The ClusPro web server for protein-protein docking

Regulatory T cells use heparanase to access IL-2 bound to extracellular matrix in inflamed tissue

Although FOXP3+ regulatory T cells (Treg) depend on IL-2 produced by other cells for their survival and function, the levels of IL-2 in inflamed tissue are low, making it unclear how Treg access this critical resource. Here, we show that Treg use heparanase (HPSE) to access IL-2 sequestered by heparan sulfate (HS) within the extracellular matrix (ECM) of inflamed central nervous system tissue. HPSE expression distinguishes human and murine Treg from conventional T cells and is regulated by the availability of IL-2. HPSE-/- Treg have impaired stability and function in vivo, including in the experimental autoimmune encephalomyelitis (EAE) mouse model of multiple sclerosis. Conversely, endowing monoclonal antibody-directed chimeric antigen receptor (mAbCAR) Treg with HPSE enhances their ability to access HS-sequestered IL-2 and their ability to suppress neuroinflammation in vivo. Together, these data identify a role for HPSE and the ECM in immune tolerance, providing new avenues for improving Treg-based therapy of autoimmunity.

Immunoinformatic Identification of Multiple Epitopes of gp120 Protein of HIV-1 to Enhance the Immune Response against HIV-1 Infection

Acquired Immunodeficiency Syndrome is caused by the Human Immunodeficiency Virus (HIV), and a significant number of fatalities occur annually. There is a dire need to develop an effective vaccine against HIV-1. Understanding the structural proteins of viruses helps in designing a vaccine based on immunogenic peptides. In the current experiment, we identified gp120 epitopes using bioinformatic epitope prediction tools, molecular docking, and MD simulations. The Gb-1 peptide was considered an adjuvant. Consecutive sequences of GTG, GSG, GGTGG, and GGGGS linkers were used to bind the B cell, Cytotoxic T Lymphocytes (CTL), and Helper T Lymphocytes (HTL) epitopes. The final vaccine construct consisted of 315 amino acids and is expected to be a recombinant protein of approximately 35.49 kDa. Based on docking experiments, molecular dynamics simulations, and tertiary structure validation, the analysis of the modeled protein indicates that it possesses a stable structure and can interact with Toll-like receptors. The analysis demonstrates that the proposed vaccine can provoke an immunological response by activating T and B cells, as well as stimulating the release of IgA and IgG antibodies. This vaccine shows potential for HIV-1 prophylaxis. The in-silico design suggests that multiple-epitope constructs can be used as potentially effective immunogens for HIV-1 vaccine development.

Multilocus functional characterization of indigenous and exotic inbreds for dgat1-2, fatb, ge2 and wri1a genes affecting kernel oil and fatty acid profile in maize

Demand for maize oil is progressively increasing due to its diverse industrial applications, aside from its primary role in human nutrition and animal feed. Oil content and composition are two crucial determinants of maize oil in the international market. As kernel oil in maize is a complex quantitative trait, improving this trait presents a challenge for plant breeders and biotechnologists. Here, we characterized a set of 292 diverse maize inbreds of both indigenous and exotic origin by exploiting functional polymorphism of the dgat1-2, fatb, ge2, and wri1a genes governing kernel oil in maize. Genotyping using gene-based functional markers revealed a lower frequencies of dgat1-2 (0.15) and fatb (0.12) mutant alleles and a higher frequencies of wild-type alleles (Dgat1-2: 0.85; fatB: 0.88). The favorable wri1a allele was conserved across genotypes, while its wild-type allele (WRI1a) was not detected. In contrast, none of the genotypes possessed the ge2 favorable allele. The frequency of favorable alleles of both dgat1-2 and fatb decreased to 0.03 when considered together. Furthermore, pairwise protein-protein interactions among target gene products were conducted to understand the effect of one protein on another and their responses to kernel oil through functional enrichments. Thus, the identified maize genotypes with dgat1-2, fatb, and wri1a favourable alleles, along with insights gained through the protein-protein association network, serve as prominent and unique genetic resources for high-oil maize breeding programs. This is the first comprehensive report on the functional characterization of diverse genotypes at the molecular and protein levels.

Computational Procedure for Predicting Excipient Effects on Protein-Protein Affinities

Protein-protein interactions lie at the center of many biological processes and are a challenge in formulating biological drugs, such as antibodies. A key to mitigating protein association is to use small-molecule additives, i.e., excipients that can weaken protein-protein interactions. Here, we develop a computationally efficient model for predicting the viscosity-reducing effect of different excipient molecules by combining atomic-resolution MD simulations, binding polynomials, and a thermodynamic perturbation theory. In a proof of principle, this method successfully ranks the order of four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting the effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.

Two Main Cancer Biomarkers as Molecular Targets of Binase Antitumor Activity

Cancer is frequently coupled with the disturbance of key signaling pathways. Aberrant activation of the mitogen-activated protein kinase (MAPK) signaling cascade, occurring in over 85% of cancers, is mainly caused by the genetic alterations of its main components-oncogenes EGFR and RAS, and plays a crucial role in cell fate. The importance of EGFR and RAS proteins in a variety of tumors suggests that they would be good therapeutic targets, but at present, no effective targeted therapy against these two oncogenes has been proven. Here, we show that ribonuclease from Bacillus pumilus (binase) inhibits MAPK signaling through direct interaction with EGFR and RAS proteins. This effect contributes to the antitumor potential of binase along with its enzymatic activity. Multitargeticity of binase prevents the development of drug resistance, which is considered a major obstacle to effective anticancer treatment.

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure is a long standing goal with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost intensive. Computational methods have potential to accelerate epitope predictions, however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologs. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2 Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis alone each proved ineffectual in differentiating between two putative binding models referred to as parallel and perpendicular. However, our integrated approach based on dynamic network analysis showed that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols including cross linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Our research highlights the potential of deploying dynamic network analysis to refine AI-based structure predictions for precise predictions of protein-protein interaction interfaces.

Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology

BACKGROUND

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective vaccine against HPyV is of high priority.

METHODS

First, the proteomes of 2 polyomavirus species (HPyV6 and HPyV7) were downloaded from the NCBI database for the selection of the target proteins. The epitope identification process focused on selecting proteins that were crucial, associated with virulence, present on the surface, antigenic, non-toxic, and non-homologous with the human proteome. Then, the immunoinformatic methods were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes from the target antigens, which could be used to create epitope-based vaccine. The physicochemical features of the designed vaccine were predicted through various online servers. The binding pattern and stability between the vaccine candidate and Toll-like receptors were analyzed through molecular docking and molecular dynamics (MD) simulation, while the immunogenicity of the designed vaccines was assessed using immune simulation.

RESULTS

Online tools were utilized to forecast the most optimal epitope from the immunogenic targets, including LTAg, VP1, and VP1 antigens of HPyV6 and HPyV7. A multi-epitope vaccine was developed by combining 10 CTL, 7 HTL, and 6 LBL epitopes with suitable linkers and adjuvant. The vaccine displayed 98.35% of the world's population coverage. The 3D model of the vaccine structure revealed that the majority of residues (87.7%) were located in favored regions of the Ramachandran plot. The evaluation of molecular docking and MD simulation revealed that the constructed vaccine exhibits a strong binding (-1414.0 kcal/mol) towards the host's TLR4. Moreover, the vaccine-TLR complexes remained stable throughout the dynamic conditions present in the natural environment. The immune simulation results demonstrated that the vaccine design had the capacity to elicit robust immune responses in the host.

CONCLUSION

The multi-parametric analysis revealed that the designed vaccine is capable of inducing sustained immunity against the selected polyomaviruses, although further in-vivo investigations are needed to verify its effectiveness.

Computational exploration of the genomic assignments, molecular structure, and dynamics of the ccdABXn2 toxin-antitoxin homolog with its bacterial target, the DNA gyrase, in the entomopathogen Xenorhabdus nematophila

Toxin-antitoxin (TA) modules, initially discovered on bacterial plasmids and subsequently identified within chromosomal contexts, hold a pivotal role in the realm of bacterial physiology. Among these, the pioneering TA system, ccd (Control of Cell Death), primarily localized on the F-plasmid, is known for its orchestration of plasmid replication with cellular division. Nonetheless, the precise functions of such systems within bacterial chromosomal settings remain a compelling subject that demands deeper investigation. To bridge this knowledge gap, our study focuses on exploring ccdABXn2, a chromosomally encoded TA module originating from the entomopathogenic bacterium Xenorhabdus nematophila. We meticulously delved into the system's genomic assignments, structural attributes, and functional interplay. Our findings uncovered intriguing patterns-CcdB toxin homologs exhibited higher conservation levels compared to their CcdA antitoxin counterparts. Moreover, we constructed secondary as well as tertiary models for both the CcdB toxin and CcdA antitoxin using threading techniques and subsequently validated their structural integrity. Our exploration extended to the identification of key interactions, including the peptide interaction with gyrase for the CcdB homolog and CcdB toxin interactions for the CcdA homolog, highlighting the intricate TA interaction network. Through docking and simulation analyses, we unequivocally demonstrated the inhibition of replication via binding the CcdB toxin to its target, DNA gyrase. These insights provide valuable knowledge about the metabolic and physiological roles of the chromosomally encoded ccdABXn2 TA module within the context of X. nematophila, significantly enhancing our comprehension of its functional significance within the intricate ecosystem of the bacterial host.Communicated by Ramaswamy H. Sarma.

