VMD as a Platform for Interactive Small Molecule Preparation and Visualization in Quantum and Classical Simulations

• Published in: Journal of chemical information and modeling Vol. 63; no. 15; pp. 4664 - 4678
• Main Authors: Spivak, Mariano, Stone, John E., Ribeiro, João, Saam, Jan, Freddolino, Peter L., Bernardi, Rafael C., Tajkhorshid, Emad
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 14.08.2023
• Subjects: Biomolecules; Biophysics; Chlamydomonas reinhardtii - chemistry; Computational Chemistry; Models, Molecular; Molecular Dynamics Simulation; Quantum mechanics; Quantum Theory; SARS-CoV-2 - chemistry; Simulation; Small Molecule Libraries - chemistry; Software; Visualization
• ISSN: 1549-9596; 1549-960X; 1549-960X
• DOI: 10.1021/acs.jcim.3c00658

Modeling and simulation of small molecules such as drugs and biological cofactors have been both a major focus of computational chemistry for decades and a growing need among computational biophysicists who seek to investigate the interaction of different types of ligands with biomolecules. Of particular interest in this regard are quantum mechanical (QM) calculations that are used to more accurately describe such small molecules, which can be of heterogeneous structures and chemistry, either in purely QM calculations or in hybrid QM/molecular mechanics (MM) simulations. QM programs are also used to develop MM force field parameters for small molecules to be used along with established force fields for biomolecules in classical simulations. With this growing need in mind, here we report a set of software tools developed and closely integrated within the broadly used molecular visualization/analysis program, VMD, that allow the user to construct, modify, and parametrize small molecules and prepare them for QM, hybrid QM/MM, or classical simulations. The tools also provide interactive analysis and visualization capabilities in an easy-to-use and integrated environment. In this paper, we briefly report on these tools and their major features and capabilities, along with examples of how they can facilitate molecular research in computational biophysics that might be otherwise prohibitively complex.