iMod: multipurpose normal mode analysis in internal coordinates

Gaussian network model revisited: Effects of mutation and ligand binding on protein behavior

The coarse-grained Gaussian Network model, GNM, considers only the alpha carbons of the folded protein. Therefore it is not directly applicable to the study of mutation or ligand binding problems where atomic detail is required. This shortcoming is improved by including all atom pairs within the coordination shell of each other into the Kirchoff Adjacency Matrix. Counting all contacts rather than only alpha carbon contacts diminishes the magnitude of fluctuations in the system. But more importantly, it changes the graph-like connectivity structure, i.e., the Kirchoff Adjacency Matrix of the protein. This change depends on amino acid type which introduces amino acid specific and position specific information into the classical coarse-grained GNM which was originally modelled in analogy with the phantom network model of rubber elasticity. With this modification, it is now possible to explain the consequences of mutation and ligand binding on residue fluctuations, their pair-correlations and mutual information (MI) shared by each pair. We refer to the new model as 'all-atom GNM'. Using examples from published data we show that the all-atom GNM gives B-factors that are in better agreement with experiment, can explain effects of mutation on long range communication in PDZ domains and can predict effects of GDP and GTP binding on the dimerization of KRAS.

Computational construction of a glycoprotein multi-epitope subunit vaccine candidate for old and new South-African SARS-CoV-2 virus strains

The discovery of a new SARS-CoV-2 virus strain in South Africa presents a major public health threat, therefore contributing to increased infections and transmission rates during the second wave of the global pandemic. This study lays the groundwork for the development of a novel subunit vaccine candidate from the circulating strains of South African SARS-CoV-2 and provides an understanding of the molecular epidemiological trend of the circulating strains. A total of 475 whole-genome nucleotide sequences from South Africa submitted between December 1, 2020 and February 15, 2021 available at the GISAID database were retrieved based on its size, coverage level and hosts. To obtain the distribution of the clades and lineages of South African SARS-CoV-2 circulating strains, the metadata of the sequence retrieved were subjected to an epidemiological analysis. There was a prediction of the cytotoxic T lymphocytes (CTL), Helper T cells (HTL) and B-cell epitopes. Furthermore, there was allergenicity, antigenicity and toxicity predictions on the epitopes. The analysis of the physicochemical properties of the vaccine construct was performed; the secondary structure, tertiary structure and B-cell 3D conformational structure of the vaccine construct were predicted. Also, molecular binding simulations and dynamics simulations were adopted in the prediction of the vaccine construct's stability and binding affinity with TLRs. Result obtained from the metadata analysis indicated lineage B.1.351 to be in higher circulation among various circulating strains of SARS-CoV-2 in South Africa and GH has the highest number of circulating clades. The construct of the novel vaccine was antigenic, non-allergenic and non-toxic. The Instability index (II) score and aliphatic index were estimated as 41.74 and 78.72 respectively. The computed half-life in mammalian reticulocytes was 4.4 h in vitro, for yeast and in E. coli was >20 h and >10 h in vivo respectively. The grand average of hydropathicity (GRAVY) score is estimated to be -0.129, signifying the hydrophilic nature of the protein. The molecular docking indicates that the vaccine construct has a high binding affinity towards the TLRs with TLR 3 having the highest binding energy (-1203.2 kcal/mol) and TLR 9 with the lowest (-1559.5 kcal/mol). These results show that the vaccine construct is promising and should be evaluated using animal model.

Oxa-376 and Oxa-530 variants of β-lactamase: computational study uncovers potential therapeutic targets of Acinetobacter baumannii

Antimicrobial resistance is a major global health crisis, resulting in thousands of deaths each year. Antibiotics' effectiveness against microorganisms deteriorates over time as multidrug resistance (MDR) develops, which is exacerbated by irregular antibiotic use, poor disease management, and the evasive nature of bacteria. The World Health Organization has recognized multidrug resistance as a critical public health concern, and Acinetobacter baumannii has been at the center of attention due to its ability to develop multidrug resistance (MDR). It generally produces carbapenem-hydrolyzing oxacillinase, which has been identified as the primary source of beta-lactam resistance in MDR bacteria. Recently, point mutations in A. baumannii have been identified as a key factor of multidrug resistance, making them a prime concern for researchers. The goal of the current work was to establish a unique way of finding multidrug-resistant variants and identify the most damaging mutations in the existing databases. We characterized the deleterious variants of oxacillinases using several computational tools. Following a thorough analysis, Oxa-376 and Oxa-530 were found to be more damaging when compared with the wild-type Oxa-51. The mutants' 3D structures were then prepared and refined with RaptorX, GalaxyRefine, and SAVES servers. Our research incorporates seven antimicrobial agents to illustrate the resistance capability of the variants of oxacillinase by evaluating binding affinity in Autodock-vina and Schrodinger software. RMSD, RMSF, Radius of gyration analysis, the solvent-accessible surface area (SASA), hydrogen bonding analysis and MM-GBSA from Molecular Dynamics Simulation revealed the dynamic nature and stability of wild-type and Oxa-376 and Oxa-530 variants. Our findings will benefit researchers looking for the deleterious mutations of Acinetobacter baumannii and new therapeutics to combat those variants. However, further studies are necessary to evaluate the mechanism of hydrolyzing activity and antibiotic resistance of these variants.

Determining novel therapeutic targets of Acinetobacter baumannii. Deleterious variants, causing antibiotic resistance, were identified by molecular docking and molecular dynamics simulation suggesting new therapeutic targets Oxa-376 and Oxa-530.

Development of Multi-epitope Subunit Vaccine Against Pseudomonas aeruginosa Using OprF/OprI and PopB Proteins

Background: The emerging problem of antibiotic resistance in Pseudomonas aeruginosa is a global health concern; hence, revealing innovative therapeutic approaches (such as designing an immunogenic vaccine candidate) is needed. There is no evidence of the availability of an effective vaccine that can combat the infection caused by this microorganism. Objectives: This research was conducted to develop a potential chimeric vaccine against P. aeruginosa using reverse vaccinology approaches. Methods: The present vaccine candidate comprised outer membrane protein F and I (OprF/OprI) and PopB with appropriate linkers. After applying meticulous immune-informatics investigation, the multi-epitope vaccine was created, including helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL), interferon gamma (IFN-γ), and interleukin 4 (IL-4) epitopes. Then, the physicochemical characteristics, allergenicity, toxicity, and antigenicity were analyzed. After investigating the secondary structure, the tertiary structure (3D) model was generated, refined, and validated via computational methods. Besides, the strong protein-ligand interaction and stability between the vaccine candidate and toll-like receptor 4 (TLR4) were determined via molecular docking and dynamics analyses. Moreover, in silico cloning accompanied by pET-22b (+) was used to achieve high translation efficiency. Results: Our results presumed that the chimeric-designed vaccine was thermostable and contained optimal physicochemical properties. This vaccine candidate was nontoxic and highly soluble and had stable protein and TLR4 interaction, adequately overexpressed in Escherichia coli. Overall, it could induce immune responses and repress this microorganism. Conclusions: Therefore, to inhibit Pseudomonas infections experimentally, the efficacy and safety of the vaccine design need to be validated.