Glyceraldehyde-3-Phosphate Dehydrogenase Binds with Spike Protein and Inhibits the Entry of SARS-CoV-2 into Host Cells

INTRODUCTION

Coronavirus disease 2019 caused by coronavirus-2 (SARS-CoV-2) has emerged as an aggressive viral pandemic. Health care providers confront a challenging task for rapid development of effective strategies to combat this and its long-term after effects. Virus entry into host cells involves interaction between receptor-binding domain (RBD) of spike (S) protein S1 subunit with angiotensin converting enzyme present on host cells. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a moonlighting enzyme involved in cellular glycolytic energy metabolism and micronutrient homeostasis. It is deployed in various cellular compartments and the extra cellular milieu. Though it is known to moonlight as a component of mammalian innate immune defense machinery, till date its role in viral restriction remains unknown.

METHOD

Recombinant S protein, the RBD, and human GAPDH protein were used for solid phase binding assays and biolayer interferometry. Pseudovirus particles expressing four different strain variants of S protein all harboring ZsGreen gene as marker of infection were used for flow cytometry-based infectivity assays.

RESULTS

Pseudovirus entry into target cells in culture was significantly inhibited by addition of human GAPDH into the extracellular medium. Binding assays demonstrated that human GAPDH binds to S protein and RBD of SARS-CoV-2 with nanomolar affinity.

CONCLUSIONS

Our investigations suggest that this interaction of GAPDH interferes in the viral docking with hACE2 receptors, thereby affecting viral ingress into mammalian cells.

Determining Structural Changes for Ligand Recognition between Human and Rat Phosphorylated BACE1 in Silico and Its Phosphorylation by GSK3β at Thr252 by in Vitro Studies

Alzheimer's disease (AD) is a neurodegenerative disease affecting older adults. AD pathogenesis involves the production of the highly neurotoxic amyloid-β peptide 1-42 (Aβ1-42) from β-site amyloid precursor protein cleaving enzyme 1 (BACE1). The phosphorylation of BACE1 at Thr252 increases its enzymatic activity. This study examined the phosphorylation of BACE1 from human and rat BACE1 in silico through phosphorylation predictors. Besides, we explored how phosphorylation at various sites affected the BACE1 structure and its affinity with amyloid precursor protein (APP) and six BACE1 inhibitors. Additionally, we evaluated the phosphorylation of Thr252-BACE1 by glycogen synthase kinase 3 β (GSK3β) in vitro. The phosphorylation predictors showed that Thr252, Ser59, Tyr76, Ser71, and Ser83 could be phosphorylated. Also, Ser127 in rat BACE1 can be phosphorylated, but human BACE1 has a Gly at this position. Molecular dynamics simulations showed that Ser127 plays an important role in the open and closed BACE1 conformational structures. Docking studies and the molecular mechanics generalized Born surface area (MMGBSA) approach showed that human BACE1 phosphorylated at Thr252 and rat BACE1 phosphorylated at Ser71 have the best binding and free energy with APP, forming hydrogen bonds with Asp672. Importantly, inhibitors have a higher affinity for the phosphorylated rat BACE1 than for its human counterpart, which could explain their failure during clinical trials. Finally, in vitro experiments showed that GSK3β could phosphorylate BACE1. In conclusion, BACE1 phosphorylation influences the BACE1 conformation and its recognition of ligands and substrates. Thus, these features should be carefully considered in the design of BACE1 inhibitors.

Immunomodulatory Peptides as Vaccine Adjuvants and Antimicrobial Agents

The underdevelopment of adjuvant discovery and diversity, compared to core vaccine technology, is evident. On the other hand, antibiotic resistance is on the list of the top ten threats to global health. Immunomodulatory peptides that target a pathogen and modulate the immune system simultaneously are promising for the development of preventive and therapeutic molecules. Since investigating innate immunity in insects has led to prominent achievements in human immunology, such as toll-like receptor (TLR) discovery, we used the capacity of the immunomodulatory peptides of arthropods with concomitant antimicrobial or antitumor activity. An SVM-based machine learning classifier identified short immunomodulatory sequences encrypted in 643 antimicrobial peptides from 55 foe-to-friend arthropods. The critical features involved in efficacy and safety were calculated. Finally, 76 safe immunomodulators were identified. Then, molecular docking and simulation studies defined the target of the most optimal peptide ligands among all human cell-surface TLRs. SPalf2-453 from a crab is a cell-penetrating immunoadjuvant with antiviral properties. The peptide interacts with the TLR1/2 heterodimer. SBsib-711 from a blackfly is a TLR4/MD2 ligand used as a cancer vaccine immunoadjuvant. In addition, SBsib-711 binds CD47 and PD-L1 on tumor cells, which is applicable in cancer immunotherapy as a checkpoint inhibitor. MRh4-679 from a shrimp is a broad-spectrum or universal immunoadjuvant with a putative Th1/Th2-balanced response. We also implemented a pathway enrichment analysis to define fingerprints or immunological signatures for further in vitro and in vivo immunogenicity and reactogenicity measurements. Conclusively, combinatorial machine learning, molecular docking, and simulation studies, as well as systems biology, open a new opportunity for the discovery and development of multifunctional prophylactic and therapeutic lead peptides.

Ksp1 is an autophagic receptor protein for the Snx4-assisted autophagy of Ssn2/Med13

Ksp1 is a casein II-like kinase whose activity prevents aberrant macroautophagy/autophagy induction in nutrient-rich conditions in yeast. Here, we describe a kinase-independent role of Ksp1 as a novel autophagic receptor protein for Ssn2/Med13, a known cargo of Snx4-assisted autophagy of transcription factors. In this pathway, a subset of conserved transcriptional regulators, Ssn2/Med13, Rim15, and Msn2, are selectively targeted for vacuolar proteolysis following nitrogen starvation, assisted by the sorting nexin heterodimer Snx4-Atg20. Here we show that phagophores also engulf Ksp1 alongside its cargo for vacuolar proteolysis. Ksp1 directly associates with Atg8 following nitrogen starvation at the interface of an Atg8-family interacting motif (AIM)/LC3-interacting region (LIR) in Ksp1 and the LIR/AIM docking site (LDS) in Atg8. Mutating the LDS site prevents the autophagic degradation of Ksp1. However, deletion of the C terminal canonical AIM still permitted Ssn2/Med13 proteolysis, suggesting that additional non-canonical AIMs may mediate the Ksp1-Atg8 interaction. Ksp1 is recruited to the perivacuolar phagophore assembly site by Atg29, a member of the trimeric scaffold complex. This interaction is independent of Atg8 and Snx4, suggesting that Ksp1 is recruited early to phagophores, with Snx4 delivering Ssn2/Med13 thereafter. Finally, normal cell survival following prolonged nitrogen starvation requires Ksp1. Together, these studies define a kinase-independent role for Ksp1 as an autophagic receptor protein mediating Ssn2/Med13 degradation. They also suggest that phagophores built by the trimeric scaffold complex are capable of receptor-mediated autophagy. These results demonstrate the dual functionality of Ksp1, whose kinase activity prevents autophagy while it plays a scaffolding role supporting autophagic degradation.Abbreviations: 3-AT: 3-aminotriazole; 17C: Atg17-Atg31-Atg29 trimeric scaffold complex; AIM: Atg8-family interacting motif; ATG: autophagy related; CKM: CDK8 kinase module; Cvt: cytoplasm-to-vacuole targeting; IDR: intrinsically disordered region; LIR: LC3-interacting region; LDS: LIR/AIM docking site; MoRF: molecular recognition feature; NPC: nuclear pore complex; PAS: phagophore assembly site; PKA: protein kinase A; RBP: RNA-binding protein; UPS: ubiquitin-proteasome system. SAA-TF: Snx4-assisted autophagy of transcription factors; Y2H: yeast two-hybrid.

A significance score for protein-protein interaction models through random docking

Comparing accuracies of structural protein-protein interaction (PPI) models for different complexes on an absolute scale is a challenge, requiring normalization of scores across structures of different sizes and shapes. To help address this challenge, we have developed a statistical significance metric for docking models, called random-docking (RD) p-value. This score evaluates a PPI model based on how likely a random docking process is to produce a model of better or equal accuracy. The binding partners are randomly docked against each other a large number of times, and the probability of sampling a model of equal or greater accuracy from this reference distribution is the RD p-value. Using a subset of top predicted models from CAPRI (Critical Assessment of PRediction of Interactions) rounds over 2017-2020, we find that the ease of achieving a given root mean squared deviation or DOCKQ score varies considerably by target; achieving the same relative metric can be thousands of times easier for one complex compared to another. In contrast, RD p-values inherently normalize scores for models of different complexes, making them globally comparable. Furthermore, one can calculate RD p-values after generating a reference distribution that accounts for prior information about the interface geometry, such as residues involved in binding, by giving the random-docking process access the same information. Thus, one can decouple improvements in prediction accuracy that arise solely from basic modeling constraints from those due to the rest of the method. We provide efficient code for computing RD p-values at https://github.com/Grigoryanlab/RDP.

