Homology modeling and virtual screening approaches to identify potent inhibitors of VEB-1 β-lactamase

Development, validation and analysis of a human profurin 3D model using comparative modeling and molecular dynamics simulations

The emergence of new viruses can lead to the outbreak of pandemics as occurred at the end of 2019 with the coronavirus disease (or COVID-19). The fastest way to effectively control viral infections is to develop broad-spectrum antivirals that can fight at least an entire class of viruses. Profurin, the furin precursor propeptide, is responsible for the autoactivation step which is crucial for the maturation of several viral substrates. This role makes the study of furin and profurin interactions interesting for the development of new potential broad-spectrum antivirals for the treatment against several human viral diseases. Since there is no 3D model of profurin published in the literature or deposited in a database, this work reports the development, validation and analysis of a profurin 3D model using comparative modeling and molecular dynamics. The model is available in ModelArchive at https://www.modelarchive.org/doi/10.5452/ma-ct8l7. The usage of this model will make possible further studies of molecular docking and MD simulations of the profurin-furin system, in the design of new potential broad-spectrum antivirals for the treatment against several human viral diseases.Communicated by Ramaswamy H. Sarma.

Leveraging Bidirectional Nature of Allostery To Inhibit Protein-Protein Interactions (PPIs): A Case Study of PCSK9-LDLR Interaction

The protein PCSK9 (proprotein convertase subtilisin/Kexin type 9) negatively regulates the recycling of LDLR (low-density lipoprotein receptor), leading to an elevated plasma level of LDL. Inhibition of PCSK9-LDLR interaction has emerged as a promising therapeutic strategy to manage hypercholesterolemia. However, the large interaction surface area between PCSK9 and LDLR makes it challenging to identify a small molecule competitive inhibitor. An alternative strategy would be to identify distal cryptic sites as targets for allosteric inhibitors that can remotely modulate PCSK9-LDLR interaction. Using several microseconds long molecular dynamics (MD) simulations, we demonstrate that on binding with LDLR, there is a significant conformational change (population shift) in a distal loop (residues 211-222) region of PCSK9. Consistent with the bidirectional nature of allostery, we establish a clear correlation between the loop conformation and the binding affinity with LDLR. Using a thermodynamic argument, we establish that the loop conformations predominantly present in the apo state of PCSK9 would have lower LDLR binding affinity, and they would be potential targets for designing allosteric inhibitors. We elucidate the molecular origin of the allosteric coupling between this loop and the LDLR binding interface in terms of the population shift in a set of salt bridges and hydrogen bonds. Overall, our work provides a general strategy toward identifying allosteric hotspots: compare the conformational ensemble of the receptor between the apo and bound states of the protein and identify distal conformational changes, if any. The inhibitors should be designed to bind and stabilize the apo-specific conformations.

Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

A Multi-epitope Vaccine Candidate Against Bolivian Hemorrhagic fever Caused by Machupo Virus

Bolivian hemorrhagic fever (BHF) caused by Machupo virus (MACV) is a New World arenavirus having a reported mortality rate of 25-35%. The BHF starts with fever, followed by headache, and nausea which rapidly progresses to severe hemorrhagic phase within 7 days of disease onset. One of the key promoters for MACV viral entry into the cell followed by viral propagation is performed by the viral glycoprotein (GPC). GPC is post-transcriptionally cleaved into GP1, GP2 and a signal peptide. These proteins all take part in the viral infection in host body. Therefore, GPC protein is an ideal target for developing therapeutics against MACV infection. In this study, GPC protein was considered to design a multi-epitope, multivalent vaccine containing antigenic and immunogenic CTL and HTL epitopes. Different structural validations and physicochemical properties were analysed to validate the vaccine. Docking and molecular dynamics simulations were conducted to understand the interactions of the vaccine with various immune receptors. Finally, the vaccine was codon optimised in silico and along with which immune simulation studies was performed in order to evaluate the vaccine's effectiveness in triggering an efficacious immune response against MACV.

Molecular interactions of paraben family of pollutants with embryonic neuronal proteins of Danio rerio: A step ahead in computational toxicity towards adverse outcome pathway

The paraben family of endocrine disruptors exhibit persistent behaviours in aquatic matrices, having bio-accumulative effects and necessitating toxicity analysis and safe use, as well as prevention of food web penetration. In this study, the toxicity effects of 9 different parabens (Methyl, Ethyl, Propyl, Butyl, Heptyl, Isopropyl, Isobutyl, benzyl parabens and p-hydroxybenzoic acid) were studied against 17 neuronal proteins (Neurog1, Ascl1a, DLA, Syn2a, Ntn1a, Pitx2, and SoxB1, Her/Hes, Zic family) expressed during the early embryonic developmental stage of Danio rerio. The neuronal genes were selected as a biomarker to study the inhibitory effects on the cascade of genes expressed in the early developmental stage. The study uses trRossetta software to predict protein structures of neuronal genes, followed by structural refinement, energy minimisation, and active site prediction, evaluated using energy value, RC plot and ERRAT scores of PROCHECK and ERRAT programs. Compared to raw structures, highly confident predicted structures and quality scores were observed for refined protein with few exceptions. Based on the polarity and charge of the aminoacids, the probable pockets were identified using active site prediction, which were then used for molecular docking analysis. Further, the ADMET analysis, ligand likeliness and toxicological test revealed the paraben family of compounds as one of the most susceptible toxic and mutagenic compounds. The molecular docking results showed an interesting pattern of increasing binding affinity with increase in the carbon chains of paraben molecules. Benzyl Paraben showed higher binding affinities across all 17 neuronal proteins. Finally, gene co-occurrence/co-expression and protein-protein interaction studies using the STRING database depict that all proteins are functionally related and play essential roles in standard biological processes or pathways, conserved and expressed in diverse organisms. The interaction between paraben compounds and neuronal genes indicates high risks of inhibiting reactions in embryonic stages, emphasising the need for effective treatment measures and strict regulations.

Molecular cloning and heterologous expression analysis of 1-Deoxy-D-Xylulose-5-Phosphate Synthase gene in Centella asiatica L

Many genes involved in triterpenoid saponins in plants control isoprenoid flux and constitute the precursor pool, which is channeled into various downstream pathways leading to the synthesis of triterpenoid saponins in C. asiatica. Full-length 1-Deoxy-D-Xylulose-5-Phosphate-Synthase (CaDXS) gene was isolated for the study from the previously annotated Centella asiatica leaves transcriptomic data. The CaDXS gene sequence was submitted to the NCBI databases with GenBank accession number MZ997832. The full-length CaDXS gene contained a 2244 base pair open reading frame that encoded a 747 amino acid polypeptide. The predicted molecular weight (MW) and theoretical pI of DXS are 76.28 kDa and 6.86, respectively. Multiple amino acid sequence alignment of amino acids and phylogenetic studies suggest that CaDXS shares high similarities with DXS from other plants DXS belonging to different families. A phylogenetic tree was constructed using Molecular Evolutionary Genetic Analysis (MEGA) version 10.1.6. Structural analysis provided fundamental information about the three-dimensional features and physicochemical parameters of the CaDXS protein. Quantitative expression analysis showed that CaDXS transcripts were maximally expressed in leaf, followed by petiole, roots, and node tissues. CaDXS was cloned into the expression vector pET28a, expressed heterologously in DH5α bacteria, confirmed by sequencing, and subsequently characterized by protein expression and functional complementation. The study focused on understanding the protein structure, biological significance, regulatory mechanism, functional analysis, and gene characterization of the centellosides biosynthetic pathway gene DXS for the first time in the plant. It would provide new information about the metabolic pathway and its relative contribution to isoprenoid biosynthesis.

HIV-1 Vif protein sequence variations in South African people living with HIV and their influence on Vif-APOBEC3G interaction

PURPOSE

Despite extensive research, HIV-1 remains a global epidemic with variations in pathogenesis across regions and subtypes. The Viral Infectivity Factor (Vif) protein, which neutralizes the host protein APOBEC3G, has been implicated in differences in clinical outcomes among people living with HIV (PLHIV). Most studies on Vif sequence diversity have focused on subtype B, leaving gaps in understanding Vif variations in HIV-1C regions like South Africa. This study aimed to identify and compare Vif sequence diversity in a cohort of 51 South African PLHIV and other HIV-1C prevalent regions.

METHODS

Sanger sequencing was used for Vif analysis in the cohort, and additional sequences were obtained from the Los Alamos database. Molecular modeling and docking techniques were employed to study the influence of subtype-specific variants on Vif-APOBEC3G binding affinity.

