In this paper, an analysis of a three-dimensional state of strain and stress in the case of the hot cogging process of X32CrMoV12-28 die steel with the application of the finite element method is presented. The results of the investigations connected with the simulation of the kinematics of metal flow and thermal phenomena are presented, accompanied by prognosing the formation of ductile fractures in the course of the hot cogging process conducted with the application of three different shape tools and of a proposed deformation criterion of the loss of cohesion. The applied anvils were found to be highly effective in the aspects of distribution of effective strains and stresses, absence of tensile stresses in the axial zones of a forging, and also of a significant thermal stability in the internal layers of a deformed material. The developed course of changes in the deformation of the damage factor in the case of forging in the investigated anvils renders it possible to predict the situation and the phase of deformation in which the loss of cohesion by a deformed material will occur. The comparison between the predicted and the experimental results showed a good agreement. The natural non-uniformity of a structure and the defects of an initial billet, as well as the non-uniformity of deformations resulting from the technological cogging process, contribute to different final properties of forgings. This multi-faceted and complicated influence is connected with changes observed in the course of hot deformation space stresses, strains and the temperature of a material ,2,3,4,5.In the course of the forging process, a material is formed into an appropriate shape; required mechanical properties, closely connected with the distribution of stresses and strains, are also obtained. Knowledge of these properties renders it possible to determine the areas with the highest plastic deformations and the situation of presumable cracks in a material. Analysis of the components of the states of strain and stress, and also of their changes in the course of the plastic shaping process, renders it possible to prognose maintaining a reforged material depending on the history of strains, owing to which one may initially prognose the internal quality of a forging at the subsequent stages of forging ,26,27.Determining the threshold workability of a material in the forging process is a significant issue from the point of view of designing the best possible technologies. One of the directions of investigations into this question was an attempt to determine the properties of a material and the parameters of the cogging process which result in the disturbance of the cohesion of the material and in the formation of cracks. The results of the conducted investigations demonstrated the significant influence exerted by the state of stress, strain rates, temperature, the parameters of microstructure and also by the conditions of friction on the contact surface between a material and a tool upon the threshold value of effective strain, after exceeding which a material cracks ,29.As a result of investigations into this issue, a number of criteria relevant to the formation of cracks using different analytical relationships based upon the values of stresses, integrated by means of material strain, were developed ,31,32. NFor that very reason, the original deformation criterion of the loss of cohesion, on the basis of the developed experimental curves of the threshold strains in the state of the function of the stress triaxiality and temperature, was applied. The possibility of predicting the situation and the phase of deformation in which the loss of cohesion of a plastically shaped material will occur is the source of numerous problems, but it is also indispensable for designing the best possible technological forging process appropriately.The objective of this paper was to conduct an analysis of the distribution of effective strain, stresses and temperature and also to predict the formation of cracks in the course of plastic shaping in the three selected kinds of shaped anvils, complementary to one another, in the technological process of cogging X32CrMoV12-28 die steel.iF is the surface traction, iu is the velocity, S is the surface, V is the volume of a sample and K is the penalty constant (K = 106).The finite element model of the cogging process is used. The solution is based upon a thermo-mechanical approach, combined with solving the Fourier equation for non-stationary heat flows. According to the variational principle, the basic equation for the finite element formulation can be written as follows ,14:(1)δΠk is the thermal conductivity, T is the temperature, ρ is the specific density, c is the specific heat and α means the part of the mechanical energy converted into heat (assumed to be 0.9).Consider that a heat transfer can be conducted by solving the following equation :(2)k∇2T+nq denotes the heat flux across the boundary surface. The temperature distribution of the workpiece can be received by solving Equation (4).The equation, Equation (2), can be rewritten as follows using the weighted residual method:m is the friction factor, k is the shear yield stress, su is the velocity vector of the workpiece relative to the anvil and u0 is a very small positive number compared to |su|.The effect of friction at the workpiece–tool interface can be allowed for by the following equation ,19:(5)f=−1. The course of the relationships between true stress and true strain and temperature for two selected strain rates—1.0 and 3.0 s−1—and also for three temperatures—1123, 1223 and 1473 K—are presented in For the analysis of the cogging process, a finite element method-based commercial software SFTC DEFORM-3D V.11 program was applied. It renders it possible to conduct thermal-mechanical simulation of the forging processes in a three-dimensional strain state. For obtaining the properties of the investigated X32CrMoV12-28 die steel at elevated temperatures, experimental plastometric tests were conducted; these included the compression of axial-symmetrical samples which had the following dimensions: ø30 × 30 mm on a cam plastometer (MAEKAWA-Japan), taking into consideration the different values of strain, strain rates and the determined scope of the temperature of hot deformation hε= 0.35 and the constant feed rate amounting to wl = 0.75 in every pass. Forging was conducted in two anvils for preparing—one convex, which had the impression angle of 130° . Tensile stress Θσ acted in the circumferential direction; hence, the calculated mean stresses on the free surface, in the middle of the upset samples, assumed variable values from tensile to compression. The conducted research allowed to establish the relationships between the threshold effective strain and stress triaxiality and temperature for the X32CrMoV12-28 die steel, which are presented in For the X32CrMoV12-28 die steel, experimental model sample upsetting was conducted in order to determine the relationships between the threshold strain and the stress triaxiality and temperature. The calculations were made for samples with heigh/-diameter ratio H/D = 0.40–1.50 for different values of the friction factor, 0.05–0.70, and for three temperatures, 1173, 1323 and 1473 K, by the finite element method. The initial diameter was ø30.0 mm and the initial height of the sample was determined from the adopted height/diameter ratio value . The samples were deformed to a final height at which cracks were observed on the free surface. The values of the friction factor used in the calculations were also determined on the basic of additional ring compression tests. The determined component of the stress tensor 1/h, where h and h1 are the height of the initial and deformed billet, respectively); (3) the feed rate amounted to 0.75 in every pass [The process conditions in the FE simulation and some thermal physical properties of the workpiece were as follows: (1) the friction factor between the billet and tool was 0.7 ; (2) the reduction ratio varied from 0.01 to 0.35 at intervals of 0.01, the assumed deformation value of 0.35 resulted from experimental analyses of forging the tested steel under production conditions  ery pass ; (8) theery pass ,32,33;  was determined with the application of the following dependence:t is microcrack healing coefficient.Calculated with the application of the above-mentioned dependence (7), this factor is a non-dimensional parameter, and the critical value of it amounts to 1. The areas which have the critical value of the factor constitute situations where it is probable that microcracks will appear. For the cyclical cogging process conducted in two consecutive passes with rotating of the billet, the deformation damage factor was determined with the application of the following dependence:t is a complicated task, the objective of which is to investigate a particular steel in changeable thermal-mechanical conditions. The t coefficient can be determined at the moment of the crack’s appearance using Equation (8), based on the assumption that the critical value deformation damage factor sΨ = 1.0. The calculations assume the constant of the t coefficient in every pass. The unknown value of the index exponent in the polynomial Equation (8) was determined by the method of successive approximations, using the developed computer program. For the investigated die steel, the determined value of coefficient t amounted to 1.485.Simultaneously, with initiating and increase in cracks in the course of plastic shaping, there occurs the process of ‘healing’ microcracks and slowing down their development. The process of bonding cracks in the conditions of triaxial compression also occurs as a result of their relative resituation. At high deformation temperatures, the microcrack ‘healing’ process also occurs as a result of the recrystallisation and diffusion processes. The microcrack ‘healing’ coefficient for a given material is the function of the factor of the stress triaxiality, effective strain rate and temperature  forging tools are analyzed. The prediction of cracks in a forged material on the basis of the proposed deformation criterion of loss of cohesion was formulated. A schematic illustration of conducting particular technological passes and also the geometrical model of the anvils and the deformed material are presented in In 962–1.07 A-b. It w 110 MPa B-b.T = 90–120 °C, was observed.The presented distribution of the mean stresses in hε = 0.70) are presented. The anvils applied in investigations demonstrated a favorable influence upon the distribution of effective strain and effective stress in the cogging process. The highest values of effective strain were observed in the areas of a forging situated under the convex surfaces of anvils  in both tools, comparable values of effective strain were obtained, whereas in the lateral areas of a forging deformed in assembly of three-radial anvils point B, a, the hiσT, in the function of reduction ratio at the selected points of the cross-section in the course of forging a sample of the X32CrMoV12-28 die steel in three investigated anvils, are presented. The convex shape of the working surfaces of convex anvils, and of the assembly of three-radial ones, brought about the concentration of significant compression stresses in the central parts of the deformation valley, on insignificantly small areas, not significant for forging technologies, subjected to the impact exerted by tensile stresses. The stress triaxiality, accompanied by an increase