R
Ruchika Bhat
Researcher at Indian Institute of Technology Delhi
Publications - 14
Citations - 61
Ruchika Bhat is an academic researcher from Indian Institute of Technology Delhi. The author has contributed to research in topics: Hepatitis B virus & Medicine. The author has an hindex of 4, co-authored 10 publications receiving 30 citations. Previous affiliations of Ruchika Bhat include Indian Institutes of Technology.
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Improving the binding affinity estimations of protein–ligand complexes using machine-learning facilitated force field method
TL;DR: A new scoring function Bappl+ is presented that is designed to predict the binding affinities of non-metallo and metallo PL complexes and outperforms other state-of-the-art scoring functions, achieving a high Pearson correlation coefficient.
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Toward development of generic inhibitors against the 3C proteases of picornaviruses.
Kamalika Banerjee,Ruchika Bhat,V. U. Bhaskara Rao,Anshu Nain,Kartik Lakshmi Rallapalli,Sohona Gangopadhyay,Ravi P. Singh,Manidipa Banerjee,Bhyravabhotla Jayaram +8 more
TL;DR: This work has targeted the 3C protease of Hepatitis A Virus, a feco‐orally transmitted virus of the family Picornaviridae, for identification of potential antivirals and identified a few compounds which could inhibit HAV 3C activity.
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Discovery of small molecule inhibitors of chikungunya virus proteins (nsP2 and E1) using in silico approaches.
TL;DR: The present study identified twenty plant bioactive compounds that are available at low price and do not have associated adverse effect against Chikungunya virus, and reveals five potential lead compounds having high binding energy that can help in the development of commercial drugs with favorable ADMET characteristic.
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Epidemiology and molecular characterization of chikungunya virus from human cases in North India, 2016.
Naushad Khan,Ruchika Bhat,Vineet Jain,Siva Raghavendhar B,Ashok Kumar Patel,Kaustuv Nayak,Anmol Chandele,Kaja Murali-Krishna,Pratima Ray +8 more
TL;DR: In this paper, epidemiology and molecular characterization of three whole-genome sequences of chikungunya virus and assessed phylogenetic analysis, physiological properties, antigenicity, and B-cell epitope prediction by in silico.
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A comprehensive automated computer-aided discovery pipeline from genomes to hit molecules
Ruchika Bhat,Rahul Kaushik,Ankita Singh,Debarati DasGupta,Abhilash Jayaraj,Anjali Soni,Ashutosh Shandilya,Vandana Shekhar,Shashank Shekhar,Bhyravabhotla Jayaram +9 more
TL;DR: Dhanvantari, a comprehensive software suite which automates the journey from genomes to hit molecules via its various modules such as gene finding, computational structural study of target proteins and virtual screening/identification of hit molecules for computer aided drug discovery is proposed.