{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/first-principles-molecular-structure-search","title":"First-principles molecular structure search with a genetic algorithm","arxiv_id":"1505.02521","date":"2015-10-13","proceeding":null,"authors":[],"abstract":"The identification of low-energy conformers for a given molecule is a\nfundamental problem in computational chemistry and cheminformatics. We assess\nhere a conformer search that employs a genetic algorithm for sampling the\nlow-energy segment of the conformation space of molecules. The algorithm is\ndesigned to work with first-principles methods, facilitated by the\nincorporation of local optimization and blacklisting conformers to prevent\nrepeated evaluations of very similar solutions. The aim of the search is not\nonly to find the global minimum, but to predict all conformers within an energy\nwindow above the global minimum. The performance of the search strategy is: (i)\nevaluated for a reference data set extracted from a database with amino acid\ndipeptide conformers obtained by an extensive combined force field and\nfirst-principles search and (ii) compared to the performance of a systematic\nsearch and a random conformer generator for the example of a drug-like ligand\nwith 43 atoms, 8 rotatable bonds and 1 cis/trans bond.","url_abs":"http://arxiv.org/abs/1505.02521v2","url_pdf":"http://arxiv.org/pdf/1505.02521v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"first-principles-molecular-structure-search","repo_url":"https://github.com/adrianasupady/fafoom","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"computational-chemistry","task_name":"Computational chemistry"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1505.02521","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}