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Sudipto Mukherjee

Researcher at Temple University

Publications -  14
Citations -  1759

Sudipto Mukherjee is an academic researcher from Temple University. The author has contributed to research in topics: Docking (molecular) & Helix. The author has an hindex of 12, co-authored 14 publications receiving 1478 citations. Previous affiliations of Sudipto Mukherjee include Stony Brook University & Statistics Finland.

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DOCK 6: Combining techniques to model RNA–small molecule complexes

TL;DR: A test set of RNA-ligand complexes is compiled to validate the ability of the DOCK suite of programs to successfully recreate experimentally determined binding poses and indicates that DOCK can indeed be useful for structure-based drug design aimed at RNA.
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DOCK 6: Impact of new features and current docking performance

TL;DR: This manuscript presents the latest algorithmic and methodological developments to the structure‐based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry‐corrected root‐mean‐square deviation algorithm, a database filter, and docking forensic tools.
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Docking Validation Resources: Protein Family and Ligand Flexibility Experiments

TL;DR: A database consisting of 780 ligand-receptor complexes, termed SB2010, has been derived from the Protein Databank to evaluate the accuracy of docking protocols for regenerating bound ligand conformations, revealing family-based success appears largely independent of ligand flexibility, suggesting a strong dependence on the binding site environment.
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Evaluation of DOCK 6 as a pose generation and database enrichment tool

TL;DR: Overall, the breadth and number of experiments performed provide a useful snapshot of current capabilities of DOCK6 as well as starting points to guide future development efforts to further improve sampling and scoring.
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Bridging Microscopic and Macroscopic Mechanisms of p53-MDM2 Binding with Kinetic Network Models

TL;DR: New ways in which microscopic models of peptide binding, coupled with simple few-state binding flux models, can be used to understand biological function in physiological contexts are suggested.