Ring Closure To Form Metal Chelates in 3D Fragment-Based de Novo Design

Foscato, Marco; Houghton, Benjamin J.; Occhipinti, Giovanni; Deeth, Robert J.; Jensen, Vidar R.

doi:10.1021/acs.jcim.5b00424

Cited by 21Computational Drug Discovery MethodsMagnetism in coordination complexesChemical Synthesis and Analysis

Ring Closure To Form Metal Chelates in 3D Fragment-Based de Novo Design

Foscato, Marco, Houghton, Benjamin J., Occhipinti, Giovanni, Deeth, Robert J., Jensen, Vidar R.·2015·Journal of Chemical Information and Modeling

DOI 10.1021/acs.jcim.5b00424

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Abstract

We describe a method for the design of multicyclic compounds from three-dimensional (3D) molecular fragments. The 3D building blocks are assembled in a controlled fashion, and closable chains of such fragments are identified. Next, the ring-closing conformations of such formally closable chains are identified, and the 3D model of a cyclic or multicyclic molecule is built. Embedding this method in an evolutionary algorithm results in a de novo design tool capable of altering the number and nature of cycles in species such as transition metal compounds with multidentate ligands in terms of, for example, ligand denticity, type and length of bridges, identity of bridgehead terms, and substitution pattern. An application of the method to the design of multidentate nitrogen-based ligands for Fe(II) spin-crossover (SCO) compounds is presented. The best candidates display multidentate skeletons new to the field of Fe(II) SCO yet resembling ligands deployed in other fields of chemistry, demonstrating the capability of the approach to explore structural variation and to suggest unexpected and realistic molecules, including structures with cycles not found in the building blocks.

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Because fitness evaluation dictates the overall time for optimization, multiple linear regression or quantitative structure-property relationship models, force field or semiempirical models, or machine learning regression models are preferable to full density functional theory evaluation.
“Because fitness evaluation dictates the overall time for optimization, MLR (i.e., quantitative structure-property relationship, or QSPR) models (59,60), force field or semiempirical models (36), or ML regression models (e.g., with ANNs) (120) are preferable in comparison to full DFT evaluation.”
From Machine Learning for the Discovery, Design, and Engineering of Materials. (2022) · cites this paper as [36]

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Authors: Foscato, M., Houghton, B. J., Occhipinti, G., Deeth, R. J., & Jensen, V. R.
Affiliations: University of Bergen (NO)
University of Warwick (GB)
Corresponding author: Jensen, Vidar R.
ORCID: Foscato, Marco
Occhipinti, Giovanni
Deeth, Robert J.
Jensen, Vidar R.
Venue: Journal of Chemical Information and Modeling
Publisher: American Chemical Society (ACS)
Published: 2015-09-14
Volume: 55
Issue: 9
Pages: 1844-1856
ISSN: 1549-9596 (ISSN-L)
1549-960X
DOI: 10.1021/acs.jcim.5b00424
OpenAlex: W1231382326
Cited by: 21
References: 104
Citations by year: 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2 · 2022: 3 · 2021: 2 · 2020: 1 · 2019: 1 · 2018: 4 · 2017: 4
FWCI: 2.74
Type: journal article
Language: en
Open access: closed
Locations: Journal of Chemical Information and Modeling (publishedVersion)
PubMed (publishedVersion)
Funders: Norges Forskningsråd (205273, 208335)
European Cooperation in Science and Technology (CM1305)
Engineering and Physical Sciences Research Council
Topics: Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Physical Sciences › Materials Science › Electronic, Optical and Magnetic Materials › Magnetism in coordination complexes
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chemical Synthesis and Analysis
Keywords: cyclization, transition metal chelates, multidentate ligands, evolutionary algorithms, nitrogen-based ligands, ligand denticity, molecular scaffolds
MeSH terms: Chelating Agents, Cyclization, Drug Design, Molecular Structure, Small Molecule Libraries

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Ring Closure To Form Metal Chelates in 3D Fragment-Based de Novo Design

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