RESULTS

The findings showed distinct genetic variations between Vif sequences from India and Uganda, while South African sequences had wider distribution and closer relatedness to both. Specific amino acid substitutions in Vif were associated with geographic groups. Molecular modeling and docking analyses consistently identified specific residues (ARGR19, LYS26, TYR30, TYR44, and TRP79) as primary contributors to intermolecular contacts between Vif and APOBEC3G, essential for their interaction. The Indian Vif variant exhibited the highest predicted binding affinity to APOBEC3G among the studied groups.

CONCLUSIONS

These results provide insights into Vif sequence diversity in HIV-1C prevalent regions and shed light on differential pathogenesis observed in different geographical areas. The identified Vif amino acid residues warrant further investigation for their diagnostic, prognostic, and therapeutic potential.

Development of Moloney Murine Leukemia Virus Reverse Transcriptase Fused with Archaeal DNA-binding Protein Sis7a

INTRODUCTION

Moloney Murine Leukemia Virus Reverse Transcriptase (MMLV RT) is a common enzyme used to convert RNA sequences into cDNA. However, it still has its shortcomings, especially in terms of processivity and thermostability. According to a previous patent, the fusion of polymerase enzyme to an archaeal DNA-binding protein has been proven to enhance its performance. Furthermore, recent studies have also stated that the fusion of a polymerase enzyme to an archaeal DNA-binding protein is predicted to improve its thermostability and processivity.

AIM

As an early stage of enzyme development, this study aimed to design, express, and purify enzymatically active MMLV RT fused with archaeal DNA-binding protein.

METHODS

RT fusion proteins were designed and evaluated using in silico methods. The RT fusion enzyme was then expressed in Escherichia coli BL21(DE3) and purified. Its reverse transcriptional activity was proved using reverse transcription quantitative polymerase chain reaction (RT-qPCR).

RESULTS

This study showed that MMLV RT fusion with Sis7a protein at its C-terminal end using commercial linker (GGVDMI) produced the best in silico evaluation results. The RT fusion was successfully expressed and purified. It was also known that the optimal condition for expression of the RT fusion was using 0.5 mM IPTG with post-induction incubation at room temperature (± 26°C) for 16 hours. In addition, the activity assay proved that the RT fusion has the reverse transcriptional activity.

CONCLUSION

This study shows that the designed MMLV RT Sis7a fusion can be expressed and purified, is enzymatically active, and has the potential to be developed as an improved RT enzyme. Further study is still needed to prove its thermostability and processivity, and further characterize, and plan production scale-up of the MMLV RT Sis7a fusion for commercial use.

Immunoinformatics Prediction and Protective Efficacy of Vaccine Candidate PiuA-PlyD4 Against Streptococcus Pneumoniae

Purpose

This study was designed to evaluate the immune protective efficacy of the novel Streptococcus pneumoniae (S. pneumoniae) protein vaccine PiuA-PlyD4 through immunoinformatics prediction and in vitro and in vivo experiments.

Methods

In this study, we conducted immunoinformatics prediction and protection analysis on the fusion protein PiuA-PlyD4. The epitope composition of the vaccine was analyzed based on the prediction of B-cell and helper T-cell epitopes. Meanwhile, the molecular docking of PiuA and TLR2/4 was simulated. After immunizing C57BL/6 mice with the prepared vaccine, the biological safety, immunogenicity and conservation were evaluated. By constructing different infection models and from the aspects of adhesion inhibition and cytokines, the protective effect of the fusion protein vaccine PiuA-PlyD4 on S. pneumoniae infection was explored.

Results

PiuA-PlyD4 has abundant B-cell and helper T-cell epitopes and shows a high antigenicity score and structural stability. Molecular docking analysis suggested the potential interaction between PiuA and TLR2/4. The specific antibody titer of fusion protein antiserum was as high as (7.81±2.32) ×105. The protective effect of the immunized mice on nasal and lung colonization was significantly better than that of the control group, and the survival rate against S. pneumoniae infection of serotype 3 reached 50%. Cytokine detection showed that the humoral immune response, Th1, Th2 and Th17 cellular immune pathways were all involved in the process.

Conclusion

The study indicates that PiuA-PlyD4, whether the results are predicted by immunoinformatics or experimentally validated in vivo and in vitro, has good immunogenicity and immunoreactivity and can provide effective protection against S. pneumoniae infection. Therefore, it can be considered a promising prophylactic vaccine candidate for S. pneumoniae.

Uncovering the hidden threat: The widespread presence of chromosome-borne accessory genetic elements and novel antibiotic resistance genetic environments in Aeromonas

The emergence of antibiotic-resistant Aeromonas strains in clinical settings has presented an escalating burden on human and public health. The dissemination of antibiotic resistance in Aeromonas is predominantly facilitated by chromosome-borne accessory genetic elements, although the existing literature on this subject remains limited. Hence, the primary objective of this study is to comprehensively investigate the genomic characteristics of chromosome-borne accessory genetic elements in Aeromonas. Moreover, the study aims to uncover novel genetic environments associated with antibiotic resistance on these elements. Aeromonas were screened from nonduplicated strains collected from two tertiary hospitals in China. Complete sequencing and population genetics analysis were performed. BLAST analysis was employed to identify related elements. All newly identified elements were subjected to detailed sequence annotation, dissection, and comparison. We identified and newly designated 19 chromosomal elements, including 18 integrative and mobilizable elements (IMEs) that could be classified into four categories: Tn6737-related, Tn6836-related, Tn6840-related, and Tn6844a-related IMEs. Each class exhibited a distinct pattern in the types of resistance genes carried by the IMEs. Several novel antibiotic resistance genetic environments were uncovered in these elements. Notably, we report the first identification of the blaOXA-10 gene and blaVEB-1 gene in clinical A. veronii genome, the first presence of a tetA(E)-tetR(E) resistance gene environment within the backbone region in IMEs, and a new mcr-3.15 resistance gene environment. The implications of these findings are substantial, as they provide new insights into the evolution, structure, and dissemination of chromosomal-borne accessory elements.

In Silico and In Vitro Analyses to Repurpose Quercetin as a Human Pancreatic α-Amylase Inhibitor

Human pancreatic α-amylase (HPA), situated at the apex of the starch digestion hierarchy, is an attractive therapeutic approach to precisely regulate blood glucose levels, thereby efficiently managing diabetes. Polyphenols offer a natural and multifaceted approach to moderate postprandial sugar spikes, with their slight modulation in carbohydrate digestion and potential secondary benefits, such as antioxidant and anti-inflammatory effects. Taking into consideration the unfavorable side effects of currently available commercial medications, we aimed to study a library of polyphenols attributed to their remarkable antidiabetic properties and screened the most potent HPA inhibitor via a comprehensive in silico study encompassing molecular docking, molecular mechanics with generalized Born and surface area solvation (MM/GBSA) calculation, molecular dynamics (MD) simulation, density functional theory (DFT) study, and pharmacokinetic properties followed by an in vitro assay. Significant hydrogen bonding with the catalytic triad residues of HPA, prominent MM/GBSA binding energy of -27.03 kcal/mol, and the stable nature of the protein-ligand complex with regard to 100 ns MD simulation screened quercetin as the best HPA inhibitor. Additionally, quercetin showed strong reactivity in the substrate-binding pocket of HPA and exhibited favorable pharmacokinetic properties with a considerable inhibitory concentration (IC50) of 57.37 ± 0.9 μg/mL against α-amylase. This study holds prospects for HPA inhibition and suggests quercetin as an approach to therapy for diabetes; however, it is imperative to conduct further research.

Exploring the potential of Halalkalibacterium halodurans laccase for endosulfan and chlorophacinone degradation: insights from molecular docking and molecular dynamics simulations

Pesticides are widely used in agriculture but at the same time, a majority of them are known to cause serious harm to health and the environment. In the recent past, laccases have been reported as key enzymes having the ability to degrade pollutants by converting them into less toxic forms. In this investigation, laccase from polyextremophilic bacterium Halalkalibacterium halodurans C-125 was analyzed for its structural, physicochemical, and functional characterization using in silico approaches. The 3D model of the said enzyme is unknown; therefore, the model was generated by template-independent modeling using ROBETTA, I-TASSER, and Alphafold server. The best-generated model from Alphafold with a confidence of 0.95 was validated from ERRAT and Verify 3D scores of 89.95 and 91.80%, respectively. The Ramachandran plot generated using the PROCHECK server further predicted the accuracy of the model with 93.7% and 5.9% of residues present in most favored and additional allowed regions of the plot respectively. The active sites, ion binding sites, and subcellular localization of laccase were also predicted. The generated model was docked with 121 pollutants (pesticides, insecticides, herbicides, fungicides, and rodenticides) for its degradation potential towards these pollutants. Two ligands chlorophacinone (based on the highest binding energy) and endosulfan (based on agricultural uses) were selected for molecular dynamic simulation studies. Endosulfan as a pesticide is banned but in some countries governments allow its use for special purposes which need serious consideration on developing bioremediation approaches for endosulfan degradation. MD simulation studies revealed that both chlorophacinone and endosulfan form hydrogen bonds and hydrophobic bonds with the active site of laccase and chlorophacinone-laccase complex were more stable in comparison to endosulfan. The present investigation provides insight into the structural features of laccase and its potential for the degradation of pesticides which can be further validated by experimental data.Communicated by Ramaswamy H. Sarma.