in reduction ratio, particularly for applied anvils, adopted favorable negative values.In hε = 0.15–0.35, it was transforming entirely into compressing stress, whereas the intensity of these changes was determined, in addition to that, by the shape of the applied anvils. The most favorable conditions for reforging the particular zones of a forging were obtained in assembly of three-radial anvils, where, at a reduction ratio of 0.15 in the lateral zones of a forging, a favorable change from tensile stresses into the compressing ones was obtained , lateral surface (B) and the internal point (C)—in the course of forging a sample of X32CrMoV12-28 die steel in three investigated anvils are presented. The presented values demonstrate significant differences in the values of deformation damage factor for the analyzed areas of the cross-section of a forging. The analysis of the results of the investigations, after the first pass (reduction ratio of 0.35), failed to demonstrate significant differences in the values of factor SΨ in particular investigated tools. The scope of the values of deformation damage factor for the analyzed points of the cross-section amounted to SΨ = 0.05–0.13. For samples deformed in convex anvils and anvils with skew working surfaces, the highest values of the deformation damage factor were observed in the central parts of a forging (point A). On the lateral surfaces (point B), lower values of the deformation damage factor were observed. For samples deformed in assembly of three-radial anvils, the highest values of the deformation damage factor were observed in the lateral zones of a forging (point B). In the central parts of a forging, the lowest values of the deformation damage factor (SΨ = 0.05) were obtained. In the zone determined by point C, the mean values of factor SΨ were observed. In the distributions of the deformation damage factor, it is possible to observe a close connection with a local distribution of the values of effective strain, accompanied by increase in reduction ratio; the varied local values of effective strain, and also the values of deformation damage factor, were more and more visible.In hε = 0.70) brought about an intensive increase in the values of the deformation damage factor, SΨ = 0.30–0.35, in the particular zones of plastic deformation represented by points A, B and C, whereas the character of these changes for particular investigated anvils was similar to the results obtained after the first technological pass (hε = 0.35). A further increase in the total reduction ratio up to the value of hε = 1.40  in the course of forging in anvils with skew working surfaces brought about a proportional increase in the deformation damage factor at particular points of the cross-section . These three kinds of applied forging tools ought to be included into the group of highly-effective ones in the aspects of distribution of effective strain and stress, absence of tensile stresses in the axial zones of a forging and also significant thermal stability in the internal layers of a deformed material. Particularly favorable was the application, at the initial stages of forging, of a special assembly of three-radial anvils. In the course of forging in these anvils, no limited workability zones were observed. The maximum values of effective strain were found upon the surface of a forging, and insignificantly smaller values were found in the central parts of it, in the absence of non-favorable tensile stresses. In the surface zones of a forging, a lot of heat of plastic deformation work was generated, and for that very reason, the cogging process was accompanied by small changes in temperature in the volume of the deformation valley, contributing to a high uniformity of the distribution of effective strain.SΨ) in the course of cogging were the shape of anvils and the value of reduction ratio. The investigated changes in the deformation damage factor in the course of forging in different investigated anvils were the source of data on the values of factor SΨ in particular zones of plastic deformation and rendered it possible to predict the situation and the phase of deformation in which the loss of cohesion of a deformed material will occur. At the initial stages of forging, it is proposed to apply highly effective convex anvils or assembly of three-radial ones; further, and also finally, forging may be conducted in universal anvils with skew working surfaces.The possibility of prediction of the ductile fracture of a shaped material in the cogging process is an indispensable element of designing the best possible forging technologies. The principal parameters changing the values of the deformation damage factor (


Mitochondrial-derived reactive oxygen species are important as antimicrobial agents and redox signals in pro-inflammatory macrophages. Macrophages produce superoxide in response to the TLR4 ligand LPS. However, the mechanism of LPS-induced superoxide generation is not fully understood. Superoxide is produced at complex I and complex III of the electron transport chain. Production of superoxide at either of these sites is highly dependent on the metabolic state of the cell which is dramatically altered by TLR4-induced metabolic reprogramming. This review will outline how metabolism impacts superoxide production in LPS-activated macrophages downstream of TLR4 signalling and address outstanding questions in this field. They Toll-like receptor 4 (TLR4)-activated macrophages adopt a specific metabolic signature characterised by suppression of oxidative phosphorylation (OXPHOS), an upregulation of glycolysis and an accumulation of the TCA cycle metabolites itaconate and succinate . LPS-stiThe major production sites of superoxide within mitochondria are complex I and complex III of the electron transport chain (ETC) .However, the relative contribution of these sites to superoxide generation in TLR4-activated macrophages is unclear. It is well established that mitochondrial properties and cellular metabolism significantly impact both the location and extent of mitochondrial superoxide production ,13. Ther2Ecsit-knockout bone marrow derived macrophages (BMDMs) have an increased baseline mtROS but do not demonstrate an LPS-induced increase in mtROS production . Th. Th+/NAD4Succinate accumulation and subsequent oxidation is associated with RET and ROS production at complex I . SuccinaoF1-ATP synthase [A high Δp also promotes mitochondrial superoxide production and it has been shown that LPS activation leads to an increased mitochondrial membrane potential (the major component of the Δp) ,19. Decrsynthase . MetaboloF1-ATP synthase activity and a high Δp have been shown to enhance mtROS production by RET at complex I in ischemia/reperfusion injury [oF1-ATP synthase activity by the activation of glycolysis , will be able to provide a clearer picture of the mechanism of generation of LPS-induced superoxide [As is evident from the contradictory interpretations of the studies described, it can be difficult to distinguish between complex I and complex III as the sites of superoxide production because interference using inhibitors or experimental conditions that inhibit complex III superoxide production often also impact RET at complex I. The use of genetic models that are unable to produce superoxide by RET, such as is the case with the peroxide –28.It is also important to consider the time frame of the experimental design of these studies when interpreting the results. As we have outlined above, changes in metabolism and altered mitochondrial function significantly impact superoxide production. What we have not yet emphasised is that LPS activation results in highly dynamic changes in macrophage metabolism and mitochondrial properties. Therefore, it is critical to consider the length of exposure to LPS and the corresponding metabolic state of the TLR4-activated macrophage when interpreting these results.6It is clear that the metabolic state of LPS-activated macrophages has a significant impact on mitochondrial superoxide production, and proinflammatory macrophages undergo highly dynamic metabolic reprogramming. Seim et al.  describeDue to these dynamic changes, we draw particular attention to the time frames used in the above studies. Mills et al.  used a 3Another caveat of these studies is that many of them use pretreatment with inhibitors that alter cellular metabolism that could lead to metabolic rewiring prior to LPS-induced metabolic reprogramming. This type of experimental design has different implications and mechanisms than being able to block superoxide production downstream of TLR4 signalling. An additional example of this type of experimental design is seen in a recent paper which investigates the role of mitochondria in NLRP3 inflammasome activation. This paper argues that ETC-derived ROS are not required for NLRP3 inflammasome activation but rather ETC inhibitors reduce phosphocreatine (PCr)-dependent generation of ATP which is necessary for inflammasome activation . ActivatThese studies demonstrate that our understanding of the dynamic nature and influence of mitochondrial metabolism and mitochondrial properties on superoxide production is fundamental to the study of superoxide production in pro-inflammatory macrophages. An outline of the time dependent metabolic changes in parallel with a study of LPS-induced superoxide production in macrophages is a fundamental gap which must be filled in this field.7Elucidating how mitochondrial superoxide generation is influenced by metabolism, will no doubt provide insights into the role of mitochondrial derived superoxide in macrophage effector functions. Before it was appreciated that mitochondria produced ROS in pro-inflammatory macrophages it was evident that macrophages used reactive species as antibacterial agents . We now Here, we have highlighted how metabolism influences the production of LPS-induced mtROS. However, as well as driving mtROS production, metabolites can also act as effector molecules in innate immunity. Therefore, it will be interesting to study mtROS production in the context of immunometabolite signalling. A clear example of the interplay between mtROS and metabolite signalling is found in succinate dependent promotion of IL-1β production in pro-inflammatory macrophages. Succinate stabilises HIF-1α, which promotes IL-1β production, both by directly inhibiting prolyl hydroxylase (PHD) and by promoting mtROS production by RET which also inhibit PHD activity ,18. SuccFinally, we would also like to highlight that generation of mtROS in pro-inflammatory macrophages is associated with many pathologies and biomedically important processes. For example, mtROS are important in the early stages of wound healing for pro-angiogenic wound macrophage function  while in8Here we have outlined that the metabolic state of macrophages strongly influences mtROS production and put forward suggestions about how this can lead us to define the source of mtROS production in TLR4-stimulated macrophages. We have described how the conditions induced by TLR4 signalling promote superoxide production by RET at complex I . In futuWe highlight that our understanding of the dynamic nature of metabolic reprogramming is important so outlining a clear model and time course of metabolic change in the context of mtROS is critical. Another consideration is that many studies investigating mtROS use non-specific probes for cellular ROS as a proxy measurement. It is crucial to directly measure mtROS and to define the particular species being studied . We alsoACAD9Acyl-CoA dehydrogenase family member 9AOXalternative oxidaseATPadenosine triphosphateBMDMbone marrow derived macrophageCD80cluster of differentiation 80CoQCoenzyme QDAMPdanger associated molecular patternhΔEreduction potentialΔpproton motive forceDMMdimethyl malonateDMSDimethyl succinateECSITevolutionarily conserved signalling intermediate in Toll pathwayETCelectron transport chainFMNFlavin mononucleotideHIF-1αHypoxia inducible factor 1 subunit alphaIFN-γinterferon-γIL-1βinterleukin-1βIL-6interleukin-6LPSlipopolysaccharideMCIAcomplex mitochondrial complex I assembly complexMHCmajor histocompatibility complexmtROSmitochondrial reactive oxygen speciesNADHdihydronicotinamide adenine dinucleotideNADPHnicotinamide adenine dinucleotide phosphateND6NADH dehydrogenase 6NDUFAF1NLRP3NOD-, LRR- and pyrin domain-containing protein 3NOS2nitric oxide synthase 2OXPHOSoxidative phosphorylationPAMPpathogen associated molecular patternPCrPhosphocreatinePDHprolyl hydroxylaseRETreverse electron transportROSreactive oxygen speciesSCNR1succinate repector 1SDHsuccinate dehydrogenaseTCAtricarboxcylic acid cycleTLRToll-like receptorTNFtumor necrosis factorTRAFtumor necrosis factor receptor-associated factor