Ebola virus VP35 interacts non-covalently with ubiquitin chains to promote viral replication

Ebolavirus (EBOV) belongs to a family of highly pathogenic viruses that cause severe hemorrhagic fever in humans. EBOV replication requires the activity of the viral polymerase complex, which includes the cofactor and Interferon antagonist VP35. We previously showed that the covalent ubiquitination of VP35 promotes virus replication by regulating interactions with the polymerase complex. In addition, VP35 can also interact non-covalently with ubiquitin (Ub); however, the function of this interaction is unknown. Here, we report that VP35 interacts with free (unanchored) K63-linked polyUb chains. Ectopic expression of Isopeptidase T (USP5), which is known to degrade unanchored polyUb chains, reduced VP35 association with Ub and correlated with diminished polymerase activity in a minigenome assay. Using computational methods, we modeled the VP35-Ub non-covalent interacting complex, identified the VP35-Ub interacting surface, and tested mutations to validate the interface. Docking simulations identified chemical compounds that can block VP35-Ub interactions leading to reduced viral polymerase activity. Treatment with the compounds reduced replication of infectious EBOV in cells and in vivo in a mouse model. In conclusion, we identified a novel role of unanchored polyUb in regulating Ebola virus polymerase function and discovered compounds that have promising anti-Ebola virus activity.

Novel role of peptidoglycan recognition protein 2 in activating NOD2-NFκB inflammatory axis in coronary artery disease

BACKGROUNDS AND AIMS

The role of inflammation in driving atherosclerosis is well-established. It exerts systemic effects beyond the local site of plaque formation. In the context of coronary artery disease (CAD), the proteins that show altered levels in the plasma, are potentially important for understanding the key regulatory mechanism in the pathogenesis of atherosclerosis. A case-control study revealed that plasma soluble Peptidoglycan Recognition Protein 2 (PGLYRP2) primarily produced by the liver, is increased in subjects with CAD. Furthermore, the concentration of PGLYRP2 in the blood correlates with the severity of coronary artery disease. Thus, it raises interest in understanding the exact role of the protein in aortic inflammation and plaque progression.

METHODS

We evaluated the plasma concentration of PGLYRP2 in three distinct groups: patients with CAD (N = 68), asymptomatic individuals (N = 34), and healthy volunteers (N = 20). Furthermore, we investigated the correlation between disease severity and PGLYRP2 levels in CAD patients. To identify potential binding partners of PGLYRP2, we employed computational analysis. We verified the PGLYRP2-NOD2 interaction in macrophage cells and elucidated the inflammatory pathways activated by PGLYRP2 within these cells. To assess the impact of PGLYRP2, we examined its effects in the atherosclerotic mice model (ApoE-/-).

RESULTS

In this study, we report for the first time that Nucleotide-binding Oligomerization domain 2 (NOD2) which is expressed on the surface of macrophages, is a receptor of PGLYRP2. The N-terminal domain of PGLYRP2 directly binds to NOD2 and activates the NOD2-RIP2-NFκB cascade that promotes the secretion of proinflammatory cytokines like TNFα, IL1β, and IL-8. In the atherosclerotic mice model (ApoE-/-) we demonstrate that elevated PGLYRP2 level is parallel with increased proinflammatory cytokines in the plasma when fed a High Cholesterol Diet (HCD). Immunohistochemical analysis reveals that PGLYRP2 is co-localized with NOD2 on the macrophages at the site of the lesion.

CONCLUSIONS

Taken together, our data demonstrate that NOD2 acts as a receptor of PGLYRP2 on macrophages, which mediates the activation of the NOD2-RIP2-NFκB pathway and promotes inflammation, thus significantly contributing to the development and progression of atherosclerosis.

Investigating Lycotoxin-An1a (An1a), a defense antiviral peptide from Alopecosa nagpag venom as prospective anti-dengue agent against DENV-2 NS2B-NS3 protease

Dengue fever is a global health concern with no effective therapy. Screening synthetic chemicals, animal-originated compounds, and phytocompounds against Dengue virus (DENV) targets has failed to find dengue antivirals. The current study examines animal drugs as antagonists against NS2B-NS3Pro, one of DENV's most promising therapeutic targets for dengue fever. Antiviral-Lycotoxin-An1a (An1a), a defence antiviral peptide isolated from the venom of Alopecosa nagpag, a toxic spider. Based on prior in vitro research, it was discovered that the venom peptide suppresses the action of DENV-2 NS2B-NS3Pro. An1a peptide with NS2B-NS3Pro wild type (WT) and two mutants (H51N and S135A) was tested for anti-dengue characteristics using in silico analysis. The WT NS2B-NS3Pro has a catalytic triad of His51, Asp75, and Ser135 in the active site, but the mutants have N51 instead of His51 and Ala135 instead of Ser135. The dynamic sites of the three proteases (WT, H51N, S135A) and the peptide toxin (An1a) were taken into account to achieve molecular docking of An1a with WT NS2B-NS3Pro in conjunction with H51N and S135A. Cluspro-2 performs rigid-flexible docking to predict peptide binding affinity, effectiveness, and inhibitory consistency. Since the ligand had a higher binding affinity, docking score, and molecular interaction network, MD simulations and MM-GBSA free energy calculations were used to investigate the stability of the three protein-peptide complexes. The computer-aided screening and manufacture of spider venom-based anti-dengue medicines yielded intriguing results in the preliminary studies. This study is significant in defining the ideal therapeutic candidate against dengue infections.

Nonsynonymous mutations in VEGF receptor binding domain alter the efficacy of bevacizumab treatment

Vascular endothelial growth factor (VEGF) mediated angiogenesis is crucial for tumor progression. Isoforms of VEGF bind to different VEGF receptors (VEGFRs) to initiate angiogenesis specific cellular signaling. Inhibitors that target both the receptors and ligands are in clinical use to impede angiogenesis. Bevacizumab, a monoclonal antibody (mAb) approved by the Food and Drug Administration (FDA), binds in the VEGF receptor binding domain (RBD) of all soluble isoforms of VEGF and inhibits the VEGF-VEGFR interaction. Bevacizumab is also used in combination with other chemotherapeutic agents for a better therapeutic outcome. Understanding the intricate polymorphic character of VEGFA gene and the influence of missense or nonsynonymous mutations in the form of nonsynonymous polymorphisms (nsSNPs) on RBD of VEGF may aid in increasing the efficacy of this drug. This study has identified 18 potential nsSNPs in VEGFA gene that affect the VEGF RBD structure and alter its binding pattern to bevacizumab. The mutated RBDs, modeled using trRosetta, in addition to the changed pattern of secondary structure, post translational modification and stability compared to the wild type, have shown contrasting binding affinity and molecular interaction pattern with bevacizumab. Molecular docking analysis by ClusPro and visualization using PyMol and PDBsum tools have detected 17 nsSNPs with decreased binding affinity to bevacizumab and therefore may impact the treatment efficacy. Whereas VEGF RBD expressed due to rs1267535717 (R229H) nsSNP of VEGFA has increased affinity to the mAb. This study suggests that genetic characterization of VEGFA before bevacizumab mediated cancer treatment is essential in predicting the appropriate efficacy of the drug, as the treatment efficiency may vary at individual level.

Loss of nephric augmenter of liver regeneration facilitates acute kidney injury via ACSL4-mediated ferroptosis

Ferroptosis, characterized by lipid accumulation in intracellular compartments, is related to acute kidney injury (AKI), but the mechanism remains obscure. In our previous study, the protective effect of augmenter of liver regeneration (ALR) on AKI was not fully clarified. In this study, we established an AKI mouse model by knocking out proximal tubule-specific ALR and an AKI cell model by inducing hypoxia, as well as enrolled AKI patients, to investigate the effects of ALR on ferroptosis and the progression of AKI. We found that ALR knockout aggravated ferroptosis and increased ROS accumulation and mitochondrial damage, whereas ALR overexpression attenuated ferroptosis through clearance of ROS and maintenance of mitochondrial morphology. Mechanistically, we demonstrated that ALR could directly bind to long-chain-fatty-acid-CoA ligase 4 (ACSL4) and further inhibit the expression of ACSL4 by interacting with certain regions. By resolution liquid chromatography coupled with triple quadruple mass spectrometry, we found that ALR could reduce the contents of polyunsaturated fatty acids, especially arachidonic acid. In addition, we showed that ALR binds to ACSL4 and attenuates oxylipin accumulation, exerting a protective effect against ferroptosis in AKI. Therefore, targeting renal ALR can attenuate ferroptosis and can offer a promising strategy for the treatment of AKI.

Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

Over the last few decades, we have witnessed growing interest from both academic and industrial laboratories in peptides as possible therapeutics. Bioactive peptides have a high potential to treat various diseases with specificity and biological safety. Compared to small molecules, peptides represent better candidates as inhibitors (or general modulators) of key protein-protein interactions. In fact, undruggable proteins containing large and smooth surfaces can be more easily targeted with the conformational plasticity of peptides. The discovery of bioactive peptides, working against disease-relevant protein targets, generally requires the high-throughput screening of large libraries, and in silico approaches are highly exploited for their low-cost incidence and efficiency. The present review reports on the potential challenges linked to the employment of peptides as therapeutics and describes computational approaches, mainly structure-based virtual screening (SBVS), to support the identification of novel peptides for therapeutic implementations. Cutting-edge SBVS strategies are reviewed along with examples of applications focused on diverse classes of bioactive peptides (i.e., anticancer, antimicrobial/antiviral peptides, peptides blocking amyloid fiber formation).

Novel toxin-based mRNA vaccine against Clostridium perfringens using in silico approaches

Clostridium perfringens is a bacterium that causes gastrointestinal diseases in humans and animals. The several powerful toxins such as alpha toxin (CPA), beta toxin (CPB), enterotoxin (CPE), Epsilon toxin (ETX), and theta toxin, play a major role in its pathogenesis. Traditional vaccine development methods are time-consuming and costly. In silico approaches offer an alternative strategy for designing vaccines by analyzing biological data and predicting immunogenic peptides. In this study, computational tools were utilized to design a RNA vaccine targeting C. perfringens toxins. Toxin protein sequences were retrieved and their linear B-cell, MHCI, and MHCII binding epitopes were predicted. Allergenicity, toxigenicity, and IFN-γ induction were assessed to select non-allergenic, non-toxic, and IFN-γ-inducing epitopes. Molecular docking was performed to identify epitopes that fit within the binding cleft of MHC alleles. A final peptide vaccine construct was designed with selected epitopes separated by a linker sequence. The antigenicity and physicochemical properties of the vaccine were evaluated. Immune response simulation showed enhanced secondary and tertiary immune responses, increased levels of immunoglobulins, cytotoxic T lymphocytes, helper T lymphocytes, macrophage activity, and elevated levels IFN-γ and interleukin-2. Docking analysis was done to assess interactions between the vaccine structure and Toll-like receptors. Codon optimization was performed, and a final RNA vaccine construct was designed. The secondary structure of the RNA vaccine was predicted and validated. Overall, this study demonstrates the potential of in silico approaches for designing an RNA vaccine against C. perfringens toxins, contributing to improved prevention and control of associated diseases.

Molecular characterization of Anaplasma ovis Msp4 protein in strains isolated from ticks in Turkey: A multi-epitope synthetic vaccine antigen design against Anaplasma ovis using immunoinformatic tools

Tick-borne pathogens increasingly threaten animal and human health as well as cause great economic loss in the livestock industry. Among these pathogens, Anaplasma ovis causing a decrease in meat and milk yield is frequently detected in sheep in many countries including Turkey. This study aimed to reveal potential vaccine candidate epitopes in Msp4 protein using sequence data from Anaplasma ovis isolates and then to design a multi-epitope protein to be used in vaccine formulations against Anaplasma ovis. For this purpose, Msp4 gene was sequenced from Anaplasma ovis isolates (n:6) detected in ticks collected from sheep in Turkey and the sequence data was compared with previous sequences from different countries in order to detect the variations of Msp4 gene/protein. Potential vaccine candidate and diagnostic epitopes were predicted using various immunoinformatics tools. Among the discovered vaccine candidate epitopes, antigenic and conserved were selected, and then a multi-epitope protein was designed. The designed vaccine protein was tested for the assessment of TLR-2, IgG, and IFN-g responses by molecular docking and immune simulation analyses. Among the discovered epitopes, EVASEGSGVM and YQFTPEISLV epitopes with properties of high antigenicity, non-allergenicity, and non-toxicity were proposed to be used for Anaplasma ovis in further serodiagnostic and vaccine studies.

Molecular insight into endosulfan degradation by Ese protein from Arthrobacter: Evidence-based structural bioinformatics and quantum mechanical calculations

Endosulfan is an organochlorine insecticide widely used for agricultural pest control. Many nations worldwide have restricted or completely banned it due to its extreme toxicity to fish and aquatic invertebrates. Arthrobacter sp. strain KW has the ability to degrade α, β endosulfan and its intermediate metabolite endosulfate; this degradation is associated with Ese protein, a two-component flavin-dependent monooxygenase (TC-FDM). Employing in silico tools, we obtained the 3D model of Ese protein, and our results suggest that it belongs to the Luciferase Like Monooxygenase family (LLM). Docking studies showed that the residues V59, V315, D316, and T335 interact with α-endosulfan. The residues: V59, T60, V315, D316, and T335 are implicated in the interacting site with β-endosulfan, and the residues: H17, V315, D316, T335, N364, and Q363 participate in the interaction with endosulfate. Topological analysis of the electron density by means of the Quantum Theory of Atoms in Molecules (QTAIM) and the Non-Covalent Interaction (NCI) index reveals that the Ese-ligands complexes are formed mainly by dispersive forces, where Cl atoms have a predominant role. As Ese is a monooxygenase member, we predict the homodimer formation. However, enzymatic studies must be developed to investigate the Ese protein's enzymatic and catalytic activity.

Combined Immunoinformatics to Design and Evaluate a Multi-Epitope Vaccine Candidate against Streptococcus suis Infection

Streptococcus suis (S. suis) is a zoonotic pathogen with multiple serotypes, and thus, multivalent vaccines generating cross-protection against S. suis infections are urgently needed to improve animal welfare and reduce antibiotic abuse. In this study, we established a systematic and comprehensive epitope prediction pipeline based on immunoinformatics. Ten candidate epitopes were ultimately selected for building the multi-epitope vaccine (MVSS) against S. suis infections. The ten epitopes of MVSS were all derived from highly conserved, immunogenic, and virulence-associated surface proteins in S. suis. In silico analyses revealed that MVSS was structurally stable and affixed with immune receptors, indicating that it would likely trigger strong immunological reactions in the host. Furthermore, mice models demonstrated that MVSS elicited high titer antibodies and diminished damages in S. suis serotype 2 and Chz infection, significantly reduced sequelae, induced cytokine transcription, and decreased organ bacterial burdens after triple vaccination. Meanwhile, anti-rMVSS serum inhibited five important S. suis serotypes in vitro, exerted beneficial protective effects against S. suis infections and significantly reduced histopathological damage in mice. Given the above, it is possible to develop MVSS as a universal subunit vaccine against multiple serotypes of S. suis infections.

Immunoinformatics approaches in developing a novel multi-epitope chimeric vaccine protective against Saprolegnia parasitica

Saprolegnia parasitica is responsible for devastating infections in fish and poses a tremendous threat to the global aquaculture industry. Presently, no safe and effective control measures are available, on the contrary, use of banned toxic compounds against the pathogen is affecting humans via biomagnification routes. This pioneering study aims to design an effective multi-epitope multi-target vaccine candidate against S. parasitica by targeting key proteins involved in the infection process. The proteins were analyzed and linear B-cell epitopes, MHC class I, and class II epitopes were predicted. Subsequently, highly antigenic epitopes were selected and fused to a highly immunogenic adjuvant, 50S ribosomal protein L7/L12, to design a multi-epitope chimeric vaccine construct. The structure of the vaccine was generated and validated for its stereochemical quality, physicochemical properties, antigenicity, allergenicity, and virulence traits. Molecular docking analyses demonstrated strong binding interactions between the vaccine and piscine immune receptors (TLR5, MHC I, MHC II). Molecular dynamics simulations and binding energy calculations of the complexes, further, reflected the stability and favorable interactions of the vaccine and predicted its cytosolic stability. Immune simulations predicted robust and consistent kinetics of the immune response elicited by the vaccine. The study posits the vaccine as a promising solution to combat saprolegniasis in the aquaculture industry.

