GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking

Designing a multi-epitope subunit vaccine against Orf virus using molecular docking and molecular dynamics

Orf virus (ORFV) is an acute contact, epitheliotropic, zoonotic, and double-stranded DNA virus that causes significant economic losses in the livestock industry. The objective of this study is to design an immunoinformatics-based multi-epitope subunit vaccine against ORFV. Various immunodominant cytotoxic T lymphocytes (CTL), helper T lymphocytes (HTL), and B-cell epitopes from the B2L, F1L, and 080 protein of ORFV were selected and linked by short connectors to construct a multi-epitope subunit vaccine. Immunogenicity was enhanced by adding an adjuvant β-defensin to the N-terminal of the vaccine using the EAAAK linker. The vaccine exhibited a significant degree of antigenicity and solubility, without allergenicity or toxicity. The 3D formation of the vaccine was subsequently anticipated, improved, and verified. The optimized model exhibited a lower Z-score of -4.33, indicating higher quality. Molecular docking results demonstrated that the vaccine strongly binds to TLR2 and TLR4. Molecular dynamics results indicated that the docked vaccine-TLR complexes were stable. Immune simulation analyses further confirmed that the vaccine can induce a marked increase in IgG and IgM antibody titers, and elevated levels of IFN-γ and IL-2. Finally, the optimized DNA sequence of the vaccine was cloned into the vector pET28a (+) for high expression in the E.coli expression system. Overall, the designed multi-epitope subunit vaccine is highly stable and can induce robust humoral and cellular immunity, making it a promising vaccine candidate against ORFV.

ALDH1A3-acetaldehyde metabolism potentiates transcriptional heterogeneity in melanoma

Cancer cellular heterogeneity and therapy resistance arise substantially from metabolic and transcriptional adaptations, but how these are interconnected is poorly understood. Here, we show that, in melanoma, the cancer stem cell marker aldehyde dehydrogenase 1A3 (ALDH1A3) forms an enzymatic partnership with acetyl-coenzyme A (CoA) synthetase 2 (ACSS2) in the nucleus to couple high glucose metabolic flux with acetyl-histone H3 modification of neural crest (NC) lineage and glucose metabolism genes. Importantly, we show that acetaldehyde is a metabolite source for acetyl-histone H3 modification in an ALDH1A3-dependent manner, providing a physiologic function for this highly volatile and toxic metabolite. In a zebrafish melanoma residual disease model, an ALDH1-high subpopulation emerges following BRAF inhibitor treatment, and targeting these with an ALDH1 suicide inhibitor, nifuroxazide, delays or prevents BRAF inhibitor drug-resistant relapse. Our work reveals that the ALDH1A3-ACSS2 couple directly coordinates nuclear acetaldehyde-acetyl-CoA metabolism with specific chromatin-based gene regulation and represents a potential therapeutic vulnerability in melanoma.

Insights into structural vaccinology harnessed for universal coronavirus vaccine development

Structural vaccinology is pivotal in expediting vaccine design through high-throughput screening of immunogenic antigens. Leveraging the structural and functional characteristics of antigens and immune cell receptors, this approach employs protein structural comparison to identify conserved patterns in key pathogenic components. Molecular modeling techniques, including homology modeling and molecular docking, analyze specific three-dimensional (3D) structures and protein interactions and offer valuable insights into the 3D interactions and binding affinity between vaccine candidates and target proteins. In this review, we delve into the utilization of various immunoinformatics and molecular modeling tools to streamline the development of broad-protective vaccines against coronavirus disease 2019 variants. Structural vaccinology significantly enhances our understanding of molecular interactions between hosts and pathogens. By accelerating the pace of developing effective and targeted vaccines, particularly against the rapidly mutating severe acute respiratory syndrome coronavirus 2 and other prevalent infectious diseases, this approach stands at the forefront of advancing immunization strategies. The combination of computational techniques and structural insights not only facilitates the identification of potential vaccine candidates but also contributes to the rational design of vaccines, fostering a more efficient and targeted approach to combatting infectious diseases.

In-silico study of protein-protein interactions in wheat blast using docking and molecular dynamics simulation approach

Despite advancements in agricultural research and the introduction of modern biotechnological and farming techniques, food security remains a significant issue. Although the efforts of farmers to meet the demands of a growing population, many plant diseases caused by pathogens, through their effects on cell division and tissue growth, lead to the annual loss of countless food crops. The recently emerged wheat blast fungus Magnaporthe oryzae pathotype Triticum (MoT) poses a significant danger to worldwide wheat cultivation. The fungus is a highly varied lineage of the M. oryzae, responsible for causing rice blast disease. In spite of being a significant challenge to successful wheat production in South America since 1985, the underlying biology of the wheat blast pathogen is still not fully understood. The initial outbreak of the wheat blast in South Asia had a severe impact on wheat production, resulting in a complete loss of yield in affected fields. For the purpose of enhancing disease management, it's vital to acquire a comprehensive comprehension of the infection biology of the fungus and its interaction with wheat plants on molecular levels. Host-pathogen protein interactions (HPIs) have the potential to reveal the pathogens' mechanism for overcoming the host organism. The current study delves into the interactions between the host plant wheat and MoT through protein-protein interactions, molecular docking, and 100 ns molecular dynamic simulations. This research uncovers the structural and functional basis of these proteins, leading to improved plant health and production.Communicated by Ramaswamy H. Sarma.

Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics

The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19. In this work, we analysed missense coding variants in several SARS-CoV-2 proteins and their human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed the impact of missense variants occurring in the protein-protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities for the human viral protein complexes. We predicted a total of 26 affinity-enhancing variants from 13 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed. Occurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.

Immunoinformatics-Based Design of Multi-epitope DNA and mRNA Vaccines Against Zika Virus

In this study, we used an immunoinformatics approach to predict antigenic epitopes of Zika virus (ZIKV) proteins to assist in designing a vaccine antigen against ZIKV. We performed the prediction of CD8+ T-lymphocyte and antigenic B-cell epitopes of ZIKV proteins. The binding interactions of T-cell epitopes with major histocompatibility complex class I (MHC-I) proteins were assessed. We selected the antigenic, conserved, nontoxic, and immunogenic epitopes, which indicated significant interactions with the human leucocyte antigen (HLA-A and HLA-B) alleles and worldwide population coverage of 76.35%. The predicted epitopes were joined with the help of linkers and an adjuvant. The vaccine antigen was then analyzed through molecular docking with TLR3 and TLR8, and it was in silico cloned in the pVAX1 vector to be used as a DNA vaccine and designed as a mRNA vaccine.

Efficient Refinement of Complex Structures of Flexible Histone Peptides Using Post-Docking Molecular Dynamics Protocols

Histones are keys to many epigenetic events and their complexes have therapeutic and diagnostic importance. The determination of the structures of histone complexes is fundamental in the design of new drugs. Computational molecular docking is widely used for the prediction of target-ligand complexes. Large, linear peptides like the tail regions of histones are challenging ligands for docking due to their large conformational flexibility, extensive hydration, and weak interactions with the shallow binding pockets of their reader proteins. Thus, fast docking methods often fail to produce complex structures of such peptide ligands at a level appropriate for drug design. To address this challenge, and improve the structural quality of the docked complexes, post-docking refinement has been applied using various molecular dynamics (MD) approaches. However, a final consensus has not been reached on the desired MD refinement protocol. In this present study, MD refinement strategies were systematically explored on a set of problematic complexes of histone peptide ligands with relatively large errors in their docked geometries. Six protocols were compared that differ in their MD simulation parameters. In all cases, pre-MD hydration of the complex interface regions was applied to avoid the unwanted presence of empty cavities. The best-performing protocol achieved a median of 32% improvement over the docked structures in terms of the change in root mean squared deviations from the experimental references. The influence of structural factors and explicit hydration on the performance of post-docking MD refinements are also discussed to help with their implementation in future methods and applications.