Effects of alcohol concentration and temperature on the dynamics and stability of mutant Staphylococcal lipase

The stability and activity of lipase in organic media are important parameters in determining how quickly biocatalysis proceeds. This study aimed to examine the effects of two commonly used alcohols in industrial applications, methanol (MtOH) and ethanol (EtOH) on the conformational stability and catalytic activity of G210C lipase, a laboratory-evolved mutant of Staphylococcus epidermidis AT2 lipase. Simulation studies were performed using an open-form predicted structure under 30, 40 and 50% of MtOH and EtOH at 25 °C and 45 °C. The overall enzyme structure becomes more flexible with increasing concentration of MtOH and exhibited the highest flexibility in 40% EtOH. In EtOH, the movement of the lid was found to be temperature-dependent with a noticeable shift in the lid position at 45 °C. Lid opening was evidenced at 50% of MtOH and EtOH which was supported by the increase in SASA of hydrophobic residues of the lid and catalytic triad. The active site remained mostly intact. An open-closed lid transition was observed when the structure was re-simulated in water. Experimental evaluation of the lipase stability showed that the half-life reduced when the enzyme was treated with 40% (v/v) and 50% (v/v) of EtOH and MtOH respectively. The finding implies that a high concentration of alcohol and elevated temperature can induce the lid opening of lipase which could be essential for the activation of the enzyme, provided that the catalytic performance in the active site is not compromised.Communicated by Ramaswamy H. Sarma.

A practical guide to machine-learning scoring for structure-based virtual screening

Structure-based virtual screening (SBVS) via docking has been used to discover active molecules for a range of therapeutic targets. Chemical and protein data sets that contain integrated bioactivity information have increased both in number and in size. Artificial intelligence and, more concretely, its machine-learning (ML) branch, including deep learning, have effectively exploited these data sets to build scoring functions (SFs) for SBVS against targets with an atomic-resolution 3D model (e.g., generated by X-ray crystallography or predicted by AlphaFold2). Often outperforming their generic and non-ML counterparts, target-specific ML-based SFs represent the state of the art for SBVS. Here, we present a comprehensive and user-friendly protocol to build and rigorously evaluate these new SFs for SBVS. This protocol is organized into four sections: (i) using a public benchmark of a given target to evaluate an existing generic SF; (ii) preparing experimental data for a target from public repositories; (iii) partitioning data into a training set and a test set for subsequent target-specific ML modeling; and (iv) generating and evaluating target-specific ML SFs by using the prepared training-test partitions. All necessary code and input/output data related to three example targets (acetylcholinesterase, HMG-CoA reductase, and peroxisome proliferator-activated receptor-α) are available at https://github.com/vktrannguyen/MLSF-protocol , can be run by using a single computer within 1 week and make use of easily accessible software/programs (e.g., Smina, CNN-Score, RF-Score-VS and DeepCoy) and web resources. Our aim is to provide practical guidance on how to augment training data to enhance SBVS performance, how to identify the most suitable supervised learning algorithm for a data set, and how to build an SF with the highest likelihood of discovering target-active molecules within a given compound library.

Comparative homology of Pleurotus ostreatus laccase enzyme: Swiss model or Modeller?

Laccases stand out in the industrial context due to their versatile biotechnological applications. Although these enzymes are frequently investigated, currently, Pleurotus ostreatus laccase structural model is unknown. Therefore, this research aims to predict and validate a P. ostreatus laccase theoretical model by means of comparative homology. The laccase target's primary structure (AOM73725.1) was obtained from the NCBI database, the model was predicted from homologous structures obtained from the PDB (PDB-ID: 5A7E, 2HRG, 4JHU, 1GYC) using the Swiss-Model and Modeller, and was refined in GalaxyRefine. The models were validated using PROCHECK, VERIFY 3D, ERRAT, PROVE and QMEAN Z-score servers. Moreover, molecular docking between the laccase model (Lacc4MN) and ABTS was performed on AutoDock Vina. The models that were generated by the Modeller showed superior stereochemical and structural characteristics to those predicted by the Swiss Model. The refinement made it difficult to stabilize the copper atoms which are typical of laccases. The Lacc4MN model showed the interactions between the amino acids in the active site of the laccase and the copper atoms, thereby hinting the stabilization of the metal through electrostatic interactions with histidine and cysteine. The molecular docking between Lacc4MN and ABTS showed negative free energy and the formation of two hydrogen bonds involving the amino acids ASP 208 and GLY 268, and a Pi-sulfur bond between residue HIS 458 and ABTS, which demonstrates the typical catalytic functionality of laccases. Furthermore, the theoretical model Lacc4MN presented stereochemical and structural characteristics that allow its use in silico tests.Communicated by Ramaswamy H. Sarma.

Computational design of a multi-epitope vaccine candidate against Langya henipavirus using surface proteins

In July 2022, Langya henipavirus (LayV) was identified in febrile patients in China. There is currently no approved vaccine against this virus. Therefore, this research aimed to design a multi-epitope vaccine against LayV using reverse vaccinology. The best epitopes were selected from LayV's fusion protein (F) and glycoprotein (G), and a multi-epitope vaccine was designed using these epitopes, adjuvant, and appropriate linkers. The physicochemical properties, antigenicity, allergenicity, toxicity, and solubility of the vaccine were evaluated. The vaccine's secondary and 3D structures were predicted, and molecular docking and molecular dynamics (MD) simulations were used to assess the vaccine's interaction and stability with toll-like receptor 4 (TLR4). Immune simulation, codon optimization, and in silico cloning of the vaccine were also performed. The vaccine candidate showed good physicochemical properties, as well as being antigenic, non-allergenic, and non-toxic, with acceptable solubility. Molecular docking and MD simulation revealed that the vaccine and TLR4 have stable interactions. Furthermore, immunological simulation of the vaccine indicated its ability to elicit immune responses against LayV. The vaccine's increased expression was also ensured using codon optimization. This study's findings were encouraging, but in vitro and in vivo tests are needed to confirm the vaccine's protective effect.Communicated by Ramaswamy H. Sarma.

Identification of novel inhibitors of Neisseria gonorrhoeae MurI using homology modeling, structure-based pharmacophore, molecular docking, and molecular dynamics simulation-based approach

MurI is one of the most significant role players in the biosynthesis of the peptidoglycan layer in Neisseria gonorrhoeae (Ng). We attempted to highlight the structural and functional relationship between Ng-MurI and D-glutamate to design novel molecules targeting this interaction. The three-dimensional (3D) model of the protein was constructed by homology modeling and the quality and consistency of generated model were assessed. The binding site of the protein was identified by molecular docking studies and a pharmacophore was identified using the interactions of the control ligand. The structure-based pharmacophore model was validated and employed for high-throughput virtual screening and molecular docking to identify novel Ng-MurI inhibitors. Finally, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with the substrate glutamate and novel molecules facilitated us to confirm the stability of the protein-ligand docked complexes. The 100 ns MD simulations of the potential lead compounds with protein confirmed that the modeled complexes were stable. This study identifies novel potential compounds with good fitness and docking scores, which made the interactions of biological significance within the protein active site. Hence, the identified compounds may act as new leads to design and develop Ng-MurI inhibitors.Communicated by Ramaswamy H. Sarma.

Alanine racemase a promising Helicobacter pylori drug target inhibited by propanoic acid

Eradication of Helicobacter pylori, the class 1 carcinogen, faces several obstacles, which demand alternative options to conventional drug development methods. Alanine racemase (Alr) was proposed as H. pylori drug target, inhibited by propanoic acid (PA), in a previous in silico study. We investigated the possible treatment of H. pylori infection through Alr inhibition. A new model of H. pylori Alr was built, validated, and the binding of PA to the active site was modelled via molecular docking with a good docking score. PA minimum inhibitory concentration (MIC) against H. pylori ATCC 43504 and six H. pylori clinical isolates ranged from 312.5 to 416.7 ± 180 μg/ml and remained unchanged after 14 serial passages in increasing PA concentrations. The minimum bactericidal concentration of PA was 625 μg/ml. Selective Alr inhibition was confirmed by a significant PA MIC increase with increasing d-alanine concentrations. Similar PA MIC in other tested pathogens was recorded (312.5-625 μg/ml). PA lacked cytotoxicity in tested cell lines and efficiently eradicated H. pylori in a rat infection model. In conclusion, Alr is a promising broad-spectrum drug target, inhibited by PA without resistance development by repeated exposure for 14 serial passages.

