S
Surendra Kumar
Researcher at Gachon University
Publications - 53
Citations - 818
Surendra Kumar is an academic researcher from Gachon University. The author has contributed to research in topics: Quantitative structure–activity relationship & Docking (molecular). The author has an hindex of 12, co-authored 47 publications receiving 565 citations. Previous affiliations of Surendra Kumar include Hatch Ltd & Northern India Engineering College.
Papers
More filters
Journal ArticleDOI
Electric-field-induced electroporation and permeation of reactive oxygen species across a skin membrane
Dharmendra Kumar Yadav,Dharmendra Kumar Yadav,Surendra Kumar,Surendra Kumar,Eun Ha Choi,Mi-hyun Kim,Mi-hyun Kim +6 more
TL;DR: The permeability study suggested that water pores in the membrane facilitate the penetration of reactive oxygen species across the membrane to the interior of the cell, which may have significance in experimental applications in vivo as they may cause oxidative stress and induce apoptosis.
Journal ArticleDOI
Non-peptide-based new class of platelet aggregation inhibitors: Design, synthesis, bioevaluation, SAR, and in silico studies.
Pradeep K. Jaiswal,Vashundhra Sharma,Surendra Kumar,Manas Mathur,Ajit K. Swami,Dharmendra Kumar Yadav,Sandeep Chaudhary +6 more
TL;DR: To the best of the knowledge, this is the first report of the identification of non‐peptide‐based functionalized 2‐oxo‐benzo[1,4]oxazines as platelet aggregation inhibitors.
Journal ArticleDOI
Ligand-based pharmacophore modeling and docking studies on vitamin D receptor inhibitors.
TL;DR: A atom‐based three‐dimensional quantitative structure‐activity relationships model was developed to rationalize the structural requirement of biological activity modulating components and provide further insights into the development of novel VDR inhibitors with better activity.
Journal ArticleDOI
SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors.
Surendra Kumar,Mi-hyun Kim +1 more
TL;DR: SMPLIP-score as discussed by the authors embeds the interaction fingerprint pattern on the ligand-binding site environment and molecular fragments of ligands into an input vectorized matrix for learning layers (random forest or deep neural network).
Journal ArticleDOI
Design, synthesis, computational and biological evaluation of new benzodiazepines as CNS agents
TL;DR: Two series of new benzodiazepine compounds synthesized and evaluated for antianxiety and skeletal muscle relaxant activity as CNS agents in albino mice revealed that the target compounds correctly dock into the binding pocket of the GABAA receptor, while their bioavailability/drug-likeness was predicted to be acceptable but requires future optimization.