Protein conformational transitions explored by a morphing approach based on normal mode analysis in internal coordinates

Large-scale conformational changes are essential for proteins to function properly. Given that these transition events rarely occur, however, it is challenging to comprehend their underlying mechanisms through experimental and theoretical approaches. In this study, we propose a new computational methodology called internal coordinate normal mode-guided elastic network interpolation (ICONGENI) to predict conformational transition pathways in proteins. Its basic approach is to sample intermediate conformations by interpolating the interatomic distance between two end-point conformations with the degrees of freedom constrained by the low-frequency dynamics afforded by normal mode analysis in internal coordinates. For validation of ICONGENI, it is applied to proteins that undergo open-closed transitions, and the simulation results (i.e., simulated transition pathways) are compared with those of another technique, to demonstrate that ICONGENI can explore highly reliable pathways in terms of thermal and chemical stability. Furthermore, we generate an ensemble of transition pathways through ICONGENI and investigate the possibility of using this method to reveal the transition mechanisms even when there are unknown metastable states on rough energy landscapes.

In Silico Designing of a Multitope Vaccine against Rhizopus microsporus with Potential Activity against Other Mucormycosis Causing Fungi

During the current era of the COVID-19 pandemic, the dissemination of Mucorales has been reported globally, with elevated rates of infection in India, and because of the high rate of mortality and morbidity, designing an effective vaccine against mucormycosis is a major health priority, especially for immunocompromised patients. In the current study, we studied shared Mucorales proteins, which have been reported as virulence factors, and after analysis of several virulent proteins for their antigenicity and subcellular localization, we selected spore coat (CotH) and serine protease (SP) proteins as the targets of epitope mapping. The current study proposes a vaccine constructed based on top-ranking cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes from filtered proteins. In addition to the selected epitopes, β-defensins adjuvant and PADRE peptide were included in the constructed vaccine to improve the stimulated immune response. Computational tools were used to estimate the physicochemical and immunological features of the proposed vaccine and validate its binding with TLR-2, where the output data of these assessments potentiate the probability of the constructed vaccine to stimulate a specific immune response against mucormycosis. Here, we demonstrate the approach of potential vaccine construction and assessment through computational tools, and to the best of our knowledge, this is the first study of a proposed vaccine against mucormycosis based on the immunoinformatics approach.

In silico vaccine design and epitope mapping of New Delhi metallo-beta-lactamase (NDM): an immunoinformatics approach

BACKGROUND

Antibiotic resistance is a global health crisis. The adage that "prevention is better than cure" is especially true regarding antibiotic resistance because the resistance appears and spreads much faster than the production of new antibiotics. Vaccination is an important strategy to fight infectious agents; however, this strategy has not attracted sufficient attention in antibiotic resistance prevention. New Delhi metallo-beta-lactamase (NDM) confers resistance to many beta-lactamases, including important carbapenems like imipenem. Our goal in this study is to use an immunoinformatics approach to develop a vaccine that can elicit strong and specific immune responses against NDMs that prevent the development of antibiotic-resistant bacteria.

RESULTS

In this study, 2194 NDM sequences were aligned to obtain a conserved sequence. One continuous B cell epitope and three T cell CD4+ epitopes were selected from NDMs conserved sequence. Epitope conservancy for B cell and HLA-DR, HLA-DQ, and HLA-DP epitopes was 100.00%, 99.82%, 99.41%, and 99.86%, respectively, and population coverage of MHC II epitopes for the world was 99.91%. Permutation of the four epitope fragments resulted in 24 different peptides, of which 6 peptides were selected after toxicity, allergenicity, and antigenicity assessment. After primary vaccine design, only one vaccine sequence with the highest similarity with discontinuous B cell epitope in NDMs was selected. The final vaccine can bind to various Toll-like receptors (TLRs). The prediction implied that the vaccine would be stable with a good half-life. An immune simulation performed by the C-IMMSIM server predicted that two doses of vaccine injection can induce a strong immune response to NDMs. Finally, the GC-Content of the vaccine was designed very similar to E. coli K12.

CONCLUSIONS

In this study, immunoinformatics strategies were used to design a vaccine against different NDM variants that could produce an effective immune response against this antibiotic-resistant factor.

Neuroprotective derivatives of tacrine that target NMDA receptor and acetyl cholinesterase - Design, synthesis and biological evaluation

The complex and multifactorial nature of neuropsychiatric diseases demands multi-target drugs that can intervene with various sub-pathologies underlying disease progression. Targeting the impairments in cholinergic and glutamatergic neurotransmissions with small molecules has been suggested as one of the potential disease-modifying approaches for Alzheimer’s disease (AD). Tacrine, a potent inhibitor of acetylcholinesterase (AChE) is the first FDA approved drug for the treatment of AD. Tacrine is also a low affinity antagonist of N-methyl-D-aspartate receptor (NMDAR). However, tacrine was withdrawn from its clinical use later due to its hepatotoxicity. With an aim to develop novel high affinity multi-target directed ligands (MTDLs) against AChE and NMDAR, with reduced hepatotoxicity, we performed in silico structure-based modifications on tacrine, chemical synthesis of the derivatives and in vitro validation of their activities. Nineteen such derivatives showed inhibition with IC₅₀ values in the range of 18.53 ± 2.09 – 184.09 ± 19.23 nM against AChE and 0.27 ± 0.05 – 38.84 ± 9.64 μM against NMDAR. Some of the selected compounds also protected rat primary cortical neurons from glutamate induced excitotoxicity. Two of the tacrine derived MTDLs, 201 and 208 exhibited in vivo efficacy in rats by protecting against behavioral impairment induced by administration of the excitotoxic agent, monosodium glutamate. Additionally, several of these synthesized compounds also exhibited promising inhibitory activitiy against butyrylcholinesterase. MTDL-201 was also devoid of hepatotoxicity in vivo. Given the therapeutic potential of MTDLs in disease-modifying therapy, our studies revealed several promising MTDLs among which 201 appears to be a potential candidate for immediate preclinical evaluations.

Proteome Based Approach Defines Candidates for Designing a Multitope Vaccine against the Nipah Virus

Nipah virus is one of the most harmful emerging viruses with deadly effects on both humans and animals. Because of the severe outbreaks, in 2018, the World Health Organization focused on the urgent need for the development of effective solutions against the virus. However, up to date, there is no effective vaccine against the Nipah virus in the market. In the current study, the complete proteome of the Nipah virus (nine proteins) was analyzed for the antigenicity score and the virulence role of each protein, where we came up with fusion glycoprotein (F), glycoprotein (G), protein (V), and protein (W) as the candidates for epitope prediction. Following that, the multitope vaccine was designed based on top-ranking CTL, HTL, and BCL epitopes from the selected proteins. We used suitable linkers, adjuvant, and PADRE peptides to finalize the constructed vaccine, which was analyzed for its physicochemical features, antigenicity, toxicity, allergenicity, and solubility. The designed vaccine passed these assessments through computational analysis and, as a final step, we ran a docking analysis between the designed vaccine and TLR-³ and validated the docked complex through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for Nipah virus. Here, we describe the computational approach for design and analysis of this vaccine.