Comprehensive analysis predicting effects of deleterious SNPs of human progesterone receptor gene on its structure and functions: a computational approach

Progesterone receptor plays a crucial role in the development of the mammary gland and breast cancer. Single nucleotide polymorphisms (SNPs) within its gene, PGR, are associated with the risk of miscarriages and preterm birth as well as many cancers across different populations. The main aim of this work is to investigate the most deleterious SNPs in the PGR gene to identify potential biomarkers for various disease susceptibility and treatments. Both sequence and structure-based computational approaches were adopted and in total 11 nsSNPs have been filtered out of 674 nsSNPs along with seven non-coding SNPs. R740Q, I744T and D746E belonged to a mutation cluster. R740Q, D746E along with S865L altered H-bond interactions within the receptor. The same mutations have been found to be associated with several cancers including uterine and breast cancer among others. It is, therefore, possible that the high-risk SNPs associated with cancers may exert their effect by causing changes in the protein structure, particularly in its bonding patterns, and thus affecting its function. In addition, seven non-coding SNPs that were located in the UTR region created a new miRNA site while three SNPs disrupted a conserved miRNA site. These high-risk SNPs can play an instrumental role in generating a dataset of the PGR gene's SNPs. Thus, the present study may pave the way to design and develop novel therapeutics for overcoming the challenges associated with certain cancers and pregnancy that result from a change in the protein structure and function due to the SNP mutations in the PGR gene.Communicated by Ramaswamy H. Sarma.

Cavity architecture based modulation of ligand binding tunnels in plant START domains

The Steroidogenic acute regulatory protein (StAR)-related lipid transfer (START) domain represents an evolutionarily conserved superfamily of lipid transfer proteins widely distributed across the tree of life. Despite significant expansion in plants, knowledge about this domain remains inadequate in plants. In this work, we explore the role of cavity architectural modulations in START protein evolution and functional diversity. We use deep-learning approaches to generate plant START domain models, followed by surface accessibility studies and a comprehensive structural investigation of the rice START family. We validate 28 rice START domain models, delineate binding cavities, measure pocket volumes, and compare these with mammalian counterparts to understand evolution of binding preferences. Overall, plant START domains retain the ancestral α/β helix-grip signature, but we find subtle variation in cavity architectures, resulting in significantly smaller ligand-binding tunnels in the plant kingdom. We identify cavity lining residues (CLRs) responsible for reduction in ancestral tunnel space, and these appear to be class specific, and unique to plants, providing a mechanism for the observed shift in domain function. For instance, mammalian cavity lining residues A135, G181 and A192 have evolved to larger CLRs across the plant kingdom, contributing to smaller sizes, minimal STARTs being the largest, while members of type-IV HD-Zip family show almost complete obliteration of lipid binding cavities, consistent with their present-day DNA binding functions. In summary, this work quantifies plant START structural & functional divergence, bridging current knowledge gaps.

In silico designing and immunoinformatics analysis of a novel peptide vaccine against metallo-beta-lactamase (VIM and IMP) variants

The rapid spread of acquired metallo-beta-lactamases (MBLs) among gram negative pathogens is becoming a global concern. Improper use of broad-spectrum antibiotics can trigger the colonization and spread of resistant strains which lead to increased mortality and significant economic loss. In the present study, diverse immunoinformatic approaches are applied to design a potential epitope-based vaccine against VIM and IMP MBLs. The amino acid sequences of VIM and IMP variants were retrieved from the GenBank database. ABCpred and BCPred online Web servers were used to analyze linear B cell epitopes, while IEDB was used to determine the dominant T cell epitopes. Sequence validation, allergenicity, toxicity and physiochemical analysis were performed using web servers. Seven sequences were identified for linear B cell dominant epitopes and 4 sequences were considered as dominant CD4+ T cell epitopes, and the predicted epitopes were joined by KK and GPGPG linkers. Stabilized multi-epitope protein structure was obtained using molecular dynamics simulation. Molecular docking showed that the designed vaccine exhibited sustainable and strong binding interactions with Toll-like receptor 4 (TLR4). Finally, codon adaptation and in silico cloning studies were performed to design an effective vaccine production strategy. Immune simulation significantly provided high levels of immunoglobulins, T helper cells, T-cytotoxic cells and INF-γ. Even though the introduced vaccine candidate demonstrates a very potent immunogenic potential, but wet-lab validation is required to further assessment of the effectiveness of this proposed vaccine candidate.

Molecular dissection studies of TAC1, a transcription activator of Candida drug resistance genes of the human pathogenic fungus Candida albicans

The up-regulation of ABC transporters Cdr1p and Cdr2p that efflux antifungal azole drugs are a leading cause of Multi-Drug Resistance (MDR) in the white fungus Candida albicans. C. albicans was reported to infect patients following the recent Covid-19 pandemic after they were given steroids for recovery. Previously, the TAC1 gene was identified as the transcriptional activator of Candida drug resistance genes (CDR1 and CDR2) and has no known human homologs. This makes it a good target for the development of novel antifungals. We, therefore, carried out the molecular dissection study of TAC1 to understand the functional regulation of the ABC transporter genes (CDR1 and CDR2) under its control. The N-terminal DNA Binding Domain (DBD) of Tac1p interacts with the Drug Responsive Element (DRE) present in the upstream promoter region of CDR1 and CDR2 genes of C. albicans. The interaction between DBD and DRE recruits Tac1p to the promoter of CDR genes. The C-terminal Acidic Activation Domain (AAD) of Tac1p interacts with the TATA box Binding Protein (TBP) and thus recruits TBP to the TATA box of CDR1 and CDR2 genes. Taking a cue from a previous study involving a TAC1 deletion strain that suggested that Tac1p acts as a xenobiotic receptor, in this study, we identified that the Middle Homology Region (MHR) of Tac1p acts as a probable xenobiotic binding domain (XBD) which plays an important role in Candida drug resistance. In addition, we studied the role of Tac1p in the regulation of some lipid profiling genes and stress response genes since they also contain the DRE consensus sequence and found that some of them can respond to xenobiotic stimuli.

A Structural Network Analysis of Neuronal ArhGAP21/23 Interactors by Computational Modeling

RhoGTPase-activating proteins (RhoGAPs) play multiple roles in neuronal development; however, details of their substrate recognition system remain elusive. ArhGAP21 and ArhGAP23 are RhoGAPs that contain N-terminal PDZ and pleckstrin homology domains. In the present study, the RhoGAP domain of these ArhGAPs was computationally modeled by template-based methods and the AlphaFold2 software program, and their intrinsic RhoGTPase recognition mechanism was analyzed from the domain structures using the protein docking programs HADDOCK and HDOCK. ArhGAP21 was predicted to preferentially catalyze Cdc42, RhoA, RhoB, RhoC, and RhoG and to downregulate RhoD and Tc10 activities. Regarding ArhGAP23, RhoA and Cdc42 were deduced to be its substrates, whereas RhoD downregulation was predicted to be less efficient. The PDZ domains of ArhGAP21/23 possess the FTLRXXXVY sequence, and similar globular folding consists of antiparalleled β-sheets and two α-helices that are conserved with PDZ domains of MAST-family proteins. A peptide docking analysis revealed the specific interaction of the ArhGAP23 PDZ domain with the PTEN C-terminus. The pleckstrin homology domain structure of ArhGAP23 was also predicted, and the functional selectivity for the interactors regulated by the folding and disordered domains in ArhGAP21 and ArhGAP23 was examined by an in silico analysis. An interaction analysis of these RhoGAPs revealed the existence of mammalian ArhGAP21/23-specific type I and type III Arf- and RhoGTPase-regulated signaling. Multiple recognition systems of RhoGTPase substrates and selective Arf-dependent localization of ArhGAP21/23 may form the basis of the functional core signaling necessary for synaptic homeostasis and axon/dendritic transport regulated by RhoGAP localization and activities.

Characterization, protein modeling, and molecular docking of factor C from Indonesian horseshoe crab (Tachypleus gigas)

BACKGROUND

Horseshoe crab (Tachypleus gigas) amebocytes are useful biomedical components for endotoxin detection, and their growing needs for biomedical purposes cause the horseshoe crab population to decline. Factor C synthesis via genetic engineering offers a solution to replace natural horseshoe crab's factor C and prevent its excessive harvest from nature. In response to these concerns, this study aimed to characterize the amebocyte lysates and factor C protein modeling of T. gigas originated from Banyuasin South Sumatra Estuary.

