How to Model for a Living: The CSGF as a Catalyst for Supermodels

Abstract

Models are ubiquitous and uniting tools for computational scientists across disciplines. As a computational biophysical chemist, I apply multiple models to understand and predict how molecules recognize and interact with each other in complex, dynamic biological environments. The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) cultivates interest in engaging in models from an multidisciplinary perspective and enables junior scientists to see how computational modeling is a creative and collaborative process. Below, I describe ways, based in part on my own experiences as a CSGF recipient, in which modeling can be used both to understand the molecular world and to excite others about computational science.

Figure 1.

Example of a “toy” model system with two bound “molecules” shown in red and blue. Figure created by Andrea Jacobs. Adapted with permission from Radhakrishnan, M.L. and Tidor, B. J. Phys. Chem. B, 111:13419–13435, 2007 and Radhakrishnan, M.L. and Tidor, B. J. Chem. Inf. Model., 48:1055–1073, 2008. Copyright 2007 and 2008 American Chemical Society.

Figure 2.

Sample crowded system with the barnase–barstar system shown in blue and red and the surrounding crowders modeled as orange spheres whose size and density can be systematically varied. Figure created by Helena Qi and related in content and appearance to figures in Qi et al.,[7] under CC-BY 4.0 license, https://creativecommons.org/licenses/by/4.0/

Figure 3.

Sample snapshot from a molecular dynamics (MD) simulation showing the peptide buforin-2 (red) in complex with DNA (blue) in a crowded environment. The crowders here are lysozyme proteins, shown in various colors. Adapted with permission from Perez, C.P., Elmore, D.E., and Radhakrishnan, M.L. J. Phys. Chem. B. 123: 10718–10734, 2019. Copyright 2019 American Chemical Society.