same site? In addition, from the data in Figure 7D it appears to this reviewer that the Ki for UCPH-101 is also changing for the double mutant. This needs to be clarified.Did the authors test if UCPH-101 inhibits the more closely related ASCT1? What is the conservation like in the UCPH-101 binding site?Reviewer #3 (Recommendations for the authors):(1) I strongly recommend to include experimental evidence that (i) compound #302 also mediates allosteric inhibition  and (ii) that it binds to the same binding pocket in ASCT-2 as UCPH-101 (perhaps using the same point mutations that you have used for the UCPH-101 experiments).(2) The MD simulations should include detailed convergence analyses to support their conclusions. Since the UCPH-101 binding pocket is presumably  only accessible via the lipid membrane, I doubt that the 100-ns timescales of your simulations are sufficiently long to permit reasonable conclusions. In any case, I would recommend that the minimum length of your MD replicas should be chosen such that you observe complete dissociation of UCPH-101 in all the ASCT2 replicas.Furthermore, Figure 5 suggests you conducted four simulation replicas for each condition, whereas the main text says you have six replicas (line 388), what is correct?Finally, how did you ensure independence of your simulation replicas?(3) The conclusions of your MD simulations will also crucially depend on the chemical accuracy of your UCPH-101 model. Unfortunately, I could not find how you parameterized this compound consistent with the CHARMM force field. Please provide this information. Reviewer #2 (Recommendations for the authors):The manuscript is written in a very technical way and should be edited to improve readership by a broader eLife community.eLife , we have completely revised the section of the manuscript on the mechanism of UCPH-101 interaction with EAAT1, removing the overly-technical detail, in particular the caged glutamate experiments , which do not contribute strongly to the general conclusions. We also revised the Discussion section accordingly. For the ASCT2 Results section, however, we believe that a thorough description of the anion-current vs transport-current recording experiments, as well as the paired-pulse analysis, are crucial for the non-expert reader to be able to follow the interpretation of the data. Therefore, we made less substantial changes to this section.We agree. To fit with the broader readership of Throughout, 'trimerization' and 'scaffold' domain are used interchangeably. One term to describe this domain should be selected and used throughout the manuscript.We have replaced "scaffold" with "trimerization" in the revised manuscript.Line 24: the EAAT1 structure was solved by X-ray crystallography, not cryo-EM.Thanks for this correction, this is now fixed.+ and co-transport of H+ that also occur with glutamate transport are not mentioned.Line 53: the counter-transport of KThese are now mentioned and the relevant references are cited.Line 63-64: the description of the TMD making up the transport domain and the scaffold domain is incorrect.Thanks for spotting this, this is now fixed.+ ion binding sites.Figure 1. in panel B, TFB-TBOA and UCPH-101 should be indicated clearly with labels and different colors. Line 233 states that UCHP-101 binding pocket is over 15A away from the substrate and cation bindings sites, but these are not indicated in the figure and it is not correct that the compound is 15A away from the substrate and all three of the NaWhat is the compound bound in Figure 2A? it would be useful to indicate the membrane in all structure figures as well as 'outside' and 'inside' the cell to orient the reader.+ from the sentence and labeled the figures as suggested by the reviewer.We thank the reviewer for this comment. We removed the NaFigure 3, panel B – it is difficult to see the data in this panel, a logarithmic scale would be better.We agree, a logarithmic scale would be preferable. We have revised Figure 3B accordingly.Line 358: the word significantly is used but I can see no statistical analysis and the effect does not seem overly large.This figure, and its description in the text, have been removed.The section (lines 362-379) is confusing, and I am not sure what these experiments are trying to show, the data in Figure S4 does not look different at all with error bars overlapping.+ binding to the apo-form of the transporter. We have revised this paragraph to make this point more clear.Yes, the data in former Figure S4  are not significantly different, showing that bound UCPH-101 does not interfere with NaTable 1 shows the Km for various substrates for the ASCT2 mutants. There is no discussion or explanation offered as to why residues distant from the substrate binding site are impacting affinity and selectivity.We performed these measurements as controls, to check whether the mutant transporters preserved WT-like activity. For serine as the substrate, this is clearly the case. However, for alanine and glutamine, some deviations from this expectation were noted. The reason for this is not clear, because these residues are far from the substrate binding site, as the reviewer points out. We can speculate that there are some indirect effects of these mutations on ASCT2 function that are not related to their contribution to the proposed allosteric site. We added a sentence explaining this in the revised manuscript.Figure 7D. Lines 460-465 state that the Ki for the single mutant does change as a function of serine concentration, and a mixed mode of inhibition is suggested. Why would the mode of inhibition change if UCPH-101 is binding in the same site? In addition, from the data in Figure 7D it appears to this reviewer that the Ki for UCPH-101 is also changing for the double mutant. This needs to be clarified.i for UCPH-101 is consistent with an inhibition mechanism, in which the compound binds somewhat more strongly to the mutant transporters in the absence of serine than in the presence, in other words a mixed mechanism. We have now revised this sentence, see also response to Reviewer #1, who also raised this point.Yes, this is correct, the [serine] dependence of the KDid the authors test if UCPH-101 inhibits the more closely related ASCT1? What is the conservation like in the UCPH-101 binding site?This is a great point. Yes, UCPH101 also inhibits ASCT1 function. However, we feel that detailed analysis of the effect on ASCT1 is beyond the scope of this manuscript. Instead, we also tested our new compound, #302, with ASCT1 and it does, in fact, inhibit ASCT1 substrate-induced currents . This is expected, since the predicted allosteric binding site is largely conserved between ASCTs 1 and 2 .Reviewer #3 (Recommendations for the authors):(1) I strongly recommend to include experimental evidence that (i) compound #302 also mediates allosteric inhibition  and (ii) that it binds to the same binding pocket in ASCT-2 as UCPH-101 (perhaps using the same point mutations that you have used for the UCPH-101 experiments).We agree. These experiments are now included in the revised version of the manuscript .(2) The MD simulations should include detailed convergence analyses to support their conclusions. Since the UCPH-101 binding pocket is presumably  only accessible via the lipid membrane, I doubt that the 100-ns timescales of your simulations are sufficiently long to permit reasonable conclusions. In any case, I would recommend that the minimum length of your MD replicas should be chosen such that you observe complete dissociation of UCPH-101 in all the ASCT2 replicas.WT , and none for the double mutant transporter. In our view, this points to the occluded nature of UCPH-101 in the binding site of the transporter, resulting in slow dissociation kinetics, consistent with experimental results. Unfortunately, due to time restrictions, we were not able to run these simulations at an even longer time scale.We have extended the length of the MD simulations for ASCT2 wild-type and double mutant transporter to at least 300 ns . Even with a 5-fold extended time scale, we observed only two UCPH dissociation events for ASCT2Furthermore, Figure 5 suggests you conducted four simulation replicas for each condition, whereas the main text says you have six replicas (line 388), what is correct?Finally, how did you ensure independence of your simulation replicas?We performed six replicas, but only four are shown in Figure 5. This is now explained in the main text.(3) The conclusions of your MD simulations will also crucially depend on the chemical accuracy of your UCPH-101 model. Unfortunately, I could not find how you parameterized this compound consistent with the CHARMM force field. Please provide this information.We apologize for the omission of this critical point. The information on the parametrization of UCPH101 is now provided in the original data (deposited parameter and topology files). We did not use physical chemistry experimentation to validate UCPH-101 MD parameters. Since the MS results are supportive in nature, and not critical to the overall conclusions, we feel that experimental validation is beyond the scope for this manuscript.