In the cell nuclei, various types of nuclear domains assemble as a result of transcriptional activity at specific chromosomal loci. Giant transcriptionally active lampbrush chromosomes, which form in oocyte nuclei of amphibians and birds enable the mapping of genomic sequences with high resolution and the visualization of individual transcription units. This makes avian and amphibian oocyte nuclei an advantageous model for studying locus-specific nuclear domains. We developed two strategies for identification and comprehensive analysis of the genomic loci involved in nuclear domain formation on lampbrush chromosomes. The first approach was based on the sequential FISH-mapping of BAC clones containing genomic DNA fragments with a known chromosomal position close to the locus of a nuclear domain. The second approach involved mechanical microdissection of the chromosomal region adjacent to the nuclear domain followed by the generation of FISH-probes and DNA sequencing. Furthermore, deciphering the DNA sequences from the dissected material by high throughput sequencing technologies and their mapping to the reference genome helps to identify the genomic region responsible for the formation of the nuclear domain. For those nuclear domains structured by nascent transcripts, identification of genomic loci of their formation is a crucial step in the identification of scaffold RNAs. According to modern knowledge on the mechanisms which underlie the formation of nuclear bodies, the assembly of certain nuclear domains is nucleated by RNA at the transcription loci ,2. FurthA nucleolus forming around transcribing clusters of ribosomal RNA genes is a vivid example of a ubiquitous locus-specific nuclear domain. However, recent studies prove that the maintenance of nucleolus integrity requires non-ribosomal RNA polymerase II transcripts . AnotherCoilin-containing nuclear bodies represent another type of nuclear domain with locus-specific localization. Coilin-containing nuclear bodies form in close association with the transcription units of RNA species requiring specific processing machinery , although they are not structured by the nascent transcripts themselves .The giant lampbrush chromosomes represent transcriptionally active meiotic half-bivalents forming at the diplotene stage of meiosis in oocytes of non-mammalian species; lampbrush chromosomes are the most well-studied in amphibians and birds ,19. SimiThe centromere protein bodies represent spherical bodies attached to the centromere regions of lampbrush chromosomes and evidently belong to meiosis-specific nuclear domains. Centromere protein bodies lack components of the RNA-processing machinery and accumulate chromosome architectural proteins: DNA topoisomerase II  and coheAnother group of locus-specific domains on lampbrush chromosomes combines RNP-rich non-spherical structures forming in association with specific transcription units. Immunofluorescence and 3D RNA FISH on isolated oocyte nuclei revealed that certain lampbrush lateral loops or loci-specific RNP aggregates manifest as nuclear domains since they accumulate specific RNA-binding proteins and RNA species as opposed to the nucleoplasm . For exaSeveral genome-wide approaches for identification of genomic loci proximal to nuclear domains were recently developed for interphase nuclei. These approaches were used to study the 3D genomic environment of nuclear speckles ,43,44, nRecently, we developed two strategies for analyzing the loci of nuclear domain formation on giant lampbrush chromosomes. The first approach was based on sequential FISH mapping of BAC clones containing genomic DNA fragments with a known position in the genome and located close to the site of the formation of a nuclear domain or marker structure in order to narrow the area of subsequent bioinformatics search and analysis of genomic loci a. This aThe second suggested approach was based on mechanical microdissection of chromosome regions adjacent to a particular nuclear structure, followed by in vitro amplification of DNA from the dissected material, FISH-mapping and high throughput sequencing of the obtained DNA samples b. We demSubsequently, deciphering the DNA sequence from the dissected material using the next generation sequencing technologies and mapping of sequenced DNA fragments to the reference genome allows for the identification of genomic loci occupying 1.5–5 Mb ,50. One It is important to emphasize that the use of such an integrated approach will accurately determine the genomic position of the nuclear domain formation, and then analyze its genomic and epigenetic characteristics. Moreover, great efforts should be given to the subsequent bioinformatics and functional analysis of the established genomic loci followed by identification of the transcripts involved in nuclear domain formation. At the moment, application of the aforementioned approaches is restricted to species with a lampbrush stage during oogenesis. However, in prospect, these approaches can be extended to mammalian species with artificial induction of lampbrush chromosomes formation using sperm head injection into the amphibian oocyte nucleus .


OTOF gene encodes otoferlin, a critical protein at the synapse of auditory sensory cells, the inner hair cells (IHCs). In the absence of otoferlin, signal transmission of IHCs fails due to impaired release of synaptic vesicles at the IHC synapse. Biallelic pathogenic and likely pathogenic variants in OTOF predominantly cause autosomal recessive profound prelingual deafness, DFNB9. Due to the isolated defect of synaptic transmission and initially preserved otoacoustic emissions (OAEs), the clinical characteristics have been termed “auditory synaptopathy”. We review the broad phenotypic spectrum reported in patients with variants in OTOF that includes milder hearing loss, as well as progressive and temperature-sensitive hearing loss. We highlight several challenges that must be addressed for rapid clinical and genetic diagnosis. Importantly, we call for changes in newborn hearing screening protocols, since OAE tests fail to diagnose deafness in this case. Continued research appears to be needed to complete otoferlin isoform expression characterization to enhance genetic diagnostics. This timely review is meant to sensitize the field to clinical characteristics of DFNB9 and current limitations in preparation for clinical trials for OTOF gene therapies that are projected to start in 2021.The  As mostentified , high-thOTOF (OMIM: 603681), encoding a transmembrane (TM) protein called otoferlin, was mapped to the DFNB9 locus and identified as causing prelingual autosomal recessive, non-syndromic deafness [OTOF cause auditory synaptopathy due to deficient pre-synaptic neurotransmitter release at the ribbon synapse of the inner hair cells (IHCs) [Using a candidate gene approach, the DFNB9 locus (OMIM: 601071) was mapped to chromosome 2p23.1 in 1996 by studying a genetically isolated family from Lebanon [deafness . Biallels (IHCs) .OTOF have been identified. In addition to an expanded understanding of the types of variants in otoferlin that cause deafness, the structure and function of otoferlin have been extensively characterized through functional studies that have greatly informed experimental therapies. This review covers the challenges of clinically diagnosing OTOF-associated hearing impairment, the spectrum of phenotypes that have been observed in patients with OTOF variants and a current review of genotype-phenotype correlations.Since its initial identification, about 220 pathogenic and likely pathogenic variants in Otof-knock-out mouse models revealed that, in the absence of otoferlin from IHCs, very few neurotransmitter-filled synaptic vesicles fuse with the plasma membrane [2+ sensor for exocytosis [2+-binding site revealed a slight delay and slowing down of Ca2+-triggered exocytosis, which would be in line with a Ca2+-dependent acceleration of exocytosis and was interpreted as a Ca2+ sensor function for otoferlin in exocytosis and vesicle replenishment [2+-binding capability of the site targeted in this study is still under debate  stimuli, but strongly impaired the synaptic transmission for longer stimuli [Notably, mouse models with reduced levels of otoferlin revealed additional functions for the protein at the synapse: In these models, Ca of IHCs ,13. A re stimuli ,13. This stimuli ,14, as tA milder reduction to 35% of wild-type otoferlin levels in the plasma membrane of a mouse model for the human p.Ile515Thr substitution halved the rate of vesicle replenishment compared to normal hearing controls . This onOTOF has been expanded since its identification to include long and short isoforms that make use of distinctive transcription and translational start sites, as well as alternative splicing of exons 6, 31, and 47. The short and long isoforms range from 28 exons spanning 21 kb [2 domains and a C-terminal transmembrane (TM) domain, whereas the short isoforms are comprised of only the final three C2 domains and the TM domain [2 domains are globular domains composed of antiparallel β-sheets, which are known for Ca2+ and phospholipid binding. In humans, the short isoforms are comprised of isoform b (NP_004793) and d (NP_919304), each with 1230 amino acids and isoform c (NP_919303), with 1307 amino acids, employing an alternate starting exon, compared to the long isoforms a (NP_919224) and e (NP_001274418), which both encode 1997 amino acids.The structural diversity of ng 21 kb , respectM domain . C2 domaWith respect to a potential functional role of the short isoforms, a review of pathogenic and likely pathogenic variants has shown no indication that variants only affecting the long, but not short, isoforms would cause a milder phenotype. This confirms that the long isoform is critically required for normal hearing function .The two long isoforms of otoferlin can be distinguished by virtue of tissue mRNA expression and subtle differences in exon usage at the 3′ end of the gene. Isoform a was identified from brain cDNA libraries with a termination codon in exon 47 . An alteOTOF sequence analysis utilizes the reference sequence for variant e, NM_001287489, encoding the 1997 amino acid protein, NP_001274418. Furthermore, we propose that OTOF variants from human molecular genetic diagnostic