Design of a multi-epitope vaccine against goatpox virus using an immunoinformatics approach

Introduction

Goatpox, a severe infectious disease caused by goatpox virus (GTPV), leads to enormous economic losses in the livestock industry. Traditional live attenuated vaccines cause serious side effects and exist a risk of dispersal. Therefore, it is urgent to develop efficient and safer vaccines to prevent and control of GTPV.

Methods

In the present study, we are aimed to design a multi-epitope subunit vaccine against GTPV using an immunoinformatics approach. Various immunodominant cytotoxic T lymphocytes (CTL) epitopes, helper T lymphocytes (HTL) epitopes, and B-cell epitopes from P32, L1R, and 095 proteins of GTPV were screened and liked by the AAY, GPGPG, and KK connectors, respectively. Furthermore, an adjuvant β-defensin was attached to the vaccine's N-terminal using the EAAAK linker to enhance immunogenicity.

Results

The constructed vaccine was soluble, non-allergenic and non-toxic and exhibited high levels of antigenicity and immunogenicity. The vaccine's 3D structure was subsequently predicted, refined and validated, resulting in an optimized model with a Z-value of -3.4. Molecular docking results demonstrated that the vaccine had strong binding affinity with TLR2(-27.25 kcal/mol), TLR3(-39.84 kcal/mol), and TLR4(-59.42 kcal/mol). Molecular dynamics simulation results indicated that docked vaccine-TLR complexes were stable. Immune simulation analysis suggested that the vaccine can induce remarkable increase in antibody titers of IgG and IgM, higher levels of IFN-γ and IL-2.

Conclusion

The designed GTPV multi-epitope vaccine is structurally stable and can induce robust humoral and cellular immune responses, which may be a promising vaccine candidate against GTPV.

Multiscale In Silico Study of the Mechanism of Activation of the RtcB Ligase by the PTP1B Phosphatase

Inositol-requiring enzyme 1 (IRE1) is a transmembrane sensor that is part of a trio of sensors responsible for controlling the unfolded protein response within the endoplasmic reticulum (ER). Upon the accumulation of unfolded or misfolded proteins in the ER, IRE1 becomes activated and initiates the cleavage of a 26-nucleotide intron from human X-box-containing protein 1 (XBP1). The cleavage is mediated by the RtcB ligase enzyme, which splices together two exons, resulting in the formation of the spliced isoform XBP1s. The XBP1s isoform activates the transcription of genes involved in ER-associated degradation to maintain cellular homeostasis. The catalytic activity of RtcB is controlled by the phosphorylation and dephosphorylation of three tyrosine residues (Y306, Y316, and Y475), which are regulated by the ABL1 tyrosine kinase and PTP1B phosphatase, respectively. This study focuses on investigating the mechanism by which the PTP1B phosphatase activates the RtcB ligase using a range of advanced in silico methods. Protein-protein docking identified key interacting residues between RtcB and PTP1B. Notably, the phosphorylated Tyr306 formed hydrogen bonds and salt bridge interactions with the "gatekeeper" residues Arg47 and Lys120 of the inactive PTP1B. Classical molecular dynamics simulation emphasized the crucial role of Asp181 in the activation of PTP1B, driving the conformational change from an open to a closed state of the WPD-loop. Furthermore, QM/MM-MD simulations provided insights into the free energy landscape of the dephosphorylation reaction mechanism of RtcB, which is mediated by the PTP1B phosphatase.

Modeling and Analysis of HIV-1 Pol Polyprotein as a Case Study for Predicting Large Polyprotein Structures

Acquired immunodeficiency syndrome (AIDS) is caused by human immunodeficiency virus (HIV). HIV protease, reverse transcriptase, and integrase are targets of current drugs to treat the disease. However, anti-viral drug-resistant strains have emerged quickly due to the high mutation rate of the virus, leading to the demand for the development of new drugs. One attractive target is Gag-Pol polyprotein, which plays a key role in the life cycle of HIV. Recently, we found that a combination of M50I and V151I mutations in HIV-1 integrase can suppress virus release and inhibit the initiation of Gag-Pol autoprocessing and maturation without interfering with the dimerization of Gag-Pol. Additional mutations in integrase or RNase H domain in reverse transcriptase can compensate for the defect. However, the molecular mechanism is unknown. There is no tertiary structure of the full-length HIV-1 Pol protein available for further study. Therefore, we developed a workflow to predict the tertiary structure of HIV-1 NL4.3 Pol polyprotein. The modeled structure has comparable quality compared with the recently published partial HIV-1 Pol structure (PDB ID: 7SJX). Our HIV-1 NL4.3 Pol dimer model is the first full-length Pol tertiary structure. It can provide a structural platform for studying the autoprocessing mechanism of HIV-1 Pol and for developing new potent drugs. Moreover, the workflow can be used to predict other large protein structures that cannot be resolved via conventional experimental methods.

Elucidation of the structural dynamics of mutations in PHB2 protein associated with growth suppression and cancer progression

Prohibitin is a multifunctional protein that plays an important role in numerous cellular processes. Membrane-associated mitochondrial prohibitin complex is made up of two subunits, PHB1 and PHB2 which are ubiquitously expressed and analogous to each other. High levels of prohibitin expression have consequently been found in esophageal cancer, endometrial adenocarcinoma, gastric cancer, hepatocellular carcinoma, breast cancer and bladder cancer. The aim of this study is to analyse two-point mutation PHB2_MT1(I → A) and PHB2_MT2(I → P), their effect on PHB2 protein and its effect on formation of mitochondrial complex. It is a residual level study, based on current experimental validation. To establish the effects of the two-point mutations, computational approaches such as molecular modelling, molecular docking, normal mode simulation, molecular dynamics simulations and MM/GBSA were used. An analysis of the energy dynamics of both unbound and complex proteins was conducted to elucidate how mutations impact the energy distribution of PHB2. Our study confirmed that the two mutations decreased the overall stability of PHB2. This was evidenced by heightened atomic fluctuations within the mutated region, accompanied by elevated deviations observed in RMSD and Rg values. Furthermore, these mutations were correlated with a decline in the organization of secondary structural elements. The mutations in PHB2_MT1 and PHB2_MT2 resulted in formation a less stable prohibitin complex. Thus, PHB1 and PHB2 may act as molecular target or novel biomarkers for therapeutic intervention in numerous forms of malignancies.

