- Vilseck, J. Z.; Cervantes, L. F.; Hayes, R. L.; Brooks, C. L., III. Optimizing Multisite lambda-Dynamics Throughput with Charge Renormalization. J Chem Inf Model 2022, 62 (6), 1479-1488. DOI: 10.1021/acs.jcim.2c00047
A collection of python scripts and procedures to enable the building of ligands for Multisite λ-Dynamics (MSλD) simulations using CHARMM/pyCHARMM
msld-prep was developed within the Brooks Research Group at the University of Michigan and is currently overseen by Jonah Vilseck at Indiana Univerity School of Medicine.
To download the msld-prep GitHub repository (housed on Jonah's site) execute the command: git clone [email protected]:Vilseck-Lab/msld-py-prep.git.
msld-prep is an integral component of running MSλD in CHARMM/pyCHARMM, software availble free of charge for academic and government laboratories.
msld-py-prep scripts assist in creating a multiple topology model for Multisite λ-Dynamics (MSλD) in CHARMM and pyCHARMM.
These scripts identify common atoms (similar partial atomic charge and identical atom types) across different compounds of interest with a maximum common substructure search. A charge renormalization algorithm is then implemented to generate a set of partial atomic charges suitable for multisite sampling of many chemical functional groups with MSλD.
The output is a directory of CHARMM (and pyCHARMM) compatible files to use for MSλD simulations, including an example CHARMM input script.
retreiveSubmodule.sh