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Dr. Pravin Ambure
Dr. Pravin Ambure
Co-founder and Researcher at MultiTargetAI (Former MSCA-IF fellow)
Verified email at multitargetai.com - Homepage
Title
Cited by
Cited by
Year
On a simple approach for determining applicability domain of QSAR models
K Roy, S Kar, P Ambure
Chemometrics and Intelligent Laboratory Systems 145, 22-29, 2015
6422015
Be aware of error measures. Further studies on validation of predictive QSAR models
K Roy, RN Das, P Ambure, RB Aher
Chemometrics and Intelligent Laboratory Systems 152, 18-33, 2016
6282016
“NanoBRIDGES” software: open access tools to perform QSAR and nano-QSAR modeling
P Ambure, RB Aher, A Gajewicz, T Puzyn, K Roy
Chemometrics and Intelligent Laboratory Systems 147, 1-13, 2015
1752015
How important is to detect systematic error in predictions and understand statistical applicability domain of QSAR models?
K Roy, P Ambure, RB Aher
Chemometrics and Intelligent Laboratory Systems 162, 44-54, 2017
1402017
Is it possible to improve the quality of predictions from an “intelligent” use of multiple QSAR/QSPR/QSTR models?
K Roy, P Ambure, S Kar, PK Ojha
Journal of Chemometrics, e2992, 2018
1102018
How precise are our quantitative structure–activity relationship derived predictions for new query chemicals?
K Roy, P Ambure, S Kar
ACS omega 3 (9), 11392-11406, 2018
872018
The “double cross-validation” software tool for MLR QSAR model development
K Roy, P Ambure
Chemometrics and Intelligent Laboratory Systems 159, 108-126, 2016
852016
QSAR-Co: an open source software for developing robust multitasking or multitarget classification-based QSAR models
P Ambure, AK Halder, H Gonzalez Diaz, MNDS Cordeiro
Journal of chemical information and modeling 59 (6), 2538-2544, 2019
812019
Pharmacophore mapping-based virtual screening followed by molecular docking studies in search of potential acetylcholinesterase inhibitors as anti-Alzheimer's agents
P Ambure, S Kar, K Roy
Biosystems 116, 10-20, 2014
782014
Identifying natural compounds as multi-target-directed ligands against Alzheimer’s disease: an in silico approach
P Ambure, J Bhat, T Puzyn, K Roy
Journal of Biomolecular Structure and Dynamics 37 (5), 1282-1306, 2019
722019
Prediction reliability of QSAR models: an overview of various validation tools
P De, S Kar, P Ambure, K Roy
Archives of Toxicology 96 (5), 1279-1295, 2022
652022
In vitro evaluation and in silico screening of synthetic acetylcholinesterase inhibitors bearing functionalized piperidine pharmacophores
G Brahmachari, CY Choo, P Ambure, K Roy
Bioorganic & Medicinal Chemistry 23 (15), 4567-4575, 2015
542015
New workflow for QSAR model development from small data sets: Small dataset curator and small dataset modeler. Integration of data curation, exhaustive double cross-validation …
P Ambure, A Gajewicz-Skretna, MNDS Cordeiro, K Roy
Journal of Chemical Information and Modeling 59 (10), 4070-4076, 2019
482019
Understanding the structural requirements of cyclic sulfone hydroxyethylamines as hBACE1 inhibitors against Aβ plaques in Alzheimer's disease: a predictive QSAR approach
P Ambure, K Roy
RSC advances 6 (34), 28171-28186, 2016
312016
3D-QSAR and molecular docking analysis of biphenyl amide derivatives as p38α mitogen-activated protein kinase inhibitors
PS Ambure, RP Gangwal, AT Sangamwar
Molecular diversity 16 (2), 377-388, 2012
302012
Advances in quantitative structure–activity relationship models of anti-Alzheimer’s agents
P Ambure, K Roy
Expert opinion on drug discovery 9 (6), 697-723, 2014
292014
Turning deep-eutectic solvents into value-added products for CO2 capture: A desirability-based virtual screening study
AK Halder, P Ambure, Y Perez-Castillo, MNDS Cordeiro
Journal of CO2 Utilization 58, 101926, 2022
282022
Exploration of synthetic antioxidant flavonoid analogs as acetylcholinesterase inhibitors: An approach towards finding their quantitative structure–activity relationship
A Karmakar, P Ambure, T Mallick, S Das, K Roy, NA Begum
Medicinal Chemistry Research 28, 723-741, 2019
252019
CADD modeling of multi-target drugs against Alzheimer's disease
P Ambure, K Roy
Current Drug Targets 18 (5), 522-533, 2017
252017
Exploring structural requirements of leads for improving activity and selectivity against CDK5/p25 in Alzheimer's disease: an in silico approach
P Ambure, K Roy
RSC Advances 4 (13), 6702-6709, 2014
232014
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