For developing high performance, low-energy ice protection systems, it is vital to understand the icing physics at the interface of the ice and substrate. Macroscopic experiments have known limitations when it comes to explaining the adhesion characteristics of ice. There is a need to look at the microscale behaviour of ice and how it interacts with the surface it adheres on. The article describes application of molecular dynamics to the ice-substrate problem by modelling two major modes of ice adhesion test – tensile and shear tests, which are used for ice adhesion strength determination. The coarse-grained model of water is nucleated to form ice at the temperature which is designated for ice adhesion test on a macroscopic level. Steered molecular dynamics (SMD) is then applied to the nucleated ice cube to then obtain tensile and shear adhesion strengths over various FCC surface morphologies that represent the crystal structure of metallic substrates. The results obtained from the adhesion simulations are then used to compare the nanoscale trends on ice adhesion to the macroscale ice adhesion trends. The simulation results show that while contact area and temperature variations have similar trends to the observed macroscopic trends, other variations like tensile and shear loading rate variation at the nanoscale are not directly understood from macroscopic interpretations of ice adhesion. For developing high performance, low-energy ice protection systems, it is vital to understand the icing physics at the interface of the ice and substrate. This can be achieved by modelling the interface at nanoscale and then studying the adhesion trends. This is achieved by testing the ice adhesion strength of various surfaces that form part of the systems or structures which are exposed to icing conditions. Ice adhesion strength is defined as the maximum force required to detach ice from a substrate surface divided by the apparent contact area.8 Traditional methods of measuring ice adhesion strength include the various tensile and shear test methods that have been developed over the years.9 The brittle and complex mechanical behaviour of ice under different kinds of loads makes it difficult to understand the adhesion phenomena and predict accurately how ice might behave when subjected to an external force. Study of interfacial ice adhesion has been conducted extensively to understand the nature of ice and it's behaviour with respect to different substrates.10–13 It is important to analyse the atomistic ice adhesion behaviour to build a comprehensive model to determine behaviour of ice on various substrates. Nanoscale mechanisms of ice adhesion describe the effect of non-bonded interactions like van der Waals and electrostatic interactions being important to adhesion of ice to a substrate.14 An in-depth look at nanoscale fracture mechanics is necessary for our complete understanding of the ice adhesion phenomenon. Macroscale experiments are not the best possible tool when it comes to understanding ice-substrate interactions or adhesion mechanisms precisely because they don't provide access to nanoscale fracture mechanics. The spatial and temporal resolution of macroscale experiments is limited.The dangers of icing are well known within the engineering domain. It can lead to hazardous conditions or in extreme cases, serious accidents that can even result in loss of life.15 It has been used in multiple studies for gaining further understanding of nanoscale ice adhesion mechanisms and interactions with various types of surfaces.16–19 Macroscopic ice adhesion trends have been studied in the past.20–23 These trends have been mostly consistent across the various studies for different factors that affect ice adhesion like temperature, contact area, loading rates etc. The previous literature reviewed for this research work shows that, these ice adhesion testing trends have not yet been studied at nanoscale. This paper describes the development of an ice-substrate atomistic model, based on known tensile and shear ice adhesion tests, using which ice adhesion strength values have been obtained for idealized FCC substrates. The variation in these adhesion strength values are studied with respect to the change in loading rate, temperature, contact area and surface morphology. These trends are then compared to the macroscopic test trends from literature to obtain the similarities or differences between the two scales which is the key contribution to knowledge from this paper. The results from this study can be fed into higher order models like crystal plasticity FEM models for ice adhesion or mesoscale ice formation models. These higher order models can be important tools for optimization of material design for ice protection in the future. The simulations are carried out in the software package called LAMMPS .24 Visualization of the models and the simulation results is done in the software package OVITO .25 For studying the various ice adhesion trends, a coarse-grained modelling strategy is adopted. The substrates for the coarse-grain model are generic Face Centred Cubic (FCC) surfaces of 4 different morphologies.The best suited tool for analysing nanoscale interactions of ice and substrate is atomistic modelling and molecular dynamics (MD) simulations. Atomistic water models can capture in more detail the solid–water interfacial region.26 and Scrape adhesion test,27 both developed at Cranfield University. They have been described below.The molecular dynamics simulations conducted in this research work reproduces a tensile and a shear adhesion test and replicate the mode of force application for both these types of tests. Although, many forms of such tests exist in industrial and research practice today, the two tests that this study focuses on, for a baseline to be used in the MD simulations, are the mode I test28 It is based off the Andrews & Lockington Blister Test. This test process makes use of a hollow cylinder which is covered partially by a small plastic disc. Ice is accreted on the cylinder to a significant enough thickness for the test to be in plane-strain conditions. The pressure is applied to the ice for delamination through the hole in the cylinder. The pressure is increased until the ice breaks of at a value called critical pressure, Pc. The failure can be categorized in 3 different ways: fully adhesive, fully cohesive, or partly adhesive and partly cohesive. This test procedure for ice adhesion has been developed by Hammond.The setup for the scrape adhesion test consists of a pipe, on which ice is accreted. A heated cutter is used to make a slot in the accreted ice such that a keyed guide shaft arm consisting of a scraping blade can be used for delamination of the ice. A load cell is used for capturing the recorded force values and a pneumatic actuator provides the requisite force to detach ice from the pipe surface in a shear manner. 