Performance and Its Limits in Rigid Body Protein-Protein Docking

Decoding the genetic landscape of allergic rhinitis: a comprehensive network analysis revealing key genes and potential therapeutic targets

BACKGROUND

Allergic Rhinitis (AR), an inflammatory affliction impacting the upper respiratory tract, has been registering a substantial surge in incidence across the globe.

METHODS

We embarked on examination of differentially expressed genes (DEGs) and the Weighted Gene Co-Expression Network Analysis (WGCNA). With this armory of genes identified, we engaged the tools of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Our study continued with the establishment of a protein-protein interaction (PPI) network and the application of LASSO regression. Finally, we leveraged a docking model to elucidate potential drug-gene interactions involving these key genes.

RESULTS

Through WGCNA and different express genes screening, PPI network was performed, identifying top 20 key genes, including CD44, CD69, CD274. LASSO regression identified three independent factors, STARD5, CST1, and CHAC1, that were significantly associated with AR. A predictive model was developed with an AUC value over 0.75. Also, 105 potential therapeutic agents were discovered, including Fluorouracil, Cyclophosphamide, Doxorubicin, and Hydrocortisone, offering promising therapeutic strategies for AR.

CONCLUSION

By fuzing DEGs with key genes derived from WGCNA, this study has illuminated a comprehensive network of gene interactions involved in the pathogenesis of AR, paving the way for future biomarker and therapeutic target discovery in AR.

Designing a T-cell epitope-based vaccine using in silico approaches against the Sal k 1 allergen of Salsola kali plant

Allergens originated from Salsola kali (Russian thistle) pollen grains are one of the most important sources of aeroallergens causing pollinosis in desert and semi-desert regions. T-cell epitope-based vaccines (TEV) are more effective among different therapeutic approaches developed to alleviate allergic diseases. The physicochemical properties, and B as well as T cell epitopes of Sal k 1 (a major allergen of S. kali) were predicted using immunoinformatic tools. A TEV was constructed using the linkers EAAAK, GPGPG and the most suitable CD4+ T cell epitopes. RS04 adjuvant was added as a TLR4 agonist to the amino (N) and carboxyl (C) terminus of the TEV protein. The secondary and tertiary structures, solubility, allergenicity, toxicity, stability, physicochemical properties, docking with immune receptors, BLASTp against the human and microbiota proteomes, and in silico cloning of the designed TEV were assessed using immunoinformatic analyses. Two CD4+ T cell epitopes of Sal k1 that had high affinity with different alleles of MHC-II were selected and used in the TEV. The molecular docking of the TEV with HLADRB1, and TLR4 showed TEV strong interactions and stable binding pose to these receptors. Moreover, the codon optimized TEV sequence was cloned between NcoI and XhoI restriction sites of pET-28a(+) expression plasmid. The designed TEV can be used as a promising candidate in allergen-specific immunotherapy against S. kali. Nonetheless, effectiveness of this vaccine should be validated through immunological bioassays.

Molecular Insights into the Inhibitory Role of α-Crystallin against γD-Crystallin Aggregation

Cataracts, a major cause of global blindness, contribute significantly to the overall prevalence of blindness. The opacification of the lens, resulting in cataract formation, primarily occurs due to the aggregation of crystallin proteins within the eye lens. Despite the high concentration of these crystallins, they remarkably maintain the lens transparency and refractive index. α-Crystallins (α-crys), acting as chaperones, play a crucial role in preventing crystallin aggregation, although the exact molecular mechanism remains uncertain. In this study, we employed a combination of molecular docking, all-atom molecular dynamics simulations, and advanced free energy calculations to investigate the interaction between γD-crystallin (γD-crys), a major structural protein of the eye lens, and α-crystallin proteins. Our findings demonstrate that α-crys exhibits an enhanced affinity for the NTD2 and CTD4 regions of γD-crys. The NTD2 and CTD4 regions form the interface between the N-terminal domain (NTD) and the C-terminal domain (CTD) of the γD-crys protein. By binding to the interface region between the NTD and CTD of the protein, α-crys effectively inhibits the formation of domain-swapped aggregates and mitigates protein aggregation. Analysis of the Markov state models using molecular dynamics trajectories confirms that minimum free energy conformations correspond to the binding of the α-crystallin domain (ACD) of α-crys to NTD2 and CTD4 that form the interdomain interface.

Computational Analysis of the Tripartite Interaction of Phasins (PhaP4 and 5)-Sigma Factor (σ24)-DNA of Azospirillum brasilense Sp7

Azospirillum brasilense Sp7 produces PHB, which is covered by granule-associated proteins (GAPs). Phasins are the main GAPs. Previous studies have shown phasins can regulate PHB synthesis. When A. brasilense grows under stress conditions, it uses sigma factors to transcribe genes for survival. One of these factors is the σ24 factor. This study determined the possible interaction between phasins and the σ24 factor or phasin-σ24 factor complex and DNA. Three-dimensional structures of phasins and σ24 factor structures were predicted using the I-TASSER and SWISS-Model servers, respectively. Subsequently, a molecular docking between phasins and the σ24 factor was performed using the ClusPro 2.0 server, followed by molecular docking between protein complexes and DNA using the HDOCK server. Evaluation of the types of ligand-receptor interactions was performed using the BIOVIA Discovery Visualizer for three-dimensional diagrams, as well as the LigPlot server to obtain bi-dimensional diagrams. The results showed the phasins (Pha4Abs7 or Pha5Abs7)-σ24 factor complex was bound near the -35 box of the promoter region of the phaC gene. However, in the individual interaction of PhaP5Abs7 and the σ24 factor, with DNA, both proteins were bound to the -35 box. This did not occur with PhaP4Abs7, which was bound to the -10 box. This change could affect the transcription level of the phaC gene and possibly affect PHB synthesis.

Fusing Peptide Epitopes for Advanced Multiplex Serological Testing for SARS-CoV-2 Antibody Detection

The tragic COVID-19 pandemic, which has seen a total of 655 million cases worldwide and a death toll of over 6.6 million seems finally tailing off. Even so, new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to arise, the severity of which cannot be predicted in advance. This is concerning for the maintenance and stability of public health, since immune evasion and increased transmissibility may arise. Therefore, it is crucial to continue monitoring antibody responses to SARS-CoV-2 in the general population. As a complement to polymerase chain reaction tests, multiplex immunoassays are elegant tools that use individual protein or peptide antigens simultaneously to provide a high level of sensitivity and specificity. To further improve these aspects of SARS-CoV-2 antibody detection, as well as accuracy, we have developed an advanced serological peptide-based multiplex assay using antigen-fused peptide epitopes derived from both the spike and the nucleocapsid proteins. The significance of the epitopes selected for antibody detection has been verified by in silico molecular docking simulations between the peptide epitopes and reported SARS-CoV-2 antibodies. Peptides can be more easily and quickly modified and synthesized than full length proteins and can, therefore, be used in a more cost-effective manner. Three different fusion-epitope peptides (FEPs) were synthesized and tested by enzyme-linked immunosorbent assay (ELISA). A total of 145 blood serum samples were used, compromising 110 COVID-19 serum samples from COVID-19 patients and 35 negative control serum samples taken from COVID-19-free individuals before the outbreak. Interestingly, our data demonstrate that the sensitivity, specificity, and accuracy of the results for the FEP antigens are higher than for single peptide epitopes or mixtures of single peptide epitopes. Our FEP concept can be applied to different multiplex immunoassays testing not only for SARS-CoV-2 but also for various other pathogens. A significantly improved peptide-based serological assay may support the development of commercial point-of-care tests, such as lateral-flow-assays.

