Literature DB >> 30938544

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

Jacopo Sgrignani1, Lorenzo Casalino2, Fabio Doro3, Angelo Spinello3, Alessandra Magistrato3.   

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.

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

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Year:  2019        PMID: 30938544     DOI: 10.4155/fmc-2018-0495

Source DB:  PubMed          Journal:  Future Med Chem        ISSN: 1756-8919            Impact factor:   3.808


  1 in total

1.  Targeting Orthosteric and Allosteric Pockets of Aromatase via Dual-Mode Novel Azole Inhibitors.

Authors:  Jessica Caciolla; Angelo Spinello; Silvia Martini; Alessandra Bisi; Nadia Zaffaroni; Silvia Gobbi; Alessandra Magistrato
Journal:  ACS Med Chem Lett       Date:  2020-03-23       Impact factor: 4.345

  1 in total

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