Open Source Python Molecular Mechanics Software

This is a collection of software modifications created to integrate NanoEngineer-1, PACKMOL and MSI2LMP for the purpose of easily creating molecular dynamics cells. NanoEngineer-1 is a molecular CAD software written by Nanorex and provides the user an easy way to create molecules, while the software modifications allow the user to type atoms using multiple force fields. PACKMOL can generate a random collection of molecules using the molecule templates from NanoEngineer-1 thus providing the initial MD cell. Modifications to PACKMOL allow the atom type data to be passed through to the MSI2LMP software. MSI2LMP creates a LAMMPS input file based on class I or class II force fields. MSI2LMP was modified to use numerically coded force field data generated by NanoEngineer-1. The MMP file format was extended and integrated into all three software applications. http://www.nanoengineer-1.net http://www.ime.unicamp.br/~martinez/packmol/ http://lammps.sandia.gov/

We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing and analyzing molecular simulations, in particular of systems of biological relevance. It focuses on a wide availability of algorithms for (advanced) sampling and is capable of combining Monte Carlo and molecular dynamics in seamless fashion. CAMPARI offers the user a very high level of control over all implemented features. For more information and features, please refer to the project's homepage at http://campari.sourceforge.net/V5

ChemTraYzer creates reaction models from molecular dynamics simulations. It's available as open software (MIT license). Please find a full description @ https://www.ltt.rwth-aachen.de/cms/LTT/Forschung/Forschung-am-LTT/Model-Based-Fuel-Design/Aktuelle-Projekte/~kqbf/ChemTraYzer/lidx/1 M.Döntgen, M.-D.Przybylski-Freund, L.C.Kröger, W.A.Kopp, A.E.Ismail, K.Leonhard, "Automated Discovery of Reaction Pathways, Rate Constants, and Transition States Using Reactive Molecular Dynamics Simulations", J. Chem. Theory Comput. 11 (2015), 2517-2524 L.C.Kröger, W.A.Kopp, M.Döntgen, K.Leonhard, "Assessing Statistical Uncertainties of Rare Events in Reactive Molecular Dynamics Simulations", J. Chem. Theory Comput. 13 (2017), 3955-3960 M.Döntgen, F.Schmalz, W.A.Kopp, L.C.Kröger, K.Leonhard, "Automated Chemical Kinetic Modeling via Hybrid Reactive Molecular Dynamics and Quantum Chemistry Simulations", J. Chem. Inf. Model. 58 (2018), 1343-1355 Check the Wiki for bug reports and fixes.

This python package aims to help people set up and analyze molecular dynamics simulations in aqueous-organic solvent mixtures. See D. Alvarez-Garcia et al. Journal of Medicinal Chemistry, 2014.

We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. In silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization.

MDcons is a tool to analyze conserved contacts during Molecular Dynamics (MD) simulations of Protein, Rna, Dna & Ligand based complexes. The input is either a Molecular Dynamics trajectory or a set of snapshots. The input can also be a single snapshot. The outputs are (1) map of most/less frequently conserved contacts during MD (2) a list of most/less frequently conserved contacts during MD.

Molecular Interaction Potential Generator MIPGEN is a python program that will calculate Molecular Interaction Potential grids over a given molecule, that could be either a protein or a small organic compound (drug). The output will be a series of grids with DX format (*.dx) that the user will be able to visualize using any Molecular visualization program like VMD, PyMol, Chimera... For more information on dependencies and usage, please read the Documentation. Users are welcome to post any bug or request under BUGS & REQUESTS menu. (sourceforge account will be needed).

ParamIT is a toolkit aiding the development of molecular mechanical force field parameterization of small, drag like, molecules within CHARMM general force field (CGenFF) protocol. The developed toolkit helps the researchers in following ways: 1) automating the creation of multiple input files for quantum and molecular mechanics programs, 2) automating the output analysis and 3) substitute the use of full MM programs with a faster specialized one. The developed tools include: 1) generator of molecule-water complexes with graphical user interface (GUI), 2) semi-automatic frequency analysis using symbolic potential energy distribution matrix and comparison of optimized internal coordinates, 3) GUI for charge fitting with three modes: manual, Monte-Carlo sampling or brute force, and 4) GUI for dihedral terms fitting. The usage of these tools decreases the labor effort, lowers manual input errors and reduces the time needed for accurate MM parameterization efforts.

PyBrella is a script designed to automate the umbrella sampling process, using the AMBER molecular dynamics package.

QDC (quick direct-method controlled) is an optimized exact implementation of the Gillespie's direct-method. It is designed for biochemical simulations when there is the need of dynamic parameters whose values can change during the simulation.

xPyder is a PyMOL plugin to analyze and visualize on the 3D structure dynamical cross-correlation matrices (DCCM), linear mutual information (LMI), communication propensities (CP), intra- and inter-molecular interactions (e.g. PSN), and more, to produce highly customizable publication-quality images. xPyder identifies networks (using concepts from graph theory, such as hubs and shortest path searching), compares matrices and focuses the analysis on relevant information by filtering the data using a modular, user-expandable plugin system that takes advantage of structural and dynamical information, contributing to bridge the gap between dynamical and mechanical properties at the molecular level.