The electronic structure of genome editors from the first principles

Author:

Nierzwicki ŁukaszORCID,Ahsan MohdORCID,Palermo GiuliaORCID

Abstract

Abstract Ab-initio molecular dynamics enables following the dynamics of biological systems from the first principles, describing the electronic structure and offering the opportunity to “watch” the evolution of biochemical processes with unique resolution, beyond the capabilities of state-of-the-art experimental techniques. This article reports the role of first-principles (ab-initio) molecular dynamics (MD) in the CRISPR-Cas9 genome editing revolution, achieving a profound understanding of the enzymatic function and offering valuable insights for enzyme engineering. We introduce the methodologies and explain the use of ab-initio MD simulations to establish the two-metal dependent mechanism of DNA cleavage in the RuvC domain of the Cas9 enzyme, and how a second catalytic domain, HNH, cleaves the target DNA with the aid of a single metal ion. A detailed description of how ab-initio MD is combined with free-energy methods—i.e., thermodynamic integration and metadynamics—to break and form chemical bonds is given, explaining the use of these methods to determine the chemical landscape and establish the catalytic mechanism in CRISPR-Cas9. The critical role of classical methods is also discussed, explaining theory and application of constant pH MD simulations, used to accurately predict the catalytic residues’ protonation states. Overall, first-principles methods are shown to unravel the electronic structure and reveal the catalytic mechanism of the Cas9 enzyme, providing valuable insights that can serve for the design of genome editing tools with improved catalytic efficiency or controllable activity.

Funder

NIH

NSF

Publisher

IOP Publishing

Subject

Electrochemistry,Materials Chemistry,Electrical and Electronic Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machines on Genes through the Computational Microscope;Journal of Chemical Theory and Computation;2023-03-22

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