In-silico design of envelope based multi-epitope vaccine candidate against Kyasanur forest disease virus

Kyasanur forest disease virus (KFDV) causing tick-borne hemorrhagic fever which was earlier endemic to western Ghats, southern India, it is now encroaching into new geographic regions, but there is no approved medicine or effective vaccine against this deadly disease. In this study, we did in-silico design of multi-epitope subunit vaccine for KFDV. B-cell and T-cell epitopes were predicted from conserved regions of KFDV envelope protein and two vaccine candidates (VC1 and VC2) were constructed, those were found to be non-allergic and possess good antigenic properties, also gives cross-protection against Alkhurma hemorrhagic fever virus. The 3D structures of vaccine candidates were built and validated. Docking analysis of vaccine candidates with toll-like receptor-2 (TLR-2) by Cluspro and PatchDock revealed strong affinity between VC1 and TLR2. Ligplot tool was identified the intermolecular hydrogen bonds between vaccine candidates and TLR-2, iMOD server confirmed the stability of the docking complexes. JCAT sever ensured cloning efficiency of both vaccine constructs and in-silico cloning into pET30a (+) vector by SnapGene showed successful translation of epitope region. IMMSIM server was identified increased immunological responses. Finally, multi-epitope vaccine candidates were designed and validated their efficiency, it may pave the way for up-coming vaccine and diagnostic kit development.

Architecturally complex O-glycopeptidases are customized for mucin recognition and hydrolysis

A challenge faced by peptidases is the recognition of highly diverse substrates. A feature of some peptidase families is the capacity to specifically use post-translationally added glycans present on their protein substrates as a recognition determinant. This is ultimately critical to enabling peptide bond hydrolysis. This class of enzyme is also frequently large and architecturally sophisticated. However, the molecular details underpinning glycan recognition by these O-glycopeptidases, the importance of these interactions, and the functional roles of their ancillary domains remain unclear. Here, using the Clostridium perfringens ZmpA, ZmpB, and ZmpC M60 peptidases as model proteins, we provide structural and functional insight into how these intricate proteins recognize glycans as part of catalytic and noncatalytic substrate recognition. Structural, kinetic, and mutagenic analyses support the key role of glycan recognition within the M60 domain catalytic site, though they point to ZmpA as an apparently inactive enzyme. Wider examination of the Zmp domain content reveals noncatalytic carbohydrate binding as a feature of these proteins. The complete three-dimensional structure of ZmpB provides rare insight into the overall molecular organization of a highly multimodular enzyme and reveals how the interplay of individual domain function may influence biological activity. O-glycopeptidases frequently occur in host-adapted microbes that inhabit or attack mucus layers. Therefore, we anticipate that these results will be fundamental to informing more detailed models of how the glycoproteins that are abundant in mucus are destroyed as part of pathogenic processes or liberated as energy sources during normal commensal lifestyles.

In silico study the inhibition of angiotensin converting enzyme 2 receptor of COVID-19 by Ammoides verticillata components harvested from Western Algeria

The objective of this present study is to focus on the in silico study to screen for an alternative drug that can block the activity of the angiotensin converting enzyme 2 (ACE2) as a receptor for SARS-CoV-2, potential therapeutic target of the COVID-19 virus using natural compounds (Isothymol, Thymol, Limonene, P-cymene and γ-terpinene) derived from the essential oil of the antiviral and antimicrobial plant Ammoides verticillata (Desf.) Briq. which is located in the occidental Algeria areas. This study reveals that Isothymol, a major component of this plant, gives the best docking scores, compared to, the co-crystallized inhibitor β-D-mannose of the enzyme ACE2, to Captropil drug as good ACE2 inhibitor and to Chloroquine antiviral drug also involved in other mechanisms as inhibition of ACE2 cellular receptor. In silico (ADME), drug-likeness, PASS & P450 site of metabolism prediction, pharmacophore Mapper showed that the compound Isothymol has given a good tests results compared to the β-D-mannose co-crystallized inhibitor, to Captopril and Chloroquine drugs. Also the other natural compounds gave good results. The Molecular Dynamics Simulation study showed good result for the Isotymol- ACE2 docked complex. This study revealed for the first time that Isothymol is a functional inhibitor of angiotensin converting enzyme 2 activity and the components of essential oils Ammoides verticillata can be used as potential inhibitors to the ACE2 receptor of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Mining the Mycobacterium tuberculosis proteome for identification of potential T-cell epitope based vaccine candidates

Identification of protective antigens for designing a high-efficacy tuberculosis vaccine is the need of the hour. Till date only 7% of the Mycobacterium tuberculosis proteome has been explored for discovering antigens capable of activating T-cell responses. Therefore, it becomes crucial to screen the remaining Mycobacterium tuberculosis proteome for more immunodominant T-cell epitopes. An extensive knowledge of the epitopes recognized by our immune system can aid this process of finding potential T cell antigens for development of a better TB vaccine. In the present in-silico study, 237 proteins belonging to the 'virulence, detoxification, and adaptation' category of Mycobacterium tuberculosis proteome were targeted for T-cell epitope screening. 50825 MHC Class I and 49357 MHC Class II epitopes were generated using NetMHC3.4 and IEDB servers respectively and tested for their antigenicity and cytokine stimulation. The highest antigenic epitopes were analyzed for their world population coverage and epitope conservancy. Molecular docking and molecular dynamics simulation studies were performed to corroborate the binding affinities and structural stability of the peptide-MHC complexes. We predicted a total of 3 MHC Class I (ILLKMCWPA, FAVGMNVYV, and SLAGNSAKV) and 7 MHC Class II (DLTIGFFLHIPFPPV, RPDLTIGFFLHIPFP, LTIGFFLHIPFPPVE, VLVFALVVALVYLQF, LVFALVVALVYLQFR, PNLVAARFIQLTPVY, and LVLVFALVVALVYLQ) epitopes that can be promising vaccine candidates. These predicted epitopes belong to 6 distinct proteins: Rv0169 (mce1a), Rv3490 (ostA), Rv3496 (mce4D), Rv1085c, Rv0563 (HtpX), Rv3497c (mce4C). All these proteins are expressed at different stages in the life cycle of Mycobacterium tuberculosis and thus, the predicted epitopes could be employed as candidates for designing a multistage-multiepitopic vaccine.

Structural Analysis of the Polymerase Protein for Multiepitopes Vaccine Prediction against Hepatitis B Virus

Hepatitis B virus (HBV) is the most common cause of hepatocellular carcinoma and liver cirrhosis with significant morbidity and mortality worldwide. DNA polymerase protein of HBV is the immunogenic protein inducing immune response against B and T cells. The aim of this study wasto develop multi-epitope vaccine fromthe polymerase protein elicitingimmune responses.The predicted vaccine comprises epitopes against B and T lymphocytesobtained by IEDB server. The predicted epitopes were linked via suitable spacers (linkers). The 50S ribosomal protein L7/L12 was used as an adjuvant at amino terminal and His-tag at the carboxyl terminal of the vaccine construct. The candidate vaccine contains 457aa and was potentially antigenic and nonallergic. Vaccine molecular weightwas 50.03 KDa with pI of 10.04. The instability index was 25.78 and GRAVY was -0.354 indicating stability andhydrophilicity of the chimeric vaccine,respectively.Vaccine structure (Secondary and tertiary structures) were predicted, refined and used for molecular docking with TLR4.The docking with TLR4 provided energy scores of -1458.7 and -1410.3 for chain A and B, respectively, demonstrated strong binding between the chimeric vaccine and TLR4 chains.The vaccine provided favorable solubility compared to E. coli proteins. Stability via disulfide bonds engineering was predicted to reduce the entropy and mobility regions invaccine construct. Molecular dynamics simulation wasperformed to strengthen the prediction. In silicomolecular cloning was usedto guarantee the efficient clonabilityof the vaccine and translation within suitable vector.

HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps

In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches. We present HOPMA, a novel method to predict protein functional states and transitions by using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures. The method is computationally efficient and available at https://github.com/elolaine/HOPMA and https://team.inria.fr/nano-d/software/nolb-normal-modes.

Potential inhibitors of angiotensin converting enzyme 2 receptor of COVID-19 by Corchorus olitorius Linn using docking, molecular dynamics, conceptual DFT investigation and pharmacophore mapping

A novel coronavirus, previously designated 2019-nCoV, was identified as the cause of a cluster of pneumonia cases in Wuhan, a city in the Hubei Province of China, at the end of 2019. Our objective focuses on the in silico study to screen for an alternative drug that can block the activity of the angiotensin converting enzyme 2 (ACE2), which is a key protein in the physiology of Covid-19, necessary for the entry of the SARS-Cov-2 virus into the host's cells using natural compounds especially phenolic antioxidants, polyphenolics and pharmaceutically phytochemicals derived from the leaves of Corchorus olitorius Linn, appear to be very potential in controlling virus-induced infection. The results of the docking simulation revealed that méthyl-1,4,5-tri-O-caféoyl quinate has a stronger bond, high affinity and gives the best docking scores compared to, the co-crystallized inhibitor (PRD_002214) of the enzyme ACE2, chloroquine, hydroxychloroquine, captopril and simerprevir antiviral drugs. The ADMET properties, Pharmacokinetics and Medicinal Chemistry & P450 site of metabolism prediction, pharmacophore Mapper enzyme revealed that the compound méthyl-1,4,5-tri-O-caféoyl quinate generates a hypothesis which can be applied successfully in biological screening for further experiments. The novel MD computational technique study showed better conformational movements result for the méthyl-1,4,5-tri-O-caféoyl quinate-ACE2 docked complex. Therefore méthyl-1,4,5-tri-O-caféoyl quinate may be considered to be potential inhibitor of the main protease enzyme of virus, but need to be investigated in vivo and in vitro for further drug development process.Communicated by Ramaswamy H. Sarma.

The Dynamic Influence of Linker Histone Saturation within the Poly-Nucleosome Array

Linker histones bind to nucleosomes and modify chromatin structure and dynamics as a means of epigenetic regulation. Biophysical studies have shown that chromatin fibers can adopt a plethora of conformations with varying levels of compaction. Linker histone condensation, and its specific binding disposition, has been associated with directly tuning this ensemble of states. However, the atomistic dynamics and quantification of this mechanism remains poorly understood. Here, we present molecular dynamics simulations of octa-nucleosome arrays, based on a cryo-EM structure of the 30-nm chromatin fiber, with and without the globular domains of the H1 linker histone to determine how they influence fiber structures and dynamics. Results show that when bound, linker histones inhibit DNA flexibility and stabilize repeating tetra-nucleosomal units, giving rise to increased chromatin compaction. Furthermore, upon the removal of H1, there is a significant destabilization of this compact structure as the fiber adopts less strained and untwisted states. Interestingly, linker DNA sampling in the octa-nucleosome is exaggerated compared to its mono-nucleosome counterparts, suggesting that chromatin architecture plays a significant role in DNA strain even in the absence of linker histones. Moreover, H1-bound states are shown to have increased stiffness within tetra-nucleosomes, but not between them. This increased stiffness leads to stronger long-range correlations within the fiber, which may result in the propagation of epigenetic signals over longer spatial ranges. These simulations highlight the effects of linker histone binding on the internal dynamics and global structure of poly-nucleosome arrays, while providing physical insight into a mechanism of chromatin compaction.

Structural Analysis of Avian Encephalomyelitis Virus Polyprotein for Development of Multi Epitopes Vaccine Using Immunoinformatics Approach

Avian Encephalomyelitis (AE) is the disease caused by avian encephalomyelitis virus (AEV). The disease mainly affects young birds nervous system worldwide causing high morbidity and variable mortality rate in chicks and noticed egg dropping and hatchability in mature hens. Vaccination is the only way to control AEV infection since there is no treatment yet to the avian encephalomyelitis. This study aimed to use immunoinformatics approaches to predict multi epitopes vaccine from the AEV polyprotein that could elicit both B and T cells. The vaccine construct comprises 482 amino acids obtained from epitopes predicted against B and T cells by IEDB server, adjuvant, linkers and 6-His-tag. The chimeric vaccine was potentially antigenic and nonallergic and demonstrated thermostability and hydrophilicity in protparam server. The solubility of the vaccine was measured in comparison to E. coli proteins. The stability was also assessed by disulfide bonds engineering to reduce the high mobility regions in the designed vaccine. Furthermore molecular dynamics simulation further strengthen stability of the predicted vaccine. Tertiary structure of the vaccine construct after prediction, refinement was used for molecular docking with chicken alleles BF2*2101 and BF2*0401 and the docking process demonstrated favourable binding energy score of -337.47 kcal/mol and -326.87 kcal/mol, respectively. Molecular cloning demonstrated the potential clonability of the chimeric vaccine in pET28a(+) vector. This could guarantee the efficient translation and expression of the vaccine within suitable expression vector.

In silico design of enzyme α-amylase and α-glucosidase inhibitors using molecular docking, molecular dynamic, conceptual DFT investigation and pharmacophore modelling

Type 2 diabetes mellitus (T2DM) is characterized by elevated blood glucose levels and can lead to serious complications such as nephropathy, neuropathy, retinopathy and cardiovascular disease. The aim of this work is to identify and investigate the inhibition mechanism of natural flavonoids and phenolics acids against, the α-amylase (αA) and α-glucosidase (αG). Therefore, we used different approaches; such as conceptual DFT and pharmacophore mapping in addition to molecular mechanics, dynamics and docking simulations. Whereas, a close agreement was found out to decide that Linarin (Flavones) provides more optimized inhibition of αA and αG enzymes. Our results have shown that Linarin could be useful as preventative agent, and possibly therapeutic modality for the treatment of metabolic diseases.Communicated by Ramaswamy H. Sarma.

In silico analysis of epitope-based vaccine candidate against tuberculosis using reverse vaccinology

Tuberculosis (TB) kills more individuals in the world than any other disease, and a threat made direr by the coverage of drug-resistant strains of Mycobacterium tuberculosis (Mtb). Bacillus Calmette-Guérin (BCG) is the single TB vaccine licensed for use in human beings and effectively protects infants and children against severe military and meningeal TB. We applied advanced computational techniques to develop a universal TB vaccine. In the current study, we select the very conserved, experimentally confirmed Mtb antigens, including Rv2608, Rv2684, Rv3804c (Ag85A), and Rv0125 (Mtb32A) to design a novel multi-epitope subunit vaccine. By using the Immune Epitopes Database (IEDB), we predicted different B-cell and T-cell epitopes. An adjuvant (Griselimycin) was also added to vaccine construct to improve its immunogenicity. Bioinformatics tools were used to predict, refined, and validate the 3D structure and then docked with toll-like-receptor (TLR-3) using different servers. The constructed vaccine was used for further processing based on allergenicity, antigenicity, solubility, different physiochemical properties, and molecular docking scores. The in silico immune simulation results showed significant response for immune cells. For successful expression of the vaccine in E. coli, in-silico cloning and codon optimization were performed. This research also sets out a good signal for the design of a peptide-based tuberculosis vaccine. In conclusion, our findings show that the known multi-epitope vaccine may activate humoral and cellular immune responses and maybe a possible tuberculosis vaccine candidate. Therefore, more experimental validations should be exposed to it.