29 and SPC,30 the strategy to use coarse-grained modelling for this work was made. The coarse-grained models are created to simulate the behaviour of complex systems using a simplified or coarse-grained representation of the system. By decreasing molecular details in the modelling, these models can study system behaviours for much longer simulation times. Monoatomic water (mW) potential31 is used for modelling the water molecule in this work. In the coarse-grained mW model, each H2O molecule is treated as a single particle interacting through anisotropic short-ranged potentials . Although explicit hydrogen atoms and electrostatic terms are not included, the mW model can correctly describe the thermodynamic properties and phase behaviour of water in bulk and on substrate. mW water model is able to replicate the melting point of hexagonal ice to a closer degree (274.6 K) when compared to other available atomistic models of water. It has been reported to reproduce the structural, thermo-dynamical properties of ice and water, and has been extensively applied to study the crystallisation of bulk water and nanodroplets as well as on different substrates.32The crucial step in atomistic modelling of ice adhesion is to determine the correct water or ice model for simulation. Since, the intent of this research was to study the adhesion trends as they occur in a test setup, it is important that the ice is nucleated on the surface rather than beginning with a pre-defined ice block of any set description. Keeping in mind the simulation timescales required for water nucleation to ice using complex, higher order water models like TIP4P33 Due to the difference in surface morphology between the four different types of FCC crystallographic surfaces, the sizes of the models vary slightly along with the number of atoms that range from 8200 to 9250 for the four models. Also, important to note that for most studies on ice adhesion test microscopic trends, FCC111 was chosen as the main representative surface to be used with the water slab. A larger model was also created with the FCC111 lattice orientation, in order to study the effects of a larger contact area on the adhesion strength at the microscopic level. Both tensile and shear simulations were performed on this larger model. The lattice constant was chosen to be around 4.05 for all the surfaces to ensure a good packing density of atoms within the substrate structure and to have a closer match to Aluminium which is the standard material used in Mode I tensile adhesion tests.26 For the water structure, a random lattice of atoms is defined in LAMMPS with dimensions of 10 × 10 × 10 A0 to give around 4000 atoms in total and surface contact area of 1 nm2. This structure is then minimized and equilibrated at 300 K within the canonical ensemble (NVT) for 20 ns to generate the final structure which can be used for the coarse-grained combined model. The different atomistic models for the substrate in the coarse-grained model are defined as four different crystallographic planes of a generic FCC crystal: {111}, {100}, {110}, and {211} surfaces. These models exhibit significant differences in terms of atomic roughness and the symmetry of the outer crystalline layer. The surfaces were created using the Atomic Simulation Environment (ASE) package in Python.0. The process of energy minimisation is used to bring both the structures in contact.The individual FCC lattices have different configurations resulting in different packing densities hence a different number of atoms. The water structure is not directly placed on top of the substrate but separated by a distance of 2 A35 The aluminium–hydrogen interactions are infinitesimal in comparison and thus are ignored for these simulations. The Lennard–Jones (LJ) potential for these interactions is based on the values defined in Mao et al.34 The main two parameters for the LJ interaction are given in The coarse-grained potentials have no surface–surface interactions since they are supposed to be generic FCC structures to allow the water model to nucleate effectively on the surface. The surface–water/ice interactions are primarily defined by aluminium–oxygen interactions.16 with use of the Nosé–Hoover coupling method to maintain the simulation temperature.36,37 The effect of the selected thermostat coupled with the NVT ensemble needs to be acknowledged before proceeding to the finer details of the modelling within this study. The use of the NVT ensemble precipitates that the results obtained from this work should be treated as figures of merit with which to investigate local effects. It is important to note that, the results do not show a one-to-one correspondence between adhesive strength obtained from the ice-substrate simulations in this work and those measured by an experiment at a much lower loading rate. The NVT ensemble with the coupling effect of a strong heat bath ensures that the model does not melt away or the simulation box doesn't vaporise under extremely high loading rates.The coarse-grained model made use of the ‘real’ units. Since the mW potential allows for larger timesteps within the simulations, a value of 10.0 picosecond (ps) for the equilibration and nucleation simulations and 5.0 ps for the force-probe simulations was used. The standard temperature selected for the ice-substrate simulations was 251 K (−22 °C). The models make use of the steepest descent algorithm for minimisation in order to relax the atomistic structures. The same equilibration process is carried out throughout for uniformity. The structures are initialised with an assigned temperature of 273 K (0 °C) and then equilibrated using the NVT ensemble for 50 ns. The NVT ensemble was selected for both the models as the appropriate ensemble to perform force-probe MD simulations,In order to perform the ice adhesion test, the starting point was the mW water model which