SARS-CoV-2 ORF7a Mutation Found in BF.5 and BF.7 Sublineages Impacts Its Functions

A feature of the SARS-CoV-2 Omicron subvariants BF.5 and BF.7 that recently circulated mainly in China and Japan was the high prevalence of the ORF7a: H47Y mutation, in which the 47th residue of ORF7a has been mutated from a histidine (H) to a tyrosine (Y). Here, we evaluated the effect of this mutation on the three main functions ascribed to the SARS-CoV-2 ORF7a protein. Our findings show that H47Y mutation impairs the ability of SARS-CoV-2 ORF7a to antagonize the type I interferon (IFN-I) response and to downregulate major histocompatibility complex I (MHC-I) cell surface levels, but had no effect in its anti-SERINC5 function. Overall, our results suggest that the H47Y mutation of ORF7a affects important functions of this protein, resulting in changes in virus pathogenesis.

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.

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.

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.

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.

Structural and biophysical properties of a [4Fe4S] ferredoxin-like protein from Synechocystis sp. PCC 6803 with a unique two domain structure

Electron carrier proteins (ECPs), binding iron-sulfur clusters, are vital components within the intricate network of metabolic and photosynthetic reactions. They play a crucial role in the distribution of reducing equivalents. In Synechocystis sp. PCC 6803, the ECP network includes at least nine ferredoxins. Previous research, including global expression analyses and protein binding studies, has offered initial insights into the functional roles of individual ferredoxins within this network. This study primarily focuses on Ferredoxin 9 (slr2059). Through sequence analysis and computational modeling, Ferredoxin 9 emerges as a unique ECP with a distinctive two-domain architecture. It consists of a C-terminal iron‑sulfur binding domain and an N-terminal domain with homology to Nil-domain proteins, connected by a structurally rigid 4-amino acid linker. Notably, in contrast to canonical [2Fe2S] ferredoxins exemplified by PetF (ssl0020), which feature highly acidic surfaces facilitating electron transfer with photosystem I reaction centers, models of Ferredoxin 9 reveal a more neutral to basic protein surface. Using a combination of electron paramagnetic resonance spectroscopy and square-wave voltammetry on heterologously produced Ferredoxin 9, this study demonstrates that the protein coordinates 2×[4Fe4S]2+/1+ redox-active and magnetically interacting clusters, with measured redox potentials of -420 ± 9 mV and - 516 ± 10 mV vs SHE. A more in-depth analysis of Fdx9's unique structure and protein sequence suggests that this type of Nil-2[4Fe4S] multi-domain ferredoxin is well conserved in cyanobacteria, bearing structural similarities to proteins involved in homocysteine synthesis in methanogens.

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.

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.

Flexible protein-protein docking with a multitrack iterative transformer

Conventional protein-protein docking algorithms usually rely on heavy candidate sampling and reranking, but these steps are time-consuming and hinder applications that require high-throughput complex structure prediction, for example, structure-based virtual screening. Existing deep learning methods for protein-protein docking, despite being much faster, suffer from low docking success rates. In addition, they simplify the problem to assume no conformational changes within any protein upon binding (rigid docking). This assumption precludes applications when binding-induced conformational changes play a role, such as allosteric inhibition or docking from uncertain unbound model structures. To address these limitations, we present GeoDock, a multitrack iterative transformer network to predict a docked structure from separate docking partners. Unlike deep learning models for protein structure prediction that input multiple sequence alignments, GeoDock inputs just the sequences and structures of the docking partners, which suits the tasks when the individual structures are given. GeoDock is flexible at the protein residue level, allowing the prediction of conformational changes upon binding. On the Database of Interacting Protein Structures (DIPS) test set, GeoDock achieves a 43% top-1 success rate, outperforming all other tested methods. However, in the standard DIPS train/test splits, we discovered contamination of close homologs in the training set. After decontaminating the training set, the success rate is 31%. On the DB5.5 test set and a benchmark dataset of antibody-antigen complexes, GeoDock outperforms the deep learning models trained using the same dataset but falls behind most of the conventional methods and AlphaFold-Multimer. GeoDock attains an average inference speed of under 1 s on a single GPU, enabling its application in large-scale structure screening. Although binding-induced conformational changes are still a challenge owing to limited training and evaluation data, our architecture sets up the foundation to capture this backbone flexibility. Code and a demonstration Jupyter notebook are available at https://github.com/Graylab/GeoDock.

In Silico Prediction and Molecular Docking of SNPs in NRP1 Gene Associated with SARS-COV-2

Neuropilin-1 (NRP1) which is a main transmembrane cell surface receptor acts as a host cell mediator resulting in increasing the SARS-Cov-2 infectivity and also plays a role in neuronal development, angiogenesis and axonal outgrowth. The goal of this study is to estimate the impact of single nucleotide polymorphisms (SNPs) in the NRP1 gene on the function, structure and stabilization of protein as well as on the miRNA-mRNA binding regions using bioinformatical tools. It is also aimed to investigate the changes caused by SNPs in NRP1 on interactions with drug molecule and spike protein. The missense type of SNPs was analyzed using SIFT, PolyPhen-2, SNAP2, PROVEAN, Mutation Assessor, SNPs&GO, PhD-SNP, I-Mutant 3.0, MUpro, STRING, Project HOPE, ConSurf, and PolymiRTS. Docking analyses were conducted by AutoDock Vina program. As a result, a total of 733 missense SNPs were determined within the NRP1 gene and nine SNPs were specified as damaging to the protein. The modelling results showed that wild and mutant type amino acids had some different properties such as size, charge, and hydrophobicity. Additionally, their three-dimensional structures of protein were utilized for confirmation of these differences. After evaluating the results, nine polymorphisms rs141633354, rs142121081, rs145954532, rs200028992, rs200660300, rs369312020, rs370117610, rs370551432, rs370641686 were determined to be damaging on the structure and function of NRP1 protein and located in conserved regions. The results of molecular docking showed that the binding affinity values are nearly the same for wild-type and mutant structures support that the mutations carried out are not in the focus of the binding site, therefore the ligand does not affect the binding energy. It is expected that the results will be useful for future studies.

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.

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.