Ex vivo binding studies of the anti-cancer drug noscapine with human hemoglobin: a spectroscopic and molecular docking study

Noscapine binds human hemoglobin spontaneously forming a stable complex that affects noscapine's ADMET profile, bioavailability and toxicity.

A comprehensive screening of the whole proteome of hantavirus and designing a multi-epitope subunit vaccine for cross-protection against hantavirus: Structural vaccinology and immunoinformatics study

Hantaviruses are an emerging zoonotic group of rodent-borne viruses that are having serious implications on global public health due to the increase in outbreaks. Since there is no permanent cure, there is increasing interest in developing a vaccine against the hantavirus. This research aimed to design a robust cross-protective subunit vaccine using a novel immunoinformatics approach. After careful evaluation, the best predicted cytotoxic & helper T-cell and B-cell epitopes from nucleocapsid proteins, glycoproteins, RdRp proteins, and non-structural proteins were considered as potential vaccine candidates. Among the four generated vaccine models with different adjuvant, the model with toll-like receptor-4 (TLR-4) agonist adjuvant was selected because of its high antigenicity, non-allergenicity, and structural quality. The selected model was 654 amino acids long and had a molecular weight of 70.5 kDa, which characterizes the construct as a good antigenic vaccine candidate. The prediction of the conformational B-lymphocyte (CBL) epitope secured its ability to induce the humoral response. Thereafter, disulfide engineering improved vaccine stability. Afterwards, the molecular docking confirmed a good binding affinity of -1292 kj/mol with considered immune receptor TLR-4 and the dynamics simulation showed high stability of the vaccine-receptor complex. Later, the in silico cloning confirmed the better expression of the constructed vaccine protein in E. coli K12. Finally, in in silico immune simulation, significantly high levels of immunoglobulin M (IgM), immunoglobulin G1 (IgG1), cytotoxic & helper T lymphocyte (CTL & HTL) populations, and numerous cytokines such as interferon-γ (IFN-γ), interleukin-2 (IL-2) etc. were found as coherence with actual immune response and also showed faster antigen clearance for repeated exposures. Nonetheless, experimental validation can demonstrate the safety and cross-protective ability of the proposed vaccine to fight against hantavirus infection.

Increasing the Sampling Efficiency of Protein Conformational Change by Combining a Modified Replica Exchange Molecular Dynamics and Normal Mode Analysis

Understanding conformational change at an atomic level is significant when determining a protein functional mechanism. Replica exchange molecular dynamics (REMD) is a widely used enhanced sampling method to explore protein conformational space. However, REMD with an explicit solvent model requires huge computational resources, immensely limiting its application. In this study, a variation of parallel tempering metadynamics (PTMetaD) with the omission of solvent-solvent interactions in exchange attempts and the use of low-frequency modes calculated by normal-mode analysis (NMA) as collective variables (CVs), namely ossPTMetaD, is proposed with the aim to accelerate MD simulations simultaneously in temperature and geometrical spaces. For testing the performance of ossPTMetaD, five protein systems with diverse biological functions and motion patterns were selected, including large-scale domain motion (AdK), flap movement (HIV-1 protease and BACE1), and DFG-motif flip in kinases (p38α and c-Abl). The simulation results showed that ossPTMetaD requires much fewer numbers of replicas than temperature REMD (T-REMD) with a reduction of ∼70% to achieve a similar exchange ratio. Although it does not obey the detailed balance condition, ossPTMetaD provides consistent results with T-REMD and experimental data. The high accessibility of the large conformational change of protein systems by ossPTMetaD, especially in simulating the very challenging DFG-motif flip of protein kinases, demonstrated its high efficiency and robustness in the characterization of the large-scale protein conformational change pathway and associated free energy profile.

Design and optimization of a subunit vaccine targeting COVID-19 molecular shreds using an immunoinformatics framework

COVID-19 has been declared as a global health emergency and exposed the world to a deadly virus, which has dramatically changed the lives of humans for an unknown period of time. In the battleground with the virus, we have employed an immunoinformatics framework to design a robust vaccine as an insurance plan for the future. The pathogenic sequence with cryptic epitope taken from patients in Wuhan, China, was harnessed to design a promiscuous cytotoxic T-lymphocyte, helper T-lymphocyte, and B-cell epitope based subunit vaccine, engineered with adjuvants and conformational linkers. The reported vaccine has high antigenicity and immunogenicity profiles with potential TAP affinity, which ensures elevated antigen processing capability. It has strong binding with major histocompatibility complex (MHC) receptors (MHC-1 and MHC-2) and virus-specific membrane receptor TLR-2, with scores of -1010.7, -1035.7, and -1076.3 kcal mol-1, respectively. Molecular dynamics simulation analysis was used to assess the stable binding with TLR-2 with minimal atomic motions through a deformation plot, covariance matrix, and elastic network. Importantly, an in silico immunization assay showed the reliable elicitation of key players in terms of immune cells together with memory cells to evoke adaptive immune responses upon administration of the construct. In view of favorable outcomes, we also propose a plausible vaccine mechanism to elicit an immune response to fight coronavirus.

Discovery of potential immune epitopes and peptide vaccine design - a prophylactic strategy against Rift Valley fever virus

Background: Rift Valley fever virus (RVFV) is an emerging arbovirus infecting both animals and humans. Any form of direct contact with body fluids, blood or tissue of infected animals is the mode of transmission of this pathogen. Despite being an emerging virus, no proper vaccinations are yet available for the public. Our objective is to compose a multiepitope vaccine utilizing immuno-bioinformatics as a strategy against RVFV. Methods: To identify immunodominant epitopes and design a potent vaccine candidate, we applied a series of immunoinformatic approaches with molecular dynamics and immune response simulation frameworks. Results: A glycoprotein with the highest antigenicity was selected and employed for determining promising epitopes. We selected T cell epitopes based on their immunological potencies and cytokine inducing properties, while B cell epitopes were selected based on their antigenic features. Finally, we selected four cytotoxic T-lymphocyte, two helper T-lymphocyte, and three linear B-lymphocyte epitopes that were arranged into a vaccine construct with appropriate adjuvants and linkers. The chimera protein was modeled, refined, and validated prior to docking against toll-like receptor 4. Docking studies suggest strong binding interactions while dynamics simulation revealed the stable nature of the docked complex. Furthermore, the immune simulation showed robust and prolonged immune responses with rapid antigen clearance. Finally, codon optimization and cloning conducted with Escherichia coli K12 suggests high translation efficiency within the host system. Conclusion: We believe that our designed multiepitope vaccine is a promising prophylactic candidate against RVFV pathogenesis.

