The development of g_mmpbsa package is initiated under Open Source Drug Discovery Consortium (OSDD), which is a collaborative platform to design and discover new drugs for neglected tropical diseases such as Malaria, Tuberculosis, Leshmaniasis etc.
The tool calculates components of binding energy using MM-PBSA method except the entropic term and energetic contribution of each residue to the binding using energy decomposition scheme.
The output from the tool is used further as input in python scripts which is provided in this package, to get the final binding energy and energetic contribution of each residue.
Kindly post problems and queries in g_mmpbsa forum, we will try our best to provide the solution.
Kumari et al (2014) g_mmpbsa - A GROMACS tool for high-throughput MM-PBSA calculations. J. Chem. Inf. Model. 54:1951-1962.
Baker et al. (2001) Electrostatics of nanosystems: Application to microtubules and the ribosome. Proc. Natl. Acad. Sci. USA 98:10037-10041.
It is an open source tool and can be modified under the terms of the GNU public license
Supports GROMACS 4.5.x, 4.6.x, GROMACS 5.0.x and GROMACS 5.1.x versions.
Supports APBS 1.2.x, 1.3.x and 1.4.x versions
Inherits APBS capability of parallel computation using OpenMP. See details here.
Supports external APBS execuatble with mpirun for parallel computation on HPC. See details here.
Options for van der Waal radii that are used for solvation free energy calculation using implicit solvent models.
Options for several non-polar solvation model such as SASA, SAV and Weeks–Chandler–Andersen (WCA).
Options for calculating contribution of each residue in the net binding energy.
Simultaneous computations of binding energy components and residue wise energy contribution, and thus it is computationally less expensive.
This tool can be modified and/or redistributed under terms of GNU public license.
Pronk et al. (2013) GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29:845-854.
Eisenhaber et al. (1995) The double cubic lattice method: Efficient approaches to numerical integration of surface area and volume and to dot surface contouring of molecular assemblies. J. Comput. Chem. 16:273-284.
Wagoner et al. (2006) Assessing implicit models for nonpolar mean solvation forces: The importance of dispersion and volume terms. Proc. Natl. Acad. Sci. USA 103:8331-8336.