Metabolic switch regulates lineage plasticity and induces synthetic lethality in triple-negative breast cancer

Metabolic reprogramming is key for cancer development, yet the mechanism that sustains triple-negative breast cancer (TNBC) cell growth despite deficient pyruvate kinase M2 (PKM2) and tumor glycolysis remains to be determined. Here, we find that deficiency in tumor glycolysis activates a metabolic switch from glycolysis to fatty acid β-oxidation (FAO) to fuel TNBC growth. We show that, in TNBC cells, PKM2 directly interacts with histone methyltransferase EZH2 to coordinately mediate epigenetic silencing of a carnitine transporter, SLC16A9. Inhibition of PKM2 leads to impaired EZH2 recruitment to SLC16A9, and in turn de-represses SLC16A9 expression to increase intracellular carnitine influx, programming TNBC cells to an FAO-dependent and luminal-like cell state. Together, these findings reveal a new metabolic switch that drives TNBC from a metabolically heterogeneous-lineage plastic cell state to an FAO-dependent-lineage committed cell state, where dual targeting of EZH2 and FAO induces potent synthetic lethality in TNBC.

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.

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.

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.

Mapping respiratory syncytial virus fusion protein interactions with the receptor IGF1R and the impact of alanine-scanning mutagenesis on viral infection

Respiratory syncytial virus (RSV) has two main surface glycoproteins, the attachment glycoprotein (G) and the fusion (F) protein, which together mediate viral entry. Attachment is mediated by the RSV-G protein, while the RSV-F protein makes specific contact with the cellular insulin-like growth factor 1 receptor (IGF1R). This interaction leads to IGF1R activation and initiates a signalling cascade that calls the co-receptor, nucleolin, from the nucleus to the cell surface, where it can trigger viral fusion. We performed molecular docking analysis, which provided a potential set of 35 residues in IGF1R that may be important for interactions with RSV-F. We used alanine-scanning mutagenesis to generate IGF1R mutants and assessed their abundance and maturation, as well as the effect of mutation on RSV infection. We identified several mutations that appear to inhibit IGF1R maturation; but surprisingly, these mutations had no significant effect on RSV infection. This suggests that maturation of IGF1R may not be required for RSV infection. Additionally, we identified one residue, S788, that, when mutated, significantly reduced RSV infection. Further analysis revealed that this mutation disrupted a hydrogen bonding network that may be important for both IGF1R maturation and RSV infection.

A computational procedure for predicting excipient effects on protein-protein affinities

Protein-protein interactions lie at the center of much biology 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 rank orders four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.

A PTP1B-Cdk3 Signaling Axis Promotes Cell Cycle Progression of Human Glioblastoma Cells through an Rb-E2F Dependent Pathway

PTP1B plays a key role in developing different types of cancer. However, the molecular mechanism underlying this effect is unclear. To identify molecular targets of PTP1B that mediate its role in tumorigenesis, we undertook a SILAC-based phosphoproteomic approach, which allowed us to identify Cdk3 as a novel PTP1B substrate. Substrate trapping experiments and docking studies revealed stable interactions between the PTP1B catalytic domain and Cdk3. In addition, we observed that PTP1B dephosphorylates Cdk3 at tyrosine residue 15 in vitro and interacts with it in human glioblastoma cells. Next, we found that pharmacological inhibition of PTP1B or its depletion with siRNA leads to cell cycle arrest with diminished activity of Cdk3, hypophosphorylation of Rb, and the downregulation of E2F target genes Cdk1, Cyclin A, and Cyclin E1. Finally, we observed that the expression of a constitutively active Cdk3 mutant bypasses the requirement of PTP1B for cell cycle progression and expression of E2F target genes. These data delineate a novel signaling pathway from PTP1B to Cdk3 required for efficient cell cycle progression in an Rb-E2F dependent manner in human GB cells.

In Silico Analysis of SARS-CoV-2 Non-Structural Proteins Reveals an Interaction with the Host's Heat Shock Proteins That May Contribute to Viral Replications and Development

The non-structural protein 2 (NSP2) is an RNA-binding protein involved in coronavirus genome replication, and it often decreases human immune response to promote viral invasion and development. It is believed that the NSP2 associates itself with polyamines and heat shock proteins inside the host cell to proceed with viral development. This study aimed to investigate how the SARS-CoV-2 virus' key non-structural proteins (NSP2) utilize polyamines and heat shock proteins using a molecular docking approach and molecular dynamics (MD). ClusPro and HADDOCK servers were used for the docking and Discovery Studio, chimera, and PyMOL were used for analysis. Docking of the heat shock proteins 40 (HSP40), 70 (HSP70), and 90 (HSP90) with SARS-CoV-2 NSP2 resulted in 32, 28, and 19 interactions, respectively. Molecular dynamics revealed Arg458, Asn508, Met297, Arg301, and Trp417 as active residues, and pharmacophore modeling indicated ZINC395648, ZINC01150525, and ZINC85324008 from the zinc database as possible inhibitors for this NSP2.

Proteome based analysis of circulating SARS-CoV-2 variants: approach to a universal vaccine candidate

The discovery of the first infectious variant in Wuhan, China, in December 2019, has posed concerns over global health due to the spread of COVID-19 and subsequent variants. While the majority of patients experience flu-like symptoms such as cold and fever, a small percentage, particularly those with compromised immune systems, progress from mild illness to fatality. COVID-19 is caused by a RNA virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our approach involved utilizing immunoinformatic to identify vaccine candidates with multiple epitopes and ligand-binding regions in reported SARS-CoV-2 variants. Through analysis of the spike glycoprotein, we identified dominant epitopes for T-cells and B-cells, resulting in a vaccine construct containing two helper T-cell epitopes, six cytotoxic T-cell epitopes, and four linear B-cell epitopes. Prior to conjugation with adjuvants and linkers, all epitopes were evaluated for antigenicity, toxicity, and allergenicity. Additionally, we assessed the vaccine Toll-Like Receptors complex (2, 3, and 4). The vaccine construct demonstrated antigenicity, non-toxicity, and non-allergenicity, thereby enabling the host to generate antibodies with favorable physicochemical characteristics. Furthermore, the 3D structure of the B-cell construct exhibited a ProSA-web z-score plot with a value of -1.71, indicating the reliability of the designed structure. The Ramachandran plot analysis revealed that 99.6% of the amino acid residues in the vaccine subunit were located in the high favored observation region, further establishing its strong candidacy as a vaccination option.

Targeting the COMMD4-H2B protein complex in lung cancer

BACKGROUND

Lung cancer is the biggest cause of cancer-related deaths worldwide. Non-small cell lung cancer (NSCLC) accounts for 85-90% of all lung cancers. Identification of novel therapeutic targets are required as drug resistance impairs chemotherapy effectiveness. COMMD4 is a potential NSCLC therapeutic target. The aims of this study were to investigate the COMMD4-H2B binding pose and develop a short H2B peptide that disrupts the COMMD4-H2B interaction and mimics COMMD4 siRNA depletion.

METHODS

Molecular modelling, in vitro binding and site-directed mutagenesis were used to identify the COMMD4-H2B binding pose and develop a H2B peptide to inhibit the COMMD4-H2B interaction. Cell viability, DNA repair and mitotic catastrophe assays were performed to determine whether this peptide can specially kill NSCLC cells.

