Normal Mode Analysis Elicits Conformational Shifts in Proteins at Both Proximal and Distal Regions to the Phosphosite Stemming from Single-Site Phosphorylation.

Phosphorylation, a fundamental biochemical switch, intricately regulates protein function and signaling pathways. Our study employs extensive computational structural analyses on a curated data set of phosphorylated and unphosphorylated protein pairs to explore the multifaceted impact of phosphorylation on protein conformation. Using normal mode analysis (NMA), we investigated changes in protein flexibility post-phosphorylation, highlighting an enhanced level of structural dynamism. Our findings reveal that phosphorylation induces not only local changes at the phosphorylation site but also extensive alterations in distant regions, showcasing its far-reaching influence on protein structure-dynamics. Through in-depth case studies on polyubiquitin B and glycogen synthase kinase-3 beta, we elucidate how phosphorylation at distinct sites leads to variable structural and dynamic modifications, potentially dictating functional outcomes. While phosphorylation largely preserves the residue motion correlation, it significantly disrupts low-frequency global modes, presenting a dualistic impact on protein dynamics. We also explored alterations in the total accessible surface area (ASA), emphasizing region-specific changes around phosphorylation sites. This study sheds light on phosphorylation-induced conformational changes, dynamic modulation, and surface accessibility alterations, leveraging an integrated computational approach with RMSD, NMA, and ASA, thereby contributing to a comprehensive understanding of cellular regulation and suggesting promising avenues for therapeutic interventions.

The alteration of structural network upon transient association between proteins studied using graph theory.

Proteins such as enzymes perform their function by predominant non-covalent bond interactions between transiently interacting units. There is an impact on the overall structural topology of the protein, albeit transient nature of such interactions, that enable proteins to deactivate or activate. This aspect of the alteration of the structural topology is studied by employing protein structural networks, which are node-edge representative models of protein structure, reported as a robust tool for capturing interactions between residues. Several methods have been optimized to collect meaningful, functionally relevant information by studying alteration of structural networks. In this article, different methods of comparing protein structural networks are employed, along with spectral decomposition of graphs to study the subtle impact of protein-protein interactions. A detailed analysis of the structural network of interacting partners is performed across a dataset of around 900 pairs of bound complexes and corresponding unbound protein structures. The variation in network parameters at, around, and far away from the interface are analyzed. Finally, we present interesting case studies, where an allosteric mechanism of structural impact is understood from communication-path detection methods. The results of this analysis are beneficial in understanding protein stability, for future engineering, and docking studies.

Hypothesis-free phenotype prediction within a genetics-first framework.

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed 'rare', even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population. Associative methods give some understanding how rare genetic variants influence disease and organism-level phenotypes. But here we show that additional discoveries can be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible genetic causes for developmental disorders that have eluded other established methods and present molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.

SIRT6 transcriptionally regulates fatty acid transport by suppressing PPARγ.

Pathological lipid accumulation is often associated with enhanced uptake of free fatty acids via specific transporters in cardiomyocytes. Here, we identify SIRT6 as a critical transcriptional regulator of fatty acid transporters in cardiomyocytes. We find that SIRT6 deficiency enhances the expression of fatty acid transporters, leading to enhanced fatty acid uptake and lipid accumulation. Interestingly, the haploinsufficiency of SIRT6 is sufficient to induce the expression of fatty acid transporters and cause lipid accumulation in murine hearts. Mechanistically, SIRT6 depletion enhances the occupancy of the transcription factor PPARγ on the promoters of critical fatty acid transporters without modulating the acetylation of histone 3 at Lys 9 and Lys 56. Notably, the binding of SIRT6 to the DNA-binding domain of PPARγ is critical for regulating the expression of fatty acid transporters in cardiomyocytes. Our data suggest exploiting SIRT6 as a potential therapeutic target for protecting the heart from metabolic diseases.

Transient association between proteins elicits alteration of dynamics at sites far away from interfaces.

Proteins are known to undergo structural changes upon binding to partner proteins. However, the prevalence, extent, location, and function of change in protein dynamics due to transient protein-protein interactions is not well documented. Here, we have analyzed a dataset of 58 protein-protein complexes of known three-dimensional structure and structures of their corresponding unbound forms to evaluate dynamics changes induced by binding. Fifty-five percent of cases showed significant dynamics change away from the interfaces. This change is not always accompanied by an observed structural change. Binding of protein partner is found to alter inter-residue communication within the tertiary structure in about 90% of cases. Also, residue motions accessible to proteins in unbound form were not always maintained in the bound form. Further analyses revealed functional roles for the distant site where dynamics change was observed. Overall, the results presented here strongly suggest that alteration of protein dynamics due to binding of a partner protein commonly occurs.