Structure-based drug discovery to identify SARS-CoV2 spike protein-ACE2 interaction inhibitors

After the emergence of the COVID-19 pandemic in late 2019, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has undergone a dynamic evolution driven by the acquisition of genetic modifications, resulting in several variants that are further classified as variants of interest (VOIs), variants under monitoring (VUM) and variants of concern (VOC) by World Health Organization (WHO). Currently, there are five SARS-CoV-2 VOCs (Alpha, Beta, Delta, Gamma and Omicron), two VOIs (Lambda and Mu) and several other VOIs that have been reported globally. In this study, we report a natural compound, Curcumin, as the potential inhibitor to the interactions between receptor binding domain (RBD(S1)) and human angiotensin-converting enzyme 2 (hACE2) domains and showcased its inhibitory potential for the Delta and Omicron variants through a computational approach by implementing state of the art methods. The study for the first time revealed a higher efficiency of Curcumin, especially for hindering the interaction between RBD(S1) and hACE-2 domains of Delta and Omicron variants as compared to other lead compounds. We investigated that the mutations in the RBD(S1) of VOC especially Delta and Omicron variants affect its structure compared to that of the wild type and other variants and therefore altered its binding to the hACE2 receptor. Molecular docking and molecular dynamics (MD) simulation analyses substantially supported the findings in terms of the stability of the docked complexes. This study offers compelling evidence, warranting a more in-depth exploration into the impact of these alterations on the binding of identified drug molecules with the Spike protein. Further investigation into their potential therapeutic effects in vivo is highly recommended.Communicated by Ramaswamy H. Sarma.

Translational and structural vaccinomics approach to design a multi-epitope vaccine against NOL4 autologous antigen of small cell lung cancer

Small cell lung cancer (SCLC) is one of the most common cancers and it is the sixth common cause for cancer-related deaths. The high plasticity and metastasis have been a major challenge for humanity to treat the disease. Hence, a vaccine for SCLC has become an urgent need of the hour due to public health concern. Implementation of immunoinformatics technique is one of the best way to find a suitable vaccine candidate. Immunoinformatics tools can be used to overcome the limitations and difficulties of traditional vaccinological techniques. Multi-epitope cancer vaccines have become a next-generation technique in vaccinology which can be used to stimulate more potent immune response against a particular antigen by eliminating undesirable molecules. In this study, we used multiple computational and immunoinformatics approach to design a novel multi-epitope vaccine for small cell lung cancer. Nucleolar protein 4 (NOL4) is an autologous cancer-testis antigen overexpressed in SCLC cells. Seventy-five percent humoral immunity have been identified for this particular antigen. In this study, we mapped immunogenic cytotoxic T lymphocyte, helper T lymphocyte, and interferon-gamma epitopes present in NOL4 antigen and designed a multi-epitope-based vaccine using the predicted epitopes. The designed vaccine was antigenic, non-allergenic, and non-toxic with 100% applicability on human population. The chimeric vaccine construct showed stable and significant interaction with endosomal and plasmalemmal toll-like receptors in molecular docking and protein-peptide interaction analysis, thus assuring a strong potent immune response against the vaccine upon administration. Therefore, these preliminary results can be used to carry out further experimental investigations.

A multi-tier computational screening framework to effectively search the mutational space of SARS-CoV-2 receptor binding motif to identify mutants with enhanced ACE2 binding abilities

SARS-CoV-2 gained crucial mutations at the receptor binding domain (RBD) that often changed the course of the pandemic leading to new waves with increased case fatality. Variants are observed with enhanced transmission and immune invasion abilities. Thus, predicting future variants with enhanced transmission ability is a problem of utmost research interest. Here, we have developed a multi-tier exhaustive SARS-CoV-2 mutation screening platform combining MM/GBSA, extensive molecular dynamics simulations, and steered molecular dynamics to identify RBD mutants with enhanced ACE2 binding capability. We have identified four RBM mutations (F490K, S494K, G504F, and the P499L) with significantly higher ACE2 binding abilities than wild-type RBD. Compared to wild-type RBD, they all form stable complexes with more hydrogen bonds and salt-bridge interactions with ACE2. Our simulation data suggest that these mutations allosterically alter the packing of the RBM interface of the RBD-ACE2 complex. As a result, the rupture force required to break the RBD-ACE2 contacts is significantly higher for these mutants.

In silico insights into the dimer structure and deiodinase activity of type III iodothyronine deiodinase from bioinformatics, molecular dynamics simulations, and QM/MM calculations

The homodimeric family of iodothyronine deiodinases (Dios) regioselectively remove iodine from thyroid hormones. Currently, structural data has only been reported for the monomer of the mus type III thioredoxin (Trx) fold catalytic domain (Dio3Trx), but the mode of dimerization has not yet been determined. Various groups have proposed dimer structures that are similar to the A-type and B-type dimerization modes of peroxiredoxins. Computational methods are used to compare the sequence of Dio3Trx to related proteins known to form A-type and B-type dimers. Sequence analysis and in silico protein-protein docking methods suggest that Dio3Trx is more consistent with proteins that adopt B-type dimerization. Molecular dynamics (MD) simulations of the refined Dio3Trx dimer constructed using the SymmDock and GalaxyRefineComplex databases indicate stable dimer formation along the β4α3 interface consistent with other Trx fold B-type dimers. Free energy calculations show that the dimer is stabilized by interdimer interactions between the β-sheets and α-helices. A comparison of MD simulations of the apo and thyroxine-bound dimers suggests that the active site binding pocket is not affected by dimerization. Determination of the transition state for deiodination of thyroxine from the monomer structure using QM/MM methods provides an activation barrier consistent with previous small model DFT studies.Communicated by Ramaswamy H. Sarma.

Structure of a superoxide dismutase from a tardigrade: Ramazzottius varieornatus strain YOKOZUNA-1

Superoxide dismutase (SOD) is an essential and ubiquitous antioxidant protein that is widely present in biological systems. The anhydrobiotic tardigrades are some of the toughest micro-animals. They have an expanded set of genes for antioxidant proteins such as SODs. These proteins are thought to play an essential role in oxidative stress resistance in critical situations such as desiccation, although their functions at the molecular level have yet to be explored. Here, crystal structures of a copper/zinc-containing SOD (RvSOD15) from an anhydrobiotic tardigrade, Ramazzottius varieornatus strain YOKOZUNA-1, are reported. In RvSOD15, one of the histidine ligands of the catalytic copper center is replaced by a valine (Val87). The crystal structures of the wild type and the V87H mutant show that even though a histidine is placed at position 87, a nearby flexible loop can destabilize the coordination of His87 to the Cu atom. Model structures of other RvSODs were investigated and it was found that some of them are also unusual SODs, with features such as deletion of the electrostatic loop or β3 sheet and unusual metal-binding residues. These studies show that RvSOD15 and some other RvSODs may have evolved to lose the SOD function, suggesting that gene duplications of antioxidant proteins do not solely explain the high stress tolerance of anhydrobiotic tardigrades.

ECPAS/Ecm29-mediated 26S proteasome disassembly is an adaptive response to glucose starvation

The 26S proteasome comprises 20S catalytic and 19S regulatory complexes. Approximately half of the proteasomes in cells exist as free 20S complexes; however, our mechanistic understanding of what determines the ratio of 26S to 20S species remains incomplete. Here, we show that glucose starvation uncouples 26S holoenzymes into 20S and 19S subcomplexes. Subcomplex affinity purification and quantitative mass spectrometry reveal that Ecm29 proteasome adaptor and scaffold (ECPAS) mediates this structural remodeling. The loss of ECPAS abrogates 26S dissociation, reducing degradation of 20S proteasome substrates, including puromycylated polypeptides. In silico modeling suggests that ECPAS conformational changes commence the disassembly process. ECPAS is also essential for endoplasmic reticulum stress response and cell survival during glucose starvation. In vivo xenograft model analysis reveals elevated 20S proteasome levels in glucose-deprived tumors. Our results demonstrate that the 20S-19S disassembly is a mechanism adapting global proteolysis to physiological needs and countering proteotoxic stress.

