SwissParam: A fast force field generation tool for small organic molecules

TLDR

Computational ligand‑ and structure‑based methods have transformed drug discovery by accelerating lead identification and optimization, but they require force‑field parameterization for many small molecules used in docking and binding‑free‑energy calculations. This study introduces SwissParam, a rapid force‑field generation tool that produces topologies and parameters for arbitrary small organic molecules based on the Merck force field and compatible with CHARMM. SwissParam generates CHARMM‑compatible parameters that can be used with CHARMM or GROMACS, are integrated into the EADock2 and EADock DSS docking workflows, and enable a short‑minimization binding‑free‑energy approach for ligand–protein complexes, and is freely available to academics at www.swissparam.ch. Using SwissParam, docking success rates of 56–78 % were achieved and a rapid binding‑free‑energy method reproduced experimental energies for 214 complexes with a standard error of 2.0 kcal mol⁻¹ and a correlation coefficient.

Abstract

Abstract The drug discovery process has been deeply transformed recently by the use of computational ligand‐based or structure‐based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure‐based computational methods for drug discovery mainly involve ligand‐protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand‐protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol −1 , and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer‐aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch . © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011