Network analysis, sequence and structure dynamics of key proteins of coronavirus and human host, and molecular docking of selected phytochemicals of nine medicinal plants

The novel coronavirus of 2019 (nCoV-19) has become a pandemic, affecting over 205 nations with over 7,410,000 confirmed cases which has resulted to over 418,000 deaths worldwide. This study aimed to identify potential therapeutic compounds and phytochemicals of medicinal plants that have potential to modulate the expression network of genes that are involve in SARS-CoV-2 pathology in human host and to understand the dynamics key proteins involved in the virus-host interactions. The method used include gene network analysis, molecular docking, and sequence and structure dynamics simulations. The results identified DNA-dependent protein kinase (DNA-PK) and Protein kinase CK2 as key players in SARS-CoV-2 lifecycle. Among the predicted drugs compounds, clemizole, monorden, spironolactone and tanespimycin showed high binding energies; among the studied repurposing compounds, remdesivir, simeprevir and valinomycin showed high binding energies; among the predicted acidic compounds, acetylursolic acid and hardwickiic acid gave high binding energies; while among the studied anthraquinones and glycosides compounds, ellagitannin and friedelanone showed high binding energies against 3-Chymotrypsin-like protease (3CL^pro), Papain-like protease (PL^pro), helicase (nsp13), RNA-dependent RNA polymerase (nsp12), 2'-O-ribose methyltransferase (nsp16) of SARS-CoV-2 and DNA-PK and CK2alpha in human. The order of affinity for CoV proteins is 5Y3E > 6NUS > 6JYT > 2XYR > 3VB6. Finally, medicinal plants with phytochemicals such as caffeine, ellagic acid, quercetin and their derivatives could possibly remediate COVID-19.Communicated by Ramaswamy H. Sarma.

Elucidating the influence of linker histone variants on chromatosome dynamics and energetics

Linker histones are epigenetic regulators that bind to nucleosomes and alter chromatin structures and dynamics. Biophysical studies have revealed two binding modes in the linker histone/nucleosome complex, the chromatosome, where the linker histone is either centered on or askew from the dyad axis. Each has been posited to have distinct effects on chromatin, however the molecular and thermodynamic mechanisms that drive them and their dependence on linker histone compositions remain poorly understood. We present molecular dynamics simulations of chromatosomes with the globular domain of two linker histone variants, generic H1 (genGH1) and H1.0 (GH1.0), to determine how their differences influence chromatosome structures, energetics and dynamics. Results show that both unbound linker histones adopt a single compact conformation. Upon binding, DNA flexibility is reduced, resulting in increased chromatosome compaction. While both variants enthalpically favor on-dyad binding, energetic benefits are significantly higher for GH1.0, suggesting that GH1.0 is more capable than genGH1 of overcoming the large entropic reduction required for on-dyad binding which helps rationalize experiments that have consistently demonstrated GH1.0 in on-dyad states but that show genGH1 in both locations. These simulations highlight the thermodynamic basis for different linker histone binding motifs, and details their physical and chemical effects on chromatosomes.

Shape-preserving elastic solid models of macromolecules

Mass-spring models have been a standard approach in molecular modeling for the last few decades, such as elastic network models (ENMs) that are widely used for normal mode analysis. In this work, we present a vastly different elastic solid model (ESM) of macromolecules that shares the same simplicity and efficiency as ENMs in producing the equilibrium dynamics and moreover, offers some significant new features that may greatly benefit the research community. ESM is different from ENM in that it treats macromolecules as elastic solids. Our particular version of ESM presented in this work, named αESM, captures the shape of a given biomolecule most economically using alpha shape, a well-established technique from the computational geometry community. Consequently, it can produce most economical coarse-grained models while faithfully preserving the shape and thus makes normal mode computations and visualization of extremely large complexes more manageable. Secondly, as a solid model, ESM’s close link to finite element analysis renders it ideally suited for studying mechanical responses of macromolecules under external force. Lastly, we show that ESM can be applied also to structures without atomic coordinates such as those from cryo-electron microscopy. The complete MATLAB code of αESM is provided.

Mass-spring models have been a standard approach in classical molecular modeling where atoms are modeled as spheres with a mass and their interactions modeled as springs. The models have been extremely successful. Thinking ahead, however, as molecular systems of our interest grow more quickly in size or dimension than what our computation resources can keep up with, some adjustments in methodology are timely. This work presents a vastly different elastic solid model (ESM) of macromolecules that shares the same simplicity and efficiency as mass-spring models in producing the equilibrium dynamics and moreover, offers some unique features that make it suitable for much larger systems. ESM is different from ENMs in that it treats macromolecules as elastic solids. Our particular version of ESM model presented in this work, named αESM, captures the shape of a given biomolecule most economically using alpha shape, a well-established technique from the computational geometry community. Consequently, it can produce most economical coarse-grained models while faithfully preserving the shape. ESM can be applied also to structures without atomic coordinates such as those from cryo-electron microscopy.

Immunoinformatics-guided designing of epitope-based subunit vaccines against the SARS Coronavirus-2 (SARS-CoV-2)

SARS Coronavirus-2 (SARS-CoV-2) pandemic has become a global issue which has raised the concern of scientific community to design and discover a counter-measure against this deadly virus. So far, the pandemic has caused the death of hundreds of thousands of people upon infection and spreading. To date, no effective vaccine is available which can combat the infection caused by this virus. Therefore, this study was conducted to design possible epitope-based subunit vaccines against the SARS-CoV-2 virus using the approaches of reverse vaccinology and immunoinformatics. Upon continual computational experimentation, three possible vaccine constructs were designed and one vaccine construct was selected as the best vaccine based on molecular docking study which is supposed to effectively act against the SARS-CoV-2. Thereafter, the molecular dynamics simulation and in silico codon adaptation experiments were carried out in order to check biological stability and find effective mass production strategy of the selected vaccine. This study should contribute to uphold the present efforts of the researches to secure a definitive preventative measure against this lethal disease.

Exploiting the reverse vaccinology approach to design novel subunit vaccines against Ebola virus

Ebola virus is a highly pathogenic RNA virus that causes the Ebola haemorrhagic fever in human. This virus is considered as one of the dangerous viruses in the world with very high mortality rate. To date, no epitope-based subunit vaccine has yet been discovered to fight against Ebola although the outbreaks of this deadly virus took many lives in the past. In this study, approaches of reverse vaccinology were utilized in combination with different tools of immunoinformatics to design subunit vaccines against Ebola virus strain Mayinga-76. Three potential antigenic proteins of this virus i.e., matrix protein VP40, envelope glycoprotein and nucleoprotein were selected to construct the subunit vaccine. The MHC class-I, MHC class-II and B-cell epitopes were determined initially and after some robust analysis i.e., antigenicity, allergenicity, toxicity, conservancy and molecular docking study, EV-1, EV-2 and EV-3 were constructed as three potential vaccine constructs. These vaccine constructs are also expected to be effective on few other strains of Ebola virus since the highly conserved epitopes were used for vaccine construction. Thereafter, molecular docking study was conducted on these vaccines and EV-1 emerged as the best vaccine construct. Afterward, molecular dynamics simulation study revealed the good performances and stability of the intended vaccine protein. Finally, codon adaptation and in silico cloning were carried out to design a possible plasmid (pET-19b plasmid vector was used) for large scale production of the EV-1 vaccine. However, further in vitro and in vivo studies might be required on the predicted vaccines for final validation.