Lamin Filament Assembly Derived from the Atomic Structure of the Antiparallel Four-Helix Bundle

The nucleoskeletal protein lamin is primarily responsible for the mechanical stability of the nucleus. The lamin assembly process requires the A11, A22, and ACN binding modes of the coiled-coil dimers. Although X-ray crystallography and chemical cross-linking analysis of lamin A/C have provided snapshots of A11 and ACN binding modes, the assembly mechanism of the entire filament remains to be explained. Here, we report a crystal structure of a coil 2 fragment, revealing the A22 interaction at the atomic resolution. The structure showed detailed structural features, indicating that two coiled-coil dimers of the coil 2 subdomain are separated and then re-organized into the antiparallel-four-helix bundle. Furthermore, our findings suggest that the ACN binding mode between coil 1a and the C-terminal part of coil 2 when the A11 tetramers are arranged by the A22 interactions. We propose a full assembly model of lamin A/C with the curvature around the linkers, reconciling the discrepancy between the in situ and in vitro observations. Our model accounts for the balanced elasticity and stiffness of the nuclear envelopes, which is essential in protecting the cellular nucleus from external pressure.

Structural insights into cardiolipin replacement by phosphatidylglycerol in a cardiolipin-lacking yeast respiratory supercomplex

Cardiolipin is a hallmark phospholipid of mitochondrial membranes. Despite established significance of cardiolipin in supporting respiratory supercomplex organization, a mechanistic understanding of this lipid-protein interaction is still lacking. To address the essential role of cardiolipin in supercomplex organization, we report cryo-EM structures of a wild type supercomplex (IV1III2IV1) and a supercomplex (III2IV1) isolated from a cardiolipin-lacking Saccharomyces cerevisiae mutant at 3.2-Å and 3.3-Å resolution, respectively, and demonstrate that phosphatidylglycerol in III2IV1 occupies similar positions as cardiolipin in IV1III2IV1. Lipid-protein interactions within these complexes differ, which conceivably underlies the reduced level of IV1III2IV1 and high levels of III2IV1 and free III2 and IV in mutant mitochondria. Here we show that anionic phospholipids interact with positive amino acids and appear to nucleate a phospholipid domain at the interface between the individual complexes, which dampen charge repulsion and further stabilize interaction, respectively, between individual complexes.

Structural Characterization of the Chlorophyllide a Oxygenase (CAO) Enzyme Through an In Silico Approach

Chlorophyllide a oxygenase (CAO) is responsible for converting chlorophyll a to chlorophyll b in a two-step oxygenation reaction. CAO belongs to the family of Rieske-mononuclear iron oxygenases. Although the structure and reaction mechanism of other Rieske monooxygenases have been described, a member of plant Rieske non-heme iron-dependent monooxygenase has not been structurally characterized. The enzymes in this family usually form a trimeric structure and electrons are transferred between the non-heme iron site and the Rieske center of the adjoining subunits. CAO is supposed to form a similar structural arrangement. However, in Mamiellales such as Micromonas and Ostreococcus, CAO is encoded by two genes where non-heme iron site and Rieske cluster localize on the distinct polypeptides. It is not clear if they can form a similar structural organization to achieve the enzymatic activity. In this study, the tertiary structures of CAO from the model plant Arabidopsis thaliana and the Prasinophyte Micromonas pusilla were predicted by deep learning-based methods, followed by energy minimization and subsequent stereochemical quality assessment of the predicted models. Furthermore, the chlorophyll a binding cavity and the interaction of ferredoxin, which is the electron donor, on the surface of Micromonas CAO were predicted. The electron transfer pathway was predicted in Micromonas CAO and the overall structure of the CAO active site was conserved even though it forms a heterodimeric complex. The structures presented in this study will serve as a basis for understanding the reaction mechanism and regulation of the plant monooxygenase family to which CAO belongs.

A novel consensus-based computational pipeline for screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including Omicron variant

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to evolve carrying flexible amino acid substitutions in the spike protein's receptor binding domain (RBD). These substitutions modify the binding of the SARS-CoV-2 to human angiotensin-converting enzyme 2 (hACE2) receptor and have been implicated in altered host fitness, transmissibility, and efficacy against antibody therapeutics and vaccines. Reliably predicting the binding strength of SARS-CoV-2 variants RBD to hACE2 receptor and neutralizing antibodies (NAbs) can help assessing their fitness, and rapid deployment of effective antibody therapeutics, respectively. Here, we introduced a two-step computational framework with 3-fold validation that first identified dissociation constant as a reliable predictor of binding affinity in hetero- dimeric and trimeric protein complexes. The second step implements dissociation constant as descriptor of the binding strengths of SARS-CoV-2 variants RBD to hACE2 and NAbs. Then, we examined several variants of concerns (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron and demonstrated that these VOCs RBD bind to the hACE2 with enhanced affinity. Furthermore, the binding affinity of Omicron variant's RBD was reduced with majority of the RBD-directed NAbs, which is highly consistent with the experimental neutralization data. By studying the atomic contacts between RBD and NAbs, we revealed the molecular footprints of four NAbs (GH-12, P2B-1A1, Asarnow_3D11, and C118)-that may likely neutralize the recently emerged Omicron variant-facilitating enhanced binding affinity. Finally, our findings suggest a computational pathway that could aid researchers identify a range of current NAbs that may be effective against emerging SARS-CoV-2 variants.

Structural basis for Y2 receptor-mediated neuropeptide Y and peptide YY signaling

Neuropeptide Y (NPY) and its receptors are expressed in various human tissues including the brain where they regulate appetite and emotion. Upon NPY stimulation, the neuropeptide Y1 and Y2 receptors (Y₁R and Y₂R, respectively) activate G_I signaling, but their physiological responses to food intake are different. In addition, deletion of the two N-terminal amino acids of peptide YY (PYY(3-36)), the endogenous form found in circulation, can stimulate Y₂R but not Y₁R, suggesting that Y₁R and Y₂R may have distinct ligand-binding modes. Here, we report the cryo-electron microscopy structures of the PYY(3-36)‒Y₂R‒G_i and NPY‒Y₂R‒G_i complexes. Using cell-based assays, molecular dynamics simulations, and structural analysis, we revealed the molecular basis of the exclusive binding of PYY(3-36) to Y₂R. Furthermore, we demonstrated that Y₂R favors G protein signaling over β-arrestin signaling upon activation, whereas Y₁R does not show a preference between these two pathways.

The impact of pathogenic and artificial mutations on Claudin-5 selectivity from molecular dynamics simulations

Tight-junctions (TJs) are multi-protein complexes between adjacent endothelial or epithelial cells. In the blood-brain-barrier (BBB), they seal the paracellular space and the Claudin-5 (Cldn5) protein forms their backbone. Despite the fundamental role in brain homeostasis, little is known on Cldn5-based TJ assemblies. Different structural models were suggested, with Cldn5 protomers generating paracellular pores that restrict the passage of ions and small molecules. Recently, the first Cldn5 pathogenic mutation, G60R, was identified and shown to induce Cl^--selective channels and Na⁺ barriers in BBB TJs, providing an excellent opportunity to validate the structural models. Here, we used molecular dynamics to study the permeation of ions and water through two distinct G60R-Cldn5 paracellular architectures. Only the so-called Pore I reproduces the functional modification observed in experiments, displaying a free energy (FE) minimum for Cl^- and a barrier for Na⁺ consistent with anionic selectivity. We also studied the artificial Q57D and Q63D mutations in the constriction region, Q57 being conserved in Cldns except for cation permeable homologs. In both cases, we obtain FE profiles consistent with facilitated passage of cations. Our calculations provide the first in-silico description of a Cldn5 pathogenic mutation, further assessing the TJ Pore I model and yielding new insight on BBB's paracellular selectivity.