Immunoinformatics Approach to Design a Chimeric CD70-Peptide Vaccine against Renal Cell Carcinoma

Renal cell carcinoma (RCC) accounts for the majority of cancer-related deaths worldwide. Overexpression of CD70 has been linked to advanced stages of RCC. Therefore, this study aims to develop a multiepitope vaccine targeting the overexpressed CD70 using immunoinformatics techniques. In this investigation, in silico multiepitope vaccines were constructed by linking specific CD70 protein epitopes for helper T lymphocytes and CD8+ T lymphocytes. To enhance immunogenicity, sequences of cell-penetrating peptide (CPP), penetratin (pAntp), along with the entire sequence of tumor necrosis factor-α (TNF-α), were attached to the N-terminal and C-terminal of the CD70 epitopes. Computational assessments were performed on these chimeric vaccines for antigenicity, allergenicity, peptide toxicity, population coverage, and physicochemical properties. Furthermore, refined 3D constructs were subjected to a range of analyses, encompassing structural B-cell epitope prediction and molecular docking. The chosen vaccine construct underwent diverse assessments such as molecular dynamics simulation, immune response simulation, and in silico cloning. All vaccines comprised antigenic, nontoxic, and nonallergenic epitopes, ensuring extensive global population coverage. The vaccine constructs demonstrated favorable physicochemical characteristics. The binding affinity of chimeric vaccines to the TNF receptor remained relatively stable, influenced by the alignment of vaccine components. Molecular docking and dynamics analyses predicted stable interactions between CD70-CPP-TNF and the TNF receptor, indicating potential efficacy. In silico codon optimization and cloning of the vaccine nucleic acid sequence were accomplished using the pET28a plasmid. Furthermore, this vaccine displayed the capacity to modulate humoral and cellular immune responses. Overall, the results suggest therapeutic potential for the chimeric CD70-CPP-TNF vaccine against RCC. However, validation through in vitro and in vivo experiments is necessary. This trial is registered with NCT04696731 and NCT04046445.

A nanobody inhibiting porcine reproductive and respiratory syndrome virus replication via blocking self-interaction of viral nucleocapsid protein

Porcine reproductive and respiratory syndrome (PRRS) is a serious global pig industry disease. Understanding the mechanism of viral replication and developing efficient antiviral strategies are necessary for combating with PRRS virus (PRRSV) infection. Recently, nanobody is considered to be a promising antiviral drug, especially for respiratory viruses. The present study evaluated two nanobodies against PRRSV nucleocapsid (N) protein (PRRSV-N-Nb1 and -Nb2) for their anti-PRRSV activity in vitro and in vivo. The results showed that intracellularly expressed PRRSV-N-Nb1 significantly inhibited PRRSV-2 replication in MARC-145 cells (approximately 100%). Then, the PRRSV-N-Nb1 fused with porcine IgG Fc (Nb1-pFc) as a delivering tag was produced and used to determine its effect on PRRSV-2 replication in porcine alveolar macrophages (PAMs) and pigs. The inhibition rate of Nb1-pFc against PRRSV-2 in PAMs could reach >90%, and it can also inhibit viral replication in vivo. Epitope mapping showed that the motif Serine 105 (S105) in PRRSV-2 N protein was the key amino acid binding to PRRSV-N-Nb1, which is also pivotal for the self-interaction of N protein via binding to Arginine 97. Moreover, viral particles were not successfully rescued when the S105 motif was mutated to Alanine (S105A). Attachment, entry, genome replication, release, docking model analysis, and blocking enzyme-linked immunosorbent assay (ELISA) indicated that the binding of PRRSV-N-Nb1 to N protein could block its self-binding, which prevents the viral replication of PRRSV. PRRSV-N-Nb1 may be a promising drug to counter PRRSV-2 infection. We also provided some new insights into the molecular basis of PRRSV N protein self-binding and assembly of viral particles.IMPORTANCEPorcine reproductive and respiratory syndrome virus (PRRSV) causes serious economic losses to the swine industry worldwide, and there are no highly effective strategies for prevention. Nanobodies are considered a promising novel approach for treating diseases because of their ease of production and low costing. Here, we showed that PRRSV-N-Nb1 against PRRSV-N protein significantly inhibited PRRSV-2 replication in vitro and in vivo. Furthermore, we demonstrated that the motif Serine 105 (S105) in PRRSV-N protein was the key amino acid to interact with PRRSV-N-Nb1 and bond to its motif R97, which is important for the self-binding of N protein. The PRRSV-N-Nb1 could block the self-interaction of N protein following viral assembly. These findings not only provide insights into the molecular basis of PRRSV N protein self-binding as a key factor for viral replication for the first time but also highlight a novel target for the development of anti-PRRSV replication drugs.

ABAG-docking benchmark: a non-redundant structure benchmark dataset for antibody-antigen computational docking

Accurate prediction of antibody-antigen complex structures is pivotal in drug discovery, vaccine design and disease treatment and can facilitate the development of more effective therapies and diagnostics. In this work, we first review the antibody-antigen docking (ABAG-docking) datasets. Then, we present the creation and characterization of a comprehensive benchmark dataset of antibody-antigen complexes. We categorize the dataset based on docking difficulty, interface properties and structural characteristics, to provide a diverse set of cases for rigorous evaluation. Compared with Docking Benchmark 5.5, we have added 112 cases, including 14 single-domain antibody (sdAb) cases and 98 monoclonal antibody (mAb) cases, and also increased the proportion of Difficult cases. Our dataset contains diverse cases, including human/humanized antibodies, sdAbs, rodent antibodies and other types, opening the door to better algorithm development. Furthermore, we provide details on the process of building the benchmark dataset and introduce a pipeline for periodic updates to keep it up to date. We also utilize multiple complex prediction methods including ZDOCK, ClusPro, HDOCK and AlphaFold-Multimer for testing and analyzing this dataset. This benchmark serves as a valuable resource for evaluating and advancing docking computational methods in the analysis of antibody-antigen interaction, enabling researchers to develop more accurate and effective tools for predicting and designing antibody-antigen complexes. The non-redundant ABAG-docking structure benchmark dataset is available at https://github.com/Zhaonan99/Antibody-antigen-complex-structure-benchmark-dataset.

APRF1 Interactome Reveals HSP90 as a New Player in the Complex That Epigenetically Regulates Flowering Time in Arabidopsis thaliana

WD40 repeat proteins (WDRs) are present in all eukaryotes and include members that are implicated in numerous cellular activities. They act as scaffold proteins and thus as molecular "hubs" for protein-protein interactions, which mediate the assembly of multifunctional complexes that regulate key developmental processes in Arabidopsis thaliana, such as flowering time, hormonal signaling, and stress responses. Despite their importance, many aspects of their putative functions have not been elucidated yet. Here, we show that the late-flowering phenotype of the anthesis promoting factor 1 (aprf1) mutants is temperature-dependent and can be suppressed when plants are grown under mild heat stress conditions. To gain further insight into the mechanism of APRF1 function, we employed a co-immunoprecipitation (Co-IP) approach to identify its interaction partners. We provide the first interactome of APRF1, which includes proteins that are localized in several subcellular compartments and are implicated in diverse cellular functions. The dual nucleocytoplasmic localization of ARRF1, which was validated through the interaction of APRF1 with HEAT SHOCK PROTEIN 1 (HSP90.1) in the nucleus and with HSP90.2 in the cytoplasm, indicates a dynamic and versatile involvement of APRF1 in multiple biological processes. The specific interaction of APRF1 with the chaperon HSP90.1 in the nucleus expands our knowledge regarding the epigenetic regulation of flowering time in A. thaliana and further suggests the existence of a delicate thermoregulated mechanism during anthesis.

Development and use of machine learning algorithms in vaccine target selection

Computer-aided discovery of vaccine targets has become a cornerstone of rational vaccine design. In this article, I discuss how Machine Learning (ML) can inform and guide key computational steps in rational vaccine design concerned with the identification of B and T cell epitopes and correlates of protection. I provide examples of ML models, as well as types of data and predictions for which they are built. I argue that interpretable ML has the potential to improve the identification of immunogens also as a tool for scientific discovery, by helping elucidate the molecular processes underlying vaccine-induced immune responses. I outline the limitations and challenges in terms of data availability and method development that need to be addressed to bridge the gap between advances in ML predictions and their translational application to vaccine design.

Core-genome-mediated promising alternative drug and multi-epitope vaccine targets prioritization against infectious Clostridium difficile

Prevention of Clostridium difficile infection is challenging worldwide owing to its high morbidity and mortality rates. C. difficile is currently being classified as an urgent threat by the CDC. Devising a new therapeutic strategy become indispensable against C. difficile infection due to its high rates of reinfection and increasing antimicrobial resistance. The current study is based on core proteome data of C. difficile to identify promising vaccine and drug candidates. Immunoinformatics and vaccinomics approaches were employed to construct multi-epitope-based chimeric vaccine constructs from top-ranked T- and B-cell epitopes. The efficacy of the designed vaccine was assessed by immunological analysis, immune receptor binding potential and immune simulation analyses. Additionally, subtractive proteomics and druggability analyses prioritized several promising and alternative drug targets against C. difficile. These include FMN-dependent nitroreductase which was prioritized for pharmacophore-based virtual screening of druggable molecule databases to predict potent inhibitors. A MolPort-001-785-965 druggable molecule was found to exhibit significant binding affinity with the conserved residues of FMN-dependent nitroreductase. The experimental validation of the therapeutic targets prioritized in the current study may worthy to identify new strategies to combat the drug-resistant C. difficile infection.