Predicting Protein Functional Motions: an Old Recipe with a New Twist

Large macromolecules, including proteins and their complexes, very often adopt multiple conformations. Some of them can be seen experimentally, for example with x-ray crystallography or cryo-electron microscopy. This structural heterogeneity is not occasional and is frequently linked with specific biological function. Thus, the accurate description of macromolecular conformational transitions is crucial for understanding fundamental mechanisms of life's machinery. We report on a real-time method to predict such transitions by extrapolating from instantaneous eigen motions, computed using the normal mode analysis, to a series of twists. We demonstrate the applicability of our approach to the prediction of a wide range of motions, including large collective opening-closing transitions and conformational changes induced by partner binding. We also highlight particularly difficult cases of very small transitions between crystal and solution structures. Our method guarantees preservation of the protein structure during the transition and allows accessing conformations that are unreachable with classical normal mode analysis. We provide practical solutions to describe localized motions with a few low-frequency modes and to relax some geometrical constraints along the predicted transitions. This work opens the way to the systematic description of protein motions, whatever their degree of collectivity. Our method is freely available as a part of the NOn-Linear rigid Block (NOLB) package.

Privileged Scaffold Chalcone: Synthesis, Characterization and Its Mechanistic Interaction Studies with BSA Employing Spectroscopic and Chemoinformatics Approaches

Chalcone, a privileged structure, is considered as an effective template in the field of medicinal chemistry for potent drug discovery. In the present study, a privileged template chalcone was designed, synthesized, and characterized by various spectroscopic techniques (NMR, high-resolution mass spectrometry, Fourier transform infrared (FT-IR) spectroscopy, UV spectroscopy, and single-crystal X-ray diffraction). The mechanism of binding of chalcone with bovine serum albumin (BSA) was determined by multispectroscopic techniques and computational methods. Steady-state fluorescence spectroscopy suggests that the intrinsic fluorescence of BSA was quenched upon the addition of chalcone by the combined dynamic and static quenching mechanism. Time-resolved spectroscopy confirms complex formation. FT-IR and circular dichroism spectroscopy suggested the presence of chalcone in the BSA molecule microenvironment and also the possibility of rearrangement of the native structure of BSA. Moreover, molecular docking studies confirm the moderate binding of chalcone with BSA and the molecular dynamics simulation analysis shows the stability of the BSA-drug complex system with minimal deformability fluctuations and potential interaction by the covariance matrix. Moreover, pharmacodynamics and pharmacological analysis show good results through Lipinski rules, with no toxicity profile and high gastrointestinal absorptions by boiled egg permeation assays. This study elucidates the mechanistic profile of the privileged chalcone scaffold to be used in therapeutic applications.

Multiepitope Subunit Vaccine to Evoke Immune Response against Acute Encephalitis

Acute encephalitis syndrome outbreak has emerged as a major health concern on both national and international scales. Brain inflammation/infections caused by Japanese encephalitis virus (JEV) can lead to death. The cases are growing in numbers globally, and this emergent health concern requires an effective and viable vaccine to strengthen the body's immune system against this deadly virus. Proteomic analyses of JEV revealed the envelope protein as a potential target for vaccine development by patient samples analysis. Hence, in this study, we aimed to design a multiepitope subunit vaccine for acute encephalitis using the advanced structural biology and immunoinformatics approaches. We report the multiepitope subunit vaccine consisted of the putative T-cell epitope (MHC-1 and MHC-2 restricted) and B-cell epitope and with high antigenicity and immunogenicity. The TAP affinity epitopes along with adjuvants were engineered to the vaccine, to ensure the ease transportation inside the host and elicitation of a strong immune response. The specificity of vaccine construct was evaluated by molecular docking with major histocompatibility complex (MHC) receptors and host membrane receptor TLR2. High docking scores and a close interaction to the binding groove of receptors confirmed the potency and specificity of the vaccine. Also, molecular dynamics simulation studies confirmed the stable interaction of vaccine with TLR2 for a long run (100 ns), which showed the prolonged elicitation of the strong immune response. Peptide dynamics studies showed the flexible, strong, and stable binding of vaccine with minimal deviation in root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and secondary structure estimation (SSE) plots till 100 ns simulation run. The in silico immune simulation approach based on the position-specific scoring matrix and machine learning methods resulted in the strong immune response reinforcement statistics of immune cells (T-cells, B-cells population, and memory cells) in response to vaccine candidate. The favorable results and well-correlated data of varied in silico techniques paved for a potent multiepitope vaccine and helped us to propose the mechanism of action of designed vaccine and generation of the immune response against acute encephalitis syndrome.

Multiepitope Subunit Vaccine Design against COVID-19 Based on the Spike Protein of SARS-CoV-2: An In Silico Analysis

The global health crisis caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of COVID-19, has resulted in a negative impact on human health and on social and economic activities worldwide. Researchers around the globe need to design and develop successful therapeutics as well as vaccines against the novel COVID-19 disease. In the present study, we conducted comprehensive computer-assisted analysis on the spike glycoprotein of SARS-CoV-2 in order to design a safe and potent multiepitope vaccine. In silico epitope prioritization shortlisted six HLA I epitopes and six B-cell-derived HLA II epitopes. These high-ranked epitopes were all connected to each other via flexible GPGPG linkers, and at the N-terminus side, the sequence of Cholera Toxin β subunit was attached via an EAAAK linker. Structural modeling of the vaccine was performed, and molecular docking analysis strongly suggested a positive association of a multiepitope vaccine with Toll-like Receptor 3. The structural investigations of the vaccine-TLR3 complex revealed the formation of fifteen interchain hydrogen bonds, thus validating its integrity and stability. Moreover, it was found that this interaction was thermodynamically feasible. In conclusion, our data supports the proposition that a multiepitope vaccine will provide protective immunity against COVID-19. However, further in vivo and in vitro experiments are needed to validate the immunogenicity and safety of the candidate vaccine.

Transferrin receptor binds virus capsid with dynamic motion

Canine parvovirus (CPV) is an important pathogen causing severe diseases in dogs, including acute hemorrhagic enteritis, myocarditis, and cerebellar disease. Cross-species transmission of CPV occurs as a result of mutations on the viral capsid surface that alter the species-specific binding to the host receptor, transferrin receptor type-1 (TfR). The interaction between CPV and TfR has been extensively studied, and previous analyses have suggested that the CPV-TfR complex is asymmetric. To enhance the understanding of the underlying molecular mechanisms, we determined the CPV-TfR interaction using cryo-electron microscopy to solve the icosahedral (3.0-Å resolution) and asymmetric (5.0-Å resolution) complex structures. Structural analyses revealed conformational variations of the TfR molecules relative to the binding site, which translated into dynamic molecular interactions between CPV and TfR. The precise footprint of the receptor on the virus capsid was identified, along with the identity of the amino acid residues in the virus-receptor interface. Our "rock-and-roll" model provides an explanation for previous findings and gives insights into species jumping and the variation in host ranges associated with new pandemics in dogs.

Normal Mode Analysis as a Routine Part of a Structural Investigation

Normal mode analysis (NMA) is a technique that can be used to describe the flexible states accessible to a protein about an equilibrium position. These states have been shown repeatedly to have functional significance. NMA is probably the least computationally expensive method for studying the dynamics of macromolecules, and advances in computer technology and algorithms for calculating normal modes over the last 20 years have made it nearly trivial for all but the largest systems. Despite this, it is still uncommon for NMA to be used as a component of the analysis of a structural study. In this review, we will describe NMA, outline its advantages and limitations, explain what can and cannot be learned from it, and address some criticisms and concerns that have been voiced about it. We will then review the most commonly used techniques for reducing the computational cost of this method and identify the web services making use of these methods. We will illustrate several of their possible uses with recent examples from the literature. We conclude by recommending that NMA become one of the standard tools employed in any structural study.