is equilibrated in a separate simulation and the final equilibrated structure is combined with the substrate to form the final model. After this step however, a nucleation simulation is required which involved a shock-quenching with an immediate drop of temperature from 273 K to 180 K at the very start of the simulation resulting in nucleation and subsequently a rise in temperature to 251 K. This technique ensures that the water structure nucleates into ice and subsequently while heating up to 251 K which is the target temperature for the simulations, the ice doesn't melt into water.et al.38 The water structure is first equilibrated at 273 K. After the structure is stable, the structure is then quenched from 273 K to 180 K which represents a drop in temperature of 93 K. This process is done at a cooling ramp of 0.5K ns−1 and the total time for this process is around 194 ns which includes some additional 8 ns for stabilization post-quenching. There are minor changes for the different lattice models with the major change being the additional time added post quenching for stabilization which varies from 8 ns to 20 ns. The quenching results is a change of thermodynamic phase from water to ice and a re-ordering of the atomic structure. A sudden and sharp drop in potential energy characterizes this phase change.38 The most natural path for the ice crystal to grow preferentially is from a basal plane.14 This is possibly the reason why a small layer of water is observed in the coarse-grained models post the nucleation process. The prismatic plane is not considered a preferential growth plane for ice on the substrate. For the ice crystal to grow into a prismatic alignment during the simulation is significant but also slightly suspect as it deviates from the natural tendency of crystal growth for ice through the basal plane. The reason for this deviation could be:In order to nucleate the water into ice, the simulations follow the strategy adopted by Fitzner Size effect: the cell is so small the amount of water molecules introduced can only grow in that direction for the box dimensions chosen.• Geometric size effect: similar to the size effect but pertains more to the geometry of the simulation box which is in effect a square.• Limitations of coarse graining: the unusual ice crystal growth could be a consequence of interactions at the interface being not captured well enough or being too non-directional, which leads to prismatic growth.This particular approach with the coarse-grained models is significant in capturing this effect of unusual ice crystal growth on some of the substrates. This also reinforces the perceived complexity in modelling ice-substrate adhesion problem. In order to have a more comprehensive and detailed look at the ice adhesion to various substrates problem and extract useful data from it, there needs to be a consideration of other types of contact between ice and the substrate like basal and pyramidal contact with each relevant substrate surface. 39–41 Using fix smd, the centre-of-mass (COM) of the ice model is attached to a virtual spring within the simulation which is tethered to a point in the direction of the push/pull. The spring is assigned a chosen value of spring force (force/distance units) and a velocity (distance/time units). The ice model is then pulled away from the substrate and the resultant force is then captured which is determined to be the requisite force for ice delamination as shown in −1 Ang−2, and the assigned velocity was 0.5 nm ns−1 for the tensile delamination. For the shear delamination, the applied spring force was 10 kcal mol−1 Ang−2 and 15 Kcal mol−1 Ang−2 with a speed of 10 nm ns−1 and 15 nm ns−1 at both spring constants. Lower values failed to shear the ice from the substrate completely. It is a trial-and-error process to find the correct force for delamination with a reasonable computational time and processing effort. For lower loading rates, delamination of ice maybe observed but the excessively long computational time required makes it undesirable while working on the parallel processing queues. In order to perform fix smd, it is essential to have a counter force acting on the substrate to prevent it from being pulled along with the ice model. This was provided by the use of ‘fix spring/self’ which constrains the substrate model in place. The simulation box is expanded in the direction of the pulling force in order to observe the effect of the ice detachment. The most suitable option within LAMMPS for application of tensile and shear force was determined to be steered molecular dynamics using ‘fix smd’.x, y, and z component of the pulling force, the total force in direction of the pull, the equilibrium distance of the spring, the distance between the two reference points, and finally the accumulated Potential mean force, PMF (the sum of pulling forces times displacement). The trends for adhesion tests were studied using idealized substrates and coarse-grained models. This facilitated faster computational times allowing for more flexibility and evaluation due to the rapid dynamics of potentials like mW. Although mode I test were used as a rough template for the simulations, it is clear that the models require further development for them to be an accurate replication. This is especially true in terms of the force replication. Mode I test employs pressurized Nitrogen through a hole in the substrate to dislodge the ice accreted on it.8 This was particularly challenging to replicate and needs further investigation in terms of the MD methods currently available. The trends observed have been discussed in more detail below.Under the applied load, the ice substrate is delaminated from the substrate. This force is captured by the 7-vector output produced by the ‘fix smd’ within LAMMPS which gives the following quantities: the 16,17,42 The values are way higher than those observed traditionally in macroscopic experiments which are around 1 MPa.8,43–46 This is mainly due to the loading rates used in molecular dynamics which are of 6–7 orders of magnitude higher than their macroscopic counterparts.The ice adhesion values found by this research work significantly higher than the ones observed at the macroscopic level. This is consistent with previous work done on ice adhesion in MD simulations.2. The temperature of the simulation was maintained at 251 K for all simulations and the