Integrative transcriptome analysis of SARS-CoV-2 human-infected cells combined with deep learning algorithms identifies two potential cellular targets for the treatment of coronavirus disease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quickly spread worldwide, leading coronavirus disease 2019 (COVID-19) to hit pandemic level less than 4 months after the first official cases. Hence, the search for drugs and vaccines that could prevent or treat infections by SARS-CoV-2 began, intending to reduce a possible collapse of health systems. After 2 years, efforts to find therapies to treat COVID-19 continue. However, there is still much to be understood about the virus' pathology. Tools such as transcriptomics have been used to understand the impact of SARS-CoV-2 on different cells isolated from various tissues, leaving datasets in the databases that integrate genes and differentially expressed pathways during SARS-CoV-2 infection. After retrieving transcriptome datasets from different human cells infected with SARS-CoV-2 available in the database, we performed an integrative analysis associated with deep learning algorithms to determine differentially expressed targets mainly after infection. The targets found represented a fructose transporter (GLUT5) and a component of proteasome 26s. These targets were then molecularly modeled, followed by molecular docking that identified potential inhibitors for both structures. Once the inhibition of structures that have the expression increased by the virus can represent a strategy for reducing the viral replication by selecting infected cells, associating these bioinformatics tools, therefore, can be helpful in the screening of molecules being tested for new uses, saving financial resources, time, and making a personalized screening for each infectious disease.

Computational study of ion permeation through claudin-4 paracellular channels

Claudins (Cldns) form a large family of protein homologs that are essential for the assembly of paracellular tight junctions (TJs), where they form channels or barriers with tissue-specific selectivity for permeants. In contrast to several family members whose physiological role has been identified, the function of claudin 4 (Cldn4) remains elusive, despite experimental evidence suggesting that it can form anion-selective TJ channels in the renal epithelium. Computational approaches have recently been employed to elucidate the molecular basis of Cldns' function, and hence could help in clarifying the role of Cldn4. In this work, we use structural modeling and all-atom molecular dynamics simulations to transfer two previously introduced structural models of Cldn-based paracellular complexes to Cldn4 to reproduce a paracellular anion channel. Free energy calculations for ionic transport through the pores allow us to establish the thermodynamic properties driving the ion-selectivity of the structures. While one model shows a cavity permeable to chloride and repulsive to cations, the other forms barrier to the passage of all the major physiological ions. Furthermore, our results confirm the charge selectivity role of the residue Lys65 in the first extracellular loop of the protein, rationalizing Cldn4 control of paracellular permeability.

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: Implications for future surveillance programmes

Understanding the origin of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unresolved issue for scientific communities all over the world. Understanding the mechanism of virus entry to the host cells is crucial to deciphering the susceptibility profiles of animal species to SARS-CoV-2. The interaction of SARS-CoV-2 ligands (receptor-binding domain on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the SARS-CoV-2 spike protein can bind to a wide range of vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Furthermore, the current study facilitated the identification of genetic determinants that may differentiate susceptible from resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified bat species' susceptibility to SARS-CoV-2. The current study's findings highlight the importance of intensive surveillance programmes aimed at identifying susceptible hosts, especially those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

Design of a specific peptide against phenolic glycolipid-1 from Mycobacterium leprae and its implications in leprosy bacilli entry

BACKGROUND

Mycobacterium leprae, the causative agent of Hansen’s disease, causes neural damage through the specific interaction between the external phenolic glycolipid-1 (PGL-1) and laminin subunit alpha-2 (LAMA2) from Schwann cells.

OBJECTIVE

To design a LAMA2-based peptide that targets PGL-1 from M. leprae.

METHODS

We retrieved the protein sequence of human LAMA2 and designed a specific peptide using the Antimicrobial Peptide Database and physicochemical parameters for antimycobacterial peptide-lipid interactions. We used the AlphaFold2 server to predict its three-dimensional structure, AUTODOCK-VINA for docking, and GROMACS programs for molecular dynamics simulations.

FINDINGS

We analysed 52 candidate peptides from LAMA2, and subsequent screening resulted in a single 60-mer peptide. The mapped peptide comprises four β-sheets and a random coiled region. This peptide exhibits a 45% hydrophobic ratio, in which one-third covers the same surface. Molecular dynamics simulations show that our predicted peptide is stable in aqueous solution and remains stable upon interaction with PGL-1 binding. In addition, we found that PGL-1 has a preference for one of the two faces of the predicted peptide, which could act as the preferential binding site of PGL-1.

MAIN CONCLUSIONS

Our LAMA2-based peptide targeting PGL-1 might have the potential to specifically block this key molecule, suggesting that the preferential region of the peptide is involved in the initial contact during the attachment of leprosy bacilli to Schwann cells.

Computational Assessment of Different Structural Models for Claudin-5 Complexes in Blood-Brain Barrier Tight Junctions

The blood-brain barrier (BBB) strictly regulates the exchange of ions and molecules between the blood and the central nervous system. Tight junctions (TJs) are multimeric structures that control the transport through the paracellular spaces between the adjacent brain endothelial cells of the BBB. Claudin-5 (Cldn5) proteins are essential for TJ formation and assemble into multiprotein complexes via cis-interactions within the same cell membrane and trans-interactions across two contiguous cells. Despite the relevant biological function of Cldn5 proteins and their role as targets of brain drug delivery strategies, the molecular details of their assembly within TJs are still unclear. Two different structural models have been recently introduced, in which Cldn5 dimers belonging to opposite cells join to generate paracellular pores. However, a comparison of these models in terms of ionic transport features is still lacking. In this work, we used molecular dynamics simulations and free energy (FE) calculations to assess the two Cldn5 pore models and investigate the thermodynamic properties of water and physiological ions permeating through them. Despite different FE profiles, both structures present single/multiple FE barriers to ionic permeation, while being permissive to water flux. These results reveal that both models are compatible with the physiological role of Cldn5 TJ strands. By identifying the protein-protein surface at the core of TJ Cldn5 assemblies, our computational investigation provides a basis for the rational design of synthetic peptides and other molecules capable of opening paracellular pores in the BBB.

Cyclin-Dependent Kinase 1 depolymerizes nuclear lamin filaments by disrupting the head-to-tail interaction of the lamin central rod domain

Nuclear lamins maintain the nuclear envelope structure by forming long linear filaments via two alternating molecular arrangements of coiled-coil dimers, known as A11 and A22 binding modes. The A11 binding mode is characterized by the antiparallel interactions between coil 1b domains, whereas the A22 binding mode is facilitated by interactions between the coil 2 domains of lamin. The junction between A11- and A22-interacting dimers in the lamin tetramer produces another parallel head–tail interaction between coil 1a and the C-terminal region of coil 2, called the ACN interaction. During mitosis, phosphorylation in the lamin N-terminal head region by the cyclin-dependent kinase (CDK) complex triggers depolymerization of lamin filaments, but the associated mechanisms remain unknown at the molecular level. In this study, we revealed using the purified proteins that phosphorylation by the CDK1 complex promotes disassembly of lamin filaments by directly abolishing the ACN interaction between coil 1a and the C-terminal portion of coil 2. We further observed that this interaction was disrupted as a result of alteration of the ionic interactions between coil 1a and coil 2. Combined with molecular modeling, we propose a mechanism for CDK1-dependent disassembly of the lamin filaments. Our results will help to elucidate the cell cycle–dependent regulation of nuclear morphology at the molecular level.