laboratories that are deposited in clinical variant repositories be adjusted to this reference sequence.Limitations in obtaining mRNA from human IHCs has presented a major bottleneck in profiling and quantifying the relative fractions of all otoferlin isoforms. According to Yasunaga et al. , an alteOTOF-associated hearing loss in humans has presented several challenges, making the selection of clinical diagnostic protocols an essential undertaking for an early diagnosis. Based on the finding that OTOF variants disrupt presynaptic function in IHCs rather than neuronal function, a change in terminology from “auditory neuropathy” to “auditory synaptopathy” has been adopted to more precisely describe this. A lesion to the neural pathway that transmits signals from the cochlea to the brain is clinically characterized by an absence of ABRs and the presence of otoacoustic emissions (OAEs). The testing of OAEs indicates proper functioning of cochlear amplification by the OHCs. As OHCs and IHCs employ the same protein machinery for mechanotransduction at their stereocilia bundle, any malfunction of this can be excluded if OAEs are present. Similarly, both hair cell types depend on proper endolymph composition and endocochlear potential as the driving force; a functional deficiency which would be detectable in altered OAE recordings. However, patients with OTOF variants lose OHC function, occasionally within the first year, and in about one-third of cases in the second year of life, with only few individuals displaying OAEs in early adulthood [OTOF.Since its discovery, dulthood ,21,22. TOTOF variants, behavioral audiometry, with or without visual reinforcement, can indicate severe to profound hearing loss across all frequencies. While some patients display residual hearing in the low-frequency region (with thresholds of ~75 dB hearing level (HL) for 250 Hz; e.g., [As is true for all forms of auditory neuropathy or synaptopathy, newborn hearing screening that tests for OAEs, e.g., with distortion product otoacoustic emissions (DPOAEs) or transient evoked otoacoustic emissions (TEOAEs), fail to detect a hearing disorder in most cases, as OAEs are initially present. Passing OAE tests despite profound deafness can be misleading and, in the worst-case scenario, prevent parents and pediatricians from pursuing a more complete audiological diagnostic testing. ABRs in patients with synaptopathies are typically absent, even for high sound pressure levels, making them well-suited for the detection of profound deafness. Moreover, even mild forms of hearing loss result in abnormal ABRs in case of DFNB9 (see below). However, as ABR testing is a more time-consuming procedure, this is not routinely applied in newborn hearing screening protocols, delaying the diagnosis of a baby with congenital auditory synaptopathy by months or even years until it is recognized and confirmed. In children with z; e.g., ), pure tOTOF variants is of relevance, especially for young children whose speech acquisition may become strongly impaired. Moreover, a precise diagnosis will also help later in life to specify impairments of speech comprehension, which, for example, may explain why following multiple speakers is much more exhausting for DFNB9 listeners than for normal hearing listeners. Despite pure tone audiograms being only mildly or moderately affected in such cases, ABRs are mostly abnormal, indicating higher thresholds than expected from psychophysical testing. ABR waves I to III are hardly detectable and waves IV and V are delayed [A reliable diagnosis of even mild forms of hearing loss caused by  delayed . Speech A more specific test for this type of synaptopathy would be to quantify the time required for synaptic regeneration. This could be done by gap detection tests, i.e., silent gaps of different length in broadband noise. Intact IHC synapses accurately detect the onset of the white noise after a gap as short as 2–4 ms in humans, at least after some training . This deOTOF mutations. Other tests do not provide additional information as, for example, even at high sound pressure levels (SPLs), no auditory reflexes can be elicited, which confirms the absence of auditory evoked signal transmission indicated by absent signals in ABRs. In only a few cases, transtympanic electrocochleography (ECochG), with a recording electrode placed at the promontory wall, will be of use for diagnoses. However, since it requires local anesthesia of the tympanic membrane and is rather invasive, it is questionable if this justifies the limited additional information. ECochG is employed to record the summating potential (SP), cochlear microphonics and compound action potentials (CAPs). Cochlear microphonics originate from functional OHCs such that this recording would be redundant to OAE tests, although amplitudes of cochlear microphonics can be highly variable [The combination OAE recordings and ABR or pure tone audiometry are, in principle, sufficient to diagnose hearing impairment due to variable ,28.Recording the SP in response to click stimuli may add novel information in particular cases when OAEs are absent, but might be hard to interpret. Since the SP derives from the depolarization of inner and outer hair cells , the deppachanga mouse model (p.Asp1772Gly) can likely explain this observation: The IHCs in this animal model display intact synaptic signal transmission for short (<10 ms) interspaced stimuli, given that the interstimulus intervals allow for sufficient recovery [pachanga mice reached up to 200 spikes/second (compared to >400 spikes/second in wild-type mice), but only when stimuli were presented once every two seconds (0.5 Hz stimulus frequency) [CAPs that record the first action potential in the auditory pathway are absent in some DFNB9 patients, while others exhibit a prolonged CAP with reduced amplitude, at least for single click stimuli . Repetitrecovery . Under requency) . Increasequency) ,13. ThusOTOF gene. Two frameshift variants were associated with absent CAPs in two patients [pachanga mice, it is tempting to speculate that an OTOF gene with premature stop codons described in this study may have undergone partial natural stop codon read-through, inducing residual synaptic function of an order of magnitude as in pachanga mice.However, why is the CAP response absent in some DFNB9 patients, or prolonged and with a small amplitude in others? This question arose in a study that analyzed CAP responses in patients with various types of variants in the patients . Individpatients ). As onlOTOF has been tested in molecular genetic diagnostic settings for over two decades, allowing an estimate of the global burden of OTOF-associated hearing loss. There are presently 219 genetic changes that are classified as pathogenic or likely pathogenic according to the literature or clinical database entries (Leiden Open Variation Database v3.0 (LOVD v3), the Deafness Variation Database (DVD), ClinVar, and the Human Gene Mutation Database (HGMD)) ) . This in (HGMD)) .OTOF-associated hearing loss varies according to population background. For example, OTOF variants account for approximately 5% of genetic diagnoses in the Turkish population [OTOF has been identified as a cause of hearing impairment in 3.1% of Taiwanese [OTOF is not a major contributor to hearing loss in the Iranian population [The prevalence of pulation , and 3.1pulation . A commopulation ,33. In oaiwanese , 2.4% ), and a limited number of suspected cases in a few other genes such as GJB2 [GJB2 cases are controversially discussed [OTOF screening in patients for genetic testing rather successful. As exemplified by a study that included Japanese patients with auditory neuropathy/synaptopathy, biallelic OTOF variants were uncovered in 56% of cases that included the identification of a founder variant (p.Arg1939Gln) [OTOF gene in 37 Chinese patients with congenital auditory neuropathy/synaptopathy had a diagnostic yield of 41.2% [Auditory synaptopathy with prelingual onset has been identified in patients with genetic aberrations in a small subset of genes  . The p.G1939Gln) . Another1939Gln) . A studyof 41.2% . On the of 41.2% .OTOF remain undiagnosed after molecular genetic screening. Such reasons include possible limitations stemming from methodology , missed copy number variations that either fall below the detection resolution of commonly used microarrays in genetic diagnostics or missed due to uneven high-throughput sequencing coverage, especially in the case of exome sequencing, or deep intronic variants that are not captured in targeted enrichment approaches. Furthermore, variant interpretation bottlenecks that could also be due to incorrect transcript usage in variant annotation, current limitations in knowledge about the pathogenicity of rare variants and lack of opportunity for segregation testing in families that can complicate outcomes for definitive statements about variant pathogenicity. Another hypothesis points to variants occurring in currently unannotated exons.The diagnostic yield of patients with audiological hallmarks of DFNB9 suggests multifaceted deficits in general isoform and variant knowledge, as well as possible technical limitations. Beyond the possibility of additional genes harboring causally associated variants that evoke the same clinical features, there are several reasons explaining why patients with auditory synaptopathy due to biallelic variants in Otof, by mapping a novel non-coding exon 6b and suggesting an in-frame exon 10b . The cochlea is encased in one of the hardest bones of the body, making it one of the least accessible tissues for transcriptome studies. However, many microarray and RNA-seq-based studies using the human and rodent whole cochlea have ensued since the early 2000s ,51. Thouexon 10b . ExtendiOTOF variants cause congenital or early onset (n = 114) hearing impairment. Few variants have been identified with progressive hearing loss (n = 3). Seven variants have been linked to temperature-sensitive hearing loss, five of which are located within C2 domains. While premature stop and frameshift variants typically cause profound prelingual deafness, non-truncating variants can cause a highly variable phenotype. Depending on the localization and the physico-chemical properties of the substituted (or deleted) amino acid residues, variants can severely affect protein stability and contribute to protein degradation. In some cases, the deterioration of protein folding is less severe, leaving some endogenous otoferlin at the plasma membrane that may vary with age and body temperature. This typically results in mildly to moderately elevated thresholds in pure tone audiograms but severely impaired speech comprehension. Notably, patients with point mutations and residual otoferlin expression report perceiving a fading out of a tone burst presented with constant intensity [The uniformity of available clinical and genetic information about the current set of identified variants is highly variable. For example, reported variant zygosity  and the extent of audiological characterization and recorded onset in patients are highly heterogeneous. Most variants lack recorded audiological information. Generally, biallelic ntensity ,53. ThesTemperature-sensitive auditory synaptopathy has been reported by parents observing profound deafness as soon as their children are febrile. Mirroring daytime changes in body temperature, fluctuations in speech comprehension have been described, which was least affected in the early morning and progressed throughout the day