In silico prediction of blood brain barrier permeability: an artificial neural network model P Garg, J Verma Journal of Chemical Information and Modeling 46 (1), 289-297, 2006 | 157 | 2006 |
Structure-based virtual screening to discover potential lead molecules for the SARS-CoV-2 main protease A Gahlawat, N Kumar, R Kumar, H Sandhu, IP Singh, S Singh, A Sjöstedt, ... Journal of Chemical Information and Modeling 60 (12), 5781-5793, 2020 | 97 | 2020 |
Synthesis and antileishmanial activity of Piperoyl-Amino acid conjugates IP Singh, SK Jain, A Kaur, S Singh, R Kumar, P Garg, SS Sharma, ... European Journal of Medicinal Chemistry 45 (8), 3439-3445, 2010 | 64 | 2010 |
The role of multidrug resistance protein (MRP-1) as an active efflux transporter on blood–brain barrier (BBB) permeability K Lingineni, V Belekar, SR Tangadpalliwar, P Garg Molecular Diversity 21 (2), 355-365, 2017 | 62 | 2017 |
Docking-based 3D-QSAR study of HIV-1 integrase inhibitors P Gupta, N Roy, P Garg European Journal of Medicinal Chemistry 44 (11), 4276-4287, 2009 | 55 | 2009 |
A systematic reconstruction and constraint-based analysis of Leishmania donovani metabolic network: identification of potential antileishmanial drug targets M Sharma, N Shaikh, S Yadav, S Singh, P Garg Molecular BioSystems 13 (5), 955-969, 2017 | 43 | 2017 |
Development of [18F]-labeled Pyrazolo[4,3-e]-1,2,4- triazolo[1,5-c]pyrimidine (SCH442416) analogs for the imaging of Cerebral Adenosine A2A receptors with Positron Emission … S Khanapur, S Paul, A Shah, S Vatakuti, MJB Koole, R Zijlma, ... Journal of Medicinal Chemistry 57 (15), 6765-6780, 2014 | 38 | 2014 |
Identification of Novel HIV‐1 Integrase Inhibitors Using Shape‐Based Screening, QSAR, and Docking Approach P Gupta, P Garg, N Roy Chemical Biology & Drug Design 79 (5), 835-849, 2012 | 38 | 2012 |
Comparative docking and CoMFA analysis of curcumine derivatives as HIV-1 integrase inhibitors P Gupta, P Garg, N Roy Molecular Diversity 15, 733-750, 2011 | 38 | 2011 |
In vitro and in vivo metabolic investigation of the Palbociclib by UHPLC-Q-TOF/MS/MS and in silico toxicity studies of its metabolites BB Chavan, S Tiwari, G Shankar, RD Nimbalkar, P Garg, R Srinivas, ... Journal of Pharmaceutical and Biomedical Analysis 157, 59-74, 2018 | 37 | 2018 |
Mycobacterium tuberculosis Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) functions as a receptor for human lactoferrin H Malhotra, A Patidar, V Boradia, R Kumar, A Kumar, RD Nimbalkar, ... Frontiers in Cellular and Infection Microbiology, doi: 10.3389/fcimb.2017.00245, 2017 | 37 | 2017 |
Role of Breast Cancer Resistance Protein (BCRP) as Active Efflux Transporter on Blood-Brain Barrier (BBB) Permeability P Garg, R Dhakne, V Belekar Molecular Diversity 19 (1), 163-172, 2015 | 37 | 2015 |
Design and synthesis of caffeoyl-anilides as portmanteau inhibitors of HIV-1 integrase and CCR5 HS Bodiwala, S Sabde, P Gupta, R Mukherjee, R Kumar, P Garg, ... Bioorganic & medicinal chemistry 19 (3), 1256-1263, 2011 | 35 | 2011 |
Physicochemical n‐Grams Tool: A tool for protein physicochemical descriptor generation via Chou’s 5‐step rule S Vishnoi, P Garg, P Arora Chemical Biology & Drug Design 95 (1), 79-86, 2020 | 34 | 2020 |
An improved approach for predicting drug-target interaction: proteochemometrics to molecular docking N Shaikh, M Sharma, P Garg Molecular BioSystems 12 (3), 1006-1014, 2016 | 34 | 2016 |
Characterization of stress degradation products of mirabegron using UPLC-QTOF-MS/MS and in silico toxicity predictions of its degradation products MVNK Talluri, PD Kalariya, TJ Reddy, M Sharma, P Garg, R Srinivas RSC Advances 5 (39), 31024-31038, 2015 | 34 | 2015 |
Shape-based virtual screening, docking and molecular dynamics simulations to identify Mtb-ASADH inhibitors R Kumar, P Garg, PV Bharatam Journal of Biomolecular Structure & Dynamics 33 (5), 1082-1093, 2015 | 34 | 2015 |
3D-QSAR studies of substituted 1-(3, 3-diphenylpropyl)-piperidinyl amides and ureas as CCR5 receptor antagonists YD Aher, A Agrawal, PV Bharatam, P Garg Journal of molecular modeling 13, 519-529, 2007 | 34 | 2007 |
Artificial intelligence and machine learning for protein toxicity prediction using proteomics data S Vishnoi, H Matre, P Garg, SK Pandey Chemical Biology & Drug Design 96 (3), 902-920, 2020 | 33 | 2020 |
Machine learning-based modeling to predict inhibitors of acetylcholinesterase H Sandhu, RN Kumar, P Garg Molecular Diversity 26, 331-340, 2022 | 32 | 2022 |