In silico analysis of the predicted protein-protein interaction of syntaxin-18, a putative receptor of Peregrinus maidis Ashmead (Hemiptera: Delphacidae) with Maize mosaic virus glycoprotein

The corn planthopper, Peregrinus maidis Ashmead (Hemiptera:Delphacidae), is a widely distributed insect pest which serves as a vector of two phytopathogenic viruses, Maize mosaic virus (MMV) and Maize stripe virus (MStV). It transmits the viruses in a persistent and propagative manner. MMV is an alphanucleorhabdovirus with a negative-sense, single-stranded RNA unsegmented genome. One identified insect vector protein that may serve as receptor to MMV is Syntaxin-18 (PmStx18) which belongs to the SNAREs (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) proteins. SNAREs play major roles in the final stage of docking and subsequent fusion of diverse vesicle-mediated transport events. In this work, in silico analysis of the interaction of MMV glycoprotein (MMV G) and PmStx18 was performed. Various freely available protein-protein docking web servers were used to predict the 3 D complex of MMV G and PmStx18. Analysis and protein-protein interaction (PPI) count showed that the complex predicted by the ZDOCK server has the highest number of interaction and highest affinity, as suggested by the calculated solvation free energy gain upon formation of the interface (ΔⁱG = -31 kcal/mol). Molecular dynamics simulation of the complex revealed important interactions at the interface over the course of 25 ns. This is the first in silico analysis performed for the interaction on a putative receptor of P. maidis and MMV G. The results of the PPI prediction provide novel information for studying the role of Stx18 in the transport, docking and fusion events involved in virus particle transport in the insect vector cells and its release.Communicated by Ramaswamy H. Sarma.

Structure of UBE2K-Ub/E3/polyUb reveals mechanisms of K48-linked Ub chain extension

Ubiquitin (Ub) chain types govern distinct biological processes. K48-linked polyUb chains target substrates for proteasomal degradation, but the mechanism of Ub chain synthesis remains elusive due to the transient nature of Ub handover. Here, we present the structure of a chemically trapped complex of the E2 UBE2K covalently linked to donor Ub and acceptor K48-linked di-Ub, primed for K48-linked Ub chain synthesis by a RING E3. The structure reveals the basis for acceptor Ub recognition by UBE2K active site residues and the C-terminal Ub-associated (UBA) domain, to impart K48-linked Ub specificity and catalysis. Furthermore, the structure unveils multiple Ub-binding surfaces on the UBA domain that allow distinct binding modes for K48- and K63-linked Ub chains. This multivalent Ub-binding feature serves to recruit UBE2K to ubiquitinated substrates to overcome weak acceptor Ub affinity and thereby promote chain elongation. These findings elucidate the mechanism of processive K48-linked polyUb chain formation by UBE2K.

Designing of nanobodies against Dengue virus Capsid: a computational affinity maturation approach

Dengue virus, an arbovirus, is one of the most prevalent diseases in the tropical environment and leads to huge number of casualties every year. No therapeutics are available till date against the viral disease and the only medications provide symptomatic relief. In this study, we have focused on utilizing conventional nanobodies and repurposing them for Dengue. Computationally affinity matured, best binding nanobodies tagged with constant antibody regions, could be proposed as therapeutics. These could also be applied for drug delivery purposes due to their high specificity against the viral Capsid. Another application of these nanobodies has been thought to utilize them for diagnostic purposes, to use the nanobodies for viral detection from patient samples at the earliest stage using ELISA. This study may open a new avenue for immunologic study in foreseeable future with the usage of the same molecules for multiple purposes. HighlightsNatural nanobodies against viruses were modified for use against Dengue virus Capsid conserved regions.Computational affinity maturation was performed making use of change in binding affinities upon mutating various residues in the complementary determining regions.Docking studies performed to inspect the docking groove, interface analysis and energy calculations.MM/GBSA calculations done to calculate binding free energy of the complex to determine stability of the complex.Communicated by Ramaswamy H. Sarma.

Benchmarking of structure refinement methods for protein complex models

Protein structure docking is the process in which the quaternary structure of a protein complex is predicted from individual tertiary structures of the protein subunits. Protein docking is typically performed in two main steps. The subunits are first docked while keeping them rigid to form the complex, which is then followed by structure refinement. Structure refinement is crucial for a practical use of computational protein docking models, as it is aimed for correcting conformations of interacting residues and atoms at the interface. Here, we benchmarked the performance of eight existing protein structure refinement methods in refinement of protein complex models. We show that the fraction of native contacts between subunits is by far the most straightforward metric to improve. However, backbone dependent metrics, based on the Root Mean Square Deviation proved more difficult to improve via refinement.

In silico analysis and characterization of medicinal mushroom cystathionine beta-synthase as an angiotensin converting enzyme (ACE) inhibitory protein

Angiotensin-converting enzyme (ACE) regulates blood pressure and has been implicated in several conditions including lung injury, fibrosis and Alzheimer's disease. Medicinal mushroom Ganordema lucidum (Reishi) cystathionine beta-synthase (GlCBS) was previously reported to possess ACE inhibitory activities. However, the inhibitory mechanism of CBS protein remains unreported. Therefore, this study integrates in silico sequencing, structural and functional based-analysis, protein modelling, molecular docking and binding affinity calculation to elucidate the inhibitory mechanism of GlCBS and Lignosus rhinocerus (Tiger milk mushroom) CBS protein (LrCBS) towards ACE. In silico analysis indicates that CBSs from both mushrooms share high similarities in terms of physical properties, structural properties and domain distribution. Protein-protein docking analysis revealed that both GlCBS and LrCBS potentially modulate the C-terminal domain of ACE (C-ACE) activity via regulation of chloride activation and/or prevention of substrate entry. GICBS and LrCBS were also shown to interact with ACE at the same region that presumably inhibits the function of ACE.

Design of a multi-epitope protein vaccine against herpes simplex virus, human papillomavirus and Chlamydia trachomatis as the main causes of sexually transmitted diseases

