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A metadynamics perspective on the reduction mechanism of the Pt(IV) asplatin prodrug
Author(s) -
Ponte Fortuna,
Piccini GiovanniMaria,
Sicilia Emilia,
Parrinello Michele
Publication year - 2020
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.26100
Subject(s) - metadynamics , chemistry , chemical space , ascorbic acid , reduction (mathematics) , mechanism (biology) , biological system , computer science , linear discriminant analysis , dimensionality reduction , computational chemistry , curse of dimensionality , molecular dynamics , mathematics , artificial intelligence , drug discovery , physics , biochemistry , food science , geometry , biology , quantum mechanics
Enhanced sampling molecular dynamics has been used to model the reduction mechanism of the antitumoral Asplatin Pt(IV) complex, c,c,t‐[PtCl2(NH3)2(OH)(aspirin)] in the presence of l ‐ascorbic acid as reducing agent. In order to overcome the timescale problem, characteristic of many chemical reactions, we enhanced the sampling of the free energy landscape using Metadynamics. To achieve such a goal, the selection of adequate collective variables is crucial for the application of the method. Recently, a new method called Multi‐Class Harmonic Linear Discriminant Analysis (MC‐HLDA) has been proposed as a tool for constructing collective variables (CVs) for complex chemical processes. The method reduces the dimensionality of the variable space by generating appropriate linear combinations of several relevant chemical descriptors. The aim of this work is to assess the ability and performance of this method in describing the fundamental features of complex chemical reactions such as the Asplatin reduction mechanism in a compact, simple, and physically transparent manner. © 2019 Wiley Periodicals, Inc.