NVT ensemble was used for the force-probe simulations. −1, 1.0 nm ns−1, 2.0 nm ns−1 to 5.0 nm ns−1. The value of adhesion strength and shear force obtained for these force-probe simulations are reported in In order to study the effects of the tensile loading rate of the adhesion strength, the assigned spring velocity which represents the loading rate (displacement/time) was varied on the FCC111-ice combined coarse-grained model with lesser apparent contact area of 1 nm20 clearly states that the strength of ice depends on the rate of loading and the manner of the load application to the substrate apart from other factors involved in the process of failure. As noted by Kasaai et al.47 ice exhibits elastic behaviour at low strain rates and brittle behaviour at high strain rates. This in turn means that adhesive failure is more likely at low strain rates and cohesive failure at higher strain rates. This is observed in the results from this research work as well with all the coarse-grained models yielding cohesive or mixed failures. The trend of ice adhesion strength with tensile loading rate is not clear from macroscopic experiments as noted by Meng et al.23 The tensile strength shows little increment with the increase in loading rate. The tensile strength of ice reaches a maximum value at a specified loading rate. The tensile strength after this point, decreases with the loading rate continuing to go up. The tensile strength of ice reaches the maximum 3.3070 MPa at −40 degrees Celsius and the loading strain rate 0.3 kN s−1 . The corresponding shear adhesion strength was 3207.53 MPa. This is considerably higher than the shear strengths observed in actual macroscopic experiments around 500–2500 kPa.8 This is to be expected due to the higher loading rates in molecular dynamic simulations which is around 6–7 order of magnitudes than the macroscopic experiments.The force profile as shown in 48 Solid ice is a kind of typical elastoplastic material. When the shear rate is slow, the ice crystal has enough time to shear slip, and it presents ductile failure characteristics. More loading rate data points are required to obtain a holistic picture of shear strength variation for ice with loading rate at the microscale.2) was subjected to force-probe simulations with the same force and loading rate of 10 kcal mol−1 Ang−2 and 0.5 nm ns−1 at two different temperatures of 251 K and 268 K. These temperatures are similar to two different temperature settings that can be used in the mode I test at Cranfield Icing tunnel. The result from this simulation is reported in 8 The adhesion strength value changes from 13 071.77 MPa for 251 K to 11 806.89 MPa for 268 K force-probe simulations.In order to study the variation of adhesion force and strength with temperature at nanoscale, the FCC111-ice combined model with lesser apparent contact area  were subjected to a tensile load at 251 K. The tensile load was applied via SMD in LAMMPS with a spring force constant of 10 kcal mol−1 Ang−2 and 0.5 nm ns−1 spring velocity. The increase in apparent area of contact shows a clear decrease in the adhesion strength and significant increase in the detachment force as seen in 2 model to 8467.56 MPa for 16 nm2 model with larger contact area.For studying the effect of contact area variation, two FCC111-ice coarse-grained models with varying dimensions and contact area  under the same simulation settings and temperature of 251 K. The tensile load is defined by the spring force constant of 10 kcal mol−1 Ang−2 and 0.5 nm ns−1 spring velocity. In order to study the effects of surface morphology on the adhesion strength at nanoscale, a tensile load is applied to the four different coarse-grained FCC lattice models with lesser apparent contact area .et al.38• This might explain the variation observed with the adhesion strength with the FCC110 surface showing highest ice adhesion strength with the FCC111 showing the second highest. However, this needs further study. There is no literature found in the macroscopic regime with respect to this trend which is understandable since this work cannot be conducted with traditional ice adhesion experimental procedures.e.g.: based on crystal plasticity finite element method (FEM) modelling). These models can be used to study in greater depth, the behaviour of ice on various substrates which is not possible from macroscopic experiments or even engineer more specific substrates. Size effects to study how change in simulation box size, aspect ratio and orientations affect the adhesion strength results and nucleation dynamics is an interesting path for further work. Thermal expansion coefficient study and analysis of structural changes of ice with respect to change in temperature would also be of interest for future work in refining this ice-substrate model study.The ice adhesion trend analysis was conducted with the use of molecular dynamics simulation. Several variations of these simulations were conducted to study the variation of the ice adhesion strength with loading rates, contact area, temperature, and surface morphology. More data points in general with respect to loading rate in both shear and tensile regimes, contact area and temperature would make for a better and more comprehensive future study. This work has tried to co-relate these trends observed using MD simulations with the trends at macroscopic level. Some of the trends are clearly similar while others need more exploration. It's important to note that research work clearly shows the difficulty in the transability of results from the macroscopic to the nanoscale regime using MD simulations. The applied force for delamination in these simulations operate as a figure-of-merit rather than actual atomic forces. Certain variables like stress and strain do not directly translate at the nanoscale level from the macroscopic level. Usually, it's not virial stress that is computed in these simulations. The strain rates are several degrees higher than the macroscopic regime and thus the results are not one-to-one. However, even with these limitations on the creation of atomic models and the results obtained, it is still worthwhile performing and further exploring the ice-substrate problem using molecular dynamics. The results although not accurate when compared to macroscopic experiments, can still be utilised to create mesoscale models (for There are no conflicts to declare.


