ORCID Profile
0000-0003-4125-6670
Current Organisations
National Center For Child Health and Development
,
Agrivet Research and Advisory Pvt Ltd (India)
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Publications
Bhageerath-H: A homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins
Publisher: Springer Science and Business Media LLC
Date: 12-2014
ProTSAV: A protein tertiary structure analysis and validation server
Publisher: Elsevier BV
Date: 2016
DOI: 10.1016/J.BBAPAP.2015.10.004
Abstract: Quality assessment of predicted model structures of proteins is as important as the protein tertiary structure prediction. A highly efficient quality assessment of predicted model structures directs further research on function. Here we present a new server ProTSAV, capable of evaluating predicted model structures based on some popular online servers and standalone tools. ProTSAV furnishes the user with a single quality score in case of in idual protein structure along with a graphical representation and ranking in case of multiple protein structure assessment. The server is validated on ~64,446 protein structures including experimental structures from RCSB and predicted model structures for CASP targets and from public decoy sets. ProTSAV succeeds in predicting quality of protein structures with a specificity of 100% and a sensitivity of 98% on experimentally solved structures and achieves a specificity of 88%and a sensitivity of 91% on predicted protein structures of CASP11 targets under 2Å.The server overcomes the limitations of any single server/method and is seen to be robust in helping in quality assessment. ProTSAV is freely available at www.scfbio-iitd.res.in/software roteomics rotsav.jsp.
Structure-Based Design of Small Peptide Ligands to Inhibit Early-Stage Protein Aggregation Nucleation
Publisher: American Chemical Society (ACS)
Date: 23-04-2020
Local and systemic responses to SARS-CoV-2 infection in children and adults
Publisher: Springer Science and Business Media LLC
Date: 22-12-2021
DOI: 10.1038/S41586-021-04345-X
Abstract: It is not fully understood why COVID-19 is typically milder in children 1–3 . Here, to examine the differences between children and adults in their response to SARS-CoV-2 infection, we analysed paediatric and adult patients with COVID-19 as well as healthy control in iduals (total n = 93) using single-cell multi-omic profiling of matched nasal, tracheal, bronchial and blood s les. In the airways of healthy paediatric in iduals, we observed cells that were already in an interferon-activated state, which after SARS-CoV-2 infection was further induced especially in airway immune cells. We postulate that higher paediatric innate interferon responses restrict viral replication and disease progression. The systemic response in children was characterized by increases in naive lymphocytes and a depletion of natural killer cells, whereas, in adults, cytotoxic T cells and interferon-stimulated subpopulations were significantly increased. We provide evidence that dendritic cells initiate interferon signalling in early infection, and identify epithelial cell states associated with COVID-19 and age. Our matching nasal and blood data show a strong interferon response in the airways with the induction of systemic interferon-stimulated populations, which were substantially reduced in paediatric patients. Together, we provide several mechanisms that explain the milder clinical syndrome observed in children.
Capturing native/native like structures with a physico-chemical metric (pcSM) in protein folding
Publisher: Elsevier BV
Date: 08-2013
DOI: 10.1016/J.BBAPAP.2013.04.023
Abstract: Specification of the three dimensional structure of a protein from its amino acid sequence, also called a "Grand Challenge" problem, has eluded a solution for over six decades. A modestly successful strategy has evolved over the last couple of decades based on development of scoring functions (e.g. mimicking free energy) that can capture native or native-like structures from an ensemble of decoys generated as plausible candidates for the native structure. A scoring function must be fast enough in discriminating the native from unfolded/misfolded structures, and requires validation on a large data set(s) to generate sufficient confidence in the score. Here we develop a scoring function called pcSM that detects true native structure in the top 5 with 93% accuracy from an ensemble of candidate structures. If we eliminate the native from ensemble of decoys then pcSM is able to capture near native structure (RMSD<=5Ǻ) in top 10 with 86% accuracy. The parameters considered in pcSM are a C-alpha Euclidean metric, secondary structural propensity, surface areas and an intramolecular energy function. pcSM has been tested on 415 systems consisting 142,698 decoys (public and CASP-largest reported hitherto in literature). The average rank for the native is 2.38, a significant improvement over that existing in literature. In-silico protein structure prediction requires robust scoring technique(s). Therefore, pcSM is easily amenable to integration into a successful protein structure prediction strategy. The tool is freely available at www.scfbio-iitd.res.in/software csm.jsp.
Understanding the mechanism of copurification of “difficult to remove” host cell proteins in rituximab biosimilar products
Publisher: Wiley
Date: 13-11-2019
DOI: 10.1002/BTPR.2936
Abstract: Host cell proteins (HCPs) are considered a critical quality attribute and are linked to safety and efficacy of biotherapeutic products. Researchers have identified 10 HCPs in Chinese hamster ovary (CHO) that exhibit common characteristics of product association, coelution, and age-dependent expression and therefore are "difficult to remove" during downstream purification. These include cathepsin D, clusterin, galectin-3-binding protein, G-protein coupled receptor 56, lipoprotein lipase, metalloproteinase inhibitor, nidogen-1 secreted protein acidic and rich in cysteine (SPARC), sulfated glycoprotein, and insulin-like growth factor-2 RNA-binding protein. While the levels of HCPs in the investigated biosimilars were within the acceptable range of <100 ppm, certain "difficult to remove" HCPs were found in the biosimilar s les. This article aims to elucidate the underlying interactions between these "difficult to remove" HCPs and the mAb product. Surface study of rituximab exhibited unstable discontinuous patches of residues on the protein surface that have high propensity to get buried and lower the solvent exposed area. The higher order structure and the receptor binding were not affected, except for one of the biosimilars, owing to extremely low-HCP levels in its final drug product. Finally, based on the combined experimental and computational data from this study, a probable mechanism of retention for the 10 HCPs is proposed. The results presented here can guide downstream process design or avenues for protein engineering during product discovery to achieve more effective removal of the impurities.