METHODS AND RESULTS

Sampling of T. gigas was carried out in Banyuasin South Sumatra Estuary, Indonesia. The endotoxin test or TAL (Tachypleus amebocyte lysates) assay was performed using gel coagulation method. Protein characterization of protease enzyme was conducted by protease activity, SDS-PAGE, and zymogram analysis. The cDNA of mitochondrial COI gene was amplified for molecular identification followed by cDNA cloning of factor C. Protein modeling was investigated by molecular docking and molecular dynamic (MD) simulation. Endotoxin test results showed that TAL-35 had endotoxin sensitivity in a range of 0.0156-1 EU/ml, while TAL 36 had a sensitivity between 00,625 and 1 EU/ml. T. gigas amebocytes have protease activity in molecular mass sizes less than 60 kDa, with 367 U/ml for TAL 35 and 430 U/ml for TAL 36. The molecular identification revealed 98.68% identity similarity to T. gigas. The docking results suggested three ligands; i.e., diphosphoryl lipid A, core lipid A, and Kdo2 lipid A can be activators of the factor C protein by binding to the region of the receptor to form a ligand-receptor complex.

CONCLUSIONS

Endotoxins can be detected using horseshoe crab amebocytes. The presence of proteases is considered responsible for this ability, as evidenced by casein zymogram results. According to docking and MD analysis, we found that lipopolysaccharides (LPS) participate to the binding site of factor C.

Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins

The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies in silico. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body.Communicated by Ramaswamy H. Sarma.

A systematic drug repurposing approach to identify promising inhibitors from FDA-approved drugs against Nsp4 protein of SARS-CoV-2

COVID-19 is caused by SARS-CoV-2 and responsible for the ongoing global pandemic in the world. After more than a year, we are still in lurch to combat and control the situation. Therefore, new therapeutic options to control the ongoing COVID-19 are urgently in need. In our study, we found that nonstructural protein 4 (Nsp4) of SARS-CoV-2 could be a potential target for drug repurposing. Due to availability of only the crystal structure of C-terminal domain of Nsp4 (Ct-Nsp4) and its crucial participation in viral RNA synthesis, we have chosen Ct-Nsp4 as a target for screening the 1600 FDA-approved drugs using molecular docking. Top 102 drugs were found to have the binding energy equal or less than -7.0 kcal/mol. Eribulin and Suvorexant were identified as the two most promising drug molecules based on the docking score. The dynamics of Ct-Nsp4-drug binding was monitored using 100 ns molecular dynamics simulations. From binding free energy calculation over the simulation, both the drugs were found to have considerable binding energy. The present study has identified Eribulin and Suvorexant as promising drug candidates. This finding will be helpful to accelerate the drug discovery process against COVID-19 disease.Communicated by Ramaswamy H. Sarma.

The glycine N-acyltransferases, GLYAT and GLYATL1, contribute to the detoxification of isovaleryl-CoA - an in-silico and in vitro validation

Isovaleric acidemia (IVA), due to isovaleryl-CoA dehydrogenase (IVD) deficiency, results in the accumulation of isovaleryl-CoA, isovaleric acid and secondary metabolites. The increase in these metabolites decreases mitochondrial energy production and increases oxidative stress. This contributes to the neuropathological features of IVA. A general assumption in the literature exists that glycine N-acyltransferase (GLYAT) plays a role in alleviating the symptoms experienced by IVA patients through the formation of N-isovalerylglycine. GLYAT forms part of the phase II glycine conjugation pathway in the liver and detoxifies excess acyl-CoA's namely benzoyl-CoA. However, very few studies support GLYAT as the enzyme that conjugates isovaleryl-CoA to glycine. Furthermore, GLYATL1, a paralogue of GLYAT, conjugates phenylacetyl-CoA to glutamine. Therefore, GLYATL1 might also be a candidate for the formation of N-isovalerylglycine. Based on the findings from the literature review, we proposed that GLYAT or GLYATL1 can form N-isovalerylglycine in IVA patients. To test this hypothesis, we performed an in-silico analysis to determine which enzyme is more likely to conjugate isovaleryl-CoA with glycine using AutoDock Vina. Thereafter, we performed in vitro validation using purified enzyme preparations. The in-silico and in vitro findings suggested that both enzymes could form N-isovaleryglycine albeit at lower affinities than their preferred substrates. Furthermore, an increase in glycine concentration does not result in an increase in N-isovalerylglycine formation. The results from the critical literature appraisal, in-silico, and in vitro validation, suggest the importance of further investigating the reaction kinetics and binding behaviors between these substrates and enzymes in understanding the pathophysiology of IVA.

In silico design of a promiscuous chimeric multi-epitope vaccine against Mycobacterium tuberculosis

Tuberculosis (TB) is a global health threat, killing approximately 1.5 million people each year. The eradication of Mycobacterium tuberculosis, the main causative agent of TB, is increasingly challenging due to the emergence of extensive drug-resistant strains. Vaccination is considered an effective way to protect the host from pathogens, but the only clinically approved TB vaccine, Bacillus Calmette-Guérin (BCG), has limited protection in adults. Multi-epitope vaccines have been found to enhance immunity to diseases by selectively combining epitopes from several candidate proteins. This study aimed to design a multi-epitope vaccine against TB using an immuno-informatics approach. Through functional enrichment, we identified eight proteins secreted by M. tuberculosis that are either required for pathogenesis, secreted into extracellular space, or both. We then analyzed the epitopes of these proteins and selected 16 helper T lymphocyte epitopes with interferon-γ inducing activity, 15 cytotoxic T lymphocyte epitopes, and 10 linear B-cell epitopes, and conjugated them with adjuvant and Pan HLA DR-binding epitope (PADRE) using appropriate linkers. Moreover, we predicted the tertiary structure of this vaccine, its potential interaction with Toll-Like Receptor-4 (TLR4), and the immune response it might elicit. The results showed that this vaccine had a strong affinity for TLR4, which could significantly stimulate CD4⁺ and CD8⁺ cells to secrete immune factors and B lymphocytes to secrete immunoglobulins, so as to obtain good humoral and cellular immunity. Overall, this multi-epitope protein was predicted to be stable, safe, highly antigenic, and highly immunogenic, which has the potential to serve as a global vaccine against TB.

Comparative Proteomics and Genome-Wide Druggability Analyses Prioritized Promising Therapeutic Targets against Drug-Resistant Leishmania tropica

Leishmania tropica is a tropical parasite causing cutaneous leishmaniasis (CL) in humans. Leishmaniasis is a serious public health threat, affecting an estimated 350 million people in 98 countries. The global rise in antileishmanial drug resistance has triggered the need to explore novel therapeutic strategies against this parasite. In the present study, we utilized the recently available multidrug resistant L. tropica strain proteome data repository to identify alternative therapeutic drug targets based on comparative subtractive proteomic and druggability analyses. Additionally, small drug-like compounds were scanned against novel targets based on virtual screening and ADME profiling. The analysis unveiled 496 essential cellular proteins of L. tropica that were nonhomologous to the human proteome set. The druggability analyses prioritized nine parasite-specific druggable proteins essential for the parasite's basic cellular survival, growth, and virulence. These prioritized proteins were identified to have appropriate binding pockets to anchor small drug-like compounds. Among these, UDPase and PCNA were prioritized as the top-ranked druggable proteins. The pharmacophore-based virtual screening and ADME profiling predicted MolPort-000-730-162 and MolPort-020-232-354 as the top hit drug-like compounds from the Pharmit resource to inhibit L. tropica UDPase and PCNA, respectively. The alternative drug targets and drug-like molecules predicted in the current study lay the groundwork for developing novel antileishmanial therapies.

Whole genome sequencing of Clarireedia aff. paspali reveals potential pathogenesis factors in Clarireedia species, causal agents of dollar spot in turfgrass

Dollar spot is one of the most damaging diseases in turfgrass, reducing its quality and playability. Two species, Clarireedia monteithiana and C. jacksonii (formerly Sclerotinia homoeocarpa) have been reported so far in the United States To study the Clarireedia genome, two isolates H2 and H3, sampled from seashore paspalum in Hawaii in 2019 were sequenced via Illumina paired-end sequencing by synthesis technology and PacBio SMRT sequencing. Both isolates were identified as C. aff. paspali, a novel species in the United States Using short and long reads, C. aff. paspali H3 contained 193 contigs with 48.6 Mbp and presented the most completed assembly and annotation among Clarireedia species. Out of the 13,428 protein models from AUGUSTUS, 349 cytoplasmic effectors and 13 apoplastic effectors were identified by EffectorP. To further decipher Clarireedia pathogenicity, C. aff. paspali genomes (H2 and H3), as well as available C. jacksonii (LWC-10 and HRI11), C. monteithiana (DRR09 and RB-19) genomes were screened for fifty-four pathogenesis determinants, previously identified in S. sclerotiorum. Seventeen orthologs of pathogenicity genes have been identified in Clarireedia species involved in oxalic acid production (pac1, nox1), mitogen-activated protein kinase cascade (pka1, smk3, ste12), appressorium formation (caf1, pks13, ams2, rgb1, rhs1) and glycolytic pathway (gpd). Within these genes, 366 species-specific SNPs were recorded between Clarireedia species; twenty-eight were non-synonymous and non-conservative. The predicted protein structure of six of these genes showed superimposition of the models among Clarireedia spp. The genomic variations revealed here could potentially lead to differences in pathogenesis and other physiological functions among Clarireedia species.