Molecular Dynamics Simulations on Spike Protein Mutants Binding with Human β Defensin Type 2

Human β defensin type 2 (hBD-2), a cationic cysteine-rich peptide secreted from the human innate immune system, can bind Spike-RBD at the same site as receptor ACE2, thus blocking viral entry into ACE2-expressing cells. In order to find out the impact of CoV-2 mutations on hBD-2's antiviral activity, it is important to investigate the binding and interaction of hBD-2 with RBD mutants. All-atom molecular dynamics simulations were conducted on typical RBD mutants, including N501Y, E484K, P479S, T478I, S477N, N439K, K417N, and N501Y-E484K-K417N, binding with hBD-2. Starting from the stable binding structure of hBD-2 and wt-RBD and ClusPro and HADDOCK docking-predicted initial structures, the RBD variants bound with hBD-2 simulations were set up, and NAMD simulations were conducted. Based on the structure and dynamics analysis, it was found that most RBD variants can still form a similar number of hydrogen bonds with hBD-2, in addition to having a similar-sized buried surface area (BSA) and a similar binding interface to the RBD wildtype. However, the RBD triple mutant formed a less stable binding structure with hBD-2 than other variants. Additionally, the free energy perturbation (FEP) method was applied to calculate the contribution of key mutant residues to the binding and the free energy change caused by the mutations. The result shows that N439K, K417N, and the trimutation increase the binding free energy of RBD with hBD-2; thus, RBD should bind less stably with hBD-2. E484K decreases the binding free energy, thus it should bind more stably with hBD-2, while N501Y, S477N, T478I, and P479S almost do not change the binding free energy with hBD-2. The MM-GBSA method predicted the binding interaction energy which shows that the trimutant should be able to escape the binding with hBD-2 but N501Y should not. The result can provide insight into understanding the functional mechanism of hBD-2 combating SARS-CoV-2 mutants.

Immunoinformatics-guided approach for designing a pan-proteome multi-epitope subunit vaccine against African swine fever virus

Despite being identified over a hundred years ago, there is still no commercially available vaccine for the highly contagious and deadly African swine fever virus (ASFV). This study used immunoinformatics for the rapid and inexpensive designing of a safe and effective multi-epitope subunit vaccine for ASFV. A total of 18,858 proteins from 100 well-annotated ASFV proteomes were screened using various computational tools to identify potential epitopes, or peptides capable of triggering an immune response in swine. Proteins from genotypes I and II were prioritized for their involvement in the recent global ASFV outbreaks. The screened epitopes exhibited promising qualities that positioned them as effective components of the ASFV vaccine. They demonstrated antigenicity, immunogenicity, and cytokine-inducing properties indicating their ability to induce potent immune responses. They have strong binding affinities to multiple swine allele receptors suggesting a high likelihood of yielding more amplified responses. Moreover, they were non-allergenic and non-toxic, a crucial prerequisite for ensuring safety and minimizing any potential adverse effects when the vaccine is processed within the host. Integrated with an immunogenic 50S ribosomal protein adjuvant and linkers, the epitopes formed a 364-amino acid multi-epitope subunit vaccine. The ASFV vaccine construct exhibited notable immunogenicity in immune simulation and molecular docking analyses, and stable profiles in secondary and tertiary structure assessments. Moreover, this study designed an optimized codon for efficient translation of the ASFV vaccine construct into the Escherichia coli K-12 expression system using the pET28a(+) vector. Overall, both sequence and structural evaluations suggested the potential of the ASFV vaccine construct as a candidate for controlling and eradicating outbreaks caused by the pathogen.

Elucidating the binding mechanism of SARS-CoV-2 NSP6-TBK1 and structure-based designing of phytocompounds inhibitors for instigating the host immune response

SARS-CoV-2, also referred to as severe acute respiratory syndrome coronavirus 2, is the virus responsible for causing COVID-19, an infectious disease that emerged in Wuhan, China, in December 2019. Among its crucial functions, NSP6 plays a vital role in evading the human immune system by directly interacting with a receptor called TANK-binding kinase (TBK1), leading to the suppression of IFNβ production. Consequently, in the present study we used the structural and biophysical approaches to analyze the effect of newly emerged mutations on the binding of NSP6 and TBK1. Among the identified mutations, four (F35G, L37F, L125F, and I162T) were found to significantly destabilize the structure of NSP6. Furthermore, the molecular docking analysis highlighted that the mutant NSP6 displayed its highest binding affinity with TBK1, exhibiting docking scores of -1436.2 for the wildtype and -1723.2, -1788.6, -1510.2, and -1551.7 for the F35G, L37F, L125F, and I162T mutants, respectively. This suggests the potential for an enhanced immune system evasion capability of NSP6. Particularly, the F35G mutation exhibited the strongest binding affinity, supported by a calculated binding free energy of -172.19 kcal/mol. To disrupt the binding between NSP6 and TBK1, we conducted virtual drug screening to develop a novel inhibitor derived from natural products. From this screening, we identified the top 5 hit compounds as the most promising candidates with a docking score of -6.59 kcal/mol, -6.52 kcal/mol, -6.32 kcal/mol, -6.22 kcal/mol, and -6.21 kcal/mol. The molecular dynamic simulation of top 3 hits further verified the dynamic stability of drugs-NSP6 complexes. In conclusion, this study provides valuable insight into the higher infectivity of the SARS-CoV-2 new variants and a strong rationale for the development of novel drugs against NSP6.

Reverse vaccinology and immunoinformatics approach to design a chimeric epitope vaccine against Orientia tsutsugamushi

Scrub typhus is a vector-borne infectious disease caused by Orientia tsutsugamushi and it is reportedly associated with up to 20 % of hospitalized cases of febrile illnesses. The major challenge of vaccine development is the lack of identified antigens that can induce both heterotypic and homotypic immunity including the production of antibodies, cytotoxic T lymphocyte, and helper T lymphocytes. We employed a comprehensive immunoinformatic prediction algorithm to identify immunogenic epitopes of the 56-kDa type-specific cell membrane surface antigen and surface cell antigen A of O. tsutsugamushi to select potential candidates for developing vaccines and diagnostic assays. We identified 35 linear and 29 continuous immunogenic B-cell epitopes and 51 and 27 strong-binding T-cell epitopes of major histocompatibility complex class I and class II molecules, respectively, in the conserved and variable regions of the 56-kDa type-specific surface antigen. The predicted B- and T-cell epitopes were used to develop immunogenic multi-epitope candidate vaccines and showed to elicit a broad-range of immune protection. A stable interactions between the multi-epitope vaccines and the host fibronectin protein were observed using docking and simulation methods. Molecular dynamics simulation studies demonstrated that the multi-epitope vaccine constructs and fibronectin docked models were stable during simulation time. Furthermore, the multi-epitope vaccine exhibited properties such as antigenicity, non-allergenicity and ability to induce interferon gamma production and had strong associations with their respective human leukocyte antigen alleles of world-wide population coverage. A correlation of immune simulations and the in-silico predicted immunogenic potential of multi-epitope vaccines implicate for further investigations to accelerate designing of epitope-based vaccine candidates and chimeric antigens for development of serological diagnostic assays for scrub typhus.

Advancements and hurdles in the development of a vaccine for triple-negative breast cancer: A comprehensive review of multi-omics and immunomics strategies

Triple-Negative Breast Cancer (TNBC) presents a significant challenge in oncology due to its aggressive behavior and limited therapeutic options. This review explores the potential of immunotherapy, particularly vaccine-based approaches, in addressing TNBC. It delves into the role of immunoinformatics in creating effective vaccines against TNBC. The review first underscores the distinct attributes of TNBC and the importance of tumor antigens in vaccine development. It then elaborates on antigen detection techniques such as exome sequencing, HLA typing, and RNA sequencing, which are instrumental in identifying TNBC-specific antigens and selecting vaccine candidates. The discussion then shifts to the in-silico vaccine development process, encompassing antigen selection, epitope prediction, and rational vaccine design. This process merges computational simulations with immunological insights. The role of Artificial Intelligence (AI) in expediting the prediction of antigens and epitopes is also emphasized. The review concludes by encapsulating how Immunoinformatics can augment the design of TNBC vaccines, integrating tumor antigens, advanced detection methods, in-silico strategies, and AI-driven insights to advance TNBC immunotherapy. This could potentially pave the way for more targeted and efficacious treatments.

The ER-Golgi transport of influenza virus through NS1-Sec13 association during virus replication

IMPORTANCE

Influenza A virus is a respiratory virus that can cause complications such as acute bronchitis and secondary bacterial pneumonia. Drug therapies and vaccines are available against influenza, albeit limited by drug resistance and the non-universal vaccine administration. Hence there is a need for host-targeted therapies against influenza to provide an effective alternative therapeutic target. Sec13 was identified as a novel host interactor of influenza. Endoplasmic reticulum-to-Golgi transport is an important pathway of influenza virus replication and viral export. Specifically, Sec13 has a functional role in influenza replication and virulence.