Immunoglobulin E (IgE) is implicated in the pathogenesis of acute myocardial infarction (AMI), and smokers often exhibit elevated plasma IgE levels. However, it remains uncertain whether the role of smoking in the development and prognosis of AMI is influenced by IgE levels. This study aimed to investigate the potential contribution of IgE in mediating the association between smoking and AMI.We conducted a prospective study involving 348 consecutive patients with chest discomfort who underwent coronary angiography. Plasma cotinine, an alkaloid present in tobacco, and IgE levels were measured. The patients were followed up for mean 39-months to assess their long-term prognosis based on major adverse cardiac and cerebrovascular events (MACCE). = 1.7, 95% CI: 1.27–2.26, P < 0.001) and IgE  with AMI. Receiver operating characteristics analyses showed that the combined use of cotinine and IgE (AUC: 0.677) had a larger predictive performance compared to cotinine alone (AUC: 0.639) or IgE alone (AUC: 0.657), although the improvement did not reach statistical significance. Multivariable logistic regression revealed a positive association between plasma cotinine and AMI . Furthermore, the inclusion of plasma IgE in the regression model led to a decrease in the OR and 95% CI of plasma cotinine . Process mediation analyses showed a significant indirect effect of plasma cotinine on AMI mediated through increased plasma IgE. Kaplan–Meier analysis during a mean 39-months follow-up revealed that higher plasma levels of IgE were associated with an increased risk of MACCE following AMI (P = 0.047). However, in the context of the COX regression analysis, no significant correlation was observed between IgE, cotinine and AMI.Our findings indicate that patients with AMI had higher plasma levels of cotinine and IgE. Univariate analyses demonstrated a positive association between plasma cotinine . Atherosclerotic cardiovascular diseases continue to be the leading cause of morbidity and mortality worldwide . Acute mImmunoglobulin E (IgE) plays a crucial role in the pathogenesis of allergic responses by mediating the activation of macrophages, leading to the release of inflammatory molecules such as TNF-α and IFN-γ . ExperimEmerging evidence supports the crucial role of inflammation in the pathophysiology of smoking-induced CHD , 13. ProGiven the existing knowledge gaps, our study aimed to evaluate the levels of two specific factors, cotinine and IgE, and investigate the associations among cotinine, IgE, and smoking exposure. Additionally, we conducted a prospective study of AMI patients, to assess the occurrence of major adverse cardiac and cerebrovascular events (MACCE) and explore the potential roles of smoking and IgE. Hypothetically, we propose that cotinine-verified smoking serves as a risk factor for AMI and predicts poor prognosis through an inflammatory response mediated by IgE.n = 2); history of asthma (n = 6), malignancies, autoimmune diseases; and treatment with anti-inflammatory drugs (n = 5). Patients with advanced liver disease, renal failure, and valvular heart disease were also excluded (n = 5). A total of 6 patients with AMI were lost during the 3-year follow-up. The study population included 260 patients with non-AMI (including 92 non-CHD patients and 168 stable CHD patients), and 88 patients diagnosed with AMI . AMI patients were followed during a mean period of 39 months and categorized according to levels of IgE and cotinine . Identification of AMI was performed following the recent consensus documents of the American Heart Association and the American College of Cardiology .Patient information was recorded, including age, sex, and cardiovascular risk factors. Smoking status was categorized as smoker and nonsmoker (lifetime smoking history of fewer than 100 cigarettes). Smoking index was calculated using average number of cigarettes smoked per day multiplied by the number of years of smoking. Diagnosis of diabetes was made according to the criteria of the American Diabetes Association  . HyperteBlood samples were obtained from all participants while in the recumbent position via antecubital venipuncture at the time of hospital admission. The plasma concentration of high-sensitivity C-reactive protein (hs-CRP), white blood cells (WBC), uric acid, creatinine, alanine aminotransferase (ALT), asparagine transaminase (AST), glycated hemoglobin (HbA1C), N-terminal pro-brain natriuretic peptide (NT-proBNP), cardiac troponin I (cTNI), and lipid profiles, including total cholesterol, triglyceride, LDL-C, and HDL-C, were measured according to standard laboratory protocols. Plasma levels of cotinine and IgE were determined by enzyme-linked immunosorbent assay (ELISA), according to the manufacturer's protocols .All participants underwent transthoracic two-dimensional and M-mode echocardiography following recommendations provided by the American Society of Echocardiography . Left veClinical follow-up was conducted using a structured questionnaire of the patient's inpatient medical records, regular outpatient visits, and telephone interview. 88 patients with AMI were followed up for 30–46 months (average 39 months). Six patients were lost during follow-up . The priU-test for comparisons between groups. Categorical variables were summarized as frequencies (percentages) and compared by chi-square test. Partial correlation test was used to assess the correlation between two variables. To determine the association between independent variables and AMI, logistic multivariate regression analysis was performed for indicators with P < 0.05 in univariate analysis to calculate odds ratio (OR) and 95% confidence interval (95%Cl). Cotinine, IgE, and NT-proBNP with larger degree of dispersion were analyzed as log-transformed normally distributed variables. Receiver-operating characteristic (ROC) curves were plotted to determine the cotinine and cotinine with IgE for detecting AMI. Using the approach by Hayes and Preacher .For the continuous variables, data were expressed as the median with inter-quartile ranges. Differences in data were evaluated using Mann–Whitney Preacher , the dirP = 0.03), higher smoking index . There were no significant differences in age and history of hypertension, diabetes, or hyperlipidemia between the two groups. At baseline, hs-CRP, WBC, creatinine, cTNI, NT-proBNP among AMI group were significantly higher, whereas HDL-C and LVEF were lower compared with that in the non-AMI group. In addition, the plasma levels of cotinine  and IgE  were significantly higher in the AMI group.In the current study, we included 348 study participants  of which 260 patients were diagnosed with non-AMI, and 88 patients were diagnosed with AMI. The baseline clinical characteristics in the non-AMI and AMI patients are presented in P < 0.001), had higher plasma creatinine (P < 0.001), cotinine  and IgE  .Because cotinine is the main metabolite of nicotine and smoking might induce the elevation of plasma IgE, we compared the difference of cotinine, IgE, and other parameters between smokers and non-smokers . Compare< 0.001) . FurtherP < 0.001) and AMI. Similarly, there was a positive association between plasma IgE (log 10)  and AMI. To investigate whether cotinine and IgE could provide better prediction of AMI compared with plasma cotinine alone, we performed ROC analyses. The results showed that the area under the curve (AUC) for IgE was 0.657 (95% CI: 0.590–0.725)   . As show0–0.725) .P = 0.036) remained statistically