β-III Tubulin Levels Determine the Neurotoxicity Induced by Colchicine-Site Binding Agent Indibulin

Indibulin, a microtubule-depolymerizing agent, produces minimal neurotoxicity in animals. It is also less cytotoxic toward differentiated neuronal cells than undifferentiated cells. We found that the levels of β-III tubulin, acetylated tubulin, and polyglutamylated tubulin were significantly increased in differentiated neuroblastoma cells (SH-SY5Y). Since neuronal cells express β-tubulin isotypes differently from other cell types, we explored the binding of indibulin to different β-tubulin isotypes. Our molecular docking analysis suggested that indibulin binds to β-III tubulin with lower affinity than to other β-tubulin isotypes. We therefore studied the implications of different β-tubulin isotypes on the cytotoxic effects of indibulin, colchicine, and vinblastine in differentiated SH-SY5Y cells. Upon depletion of β-III tubulin in the differentiated cells, the toxicity of indibulin and colchicine significantly increased, while sensitivity to vinblastine was unaffected. Using biochemical, bioinformatics, and fluorescence spectroscopic techniques, we have identified the binding site of indibulin on tubulin, which had not previously been established. Indibulin inhibited the binding of colchicine and C12 (a colchicine-site binder) to tubulin and also increased the dissociation constant of the interaction between tubulin and colchicine. Indibulin did not inhibit the binding of vinblastine or taxol to tubulin. Interestingly, indibulin antagonized colchicine treatment but synergized with vinblastine treatment in a combination study performed in MDA-MB-231 cells. The results indicate that indibulin is a colchicine-site binder and that the efficacy of colchicine-site binders is affected by the β-III tubulin levels in the cells.

A subunit vaccine against pneumonia: targeting Streptococcus pneumoniae and Klebsiella pneumoniae

Community-acquired pneumonia is primarily caused by Streptococcus pneumoniae and Klebsiella pneumoniae, two pathogens that have high morbidity and mortality rates. This is largely due to bacterial resistance development against current antibiotics and the lack of effective vaccines. The objective of this work was to develop an immunogenic multi-epitope subunit vaccine capable of eliciting a robust immune response against S. pneumoniae and K. pneumoniae. The targeted proteins were the pneumococcal surface proteins (PspA and PspC) and choline-binding protein (CbpA) of S. pneumoniae and the outer membrane proteins (OmpA and OmpW) of K. pneumoniae. Different computational approaches and various immune filters were employed for designing a vaccine. The immunogenicity and safety of the vaccine were evaluated by utilizing many physicochemical and antigenic profiles. To improve structural stability, disulfide engineering was applied to a portion of the vaccine structure with high mobility. Molecular docking was performed to examine the binding affinities and biological interactions at the atomic level between the vaccine and Toll-like receptors (TLR2 and 4). Further, the dynamic stabilities of the vaccine and TLRs complexes were investigated by molecular dynamics simulations. While the immune response induction capability of the vaccine was assessed by the immune simulation study. Vaccine translation and expression efficiency was determined through an in silico cloning experiment utilizing the pET28a(+) plasmid vector. The obtained results revealed that the designed vaccine is structurally stable and able to generate an effective immune response to combat pneumococcal infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13721-023-00416-3.

Identification of novel inhibitors for SARS-CoV-2 as therapeutic options using machine learning-based virtual screening, molecular docking and MD simulation

The new coronavirus SARS-COV-2, which emerged in late 2019 from Wuhan city of China was regarded as causing agent of the COVID-19 pandemic. The primary protease which is also known by various synonymous i.e., main protease, 3-Chymotrypsin-like protease (3CL^PRO) has a vital role in the replication of the virus, which can be used as a potential drug target. The current study aimed to identify novel phytochemical therapeutics for 3CL^PRO by machine learning-based virtual screening. A total of 4,000 phytochemicals were collected from deep literature surveys and various other sources. The 2D structures of these phytochemicals were retrieved from the PubChem database, and with the use of a molecular operating environment, 2D descriptors were calculated. Machine learning-based virtual screening was performed to predict the active phytochemicals against the SARS-CoV-2 3CL^PRO. Random forest achieved 98% accuracy on the train and test set among the different machine learning algorithms. Random forest model was used to screen 4,000 phytochemicals which leads to the identification of 26 inhibitors against the 3CL^PRO. These hits were then docked into the active site of 3CL^PRO. Based on docking scores and protein-ligand interactions, MD simulations have been performed using 100 ns for the top 5 novel inhibitors, ivermectin, and the APO state of 3CL^PRO. The post-dynamic analysis i.e,. Root means square deviation (RMSD), Root mean square fluctuation analysis (RMSF), and MM-GBSA analysis reveal that our newly identified phytochemicals form significant interactions in the binding pocket of 3CL^PRO and form stable complexes, indicating that these phytochemicals could be used as potential antagonists for SARS-COV-2.

In silico study on miRNA regulation and NSs protein interactome characterization of the SFTS virus

Severe fever with thrombocytopenia syndrome causing virus i.e. SFTS virus has increased in the last few years. The underlying cause and mechanism of disease progression and development of symptoms is not well known. Many viruses including Hepatitis B, Hepatitis C, HIV-1, Herpes virus, Dengue virus and many others have been seen to regulate their functions at the miRNA level. This study aimed to find out those cellular miRNAs, which can be mimicked or antagonized by the viral genome and analyze the effect of these miRNAs on various gene functions. Investigations in this study suggest a correlation between miRNA regulation with the disease symptoms and progression. By exhaustive literature survey we have tried to identify the interacting partners of the Non Structural S (NSs) protein and characterized the protein-protein interactions. The binding interface that can serve as target for therapeutic studies involving the interfacial residues was analyzed. This study would serve as an avenue to design therapeutics making use of not only protein-protein interactions but also miRNA based regulation as well.

Exploiting reverse vaccinology approach for the design of a multiepitope subunit vaccine against the major SARS-CoV-2 variants

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.

Construction and protective efficacy of a novel Streptococcus pneumoniae fusion protein vaccine NanAT1-TufT1-PlyD4

During the past decades, with the implementation of pneumococcal polysaccharide vaccine (PPV) and pneumococcal conjugate vaccines (PCVs), a dramatic reduction in vaccine type diseases and transmissions has occurred. However, it is necessary to develop a less expensive, serotype-independent pneumococcal vaccine due to the emergence of nonvaccine-type pneumococcal diseases and the limited effect of vaccines on colonization. As next-generation vaccines, conserved proteins, such as neuraminidase A (NanA), elongation factor Tu (Tuf), and pneumolysin (Ply), are promising targets against pneumococcal infections. Here, we designed and constructed a novel fusion protein, NanAT1-TufT1-PlyD4, using the structural and functional domains of full-length NanA, Tuf and Ply proteins with suitable linkers based on bioinformatics analysis and molecular cloning technology. Then, we tested whether the protein protected against focal and lethal pneumococcal infections and examined its potential protective mechanisms. The fusion protein NanAT1-TufT1-PlyD4 consists of 627 amino acids, which exhibits a relatively high level of thermostability, high stability, solubility and a high antigenic index without allergenicity. The purified fusion protein was used to subcutaneously immunize C57BL/6 mice, and NanAT1-TufT1-PlyD4 induced a strong and significant humoral immune response. The anti-NanAT1-TufT1-PlyD4 specific IgG antibody assays increased after the first immunization and reached the highest value at the 35th day. The results from in vitro experiments showed that anti-NanAT1-TufT1-PlyD4 antisera could inhibit the adhesion of Streptococcus pneumoniae (S. pneumoniae) to A549 cells. In addition, immunization with NanAT1-TufT1-PlyD4 significantly reduced S. pneumoniae colonization in the lung and decreased the damage to the lung tissues induced by S. pneumoniae infection. After challenge with a lethal dose of serotype 3 (NC_WCSUH32403), a better protection effect was observed with NanAT1-TufT1-PlyD4-immunized mice than with the separate full-length proteins and the adjuvant control; the survival rate was 50%, which met the standard of the marketed vaccine. Moreover, we showed that the humoral immune response and the Th1, Th2 and Th17-cellular immune pathways are involved in the immune protection of NanAT1-TufT1-PlyD4 to the host. Collectively, our results support that the novel fusion protein NanAT1-TufT1-PlyD4 exhibits extensive immune stimulation and is effective against pneumococcal challenges, and these properties are partially attributed to humoral and cellular-mediated immune responses.