Molecular and Structural Basis of Cross-Reactivity in M. tuberculosis Toxin-Antitoxin Systems.

Mycobacterium tuberculosis genome encodes over 80 toxin-antitoxin (TA) systems. While each toxin interacts with its cognate antitoxin, the abundance of TA systems presents an opportunity for potential non-cognate interactions. TA systems mediate manifold interactions to manage pathogenicity and stress response network of the cell and non-cognate interactions may play vital roles as well. To address if non-cognate and heterologous interactions are feasible and to understand the structural basis of their interactions, we have performed comprehensive computational analyses on the available 3D structures and generated structural models of paralogous M. tuberculosis VapBC and MazEF TA systems. For a majority of the TA systems, we show that non-cognate toxin-antitoxin interactions are structurally incompatible except for complexes like VapBC15 and VapBC11, which show similar interfaces and potential for cross-reactivity. For TA systems which have been experimentally shown earlier to disfavor non-cognate interactions, we demonstrate that they are structurally and stereo-chemically incompatible. For selected TA systems, our detailed structural analysis identifies specificity conferring residues. Thus, our work improves the current understanding of TA interfaces and generates a hypothesis based on congenial binding site, geometric complementarity, and chemical nature of interfaces. Overall, our work offers a structure-based explanation for non-cognate toxin-antitoxin interactions in M. tuberculosis.

Potent HCV NS3 Protease Inhibition by a Water-Soluble Phyllanthin Congener.

NS3/4A protease of hepatitis C virus (HCV) plays an important role in viral RNA replication. A 1,4-diphenylbutanedicarboxylic acid derivative, namely, phyllanthin, extracted from the leaf of a herbal plant, Phyllanthus amarus, inhibits HCV NS3/4A protease and replication activities. However, the reduced aqueous solubility, high toxicity, and poor oral bioavailability are major impediments with phyllanthin. We herein present a design approach to generate phyllanthin congeners in order to potentiate inhibition activity against protease. The phyllanthin congeners were synthesized by chemical methods and subjected to systematic biological studies. One of the congeners, annotated as D8, is identified as a novel and potent inhibitor of the HCV-NS3/4Aprotease activity in vitro and the viral RNA replication in cell culture. Structural analysis using the computational-based docking approach demonstrated important noncovalent interactions between D8 and the catalytic residues of the viral protease. Furthermore, D8 was found to be significantly nontoxic in cell culture. More importantly, oral administration of D8 in BALB/c mice proved its better tolerability and bioavailability, as compared to native phyllanthin. Taken together, this study reveals a promising candidate for developing anti-HCV therapeutics to control HCV-induced liver diseases.

Mechanism of CcdA-Mediated Rejuvenation of DNA Gyrase.

Most biological processes involve formation of transient complexes where binding of a ligand allosterically modulates function. The ccd toxin-antitoxin system is involved in plasmid maintenance and bacterial persistence. The CcdA antitoxin accelerates dissociation of CcdB from its complex with DNA gyrase, binds and neutralizes CcdB, but the mechanistic details are unclear. Using a series of experimental and computational approaches, we demonstrate the formation of transient ternary and quaternary CcdA:CcdB:gyrase complexes and delineate the molecular steps involved in the rejuvenation process. Binding of region 61-72 of CcdA to CcdB induces the vital structural and dynamic changes required to facilitate dissociation from gyrase, region 50-60 enhances the dissociation process through additional allosteric effects, and segment 37-49 prevents gyrase rebinding. This study provides insights into molecular mechanisms responsible for recovery of CcdB-poisoned cells from a persister-like state. Similar methodology can be used to characterize other important transient, macromolecular complexes.

Bioinformatic and mutational studies of related toxin-antitoxin pairs in Mycobacterium tuberculosis predict and identify key functional residues.