2B4: A potential target in Staphylococcus aureus associated allergic inflammation

Staphylococcus aureus (SA) and its exotoxins activate eosinophils (Eos) and mast cells (MCs) via CD48, a GPI-anchored receptor belonging to the signaling lymphocytes activation molecules (SLAM) family. 2B4 (CD244), an immuno-regulatory transmembrane receptor also belonging to the SLAM family, is the high-affinity ligand for CD48. 2B4 is expressed on several leukocytes including NK cells, T cells, basophils, monocytes, dendritic cells (DCs), and Eos. In the Eos and MCs crosstalk carried out by physical and soluble interactions (named the 'allergic effector unit', AEU), 2B4-CD48 binding plays a central role. As CD48 and 2B4 share some structural characteristics and SA colonization accompanies most of the allergic diseases, we hypothesized that SA exotoxins (e.g. Staphylococcus enterotoxin B, SEB) can also bind and activate 2B4 and thereby possibly further aggravate inflammation. To check our hypothesis, we used in vitro, in silico, and in vivo methods. By enzyme-linked immunosorbent assay (ELISA), flow cytometry (FC), fluorescence microscopy, and microscale thermophoresis, we have shown that SEB can bind specifically to 2B4. By Eos short- and long-term activation assays, we confirmed the functionality of the SEB-2B4 interaction. Using computational modeling, we identified possible SEB-binding sites on human and mouse 2B4. Finally, in vivo, in an SEB-induced peritonitis model, 2B4-KO mice showed a significant reduction of inflammatory features compared with WT mice. Altogether, the results of this study confirm that 2B4 is an important receptor in SEB-mediated inflammation, and therefore a role is suggested for 2B4 in SA associated inflammatory conditions.

Development and immunological evaluation of an mRNA-based vaccine targeting Naegleria fowleri for the treatment of primary amoebic meningoencephalitis

More than 95% of patients fall victim to primary amoebic meningoencephalitis (PAM), a fatal disease attacking the central nervous system. Naegleria fowleri, a brain-eating microorganism, is PAM's most well-known pathogenic ameboflagellate. Despite the use of antibiotics, the fatality rate continues to rise as no clinical trials have been conducted against this disease. To address this, we mined the UniProt database for pathogenic proteins and selected assumed epitopes to create an mRNA-based vaccine. We identified thirty B-cell and T-cell epitopes for the vaccine candidate. These epitopes, secretion boosters, subcellular trafficking structures, and linkers were used to construct the vaccine candidate. Through predictive modeling and confirmation via the Ramachandran plot (with a quality factor of 92.22), we assessed secondary and 3D structures. The adjuvant RpfE was incorporated to enhance the vaccine construct's immunogenicity (GRAVY index: 0.394, instability index: 38.99, antigenicity: 0.8). The theoretical model of immunological simulations indicated favorable responses from both innate and adaptive immune cells, with memory cells expected to remain active for up to 350 days post-vaccination, while the antigen was eliminated from the body within 24 h. Notably, strong interactions were observed between the vaccine construct and TLR-4 (- 11.9 kcal/mol) and TLR-3 (- 18.2 kcal/mol).

In silico analysis of virulence factors of Streptococcus uberis for a chimeric vaccine design

Streptococcus uberis is one of the causative agents of bovine mastitis, which has detrimental effects on animal health and the dairy industry. Despite decades of research, the requirement for effective vaccines against the disease remains unmet. The goal of this study was to create a multi-epitope vaccine using five virulence factors of S. uberis through the reverse vaccinology approach, which has been employed due to its high efficiency and applicability. Plasminogen activator A (PauA), glyceraldehyde-3-phosphate dehydrogenase C (GapC), C5a peptidase, S. uberis adhesion molecule (SUAM), and sortase A (SrtA) were selected for the T cytotoxic (CTL) and B cell epitope analyses as they were extensively studied in S. uberis or other pathogens. Eighteen CTL and ten B cell epitopes that were antigenic, non-toxic, and non-allergenic were selected in order to design a chimeric vaccine candidate that in silico analysis revealed to be potentially immunogenic, non-allergenic, and stable. Molecular docking analysis of the vaccine candidate with Toll-like receptor (TLR) 2 and TLR 4 revealed stable interactions between the candidate and the immune receptors. Meanwhile, the stability of the docked complexes was confirmed using normal mode analysis. Additionally, in silico immune simulation of the vaccine candidate demonstrated the stimulation of primary immune responses, indicating that the chimeric protein can hold promise as a viable vaccine candidate for preventing S. uberis mastitis. Moreover, the current study can provide a background for designing epitope-based vaccines based on the explored epitopes.

Aggregation Dynamics Characteristics of Seven Different Aβ Oligomeric Isoforms-Dependence on the Interfacial Interaction

The aggregation of β-amyloid (Aβ) peptides has been confirmed to be associated with the onset of Alzheimer's disease (AD). Among the three phases of Aβ aggregation, the lag phase has been considered to be the best time for early Aβ pathological deposition clinical intervention and prevention for potential patients with normal cognition. Aβ peptide exists in various lengths in vivo, and Aβ oligomer in the early lag phase is neurotoxic but polymorphous and metastable, depending on Aβ length (isoform), molecular weight, and specific phase, and therefore hardly characterized experimentally. To cope with the problem, molecular dynamics simulation was used to investigate the aggregation process of five monomers for each of the seven common Aβ isoforms during the lag phase. Results showed that Aβ(1-40) and Aβ(1-38) monomers aggregated faster than their truncated analogues Aβ(4-40) and Aβ(4-38), respectively. However, the aggregation rate of Aβ(1-42) was slower than that of its truncated analogues Aβ(4-42) rather than that of Aβpe(3-42). More importantly, Aβ(1-38) is first predicted as more likely to form stable hexamer than the remaining five Aβ isoforms, as Aβ(1-42) does. It is hydrophobic interaction mainly (>50%) from the interfacial β1 and β2 regions of two reactants, pentamer and monomer, aggregated by Aβ(1-38)/Aβ(1-42) rather than by other Aβ isoforms, that drives the hexamer stably as a result of the formation of the effective hydrophobic collapse. This paper provides new insights into the aggregation characteristics of Aβ with different lengths and the conditions necessary for Aβ to form oligomers with a high molecular weight in the early lag phase, revealing the dependence of Aβ hexamer formation on the specific interfacial interaction.

Designing of a new multi-epitope vaccine against Leishmania major using Leish-F1 epitopes: An In-silico study

Cutaneous leishmaniasis (CL) is the most common form of the disease which can cause malignant lesions on the skin. Vaccination for the prevention and treatment of leishmaniasis can be the most effective way to combat this disease. In this study, we designed a novel multi-epitope vaccine against Leishmania major (L. major) using immunoinformatics tools to assess its efficacy in silico. Sequences of Leish-F1 protein (TSA, Leif, and LMSTI1) of L. major were taken from GenBank. The helper T (Th) and cytotoxic T (Tc) epitopes of the protein were predicted. The final multi-epitope consisted of 18 CTL epitopes joined by AAY linker. There were also nine HTL epitopes in the structure of the vaccine construct, joined by GPGPG linker. The profilin adjuvant (the toll-like receptor 11 agonist) was also added into the construct by AAY Linker. There were 613 residues in the structure of the vaccine construct. The multi-epitope vaccine candidate was stable and non-allergic. The data obtained from the binding of final multi-epitope vaccine-TLR11 residues (band lengths and weighted scores) unveiled the ligand and the receptor high score of binding affinity. Moreover, in silico assessment of the vaccine construct cloning achieved its suitable expression in E. coli host. Based on these results, the current multi-epitope vaccine prevents L. major infection in silico, while further confirmatory assessments are required.

White matter hyperintensity genetic risk factor TRIM47 regulates autophagy in brain endothelial cells

White matter hyperintensity (WMH) is strongly correlated with age-related dementia and hypertension, but its pathogenesis remains obscure. GWAS identified TRIM47 at 17q25 locus as a top genetic risk factor for WMH formation. TRIM family is a class of E3 ubiquitin ligase with pivotal functions in autophagy, which is critical for brain endothelial cell (ECs) remodeling during hypertension. We hypothesize that TRIM47 regulates autophagy and its loss-of-function disturbs cerebrovasculature. Based on transcriptomics and immunohistochemistry, TRIM47 is found selectively expressed by brain ECs in human and mouse, and its transcription is upregulated by artificially-induced autophagy while downregulated in hypertension-like conditions. Using in silico simulation, immunocytochemistry and super-resolution microscopy, we identified the highly conserved binding site between TRIM47 and the LIR (LC3-interacting region) motif of LC3B. Importantly, pharmacological autophagy induction increased Trim47 expression on mouse ECs (b.End3) culture, while silencing Trim47 significantly increased autophagy with ULK1 phosphorylation induction, transcription and vacuole formation. Together, we confirm that TRIM47 is an endogenous inhibitor of autophagy in brain ECs, and such TRIM47-mediated regulation connects genetic and physiological risk factors for WMH formation but warrants further investigation.

SUMMARY STATEMENT

TRIM47, top genetic risk factor for white matter hyperintensity formation, is a negative regulator of autophagy in brain endothelial cells and implicates a novel cellular mechanism for age-related cerebrovascular changes.

