GalaxyTBM: template-based modeling by building a reliable core and refining unreliable local regions

Improved Thermal Stability of a Novel Acidophilic Phytase

Phytase increases the availability of phosphate and trace elements by hydrolyzing the phosphomonoester bond in phytate present in animal feed. It is also an important enzyme from an environmental perspective because it not only promotes the growth of livestocks but also prevents phosphorus contamination released into the environment. Here we present a novel phytase derived from Turicimonas muris, TmPhy, which has distinctive structure and properties compared to other previously known phytases. TmPhy gene expressed in the Pichia system was confirmed to be 41 kDa in size and was used in purified form to evaluate optimal conditions for maximum activity. TmPhy has a dual optimum pH at pH3 and pH6.8 and exhibited the highest activity at 70°C. However, the heat tolerance of the wildtype was not satisfactory for feed application. Therefore, random mutation, disulfide bond introduction, and N-terminal mutation were performed to improve the thermostability of the TmPhy. Random mutation resulted in TmPhyM with about 45% improvement in stability at 60°C. Through further improvements, a total of three mutants were screened and their heat tolerance was evaluated. As a result, we obtained TmPhyMD1 with 46.5% residual activity, TmPhyMD2 with 74.1%, and TmPhyMD3 with 66.8% at 80°C heat treatment without significant loss of or with increased activity.

XRCC1 Polymorphisms p.Arg194Trp, p.Arg280His, and p.Arg399Gln, Polycyclic Aromatic Hydrocarbons, and Infertility: A Case-Control and In Silico Study

XRCC1 is involved in repair of single-strand breaks generated by mutagenic exposure. Polymorphisms within XRCC1 affect its ability to efficiently repair DNA damage. Polycyclic aromatic hydrocarbons or PAHs are genotoxic compounds which form bulky DNA adducts that are linked with infertility. Few reports suggest combined role of XRCC1 polymorphisms and PAHs in infertility. Present study investigates association of three XRCC1 polymorphisms (p.Arg194Trp, p.Arg280His, p.Arg399Gln) with male and female infertility in a North-West Indian population using case-control approach. Additionally, in silico approach has been used to predict whether XRCC1 polymorphisms effect interaction of XRCC1 with different PAHs. For case-control study, XRCC1 polymorphisms were screened in peripheral blood samples of age- and gender-matched 201 infertile cases (♂-100, ♀-101) and 201 fertile controls (♂-100, ♀-101) using PCR-RFLP method. For in silico study, AutoDock v4.2.6 was used for molecular docking of B[a]P, BPDE-I, ( ±)-anti-BPDE, DB[a,l]P, 1-N, 2-N, 1-OHP, 2-OHF with XRCC1 and assess effect of XRCC1 polymorphisms on their interaction. In case-control study, statistical analysis showed association of XRCC1 p.Arg280His GA genotype (p = 0.027), A allele (p = 0.019) with reduced risk of male infertility. XRCC1 p.Arg399Gln AA genotype (p = 0.021), A allele (p = 0.014) were associated with reduced risk for female primary infertility. XRCC1 p.Arg194Trp T allele was associated with increased risk for female infertility (p = 0.035). In silico analysis showed XRCC1-PAH interaction with non-significant effect of XRCC1 polymorphisms on predicted binding. Therefore, present study concludes that XRCC1 polymorphism-modified risk for male and female infertility in North-West Indians without significant effect on predicted XRCC1-PAH interactions. This is the first report on XRCC1 in female infertility.

Discovery of thiophen-2-ylmethylene bis-dimedone derivatives as novel WRN inhibitors for treating cancers with microsatellite instability

Microsatellite instability (MSI) is a hypermutable condition caused by DNA mismatch repair system defects, contributing to the development of various cancer types. Recent research has identified Werner syndrome ATP-dependent helicase (WRN) as a promising synthetic lethal target for MSI cancers. Herein, we report the first discovery of thiophen-2-ylmethylene bis-dimedone derivatives as novel WRN inhibitors for MSI cancer therapy. Initial computational analysis and biological evaluation identified a new scaffold for a WRN inhibitor. Subsequent SAR study led to the discovery of a highly potent WRN inhibitor. Furthermore, we demonstrated that the optimal compound induced DNA damage and apoptotic cell death in MSI cancer cells by inhibiting WRN. This study provides a new pharmacophore for WRN inhibitors, emphasizing their therapeutic potential for MSI cancers.

Mce1R of Mycobacterium tuberculosis prefers long-chain fatty acids as specific ligands: a computational study

The mce1 operon of Mycobacterium tuberculosis, which codes the Mce1 transporter, facilitates the transport of fatty acids. Fatty acids are one of the major sources for carbon and energy for the pathogen during its intracellular survival and pathogenicity. The mce1 operon is transcriptionally regulated by Mce1R, a VanR-type regulator, which could bind specific ligands and control the expression of the mce1 operon accordingly. This work reports computational identification of Mce1R-specific ligands. Initially by employing cavity similarity search algorithm by the ProBis server, the cavities of the proteins similar to that of Mce1R and the bound ligands were identified from which fatty acids were selected as the potential ligands. From the earlier-generated monomeric structure, the dimeric structure of Mce1R was then modeled by the GalaxyHomomer server and validated computationally to use in molecular docking and molecular dynamics simulation analysis. The fatty acid ligands were found to dock within the cavity of Mce1R and the docked complexes were subjected to molecular dynamics simulation to explore their stabilities and other dynamic properties. The data suggest that Mce1R preferably binds to long-chain fatty acids and undergoes distinct structural changes upon binding.

Multi-epitope vaccine candidates based on mycobacterial membrane protein large (MmpL) proteins against Mycobacterium ulcerans

Buruli ulcer (BU) is a neglected tropical disease. It is caused by the bacterium Mycobacterium ulcerans and is characterized by skin lesions. Several studies were performed testing the Bacillus Calmette-Guérin (BCG) vaccine in human and animal models and M. ulcerans-specific vaccines in animal models. However, there are currently no clinically accepted vaccines to prevent M. ulcerans infection. The aim of this study was to identify T-cell and B-cell epitopes from the mycobacterial membrane protein large (MmpL) proteins of M. ulcerans. These epitopes were analysed for properties including antigenicity, immunogenicity, non-allergenicity, non-toxicity, population coverage and the potential to induce cytokines. The final 8 CD8+, 12 CD4+ T-cell and 5 B-cell epitopes were antigenic, non-allergenic and non-toxic. The estimated global population coverage of the CD8+ and CD4+ epitopes was 97.71%. These epitopes were used to construct five multi-epitope vaccine constructs with different adjuvants and linker combinations. The constructs underwent further structural analyses and refinement. The constructs were then docked with Toll-like receptors. Three of the successfully docked complexes were structurally analysed. Two of the docked complexes successfully underwent molecular dynamics simulations (MDS) and post-MDS analysis. The complexes generated were found to be stable. However, experimental validation of the complexes is required.