RESULTS

Based on the COMMD4-H2B binding pose, we have identified a H2B peptide that inhibits COMMD4-H2B by directly binding to COMMD4 on its H2B binding binding site, both in vitro and in vivo. Treatment of NSCLC cell lines with this peptide resulted in increased sensitivity to ionising radiation, increased DNA double-strand breaks and induction of mitotic catastrophe in NSCLC cell lines.

CONCLUSIONS

Our data shows that COMMD4-H2B represents a novel potential NSCLC therapeutic target.

Prediction of an immunogenic peptide ensemble and multi-subunit vaccine for Visceral leishmaniasis using bioinformatics approaches

Visceral Leishmaniasis (VL) is a neglected tropical disease of public health importance in the Indian subcontinent. Despite consistent elimination initiatives, the disease has not yet been eliminated and there is an increased risk of resurgence from active VL reservoirs including asymptomatic, post kala azar dermatitis leishmaniasis (PKDL) and HIV-VL co-infected individuals. To achieve complete elimination and sustain it in the long term, a prophylactic vaccine, which can elicit long lasting immunity, is desirable. In this study, we employed immunoinformatic tools to design a multi-subunit epitope vaccine for the Indian population by targeting antigenic secretory proteins screened from the Leishmania donovani proteome. Out of 8014 proteins, 277 secretory proteins were screened for their cellular location and proteomic evidence. Through NCBI BlastP, unique fragments of the proteins were cropped, and their antigenicity was evaluated. B-cell, HTL and CTL epitopes as well as IFN-ɣ, IL-17, and IL-10 inducers were predicted, manually mapped to the fragments and common regions were tabulated forming a peptide ensemble. The ensemble was evaluated for Class I MHC immunogenicity and toxicity. Further, immunogenic peptides were randomly selected and used to design vaccine constructs. Eight vaccine constructs were generated by linking random peptides with GS linkers. Synthetic TLR-4 agonist, RS09 was used as an adjuvant and linked with the constructs using EAAK linkers. The predicted population coverage of the constructs was ∼99.8 % in the Indian as well as South Asian populations. The most antigenic, nontoxic, non-allergic construct was chosen for the prediction of secondary and tertiary structures. The 3D structures were refined and analyzed using Ramachandran plot and Z-scores. The construct was docked with TLR-4 receptor. Molecular dynamic simulation was performed to check for the stability of the docked complex. Comparative in silico immune simulation studies showed that the predicted construct elicited humoral and cell-mediated immunity in human host comparable to that elicited by Leish-F3, which is a promising vaccine candidate for human VL.

A computational simulation appraisal of banana lectin as a potential anti-SARS-CoV-2 candidate by targeting the receptor-binding domain

BACKGROUND

The ongoing concern surrounding coronavirus disease 2019 (COVID-19) primarily stems from continuous mutations in the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), leading to the emergence of numerous variants. The receptor-binding domain (RBD) in the S1 subunit of the S protein of the virus plays a crucial role in recognizing the host's angiotensin-converting enzyme 2 (hACE2) receptor and facilitating cell membrane fusion processes, making it a potential target for preventing viral entrance into cells. This research aimed to determine the potential of banana lectin (BanLec) proteins to inhibit SARS-CoV-2 attachment to host cells by interacting with RBD through computational modeling.

MATERIALS AND METHODS

The BanLecs were selected through a sequence analysis process. Subsequently, the genes encoding BanLec proteins were retrieved from the Banana Genome Hub database. The FGENESH online tool was then employed to predict protein sequences, while web-based tools were utilized to assess the physicochemical properties, allergenicity, and toxicity of BanLecs. The RBDs of SARS-CoV-2 were modeled using the SWISS-MODEL in the following step. Molecular docking procedures were conducted with the aid of ClusPro 2.0 and HDOCK web servers. The three-dimensional structures of the docked complexes were visualized using PyMOL. Finally, molecular dynamics simulations were performed to investigate and validate the interactions of the complexes exhibiting the highest interactions, facilitating the simulation of their dynamic properties.

RESULTS

The BanLec proteins were successfully modeled based on the RNA sequences from two species of banana (Musa sp.). Moreover, an amino acid modification in the BanLec protein was made to reduce its mitogenicity. Theoretical allergenicity and toxicity predictions were conducted on the BanLecs, which suggested they were likely non-allergenic and contained no discernible toxic domains. Molecular docking analysis demonstrated that both altered and wild-type BanLecs exhibited strong affinity with the RBD of different SARS-CoV-2 variants. Further analysis of the molecular docking results showed that the BanLec proteins interacted with the active site of RBD, particularly the key amino acids residues responsible for RBD's binding to hACE2. Molecular dynamics simulation indicated a stable interaction between the Omicron RBD and BanLec, maintaining a root-mean-square deviation (RMSD) of approximately 0.2 nm for a duration of up to 100 ns. The individual proteins also had stable structural conformations, and the complex demonstrated a favorable binding-free energy (BFE) value.

CONCLUSIONS

These results confirm that the BanLec protein is a promising candidate for developing a potential therapeutic agent for combating COVID-19. Furthermore, the results suggest the possibility of BanLec as a broad-spectrum antiviral agent and highlight the need for further studies to examine the protein's safety and effectiveness as a potent antiviral agent.

Computational Analysis of CD46 Protein Interaction with SARS-CoV-2 Structural Proteins: Elucidating a Putative Viral Entry Mechanism into Human Cells

This study examines an unexplored aspect of SARS-CoV-2 entry into host cells, which is widely understood to occur via the viral spike (S) protein's interaction with human ACE2-associated proteins. While vaccines and inhibitors targeting this mechanism are in use, they may not offer complete protection against reinfection. Hence, we investigate putative receptors and their cofactors. Specifically, we propose CD46, a human membrane cofactor protein, as a potential putative receptor and explore its role in cellular invasion, acting possibly as a cofactor with other viral structural proteins. Employing computational techniques, we created full-size 3D models of human CD46 and four key SARS-CoV-2 structural proteins-EP, MP, NP, and SP. We further developed 3D models of CD46 complexes interacting with these proteins. The primary aim is to pinpoint the likely interaction domains between CD46 and these structural proteins to facilitate the identification of molecules that can block these interactions, thus offering a foundation for novel pharmacological treatments for SARS-CoV-2 infection.

Deciphering cell wall sensors enabling the construction of robust P. pastoris for single-cell protein production

Single-cell protein (SCP) production in the methylotrophic yeast Pichia pastoris has the potential to achieve a sustainable protein supply. However, improving the methanol fermentation efficiency and reducing carbon loss has been a long-standing challenge with far-reaching scientific and practical implications. Here, comparative transcriptomics revealed that PAS_0305, a gene directly associated with cell wall thickness under methanol stress, can be used as a target for unlocking cell wall sensors. Intracellular trehalose accumulation confirmed that cell wall sensors were activated after knocking out PAS_0305, which resulted in increased cell wall permeability. Genome-wide signal perturbations were transduced through the HOG module and the CWI pathway, which was confirmed to connected by Pbs2-Mkk. As a consequence of CWI pathway activation, ΔPAS_0305 elicited a rescue response of cell wall remodeling by increasing the β-1,3-glucan content and decreasing the chitin/mannose content. Remarkably, perturbations in global stress signals led to a fine-tuning of the metabolic network of ΔPAS_0305, resulting in a superior phenotype with highest crude protein and methanol conversion rate of 67.21% and 0.46 gDCW/g. Further genome-scale metabolic models were constructed to validate the experimental results, confirming that unlocking cell wall sensors resulted in maximized flux from methanol towards SCP and effectively addressing the issue of carbon loss in methanol fermentation. This work sheds new light on the potential of manipulating cellular signaling pathways to optimize metabolic networks and achieve exceptional phenotypic characteristics, providing new strategies for constructing versatile cell factories in P. pastoris.