Toxicity Prediction by Multimodal Deep Learning
Publisher: Springer International Publishing
Date: 2019
Synergistic Effects of Natural Compounds Toward Inhibition of SARS-CoV-2 3CL Protease
Publisher: American Chemical Society (ACS)
Date: 25-10-2021
D2N: Distance to the native
Publisher: Elsevier BV
Date: 10-2014
DOI: 10.1016/J.BBAPAP.2014.07.010
Abstract: Root-mean-square-deviation (RMSD), of computationally-derived protein structures from experimentally determined structures, is a critical index to assessing protein-structure-prediction-algorithms (PSPAs). The development of PSPAs to obtain 0Å RMSD from native structures is considered central to computational biology. However, till date it has been quite challenging to measure how far a predicted protein structure is from its native - in the absence of a known experimental/native structure. In this work, we report the development of a metric "D2N" (distance to the native) - that predicts the "RMSD" of any structure without actually knowing the native structure. By combining physico-chemical properties and known universalities in spatial organization of soluble proteins to develop D2N, we demonstrate the ability to predict the distance of a proposed structure to within ±1.5Ǻ error with a remarkable average accuracy of 93.6% for structures below 5Ǻ from the native. We believe that this work opens up a completely new avenue towards assigning reliable structures to whole proteomes even in the absence of experimentally determined native structures. The D2N tool is freely available at www.scfbio-iitd.res.in/software/d2n.jsp.
Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees
Publisher: American Chemical Society (ACS)
Date: 23-01-2019
Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments
Publisher: Springer Science and Business Media LLC
Date: 07-2022
Pharmacophore screening to identify natural origin compounds to target RNA-dependent RNA polymerase (RdRp) of SARS-CoV2
Publisher: Springer Science and Business Media LLC
Date: 09-01-2022
Role of solvent accessibility for aggregation-prone patches in protein folding
Publisher: Springer Science and Business Media LLC
Date: 27-08-2018
DOI: 10.1038/S41598-018-31289-6
Abstract: The arrangement of amino acids in a protein sequence encodes its native folding. However, the same arrangement in aggregation-prone regions may cause misfolding as a result of local environmental stress. Under normal physiological conditions, such regions congregate in the protein’s interior to avoid aggregation and attain the native fold. We have used solvent accessibility of aggregation patches (SAAP p ) to determine the packing of aggregation-prone residues. Our results showed that SAAP p has low values for native crystal structures, consistent with protein folding as a mechanism to minimize the solvent accessibility of aggregation-prone residues. SAAP p also shows an average correlation of 0.76 with the global distance test (GDT) score on CASP12 template-based protein models. Using SAAP p scores and five structural features, a random forest machine learning quality assessment tool, SAAP-QA, showed 2.32 average GDT loss between best model predicted and actual best based on GDT score on independent CASP test data, with the ability to discriminate native-like folds having an AUC of 0.94. Overall, the Pearson correlation coefficient (PCC) between true and predicted GDT scores on independent CASP data was 0.86 while on the external CAMEO dataset, comprising high quality protein structures, PCC and average GDT loss were 0.71 and 4.46 respectively. SAAP-QA can be used to detect the quality of models and iteratively improve them to native or near-native structures.
UNIVERSALITIES IN PROTEIN TERTIARY STRUCTURES: SOME NEW CONCEPTS
Publisher: WORLD SCIENTIFIC / INDIAN INST OF SCIENCE, INDIA
Date: 02-2013
Identification of a Novel Scaffold for Inhibition of Dipeptidyl Peptidase-4
Publisher: Mary Ann Liebert Inc
Date: 12-2019
Abstract: Dipeptidyl peptidase-4 (DPP-4) is considered a major drug target for type 2 diabetes mellitus (T2DM). In addition to T2DM, a regulatory role of DPP-4 was also found in cardiovascular diseases. Existing DPP-4 inhibitors have been reported to have several adverse effects. In this study, a computer-aided drug design approach and its use to detect a novel class of inhibitor for DPP-4 are reported. Through structure and pharmacophore-based screening, we identified 13 hit compounds from an ∼4-million-compound library. Physical interactions of these hits with DPP-4 were studied using docking and explicit solvent molecular dynamics (MD) simulations. Later, MMPBSA binding energy was calculated for the ligand rotein simulation trajectories to determine the stability of compounds in the binding cavity. These compounds have a novel scaffold and exhibited a stable binding mode. "Best-in-screen" compounds (or their closest available analogs) were resourced and their inhibition of DPP-4 activity was experimentally validated using an in vitro enzyme activity assay in the presence of 100 and 10 μM compounds. These assays identified a compound with a spirochromanone center with 53% inhibition activity at a 100 μM concentration. A further five spirochromanone compounds were synthesized and examined in silico and in vitro again, one compound showed 53% inhibitory activity action at 100 μM. Overall, this study identified two novel "spirochromanone" compounds that lowered DPP-4 activity by more than ∼50% at 100 μM. This study also showed the impact of fast in silico drug design techniques utilizing virtual screening and MD to identify novel scaffolds to bind and inhibit DPP-4. Spirochromanone motif identified here may be used to design molecules to achieve drug-like inhibitory action against DPP-4.
Quantitative toxicity prediction via meta ensembling of multitask deep learning models
Publisher: American Chemical Society (ACS)
Date: 03-05-2021
Related Organisations
Wellcome Sanger Institute
Location: United Kingdom of Great Britain and Northern Ireland
Wellcome Trust Sanger Institute
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
No related grants have been discovered for Avinash Mishra.