Screening of apical membrane antigen-1 (AMA1), dense granule protein-7 (GRA7) and rhoptry protein-16 (ROP16) antigens for a potential vaccine candidate against Toxoplasma gondii for chickens

Toxoplasmosis is a zoonotic disease caused by the protozoan parasite, Toxoplasma gondii known to infect almost all animals, including birds and humans globally. This disease has impacted the livestock industry and public health, where infection of domestic animals increases the zoonotic risk of transmission of infection to humans, threatening public health. Hence the need to discover novel and safe vaccines to fight against toxoplasmosis. In the current study, a novel multiepitope vaccine was designed using immunoinformatics techniques targeting T. gondii AMA1, GRA7 and ROP16 antigens, consisting of antigenic, immunogenic, non-allergenic and cytokine inducing T-cell (9 CD8⁺ and 15 CD4⁺) epitopes and four (4) B-cell epitopes fused together using AAY, KK and GPGPG linkers. The tertiary model of the proposed vaccine was predicted and validated to confirm the structural quality of the vaccine. The designed vaccine was highly antigenic (antigenicity = 0.6645), immunogenic (score = 2.89998), with molecular weight of 73.35 kDa, instability and aliphatic index of 28.70 and 64.10, respectively; and GRAVY of -0.363. The binding interaction, stability and flexibility were assessed with molecular docking and dynamics simulation, which revealed the proposed vaccine to have good structural interaction (binding affinity = -106.882 kcal/mol) and stability when docked with Toll like receptor-4 (TLR4). The results revealed that the Profilin-adjuvanted vaccine is promising, as it predicted induction of enhanced immune responses through the production of cytokines and antibodies critical in blocking host invasion.

Quantitative comparison of protein-protein interaction interface using physicochemical feature-based descriptors of surface patches

Driving mechanisms of many biological functions in a cell include physical interactions of proteins. As protein-protein interactions (PPIs) are also important in disease development, protein-protein interactions are highlighted in the pharmaceutical industry as possible therapeutic targets in recent years. To understand the variety of protein-protein interactions in a proteome, it is essential to establish a method that can identify similarity and dissimilarity between protein-protein interactions for inferring the binding of similar molecules, including drugs and other proteins. In this study, we developed a novel method, protein-protein interaction-Surfer, which compares and quantifies similarity of local surface regions of protein-protein interactions. protein-protein interaction-Surfer represents a protein-protein interaction surface with overlapping surface patches, each of which is described with a three-dimensional Zernike descriptor (3DZD), a compact mathematical representation of 3D function. 3DZD captures both the 3D shape and physicochemical properties of the protein surface. The performance of protein-protein interaction-Surfer was benchmarked on datasets of protein-protein interactions, where we were able to show that protein-protein interaction-Surfer finds similar potential drug binding regions that do not share sequence and structure similarity. protein-protein interaction-Surfer is available at https://kiharalab.org/ppi-surfer.

EhSir2c, a Sir2 homolog from the human pathogen Entamoeba histolytica interacts with a DNA repair protein, EhRAD23: Protein-protein interaction, docking and functional study

Chromosome segregation is a crucial phenomenon in the cell cycle and defects in genome segregation result in an abnormality in various cellular events. Unlike higher eukaryotes, chromosome segregation and a number of cell cycle events are unusual in the protozoan parasite Entamoeba histolytica (E. histolytica). Characterization of Sir2 proteins from E. histolytica may reveal its unique cellular events as they play role in diverse cellular processes including chromosome segregation. E. histolytica has four homologs of Sir2 proteins. EhSir2a and EhSir2b show sequence similarity towards eukaryotic Sir2 homologs, whereas EhSir2c and EhSir2d are more like prokaryotic sirtuins. Using both computational and experimental methods, EhSir2c has been characterized in this study. The three-dimensional structure of EhSir2c is predicted by homology modelling. The protein interactors of EhSir2c have been identified by yeast-two-hybrid screening against the cDNA library of E. histolytica. We have identified a novel interactor, EhRAD23 which is a homolog of UV excision repair protein RAD23. The interaction of EhSir2c and EhRAD23 was validated by pull-down assay. UV-C irradiation up-regulates the relative expression of EhSir2c, suggesting the necessity of EhSir2c in UV-induced stress in this parasite.Communicated by Ramaswamy H. Sarma.

In silico analysis of a Skp1 protein homolog from the human pathogen E. histolytica

SCF complex consisting of Skp1, Cullins, F-box proteins, is the largest family of E3 ubiquitin ligases that promotes ubiquitination of many substrate proteins and controls numerous cellular processes. Skp1 is an adapter protein that binds directly to the F-box proteins. In this study, we have presented the first comprehensive analysis of the presence of peptides or proteins in the human pathogen Entamoeba histolytica having homology to Skp1protein. The occurrence of other protein components of the SCF complex has been identified from protein-protein interaction network of EhSkp1A. Studying the role of Skp1protein in this pathogen would help to understand its unique chromosome segregation and cell division which are different from higher eukaryotes. Further, owing to the development of resistance over several drugs that are currently available, there is a growing need for a novel drug against E. histolytica. Proteins from ubiquitin-proteasome pathway have received attention as potential drug targets in other parasites. We have identified four homologs of Skp1 protein in E. histolytica strain HM-1: IMSS. Molecular docking study between EhSkp1A and an F-box/WD domain-containing protein (EhFBXW) shows that the F-box domain in the N-terminal region of EhFBXW interacts with EhSkp1A. Therefore, the results of the present study shall provide a stable foundation for further research on the cell cycle regulation of E. histolytica and this will help researchers to develop new drugs against this parasite.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12639-022-01523-0.

Identification of intrinsically disordered regions in hub genes of acute myeloid leukemia: A bioinformatics approach

Acute myeloid leukemia (AML) is the most common acute leukemia in adults. Over the past decades, there has been a great challenge in the treatment of AML. A combination of gene expression profiling with computational approaches can lead to the identification of hub genes in AML. However, it is important to study the structure of these hub genes considering their importance in the protein-protein interaction (PPI) network of specific cancer. In this study, we designed an integrated method to analyze the presence of intrinsically disordered regions (IDRs) in selected hub genes of AML. A gene expression profile of AML was obtained from Gene Expression Omnibus (GEO) database. Further analysis identified differentially expressed genes (DEGs) in AML. Additionally, the top 15 hub genes following construction and analysis of the PPI network of DEGs were selected. Validation of hub genes revealed that there is a reverse relationship between overexpression of FLT3, PPBP, and PF4 genes and the survival of AML patients. Based on IDRs investigation, FLT3 and PF4 are partially disordered, while PPBP is mostly disordered. Through clustering the network into structural modules, we identified two important modules in the PPI network of DEGs that showed the important position of PPBP in module 1. Based on further analysis of protein flexibility and its important role in biological processes, we suggest that PPBP can be considered as a potential drug target in AML.

Immune epitopes identification and designing of a multi-epitope vaccine against bovine leukemia virus: a molecular dynamics and immune simulation approaches

Background

Bovine leukemia virus (BLV) is an oncogenic delta-retrovirus causing bovine leucosis. Studies on BLV have shown the association with human breast cancer. However, the exact molecular mechanism is neither known nor their appropriate preventative measure to halt the disease initiation and progression. In this study, we designed a multi-epitope vaccine against BLV using a computational analyses.

Methods

Following a rigorous assessment, the vaccine was constructed using the T-cell epitopes from each BLV-derived protein with suitable adjuvant and linkers. Both physicochemistry and immunogenic potency as well as the safeness of the vaccine candidate were assessed. Population coverage was done to evaluate the vaccine probable efficiency in eliciting the immune response worldwide. After homology modeling, the three-dimensional structure was refined and validated to determine the quality of the designed vaccine. The vaccine protein was then subjected to molecular docking with Toll-like receptor 3 (TLR3) to evaluate the binding efficiency followed by dynamic simulation for stable interaction.

