@article {149369, title = {Computational analysis of human gut microbial prolyl oligopeptidases (POPs) reveal candidate genes as therapeutics for celiac disease.}, journal = {Sci Rep}, volume = {14}, year = {2024}, month = {2024 Aug 23}, pages = {19641}, abstract = {

Celiac disease (CD) is a common autoimmune disorder in which the patients are unable to digest gluten, which is present in foods made up of wheat, barley and rye. Whilst diagnosis happens late in 80\% of the cases, avoidance of such foods appears to be the common solution. Alternative management strategies are required for the patients and their families since CD is also genetically carried over. Probiotic therapeutics and the consumption of appropriate enzymes, such as prolyloligopeptidases (POPs), from gut-friendly bacteria could reduce the disease burden and provide a better lifestyle for CD patients. We have examined around 5000 gut bacterial genomes and identified nearly 4000 non-redundant putative POPs. A select set of 10 gut bacterial POP sequences were subject to three-dimensional modelling, ligand docking and molecular dynamics simulations where stable interactions were observed between the POPs and gluten peptides. Our study provides sequence and structural analysis of potential POP enzymes in gut bacterial genomes, which form a strong basis to offer probiotic solutions to CD patients. In particular, these enzymes could be lead future therapeutics for this disease.

}, keywords = {Bacteria, Celiac Disease, Computational Biology, Gastrointestinal Microbiome, Glutens, Humans, Molecular Docking Simulation, Molecular Dynamics Simulation, Probiotics, Prolyl Oligopeptidases, Serine Endopeptidases}, issn = {2045-2322}, doi = {10.1038/s41598-024-70079-1}, author = {Nayak, Soumya and Regati, Dheemanth Reddy and Sowdhamini, Ramanathan} } @article {153395, title = {Toll-like receptor 4 pathway evolutionary trajectory and functional emergence.}, journal = {Frontiers in Immunology}, volume = {15}, year = {2024}, month = {2024}, pages = {1494017}, abstract = {

INTRODUCTION: Toll-like receptors 4 (TLR4) recognize lipopolysaccharides (LPS) from bacteria as their conventional ligands and undergo downstream signaling to produce cytokines. They mediate the signaling either by the TIRAP-MyD88 complex or by the TRAM-TRIF complex. The MyD88 pathway is common to all other TLRs, whereas the TRAM-TRIF complex is largely exclusive to TLR4. Here we study the TIR domain of TRAM and TRIF ortholog proteins that are crucial for downstream signaling. Our previous work on pan-genome-wide survey, indicates to be the ancestral organism with both TRAM and TRIF proteins.

METHODS: To gain a deeper insight into the protein function and to compare them with adaptor proteins, we modeled the docking of the TRAM-TRIF complex of representative organisms across various taxa. These modeling experiments provide insights to ascertain a possible interaction surface and calculate the energetics and electrostatic potential of the complex. Furthermore, this enables us to employ normal mode analysis (NMA) to examine fluctuating, interacting, and other specific residue clusters that could have a role in protein functioning in both and . We also performed molecular dynamics simulations of these complexes and cross-validated the functionally important residues using network parameters.

RESULTS: We compared the stoichiometry of TRAM-TRIF complexes and found that the tetrameric models (TRAM and TRIF dimer) were more stable than the trimeric model (TRAM dimer and TRIF monomer). While the critical residues of TIRAP, TRIF, and MyD88 were preserved, we also found that the important residues of TRAM signaling were not conserved in .

DISCUSSION: This suggests the presence of functional TIRAP-MyD88-mediated TLR4 signaling and TRIF-mediated TLR3 signaling in the ancestral species. The overall biological function of this signaling domain appears to be gradually acquired through the orchestration of several motifs through an evolutionary scale.

}, keywords = {Adaptor Proteins, Vesicular Transport, Animals, Evolution, Molecular, Humans, Membrane Glycoproteins, Molecular Docking Simulation, Myeloid Differentiation Factor 88, Protein Binding, Receptors, Interleukin-1, Signal Transduction, Toll-Like Receptor 4}, issn = {1664-3224}, doi = {10.3389/fimmu.2024.1494017}, url = {https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1494017/full}, author = {Verma, Shailya and Sowdhamini, Ramanathan} } @article {117966, title = {Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening.}, journal = {Sci Rep}, volume = {12}, year = {2022}, month = {2022 Sep 24}, pages = {15952}, abstract = {

IFITM3 is a transmembrane protein that confers innate immunity. It has been established to restrict entry of multiple viruses. Overexpression of IFITM3 has been shown to be associated with multiple cancers, implying IFITM3 to be good therapeutic target. The regulation of IFITM3 activity is mediated by multiple post-translational modifications (PTM). In this study, we have modelled the structure of IFITM3, consistent with experimental predictions on its membrane topology. MD simulation in membrane-aqueous environment revealed the stability of the model. Ligand binding sites on the IFITM3 surface were predicted and it was observed that the best site includes important residues involved in PTM and has good druggable score. Molecular docking was performed using FDA approved ligands and natural ligands from Super Natural II database. The ligands were re-ranked by calculating binding free energy. Select docking complexes were simulated again to substantiate the binding between ligand and IFITM3. We observed that known drugs like Eluxadoline and natural products like SN00224572 and Parishin A have good binding affinity against IFITM3. These ligands form persistent interactions with key lysine residues (Lys83, Lys104) and hence can potentially alter the activity of IFITM3. The results of this computational study can provide a starting point for experimental investigations on IFITM3 modulators.

}, keywords = {Biological Products, Ligands, Lysine, Molecular Docking Simulation, RNA-Binding Proteins}, issn = {2045-2322}, doi = {10.1038/s41598-022-20259-8}, author = {Tiwari, Vikas and Viswanath, Shruthi} } @article {869, title = {DOCKSCORE: a webserver for ranking protein-protein docked poses.}, journal = {BMC Bioinformatics}, volume = {16}, year = {2015}, month = {2015}, pages = {127}, abstract = {

BACKGROUND: Proteins interact with a variety of other molecules such as nucleic acids, small molecules and other proteins inside the cell. Structure-determination of protein-protein complexes is challenging due to several reasons such as the large molecular weights of these macromolecular complexes, their dynamic nature, difficulty in purification and sample preparation. Computational docking permits an early understanding of the feasibility and mode of protein-protein interactions. However, docking algorithms propose a number of solutions and it is a challenging task to select the native or near native pose(s) from this pool. DockScore is an objective scoring scheme that can be used to rank protein-protein docked poses. It considers several interface parameters, namely, surface area, evolutionary conservation, hydrophobicity, short contacts and spatial clustering at the interface for scoring.

RESULTS: We have implemented DockScore in form of a webserver for its use by the scientific community. DockScore webserver can be employed, subsequent to docking, to perform scoring of the docked solutions, starting from multiple poses as inputs. The results, on scores and ranks for all the poses, can be downloaded as a csv file and graphical view of the interface of best ranking poses is possible.

CONCLUSIONS: The webserver for DockScore is made freely available for the scientific community at: http://caps.ncbs.res.in/dockscore/ .

}, keywords = {Algorithms, Humans, Internet, Molecular Docking Simulation, Protein Binding, Protein Interaction Domains and Motifs, Proteins, ras GTPase-Activating Proteins, Software}, issn = {1471-2105}, doi = {10.1186/s12859-015-0572-6}, author = {Malhotra, Sony and Mathew, Oommen K and Sowdhamini, Ramanathan} }