significant. When IgE (log 10) was added into the multivariable analyses model, a decrease in the association of cotinine  with incident AMI was observed  and incidence of AMI with or without IgE (log 10). By univariate analyses, we confirmed that sex, WBC, HDL-C, hs-CRP, LVEF, cTNI, and NT-proBNP (log 10) were significantly positively associated with AMI . In multobserved . HoweverTo evaluate whether the reduced odds ratio is indeed due to increased IgE, we further performed mediation analyses using the statistical approach by Hayes and Preacher . By thisP = 0.001), and plasma IgE , and HbA1c  in MACCE (+) group were higher compared with that in the MACCE (−) group (P = 0.798) and other clinical markers  AMI patients suffered from MACCE. Patients with AMI were divided into two groups based on MACCE, namely MACCE (+) and MACCE (−) groups. We compared the baseline characteristics between the two groups, and found that patients in the MACCE (−) group were significantly younger than those in the MACCE (+) group  group . However markers .P = 0.047). However, no difference was found for survival time between high and low levels of plasma cotinine  and low (Q1–Q2) level groups based on plasma cotinine and IgE quartiles. The Kaplan–Meier curve depicted the follow-up without MACCE (MACCE-free) survival by comparing high and low levels of cotinine and IgE in AMI patients, followed by comparison of survival curves using the log-rank test. As presented in We further conducted multivariate COX proportional hazard regression analysis to identify risk factors for MACCE. However, after adjustment for confounders, the results showed that only age was significantly associated with MACCE, while IgE and cotinine did not show any significant correlation with MACCE .In the present study, we observed a significant elevation in the concentrations of both plasma cotinine and IgE in patients with AMI. Both elevations in plasma cotinine and IgE were associated with AMI, and the predictive performance of cotinine combined with IgE was better than that of either alone. Importantly, our data suggest that the impact of cotinine on AMI is partly mediated by an increase in plasma IgE concentration. Additionally, plasma IgE, not cotinine, was significantly associated with MACCE events within a mean 39-months follow-up after AMI.Elevated plasma concentration of IgE has been investigated as a potential risk factor for CVDs , 27. MeaSmoking disturbs immune homeostasis by modulating immune-regulatory activities, leading to various pathogenic mechanisms, including increased oxidative stress, reactive oxygen species (ROS), and the activation of T and B cell proliferation, which subsequently enhance the expression of pro-inflammatory markers . StudiesA higher proportion of patients with AMI were found to have a history of smoking and elevated plasma cotinine levels, which is consistent with previous reports , 36. BasDespite extensive clinical, experimental and epidemiological investigations on the association between smoking and AMI, the underlying mechanisms are still subject to ongoing scrutiny , 38. SmoP = 0.048) of MACCE. Both AMI and smoking can trigger immune-inflammatory responses that lead to IgE release. Furthermore, IgE not only plays a role in the acute phase of AMI, but also contributes to the process of ventricular remodeling  and non-ST-segment elevation myocardial infarction (NSTEMI), both conditions are considered acute coronary syndromes characterized by acute myocardial injury due to coronary artery ischemia. As IgE is involved in acute inflammatory responses, it is plausible that there may be no significant differences between the two groups regarding acute myocardial injury and inflammatory response. Finally, the cotinine-based correction introduces potential bias as cotinine levels can be influenced by other factors, which may in turn affect a minority of the participants. Further studies with larger sample sizes are warranted to validate our findings and elucidate the underlying biological mechanisms.Our study demonstrates that elevated plasma cotinine and IgE concentrations are associated with AMI. IgE may partially explain the increased incidence of AMI in smokers as indicated by cotinine measurement. Additionally, IgE shows promise as a predictor of MACCE after AMI. These findings support the role of elevated IgE as a mediator in the pathogenesis of smoking-related cardiovascular disease. Targeting the IgE pathway and its associated inflammatory mechanisms may hold promise for preventing fatal cardiovascular events among smokers.


Post-translational modifications (PTMs) provide a rapid response to stimuli, finely tuning metabolism and gene expression and maintain homeostasis. Advances in mass spectrometry over the past two decades have significantly expanded the list of known PTMs in biology and as instrumentation continues to improve, this list will surely grow. While many PTMs have been studied in detail , the vast majority lack defined mechanisms for their regulation and impact on cell fate. In this review, we will highlight the field of PTM research as it currently stands, discussing the mechanisms that dictate site specificity, analytical methods for their detection and study, and the chemical tools that can be leveraged to define PTM regulation. In addition, we will highlight the approaches needed to discover and validate novel PTMs. Lastly, this review will provide a starting point for those interested in PTM biology, providing a comprehensive list of PTMs and what is known regarding their regulation and metabolic origins. The ability of cells to rapidly detect and respond to stimuli is critical to maintaining homeostasis ,2. As prIn the context of cell fate, there is no place where the regulation of PTMs is more critical than the nucleus . HistoneAre all PTMs regulatory?While many PTMs are tightly regulated through enzyme-catalyzed reactions, there is now mounting evidence that PTMs generated through non-enzymatic means may play a significant role in cell signaling, rather than serving as simple markers of toxicity . A primeIn this review, we will highlight the field of PTM research from the proverbial 30 000-foot view, solely focusing on modifications to amino acid sidechains and neglecting N- and C-terminal modifications. As an in-depth review could be written about nearly every PTM, our intent is not to take a deep dive into any single modification, but rather take a global view the field, the mechanisms that govern PTM site-specificity, and the technologies to investigate their role in health and disease. We will also close by discussing a growing notion that many PTMs simply serve as a metabolic reserve for nutrients and play a minimal role in the regulation of protein function. This review also aims to serve as a starting point and resource for those interested in studying PTMs using thorough analytical approaches.https://awi.cuhk.edu.cn/dbPTM/) is an open access software that mines and curates existing PTM databases to provide functional and structural insights into >2 000 000 experimentally validated PTM sites . The2O2 due to the oxidation of an active site Cys and full restoration 30 min post-exposure . Am. AmQuantUndoubtedly the utility of bottom-up proteomic approaches has been instrumental in the discovery and quantitation of PTMs in biology. A significant shortcoming of these approaches, however, is that PTM stoichiometry on a single molecule is lost. Top-down proteomic approaches