Results

Our vaccine construct has the potential immune response and good physicochemical properties. The vaccine is antigenic and immunogenic, and has no allergenic or toxic effect on the human body. This novel vaccine contains a significant interactions and binding affinity with the TLR3 receptor.

Conclusions

The proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat BLV infections. However, experimental evaluations are essential to validate the exact safety and immunogenic profiling of this vaccine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00262-022-03181-w.

A unique antigen against SARS-CoV-2, Acinetobacter baumannii, and Pseudomonas aeruginosa

The recent outbreak of COVID-19 has increased hospital admissions, which could elevate the risk of nosocomial infections, such as A. baumannii and P. aeruginosa infections. Although effective vaccines have been developed against SARS-CoV-2, no approved treatment option is still available against antimicrobial-resistant strains of A. baumannii and P. aeruginosa. In the current study, an all-in-one antigen was designed based on an innovative, state-of-the-art strategy. In this regard, experimentally validated linear epitopes of spike protein (SARS-CoV-2), OmpA (A. baumannii), and OprF (P. aeruginosa) were selected to be harbored by mature OmpA as a scaffold. The selected epitopes were used to replace the loops and turns of the barrel domain in OmpA; OprF_311–341 replaced the most similar sequence within the OmpA, and three validated epitopes of OmpA were retained intact. The obtained antigen encompasses five antigenic peptides of spike protein, which are involved in SARS-CoV-2 pathogenicity. One of these epitopes, viz. QTQTNSPRRARSV could trigger antibodies preventing super-antigenic characteristics of spike and alleviating probable autoimmune responses. The designed antigen could raise antibodies neutralizing emerging variants of SARS-CoV-2 since at least two epitopes are consensus. In conclusion, the designed antigen is expected to raise protective antibodies against SARS-CoV-2, A. baumannii, and P. aeruginosa.

B-Cell Epitope Mapping from Eight Antigens of Candida albicans to Design a Novel Diagnostic Kit: An Immunoinformatics Approach

Invasive candidiasis is an emerging fungal infection and a leading cause of morbidity in health care facilities. Despite advances in antifungal therapy, increased antifungal drug resistance in Candida albicans has enhanced patient fatality. The most common method for Candida albicans diagnosing is blood culture, which has low sensitivity. Therefore, there is an urgent need to establish a valid diagnostic method. Our study aimed to use the bioinformatics approach to design a diagnostic kit for detecting Candida albicans with high sensitivity and specificity. Eight antigenic proteins of Candida albicans (HYR1, HWP1, ECE1, ALS, EAP1, SAP1, BGL2, and MET6) were selected. Next, a construct containing different immunodominant B-cell epitopes was derived from the antigens and connected using a suitable linker. Different properties of the final construct, such as physicochemical properties, were evaluated. Moreover, the designed construct underwent 3D modeling, reverse translation, and codon optimization. The results confirmed that the designed construct could identify Candida albicans with high sensitivity and specificity in serum samples of patients with invasive candidiasis. However, experimental studies are needed for final confirmation.

Biallelic pathogenic variants in roundabout guidance receptor 1 associate with syndromic congenital anomalies of the kidney and urinary tract

Congenital anomalies of the kidney and urinary tract (CAKUT) represent the most common cause of chronic kidney failure in children. Despite growing knowledge of the genetic causes of CAKUT, the majority of cases remain etiologically unsolved. Genetic alterations in roundabout guidance receptor 1 (ROBO1) have been associated with neuronal and cardiac developmental defects in living individuals. Although Slit-Robo signaling is pivotal for kidney development, diagnostic ROBO1 variants have not been reported in viable CAKUT to date. By next-generation-sequencing methods, we identified six unrelated individuals and two non-viable fetuses with biallelic truncating or combined missense and truncating variants in ROBO1. Kidney and genitourinary manifestation included unilateral or bilateral kidney agenesis, vesicoureteral junction obstruction, vesicoureteral reflux, posterior urethral valve, genital malformation, and increased kidney echogenicity. Further clinical characteristics were remarkably heterogeneous, including neurodevelopmental defects, intellectual impairment, cerebral malformations, eye anomalies, and cardiac defects. By in silico analysis, we determined the functional significance of identified missense variants and observed absence of kidney ROBO1 expression in both human and murine mutant tissues. While its expression in multiple tissues may explain heterogeneous organ involvement, variability of the kidney disease suggests gene dosage effects due to a combination of null alleles with mild hypomorphic alleles. Thus, comprehensive genetic analysis in CAKUT should include ROBO1 as a new cause of recessively inherited disease. Hence, in patients with already established ROBO1-associated cardiac or neuronal disorders, screening for kidney involvement is indicated.

Designing a Multi-Epitope Antigen for Serodiagnosis of Strongyloides stercoralis Based on L3Nie.01 and IgG Immunoreactive Epitopes

Background

Serological diagnosis of Strongyloides stercoralis (S. stercoralis) is fre-quently challenging because of cross-reactivity with other parasitic nematodes. Therefore, it is necessary to introduce novel serological tests with high performance to properly diagnose this neglected parasitic infection. The purpose of the current study was to design a multi-epitope construct for the diagnosis of S. stercoralis.

Methods

For the purpose of this study, first, highly antigenic segments and potential immunodominant epitopes of S. stercoralis were identified from two antigenic proteins, and then all of the selected parts were linked by an appropriate linker. Next, the physicochemical features of the designed construct were analyzed. Then, tertiary structures of the construct were built and evaluated to find out the best one. Lastly, the amino acid sequence was reverse-translated and optimized for over-expression in Escherchia coli (E. coli).

Results

The bioinformatic evaluation indicated that the designed protein construct could be hydrophilic, thermostable, and acidic and the estimated half-life was more than 10 hr in E. coli.

Conclusion

According to the results of the study, the designed construct could be used as an efficient antigen in the ELISA system for serological diagnosis of human strong-yloidiasis.

Dynamic Interactions of Fully Glycosylated SARS-CoV-2 Spike Protein with Various Antibodies

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a public health crisis, and the vaccines that can induce highly potent neutralizing antibodies are essential for ending the pandemic. The spike (S) protein on the viral envelope mediates human angiotensin-converting enzyme 2 binding and thus is the target of a variety of neutralizing antibodies. In this work, we built various S trimer-antibody complex structures on the basis of the fully glycosylated S protein models described in our previous work and performed all-atom molecular dynamics simulations to gain insight into the structural dynamics and interactions between S protein and antibodies. Investigation of the residues critical for S-antibody binding allows us to predict the potential influence of mutations in SARS-CoV-2 variants. Comparison of the glycan conformations between S-only and S-antibody systems reveals the roles of glycans in S-antibody binding. In addition, we explored the antibody binding modes and the influences of antibody on the motion of S protein receptor binding domains. Overall, our analyses provide a better understanding of S-antibody interactions, and the simulation-based S-antibody interaction maps could be used to predict the influences of S mutation on S-antibody interactions, which will be useful for the development of vaccine and antibody-based therapy.

Designing a therapeutic and prophylactic candidate vaccine against human papillomavirus through vaccinomics approaches

OBJECTIVE

Human papillomavirus (HPV) is the main cause of cervical cancer, the 4^th prominent cause of death in women globally. Previous vaccine development projects have led to several approved prophylactic vaccines available commercially, all of which are made using major capsid-based (L1). Administration of minor capsid protein (L2) gave rise to the second generation investigational prophylactic HPV vaccines, none of which are approved yet due to low immunogenicity provided by the L2 capsid protein. On the other hand, post-translation proteins, E6 and E7, have been utilized to develop experimental therapeutic vaccines. Here, in silico designing of a therapeutic and prophylactic vaccine against HPV16 is performed.

