G
Gopalakrishnan Bulusu
Researcher at Tata Consultancy Services
Publications - 37
Citations - 635
Gopalakrishnan Bulusu is an academic researcher from Tata Consultancy Services. The author has contributed to research in topics: Porphobilinogen & Hydroxymethylbilane Synthase. The author has an hindex of 12, co-authored 34 publications receiving 432 citations. Previous affiliations of Gopalakrishnan Bulusu include University of Hyderabad & Harvard University.
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MD simulations of ligand-bound and ligand-free aptamer: Molecular level insights into the binding and switching mechanism of the add A-riboswitch
TL;DR: The results of 15-nsec-long explicit-solvent molecular dynamics simulations of the add A-riboswitch crystal structure are reported, revealing the interaction network responsible for, and conformational changes associated with, the communication between the binding pocket and the expression platform.
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De novo design of new chemical entities for SARS-CoV-2 using artificial intelligence.
TL;DR: De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence
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Understanding the thermostability and activity of Bacillus subtilis lipase mutants: insights from molecular dynamics simulations.
TL;DR: The authors' analysis indicates the possibility of nonadditive effects of point mutations on the conformational stability of LTMs, and suggests the LTMs having marginally higher thermostabilities than WT show greater probabilities of accessing non-native conformations, which have reduced possibilities of reverting to their respective native states under refolding conditions.
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New styryl sulfones as anticancer agents
Manohar Sharma Vedula,Aravinda B. Pulipaka,Chandrasekhar Venna,Vamsee Krishna Chintakunta,Sreenu Jinnapally,Venkata Adiseshu Kattuboina,Ravikrishna Vallakati,Vishnu Basetti,Venkateswarlu Akella,Sriram Rajgopal,Ajaya Kumar Reka,Sravan Kumar Teepireddy,Prem Kumar Mamnoor,Ramanujam Rajagopalan,Gopalakrishnan Bulusu,Akash Khandelwal,Vijay V. Upreti,Srinivas Rao Mamidi +17 more
TL;DR: New styryl sulfone compounds have been synthesized and evaluated for their anti-proliferative activity and one compound has shown 51% tumor growth inhibition in mice implanted with HT-29 human carcinoma at 400 mg kg(-1) orally.
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Accelerating De Novo Drug Design against Novel Proteins Using Deep Learning.
TL;DR: In this article, the potential of deep learning and molecular modeling approaches was leveraged to develop a drug design pipeline, which can be useful for cases where there is limited or no availability of target-specific ligand datasets.