2024

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• Prathith's  work on "AlphaMut: A Deep Reinforcement Learning Model to Suggest Helix-Disrupting Mutations. " accepted and published online in JCTC special issue:

       https://doi.org/10.1021/acs.jctc.4c01387

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• Bikirna and Hridya's work on using Memory effects to explain Internal Friction is published in JPCB:

       https://doi.org/10.1021/acs.jpcb.4c05394

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• Amal's work on beta-catenin published in PCCP: Unraveling the folding-assisted unbinding mechanism of TCF with its binding partner ß-catenin.

        https://doi.org/10.1039/D4CP01451K

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• Amal successfully defended his Ph.D. thesis

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• SPOTLIGHT: Sreyas's work on combining Reinforcement Learning with Physics based de novo Drug Design  accepted in Digital Discovery.

       https://doi.org/10.1039/D3DD00194F

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   2023

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• Amal's work published in ACS Applied Bio Materials:

      "Targeting RdRp of SARS-CoV-2 with De Novo 

       Molecule Generation"

      

       https://doi.org/10.1021/acsabm.3c00339

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• Our Collaborative work accepted in Chemical Science:

      "Engineered vitamin E-tethered non-immunogenic facial           lipopeptide for developing improved siRNA based      

      combination therapy against metastatic breast cancer."

      Chemical Science (accepted).

      

       https://doi.org/10.1039/D3SC01071F

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• Sreyas was awarded the "Best MS Thesis Award" in Chemistry.​