Computational Target-Based Screening of Anti-MRSA Natural Products Reveals Potential Multitarget Mechanisms of Action through Peptidoglycan Synthesis Proteins

Methicillin-resistant Staphylococcus aureus (MRSA) is one of the leading causes of bacterial infections in both healthcare and community settings. MRSA can acquire resistance to any current antibiotic, which has major implications for its current and future treatment options. As such, it is globally a major focus for infection control efforts. The mechanical rigidity provided by peptidoglycans in the bacteria cell walls makes it a promising target for broad-spectrum antibacterial drug discovery. The development of drugs that can target different stages of the synthesis of peptidoglycan in MRSA may compromise the integrity of its cell wall and consequently result in the rapid decline of diseases associated with this drug-resistant bacteria. The present study is aimed at screening natural products with known in vitro activities against MRSA to identify their potential to inhibit the proteins involved in the biosynthesis of the peptidoglycan cell wall. A total of 262 compounds were obtained when a literature survey was conducted on anti-MRSA natural products (AMNPs). Virtual screening of the AMNPs was performed against various proteins (targets) that are involved in the biosynthesis of the peptidoglycan (PPC) cell wall using Schrödinger software (release 2020-3) to determine their binding affinities. Nine AMNPs were identified as potential multitarget inhibitors against peptidoglycan biosynthesis proteins. Among these compounds, DB211 showed the strongest binding affinity and interactions with six protein targets, representing three stages of peptidoglycan biosynthesis, and thus was selected as the most promising compound. The MD simulation results for DB211 and its proteins indicated that the protein-ligand complexes were relatively stable over the simulation period of 100 ns. In conclusion, DB211 showed the potential to inhibit six proteins involved in the biosynthesis of the peptidoglycan cell wall in MRSA, thus reducing the chance of MRSA developing resistance to this compound. Therefore, DB211 provided a starting point for the design of new compounds that can inhibit multiple targets in the biosynthesis of the peptidoglycan layer in MRSA.

Nontoxic and Naturally Occurring Active Compounds as Potential Inhibitors of Biological Targets in Liriomyza trifolii

In recent years, novel strategies to control insects have been based on protease inhibitors (PIs). In this regard, molecular docking and molecular dynamics simulations have been extensively used to investigate insect gut proteases and the interactions of PIs for the development of resistance against insects. We, herein, report an in silico study of (disodium 5'-inosinate and petunidin 3-glucoside), (calcium 5'-guanylate and chlorogenic acid), chlorogenic acid alone, (kaempferol-3,7-di-O-glucoside with hyperoside and delphinidin 3-glucoside), and (myricetin 3'-glucoside and hyperoside) as potential inhibitors of acetylcholinesterase receptors, actin, α-tubulin, arginine kinase, and histone receptor III subtypes, respectively. The study demonstrated that the inhibitors are capable of forming stable complexes with the corresponding proteins while also showing great potential for inhibitory activity in the proposed protein-inhibitor combinations.

Immunoinformatics-Based Identification of B and T Cell Epitopes in RNA-Dependent RNA Polymerase of SARS-CoV-2

INTRODUCTION

The ongoing coronavirus disease 2019 (COVID-19), which emerged in December 2019, is a serious health concern throughout the world. Despite massive COVID-19 vaccination on a global scale, there is a rising need to develop more effective vaccines and drugs to curb the spread of coronavirus.

METHODOLOGY

In this study, we screened the amino acid sequence of the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 (the causative agent of COVID-19) for the identification of B and T cell epitopes using various immunoinformatic tools. These identified potent B and T cell epitopes with high antigenicity scores were linked together to design the multi-epitope vaccine construct. The physicochemical properties, overall quality, and stability of the designed vaccine construct were confirmed by suitable bioinformatic tools.

RESULTS

After proper in silico prediction and screening, we identified 3 B cell, 18 CTL, and 10 HTL epitopes from the RdRp protein sequence. The screened epitopes were non-toxic, non-allergenic, and highly antigenic in nature as revealed by appropriate servers. Molecular docking revealed stable interactions of the designed multi-epitope vaccine with human TLR3. Moreover, in silico immune simulations showed a substantial immunogenic response of the designed vaccine.

CONCLUSIONS

These findings suggest that our designed multi-epitope vaccine possessing intrinsic T cell and B cell epitopes with high antigenicity scores could be considered for the ongoing development of peptide-based novel vaccines against COVID-19. However, further in vitro and in vivo studies need to be performed to confirm our in silico observations.

A subtractive proteomics and immunoinformatics approach towards designing a potential multi-epitope vaccine against pathogenic Listeriamonocytogenes

Listeria monocytogenes is the causative agent of listeriosis, which is dangerous for pregnant women, the elderly or individuals with a weakened immune system. Individuals with leukaemia, cancer, HIV/AIDS, kidney transplant and steroid therapy suffer from immunological damage are menaced. World Health Organization (WHO) reports that human listeriosis has a high mortality rate of 20-30% every year. To date, no vaccine is available to treat listeriosis. Thereby, it is high time to design novel vaccines against L. monocytogenes. Here, we present computational approaches to design an antigenic, stable and safe vaccine against the L. monocytogenes that could help to control the infections associated with the pathogen. Three vital pathogenic proteins of L. monocytogenes, such as Listeriolysin O (LLO), Phosphatidylinositol-specific phospholipase C (PI-PLC), and Actin polymerization protein (ActA), were selected using a subtractive proteomics approach to design the multi-epitope vaccine (MEV). A total of 5 Cytotoxic T-lymphocyte (CTL) and 9 Helper T-lymphocyte (HTL) epitopes were predicted from these selected proteins. To design the multi-epitope vaccine (MEV) from the selected proteins, CTL epitopes were joined with the AAY linker, and HTL epitopes were joined with the GPGPG linker. Additionally, a human β-defensin-3 (hBD-3) adjuvant was added to the N-terminal side of the final MEV construct to increase the immune response to the vaccine. The final MEV was predicted to be antigenic, non-allergen and non-toxic in nature. Physicochemical property analysis suggested that the MEV construct is stable and could be easily purified through the E. coli expression system. This in-silico study showed that MEV has a robust binding interaction with Toll-like receptor 2 (TLR2), a key player in the innate immune system. Current subtractive proteomics and immunoinformatics study provides a background for designing a suitable, safe and effective vaccine against pathogenic L. monocytogenes.

Proteomic and computational characterisation of 11S globulins from grape seed flour by-product and its interaction with malvidin 3-glucoside by molecular docking

Grape seed flour by-product (GSBP) is an economic and renewable source of proteins, increasingly being explored due to interesting technological application such as colour protection in rich-anthocyanins beverages. Globulin-like proteins from GSBP were characterised by proteomic and computational studies. MALDI TOF/TOF analysis revealed the presence of two 11S globulins (acid and basic), whose 3D structures have been elucidated for the first time in Vitis vinifera L. grape seeds by using homology models and molecular dynamics. The secondary structure showed 11 α-helices and 25 β-sheets for acid and 12 α-helices and 24 β-sheets for basic 11S globulins. Molecular docking results indicate that both grape seed 11S globulins could establish different types of non-covalent interactions (π-π) with malvidin 3-O-glucoside (wine anthocyanin), which suggest a possible colour protection similar to that occurring in copigmentation phenomenon. These findings provide valuable information of globulin family proteins that could be relevant in food industry applications.

Plant catalase in silico characterization and phylogenetic analysis with structural modeling

Background

Catalase (EC 1.11.1.6) is a heme-containing tetrameric enzyme that plays a critical role in signaling and hydrogen peroxide metabolism. It was the first enzyme to be crystallized and isolated. Catalase is a well-known industrial enzyme used in diagnostic and analytical methods in the form of biomarkers and biosensors, as well as in the textile, paper, food, and pharmaceutical industries. In silico analysis of CAT genes and proteins has gained increased interest, emphasizing the development of biomarkers and drug designs. The present work aims to understand the catalase evolutionary relationship of plant species and analyze its physicochemical characteristics, homology, phylogenetic tree construction, secondary structure prediction, and 3D modeling of protein sequences and its validation using a variety of conventional computational methods to assist researchers in better understanding the structure of proteins.