to a point where vocal communication is hardly possible . Even a 2C domain reduces the likelihood of proper refolding. This interpretation would be in concordance with the observation that patients regain hearing a few hours after temperature-induced deafening, which would be consistent with the time required for de novo synthesis of sufficient quantities of otoferlin.When measured in febrile conditions, both an elevation in pure tone thresholds and zero speech comprehension can confirm the diagnosis of temperature-sensitive auditory synaptopathy. The first variant discovered causing temperature-sensitive auditory synaptopathy, p.Ile515Thr , has bee2C domain of otoferlin [2E domain [2D domain [2F domain, was also attributed to temperature-dependent hearing loss [OTOF have been associated with temperature-sensitive forms of hearing loss and all cases presenting a similar phenotype in the literature have disclosed pathogenic OTOF variants, regardless of population background. All described substitutions seem to cause only slight destabilizations of one C2 domain. However, since mutations in different otoferlin C2 domains cause a similar phenotype, we consider it unlikely that each of the substitutions causes heat-sensitivity of the protein. Rather, as shown in Strenzke et al. [A similar phenotype to the p.Ile515Thr variant was described in humans with the p.Gly541Ser variant, which also localizes to the Ctoferlin ,46. In aE domain ,49 and fD domain . RemarkaD domain . An in-fing loss . Notablye et al. , even thOTOF hearing impairment have been described for three variants: p.Ile1573Thr, p.Glu1700Gln and p.Ter1998Argext30Ter [Progressive forms of ext30Ter ,47,57. I2E and the C2F domains, in which this substitution lies, has not been studied so far.The homozygous p.Glu1700Gln substitution was identified in several Taiwanese families . In pati2E domain likely reduces the stability of protein folding. The four children of this family were found to have mild (9 years of age), moderate  or severe hearing loss (17 y). All children displayed OAEs. Absence of ABR waves in the 9-year-old child (the only one tested) is in concordance with the severe abnormality described for all DFNB9 patients, even those with only mildly elevated hearing thresholds. A follow-up of the progression of hearing impairment of this family has not been performed so far.A homozygous p.Ile1573Thr substitution was identified in a child with parental consanguinity, in whom hearing deterioration correlated with age [A stop loss variant p.Ter1998Argext30Ter associated with progressive hearing impairment was found in compound heterozygosity with the p.Arg1939Gln substitution . Since tIn summary, progression of hearing impairment was typically observed over the course of a few months or years, such that affected individuals reached profound deafness in the second decade of life. Presumably due to the residual otoferlin function, OAEs remained preserved in these intermediate forms of hearing impairment; thus, affected individuals may be candidates for gene therapies even in adulthood.2, FerA and TM domains, meriting a broader discussion about domain functions and deteriorating effects due to substitutions. C2 domains are globular domains comprised of eight antiparallel β-strands, many of which bind phospholipids and Ca2+. Since the Ca2+-binding site is localized in the structure to five specific aspartate residues in two top loops, the Ca2+-binding ability can be reasonably predicted from the sequence. With respect to the C2A domain, the structure of the rat protein, which is 91% identical and 96% similar to the human otoferlin C2A domain, has been solved with X-ray crystallography [2A domain was predicted not to bind Ca2+, which was confirmed experimentally [Many of the non-truncating variants affect the Clography . Since omentally ,59,60.2 domains, neither amino acid replacements in the β-strands nor in the loops of the C2A domain cause malfunction of the protein. The reasons for this might be first, that the C2A domain folds much more stably than the other C2 domains. Crystallization from heterologous expression has been successful for the C2A domain. However, despite laborious efforts from several research groups, this has not been the case for other C2 domains so far, presumably because higher protein dynamics prevent the forming of crystals. Notably, the same seems to be true for the myoferlin and dysferlin C2 domains, of which only the structures of the C2A domains could be resolved to date [2B-C2F domains is a biological defect or a feature relevant for proper function remains to be determined. The second reason why substitutions may be tolerated well in the C2A domain is that this domain does not bind Ca2+ or phospholipids [2+-triggered vesicle fusion or Ca2+-dependent vesicle replenishment.Different from substitutions in the other otoferlin C to date . Whetherholipids ,59,60 an2+-binding sites or the location of pathogenic substitutions in the other C2 domains is rather challenging due to the low sequence similarity of the otoferlin C2B to C2F domains to C2 domains with known structure. Automatic domain annotation algorithms such as SMART  [2E domain and the 7th β-strand of the C2F domain, all β-strands could be localized in the predictions. The first top loop connecting β-strands 1 and 2 and the third top loop between β-strand 5 and 6 comprise five aspartate residues (blue fonts) that coordinate one to three Ca2+ ions. Consistent with experimental data revealing that the C2A domain does not bind Ca2+, its first top loop misses the motif containing the first aspartate, and, in the third top loop, the three aspartate sites are replaced by neutral or positively charged amino acids. Similarly, the C2B domain comprises only one aspartate residue in the top loops, indicating that this C2 domain cannot bind Ca2+. Consistent with this prediction, one lab found no Ca2+ binding for the C2B domain using microscale thermophoresis assays [2+ binding with other tests   do not pGermany)  .2C domains, for which some labs found Ca2+ and phospholipid binding, while one other lab found that this domain binds Ca2+ only after including a phosphomimetic mutation in the first top loop  and a confirmed (PKCα) α-helical region. The PKCα C2 domain does bind phospholipids, but not Ca2+. For the otoferlin C2C domain, one aspartate resides in the first top loop and two aspartates to a short top loop three, allowing no clear prediction whether this domain can bind Ca2+. We presume that the Ca2+ binding of this domain likely depends on posttranslational modifications such as phosphorylation and the direct domain environment, which could be phospholipid membranes, interacting proteins, or both. In a mouse model in which two aspartate residues in the C2C domain were replaced by alanine residues, exocytosis appeared to be slightly slowed [2+-binding ability of this domain, but also with interfered phospholipid binding due to altered domain folding.The same is true for the Crylation ). The acy slowed . This fi2D and C2E domains exhibit the five canonical aspartate residues at respective positions in the top loops, and experimental data confirm that both domains bind Ca2+ and phospholipids [2E domain, the precise localization of the last two β-strands could not be predicted with the algorithm and the current dataset of structures. Since a growing number of structures is solved and deposited in databases, future structure predictions might result in a reasonable model of the position of the two β-strands. Pathogenic single amino acid substitutions in these domains typically lie within β-strands  and two in the third top loop (p.Asp1834Asn and p.Asp1842Asn) are each pathogenic. Accordingly, Ca2+ co-ordination seems plausible and has experimentally been confirmed [2+ affinity is strongly reduced by these substitutions, indicating that Ca2+ binding to the C2F domain is essential for proper function.The first top loop comprises eight negatively charged amino acid residues that could potentially contribute to Caonfirmed ,60, desp2 domains, where only two amino acids form the bottom loop between β-strands 2 and 3, the loop in the C2F domain is predicted to be longer and consists of hydrophobic tryptophane residues flanked by positively charged side chains. This loop comprises the p.Asp1772Gly mutation found in pachanga mice which strongly reduced plasma membrane association of otoferlin [2F domains [2F domain is especially sensitive to point mutations and that Ca2+ and phospholipid binding are crucial for proper protein function.Different from the other otoferlin Ctoferlin ,13,14. T domains , seems t domains . The sub2+. Four non-truncating substitutions have been identified in the FerA domain so far, but three of those could not be linked to a phenotype . The fourth homozygous substitution found in a Taiwanese family alters the second helix (p.Leu760Pro). This suggests that misfolding of the FerA domain is not tolerated, indicating a role for the FerA domain for synaptic transmission that requires further studies.The function of the FerA domain for synaptic transmission is presently less clear. Small-angle X-ray scattering and in vitro experiments indicated that this domain is comprised of four α-helices, which are connected by a dynamic linker region . The Fer2F domain and before the TM domain, such as p.Gln1883Ter or the c.5833delA deletion (p.Ile1945Serfs*4), cause profound deafness, indicating that the TM domain is essential for protein function [Substitutions of amino acids in the TM domain cause variable severities of hearing loss. The homozygous p.Pro1987Arg substitution causes early onset, severe to profound hearing impairment, in this specific case, with a bowl-shaped audiogram . This isfunction .OTOF pass newborn hearing testing because, in most countries, the assessment of OAEs is the method of choice for screening. These children are typically diagnosed at a later stage after parents report a severe delay in speech development. Knowing that deafness, either due to biallelic variants in OTOF or auditory neuropathies/synaptopathies of other etiologies, cannot be reliably diagnosed with OAE screenings, but could be aided with currently available therapies, requires switching newborn hearing screenings to routine ABR testing. This is not only of importance with respect to cochlear implantation, which will yield much better outcomes if implanted earlier, but also with respect to a gene therapy, which is currently under development.The established therapy for individuals with severe to profound hearing loss due to otoferlin deficiency is currently cochlear implantation. Since this prosthetic bridges the first auditory synapse, which is the only part of the auditory pathway involved in DFNB9, patients benefit well from these devices and gain good or even excellent speech understanding. However, the most sensitive period for developing the capability to understand spoken language is within the first two years of life. It is, therefore, critical to implant patients as early as possible. This requires an early diagnosis, but most children with severe to profound hearing loss due to variants in Otof−/− mice have revealed that such dual-AAV strategies successfully and persistently restored hearing [The currently favored gene therapeutic approach involves replacing the defective gene by transducing IHCs with correct cDNA by means of recombinant adeno-associated viruses . These  hearing ,71. At lEspecially with respect to the envisioned gene therapy, the use of