Mycobacterium tuberculosis possesses an unusually large representation of type II toxin-antitoxin (TA) systems, whose functions and targets are mostly unknown. To better understand the basis of their unique expansion and to probe putative functional similarities among these systems, here we computationally and experimentally investigated their sequence relationships. Bioinformatic and phylogenetic investigations revealed that 51 sequences of the VapBC toxin family group into paralogous sub-clusters. On the basis of conserved sequence fingerprints within paralogues, we predicted functional residues and residues at the putative TA interface that are useful to evaluate TA interactions. Substitution of these likely functional residues abolished the toxin's growth-inhibitory activity. Furthermore, conducting similarity searches in 101 mycobacterial and ∼4500 other prokaryotic genomes, we assessed the relative conservation of the M. tuberculosis TA systems and found that most TA orthologues are well-conserved among the members of the M. tuberculosis complex, which cause tuberculosis in animal hosts. We found that soil-inhabiting, free-living Actinobacteria also harbor as many as 12 TA pairs. Finally, we identified five novel putative TA modules in M. tuberculosis. For one of them, we demonstrate that overexpression of the putative toxin, Rv2514c, induces bacteriostasis and that co-expression of the cognate antitoxin Rv2515c restores bacterial growth. Taken together, our findings reveal that toxin sequences are more closely related than antitoxin sequences in M. tuberculosis Furthermore, the identification of additional TA systems reported here expands the known repertoire of TA systems in M. tuberculosis.

Mycobacterium tuberculosis Rv0366c-Rv0367c encodes a non-canonical PezAT-like toxin-antitoxin pair.

Toxin-antitoxin (TA) systems are ubiquitously existing addiction modules with essential roles in bacterial persistence and virulence. The genome of Mycobacterium tuberculosis encodes approximately 79 TA systems. Through computational and experimental investigations, we report for the first time that Rv0366c-Rv0367c is a non-canonical PezAT-like toxin-antitoxin system in M. tuberculosis. Homology searches with known PezT homologues revealed that residues implicated in nucleotide, antitoxin-binding and catalysis are conserved in Rv0366c. Unlike canonical PezA antitoxins, the N-terminal of Rv0367c is predicted to adopt the ribbon-helix-helix (RHH) motif for deoxyribonucleic acid (DNA) recognition. Further, the modelled complex predicts that the interactions between PezT and PezA involve conserved residues. We performed a large-scale search in sequences encoded in 101 mycobacterial and 4500 prokaryotic genomes and show that such an atypical PezAT organization is conserved in 20 other mycobacterial organisms and in families of class Actinobacteria. We also demonstrate that overexpression of Rv0366c induces bacteriostasis and this growth defect could be restored upon co-expression of cognate antitoxin, Rv0367c. Further, we also observed that inducible expression of Rv0366c in Mycobacterium smegmatis results in decreased cell-length and enhanced tolerance against a front-line tuberculosis (TB) drug, ethambutol. Taken together, we have identified and functionally characterized a novel non-canonical TA system from M. tuberculosis.

A natural small molecule inhibitor corilagin blocks HCV replication and modulates oxidative stress to reduce liver damage.

Hepatitis C virus (HCV) infection causes chronic liver disease, which often leads to hepatocellular carcinoma. Earlier, we have demonstrated anti-HCV property of the methanolic extract of Phyllanthus amarus, an age-old folk-medicine against viral hepatitis. Here, we report identification of a principal bioactive component 'corilagin', which showed significant inhibition of the HCV key enzymes, NS3 protease and NS5B RNA-dependent-RNA-polymerase. This pure compound could effectively inhibit viral replication in the infectious cell culture system, displayed strong antioxidant activity by blocking HCV induced generation of reactive oxygen species and suppressed up-regulation of NOX4 and TGF-ß mRNA levels. Oral administration of corilagin in BALB/c mice demonstrated its better tolerability and systemic bioavailability. More importantly, corilagin could restrict serum HCV RNA levels, decrease collagen deposition and hepatic cell denaturation in HCV infected chimeric mice harbouring human hepatocytes. Taken together, results provide a basis towards developing a pure natural drug as an alternate therapeutic strategy for restricting viral replication and prevent liver damage towards better management of HCV induced pathogenesis.

Identification of a novel epitope in the C terminus of hepatitis C virus-E2 protein that induces potent and cross-reactive neutralizing antibodies.

Hepatitis C virus (HCV) is a leading cause of chronic viral hepatitis, but an effective vaccine is still not available to prevent infection. Use of neutralizing antibodies could be a potential therapeutic option. In this study, the presence of anti-HCV antibodies in HCV-infected patients was assessed from 50 patients and the presence of neutralizing antibodies was examined using 'hepatitis C virus-like particles'. Antibodies from two samples exhibited significant inhibitory activity, suggesting that these may neutralize viral infection. Antigenic determinants generating the neutralizing antibodies from these two samples were delineated by epitope mapping using the core, E1 and E2 regions and a stretch of 45 amino acid peptide (E2C45) derived from the C-terminal region of HCV-E2 protein (aa 634-679) was designed. Results suggest that this hitherto uncharacterized region has the potential to generate neutralizing antibodies against HCV and thus be effective in preventing virus entry into liver cells. Computational analysis of the structure of the modelled peptide (E2C45) suggested high conformational entropy for this region. Furthermore, E2C45 peptide-generated antibodies could block virus entry and monoclonal antibodies generated against this peptide could also significantly reduce virus replication in a cell culture system. It is possible that the inhibition could be partly due to a conformational alteration of the CD81-binding region, preventing virus attachment to liver cells. In conclusion, this work focused on the discovery of a novel epitope at the C terminus of E2 that induces potent neutralizing antibodies in HCV-infected patients.

