A5015469857- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Computational Drug Discovery Methods
- Spectroscopy and Quantum Chemical Studies
- Calpain Protease Function and Regulation
- Mass Spectrometry Techniques and Applications
- Genetics, Bioinformatics, and Biomedical Research
- Bioinformatics and Genomic Networks
- Pharmacogenetics and Drug Metabolism
- Ubiquitin and proteasome pathways
- Endoplasmic Reticulum Stress and Disease
- Enzyme Structure and Function
- Glycosylation and Glycoproteins Research
- Genetic Associations and Epidemiology
- Microfluidic and Capillary Electrophoresis Applications
- CRISPR and Genetic Engineering
- Cell Adhesion Molecules Research
- Epigenetics and DNA Methylation
- Biological Research and Disease Studies
- Genetics and Neurodevelopmental Disorders
- Genomics and Phylogenetic Studies
- Genetic Mapping and Diversity in Plants and Animals
- Plant and Fungal Interactions Research
- Molecular Junctions and Nanostructures
Astronomy and Space
2025
Clemson University
2019-2025
Jawaharlal Nehru University
2017-2020
University of Padua
2019
Chaudhary Charan Singh Haryana Agricultural University
2002
Modeling the effect of mutations on protein thermodynamics stability is useful for engineering and understanding molecular mechanisms disease-causing variants. Here, we report a new development SAAFEC method, SAAFEC-SEQ, which gradient boosting decision tree machine learning method to predict change folding free energy caused by amino acid substitutions. The does not require 3D structure corresponding protein, but only its sequence and, thus, can be applied genome-scale investigations where...
Electrostatic potential, energies, and forces affect virtually any process in molecular biology, however, computing these quantities is a difficult task due to irregularly shaped macromolecules the presence of water. Here, we report new edition popular software package DelPhi along with describing its functionalities. The C++ object‐oriented supporting various levels multiprocessing memory distribution. It demonstrated that results significant improvement computational time. Furthermore, for...
Here, we present a Gaussian-based method for estimation of protein–protein binding entropy to augment the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) computational prediction free energy (ΔG). The is termed f5-MM/PBSA/E, where "E" stands and f5 five adjustable parameters. enthalpy components ΔG (molecular mechanics, polar non-polar solvation energies) are computed from single implicit solvent generalized Born (GB) minimized structure complex, while using independently GB...
The development of methods and algorithms to predict the effect mutations on protein stability, protein-protein interaction, protein-DNA/RNA binding is necessitated by needs engineering for understanding molecular mechanism disease-causing variants. vast majority leading require a database experimentally measured folding free energy changes training. These databases are collections experimental data taken from scientific investigations typically aimed at probing role particular residues...
Calpain-1 and calpain-2 are heterodimeric proteases consisting of a common small regulatory subunit CAPNS1 large catalytic subunit, CAPN1 or CAPN2, respectively. These calpains have emerged as potential therapeutic targets in cancer other diseases through their roles cell signaling pathways affecting sensitivity to chemotherapeutic targeted drugs, promoting metastasis. While inhibition has the provide benefit patients, there currently no clinically approved active site directed drugs that...
Dysregulated calpain-1 and calpain-2 protease activity linked to several diseases has encouraged efforts explore inhibiting calpain provide therapeutic benefits. However, there are currently no clinically approved drugs that specifically target functionality. To address this unmet need, we carried out in silico drug discovery identify small molecules capable of modulating activity. Our approach is based on the observation heterodimer formation catalytic (CAPN2) regulatory (CAPNS1) subunits...
Background/Objectives: Predicting the effects of protein and DNA mutations on binding free energy protein–DNA complexes is crucial for understanding how variants impact wild-type cellular function. As many interactions involve binding, accurately predicting changes in (ΔΔG) valuable distinguishing pathogenic from benign ones. Methods: This study describes development optimization SAMPDI-3Dv2 machine learning method, which trained an expanded database experimentally measured ΔΔGs. enhanced...
Mutations that alter protein-DNA interactions may be pathogenic and cause diseases. Therefore, it is extremely important to quantify the effect of mutations on binding free energy reveal molecular origin diseases assist development treatments. Although several methods predict change affinity upon in protein were developed, DNA was not considered yet.Here, we report a new version SAMPDI, SAMPDI-3D, which gradient boosting decision tree machine learning method caused by both bases...
Abstract Motivation Mutations in protein–protein interactions can affect the corresponding complexes, impacting function and potentially leading to disease. Given abundance of membrane proteins, it is crucial assess impact mutations on binding affinity these proteins. Although several methods exist predict free energy change due most require structural information protein complex are primarily trained SKEMPI database, which composed mainly soluble Results A novel sequence-based method...
The biomolecules interact with their partners in an aqueous media; thus, solvation energy is important thermodynamics quantity. In previous works (J. Chem. Theory Comput. 14(2): 1020-1032), we demonstrated that the Poisson-Boltzmann (PB) approach reproduces calculated via thermodynamic integration (TI) protocol if structures of proteins are kept rigid. However, not rigid bodies and computing must account for flexibility. Typically, framework PB calculations, this done by collecting snapshots...
Our group has implemented a smooth Gaussian-based dielectric function in DelPhi (J. Chem. Theory Comput.2013,9 (4), 2126-2136) which models the solute as an object with inhomogeneous permittivity and provides transition of from surface-bound water to bulk solvent. Although it is well-understood that protein hydrophobic core less polarizable than hydrophilic surface, attention paid polarizability molecules inside on its surface. Here, we apply explicit simulations study behavior buried...
Opioid addiction disorder (OAD) affects millions of people worldwide. While it is known that OAD originates from many factors, including social and environmental the role genetic variants in developing disease has also been reported. This study aims to investigate may be associated with risk upon exposure. Twenty-three subjects who had previously given opioid-based painkillers undergo small surgical treatment were recruited at Prisma Health Upstate clinic elsewhere. Eleven them considered...
Electrostatics play indispensable role in practically any process molecular biology. Indeed, at distances larger than several Angstroms all other forces are negligibly small and electrostatic force dominates. However, modeling electrostatics biology is a complicated task due to presence of water phase, mobile ions irregularly shaped inhomogeneous biological macromolecules. A particular approach calculating such systems apply Poisson-Boltzmann equation (PBE). Here we provide tutorial for the...
Ions play significant roles in biological processes—they may specifically bind to a protein site or non-specifically on its surface. Although the role of bound ions ranges from actively providing structural compactness via coordination charge–charge interactions numerous enzymatic activities, surface-bound are also crucial maintaining protein’s stability, responding pH and ion concentration changes, contributing other processes. However, experimental determination positions is not trivial,...
Exploring at the molecular level, all possible ligand-protein approaching pathways and, consequently, identifying energetically favorable binding sites is considered crucial to depict a clear picture of whole scenario binding. In fact, ligand can recognize protein in multiple sites, adopting conformations every single site and inducing modifications upon present work, we would like how it couple supervised dynamics (SuMD) approach explore, from an unbound state, most recognition its protein,...
In protein design, correct use of topology is among the initial and most critical feature. Meticulous selection backbone aids in drastically reducing structure search space. With ProLego, we present a server application to explore component aspect structures provide an intuitive efficient way scan We have implemented in-house developed "topological representation" automated-pipeline extract from given structure. Using string, compares against non-redundant extensive database (ProLegoDB) as...