Results

Around 65 plant catalase sequences were computationally evaluated and subjected to bioinformatics assessment for physicochemical characterization, multiple sequence alignment, phylogenetic construction, motif and domain identification, and secondary and tertiary structure prediction. The phylogenetic tree revealed six unique clusters where diversity of plant catalases was found to be the largest for Oryza sativa. The thermostability and hydrophilic nature of these proteins were primarily observed, as evidenced by a relatively high aliphatic index and negative GRAVY value. The distribution of 5 sequence motifs was uniformly distributed with a width length of 50 with the best possible amino residue sequences that resemble the plant catalase PLN02609 superfamily. Using SOPMA, the predicted secondary structure of the protein sequences revealed the predominance of the random coil. The predicted 3D CAT model from Arabidopsis thaliana was a homotetramer, thermostable protein with 59-KDa weight, and its structural validation was confirmed by PROCHECK, ERRAT, Verify3D, and Ramachandran plot. The functional relationships of our query sequence revealed the glutathione reductase as the closest interacting protein of query protein.

Conclusions

This theoretical plant catalases in silico analysis provide insight into its physiochemical characteristics and functional and structural understanding and its evolutionary behavior and exploring protein structure-function relationships when crystal structures are unavailable.

Is the Glycoprotein Responsible for the Differences in Dispersal Rates between Lettuce Necrotic Yellows Virus Subgroups?

Lettuce necrotic yellows virus is a type of species in the Cytorhabdovirus genus and appears to be endemic to Australia and Aotearoa New Zealand (NZ). The population of lettuce necrotic yellows virus (LNYV) is made up of two subgroups, SI and SII. Previous studies demonstrated that SII appears to be outcompeting SI and suggested that SII may have greater vector transmission efficiency and/or higher replication rate in its host plant or insect vector. Rhabdovirus glycoproteins are important for virus–insect interactions. Here, we present an analysis of LNYV glycoprotein sequences to identify key features and variations that may cause SII to interact with its aphid vector with greater efficiency than SI. Phylogenetic analysis of glycoprotein sequences from NZ isolates confirmed the existence of two subgroups within the NZ LNYV population, while predicted 3D structures revealed the LNYV glycoproteins have domain architectures similar to Vesicular Stomatitis Virus (VSV). Importantly, changing amino acids at positions 244 and 247 of the post-fusion form of the LNYV glycoprotein altered the predicted structure of Domain III, glycosylation at N248 and the overall stability of the protein. These data support the glycoprotein as having a role in the population differences of LNYV observed between Australia and New Zealand.

In silico and experimental validation of a new modified arginine-rich cell penetrating peptide for plasmid DNA delivery

Cell-penetrating peptides (CPPs) attracted great attention because of the capability to deliver various types of cargo molecules across into the cells. In this study, we presented a new arginine rich CPP, named MR, for efficient transporting plasmid DNA. We used a combined bioinformatic-based approach to improve the speed and accuracy of CPP evaluation. MR protein properties, structural models, interaction with DNA, as well as cell localization and membrane interaction were evaluated through multiple servers. Importantly, analysis using different algorithms showed the high CPP prediction confidence of MR. Experimental results also revealed the capacity of this gene delivery system in vitro for efficient plasmid DNA transfection. Additionally, in vitro mechanistically studies together with bioinformatic investigation suggested that MR peptide may internalize into the cell through endocytosis pathways. Moreover, in silico safety analysis such as immunogenicity, allergenicity, toxicity, and hemolysis activity as well as MTT assay also confirmed the safety of MR peptide. This study illustrated that MR peptide could be presented as remarkable potential gene delivery system for promising transport of plasmid DNA towards the therapeutic applications.

A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements

In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.

In silico comprehensive analysis of coding and non-coding SNPs in human mTOR protein

The mammalian/mechanistic target of rapamycin (mTOR) protein is an important growth regulator and has been linked with multiple diseases including cancer and diabetes. Non-synonymous mutations of this gene have already been found in patients with renal clear cell carcinoma, melanoma, and acute lymphoid leukemia among many others. Such mutations can potentially affect a protein’s structure and hence its functions. In this study, therefore, the most deleterious SNPs of mTOR protein have been determined to identify potential biomarkers for various disease treatments. The aim is to generate a structured dataset of the mTOR gene’s SNPs that may prove to be an asset for the identification and treatment of multiple diseases associated with the target gene. Both sequence and structure-based approaches were adopted and a wide variety of bioinformatics tools were applied to analyze the SNPs of mTOR protein. In total 11 nsSNPs have been filtered out of 2178 nsSNPs along with two non-coding variations. All of the nsSNPs were found to destabilize the protein structure and disrupt its function. While R619C, A1513D, and T1977R mutations were shown to alter C alpha distances and bond angles of the mTOR protein, L509Q, R619C and N2043S were predicted to disrupt the mTOR protein’s interaction with NBS1 protein and FKBP1A/rapamycin complex. In addition, one of the non-coding SNPs was shown to alter miRNA binding sites. Characterizing nsSNPs and non-coding SNPs and their harmful effects on a protein’s structure and functions will enable researchers to understand the critical impact of mutations on the molecular mechanisms of various diseases. This will ultimately lead to the identification of potential targets for disease diagnosis and therapeutic interventions.

Homology Modeling, de Novo Design of Ligands, and Molecular Docking Identify Potential Inhibitors of Leishmania donovani 24-Sterol Methyltransferase

The therapeutic challenges pertaining to leishmaniasis due to reported chemoresistance and toxicity necessitate the need to explore novel pathways to identify plausible inhibitory molecules. Leishmania donovani 24-sterol methyltransferase (LdSMT) is vital for the synthesis of ergosterols, the main constituents of Leishmania cellular membranes. So far, mammals have not been shown to possess SMT or ergosterols, making the pathway a prime candidate for drug discovery. The structural model of LdSMT was elucidated using homology modeling to identify potential novel 24-SMT inhibitors via virtual screening, scaffold hopping, and de-novo fragment-based design. Altogether, six potential novel inhibitors were identified with binding energies ranging from −7.0 to −8.4 kcal/mol with e-LEA3D using 22,26-azasterol and S1–S4 obtained from scaffold hopping via the ChEMBL, DrugBank, PubChem, ChemSpider, and ZINC15 databases. These ligands showed comparable binding energy to 22,26-azasterol (−7.6 kcal/mol), the main inhibitor of LdSMT. Moreover, all the compounds had plausible ligand efficiency-dependent lipophilicity (LELP) scores above 3. The binding mechanism identified Tyr92 to be critical for binding, and this was corroborated via molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) calculations. The ligand A1 was predicted to possess antileishmanial properties with a probability of activity (Pa) of 0.362 and a probability of inactivity (Pi) of 0.066, while A5 and A6 possessed dermatological properties with Pa values of 0.205 and 0.249 and Pi values of 0.162 and 0.120, respectively. Structural similarity search via DrugBank identified vabicaserin, daledalin, zanapezil, imipramine, and cefradine with antileishmanial properties suggesting that the de-novo compounds could be explored as potential antileishmanial agents.

Identification of the most damaging nsSNPs in the human CFL1 gene and their functional and structural impacts on cofilin-1 protein

The cofilin-1 protein, encoded by CFL1, is an actin-binding protein that regulates F-actin depolymerization and nucleation activity through phosphorylation and dephosphorylation. CFL1 has been implicated in the development of neurodegenerative diseases (Alzheimer's disease and Huntington's disease), neuronal migration disorders (lissencephaly, epilepsy, and schizophrenia), and neural tube closure defects. Mutations in CFL1 have been associated with impaired neural crest cell migration and neural tube closure defects. In our study, various computational approaches were utilized to explore single-nucleotide polymorphisms (SNPs) in CFL1. The Variation Viewer and gnomAD databases were used to retrieve CFL1 SNPs, including 46 nonsynonymous SNPs (nsSNPs). The functional and structural annotation of SNPs was performed using 12 sequence-based web applications, which identified 20 nsSNPs as being the most likely to be deleterious or disease-causing. The conservation of cofilin-1 protein structures was illustrated using the ConSurf and PROSITE web servers, which projected the 12 most deleterious nsSNPs onto conserved domains, with the potential to disrupt the protein's functionality. These 12 nsSNPs were selected for protein structure construction, and the DynaMut/DUET servers predicted that the protein variants V7G, L84P, and L99A were the most likely to be damaging to the cofilin-1 protein structure or function. The evaluation of molecular docking studies demonstrated that the L99A and L84P cofilin-1 variants reduce the binding affinity for actin compared with the native cofilin-1 structure, and molecular dynamic simulation studies confirmed that these variants might destabilize the protein structure. The consequences of putative mutations on protein-protein interactions and post-translational modification sites in the cofilin-1 protein structure were analyzed. This study represents the first complete approach to understanding the effects of nsSNPs within the actin-depolymerizing factor/cofilin family, which suggested that SNPs resulting in L84P (rs199716082) and L99A (rs267603119) variants represent significant CFL1 mutations associated with disease development.

Computational vaccinology guided design of multi-epitope subunit vaccine against a neglected arbovirus of the Americas

Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions.Communicated by Ramaswamy H. Sarma.