AVP-IC50 Pred: Multiple machine learning techniques-based prediction of peptide antiviral activity in terms of half maximal inhibitory concentration (IC50).

Peptide-based antiviral therapeutics has gradually paved their way into mainstream drug discovery research. Experimental determination of peptides' antiviral activity as expressed by their IC50 values involves a lot of effort. Therefore, we have developed "AVP-IC50 Pred," a regression-based algorithm to predict the antiviral activity in terms of IC50 values (µM). A total of 759 non-redundant peptides from AVPdb and HIPdb were divided into a training/test set having 683 peptides (T(683)) and a validation set with 76 independent peptides (V(76)) for evaluation. We utilized important peptide sequence features like amino-acid compositions, binary profile of N8-C8 residues, physicochemical properties and their hybrids. Four different machine learning techniques (MLTs) namely Support vector machine, Random Forest, Instance-based classifier, and K-Star were employed. During 10-fold cross validation, we achieved maximum Pearson correlation coefficients (PCCs) of 0.66, 0.64, 0.56, 0.55, respectively, for the above MLTs using the best combination of feature sets. All the predictive models also performed well on the independent validation dataset and achieved maximum PCCs of 0.74, 0.68, 0.59, 0.57, respectively, on the best combination of feature sets. The AVP-IC50 Pred web server is anticipated to assist the researchers working on antiviral therapeutics by enabling them to computationally screen many compounds and focus experimental validation on the most promising set of peptides, thus reducing cost and time efforts. The server is available at http://crdd.osdd.net/servers/ic50avp.

CrisprGE: a central hub of CRISPR/Cas-based genome editing.

CRISPR system is a powerful defense mechanism in bacteria and archaea to provide immunity against viruses. Recently, this process found a new application in intended targeting of the genomes. CRISPR-mediated genome editing is performed by two main components namely single guide RNA and Cas9 protein. Despite the enormous data generated in this area, there is a dearth of high throughput resource. Therefore, we have developed CrisprGE, a central hub of CRISPR/Cas-based genome editing. Presently, this database holds a total of 4680 entries of 223 unique genes from 32 model and other organisms. It encompasses information about the organism, gene, target gene sequences, genetic modification, modifications length, genome editing efficiency, cell line, assay, etc. This depository is developed using the open source LAMP (Linux Apache MYSQL PHP) server. User-friendly browsing, searching facility is integrated for easy data retrieval. It also includes useful tools like BLAST CrisprGE, BLAST NTdb and CRISPR Mapper. Considering potential utilities of CRISPR in the vast area of biology and therapeutics, we foresee this platform as an assistance to accelerate research in the burgeoning field of genome engineering.

AVPdb: a database of experimentally validated antiviral peptides targeting medically important viruses.

Antiviral peptides (AVPs) have exhibited huge potential in inhibiting viruses by targeting various stages of their life cycle. Therefore, we have developed AVPdb, available online at http://crdd.osdd.net/servers/avpdb, to provide a dedicated resource of experimentally verified AVPs targeting over 60 medically important viruses including Influenza, HCV, HSV, RSV, HBV, DENV, SARS, etc. However, we have separately provided HIV inhibiting peptides in 'HIPdb'. AVPdb contains detailed information of 2683 peptides, including 624 modified peptides experimentally tested for antiviral activity. In modified peptides a chemical moiety is attached for increasing their efficacy and stability. Detailed information include: peptide sequence, length, source, virus targeted, virus family, cell line used, efficacy (qualitative/quantitative), target step/protein, assay used in determining the efficacy and PubMed reference. The database also furnishes physicochemical properties and predicted structure for each peptide. We have provided user-friendly browsing and search facility along with other analysis tools to help the users. Entering of many synthetic peptide-based drugs in various stages of clinical trials reiterate the importance for the AVP resources. AVPdb is anticipated to cater to the needs of scientific community working for the development of antiviral therapeutics.