Computational design and evaluation of mRNA- and protein-based conjugate vaccines for influenza A and SARS-CoV-2 viruses

BACKGROUND

Israel confirmed the first case of "flurona"-a co-infection of seasonal flu (IAV) and SARS-CoV-2 in an unvaccinated pregnant woman. This twindemic has been confirmed in multiple countries and underscores the importance of managing respiratory viral illnesses.

RESULTS

The novel conjugate vaccine was designed by joining four hemagglutinin, three neuraminidase, and four S protein of B-cell epitopes, two hemagglutinin, three neuraminidase, and four S proteins of MHC-I epitopes, and three hemagglutinin, nine neuraminidase, and five S proteins of MHC-II epitopes with linkers and adjuvants. The constructed conjugate vaccine was found stable, non-toxic, non-allergic, and antigenic with 0.6466 scores. The vaccine contained 14.87% alpha helix, 29.85% extended strand, 9.64% beta-turn, and 45.64% random coil, which was modeled to a 3D structure with 94.7% residues in the most favored region of the Ramachandran plot and Z-score of -3.33. The molecular docking of the vaccine with TLR3 represented -1513.9 kcal/mol of binding energy with 39 hydrogen bonds and 514 non-bonded contacts, and 1.582925e-07 of eigenvalue complex. Immune stimulation prediction showed the conjugate vaccine could activate T and B lymphocytes to produce high levels of Th1 cytokines and antibodies.

CONCLUSION

The in silico-designed vaccine against IAV and SARS-CoV-2 showed good population coverage and immune response with predicted T- and B-cell epitopes, favorable molecular docking, Ramachandran plot results, and good protein expression. It fulfilled safety criteria, indicating potential for preclinical studies and experimental clinical trials.

An In Silico Multi-epitopes Vaccine Ensemble and Characterization Against Nosocomial Proteus penneri

Proteus penneri (P. penneri) is a bacillus-shaped, gram-negative, facultative anaerobe bacterium that is primarily an invasive pathogen and the etiological agent of several hospital-associated infections. P. penneri strains are naturally resistant to macrolides, amoxicillin, oxacillin, penicillin G, and cephalosporins; in addition, no vaccines are available against these strains. This warrants efforts to propose a theoretical based multi-epitope vaccine construct to prevent pathogen infections. In this research, reverse vaccinology bioinformatics and immunoinformatics approaches were adopted for vaccine target identification and construction of a multi-epitope vaccine. In the first phase, a core proteome dataset of the targeted pathogen was obtained using the NCBI database and subjected to bacterial pan-genome analysis using bacterial pan-genome analysis (BPGA) to predict core protein sequences which were then used to find good vaccine target candidates. This identified two proteins, Hcp family type VI secretion system effector and superoxide dismutase family protein, as promising vaccine targets. Afterward using the IEDB database, different B-cell and T-cell epitopes were predicted. A set of four epitopes "KGSVNVQDRE, NTGKLTGTR, IIHSDSWNER, and KDGKPVPALK" were chosen for the development of a multi-epitope vaccine construct. A 183 amino acid long vaccine design was built along with "EAAAK" and "GPGPG" linkers and a cholera toxin B-subunit adjuvant. The designed vaccine model comprised immunodominant, non-toxic, non-allergenic, and physicochemical stable epitopes. The model vaccine was docked with MHC-I, MHC-II, and TLR-4 immune cell receptors using the Cluspro2.0 web server. The binding energy score of the vaccine was - 654.7 kcal/mol for MHC-I, - 738.4 kcal/mol for MHC-II, and - 695.0 kcal/mol for TLR-4. A molecular dynamic simulation was done using AMBER v20 package for dynamic behavior in nanoseconds. Additionally, MM-PBSA binding free energy analysis was done to test intermolecular binding interactions between docked molecules. The MM-GBSA net binding energy score was - 148.00 kcal/mol, - 118.00 kcal/mol, and - 127.00 kcal/mol for vaccine with TLR-4, MHC-I, and MHC-II, respectively. Overall, these in silico-based predictions indicated that the vaccine is highly promising in terms of developing protective immunity against P. penneri. However, additional experimental validation is required to unveil the real immune response to the designed vaccine.

Anti-CD19/CD8 bispecific T cell engager for the potential treatment of B cell malignancies

The administration of blinatumomab was accompanied by several adverse effects, including activation of regulatory T-cells and cytokine storm. The objective of this study was to produce and evaluate a novel αCD8/CD19 BiTE (αCD8/CD19) with the potency to directly target CD8+T-cells. In-silico studies were utilized for determining proper folding, receptor binding, and structural stability of αCD8/CD19 protein. Western blotting and indirect surface staining were used to evaluate the size accuracy and binding potency of the purified protein. Functionality was assessed for granzyme B production, cytotoxicity, and proliferation. TheαCD8/CD19recombinant protein was produced in the CHO-K1 cell line with a final concentration of 1.94 mg/l. The αCD8/CD19 bound to CD8+and CD19+cell lines and induced significant granzyme B production, cytotoxic activity and proliferation potential in the presence of IL-2 and tumor target cells. The maximum CD8+T-cell biological activity was observed on the 10th day with 10:1 effector-to-target ratio.

Daboxin P, a phospholipase A2 of Indian Daboia russelii venom, modulates thrombin-mediated platelet aggregation

Daboxin P, reported earlier from the venom of Daboia russellii, disturbs the blood coagulation cascade by targeting factor X and factor Xa. The present study exhibits that Daboxin P also inhibits platelet aggregation induced by various agonists. The thrombin-induced platelet aggregation was inhibited maximum whereas inhibition of collagen-induced platelet aggregation was found to be 50% and no inhibition of adenosine diphosphate (ADP) and arachidonic acid-induced aggregation was observed. Daboxin P dose-dependently inhibited the thrombin-induced platelet aggregation with Anti-Aggregation 50 (AD50 ) dose of 55.166 nM and also reduced the thrombin-mediated calcium influx. In-silico interaction studies suggested that Daboxin P binds to thrombin and blocks its interaction with its receptor on the platelet surface. Quenching of thrombin's emission spectrum by Daboxin P and electrophoretic profiles of pull-down assay further reveals the binding between Daboxin P and thrombin. Thus, the present study demonstrates that Daboxin P inhibits thrombin-induced platelet aggregation by binding to thrombin.