METHODS

In this study, several immunoinformatic and computational tools were administered to identify and design a vaccine construct with dual prophylactic and therapeutic applications consisting of several epitope regions on L2, E6, and E7 proteins of HPV16.

RESULTS

Immunodominant epitope regions (aa 12-23 and 78-78 of L2 protein, aa 11-27 of E6 protein, and aa 70-89 of E7 protein) were employed, which offered adequate immunogenicity to induce immune responses. Resuscitation-promoting factors (RpfB and RpfE) of Mycobacterium tuberculosis were integrated in two separate constructs as TLR4 agonists to act as vaccine adjuvants. Following physiochemical and structural evaluations carried out by various bioinformatics tools, the designed constructs were modeled and validated, resulting in two 3D structures. Molecular docking and molecular dynamic simulations suggested stable ligand-receptor interactions between the designed construct and TLR4.

CONCLUSION

Ultimately, this study led to suggest the designed construct as a potential vaccine candidate with both prophylactic and therapeutic applications against HPV by promoting Th1, Th2, CTL, and B cell immune responses, which should be further confirmed in experimental studies.

Designing multiepitope-based vaccine against Eimeria from immune mapped protein 1 (IMP-1) antigen using immunoinformatic approach

Drug resistance against coccidiosis has posed a significant threat to chicken welfare and productivity worldwide, putting daunting pressure on the poultry industry to reduce the use of chemoprophylactic drugs and live vaccines in poultry to treat intestinal diseases. Chicken coccidiosis, caused by an apicomplexan parasite of Eimeria spp., is a significant challenge worldwide. Due to the experience of economic loss in production and prevention of the disease, development of cost-effective vaccines or drugs that can stimulate defence against multiple Eimeria species is imperative to control coccidiosis. This study explored Eimeria immune mapped protein-1 (IMP-1) to develop a multiepitope-based vaccine against coccidiosis by identifying antigenic T-cell and B-cell epitope candidates through immunoinformatic techniques. This resulted in the design of 7 CD8⁺, 21 CD4⁺ T-cell epitopes and 6 B-cell epitopes, connected using AAY, GPGPG and KK linkers to form a vaccine construct. A Cholera Toxin B (CTB) adjuvant was attached to the N-terminal of the multiepitope construct to improve the immunogenicity of the vaccine. The designed vaccine was assessed for immunogenicity (8.59968), allergenicity and physiochemical parameters, which revealed the construct molecular weight of 73.25 kDa, theoretical pI of 8.23 and instability index of 33.40. Molecular docking simulation of vaccine with TLR-5 with binding affinity of - 151.893 kcal/mol revealed good structural interaction and stability of protein structure of vaccine construct. The designed vaccine predicts the induction of immunity and boosted host's immune system through production of antibodies and cytokines, vital in hindering surface entry of parasites into host. This is a very important step in vaccine development though further experimental study is still required to validate these results.

Modeling and Structure Determination of Homo-Oligomeric Proteins: An Overview of Challenges and Current Approaches

Protein homo-oligomerization is a very common phenomenon, and approximately half of proteins form homo-oligomeric assemblies composed of identical subunits. The vast majority of such assemblies possess internal symmetry which can be either exploited to help or poses challenges during structure determination. Moreover, aspects of symmetry are critical in the modeling of protein homo-oligomers either by docking or by homology-based approaches. Here, we first provide a brief overview of the nature of protein homo-oligomerization. Next, we describe how the symmetry of homo-oligomers is addressed by crystallographic and non-crystallographic symmetry operations, and how biologically relevant intermolecular interactions can be deciphered from the ordered array of molecules within protein crystals. Additionally, we describe the most important aspects of protein homo-oligomerization in structure determination by NMR. Finally, we give an overview of approaches aimed at modeling homo-oligomers using computational methods that specifically address their internal symmetry and allow the incorporation of other experimental data as spatial restraints to achieve higher model reliability.

Protein oligomer structure prediction using GALAXY in CASP14

Proteins perform their functions by interacting with other biomolecules. For these interactions, proteins often form homo- or hetero-oligomers as well. Thus, oligomer protein structures provide important clues regarding the biological roles of proteins. To this end, computational prediction of oligomer structures may be a useful tool in the absence of experimentally resolved structures. Here, we describe our server and human-expert methods used to predict oligomer structures in the CASP14 experiment. Examples are provided for cases in which manual domain-splitting led to improved oligomeric domain structures by ab initio docking, automated oligomer structure refinement led to improved subunit orientation and terminal structure, and manual oligomer modeling utilizing literature information generated a reasonable oligomer model. We also discussed the results of post-prediction docking calculations with AlphaFold2 monomers as input in comparison to our blind prediction results. Overall, ab initio docking of AlphaFold2 models did not lead to better oligomer structure prediction, which may be attributed to the interfacial structural difference between the AlphaFold2 monomer structures and the crystal oligomer structures. This result poses a next-stage challenge in oligomer structure prediction after the success of AlphaFold2. For successful protein assembly structure prediction, a different approach that exploits further evolutionary information on the interface and/or flexible docking taking the interfacial conformational flexibilities of subunit structures into account is needed.

GalaxyHeteromer: protein heterodimer structure prediction by template-based and ab initio docking

Protein–protein interactions play crucial roles in diverse biological processes, including various disease progressions. Atomistic structural details of protein–protein interactions may provide important information that can facilitate the design of therapeutic agents. GalaxyHeteromer is a freely available automatic web server (http://galaxy.seoklab.org/heteromer) that predicts protein heterodimer complex structures from two subunit protein sequences or structures. When subunit structures are unavailable, they are predicted by template- or distance-prediction-based modelling methods. Heterodimer complex structures can be predicted by both template-based and ab initio docking, depending on the template's availability. Structural templates are detected from the protein structure database based on both the sequence and structure similarities. The templates for heterodimers may be selected from monomer and homo-oligomer structures, as well as from hetero-oligomers, owing to the evolutionary relationships of heterodimers with domains of monomers or subunits of homo-oligomers. In addition, the server employs one of the best ab initio docking methods when heterodimer templates are unavailable. The multiple heterodimer structure models and the associated scores, which are provided by the web server, may be further examined by user to test or develop functional hypotheses or to design new functional molecules.

Structural and Dynamical Differences in the Spike Protein RBD in the SARS-CoV-2 Variants B.1.1.7 and B.1.351

The novel coronavirus (SARS-CoV-2) pandemic that started in late 2019 is responsible for hundreds of millions of cases worldwide and millions of fatalities. Though vaccines are available, the virus is mutating to form new strains among which are the variants B.1.1.7 and B.1.351 that demonstrate increased transmissivity and infectivity. In this study, we performed molecular dynamics simulations to explore the role of the mutations in the interaction of the virus spike protein receptor binding domain (RBD) with the host receptor ACE2. We find that the hydrogen bond networks are rearranged in the variants and also that new hydrogen bonds are established between the RBD and ACE2 as a result of mutations. We investigated three variants: the wild-type (WT), B.1.1.7, and B.1.351. We find that the B.1.351 variant (also known as 501Y.V2) shows larger flexibility in the RBD loop segment involving residue K484, yet the RBD-ACE2 complex shows higher stability. Mutations that allow a more flexible interface that can result in a more stable complex may be a factor contributing to the increased infectivity of the mutated variants.

