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Sowmya Ramaswamy Krishnan
Sowmya Ramaswamy Krishnan
Researcher, TCS Research | PhD student, IIT Madras
Zweryfikowany adres z tcs.com
Tytuł
Cytowane przez
Cytowane przez
Rok
De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence
N Bung, SR Krishnan, G Bulusu, A Roy
Future Medicinal Chemistry 13 (6), 575-585, 2021
1172021
Accelerating De Novo Drug Design against Novel Proteins Using Deep Learning
SR Krishnan, N Bung, G Bulusu, A Roy
Journal of Chemical Information and Modeling 61 (2), 621-630, 2021
732021
De Novo Structure-Based Drug Design Using Deep Learning
SR Krishnan, N Bung, SR Vangala, R Srinivasan, G Bulusu, A Roy
Journal of Chemical Information and Modeling, 2021
582021
An In Silico Explainable Multi-Parameter Optimization Approach for De Novo Drug Design Against Proteins from Central Nervous System
N Bung, SR Krishnan, A Roy
Journal of Chemical Information and Modeling, 2022
172022
Reliable method for predicting the binding affinity of RNA-small molecule interactions using machine learning
SR Krishnan, A Roy, MM Gromiha
Briefings in Bioinformatics 25 (2), bbae002, 2024
122024
pBRICS: a novel fragmentation method for explainable property prediction of drug-like small molecules
SR Vangala, SR Krishnan, N Bung, R Srinivasan, A Roy
Journal of Chemical Information and Modeling 63 (16), 5066-5076, 2023
112023
Understanding drug resistance of wild-type and L38HL insertion mutant of HIV-1 C protease to saquinavir
S Venkatachalam, N Murlidharan, SR Krishnan, C Ramakrishnan, ...
Genes 14 (2), 533, 2023
92023
R-SIM: A database of binding affinities for RNA-small molecule interactions
SR Krishnan, A Roy, MM Gromiha
Journal of Molecular Biology, 2022
92022
A network-based approach reveals novel invasion and Maurer's clefts-related proteins in Plasmodium falciparum
D Das, SR Krishnan, A Roy, G Bulusu
Molecular Omics 15 (6), 431-441, 2019
82019
De novo design of anti-tuberculosis agents using a structure-based deep learning method
SR Krishnan, N Bung, S Padhi, G Bulusu, P Misra, M Pal, S Oruganti, ...
Journal of Molecular Graphics and Modelling, 2022
62022
Target-specific novel molecules with their recipe: incorporating synthesizability in the design process
SR Krishnan, N Bung, R Srinivasan, A Roy
Journal of Molecular Graphics and Modelling 129, 108734, 2024
42024
An Interpretable Machine Learning model for Selectivity of Small Molecules against Homologous Protein Family
SR Vangala, N Bung, SR Krishnan, A Roy
Future Medicinal Chemistry, 2022
42022
Computational resources for understanding the effect of mutations in binding affinities of protein–RNA complexes
K Harini, SR Krishnan, M Sekijima, MM Gromiha
PROTEIN MUTATIONS: Consequences on Structure, Functions, and Diseases, 151-170, 2025
32025
Generating novel leads for drug discovery using LLMs with logical feedback
SB Brahmavar, A Srinivasan, T Dash, SR Krishnan, L Vig, A Roy, R Aduri
Proceedings of the AAAI Conference on Artificial Intelligence 38 (1), 21-29, 2024
32024
Mechanism of drug resistance in HIV-1 protease subtype C in the presence of Atazanavir
SV Sankaran, SR Krishnan, Y Sayed, MM Gromiha
Current Research in Structural Biology 7, 100132, 2024
32024
AutoPLP: A Padlock Probe Design Pipeline for Zoonotic Pathogens
SR Krishnan, RRG Soares, N Madaboosi, MM Gromiha
ACS infectious diseases 9 (3), 459-469, 2023
22023
ZFP-CanPred: Predicting the effect of mutations in zinc-finger proteins in cancers using protein language models
A Phogat, SR Krishnan, M Pandey, MM Gromiha
Methods, 2025
2025
SYSTEMS AND METHODS FOR SYNTHESIS-AWARE GENERATION OF PROPERTY OPTIMIZED SMALL MOLECULES
SR Krishnan, A Roy, N Bung, R Srinivasan
US Patent App. 18/752,455, 2025
2025
Systems and methods for predicting potential inhibitors of target protein
ROY Arijit, SR KRISHNAN, B Navneet, G Bulusu
US Patent 12,190,999, 2025
2025
Structural Implications of HIV‐1 Protease Subtype C Bound to Darunavir: A Molecular Dynamics Study
S Venkatachalam, SR Krishnan, R Pandian, Y Sayed, MM Gromiha
Proteins: Structure, Function, and Bioinformatics, 2025
2025
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