Underpinning Endogeneous Damp EDA-Fibronectin in the Activation of Molecular Targets of Rheumatoid Arthritis and Identifcation of its Effective Inhibitors by Computational Methods

Rheumatoid arthritis (RA) is one of the most severe inflammatory diseases that cause swelling, stiffness and pain in the joints, which pose a significant threat worldwide. Damage-associated molecular patterns (DAMPs) are danger molecules of endogenous origin, released during cell injury or cell death, interacts with various Pattern recognition receptors (PRRs) and activates various inflammatory diseases. One of the DAMP molecules, so-called EDA-fibronectin (Fn) is also responsible for causing RA. EDA-Fn triggers RA through its interaction with TLR4. Apart from TLR4, it is divulged that certain other PRR's are also responsible for RA, but the identity and mechanism of those PRRs remain unknown until now. Hence, for the first time, we tried to reveal those PRR's interaction with EDA-Fn in RA through computational methods. Protein-protein interaction (PPI) was checked using ClusPro between EDA-Fn and certain Pattern recognition receptors (PRRs) to explore the binding affinities of the potential PRRs. Protein-protein docking unveiled that TLR5, TLR2 and RAGE has good interaction with EDA-Fn than the well-reported TLR4. Macromolecular simulation was performed for TLR5, TLR2 and RAGE complexes along with the control group TLR4 for 50 ns to further investigate the stability, leading to the identification of TLR2, TLR5 and RAGE as the stable complexes. Hence, TLR2, TLR5 and RAGE on interaction with EDA-Fn may lead to the progression of RA that may need additional validations through in vitro and in vivo animal models. Molecular docking was used to analyse the binding force of the top 33 active anti-arthritic compounds with the target protein EDA-Fn. Molecular docking study showed that withaferin A has a good binding activity with EDA-fibronectin target. Hence, it is emphasized that guggulsterone and berberine could modulate the EDA-Fn-mediated TLR5/TLR2/RAGE pathways, thereby it could inhibit the deteriorating effects of RA which needs further in vitro and in vivo experimental validations.

"Affimer" synthetic protein scaffolds block oxidized LDL binding to the LOX-1 scavenger receptor and inhibit ERK1/2 activation

In multicellular organisms, a variety of lipid-protein particles control the systemic flow of triacylglycerides, cholesterol, and fatty acids between cells in different tissues. The chemical modification by oxidation of these particles can trigger pathological responses, mediated by a group of membrane proteins termed scavenger receptors. The lectin-like oxidized low-density lipoprotein (LOX-1) scavenger receptor binds to oxidized low-density lipoprotein (oxLDL) and mediates both signaling and trafficking outcomes. Here, we identified five synthetic proteins termed Affimers from a phage display library, each capable of binding recombinant LOX-1 extracellular (oxLDL-binding) domain with high specificity. These Affimers, based on a phytocystatin scaffold with loop regions of variable sequence, were able to bind to the plasma membrane of HEK293T cells exclusively when human LOX-1 was expressed. Binding and uptake of fluorescently labeled oxLDL by the LOX-1-expressing cell model was inhibited with subnanomolar potency by all 5 Affimers. ERK1/2 activation, stimulated by oxLDL binding to LOX-1, was also significantly inhibited (p < 0.01) by preincubation with LOX-1-specific Affimers, but these Affimers had no direct agonistic effect. Molecular modeling indicated that the LOX-1-specific Affimers bound predominantly via their variable loop regions to the surface of the LOX-1 lectin-like domain that contains a distinctive arrangement of arginine residues previously implicated in oxLDL binding, involving interactions with both subunits of the native, stable scavenger receptor homodimer. These data provide a new class of synthetic tools to probe and potentially modulate the oxLDL/LOX-1 interaction that plays an important role in vascular disease.

Crystal structures of PirA and PirB toxins from Photorhabdus akhurstii subsp. akhurstii K-1

PirAB binary toxin from Photorhabdus is toxic to the larvae of dipteran and lepidopteran insect pests. However, the 3-D structures and their toxicity mechanism are not yet fully understood. Here we report the crystal structures of PirA and PirB proteins from Photorhabdus akhurstii subsp. akhurstii K-1 at 1.6 and 2.1 Å, respectively. PirA comprises of eight β-strands depicting jelly-roll topology while PirB folds into two distinct domains, an N-terminal domain (PirB-N) made up of seven α-helices and a C-terminal domain (PirB-C) consists of ten β-strands. Despite the low sequence identity, PirA adopts similar architecture as domain III and PirB shared similar architecture as domain I/II of the Cry δ-endotoxin of Bacillus thuringiensis, respectively. However, PirA shows significant structural variations as compared to domain III of lepidopteran and dipteran specific Cry toxins (Cry1Aa and Cry11Ba) suggesting its role in virulence among range of insect pests and hence, in receptor binding. High structural resemblance between PirB-N and domain I of Cry toxin raises the possibility that the putative PirAB binary toxin may mimic the toxicity mechanism of the Cry protein, particularly its ability to perform pore formation. The mixture of independently purified PirA and PirB proteins are not toxic to insects. However, PirA-PirB protein complex purified from expression of pir operon with non-coding Enterobacterial Repetitive Intergenic Consensus (ERIC) sequences found toxic to Galleria mellonella larvae with LD50 value of 1.62 μg/larva. This suggests that toxic conformation of PirA and PirB are achieved in-vivo with the help of ERIC sequences.

Atheroprotective Effect of Fucoidan in THP-1 Macrophages by Potential Upregulation of ABCA1

Targeting foam cells reduces the risk and pathophysiology of atherosclerosis, of which they are one of its early hallmarks. The precise mechanism of action of fucoidan, a potential anti-atherogenic drug, is still unknown. Our objective was to assess the ability of fucoidan to regulate expression of ATP-binding cassette transporter A1 (ABCA1) in ox-LDL-induced THP-1 macrophages. Molecular docking was used to predict how fucoidan interacts with anti-foam cell markers, and further in vitro experiments were performed to evaluate the protective effect of fucoidan on modulating uptake and efflux of lipids. THP-1 macrophages were protected by 50 µg/mL of fucoidan and were then induced to form foam cells with 25 µg/mL of ox-LDL. Expression levels were assessed using RT-qPCR, and an Oil Red O stain was used to observe lipid accumulation in THP-1 macrophages. In addition, ABCA1 protein was examined by Western blot, and cellular cholesterol efflux was determined using fluorescently labeled cholesterol. Under a light microscope, decreased lipid accumulation in ox-LDL-induced-THP-1 macrophages pre-treated with fucoidan showed a significant effect, although it did not affect the expression of scavenger receptors (SR-AI and CD36). It is interesting to note that fucoidan dramatically increased the gene and protein expression of ABCA1, perhaps via the liver X receptor-α (LXR-α). Moreover, fucoidan's ability to increase and control the efflux of cholesterol from ox-LDL-induced THP-1 macrophages revealed how it may alter ABCA1's conformation and have a major effect on how it interacts with apolipoprotein A (ApoA1). In vitro results support a rationale for predicting fucoidan and its interaction with its receptor targets' predicted data, hence validating its anti-atherogenic properties and suggesting that fucoidan could be promising as an atheroprotective.