Isolation and characterization of a new cold-active protease from psychrotrophic bacteria of Western Himalayan glacial soil

As an approach to the exploration of cold-active enzymes, in this study, we isolated a cold-active protease produced by psychrotrophic bacteria from glacial soils of Thajwas Glacier, Himalayas. The isolated strain BO1, identified as Bacillus pumilus, grew well within a temperature range of 4-30 °C. After its qualitative and quantitative screening, the cold-active protease (Apr-BO1) was purified. The Apr-BO1 had a molecular mass of 38 kDa and showed maximum (37.02 U/mg) specific activity at 20 °C, with casein as substrate. It was stable and active between the temperature range of 5-35 °C and pH 6.0-12.0, with an optimum temperature of 20 °C at pH 9.0. The Apr-BO1 had low K_m value of 1.0 mg/ml and V_max 10.0 µmol/ml/min. Moreover, it displayed better tolerance to organic solvents, surfactants, metal ions and reducing agents than most alkaline proteases. The results exhibited that it effectively removed the stains even in a cold wash and could be considered a decent detergent additive. Furthermore, through protein modelling, the structure of this protease was generated from template, subtilisin E of Bacillus subtilis (PDB ID: 3WHI), and different methods checked its quality. For the first time, this study reported the protein sequence for psychrotrophic Apr-BO1 and brought forth its novelty among other cold-active proteases.

Determination of intermediate state structures in the opening pathway of SARS-CoV-2 spike using cryo-electron microscopy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of COVID-19, a highly infectious disease that is severely affecting our society and welfare systems. In order to develop therapeutic interventions against this condition, one promising strategy is to target spike, the trimeric transmembrane glycoprotein that the virus uses to recognise and bind its host cells. Here we use a metainference cryo-electron microscopy approach to determine the opening pathway that brings spike from its inactive (closed) conformation to its active (open) one. The knowledge of the structures of the intermediate states of spike along this opening pathway enables us to identify a cryptic pocket that is not exposed in the open and closed states. These results underline the opportunities offered by the determination of the structures of the transient intermediate states populated during the dynamics of proteins to allow the therapeutic targeting of otherwise invisible cryptic binding sites.

A structural ensemble derived from cryo-electron microscopy reveals a cryptic pocket site in intermediate states along the opening pathway of the SARS-CoV-2 spike protein.

Clinical, neuroimaging, and molecular spectrum of TECPR2-associated hereditary sensory and autonomic neuropathy with intellectual disability

Bi-allelic TECPR2 variants have been associated with a complex syndrome with features of both a neurodevelopmental and neurodegenerative disorder. Here, we provide a comprehensive clinical description and variant interpretation framework for this genetic locus. Through international collaboration, we identified 17 individuals from 15 families with bi-allelic TECPR2-variants. We systemically reviewed clinical and molecular data from this cohort and 11 cases previously reported. Phenotypes were standardized using Human Phenotype Ontology terms. A cross-sectional analysis revealed global developmental delay/intellectual disability, muscular hypotonia, ataxia, hyporeflexia, respiratory infections, and central/nocturnal hypopnea as core manifestations. A review of brain magnetic resonance imaging scans demonstrated a thin corpus callosum in 52%. We evaluated 17 distinct variants. Missense variants in TECPR2 are predominantly located in the N- and C-terminal regions containing β-propeller repeats. Despite constituting nearly half of disease-associated TECPR2 variants, classifying missense variants as (likely) pathogenic according to ACMG criteria remains challenging. We estimate a pathogenic variant carrier frequency of 1/1221 in the general and 1/155 in the Jewish Ashkenazi populations. Based on clinical, neuroimaging, and genetic data, we provide recommendations for variant reporting, clinical assessment, and surveillance/treatment of individuals with TECPR2-associated disorder. This sets the stage for future prospective natural history studies.

Dynamic Interactions of Fully Glycosylated SARS-CoV-2 Spike Protein with Various Antibodies

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a public health crisis, and the vaccines that can induce highly potent neutralizing antibodies are essential for ending the pandemic. The spike (S) protein on the viral envelope mediates human angiotensin-converting enzyme 2 (ACE2) binding and thus is the target of a variety of neutralizing antibodies. In this work, we built various S trimer-antibody complex structures on the basis of the fully glycosylated S protein models described in our previous work, and performed all-atom molecular dynamics simulations to get insight into the structural dynamics and interactions between S protein and antibodies. Investigation of the residues critical for S-antibody binding allows us to predict the potential influence of mutations in SARS-CoV-2 variants. Comparison of the glycan conformations between S-only and S-antibody systems reveals the roles of glycans in S-antibody binding. In addition, we explored the antibody binding modes, and the influences of antibody on the motion of S protein receptor binding domains. Overall, our analyses provide a better understanding of S-antibody interactions, and the simulation-based S-antibody interaction maps could be used to predict the influences of S mutation on S-antibody interactions, which will be useful for the development of vaccine and antibody-based therapy.

Potential aggregation hot spots in recombinant human keratinocyte growth factor: a computational study

The recombinant human keratinocyte growth factor (rhKGF) is a highly aggregation-prone therapeutic protein. The high aggregation liability of rhKGF is manifested by loss of the monomeric state, and accumulation of the aggregated species even at moderate temperatures. Here, we analyzed the rhKGF for its vulnerability toward aggregation by detection of aggregation-prone regions (APRs) using several sequence-based computational tools including TANGO, ZipperDB, AGGRESCAN, Zyggregator, Camsol, PASTA, SALSA, WALTZ, SODA, Amylpred, AMYPDB, and structure-based tools including SolubiS, CamSol structurally corrected, Aggrescan3D and spatial aggregation propensity (SAP) algorithm. The sequence-based prediction of APRs in rhKGF indicated that they are mainly located at positions 10-30, 40-60, 61-66, 88-120, and 130-140. Mapping on the rhKGF structure revealed that most of these residues including F16-R25, I43, E45, R47-I56, F61, Y62, N66, L88-E91, E108-F110, A112, N114, T131, and H133-T140 are surface-exposed in the native state which can promote aggregation without major unfolding event, or the conformational change may occur in the oligomers. The other regions are buried in the native state and their contribution to non-native aggregation is mediated by a preceding unfolding event. The structure-based prediction of APRs using the SAP tool limited the number of identified APRs to the dynamically-exposed hydrophobic residues including V12, A50, V51, L88, I89, L90, I118, L135, and I139 mediating the native-state aggregation. Our analysis of APRs in rhKGF identified the regions determining the intrinsic aggregation propensity of the rhKGF which are the candidate positions for engineering the rhKGF to reduce its aggregation tendency.Communicated by Ramaswamy H. Sarma.