have aimed to address this, by ionizing intact proteins and analyzing subsequent fragment ions . This yiSpectral Alignment-based Modified Peptide Identification, or SAMPEI, was developed based on the rationale that MS/MS spectra of protein are produced from both modified and unmodified peptides, and thus any statistics-based algorithm, such as X!Tandem, can be used for peptide sequence matches (PSMs) [Due to the chemical heterogeneity of PTMs, MS and MS/MS spectra are often complex . Databass (PSMs) . The rems (PSMs) . These Ps (PSMs) ,89. Thisin silico digestion of a protein database [in silico digested peptides are compared with experimental spectra. It is noteworthy that an inaccurate estimation of FDR occurs in a narrow-window search using a target-decoy strategy and this can be improved by accounting for all modifications under an open search strategy [Open search, which allows for a larger precursor mass tolerance resulting in the analysis of more spectra, is employed to explore the vast diversity of PTMs that are not accounted for in database search algorithms; however, achieving a comprehensive PTM search with practicality requires a sophisticated computational strategy. MSFragger, generates a theoretical fragment-ion index of peptides from database . Mass bistrategy . In addistrategy .The sequence alignment software, PTMap, has been immensely successfully in identifying novel PTMs, particulary on histones, including Lys succinylation, Lys crotonylation, Lys benzoylation, and Lys lactylation ,92–95. Pin vivo [. Alternatively, stable isotope labeling can be used to verify PTMs and their metabolic origins. Here, a metabolic precursor (e.g. 13C6 glucose) is fed to cells and the incorporation of isotopic labels can be monitored on PTMs of interest (e.g. +2 Da for Lys acetylation) [MS-based proteomic studies have become commonplace in PTM research; however, appropriate analytical rigor must be maintained to ensure reproducibility. While many studies are focused on bulk PTM inventories using antibody-based pulldowns, it is important to manually validate and characterize sites of interest. This can be achieved using synthetic peptides to demonstrate co-elution and identical MS/MS fragmentations (i.e. y- and b-ions) ,94. Thisin vivo . Alternaylation) . This adN-acetyl-a-galactosaminyltransferases [Although immunoaffinity enrichments are commonplace in PTM research, chemical biology approaches are being adapted at an increasing rate and offer improved specificity and assay diversity. The advent of click chemistry-based probes has transformed our ability to study PTMs in cells with unparalleled specificity. By appending relatively inert bioorthogonal chemical tags  onto metabolic PTM precursors, it is possible to track the incorporation and regulation of these modifications over time, providing information on PTM half-life, protein turnover, and cellular fate . The firsferases ,99. Clicsferases .The metabolic labeling of precursor molecules is the desired approach for the use of chemical biology probes, as they rely on the cells natural mechanism to deposit and regulate PTMs. This approach, however, is not possible for all PTMs as many are sterically restricted or too small  to allow for the incorporation of a chemical tag. Reactivity-based protein profiling has been instrumental in the study of numerous PTMs through an agnostic ‘addition by subtraction’ approach ,104. Usi2), selectively forming a complex with phosphorylated substrates. Modified samples are then eluted and can be monitored using either immunoblotting or LC–MS/MS [Perhaps the original application of chemical biology for the study PTMs was the use of metal oxide affinity chromatography (i.e. IMAC) to selectively isolate phosphorylated proteins ,111. HerLC–MS/MS . This siLC–MS/MS .What are the parameters that determine site-specificity? How are PTMs that lack a sequence motif regulated?Traditionally, PTMs are viewed as tightly regulated and precisely placed through enzyme-controlled processes. PTM ‘writers’ often recognize a consensus sequence (i.e. a sequence motif) that marks a site for modification. For example, N-linked glycosylation occurs on Asn that reside in the Asn-X-Ser/Thr motif, where X is any amino acid except Pro . This moAn argument could be made that the vast majority of PTMs are derived from non-enzymatic reactions  and drivThis ‘mass action’ mode of PTM generation is perhaps best explained through the oxidation of Cys residues. Cys152 of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is heavily prone to modification, susceptible to sulfenylation , sulfinyJust as the site-specific addition of a PTM is critical to enzyme activity, efficient removal is also important to restore enzyme function. This action is performed by molecular ‘erasers’ which have been identified for many PTMs . When erPTMs have historically been viewed as regulatory additions to proteins, providing a rapid response to regulate function ,117. In Multiple factors dictate whether a PTM serves a functional and/or regulatory role. PTMs residing within the active site are often regulatory, altering substrate and/or cofactor binding. This is typically confirmed using recombinant protein, providing kinetic parameters of enzyme inhibition. Recombinant approaches, however, do not provide information on the role of PTMs in cellular trafficking, protein–protein binding, and/or half-life. These questions can be addressed using site-directed mutagenesis, altering the PTM site to either a ‘null’ amino acid, incapable of modification while maintaining necessary electrostatics (e.g. Lys to Arg) or to a PTM mimetic (e.g. Lys to Gln for acetylation) ,134. AltN and IntC, respectively) it is possible to precisely incorporate a modification of interest into a target protein [N or IntC. Cells are then loaded with a synthetic polypeptide containing the opposing Int. When partner Ints interact, they undergo a rapid association and excision, resulting in chemical ligation of the peptide to the target protein [An alternative approach for the site-specific incorporation of PTMs into proteins relies on ultrafast split inteins ,139. Int protein . A major protein . While iPTMs are an integral part of biology, functioning as important signaling molecules to maintain homeostasis and adjust to metabolic and xenobiotic stressors. Consistent with this, there has long been a notion that most PTM sites are regulatory. Although many PTMs do serve this purpose, increasing evidence indicates that many PTMs may simply be along for the ride, providing no alterations in enzyme function. This idea has largely come to light with significant advances in chemical biology approaches. Notably, codon expansion allows for the precise incorporation of a PTM at a single site of investigation, rather than traditional ‘addition by subtraction’ approaches such as site-directed mutagenesis. Collectively, this has led to an intriguing hypothesis that PTMs may serve as a carbon sink, providing metabolic intermediates on demand through their enzymatic removal from protein substrates. As this field continues to experience a rapid expansion, it will be important for studies to maintain high analytical rigor, confirming observations with sound mechanistic studies. Advances in MS approaches have provided much of this added rigor, leading to increased reproducibility sound mechanistic insights into PTM biology.The authors declare that there are no competing interests associated with the manuscript.