hearing aids for rehabilitation of severe to profound hearing impairment should be critically evaluated. While power hearing aids have successfully induced behavioral responses in DFNB9 children with severe to profound deafness , we haveIn addition to being questionable for language acquisition, the use of power hearing aids might accelerate the loss of OHCs, as proposed from observations in retrospective studies ,72,73. WOTOF hearing impairment should be made as early as possible. Ideally, a clinical diagnosis should occur within the first few days of life if already apparent at birth, with rapid molecular genetic diagnostic results thereafter. Therefore, changes in newborn hearing screening protocols from OAEs to ABRs, or a combination of the two will support an early diagnosis. This will become increasingly important as promising gene therapies emerge. The structure of otoferlin, particularly of the C2E and C2F domains, is provisionally incomplete based on structural modelling. The possibility of an incomplete overall structure is supported by the identification of novel exons in mouse IHC transcriptome data. Therefore, we recommend genetic re-testing of undiagnosed individuals, especially those with auditory neuropathy/synaptopathy to profit from advances in basic knowledge of isoform structure, as well as improvements in sequencing technologies, bioinformatics approaches, and variant interpretation. Diagnostic laboratories critically rely on annotation of variants to the correct transcript in databases such as LOVD, DVD, ClinVar, and HGMD. In many instances in current versions of these databases, the transcript that is used is incorrect. Therefore, careful attention must be exercised by medical geneticists to report variants with the correct transcript until this can be revised.A timely clinical and molecular genetic diagnosis of


A review of programmed cell death and its morphotypes in cyanobacteria, describing the functionality of orthocaspases based on distribution, domain architecture, mutations, and phylogeny, and their evolutionary and ecological significance. in silico approaches. We also review the evolutionary and ecological significance of PCD in cyanobacteria. In the future, the analysis of cyanobacterial PCD will identify novel proteins that have varied functional roles in signalling cascades and also help in understanding the incipient mechanism of PCD morphotype(s) from where eukaryotic PCD might have originated.Programmed cell death (PCD), a genetically orchestrated mechanism of cellular demise, is paradoxically required to support life. As in lower eukaryotes and bacteria, PCD in cyanobacteria is poorly appreciated, despite recent biochemical and molecular evidence that supports its existence. Cyanobacterial PCD is an altruistic reaction to stressful conditions that significantly enhances genetic diversity and inclusive fitness of the population. Recent bioinformatic analysis has revealed an abundance of death-related proteases, i.e. orthocaspases (OCAs) and their mutated variants, in cyanobacteria, with the larger genomes of morphologically complex strains harbouring most of them. Sequence analysis has depicted crucial accessory domains along with the proteolytic p20-like sub-domain in OCAs, predicting their functional versatility. However, the cascades involved in sensing death signals, their transduction, and the downstream expression and activation of OCAs remain to be elucidated. Here, we provide a comprehensive description of the attempts to identify mechanisms of PCD and the existence and importance of OCAs based on  The concept of cell death has been known to researchers for a long time from its physiological or pathological consequences. With the turn of century, the involvement of RNAs and proteins in cell demise mechanisms became clear as inhibition of transcription and translation was found to suppress cell death . On the Today, the understanding of PCD in metazoans has reached a new height where the meaning of PCD has been broadened to subsume all the gene-dependent cell death mechanisms. This phenomenon of orchestrated cell demise is required by multicellular life forms for the sculpting of organs  treatment  in cyanobacteria  or lysine (Lys) instead of aspartate (Asp) at the P1 position. Recently, the caspase homologue MaOC1 in M. aeruginosa PCC 7806 was characterized as an orthocaspase that is activated by calcium-independent autocatalysis at Arg219, separating a 55 kDa catalytic subunit, and it displayed high catalytic efficacy for z-RR-AMC substrate  and release of proteins from the mitochondrial intermembrane space , entosis , ferroptosis , parthanatos (involving early activation of poly [ADP-ribose] polymerase 1), pyroptosis (with death dependent on caspase-1 and associated with a pyrogenic mediator like IL-1β and IL-18), NETosis (reactive oxygen species (ROS)-dependent cell death in neutrophils, associated with extrusion of neutrophil extracellular traps), and cornification .Extrinsic apoptosis is defined as a caspase-dependent process and it requires death receptor signalling, differentiating it from an intrinsic counterpart that depends on mitochondrial outer membrane permeabilization. Hence, intrinsic apoptosis is associated with dissipation of the mitochondrial transmembrane potential  induction, along with enhanced caspase-like activity  and animals (caspases) to cleave a phylogenetically conserved substrate, Tudor staphylococcal nuclease, argued for a common origin of PCD in plants and animals : C14A (caspases)   and metaaspases) . TherefoMoreover, domain configurations also displayed characteristic variabilities between MCAs and PCAs, and further divided them into three and two subgroups, respectively. PCAs lack a p10-like sub-domain but the prodomain is characterized by death and immunoglobin (Ig) domains .In silico studies of caspase homologues in bacterial phyla showed wide and scattered distribution, with an abundance among the members of the actinomycetes, α-, β-, and γ-proteobacteria, and cyanobacteria  to filamentous  cyanobacteria  showed the distribution of 98 p20-like sub-domain-containing proteins (representing OCAs) among 33% of these strains (29 strains). Among these 98 OCAs, about 44% were pseudo-variants, having a mutated active site (HC dyad)  . Furtherectively . It was ectively , B. The Synechococcus sp. JA-3-3Ab and Synechococcus sp. JA-2-3B′a(2–13), p20-like sub-domain-containing protein from Synechococcus sp. PCC 7942 , colonies (M. aeruginosa NIES-843), or filaments, in which interdependency among individual cells resulted in a synchronized activity transforming them into a single unit. In such a situation the presence of true OCA activity seemed to induce altruistic adaptation whenever the population was subjected to harsh conditions.The loss of OCA genes from the majority of these unicellular strains perhaps occurred during the course of evolution as these genes might not have conferred significant selective advantages to their lifestyle . HoweverNostoc azollae 0708, N. punctiforme PCC 73102, and A. marina MBIC 11017. While N. azollae 0708 and A. marina MBIC 11017 have only mutated and wild-type OCAs, respectively, N. punctiforme PCC 73102 harbours both of them  and PHMMER (https://www.ebi.ac.uk/Tools/hmmer/search/phmmer) exhibited 24 unique Pfam domains along with the p20-like sub-domain (peptidase C14) (see JXB online) and a transmembrane domain. These additional domains associated with OCAs are involved in protein–protein interactions, protein modification, signalling, or PCD, or act as scaffold protein or chaperonins, whereas some domains have helicase and NTPase activity as well  and WD40, except Ava_2183 and Npun_F0844, which had NACHT and PLN02742 domains, respectively . The disConsidering the occurrence of different domain types among OCAs, but disregarding successive repeats in a single protein, three domains, i.e. WD40 (9%), AAA_16 (6%), and NACHT (4%), appeared most. Additionally, DUF4384, DUF2808, DUF2610, and pentapeptide repeats were also associated with several OCAs . Among aThe prevalence of WD40 in most of the OCAs suggested their interaction with the target proteins may be carried out via this domain. The presence of NACHT in Tery_1841, Ava_2184, and GEI7407_1529 indicated their putative roles in PCD or related pathways. Interestingly, the co-occurrence of NACHT and WD40 domains in the wild-type OCAs, i.e. Ava_2184 and GEI 7407_1529, except Tery_1841, may indicate protein–protein interactions during proteolytic cleavage. OCAs containing the wild-type p20-like sub-domain and WD40 at N- and C-termini, respectively, flanking a transmembrane domain, probably have an extracellular localization of WD40 leaving the p20-like sub-domain free for catalysis in the cytoplasm. This extracellular WD40 may interact with the specific growth or death regulatory proteins, and probably modulates the activity of the p20-like sub-domain in the predicted cytoplasmic portion. This presumed topology prevailed in six true OCAs: Ava_0039, Ava_3079, Cri9333_3253, GEI7407_1667, GEI7407_1667, and Glo7428_1095. Among these, the presence of NACHT in the predicted cytoplasmic portion of GEI7407_1667 implies its activity during PCD. Moreover, Ava_0039, Ava_3079, and GEI7407_1667 have an AAA_16 domain placed N-terminally to the transmembrane domain, probably indicating energy-dependent activity of OCAs. Nevertheless, three putative cytoplasmic OCAs consisting Tery_2471, AMI_G0162, and Ava_2184 also have an AAA_16 domain providing NTPase and chaperone activities. The prevalence of abhydrolase, a domain having serine protease-like activity due to the catalytic triad of Ser, Glu/Asp, and His in Osc7112_0662, Cri9333_0714, and Nos7107_1322 inclusive of the p20-like sub-domain probably implies dual specificity of OCA  or by external  factors, whereas PCD in the cyanobacteria having only cytosolic wild-type OCAs, such as C. stanieri PCC 7202 and C. thermalis PCC 7203, depends only on an intracellular stimulus. Further, the presence of extracellular domains may result in neighbouring cells being engaged in PCD as well  and YS (II) clades  was composed of heterocytous, filamentous, and unicellular δOCAs. Apart from that, all other p20 variants from different strains are scattered throughout the tree. Such a phylogenetic arrangement of δOCA has not only conferred functional variability but may also indicate a diverse origin and independent emergence. This probably implies the acquisition of OCA subtypes in the cyanobacteria from multiple donors harbouring different OCAs. It is also possible that the mutation has occurred in cyanobacteria after HGT to acquire adaptive advantages during evolution. Yet no conclusion can be drawn without explicit studies in the context that has crafted the present scenario.Phylogenetic analysis of these p20-like sub-domains displayed intermixing of unicellular, filamentous, and heterocytous strains . Therefo) clades . Further) clades . InteresDunaliella–Halobacterium model  that further induces rapid cell death  may be considered as an outcome of sequential PCD in the parent filament -specificity pocket’ of 98 p20-like catalytic sub-domains of OCAs obtained from 29 cyanobacterial strains.Fig. S2. Multiple sequence alignment of ‘cysteine (C)-specificity pocket’ of 98 p20-like catalytic sub-domains of OCAs obtained from 29 cyanobacterial strains.Table S1. Different domains of cyanobacterial orthocaspases (OCAs) and their positions.eraa213_suppl_Supplementary_Table_S1_Figures_S1-S2Click here for additional data file.


