msld-py-prep scripts for creating a multiple topology model for Multisite λ-Dynamics (MSλD) in CHARMM.
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 compatible files to use for MSλD simulations, including an example CHARMM input script.
You can start using the scripts by cloning this repository and following the tutorial in the examples directory:
git clone https://github.com/Vilseck-Lab/msld-py-prep.git
cd msld-py-prep
We suggest installing a conda environment built using the requirements.txt file:
conda create --name <env> --file requirements.txt --channel schrodinger
To activate:
conda activate <env>
This installs the correct pandas version, RDKit, and PyMOL.
The following are some other considerations:
- Lg_Solvate.sh uses convpdb.pl from the MMTSB toolset
- vis_check.py is written for use with PyMOL
Please see the examples directory for a detailed tutorial.
Please cite the following reference: "Optimizing Multisite λ-Dynamics Throughput with Charge Renormalization" Jonah Z. Vilseck, Luis F. Cervantes, Ryan L. Hayes, and Charles L. Brooks Journal of Chemical Information and Modeling 2022 62 (6), 1479-1488; DOI: 10.1021/acs.jcim.2c00047
These scripts are provided as is and are subject to future modification.