Sexually transmitted diseases (STDs) have a profound effect on reproductivity and sexual health worldwide. According to world health organization (WHO) 375 million new case of STD, including chlamydia trachomatis (chlamydia), Neisseria gonorrhoeae, HSV, HPV has been reported in 2016. More than 30 diverse pathogenesis have identified to be transmitted through sexual intercourse. Of these, viral infections (hepatitis B, herpes simplex virus (HSV or herpes), HIV, and human papillomavirus (HPV) are incurable. However, symptoms caused by the incurable viral infections can be alleviated through treatment. Antimicrobial resistance (AMR) of sexually transmitted infections (STIs) to antibiotics has increased recent years, in this regard, vaccination is proposed as an important strategy for prevention or treatment of STDs. Vaccine against HPV 16 and 18 suggests a new approach for controlling STDs but until now, there is no prophylactic or therapeutic vaccine have been approved for HSV-2 and Chlamydia trachomatis (CT); in this reason, developing an efficient vaccine is inevitable. Recently, different combinatorial forms of subunit vaccines against two or three type of bacteria have been designed. In this study, to design a combinatorial vaccine against HSV, CT, and HPV, the E7 and L2 from HPV, glycoprotein D from HSV-2 and ompA from CT were selected as final antigens. Afterward, the immunodominant helper T lymphocytes (HTLs) and cytolytic T lymphocytes (CTLs) epitopes were chosen from aforesaid antigens. P30 (tetanus toxoid epitope) as universal T-helper were also added to the vaccine. Moreover, flagellin D_1/D₀ as TLR5 agonist and the RS09 as a TLR4 ligand were incorporated to N and C-terminals of peptide vaccine, respectively. Finally, all selected parts were fused together by appropriate linkers to enhance vaccine efficiency. The physicochemical, structural, and immunological properties of the designed vaccine protein were assessed. To achieve the best 3D model of the protein vaccine, modeling, refinement, and validation of modeled structures were also done. Docking evaluation demonstrated suitable interaction between the vaccine and TLR5. Moreover, molecular dynamics (MD) studies showed an appropriate and stable structure of protein and TLR5. Based on immunoinformatic analysis, our vaccine candidate could potentially incite humoral and cellular immunities, which are critical for protection against HPV, HSV-2, and chlamydia trachomatis. It should be noted that, experimental studies are needed to confirm the efficacy of the designed vaccine.

A conserved Neurite Outgrowth and Guidance motif with biomimetic potential in neuronal Cell Adhesion Molecules

The discovery of conserved protein motifs can, in turn, unveil important regulatory signals, and when properly designed, synthetic peptides derived from such motifs can be used as biomimetics for biotechnological and therapeutic purposes. We report here that specific Ig-like repeats from the extracellular domains of neuronal Cell Adhesion Molecules share a highly conserved Neurite Outgrowth and Guidance (NOG) motif, which mediates homo- and heterophilic interactions crucial in neural development and repair. Synthetic peptides derived from the NOG motif of such proteins can boost neuritogenesis, and this potential is also retained by peptides with recombinant sequences, when fitting the NOG sequence pattern. The NOG motif discovery not only provides one more tile to the complex puzzle of neuritogenesis, but also opens the route to new neural regeneration strategies via a tunable biomimetic toolbox.

Discovery of a transdermally deliverable pentapeptide for activating AdipoR1 to promote hair growth

Alopecia induced by aging or side effects of medications affects millions of people worldwide and impairs the quality of life; however, there is a limit to the current medications. Here, we identify a small transdermally deliverable 5-mer peptide (GLYYF; P5) that activates adiponectin receptor 1 (AdipoR1) and promotes hair growth. P5 sufficiently reproduces the biological effect of adiponectin protein via AMPK signaling pathway, increasing the expression of hair growth factors in the dermal papilla cells of human hair follicle. P5 accelerates hair growth ex vivo and induces anagen hair cycle in mice in vivo. Furthermore, we elucidate a key spot for the binding between AdipoR1 and adiponectin protein using docking simulation and mutagenesis studies. This study suggests that P5 could be used as a topical peptide drug for alleviating pathological conditions, which can be improved by adiponectin protein, such as alopecia.

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

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

Protein oligomer structure prediction using GALAXY in CASP14

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

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

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

Reconstruction of the Fas-Based Death-Inducing Signaling Complex (DISC) Using a Protein-Protein Docking Meta-Approach

The death-inducing signaling complex (DISC) is a fundamental multiprotein complex, which triggers the extrinsic apoptosis pathway through stimulation by death ligands. DISC consists of different death domain (DD) and death effector domain (DED) containing proteins such as the death receptor Fas (CD95) in complex with FADD, procaspase-8, and cFLIP. Despite many experimental and theoretical studies in this area, there is no global agreement neither on the DISC architecture nor on the mechanism of action of the involved species. In the current work, we have tried to reconstruct the DISC structure by identifying key protein interactions using a new protein-protein docking meta-approach. We combined the benefits of five of the most employed protein-protein docking engines, HADDOCK, ClusPro, HDOCK, GRAMM-X, and ZDOCK, in order to improve the accuracy of the predicted docking complexes. Free energy of binding and hot spot interacting residues were calculated and determined for each protein-protein interaction using molecular mechanics generalized Born surface area and alanine scanning techniques, respectively. In addition, a series of in-cellulo protein-fragment complementation assays were conducted to validate the protein-protein docking procedure. The results show that the DISC formation initiates by dimerization of adjacent Fas_DD trimers followed by recruitment of FADD through homotypic DD interactions with the oligomerized death receptor. Furthermore, the in-silico outcomes indicate that cFLIP cannot bind directly to FADD; instead, cFLIP recruitment to the DISC is a hierarchical and cooperative process where FADD initially recruits procaspase-8, which in turn recruits and heterodimerizes with cFLIP. Finally, a possible structure of the entire DISC is proposed based on the docking results.

Current status and relevance of single nucleotide polymorphisms in IL-6-/IL-12-type cytokine receptors

Cytokines control immune related events and are critically involved in a plethora of patho-physiological processes including autoimmunity and cancer development. In rare cases, single nucleotide polymorphisms (SNPs) or single nucleotide variations (SNVs) in cytokine receptors eventually cause detrimental ligand-independent, constitutive activation of signal transduction. Most SNPs have, however, no or only marginal influences on gene expression, protein stability, localization and function and thereby only slightly affecting pathogenesis probability. The SNP database (dbSNP) is an archive for a broad collection of polymorphisms in which SNPs are categorized and marked with a locus accession number "reference SNP" (rs). Here, we engineered an algorithm to directly align dbSNP information to DNA and protein sequence information to clearly illustrate a genetic SNP landscape exemplified for all tall cytokine receptors of the IL-6/IL-12 family, including IL-23R, IL-12Rβ1, IL-12Rβ2, gp130, LIFR, OSMR and WSX-1. This information was complemented by a comprehensive literature summary and structural insights of relevant disease-causing SNPs in cytokine/cytokine receptor interfaces. In summary, we present a general strategy with potential to apply to other cytokine receptor networks.

Designing multi-epitope vaccine candidates against functional amyloids in Pseudomonas aeruginosa through immunoinformatic and structural bioinformatics approach

Pseudomonas aeruginosa (P. aeruginosa) displays high drug resistance and biofilm-mediated adaptability, which makes its infections difficult to treat. Alternative intervention methods and targets have made such infections treatment manageable. One of the biofilm components, functional amyloids of Pseudomonas (Fap) is correlated positively with virulence and mucoidy phenotype found in infection in cystic fibrosis (CF) patients. Extracellular accessibility, conservation across P. aeruginosa isolates and linkage with lung infections phenotype in CF patients, makes Fap a promising intervention target. Furthermore, the reported effect of bacterial amyloid on neuronal function and immune response makes it a targetable candidate. In the current study, Fap C protein and its immediate interactions were explored to extract antigenic T-cell and B-cell epitopes. A combination of epitopes and peptide adjuvants has been linked to derive vaccine candidate structures. The vaccine candidates were validated for antigenicity, allergenicity, physiochemical properties, stability and interactions with TLRs and MHC alleles. Immunosimulation studies have demonstrated that vaccines elicit Th1 dominated response, which can assist in good prognosis of infection in CF patients.

