
Krishnendu Sinha
@krish_theorchem
ID: 1329719905491554305
20-11-2020 09:35:23
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A press release from DSTIndia highlights the research carried out at S.N. Bose National Centre for Basic Sciences. Team of Prof. Ranjit Biswas and Dr. Suman Chakrabarty elucidates the molecular mechanism of substrate promiscuity in the enzyme Laccase. Read here: pib.gov.in/PressReleasePa… DSTIndia chandra Srivari



Just published nature New evidence from 70 years ago: Rosalind Franklin was a co-discoverer of DNA's double-helix structure by Matthew Cobb Nathaniel Comfort nature.com/articles/d4158…



New artificial #light-#harvesting system using organic #nanotubes useful for solar cells, photocatalysis, #optical #sensors & tunable multi-color light emitting #materials . Dr Jitendra Singh chandra Srivari S.N. Bose National Centre for Basic Sciences IISER Kolkata 🔗dst.gov.in/new-artificial…





Thanks to Ruth Nussinov for bringing this exciting yet challenging problem to our attention. All the credits go to the hard work and patience of Amit Krishnendu Sinha. Thanks to SERB DSTIndia S.N. Bose National Centre for Basic Sciences for support. #compchem

Leveraging Bidirectional Nature of Allostery To Inhibit Protein–Protein Interactions (PPIs): A Case Study of PCSK9–LDLR Interaction JCIM & JCTC Journals Krishnendu Sinha Ipsita Basu Thanks to S.N. Bose National Centre for Basic Sciences SERB and Sarfez Cure for funding #compchem doi.org/10.1021/acs.jc…



Leveraging Bidirectional Nature of Allostery To Inhibit Protein–Protein Interactions (PPIs): A Case Study of PCSK9–LDLR Interaction #MolecularDynamics #MSM pubs.acs.org/doi/10.1021/ac… Krishnendu Sinha Ipsita Basu j #JCIM Vol64 Issue9 #compchem



Our "WeTICA" paper is finally out in The Journal of Chemical Physics. I am particularly excited about this work, because this is our first published foray into computational method development, particularly in the context of enhanced sampling of rare event processes. #compchem We have implemented a



One order parameter to rule them all! Well, just two! 😉 Our "IceCoder" ML framework combines SOAP descriptors with variational autoencoder (VAE) to distinguish and track a large number of ice phases (and liquid water) in mixed phase MD simulation trajectories. JCIM & JCTC Journals

