DENOPTIM: Software for Computational de Novo Design of Organic and Inorganic Molecules
Open accessAbstract
design and virtual screening of functional molecules is described. Molecules of any element and kind, including metastable species and transition states, are handled as chemical objects that go beyond valence-rules representations. Synthetic accessibility of the generated molecules is ensured via detailed control of the kinds of bonds that are allowed to form in the automated molecular building process. DENOPTIM contains a combinatorial explorer for screening and a genetic algorithm for global optimization of user-defined properties. Estimates of these properties may be obtained to form the fitness function (figure of merit or scoring function) from external molecular modeling programs via shell scripts. Examples of a range of different fitness functions and DENOPTIM applications, including an easy-to-do test case, are described. DENOPTIM is available as Open Source from https://github.com/denoptim-project/DENOPTIM .
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- Authors
- Foscato, M., Venkatraman, V., & Jensen, V. R.
- Affiliations
- University of Bergen (NO)
- Norwegian University of Science and Technology (NO)
- Corresponding author
- Jensen, Vidar R.
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-09-03
- Volume
- 59
- Issue
- 10
- Pages
- 4077-4082
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- OpenAlex
- W2972147476
- Cited by
- 45
- References
- 38
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 11 · 2023: 10 · 2022: 7 · 2021: 4 · 2020: 6
- FWCI
- 2.89
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Journal of Chemical Information and Modeling (publishedVersion)
- PubMed (publishedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Funders
- Norges Forskningsr?d (NN2506K, NS2506K, 262370, 233776, 262152, 205273)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- 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
- Keywords
- de novo molecular design, virtual screening, genetic algorithm, fitness function, scoring functions, synthetic accessibility, transition state, metastable species, organic compounds, inorganic molecules, open source software
- MeSH terms
- Computer Simulation, Humans, Inorganic Chemicals, Models, Chemical, Organic Chemicals, Software, Drug Design
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