Skip to main navigation Skip to search Skip to main content

Multiscale Workflow for Modeling Ligand Complexes of Zinc Metalloproteins

Zongfan Yang, Rebecca M Twidale, Silvia Gervasoni, Reynier Suardíaz, Charlotte K Colenso, Eric J M Lang, James Spencer, Adrian J Mulholland

Research output: Contribution to journalArticle (Academic Journal)peer-review

15 Citations (Scopus)
199 Downloads (Pure)

Abstract

Zinc metalloproteins are ubiquitous, with protein zinc centers of structural and functional importance, involved in interactions with ligands and substrates and often of pharmacological interest. Biomolecular simulations are increasingly prominent in investigations of protein structure, dynamics, ligand interactions, and catalysis, but zinc poses a particular challenge, in part because of its versatile, flexible coordination. A computational workflow generating reliable models of ligand complexes of biological zinc centers would find broad application. Here, we evaluate the ability of alternative treatments, using (nonbonded) molecular mechanics (MM) and quantum mechanics/molecular mechanics (QM/MM) at semiempirical (DFTB3) and density functional theory (DFT) levels of theory, to describe the zinc centers of ligand complexes of six metalloenzyme systems differing in coordination geometries, zinc stoichiometries (mono- and dinuclear), and the nature of interacting groups (specifically the presence of zinc-sulfur interactions). MM molecular dynamics (MD) simulations can overfavor octahedral geometries, introducing additional water molecules to the zinc coordination shell, but this can be rectified by subsequent semiempirical (DFTB3) QM/MM MD simulations. B3LYP/MM geometry optimization further improved the accuracy of the description of coordination distances, with the overall effectiveness of the approach depending upon factors, including the presence of zinc-sulfur interactions that are less well described by semiempirical methods. We describe a workflow comprising QM/MM MD using DFTB3 followed by QM/MM geometry optimization using DFT (e.g., B3LYP) that well describes our set of zinc metalloenzyme complexes and is likely to be suitable for creating accurate models of zinc protein complexes when structural information is more limited.

Original languageEnglish
Pages (from-to)5658-5672
Number of pages15
JournalJournal of Chemical Information and Modeling
Volume61
Issue number11
Early online date8 Nov 2021
DOIs
Publication statusPublished - 22 Nov 2021

Bibliographical note

Funding Information:
The authors thank the China Scholarship Council and the U.K. Engineering and Physical Sciences Research Council (EPSRC) for funding studentships to Z.Y. and R.M.T., respectively. This work was supported by the U.K. Biotechnology and Biological Sciences Research Council (BBSRC)-funded SouthWest Biosciences Doctoral Training Partnership (training grant reference BB/J014400/1). A.J.M. thanks EPSRC and BBSRC for funding (Grant Numbers EP/M022609/1, EP/M013219/1, BB/M000354/1, and BB/L01386X/1), and R.S. thanks RSC for Research Funds (Grants R19-3409 and R20-6912) and MCIN/AEI/10.13039/501100011033 (Grant PID2020-113147GA-I00). This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (NIH) to J.S. under Award Number R01AI100560. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Publisher Copyright:
© 2021 American Chemical Society.

Research Groups and Themes

  • Physical & Theoretical

Keywords

  • Zinc
  • Metalloenzyme
  • Molecular Dynamics
  • DFTB3
  • QM/MM
  • Metallo-beta-lactamase

Fingerprint

Dive into the research topics of 'Multiscale Workflow for Modeling Ligand Complexes of Zinc Metalloproteins'. Together they form a unique fingerprint.

Cite this