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DockOnSurf: A Python Code for the High-Throughput Screening of Flexible Molecules Adsorbed on Surfaces.
Martí, Carles; Blanck, Sarah; Staub, Ruben; Loehlé, Sophie; Michel, Carine; Steinmann, Stephan N.
Afiliação
  • Martí C; Univ Lyon, Ens de Lyon, CNRS UMR 5182, Laboratoire de Chimie, F69342 Lyon, France.
  • Blanck S; Total Marketing & Services, Chemin du Canal-BP 22, 69360 Solaize, France.
  • Staub R; Univ Lyon, Ens de Lyon, CNRS UMR 5182, Laboratoire de Chimie, F69342 Lyon, France.
  • Loehlé S; Total Marketing & Services, Chemin du Canal-BP 22, 69360 Solaize, France.
  • Michel C; Univ Lyon, Ens de Lyon, CNRS UMR 5182, Laboratoire de Chimie, F69342 Lyon, France.
  • Steinmann SN; Univ Lyon, Ens de Lyon, CNRS UMR 5182, Laboratoire de Chimie, F69342 Lyon, France.
J Chem Inf Model ; 61(7): 3386-3396, 2021 07 26.
Article em En | MEDLINE | ID: mdl-34160214
ABSTRACT
We present the open-source python package DockOnSurf which automates the generation and optimization of low-energy adsorption configurations of molecules on extended surfaces and nanoparticles. DockOnSurf is especially geared toward handling polyfunctional flexible adsorbates. The use of this high-throughput workflow allows us to carry out the screening of adsorbate-surface configurations in a systematic, customizable, and traceable way, while keeping the focus on the chemically relevant structures. The screening strategy consists in splitting the exploration of the adsorbate-surface configurational space into chemically meaningful domains, that is, by choosing among different conformers to adsorb, surface adsorption sites, adsorbate anchoring points, and orientations and allowing dissociation of (acidic) protons. We demonstrate the performance of the main features based on varying examples, ranging from CO adsorption on a gold nanoparticle to sorbitol adsorption on hematite. Through the use of the presented program, we aim to foster efficiency, traceability, and ease of use in research within tribology, catalysis, nanoscience, and surface science in general.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Screening_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Screening_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article