Structure, Dynamics, Receptor Binding, and Antibody Binding of the Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein in a Viral Membrane

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediates host cell entry by binding to angiotensin-converting enzyme 2 (ACE2) and is considered the major target for drug and vaccine development. We previously built fully glycosylated full-length SARS-CoV-2 S protein models in a viral membrane including both open and closed conformations of the receptor-binding domain (RBD) and different templates for the stalk region. In this work, multiple μs-long all-atom molecular dynamics simulations were performed to provide deeper insights into the structure and dynamics of S protein and glycan functions. Our simulations reveal that the highly flexible stalk is composed of two independent joints and most probable S protein orientations are competent for ACE2 binding. We identify multiple glycans stabilizing the open and/or closed states of the RBD and demonstrate that the exposure of antibody epitopes can be captured by detailed antibody–glycan clash analysis instead of commonly used accessible surface area analysis that tends to overestimate the impact of glycan shielding and neglect possible detailed interactions between glycan and antibodies. Overall, our observations offer structural and dynamic insights into the SARS-CoV-2 S protein and potentialize for guiding the design of effective antiviral therapeutics.

Glycan Cluster Shielding and Antibody Epitopes on Lassa Virus Envelop Protein

An understanding of how an antiviral monoclonal antibody recognizes its target is vital for the development of neutralizing antibodies and vaccines. The extensive glycosylation of viral proteins almost certainly affects the antibody response, but the investigation of such effects is hampered by the huge range of structures and interactions of surface glycans through their inherent complexity and flexibility. Here, we built an atomistic model of a fully glycosylated envelope protein complex of the Lassa virus and performed molecular dynamics simulations to characterize the impact of surface glycans on the antibody response. The simulations attested to the variety of conformations and interactions of surface glycans. The results show that glycosylation nonuniformly shields the surface of the complex and only marginally affects protein dynamics. The glycans gather in distinct clusters through interaction with protein residues, and only a few regions are left accessible by an antibody. We successfully recovered known protein epitopes by integrating the simulation results with existing sequence- and structure-based epitope prediction methods. The results emphasize the rich structural environment of glycans and demonstrate that shielding is not merely envelopment by a uniform blanket of sugars. This work provides a molecular basis for integrating otherwise elusive structural properties of glycans into vaccine and neutralizing antibody developments.

A synthetic diterpene analogue inhibits mycobacterial persistence and biofilm formation by targeting (p)ppGpp synthetases

Bacterial persistence coupled with biofilm formation is directly associated with failure of antibiotic treatment of tuberculosis. We have now identified 4-(4,7-DiMethyl-1,2,3,4-tetrahydroNaphthalene-1-yl)Pentanoic acid (DMNP), a synthetic diterpene analogue, as a lead compound that was capable of suppressing persistence and eradicating biofilms in Mycobacterium smegmatis. By using two reciprocal experimental approaches - Δrel_Msm and ΔrelZ gene knockout mutations versus rel_Msm and relZ overexpression technique - we showed that both Rel_Msm and RelZ (p)ppGpp synthetases are plausible candidates for serving as targets for DMNP. In vitro, DMNP inhibited (p)ppGpp-synthesizing activity of purified Rel_Msm in a concentration-dependent manner. These findings, supplemented by molecular docking simulation, suggest that DMNP targets the structural sites shared by Rel_Msm, RelZ, and presumably by a few others as yet unidentified (p)ppGpp producers, thereby inhibiting persister cell formation and eradicating biofilms. Therefore, DMNP may serve as a promising lead for development of antimycobacterial drugs.

Identification of homozygous mutations for hearing loss

BACKGROUND

Hearing loss is the most common sensory disorder worldwide, affecting about 1 out of every 1000 newborns. The disease has major genetic components, and can be inherited as a single gene disorder either in autosomal dominant or recessive fashions. Due to the high rate of consanguineous unions, Iran has one of the highest prevalence of autosomal recessive nonsyndromic deafness (ARNSD) in the world.

METHODS

We carried out a genetic screening of ten Iranian kindreds with more than one offspring affected by ARNSD caused by consanguineous unions. Sanger sequencing and whole exome sequencing together with in silico 3D structure modeling and protein stability prediction were used to identify the underlying disease causing genes.

CONCLUSION

We identified the causes of deafness in all 10 kindred. In six kindreds homozygous mutations were identified in GJB2 gene by Sanger sequencing. By using whole exome sequencing (WES), a homozygous missense mutation was identified in ESRRB gene as the first ever reported disease gene in Iran. Also two novel homozygous frameshift and missense mutations were identified in MYO15A gene and one previously reported mutation in TMC1 gene in three independent kindred. Our study shows the efficacy of WES for unraveling new pathogenic mutations in ARNSD patients and expands the spectrum of genes contributing to ARNSD in the Iranian population. The findings of our study can facilitate future genetic screening of patients with ARNSD , early screening and optimal design of novel therapeutics.

Elucidation of interactions regulating conformational stability and dynamics of SARS-CoV-2 S-protein

The ongoing COVID-19 pandemic caused by the new coronavirus, SARS-CoV-2, calls for urgent developments of vaccines and antiviral drugs. The spike protein of SARS-CoV-2 (S-protein), which consists of trimeric polypeptide chains with glycosylated residues on the surface, triggers the virus entry into a host cell. Extensive structural and functional studies on this protein have rapidly advanced our understanding of the S-protein structure at atomic resolutions, although most of these structural studies overlook the effect of glycans attached to the S-protein on the conformational stability and functional motions between the inactive down and active up forms. Here, we performed all-atom molecular dynamics simulations of both down and up forms of a fully glycosylated S-protein in solution as well as targeted molecular dynamics simulations between them to elucidate key interdomain interactions for stabilizing each form and inducing the large-scale conformational transitions. The residue-level interaction analysis of the simulation trajectories detects distinct amino acid residues and N-glycans as determinants on conformational stability of each form. During the conformational transitions between them, interdomain interactions mediated by glycosylated residues are switched to play key roles on the stabilization of another form. Electrostatic interactions, as well as hydrogen bonds between the three receptor binding domains, work as driving forces to initiate the conformational transitions toward the active form. This study sheds light on the mechanisms underlying conformational stability and functional motions of the S-protein, which are relevant for vaccine and antiviral drug developments.

Biochemical Characterization and Functional Analysis of Heat Stable High Potential Protease of Bacillus amyloliquefaciens Strain HM48 from Soils of Dachigam National Park in Kashmir Himalaya

A novel temperature stable alkaline protease yielding bacteria was isolated from the soils of Dachigam National Park, which is known to be inhabited by a wide variety of endemic plant and animal species of Western Himalaya. This high-potential protease producing isolate was characterized and identified as Bacillus amyloliquefaciens strain HM48 by morphological, Gram’s staining and biochemical techniques followed by molecular characterization using 16S rRNA approach. The extracellular protease of B. amyloliquefaciens HM48 was purified by precipitating with ammonium sulfate (80%), followed by dialysis and Gel filtration chromatography increasing its purity by 5.8-fold. The SDS–PAGE analysis of the purified enzyme confirmed a molecular weight of about ≈25 kDa. The enzyme displayed exceptional activity in a broad temperature range (10–90 °C) at pH 8.0, retaining its maximum at 70 °C, being the highest reported for this proteolytic Bacillus sp., with K_M and V_max of 11.71 mg/mL and 357.14 µmol/mL/min, respectively. The enzyme exhibited remarkable activity and stability against various metal ions, surfactants, oxidizing agent (H₂O₂), organic solvents and displayed outstanding compatibility with widely used detergents. This protease showed effective wash performance by exemplifying complete blood and egg-yolk stains removal at 70 °C and efficiently disintegrated chicken feathers making it of vital importance for laundry purpose and waste management. For functional analysis, protease gene amplification of strain HM48 yielded a nucleotide sequence of about 700 bp, which, when checked against the available sequences in NCBI, displayed similarity with subtilisin-like serine protease of B. amyloliquefaciens. The structure of this protease and its highest-priority substrate β-casein was generated through protein modeling. These protein models were validated through futuristic algorithms following which protein–protein (protease from HM48 and β-casein) docking was performed. The interaction profile of these proteins in the docked state with each other was also generated, shedding light on their finer details. Such attributes make this thermally stable protease novel and suitable for high-temperature industrial and environmental applications.

