About
PMX is a service for users who need to do free energy calculations. Free energy calculations are extremely common in life sciences research. In molecular dynamics simulations, such as investigating how mutations affect protein function, these calculations provide insight into stability and affinity changes.
One important branch of free energy calculations involves alchemical transformations such as the mutation of amino acids, nucleic acids or ligand modifications. A challenging aspect of these calculations is the creation of associated structures and molecular topologies. PMX provides an automated framework for the system setup and analysis for all these various kinds of mutation. Several state-of-the-art force fields are supported that can be used in the GROMACS molecular dynamics package.
As well as implementing the new web-based features, the core PMX functionality – hybrid structure/topology generation – was also expanded. In addition to the already established ability to process amino acid mutations, PMX was also extended to handle DNA nucleotide alchemical transformations, and ligand relative and absolute binding free energy calculations. The protein-ligand alchemy employing the open-source PMX tool has great potential in the computer-aided drug discovery pipeline.
Alchemical free energy calculations using PMX
Whether you are new to PMX or you already have some experience, we have collated a number of relevant learning and support resources to help you out. Access the PMX documentation, dedicated support forum, lectures, tutorials and more!
Find out more about our user-driven development plans for PMX which feature four main categories: core code and usability, mutation libraries, features and documentation. A roadmap with timelines extending until the end of 2026 is presented.
Licensing
PMX is free to use. Please cite the below references when publishing your work using PMX.
References
Gapsys & de Groot (2017) J. Chem. Inf. Mod. 2:109-114 (DOI: 10.1021/acs.jcim.6b00498)
Gapsys et al. (2015) J. Comput. Chem. 36:348-354 (DOI: 10.1002/jcc.23804).
Gapsys et al. (2014) Molecular Modeling of Proteins 173–209 (DOI: 10.1007/978-1-4939-1465-4_9)