Adaptive evolution of the Clf-Sdr subfamily contributes to Staphylococcus aureus musculoskeletal infection: Evidence from comparative genomics

Persistent Staphylococcus aureus infections of the musculoskeletal system are a challenge in clinical practice. Although extensive studies on the genotypic changes in S. aureus in soft tissue and blood system infections have been conducted, little is known about how S. aureus adapts to the microenvironment of the musculoskeletal system. Here, we used comparative genomics to analyze the isolates from patients with an S. aureus infection of the musculoskeletal system. We observed that mutations in the Clf-Sdr subfamily proteins frequently occurred during persistent infections. Furthermore, these mutations were primarily located in the non-active site (R region), rather than in the active site (A region). Mechanistically, the clfA/B mutation enhanced the S. aureus biofilm formation ability through the binding to fibrinogen and intercellular adhesion. Complementation studies using the USA300-ΔMSCRAMMs strains clfA and clfB revealed that mutations in both the A and R regions could enhance their corresponding function. The results of protein structure prediction and ligand-binding simulations suggest that these mutations influence the protein structure and ligand binding. In conclusion, our study suggests that the Clf-Sdr subfamily mutations may be one of the mechanisms contributing to persistent S. aureus infections of the musculoskeletal system.

Development of a novel multi-epitope oral DNA vaccine for rabies based on a food-borne microbial vector

Rabies has been with humans for a long time, and its special transmission route and almost 100 % lethality rate made it once a nightmare for humans. In this study, by predicting the rabies virus glycoprotein outer membrane region and nucleoprotein B-cell antigenic epitopes, the coding sequence of the predicted highly antigenic polypeptide region obtained was assembled using the eukaryotic expression vector pcDNA3.1(-), and then E. coli was used as the delivery vector. The immunogenicity and protective properties of the vaccine were verified by in vivo and in vitro experiments, which demonstrated that the vaccine could produce antibodies in mice and prolong the survival time of mice exposed to the strong virus without any side effects. This study demonstrated that the preparation of an oral rabies DNA vaccine using food-borne microorganisms as a transport vehicle is feasible and could be a new strategy to eradicate rabies starting with wild animals.

Prolonged exposure of environmental concentration benzo[a]pyrene promoted cancer stemness through AhR/PKA/SOX2 dependent pathway in small cell lung cancer

Benzo[a]pyrene (BaP) is commonly found in the environment as a result of incomplete combustion of organic materials and cigarette smoke. Epidemiological studies have consistently suggested that elderly smokers are at higher risk for small cell lung cancer (SCLC), with risks and clinical stages increasing with the intensity and duration of smoking. However, the underlying mechanism remains insufficiently investigated. Here, we established a positive correlation between smoking and BaP metabolite 3-hydroxybenzo[a]pyrene (3OH-BaP) in urine. The pooled standardized mean difference of urinary 3OH-BaP concentration for smokers versus nonsmokers was 5.18 (95 % CI 2.86-7.50). Clinical data suggested that smoking led to more lymph node metastasis, higher pathological N-stage, and worse overall survival in SCLC patients. We identified 75 genes that participate in BaP-associated cancer stemness of SCLC from Comparative Toxicogenomics Database and validated the expression of these candidate genes in SCLC patient samples. Protein kinase cAMP-activated catalytic subunit alpha (PRKACA) was found to be most upregulated in SCLC patients and in vitro experiments indicated that long-term exposure of SCLC cells to BaP, at the concentration equivalent to those detected in blood, increased PKA protein level. Further investigation revealed that PKA could directly interact with SOX2 and protect SOX2 from COP1-mediated ubiquitination and degradation. Upregulated SOX2 then contributed to the stemness and metastasis of SCLC cells while inhibition of aryl hydrocarbon receptor (AhR) signaling pathway abolished BaP induced PKA expression and downstream PKA/SOX2 axis. Our findings firstly pinpoint BaP exposure as a high-risk factor for SCLC and worse outcomes in patients, with the underlying mechanism being the activation of cancer stemness of SCLC via the AhR/PKA/SOX2 axis.

Proteomic analysis of boar seminal plasma: Putative markers for fertility based on capacity of semen preservation at 17°C

Boar seminal plasma (SP) proteins were associated with differences on sperm resistance to cooling at 17°C. However, information about seminal plasma proteins in boars classified by capacity of semen preservation and in vivo fertility remains lacking. Thus, the objective was to evaluate the SP proteome in boars classified by capacity of semen preservation and putative biomarkers for fertility. The ejaculates from high-preservation (HP) showed higher progressive motility during all 5 days than the low-preservation (LP) boars. There was no difference for farrowing rate between ejaculates from LP (89.7%) and HP boars (88.4%). The LP boars presented lower total piglets born (14.0 ± 0.2) than HP (14.8 ± 0.2; p < 0.01). A total of 257 proteins were identified, where 184 were present in both classes of boar, and 41 and 32 were identified only in LP and HP boars, respectively. Nine proteins were differently expressed: five were more abundant in HP (SPMI, ZPBP1, FN1, HPX, and C3) and four in LP boars (B2M, COL1A1, NKX3-2, and MPZL1). The HP boars had an increased abundance of SP proteins related to sperm resistance and fecundation process which explains the better TPB. LP boars had a higher abundance of SP proteins associated with impaired spermatogenesis.

GRAMM Web Server for Protein Docking

Prediction of the structure of protein complexes by docking methods is a well-established research field. The intermolecular energy landscapes in protein-protein interactions can be used to refine docking predictions and to detect macro-characteristics, such as the binding funnel. A new GRAMM web server for protein docking predicts a spectrum of docking poses that characterize the intermolecular energy landscape in protein interaction. A user-friendly interface provides options to choose free or template-based docking, as well as other advanced features, such as clustering of the docking poses, and interactive visualization of the docked models.

Interaction of Tau with G-Protein-Coupled Purinergic P2Y12 Receptor by Molecular Docking and Molecular Dynamic Simulation

Alzheimer's disease, a progressive neurological disorder, is characterized by the accumulation of neurofibrillary tangles and senile plaques by Tau and amyloid-β, respectively, in the brain microenvironment. The misfolded protein aggregates interact with several components of neuronal and glial cells such as membrane lipids, receptors, transporters, enzymes, cytoskeletal proteins, etc. Under pathological conditions, Tau interacts with several G-protein-coupled receptors (GPCRs), which undergoes either receptor signaling or desensitization followed by internalization of the protein complex. The purinergic GPCR, P2Y12 which is expressed in microglial cells, plays a key role in its activation and migration. Microglial cells sense and migrate to the site of injury aided by P2Y12 receptor that interacts with ADP released from damaged cells. P2Y12 receptor also interacts with misfolded Tau accumulated at the extracellular space and promotes receptor-mediated internalization. Immunocolocalization and co-immunoprecipitation studies demonstrated the interaction of Tau species with the P2Y12 receptor. Later, in-silico analyses were carried out with the repeat domain of Tau (TauRD), which has been identified as the interacting partner of P2Y12 receptor by in-vitro studies. Molecular docking and molecular dynamics simulation studies show the stability and the type of interaction in TauRD-receptor complex. Tau interaction with P2Y12 receptor plays a significant role in maintaining the active state of microglia which could lead to neuroinflammation and neuronal damage in AD brain. Hence, blocking P2Y12-Tau interaction and P2Y12-mediated Tau internalization in microglial cells could be possible therapeutic strategies in downregulating the severity of neuroinflammation in AD.

Molecular Dynamics and Other HPC Simulations for Drug Discovery

High performance computing (HPC) is taking an increasingly important place in drug discovery. It makes possible the simulation of complex biochemical systems with high precision in a short time, thanks to the use of sophisticated algorithms. It promotes the advancement of knowledge in fields that are inaccessible or difficult to access through experimentation and it contributes to accelerating the discovery of drugs for unmet medical needs while reducing costs. Herein, we report how computational performance has evolved over the past years, and then we detail three domains where HPC is essential. Molecular dynamics (MD) is commonly used to explore the flexibility of proteins, thus generating a better understanding of different possible approaches to modulate their activity. Modeling and simulation of biopolymer complexes enables the study of protein-protein interactions (PPI) in healthy and disease states, thus helping the identification of targets of pharmacological interest. Virtual screening (VS) also benefits from HPC to predict in a short time, among millions or billions of virtual chemical compounds, the best potential ligands that will be tested in relevant assays to start a rational drug design process.

A dissected non-ribosomal peptide synthetase maintains activity

Non-ribosomal peptide synthetases (NRPSs) generate chemically complex compounds and their modular architecture suggests that changing their domain organization can predictably alter their products. Ebony, a small three-domain NRPS, catalyzes the formation of β-alanine containing amides from biogenic amines. To examine the necessity of interdomain interactions, we modeled and docked domains of Ebony to reveal potential interfaces between them. Testing the same domain combinations in vitro showed that 8 % of activity was preserved after Ebony was dissected into a di-domain and a detached C-terminal domain, suggesting that sufficient interaction was maintained after dissection. Our work creates a model to identify domain interfaces necessary for catalysis, an important step toward utilizing Ebony as a combinatorial engineering platform for novel amides.