Computational designing of a peptide that potentially blocks the entry of SARS-CoV, SARS-CoV-2 and MERS-CoV

Last decade has witnessed three major pandemics caused by SARS-CoV, SARS-CoV-2 and MERS-CoV that belong to Coronavirus family. Currently, there are no effective therapies available for corona virus infections. Since the three viruses belong to the same family and share many common features, we can theoretically design a drug that can be effective on all the three of them. In this study, using computational approach, we designed a peptide (Peptide 7) that can bind to the Receptor Binding Domain (RBD) of SARS-CoV, SARS-CoV-2 and MERS-CoV thereby preventing the entry of the viruses into the host cell. The peptide inhibitor was designed as a consensus peptide from three different peptides that might individually bind to the RBD of the three viruses. Docking studies and molecular dynamic simulations using Peptide 7 has shown that it binds with higher affinity than the native receptors of the RBD and forms a stable complex thereby preventing further viral-receptor interaction and inhibiting their cellular entry. This effective binding is observed for the three RBDs, despite the Peptide 7 interactions being slightly different. Hence; this peptide inhibitor can be used as a potential candidate for the development of peptide based anti-viral therapy against Corona viruses.

A hydrophobic residue stabilizes dimers of regulatory ACT-like domains in plant basic helix-loop-helix transcription factors

About a third of the plant basic helix–loop–helix (bHLH) transcription factors harbor a C-terminal aspartate kinase, chorismate mutase, and TyrA (ACT)-like domain, which was originally identified in the maize R regulator of anthocyanin biosynthesis, where it modulates the ability of the bHLH to dimerize and bind DNA. Characterization of other bHLH ACT-like domains, such as the one in the Arabidopsis R ortholog, GL3, has not definitively confirmed dimerization, raising the question of the overall role of this potential regulatory domain. To learn more, we compared the dimerization of the ACT-like domains of R (R^ACT) and GL3 (GL3^ACT). We show that R^ACT dimerizes with a dissociation constant around 100 nM, over an order of magnitude stronger than GL3^ACT. Structural predictions combined with mutational analyses demonstrated that V568, located in a hydrophobic pocket in R^ACT, is important: when mutated to the Ser residue present in GL3^ACT, dimerization affinity dropped by almost an order of magnitude. The converse S595V mutation in GL3^ACT significantly increased the dimerization strength. We cloned and assayed dimerization for all identified maize ACT-like domains and determined that 12 of 42 formed heterodimers in yeast two-hybrid assays, irrespective of whether they harbored V568, which was often replaced by other aliphatic amino acids. Moreover, we determined that the presence of polar residues at that position occurs only in a small subset of anthocyanin regulators. The combined results provide new insights into possibly regulatory mechanisms and suggest that many of the other plant ACT-like domains associate to modulate fundamental cellular processes.

Recognition of plausible therapeutic agents to combat COVID-19: An omics data based combined approach

Coronavirus disease-2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has become an immense threat to global public health. In this study, we performed complete genome sequencing of a SARS-CoV-2 isolate. More than 67,000 genome sequences were further inspected from Global Initiative on Sharing All Influenza Data (GISAID). Using several in silico techniques, we proposed prospective therapeutics against this virus. Through meticulous analysis, several conserved and therapeutically suitable regions of SARS-CoV-2 such as RNA-dependent RNA polymerase (RdRp), Spike (S) and Membrane glycoprotein (M) coding genes were selected. Both S and M were chosen for the development of a chimeric vaccine that can generate memory B and T cells. siRNAs were also designed for S and M gene silencing. Moreover, six new drug candidates were suggested that might inhibit the activity of RdRp. Since SARS-CoV-2 and SARS-CoV-1 have 82.30% sequence identity, a Gene Expression Omnibus (GEO) dataset of Severe Acute Respiratory Syndrome (SARS) patients were analyzed. In this analysis, 13 immunoregulatory genes were found that can be used to develop type 1 interferon (IFN) based therapy. The proposed vaccine, siRNAs, drugs and IFN based analysis of this study will accelerate the development of new treatments.

Computational Insight Into the Mechanism of SARS-CoV-2 Membrane Fusion

Membrane fusion, a key step in the early stages of virus propagation, allows the release of the viral genome in the host cell cytoplasm. The process is initiated by fusion peptides that are small, hydrophobic components of viral membrane-embedded glycoproteins and are typically conserved within virus families. Here, we attempted to identify the correct fusion peptide region in the Spike protein of SARS-CoV-2 by all-atom molecular dynamics simulations of dual membrane systems with varied oligomeric units of putative candidate peptides. Of all of the systems tested, only a trimeric unit of a 40-amino-acid region (residues 816-855 of SARS-CoV-2 Spike) was effective in triggering the initial stages of membrane fusion, within 200 ns of simulation time. Association of this trimeric unit with dual membranes resulted in the migration of lipids from the upper leaflet of the lower bilayer toward the lower leaflet of the upper bilayer to create a structural unit reminiscent of a fusion bridge. We submit that residues 816-855 of Spike represent the bona fide fusion peptide of SARS-CoV-2 and that computational methods represent an effective way to identify fusion peptides in viral glycoproteins.

Ensemble-based high-throughput virtual screening of natural ligands using the Super Natural-II database against cell-wall protein dTDP-4-dehydrorhamnose reductase (RmlD) in Mycobacterium tuberculosis

The disease Tuberculosis (TB) is caused by a bacterium called Mycobacterium tuberculosis (Mtb). The bacterial cell-wall consists of peptidoglycan layer maintains the cellular integrity and cell viability. The main problem resides in the cell cycle of Mycobacterium tuberculosis in its quiescent form which is not targeted by any drugs hence there is an immediate need for new antibiotics to target the cell wall. The current study deals with the dTDP-4-dehydrorahmnose reductase (RmlD) which is the final enzyme in the series of cell-wall proteins of Mtb. The RmlD is a part of Carbohydrate biosynthesis has been considered as a good drug target for the novel class of antibiotics. Our study begins with the protein structure prediction, Homology studies were conducted using the Phyre2 web server. The structure is then refined and subjected to molecular dynamics simulations for 50 ns using GROMACS. The clustering analysis has been carried out and generated 41 clusters with 2 Å as the cut-off. Blind docking virtual screening was performed against RmlD protein using the Super Natural-II database with AutoDock4.0. its results helped to screen top ligands based on best binding energies. In both dockings, there are some common residues in which the ligands are interacting and forming the Hydrogen bonds such as Asp-105, Val-158, Thr-160, Gly-161, Arg-224, Arg-256. The ligand-567 giving the best results by being in the top-3 of all the clusters in both blind docking as well as the active-site docking. Hence ligand-567 can be a potential inhibitor of RmlD which can further inhibit the cell-wall synthesis of Mycobacterium tuberculosis.Communicated by Ramaswamy H. Sarma.

A bacteriophage mimic of the bacterial nucleoid-associated protein Fis

We report the identification and characterization of a bacteriophage λ-encoded protein, NinH. Sequence homology suggests similarity between NinH and Fis, a bacterial nucleoid-associated protein (NAP) involved in numerous DNA topology manipulations, including chromosome condensation, transcriptional regulation and phage site-specific recombination. We find that NinH functions as a homodimer and is able to bind and bend double-stranded DNA in vitro. Furthermore, NinH shows a preference for a 15 bp signature sequence related to the degenerate consensus favored by Fis. Structural studies reinforced the proposed similarity to Fis and supported the identification of residues involved in DNA binding which were demonstrated experimentally. Overexpression of NinH proved toxic and this correlated with its capacity to associate with DNA. NinH is the first example of a phage-encoded Fis-like NAP that likely influences phage excision-integration reactions or bacterial gene expression.