A5000397120- Computational Drug Discovery Methods
- Viral Infections and Vectors
- Microbial Natural Products and Biosynthesis
- Mosquito-borne diseases and control
- Leptospirosis research and findings
- Machine Learning in Materials Science
- Veterinary medicine and infectious diseases
- Neuropeptides and Animal Physiology
- Metabolomics and Mass Spectrometry Studies
- Synthesis and biological activity
- Receptor Mechanisms and Signaling
- Bioinformatics and Genomic Networks
- Viral Infections and Outbreaks Research
- Wood and Agarwood Research
- Plant Pathogens and Fungal Diseases
- Pharmacogenetics and Drug Metabolism
Soongsil University
2021-2025
Regional Medical Research Centre
2018-2020
Regional Medical Research Centre
2020
Indian Council of Medical Research
2020
Pondicherry University
2017-2018
G protein-coupled receptors (GPCRs) play vital roles in various physiological processes, making them attractive drug discovery targets. Meanwhile, deep learning techniques have revolutionized by facilitating efficient tools for expediting the identification and optimization of ligands. However, existing models GPCRs often focus on single-target or a small subset employ binary classification, constraining their applicability high throughput virtual screening. To address these issues, we...
Abstract The Triton X‐114‐based solubilization and temperature‐dependent phase separation of proteins is used for subcellular fractionation where, aqueous, detergent, pellet fractions represents cytoplasmic, outer membrane (OM), inner proteins, respectively. Mass spectrometry‐based proteomic analysis X‐114 Leptospira interrogans identified 2957 unique distributed across the fractions. results are compared with bioinformatics predictions on their localization pathogenic nature. Analysis...
The discovery of selective and potent kinase inhibitors is crucial for the treatment various diseases, but process challenging due to high structural similarity among kinases. Efficient kinome-wide bioactivity profiling essential understanding function identifying inhibitors. In this study, we propose AiKPro, a deep learning model that combines structure-validated multiple sequence alignments molecular 3D conformer ensemble descriptors predict kinase-ligand binding affinities. Our uses an...
Abstract Kinases play a vital role in regulating essential cellular processes, including cell cycle progression, growth, apoptosis, and metabolism, by catalyzing the transfer of phosphate groups from adenosing triphosphate to substrates. Their dysregulation has been closely associated with numerous diseases, cancer development, making them attractive targets for drug discovery. However, accurately predicting binding affinity between chemical compounds kinase remains challenging due highly...
Zika virus (ZIKV), a single-strand RNA flavivirus, is transmitted primarily through Aedes aegypti. The recent outbreaks in America and unexpected association between ZIKV infection birth defects have triggered the global attention. This vouches to understand molecular mechanisms of develop effective drug therapy. A systems-level understanding biological process affected by fetal brain sample led us identify candidate genes for pharmaceutical intervention potential biomarkers diagnosis. To...
Abstract Since the successful debut of AlphaGo, deep learning (DL) techniques have been applied to almost all areas data sciences and are achieving remarkable milestones. For example, in predicting cytochrome P450 (CYP450) inhibition, DL other machine were proven significantly useful. However, currently, most models focused on how much they can improve compared previously published methods by using different methodologies larger sets without considering bio‐selectivity. This study provides a...
Abstract Proteomes of pathogenic Leptospira interrogans and L. borgpetersenii the saprophytic biflexa were filtered through computational tools to identify Outer Membrane Proteins (OMPs) that satisfy required biophysical parameters for their presence on outer membrane. A total 133, 130, 144 OMPs identified in , respectively, which forms approximately 4% proteomes. holistic analysis transporting characteristics together with Clusters Orthologous Groups (COGs) among distribution across 3...
Endophytes; a ubiquitous group of microorganisms considered as gem box bioactive constituents medical significance. Studies on this emerging field is very less among the research communities. The present study focused molecular phylogenetics endophytic fungus that associated with leaf Kayea assamica, an endemic plant species Northeast India and identification its secondary metabolites (natural product) produced under in vitro condition. endogenous was isolated from sterile disease-free...
Abstract The discovery of selective and potent kinase inhibitors is crucial for the treatment various diseases, but process challenging due to high structural similarity among kinases. Efficient kinome-wide bioactivity profiling essential understanding function identifying inhibitors. In this study, we propose AiKPro, a deep learning model that combines structure-validated multiple sequence alignments (svMSA) molecular 3D conformer ensemble descriptors (3CED) predict kinase-ligand binding...