AI3SD Video: Multiscale simulation of biomolecular mechanisms and dynamics: from enzyme evolution to receptor activation

Abstract

Simulations are revealing detailed mechanisms of biomolecular systems and functionally relevant dynamics, and contributing to enzyme design. Biomolecular simulations can be used as computational ‘assays’ of biological activity, e.g. to predict drug resistance or the effects of mutation. Molecular simulation methods of various types are now capable of modelling processes ranging from biochemical reactions to membrane dynamics, and offer increasing predictive power. Recently, this has included identifying key features of SARS-CoV-2 proteins. Molecular dynamics (MD) simulations on long timescales can model substrate binding, and reveal dynamical changes associated with thermoadaptation and directed evolution of enzyme catalytic activity. MD simulations can calculate thermodynamic properties such as activation heat capacities. Increasingly, simulations are contributing to the design and engineering of natural enzymes and de novo biocatalysts. Interactive MD simulation in virtual reality allows direct manipulation of biological macromolecules, going beyond mere visualization to allow e.g. fully flexible docking of drugs into protein targets such as the SARS-CoV-2 main protease. Groups of researchers can work together in the same virtual environment. Mechanisms of signal transduction in receptors can be studied by a combination of equilibrium and nonequilibrium MD simulations, e.g. identifying a general mechanism of signal propagation in nicotinic acetylcholine receptors. Different types of application (e.g. ranging from chemical reactions to signal transduction) require different levels of treatment, which can be combined in multiscale models to tackle a range of time- and length-scales, e.g. to study drug metabolism by cytochrome P450 enzymes combining coarse-grained and atomistic MD and QM/MM methods. By coupling together different levels of description, multiscale methods can address e.g. how chemical changes in individual molecules cause changes at larger scales. QM/MM methods are an archetype of multiscale methods in biochemistry and can be used for modelling transition states and reaction intermediates, to identify catalytic interactions, and to analyse determinants of reactivity. QM/MM modelling can identify mechanisms of covalent inhibition and predict the activity of bacterial enzymes against antibiotics. References ‘Evolution of dynamical networks enhances catalysis in a designer enzyme’ H.A. Bunzel et al. Nature Chemistry, in press (2021). https://www.biorxiv.org/content/10.1101/2020.08.21.260885v1 ‘Designing better enzymes: Insights from directed evolution’ HA Bunzel, JLR Anderson, AJ Mulholland Current Opinion in Structural Biology 67, 212-218 (2021) ‘Allosteric communication in class A β-lactamases occurs via cooperative coupling of loop dynamics’ I. Galdadas et al. eLife 10:e66567 DOI: 10.7554/eLife.66567 (2021) ‘Mechanism of covalent binding of ibrutinib to Bruton’s tyrosine kinase revealed by QM/MM calculations’ A Voice et al. Chemical Science https://doi.org/10.1039/D0SC06122K (2021) ‘Interactive Molecular Dynamics in Virtual Reality Is an Effective Tool for Flexible Substrate and Inhibitor Docking to the SARS-CoV-2 Main Protease’ HM Deeks et al. Journal of Chemical Information and Modeling 60, 5803-5814 (2020) https://doi.org/10.1021/acs.jcim.0c01030 ‘Molecular Simulations suggest Vitamins, Retinoids and Steroids as Ligands of the Free Fatty Acid Pocket of the SARS-CoV-2 Spike Protein’ D.K. Shoemark et al. 133, 7174-7186 (2021) ‘Biomolecular Simulations in the Time of COVID-19, and After’ R.E. Amaro & A.J. Mulholland Computing in Science & Engineering 22, 30-36 (2020) DOI: 10.1109/MCSE.2020.3024155

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Identifiers

ORCID for Samantha Kanza: orcid.org/0000-0002-4831-9489

ORCID for Jeremy G. Frey: orcid.org/0000-0003-0842-4302

ORCID for Mahesan Niranjan: orcid.org/0000-0001-7021-140X

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