Immunoinformatic-guided designing and evaluating protein and mRNA-based vaccines against Cryptococcus neoformans for immunocompromised patients

BACKGROUND

Cryptococcus neoformans is a fungal pathogen that can cause serious meningoencephalitis in individuals with compromised immune systems due to HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome), liver cirrhosis, and transplantation. Mannoproteins (MPs), glycoproteins in the C. neoformans capsule, crucially impact virulence by mediating adhesion to lung cells and modulating immune response via cytokine induction and phagocytosis influence. Therefore, creating a vaccine that can generate targeted antibodies to fight infection and prevent fungal illnesses is essential.

RESULTS

This research aims to create a unique, stable, and safe vaccine through bioinformatics methodologies, aiming at epitopes of T and B cells found in the MP of C. neoformans. Based on toxicity, immunogenicity, and antigenicity, this research predicted novel T cells (GNPVGGNVT, NPVGGNVTT, QTSYARLLS, TSVGNGIAS, WVMPGDYTN, AAATGSSSSGSTGSG, GSTGSGSGSAAAGST, SGSTGSGSGSAAAGS, SSGSTGSGSGSAAAG, and SSSGSTGSGSGSAAA) and B cell (ANGSTSTFQQRYTGTYTNGDGSLGTWTQGETVTPQTAYSTPATSNCKTYTSVGNGIASLALSNAGSNSTAAATNSSSGGASAAATGSSSSGSTGSGSGSAAAGSTAAASSSGDSSSSTSAAMSNGI, HGATGLGNPVGGNVTT, TMGPTNPSEPTLGTAI, GNPVGGNVTTNATGSD, and NSTAAATNSSSGGASA) epitopes for a multiple-epitope vaccine and constructed a vaccine subunit with potential immunogenic properties. The present study used four linkers (AAY, GPGPG, KK, and EAAAK linkers) to connect the epitopes and adjuvant. After constructing the vaccine, it was confronted with receptor docking and simulation analysis. Subsequently, the vaccine was cloned into the vector of Escherichia coli pET-28a ( +) by ligation process for the expression using the SnapGene tool, which confirmed a significant immune response. To assess the constructed vaccine's properties, multiple computational tools were employed. Based on the MP sequence, the tools evaluated the antigenicity, immunogenicity, cytokine-inducing capacity, allergenicity, toxicity, population coverage, and solubility.

CONCLUSION

Eventually, the results revealed a promising multi-epitope vaccine as a potential candidate for addressing global C. neoformans infection, particularly in immunocompromised patients. Yet, additional in vitro and in vivo investigations are necessary to validate its safety and effectiveness.

A morpheein equilibrium regulates catalysis in phosphoserine phosphatase SerB2 from Mycobacterium tuberculosis

Mycobacterium tuberculosis phosphoserine phosphatase MtSerB2 is of interest as a new antituberculosis target due to its essential metabolic role in L-serine biosynthesis and effector functions in infected cells. Previous works indicated that MtSerB2 is regulated through an oligomeric transition induced by L-Ser that could serve as a basis for the design of selective allosteric inhibitors. However, the mechanism underlying this transition remains highly elusive due to the lack of experimental structural data. Here we describe a structural, biophysical, and enzymological characterisation of MtSerB2 oligomerisation in the presence and absence of L-Ser. We show that MtSerB2 coexists in dimeric, trimeric, and tetrameric forms of different activity levels interconverting through a conformationally flexible monomeric state, which is not observed in two near-identical mycobacterial orthologs. This morpheein behaviour exhibited by MtSerB2 lays the foundation for future allosteric drug discovery and provides a starting point to the understanding of its peculiar multifunctional moonlighting properties.

Structure-based design of nanobodies that inhibit seeding of Alzheimer's patient-extracted tau fibrils

Despite much effort, antibody therapies for Alzheimer's disease (AD) have shown limited efficacy. Challenges to the rational design of effective antibodies include the difficulty of achieving specific affinity to critical targets, poor expression, and antibody aggregation caused by buried charges and unstructured loops. To overcome these challenges, we grafted previously determined sequences of fibril-capping amyloid inhibitors onto a camel heavy chain antibody scaffold. These sequences were designed to cap fibrils of tau, known to form the neurofibrillary tangles of AD, thereby preventing fibril elongation. The nanobodies grafted with capping inhibitors blocked tau aggregation in biosensor cells seeded with postmortem brain extracts from AD and progressive supranuclear palsy (PSP) patients. The tau capping nanobody inhibitors also blocked seeding by recombinant tau oligomers. Another challenge to the design of effective antibodies is their poor blood-brain barrier (BBB) penetration. In this study, we also designed a bispecific nanobody composed of a nanobody that targets a receptor on the BBB and a tau capping nanobody inhibitor, conjoined by a flexible linker. We provide evidence that the bispecific nanobody improved BBB penetration over the tau capping inhibitor alone after intravenous administration in mice. Our results suggest that the design of synthetic antibodies that target sequences that drive protein aggregation may be a promising approach to inhibit the prion-like seeding of tau and other proteins involved in AD and related proteinopathies.

Is the BNT162b2 vaccine still effective against the latest variant: XBB.1.5?

Background

The XBB.1.5 sub-variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron now continues to spread rapidly due to the increased transmission rate as a result of increased affinity of the virus binding over the ACE-2 receptor - a gained property due to the mutation that occurred in spike protein.

Aim

The protectivity of BNT162b2 antibodies produced in the serum of patients is an important parameter for preventing transmission. However, the affinity of the antibodies of patients vaccinated with BNT162b2 over the latest SARS-CoV-2 variant, XBB.1.5, is not well established. This study aimed to evaluate the efficacy of the BNT162b2 vaccine-induced antibody on XBB.1.5 by comparing the X-ray crystallographic structures and spike protein mutations of BA.5 and XBB.1.5 using in silico methods.

Materials and Methods

Binding points and binding affinity values of the BNT162b2 antibody with BA.5 and XBB.1.5 spike protein were calculated using ClusPro 2.0 protein-protein docking and Discovery Studio 2021 Client software. Mutations in the genetic code of the spike protein for SARS-CoV-2 BA.5 and XBB.1.5 sub-variants were screened using the GISAID database.

Results

Binding affinity values showed that BNT162b2 had higher negative values in the XBB.1.5 sub-variant than BA.5 at the mutation sites at the binding region. The results suggested that BNT162b2 may retain its activity despite mutations and conformational changes in the binding site of the XBB.1.5.

Conclusion

The findings of this study shed light on the importance and usability of the current BNT162b2 vaccine for XBB.1.5 and future variants of concern.

