Towards the online computer-aided design of catalytic pockets
Abstract
The engineering of catalysts with desirable properties can be accelerated by computer-aided design. To achieve this aim, features of molecular catalysts can be condensed into numerical descriptors that can then be used to correlate reactivity and structure. Based on such descriptors, we have introduced topographic steric maps that provide a three-dimensional image of the catalytic pocket-the region of the catalyst where the substrate binds and reacts-enabling it to be visualized and also reshaped by changing various parameters. These topographic steric maps, especially when used in conjunction with density functional theory calculations, enable catalyst structural modifications to be explored quickly, making the online design of new catalysts accessible to the wide chemical community. In this Perspective, we discuss the application of topographic steric maps either to rationalize the behaviour of known catalysts-from synthetic molecular species to metalloenzymes-or to design improved catalysts.
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These include relationships between catalysis or ligand binding and the steric bulk of a ligand.
“These include relationships between catalysis or ligand binding and the steric bulk [e.g., Tolman cone angle (77,78) or buried volume (79)] of a ligand.”
From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [79]
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- Authors
- Falivene, L., Cao, Z., Petta, A., Serra, L., Poater, A., Oliva, R., Scarano, V., & Cavallo, L.
- Affiliations
- King Abdullah University of Science and Technology (SA)
- University of Salerno (IT)
- Universitat de Girona (ES)
- Parthenope University of Naples (IT)
- Corresponding author
- Cavallo, Luigi
- Venue
- Nature Chemistry
- Published
- 2019-09-02
- Volume
- 11
- Issue
- 10
- Pages
- 872-879
- ISSN
- 1755-4330 (ISSN-L)
- 1755-4349
- OpenAlex
- W2971791401
- Cited by
- 1,290
- References
- 57
- Citations by year
- 2026: 155 · 2025: 233 · 2024: 207 · 2023: 195 · 2022: 191 · 2021: 164 · 2020: 130 · 2019: 15
- FWCI
- 7.59
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature Chemistry (publishedVersion)
- PubMed (publishedVersion)
- King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) (submittedVersion)
- CINECA IRIS Institutial research information system (Parthenope University of Naples) (submittedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Chemistry › Organic Chemistry › Organometallic Complex Synthesis and Catalysis
- Keywords
- molecular descriptors, shape complementarity, active site, metalloenzymes, density functional theory
- MeSH terms
- Density Functional Theory, Metalloproteins, Computer-Aided Design, Imaging, Three-Dimensional, Biocatalysis
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