Through the simulation results of this website, users can predict the evolution trend of the protein domain architecture.Proteins play primary roles in important biological processes such as catalysis, physiological functions, and immune system functions. Thus, the research on how proteins evolved has been a nuclear question in the field of evolutionary biology. General models of protein evolution help to determine the baseline expectations for evolution of sequences, and these models have been extensively useful in sequence analysis as well as for the computer simulation of artificial sequence data sets. We have developed a new method of simulating multi-domain protein evolution, including fusions of domains, insertion, and deletion. It has been observed via the simulation test that the success rates achieved by the proposed predictor are remarkably high. For the convenience of the most experimental scientists, a user-friendly web server has been established at  Proteins are the biological macromolecular entities most close-knitly related to organismal functions. Evolution in the sequences of proteins results in the way these proteins function, and protein evolution is a critical component of organismal evolution and a valuable method for generating useful molecules in the laboratory  in FASTA format, the system annotates the protein domain of each protein sequence pi based on the HMMER and Pfam databases, and each protein pi generates a corresponding annotation file fi. By analyzing the annotation file fi, the domain information of protein pi can be screened out and expressed as a multi-domain sequence:After receiving the protein sequence file P  value of each domain, we determine the position of these domains in the protein sequence or the order of domains in the sequence. The protein pi is expressed as an ordered multi-domain sequence where The protein sequence file P is expressed as a set of multi-domain sequences as file P′:w is the number of domains in protein u is the number of domains in protein P′ for the proposed evolutionary simulation model.where Inspired by incorporating the dipeptide position-specific propensity into the general pseudo nucleotide composition  couple: X-startD1, X-startD2,…, D1D1 (where domain D1 and domain D1 are connected together), D1D2, D1D3,…, DgDg, D1X. -ending,…, DgX-ending. Thus, for the training data set P′, its profile (or detailed information) of mmarized by the following two matrices:If F2B(from front to back) is matrix of evolution prior probability from front to back and B2F(from back to front) is the matrix of evolution prior probability from back to front. In the matrix F2B, DiDj  is the occurrence frequency of domainDi attached to Dj, and Dj behind Di. In the matrix B2F, Di attached to Dj, and Di is followed by Dj.where i-m, …, i-3, i-2, i-1, i, i+1, i+2, i+3, …, i+m, and the corresponding states of these cells are Ci−m, ⋯ , Ci−2, Ci−1, Ci, Ci+1, Ci+2, ⋯ , Ci+m. The symbol i is the center of initial sequence with length equals to 2m+1. The state of the ith cell takes value from a predefined discrete set: Ci∈{c1, c2, ⋯ , cQ}, where c1, c2, ⋯ , cQ are the elements of the set. The CA evolves in discrete time steps, and its evolution is manifested by the change of its cell states with time. The state of each cell is affected by the states of its neighboring cells. The neighborhood is defined as N = {Ci−r, ⋯ , Ci−1, Ci, Ci+1, ⋯ , Ci+r}, where r is the size of the neighborhood. If r = 1, the neighborhood of the ith cell consists of the same cell and its left and right immediate neighbors N = {Ci−1, Ci, Ci+1}. The state of the ith cell at time step t+1 is affected by the states of its neighbors at the previous time step t, F is the CA evolution rule  and the time step in CA evolution is set as m. The model was a (g+3)-state model in which each cell in the lattice was one of the following (g+3) states: (1) g domain classes appeared in the training data set P′; (2) evolution termination symbols “X-start”; (3) evolution termination symbols “X-end”; (4) an empty state “∅″. The state of the cell at time tcan be expressed as j. When the CA is initialized (t = 0), the state of the cell Y, and the state of the other cells is set to the empty state ∅, as shown in t+1 is determined by the state t and the state t.In this study, the non-uniform 1D CA was used to simulate the domain evolution in proteins. The square arrays are a very basic data structure in computers, and it was rational to use a square lattice in our model. If protein pThe evolution rules of the proposed CA model can be expressed as follows :Inheritance. If the state of cell E(E≠∅), it means that the cell has evolved into domain E, so this cell E.Rule A: Rules of evolution from front to back. If the state of cells F(F≠∅), the state F2B (from front to back evolution prior probability matrix), we know that the probability of all domains to appear behind domain F. It is not true that the domain of the biggest probability certainly appears behind domain F in natural evolution course. Hence, we determined the state F probability is not zero based on Roulette wheel selection algorithm. The probability of selecting a domain G is the same as the probability of domain F appearing after domain G in matrix F2B.Rule B: Rules of evolution from back to front. If the state of cells V(V≠∅), then the state B2F (from back to front evolution prior probability matrix) was used instead of the matrix F2B. The probability of selecting a domain H being selected is the same as the probability of domain H appearing before domain V in matrix B2F.Rule C: Return inanimateness. If the states of cells Rule D: Y, and where the common domains in the P′ are considered to be the hypothetical ancestral domain. By running the model once, a new protein will be simulated, and the evolved protein is represented by an ordered sequence of multi-domains.Proteins in a family descend from a common ancestor and have similar 3D structures, functions, and sequence similarity. Thus, the model assumes that all of the evolved proteins contain ancestral domains t = 0), the state of the cell Y, and the state of the other cells is set to the empty state ∅.As shown in t = 1, the state of Y(Y≠∅), then Y according to rule A inherit the state of Y, the state of B2F to obtain the domain E. The state of Y and the state of B, the state of F2B to obtain the domain F after the domain Y. Keep the rule D in mind, the state of the other cells is the empty domain ∅ because the state of the other cells at the previous moment and the states of their neighbors are the empty domain ∅.When t = 2, the states of E, Y and domain F; the state of E, according to rule C, the state of B2F to obtain the domain G in front of the domain E; the state of F, the state of F2B to obtain the domain H after the domain F. According to rule D, the state of the other cells is the domain ∅ on the basis of that the state of the other cells and the states of their neighbors are the domain ∅.When t = k(k<m), the cells with the state of termination symbols X-start and X-end are evolved in the cell space, and the simulated evolution of the protein comes to an end. The state of the cell space at time k is taken as an ordered sequence of multi-domain, removing the cells with the empty state ∅. The simulated multi-domain sequence of protein A is expressed as:When t = m, if termination symbols X-start and X-end have not evolved in the cell space, the simulated evolution of the protein also comes to an end. The state of the cell space at time m is taken as an ordered sequence of multi-domain, removing the cells with the empty state ∅ and adding two termination symbols to the left and right ends of the cell space. The simulated multi-domain sequence of protein B is expressed as:As shown in In order to facilitate the use of researchers, we have developed a web server, where users can directly submit protein sequence files and select various parameters for protein evolution simulation. The system will send the results to the user's e-mail address. The graphical user interface of the website is shown in The user uploads a protein sequence file in FASTA format by clicking the button “Submit Sequence.”The ancestral domains are the initial state of the cell in the middle of the CA space. The model uses this parameter as a common ancestor of the protein. Once this parameter is filled in, all evolved proteins will contain this domain.The E-value is a parameter used in the HMMER software; it is the expected number of false positives (non-homologous sequences) that scored this well or better. The E-value is a measure of statistical significance. The lower the E-value, the more significant the hit. Changing the value of E-value will cause the same protein to compare different domain architectures, and the default value is “1e-37.”The number of times of model simulation.The model analyzes automatically the evolved proteins and sends the top top-num frequency of the domain architectures to users.After submitting the protein sequence file and parameters, the system will compare the uploaded protein sequences based on HMMER. By setting the value of the E-value, each protein will generate a homology domain information file. The domain of each protein is then extracted and sorted according to the position of the domain in the protein sequence, such that each protein can be represented as a multi-domain sequence.Next, the sliding window processing is performed on each multi-domain sequence (the sliding window size is 2), the matrix of probability from back to front and the matrix of probability from front to back are obtained by counting the frequency of the domain in pairs.In the evolution process of the CA, the next time state of the cell is obtained according to the CA evolution rule. When evolution is terminated, the system removes the domain ∅ and generates a complete multi-domain protein. The user can control the number of proteins that the system simulates by adjusting the size of Evo-num.After the evolution of the protein, the system calculates the frequency of each domain architecture based on the multi-domain protein of the original file and the multi-domain protein obtained by the proposed simulation model, sorts the frequency from large to small, and saves it as two files in comma-separated values (CSV) format. Since there are many protein domain architectures obtained by simulation, users can adjust the value of Top-num to preserve the domain architectures with high frequency.Finally, the system will send the results to the user's e-mail address. The contents of the e-mail are the parameters selected by the user, and in the attachment, there are two data files in CSV format. The CA model can be described by the flowchart in Homo sapiens to download a multi-sequence file containing 1,597 proteins and used it as a protein sequence file P. In addition to the above methods, researchers can also build data sets by the following methods. The Conservative Domain Database  collects a large number of protein domains and domain families , goodness of fit between the simulation proteins and nature protein in P′, used in this literature based on counting the type and number of the DAWPs. Hit-Acc (TAPD), goodness of fit between the triplet domain architectures in P′ and Pevo, Hit-Acc (QAPD), goodness of fit between the quadruple domain architectures in P′ and Pevo as supplementary.In order to examine the performance of a predictor in simulating domain evolution of proteins, evo is the set of triplet domain architectures in Pevo, ∩ represents