Computational prediction of B and T-cell epitopes of Kyasanur Forest Disease virus marker proteins towards the development of precise diagnosis and potent subunit vaccine

Kyasanur Forest Disease (KFD), also known as 'monkey fever', caused by KFD Virus (KFDV), is a highly neglected tropical disease endemic to Western Ghat region of Karnataka, India. Recently, KFD, which is fatal for both monkeys and humans with a mortality rate of 2-10% has been found to spread from its epicenter to neighboring districts and states also. The current ELISA based KFD detection method is very non-specific due to cross-reactivity with other flaviviruses. Further, presently available formalin-inactivated vaccine has been found to be less effective leading to disease susceptibility and severity. To address these, the present study was aimed at predicting the potent specific B and T-cell epitopes of KFDV immunogenic marker proteins using diverse computational tools aiming at developing precise diagnostic method and an effective subunit vaccine. Here, we have chosen E, NS1 and NS5 proteins as markers of KFDV by taking into account of their differential and non-overlapping sequences with selected arboviruses. Based on the linear and nonlinear epitope prediction tools and important biophysical parameters, we identified three potential linear and ten nonlinear B-cell epitopes. We also predicted T-cell epitope peptides which binds to MHC class-I and class-II receptors for the effective T-cell activation. Thus, our molecular docking and molecular dynamics simulation analysis has identified six different TH-cell epitopes based on the distribution frequency of MHC-II haplotypes in the human population and one TC-cell epitope from NS5 protein that has maximum interaction with class-I MHC. Overall, we have successfully identified potential B and T-cell epitope marker peptides present in the envelope and two non-structural proteins.Communicated by Ramaswamy H. Sarma.

Exploring binding positions and backbone conformations of peptide ligands of proteins with a backbone-centred statistical energy function

When designing peptide ligands based on the structure of a protein receptor, it can be very useful to narrow down the possible binding positions and bound conformations of the ligand without the need to choose its amino acid sequence in advance. Here, we construct and benchmark a tool for this purpose based on a recently reported statistical energy model named SCUBA (Sidechain-Unknown Backbone Arrangement) for designing protein backbones without considering specific amino acid sequences. With this tool, backbone fragments of different local conformation types are generated and optimized with SCUBA-driven stochastic simulations and simulated annealing, and then ranked and clustered to obtain representative backbone fragment poses of strong SCUBA interaction energies with the receptor. We computationally benchmarked the tool on 111 known protein-peptide complex structures. When the bound ligands are in the strand conformation, the method is able to generate backbone fragments of both low SCUBA energies and low root mean square deviations from experimental structures of peptide ligands. When the bound ligands are helices or coils, low-energy backbone fragments with binding poses similar to experimental structures have been generated for approximately 50% of benchmark cases. We have examined a number of predicted ligand-receptor complexes by atomistic molecular dynamics simulations, in which the peptide ligands have been found to stay at the predicted binding sites and to maintain their local conformations. These results suggest that promising backbone structures of peptides bound to protein receptors can be designed by identifying outstanding minima on the SCUBA-modeled backbone energy landscape.

Identification and characterization of the conformation and size of amyloid-β (42) oligomers targeting the receptor LilrB2

Experimental observations revealed that the amyloid-β 42 oligomer (AβO) can directly bind to the LilrB2 D1D2(LDD) receptor with nanomolar-affinity, leading to changes in synaptic plasticity and cognitive deficits. However, the dependence of neurotoxicity on the morphology, size, and aggregation stage (SP1, SP2) of AβO, as well as the specific molecular mechanism of AβO-LDD interaction, remain uncertain. To address these uncertainties, we investigated the interaction between the LDD neuroreceptor and AβO with different Aβ42 species (nontoxic species, toxic species, and protofibril) and sizes. Our results showed that the LDD selectively binds AβO species rather than the Aβ42 monomer, accommodating various Aβ42 dimers and trimers as well as SP2 AβO, in a specific pose in the pocket of the LDD receptor (region I). Additionally, protofibrils with exposed β1/β2 regions can also bind to region I of the LDD receptor, as observed experimentally (Cao, et al., Nat. Chem., 2018, 10, 1213; and Aim et al., Nat. Commun., 2021, 12, 3451). More extensively, we identified two additional regions of the LDD receptor, regions II and III, suitable for binding to larger AβO species at the SP1 with different molecular weights and conformations, accounting for the stronger binding strength obtained experimentally. We suggest that the two regions are more competitive than region I in causing toxicity by AβO binding. The detailed and systematic characterization for the complexes generated between the LDD receptor and various AβO species, including the protofibril, offers deep insight into the dependence of neurotoxicity on the AβO size and conformation at the molecular level, and provides novel and specific targets for drug design of Alzheimer's disease.

A Structural Model for the Core Nup358-BicD2 Interface

Dynein motors facilitate the majority of minus-end-directed transport events on microtubules. The dynein adaptor Bicaudal D2 (BicD2) recruits the dynein machinery to several cellular cargo for transport, including Nup358, which facilitates a nuclear positioning pathway that is essential for the differentiation of distinct brain progenitor cells. Previously, we showed that Nup358 forms a "cargo recognition α-helix" upon binding to BicD2; however, the specifics of the BicD2-Nup358 interface are still not well understood. Here, we used AlphaFold2, complemented by two additional docking programs (HADDOCK and ClusPro) as well as mutagenesis, to show that the Nup358 cargo-recognition α-helix binds to BicD2 between residues 747 and 774 in an anti-parallel manner, forming a helical bundle. We identified two intermolecular salt bridges that are important to stabilize the interface. In addition, we uncovered a secondary interface mediated by an intrinsically disordered region of Nup358 that is directly N-terminal to the cargo-recognition α-helix and binds to BicD2 between residues 774 and 800. This is the same BicD2 domain that binds to the competing cargo adapter Rab6, which is important for the transport of Golgi-derived and secretory vesicles. Our results establish a structural basis for cargo recognition and selection by the dynein adapter BicD2, which facilitates transport pathways that are important for brain development.

An alternative vaccine target for bovine Anaplasmosis based on enolase, a moonlighting protein

The discovery of new targets for preventing bovine anaplasmosis has moved away from focusing on proteins that have already been extensively studied in Anaplasma marginale, including the Major Surface Proteins, Outer Membrane Proteins, and Type IV Secretion System proteins. An alternative is moonlighting or multifunctional proteins, capable of performing various biological functions within various cellular compartments. There are several reports on the role of moonlighting proteins as virulence factors in various microorganisms. Moreover, it is known that about 25% of all moonlighting is involved in the virulence of pathogens. In this work, for the first time, we present the identification of three enolase proteins (AmEno01, AmEno15, and AmEno31) in the genome of Mexican strains of A. marginale. Using bioinformatics tools, we predicted the catalytic domains, enolase signature, and amino acids binding magnesium ion of the catalytic domain and performed a phylogenetic reconstruction. In addition, by molecular docking analysis, we found that AmEno01 would bind to erythrocyte proteins spectrin, ankyrin, and stomatin. This adhesion function has been reported for enolases from other pathogens. It is considered a promising target since blocking this function would impede the fundamental adhesion process that facilitates the infection of erythrocytes. Additionally, molecular docking predicts that AmEno01 could bind to extracellular matrix protein fibronectin, which would be significant if we consider that some proteins with fibronectin domains are localized in tick gut cells and used as an adhesion strategy to gather bacteria before traveling to salivary glands. Derived from the molecular docking analysis of AmEno01, we hypothesized that enolases could be proteins driven by the pathogen and redirected at the expense of the pathogen's needs.