Contriving a chimeric polyvalent vaccine to prevent infections caused by herpes simplex virus (type-1 and type-2): an exploratory immunoinformatic approach

Herpes simplex virus type 1 (HSV-1) and 2 (HSV-2) cause a variety of infections including oral-facial infections, genital herpes, herpes keratitis, cutaneous infection and so on. To date, FDA-approved licensed HSV vaccine is not available yet. Hence, the study was conducted to identify and characterize an effective epitope based polyvalent vaccine against both types of Herpes Simplex Virus. The selected proteins were retrieved from ViralZone and assessed to design highly antigenic epitopes by binding analyses of the peptides with MHC class-I and class-II molecules, antigenicity screening, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach. The final vaccine was constructed by the combination of top CTL, HTL and BCL epitopes from each protein along with suitable adjuvant and linkers. Physicochemical and secondary structure analysis, disulfide engineering, molecular dynamic simulation and codon adaptation were further employed to develop a unique multi-epitope peptide vaccine. Docking analysis of the refined vaccine structure with different MHC molecules and human immune TLR-2 receptor demonstrated higher interaction. Complexed structure of the modeled vaccine and TLR-2 showed minimal deformability at molecular level. Moreover, translational potency and microbial expression of the modeled vaccine was analyzed with pET28a(+) vector for E. coli strain K12 and the vaccine constructs had no similarity with entire human proteome. The study enabled design of a novel chimeric polyvalent vaccine to confer broad range immunity against both HSV serotypes. However, further wet lab based research using model animals are highly recommended to experimentally validate our findings.Communicated by Ramaswamy H. Sarma.

DynOmics: dynamics of structural proteome and beyond

DynOmics (dynomics.pitt.edu) is a portal developed to leverage rapidly growing structural proteomics data by efficiently and accurately evaluating the dynamics of structurally resolved systems, from individual molecules to large complexes and assemblies, in the context of their physiological environment. At the core of the portal is a newly developed server, ENM 1.0, which permits users to efficiently generate information on the collective dynamics of any structure in PDB format, user-uploaded or database-retrieved. ENM 1.0 integrates two widely used elastic network models (ENMs)—the Gaussian Network Model (GNM) and the Anisotropic Network Model (ANM), extended to take account of molecular environment. It enables users to assess potentially functional sites, signal transduction or allosteric communication mechanisms, and protein–protein and protein–DNA interaction poses, in addition to delivering ensembles of accessible conformers reconstructed at atomic details based on the global modes of motions predicted by the ANM. The ‘environment’ is defined in a flexible manner, from lipid bilayer and crystal contacts, to substrate or ligands bound to a protein, or surrounding subunits in a multimeric structure or assembly. User-friendly interactive features permit users to easily visualize how the environment alter the intrinsic dynamics of the query systems. ENM 1.0 can be accessed at http://enm.pitt.edu/ or http://dyn.life.nthu.edu.tw/oENM/.

Ligand binding effects on the activation of the EGFR extracellular domain

The epidermal growth factor receptor (EGFR) is one of the most common target proteins in anti-cancer therapy. The binding of the EGF ligand to the EGFR extracellular domain (EGFR-ECD) promotes its inactive-to-active conformational transition (activation) but the relevant detailed mechanism remains elusive still. Here, the structural characterization and energetics of the EGFR-ECD conformational transition with and without the binding of the EGF are quantitatively explored using an innovative enhanced sampling MD simulation method. Intriguingly, the EGF offers hydrophobic interactions (e.g., EGF residues of Tyr44 and Leu47) and electrostatic interactions (e.g., the EGF residues of Glu5, Asp11, Asp17, and Arg41) to play a dominant role in dragging domain III to close the ligand binding domain gap. Subsequently, the correlation between domains III and II is enhanced through salt-bridges among Glu376, Arg403, and Arg405 from domain III and Glu293, Glu295, and Arg300 from domain II. Finally, the structural bending of domain II is regulated to facilitate the disengagement of domain II from domain IV. In this regard, the functional conformational transition of EGFR-ECD is a consequence of the cooperative motion of protein domains driven by the EGF ligand binding. The present study shows a detailed scenario of the EGF induced activation of EGFR-ECD and provides valuable information for drug discovery targeting the EGFR.

Conformational plasticity of the VEEV macro domain is important for binding of ADP-ribose

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ADPr’s binding triggers conformational changes to the whole VEEV macro domain.

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High flexibility of the loops β5-α3 and α3-β6 assist the ADPr’s binding.

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Loops around ADPr site undergo a transition pathway between apo and complex state.

Venezuelan equine encephalitis virus (VEEV) is a new world alphavirus which can be involved in several central nervous system disorders such as encephalitis and meningitis. The VEEV genome codes for 4 non-structural proteins (nsP), of which nsP3 contains a Macro domain. Macro domains (MD) can be found as stand-alone proteins or embedded within larger proteins in viruses, bacteria and eukaryotes. Their most common feature is the binding of ADP-ribose (ADPr), while several macro domains act as ribosylation writers, erasers or readers. Alphavirus MD erase ribosylation but their precise contribution in viral replication is still under investigation. NMR-driven titration experiments of ADPr in solution with the VEEV macro domain (in apo- and complex state) show that it adopts a suitable conformation for ADPr binding. Specific experiments indicate that the flexibility of the loops β5-α3 and α3-β6 is critical for formation of the complex and assists a wrapping mechanism for ADPr binding. Furthermore, along with this sequence of events, the VEEV MD undergoes a conformational exchange process between the apo state and a low-populated “dark” conformational state.

Reverse vaccinology approach to design a novel multi-epitope subunit vaccine against avian influenza A (H7N9) virus

H7N9, a novel strain of avian origin influenza was the first recorded incidence where a human was transited by a N9 type influenza virus. Effective vaccination against influenza A (H7N9) is a major concern, since it has emerged as a life threatening viral pathogen. Here, an in silico reverse vaccinology strategy was adopted to design a unique chimeric subunit vaccine against avian influenza A (H7N9). Induction of humoral and cell-mediated immunity is the prime concerned characteristics for a peptide vaccine candidate, hence both T cell and B cell immunity of viral proteins were screened. Antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach were adopted to generate the most antigenic epitopes of avian influenza A (H7N9) proteome. Further, a novel subunit vaccine was designed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. Physicochemical properties and secondary structure of the designed vaccine were assessed to ensure its thermostability, h ydrophilicity, theoretical PI and structural behavior. Homology modeling, refinement and validation of the designed vaccine allowed to construct a three dimensional structure of the predicted vaccine, further employed to molecular docking analysis with different MHC molecules and human immune TLR8 receptor present on lymphocyte cells. Moreover, disulfide engineering was employed to lessen the high mobility region of the designed vaccine in order to extend its stability. Furthermore, we investigated the molecular dynamic simulation of the modeled subunit vaccine and TLR8 complexed molecule to strengthen our prediction. Finally, the suggested vaccine was reverse transcribed and adapted for E. coli strain K12 prior to insertion within pET28a(+) vector for checking translational potency and microbial expression.