the symbol for “intersection” in the set theory, ti in Pevo, and Pevo.where T′ is the set of triplet domain architectures in P′, TQ′ is the set of quadruple domain architectures in P′, Qevo is the set of quadruple domain architectures in Pevo, qi in Pevo, and Pevo.where Homo sapiens' protein family RhoGEF, and set the value of E-values from 1e-1 to 1e-50, so that the protein domain information file corresponding to E-values would be generated, and 50 simulation training data sets would be obtained after processing the file. The smaller the value of E-value, the higher the accuracy of the aligned homology domain. Changing the value of E-value will cause the same protein match different domain architectures when the value of E-value is 1e-1. A total of 228 domains existed in the simulation data set P, and the number of types of protein domain architectures was 326. When the value of E-value is 1e-37, there are 43 domains in the simulation data set P, the number of types of protein domain architecture is 55, and the most complex protein domain architecture is {′I-set′,′V-set′,′Ig′,′Ig′,′Ig′,′Izumo-Ig′,′Ig′,′Ig′,′Pkinase′,′Pkinase′}. The 10 most frequent protein domains are shown in In the process of testing system performance, we used HMMER to perform multi-domain sequence alignment on X. -start, and X-end as ancestral protein domains to simulate each training set, and each training set simulates 50,000 proteins represented by multiple domain sequences. In order to eliminate the impact of individual results on the model evaluation, we repeated the simulation of each parameter combination 50 times and then calculated the average value of Hit-Acc. as the evaluation of the model; the obtned results are shown in The model uses RhoGEF, X-start or X-end, the test results are basically the same as the ancestral protein domain RhoGEF. The Hit-Acc (TAPD) and Hit-Acc (DAWP) reach the maximum when the E-value is 1e-37, the Hit-Acc (TAPD) is 91.01%, and the Hit-Acc (DAWP) is 88.26%. These test results show that the model has good simulation characteristics and robustness. The model can also get better results in most cases by using X-start and X-end as the ancestral protein domain for simulated evolution. The reason is that this model uses HMMER for automated annotation of protein domains. The smaller the E-values, the fewer domains are annotated. Some proteins will not annotate the ancestral domain because the set E-value is too small. For example, if the E-value is 1e-1, 1,440 proteins are annotated with the RhoGEF domain; if the E-value is 1e-37, only 619 proteins are annotated with the RhoGEF domain. In order to solve this problem, the model added X-start and X-end to the left and right ends of each protein when composing the protein simulation training data set. If the model uses X-start or X-end as the ancestral protein domain, each protein domain architecture could be simulated, which also allows the system to simulate more protein domain architectures that appear in the original file. This also means that if the user does not know the ancestor domain of the submitted protein sequence file, X-start or X-end can be used as the ancestral domain for protein simulation. It can be seen from the results that the model can effectively simulate the DAWPs under various parameters. It also simulated existing triplet and quadruplet domain architectures successfully. Analysis on the results shows that the model not only has good stability but also has strong robustness.When the ancestral protein domain is RhoGEF, the Hit-Acc (TAPD). and Hit-Acc (DAWP) reach the maximum; when the E-value is 1e−43, the Hit-Acc (TAPD) is 90.27%, the Hit-Acc (DAWP) is 89.59%. When the ancestral protein domain is Although the proposed model simulating the evolution of protein domain architectures only by fusion operation, the obtained results do contain the results of insertion, deletion, and mutation operations. For example, given that the simulation starts with “RhoGEF,” if one result is “RhoGEF-PH-PH-C2” and another is “RhoGEF-PH-C2,” then we can assume that the later one is the result of the fore in which the “PH” was deleted. The operations are shown in Moreover, statistical analysis by the triplet and quadruple domain architectures derived from the evolution of the model shows that only a few domains contain a large number of immediate neighbors, and most of the domains contain only a small number of immediate neighbors, the frequency distribution of each domain neighbor in accordance with a power law (Qian et al., The goal of this work was to provide a tool that can reveal how domain architectures have evolved in protein sequences. This tool is very important in analyzing orthologous relationships between proteins in different organisms. CA has been applied in many fundamental issues in biology. Some works have already been devoted to providing a framework for simulation evolution of protein and DNA sequences. In this work, 1D probabilistic CA is used to simulate the evolution of protein domain. This model simulates the fission, fusion, deletion, and insertion of the natural evolution processes by randomly appointing transitional rules. This is the reason that our model is more in line with the natural characteristics of protein evolution. Through this website, users can know the domain architecture distribution of the submitted protein sequence and can also view the evolution results of the model to predict the evolution direction of the protein sequence file with the emergence of new and frequent protein domain architecture.Publicly available datasets were analyzed in this study. This data can be found here: access protein sequence data from NCBI, and searching HMM domains from Pfam with HMMER.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In silico analysis revealed that a lectin, jacalin from jackfruit seeds, recognizes a glycosylated region of the receptor-binding domain (RBD) of SARS-CoV2. Jacalin binding induces conformational changes in RBD and significantly affects its interaction with human angiotensin-converting enzyme 2. The result may open up exploration of lectin-based strategies against COVID-19. Thus, quarantine of the infected people, the lockdown of the states and imposing travel restrictions are suggested as an option to minimize the spread, which eventually disturb the economy . AmoCoV is a long single-stranded positive RNA virus with size ranging from 27 to 34 kilobases. The genome encodes for structural proteins and a non-structural replicase polyprotein. CoV contains four structural proteins, they are spike (S), envelope (E), membrane (M) and nucleocapsid (N) proteins ,6. Therein silico approach. In addition, we studied the docking of the proposed drug, hydroxychloroquine (HCQ) with jacalin. The result indicates that jacalin recognizes the NAG of RBD and also has the ability to bind to HCQ, suggesting the potential of jacalin to carry targeted inhibitors or neutralizing agents.Lectins are glycan-binding proteins, present ubiquitously in all forms of life. Some lectins are known for antiviral, antibacterial and anti-cancer activity . The spe2.The crystal structures used for the analysis were downloaded from the protein data bank (PDB). The recently solved structure of SARS-CoV2 RBD complex with ACE2 receptor (PDB ID: 6LZG) was used in our study . PDB ID:Protein–protein docking was performed using HADDOCK and ClusPro 2.0 online servers ,16. We sThe secondary structure information for models was calculated using the web server ‘2Struc’, which uses DSSP (Dictionary of Secondary Structure of Proteins), a gold standard approach for secondary structure assignments .The structure of hydroxychloroquine (HCQ) drug is obtained from the PubChem database (PubChem ID: 3652). Molecular docking of HCQ was performed using AutoDock Vina with help of PyRx tool . The gri3.The crystal structure of the novel corona spike RBD-ACE2 receptor (PDB ID: 6LZG) with 2.5 Å resolution was exploited in this work . It consIn order to establish the interaction between the glycation site of RDB or hACE2 with jacalin, we used two different protein–protein docking servers, ClusPro 2.0 and HADDOCK (High Ambiguity Driven bimolecular DOCKing). To validate the docking procedure, the docking between hACE2 and RBD was performed (separately for both methods) and the predicted top model compared with the PDB structure (as it is docked). Interestingly, the top model selected based on the top-scoring function matches with PDB structure, and the residues involved in the interactions are similar . This supports that ClusPro 2.0 and HADDOCK are suitable for studying protein–protein interaction. From the crystal structure of jacalin-T antigen complex (PDB: 1M26) , the cooThe top-ranked docked model of jacalin–RBD is shown in in silico mutation study. The NAG linked N343 of RBD was mutated to G343 and docking studies was performed as described above. As a result of a mutation in RBD (N343G), the HADDOCK score decreased from −82.6 to −52.9, suggesting that the binding affinity of jacalin to N343G RBD was reduced. A detailed analysis is present in 2 decreases to 1263.6 Å2, indicating that RBD (N343G) was poorly recognized by jacalin. Similar results were obtained from ClusPro 2.0, where the score for a balanced model decreased from −1308.8 to −1157.4 and the score for the electrostatic-favoured model was affected significantly .Having learnt of the jacalin preference to RBD, we extend the analysis on the impact of the jacalin on RBD–hACE2 complex. It is noted from the crystal structure, the NAGs of hACE2 were not involved in RBD-hACEs interaction . Thus, tThe change in the secondary structure of the model was analysed by DSSP approach . The α-h−1, and the inhibition constant is 65.25 µM. The docking was further verified by DockThor, a free web server. The free energy value  obtained by DockThor is comparable to Autodock Vina server, suggesting the interaction between jacalin and HCQ. The free energy values suggest stronger binding, which is comparable to those observed for the interaction of carbohydrate and lectin [−1 [In order to explore RBD recognizing property of jacalin in drug delivery, we analysed the interaction of jacalin with hydroxychloroquine. HCQ was considered as a model drug; moreover, HCQ was proposed for treatment against COVID-19 infection . Previoud lectin . Jacalinctin [−1 . Analysiet al. showed that jacalin binds to HIV-1 envelope glycoprotein (gp120) and its precursor (gp160) and inhibits the HIV-1 infection of CD4 + lymphoblastoid cells [in silico study, we propose that the jacalin recognization of RBD may act as an inhibitor or be useful in developing targeted drug delivery vehicle against COVID-19.To support the global research effort of finding solutions for COVID-19 drives us to propose jacalin, because the recent study showed that jacalin-CuS NPs (JCuS NPs) eliminate the bacterial infection in zebra fish model . The bacid cells . The spi4.in silico analysis suggests that jacalin effectively binds to RBD through NAG present in N343. As a result of jacalin binding, the interaction between RBD and hACE2 was affected significantly due to the change in the conformation of RBD. These results are promising because weakening the interaction between RBD and hACE2 may prevent the viral entry. Further, molecular dynamics and experimental investigation with diverse lectin against SARS-CoV2 may open up newer therapeutic options against viral infection.The interaction between a lectin, jacalin and RBD of SARS-CoV2 was reported for the first time. A detailed