Methods for Molecular Modelling of Protein Complexes

Biological processes are often mediated by complexes formed between proteins and various biomolecules. The 3D structures of such protein-biomolecule complexes provide insights into the molecular mechanism of their action. The structure of these complexes can be predicted by various computational methods. Choosing an appropriate method for modelling depends on the category of biomolecule that a protein interacts with and the availability of structural information about the protein and its interacting partner. We intend for the contents of this chapter to serve as a guide as to what software would be the most appropriate for the type of data at hand and the kind of 3D complex structure required. Particularly, we have dealt with protein-small molecule ligand, protein-peptide, protein-protein, and protein-nucleic acid interactions.Most, if not all, model building protocols perform some sampling and scoring. Typically, several alternate conformations and configurations of the interactors are sampled. Each such sample is then scored for optimization. To boost the confidence in these predicted models, their assessment using other independent scoring schemes besides the inbuilt/default ones would prove to be helpful. This chapter also lists such software and serves as a guide to gauge the fidelity of modelled structures of biomolecular complexes.

Homology modeling in the time of collective and artificial intelligence

Homology modeling is a method for building protein 3D structures using protein primary sequence and utilizing prior knowledge gained from structural similarities with other proteins. The homology modeling process is done in sequential steps where sequence/structure alignment is optimized, then a backbone is built and later, side-chains are added. Once the low-homology loops are modeled, the whole 3D structure is optimized and validated. In the past three decades, a few collective and collaborative initiatives allowed for continuous progress in both homology and ab initio modeling. Critical Assessment of protein Structure Prediction (CASP) is a worldwide community experiment that has historically recorded the progress in this field. Folding@Home and Rosetta@Home are examples of crowd-sourcing initiatives where the community is sharing computational resources, whereas RosettaCommons is an example of an initiative where a community is sharing a codebase for the development of computational algorithms. Foldit is another initiative where participants compete with each other in a protein folding video game to predict 3D structure. In the past few years, contact maps deep machine learning was introduced to the 3D structure prediction process, adding more information and increasing the accuracy of models significantly. In this review, we will take the reader in a journey of exploration from the beginnings to the most recent turnabouts, which have revolutionized the field of homology modeling. Moreover, we discuss the new trends emerging in this rapidly growing field.

Developing a Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein Model in a Viral Membrane

This technical study describes all-atom modeling and simulation of a fully glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB: 6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19) so that researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.

In Silico Approach in Designing a Novel Multi-Epitope Vaccine Candidate against Non-Small Cell Lung Cancer with Overexpressed G Protein-Coupled Receptor 56

Background:

Majority of cancer-related deaths worldwide is attributed to non-small cell lung cancer (NSCLC). G protein-coupled receptor 56 (GPR56) is overexpressed and associated in the progression of NSCLC. The aim of this study is to use immunoinformatics approach in designing a multi-epitope vaccine to target overexpressed GPR56 which can potentially activate antibody-mediated cell death mechanisms and inhibit pathways involved in the proliferation, migration and survival of NSCLC.

Methods:

Herein, the reported overexpression of GPR56 was further investigated by conducting a differential gene expression analysis of NSCLC samples from GEO DataSets (GSE29249). Results confirmed significant overexpression of GPR56 in NSCLC compared to adjacent normal samples. A multi-epitope vaccine (Fvax) was constructed in silico by adjoining B lymphocytes (BL) and helper T lymphocytes (HTL) epitopes from the extracellular sequence of GPR56. Population coverage (PC) of HTL epitopes was also estimated. To enhance its immunogenicity, sequences of flagellin domains were fused as adjuvant. Fvax was evaluated in silico for antigenicity, allergenicity, peptide toxicity, physicochemical properties and cross-reactivity. Its tertiary structure was predicted, refined, and validated followed by structural epitope prediction. Lastly, Fvax DNA was optimized and cloned in silico.

Results:

This is the first work to design a potential vaccine against GPR56-overexpressing NSCLC. Fvax has 3 BL and 7 HTL immunogenic epitopes on GPR56. In silico evaluations suggest that Fvax is antigenic, non-toxic, non-allergenic, stable, and has accessible BL epitopes with high PC worldwide for HTL epitopes.

Conclusion:

Overall, results showed that Fvax is a potential vaccine against NSCLC. The approach of this study efficiently minimized the number of tests, cost and time required to select the best epitopes and to design a vaccine for the treatment of NSCLC.

Developing a Fully-glycosylated Full-length SARS-CoV-2 Spike Protein Model in a Viral Membrane

This technical study describes all-atom modeling and simulation of a fully-glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB:6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently-determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully-glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19), so researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.

Improved Consensus-Fragment Selection in Template-Assisted Prediction of Protein Structures with the UNRES Force Field in CASP13

The method for protein-structure prediction, which combines the physics-based coarse-grained UNRES force field with knowledge-based modeling, has been developed further and tested in the 13th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP13). The method implements restraints from the consensus fragments common to server models. In this work, the server models to derive fragments have been chosen on the basis of quality assessment; a fully automatic fragment-selection procedure has been introduced, and Dynamic Fragment Assembly pseudopotentials have been fully implemented. The Global Distance Test Score (GDT_TS), averaged over our “Model 1” predictions, increased by over 10 units with respect to CASP12 for the free-modeling category to reach 40.82. Our “Model 1” predictions ranked 20 and 14 for all and free-modeling targets, respectively (upper 20.2% and 14.3% of all models submitted to CASP13 in these categories, respectively), compared to 27 (upper 21.1%) and 24 (upper 18.9%) in CASP12, respectively. For oligomeric targets, the Interface Patch Similarity (IPS) and Interface Contact Similarity (ICS) averaged over our best oligomer models increased from 0.28 to 0.36 and from 12.4 to 17.8, respectively, from CASP12 to CASP13, and top-ranking models of 2 targets (H0968 and T0997o) were obtained (none in CASP12). The improvement of our method in CASP13 over CASP12 was ascribed to the combined effect of the overall enhancement of server-model quality, our success in selecting server models and fragments to derive restraints, and improvements of the restraint and potential-energy functions.

Prediction of protein oligomer structures using GALAXY in CASP13

Many proteins need to form oligomers to be functional, so oligomer structures provide important clues to biological roles of proteins. Prediction of oligomer structures therefore can be a useful tool in the absence of experimentally resolved structures. In this article, we describe the server and human methods that we used to predict oligomer structures in the CASP13 experiment. Performances of the methods on the 42 CASP13 oligomer targets consisting of 30 homo-oligomers and 12 hetero-oligomers are discussed. Our server method, Seok-assembly, generated models with interface contact similarity measure greater than 0.2 as model 1 for 11 homo-oligomer targets when proper templates existed in the database. Model refinement methods such as loop modeling and molecular dynamics (MD)-based overall refinement failed to improve model qualities when target proteins have domains not covered by templates or when chains have very small interfaces. In human predictions, additional experimental data such as low-resolution electron microscopy (EM) map were utilized. EM data could assist oligomer structure prediction by providing a global shape of the complex structure.

GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure

Homo-oligomerization of proteins is abundant in nature, and is often intimately related with the physiological functions of proteins, such as in metabolism, signal transduction or immunity. Information on the homo-oligomer structure is therefore important to obtain a molecular-level understanding of protein functions and their regulation. Currently available web servers predict protein homo-oligomer structures either by template-based modeling using homo-oligomer templates selected from the protein structure database or by ab initio docking of monomer structures resolved by experiment or predicted by computation. The GalaxyHomomer server, freely accessible at http://galaxy.seoklab.org/homomer, carries out template-based modeling, ab initio docking or both depending on the availability of proper oligomer templates. It also incorporates recently developed model refinement methods that can consistently improve model quality. Moreover, the server provides additional options that can be chosen by the user depending on the availability of information on the monomer structure, oligomeric state and locations of unreliable/flexible loops or termini. The performance of the server was better than or comparable to that of other available methods when tested on benchmark sets and in a recent CASP performed in a blind fashion.

GalaxyTongDock: Symmetric and asymmetric ab initio protein-protein docking web server with improved energy parameters

Protein-protein docking methods are spotlighted for their roles in providing insights into protein-protein interactions in the absence of full structural information by experiment. GalaxyTongDock is an ab initio protein-protein docking web server that performs rigid-body docking just like ZDOCK but with improved energy parameters. The energy parameters were trained by iterative docking and parameter search so that more native-like structures are selected as top rankers. GalaxyTongDock performs asymmetric docking of two different proteins (GalaxyTongDock_A) and symmetric docking of homo-oligomeric proteins with C_n and D_n symmetries (GalaxyTongDock_C and GalaxyTongDock_D). Performance tests on an unbound docking benchmark set for asymmetric docking and a model docking benchmark set for symmetric docking showed that GalaxyTongDock is better or comparable to other state-of-the-art methods. Experimental and/or evolutionary information on binding interfaces can be easily incorporated by using block and interface options. GalaxyTongDock web server is freely available at http://galaxy.seoklab.org/tongdock. © 2019 Wiley Periodicals, Inc.

Novel Compound Heterozygote Mutation in IL10RA in a Patient With Very Early-Onset Inflammatory Bowel Disease

BACKGROUND

Very early-onset inflammatory bowel disease (VEO-IBD) is often associated with monogenetic disorders. IL-10RA deficiency is one of the major causal mutations in VEO-IBD. Here, we aimed to identify the causal mutation associated with severe IBD in a 1-year-old patient, validate the pathogenicity of the mutation, and characterize the mutant protein.

METHODS

To identify the causal mutation, targeted exome sequencing (ES) was performed using the genomic DNA from the patient. To validate the pathogenicity, IL-10RA functional tests were performed using the patient's peripheral blood mononuclear cells (PBMCs). Additionally, flow cytometry analysis, confocal microscopy on overexpressed green fluorescent protein-fused mutants, and computational analysis on the structures of IL-10RA proteins were performed.

RESULTS

We identified a novel compound heterozygote mutation p.[Tyr91Cys];[Pro146Alafs*40] in the IL10RA gene of the patient. The missense variant p.Tyr91Cys was previously identified but not functionally tested, and a frameshift variant, p.Pro146Alafs*40, is novel and nonfunctional. PBMCs from the patient showed defective signal transducer and activator of transcription 3 activation. The p.Tyr91Cys mutant protein failed to properly localize on the plasma membrane. The p.Tyr91Cys mutation seems to disrupt the hydrophobic core structure surrounding the tyrosine 91 residue, causing structural instability.

CONCLUSIONS

Targeted ES and linkage analysis identified novel compound heterozygous mutations p.[Tyr91Cys];[Pro146Alafs*40] in the IL10RA gene of a child with severe VEO-IBD. p.Tyr91Cys proteins were functionally defective in IL-10RA signaling and failed to properly localize on the plasma membrane, probably due to its structural instability.

Large-scale docking predicts that sORF-encoded peptides may function through protein-peptide interactions in Arabidopsis thaliana

Several recent studies indicate that small Open Reading Frames (sORFs) embedded within multiple eukaryotic non-coding RNAs can be translated into bioactive peptides of up to 100 amino acids in size. However, the functional roles of the 607 Stress Induced Peptides (SIPs) previously identified from 189 Transcriptionally Active Regions (TARs) in Arabidopsis thaliana remain unclear. To provide a starting point for functional annotation of these plant-derived peptides, we performed a large-scale prediction of peptide binding sites on protein surfaces using coarse-grained peptide docking. The docked models were subjected to further atomistic refinement and binding energy calculations. A total of 530 peptide-protein pairs were successfully docked. In cases where a peptide encoded by a TAR is predicted to bind at a known ligand or cofactor-binding site within the protein, it can be assumed that the peptide modulates the ligand or cofactor-binding. Moreover, we predict that several peptides bind at protein-protein interfaces, which could therefore regulate the formation of the respective complexes. Protein-peptide binding analysis further revealed that peptides employ both their backbone and side chain atoms when binding to the protein, forming predominantly hydrophobic interactions and hydrogen bonds. In this study, we have generated novel predictions on the potential protein-peptide interactions in A. thaliana, which will help in further experimental validation.

Immune-Informatic Analysis and Design of Peptide Vaccine From Multi-epitopes Against Corynebacterium pseudotuberculosis

Caseous lymphadenitis (CLA) is a disease caused by Corynebacterium pseudotuberculosis bacteria that affects sheep and goats. The absence of a serologic diagnose is a factor that contributes for the disease dissemination, and due to the formation of granuloma, the treatment is very expensive. Therefore, prophylaxis is the approach with best cost-benefit relation; however, it still lacks an effective vaccine. In this sense, this work seeks to apply bioinformatic tools to design an effective vaccine against CLA, using CP40 protein as standard for the design of immunodominant epitopes, from which a total of 6 sequences were obtained, varying from 10 to 16 amino acid residues. The evaluation of different properties of the vaccines showed that the vaccine is a potent and nonallergenic antigen remaining stable in a wide range of temperatures. The initial tertiary structure of the vaccine was then predicted and a model selected. Later, the process of CP40 protein and TLR2 receptor binding was performed, presenting interaction with this receptor, which plays an important role in the activation of the immune response.

Assessment of the transmembrane domain structures in GPCR Dock 2013 models

The community-wide blind prediction of G-protein coupled receptor (GPCR) structures and ligand docking has been conducted three times and the quality of the models was primarily assessed by the accuracy of ligand binding modes. The seven transmembrane (TM) helices of the receptors were taken as a whole; thus the model quality within the 7TM domains has not been evaluated. Here we evaluate the 7TM domain structures in the models submitted for the last round of prediction - GPCR Dock 2013. Applying the 7 × 7 RMSD matrix analysis described in our prior work, we show that the models vary widely in prediction accuracy of the 7TM structures, exhibiting diverse structural differences from the targets. For the prediction of the 5-hydroxytryptamine receptors, the top 7TM models are rather close to the targets, which however are not ranked top by ligand-docking. On the other hand, notable deviations of the TMs are found in in the previously identified top docking models that closely resemble other receptors. We further reveal reasons of success and failure in ligand docking for the models. This current assessment not only complements the previous assessment, but also provides important insights into the current status of GPCR modeling and ligand docking.