Can multiscale simulations unravel the function of metallo-enzymes to improve knowledge-based drug discovery?

Future Med Chem. 2019 Apr;11(7):771-791. doi: 10.4155/fmc-2018-0495. Epub 2019 Apr 2.

Abstract

Metallo-enzymes are a large class of biomolecules promoting specialized chemical reactions. Quantum-classical quantum mechanics/molecular mechanics molecular dynamics, describing the metal site at quantum mechanics level, while accounting for the rest of system at molecular mechanics level, has an accessible time-scale limited by its computational cost. Hence, it must be integrated with classical molecular dynamics and enhanced sampling simulations to disentangle the functions of metallo-enzymes. In this review, we provide an overview of these computational methods and their capabilities. In particular, we will focus on some systems such as CYP19A1 a Fe-dependent enzyme involved in estrogen biosynthesis, and on Mg2+-dependent DNA/RNA processing enzymes/ribozymes and the spliceosome, a protein-directed ribozyme. This information may guide the discovery of drug-like molecules and genetic manipulation tools.

Keywords: CYP19A1; DNA processing enzymes; Metallo-proteins; QM/MM molecular dynamics; drug discovery; ribozyme; spliceosome; steroid synthesis.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Aromatase / chemistry
  • Aromatase / metabolism
  • Biosynthetic Pathways
  • Catalytic Domain
  • DNA / metabolism
  • Density Functional Theory
  • Drug Discovery
  • Enzymes / chemistry*
  • Enzymes / metabolism*
  • Metals / chemistry*
  • Metals / metabolism*
  • Models, Molecular*
  • Protein Binding
  • Protein Conformation
  • RNA / metabolism
  • RNA, Catalytic / chemistry
  • RNA, Catalytic / metabolism
  • Structure-Activity Relationship
  • Thermodynamics

Substances

  • Enzymes
  • Metals
  • RNA, Catalytic
  • RNA
  • DNA
  • Aromatase
  • CYP19A1 protein, human