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Sloan Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000879","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004341","name":"Dow Chemical Company","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004341","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Simon Family Faculty Research Innovation Fund"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,7,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Understanding ligand properties is essential for computational high-throughput screening of transition metal complexes. However, ligand properties such as net charge and other information such as their application area are often absent or inconsistently recorded in crystallographic data sets. Here, we construct a ligand data set from 126,985 mononuclear transition metal complexes curated from the Cambridge Structural Database. Using an iterative charge-balancing workflow that combines complex charges, metal oxidation states, and consensus across crystallographic observations, we confidently assign net charges to 66,810 ligands among 94,581 identified unique ligand structures to curate the Boston Open-Shell Ligand (BOS-Lig) data set. The workflow assigns ligand charges in homoleptic complexes first and then iteratively propagates these assignments across heteroleptic environments, allowing charges to be inferred even when direct charge information is unavailable. We analyze cases where simple heuristics such as the octet rule would have failed and introduce a purity metric to identify when our charge assignments may be incorrect. Each ligand is also classified in terms of its metal-coordinating atoms and whether there are multiple variants (i.e., hemilability). We then link complexes to their associated journal abstracts and apply a topic-modeling workflow to link 25,146 ligands with functional application areas spanning reactivity, redox chemistry, biological chemistry, and photophysical chemistry. Together, we provide an experimentally grounded data set of ligand chemical space that connects charge and functional application as a foundation for computational screening and data-driven ligand design.<\/jats:p>","DOI":"10.1021\/acs.jcim.6c01063","type":"journal-article","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T07:07:47Z","timestamp":1783926467000},"page":"8336-8348","source":"Crossref","is-referenced-by-count":1,"title":["The BOS-Lig Data\nSet: Accurate Ligand Charges from\na Consensus Approach for 66,810 Experimentally Synthesized Ligands"],"prefix":"10.1021","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-6353-3111","authenticated-orcid":true,"given":"Roland G.","family":"St Michel","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology , , , ,","place":["Cambridge, Massachusetts, United States, 02139"]},{"name":"Massachusetts Institute of Technology , , , ,","place":["Cambridge, Massachusetts, United States, 02139"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan J.","family":"Jang","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology , , , ,","place":["Cambridge, Massachusetts, United States, 02139"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8011-2704","authenticated-orcid":true,"given":"Aaron G.","family":"Garrison","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology , , , ,","place":["Cambridge, Massachusetts, United States, 02139"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8133-4165","authenticated-orcid":true,"given":"Ilia","family":"Kevlishvili","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology , , , ,","place":["Cambridge, Massachusetts, United States, 02139"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9342-0191","authenticated-orcid":true,"given":"Heather J.","family":"Kulik","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology , , , ,","place":["Cambridge, Massachusetts, United States, 02139"]},{"name":"Massachusetts Institute of Technology , , , ,","place":["Cambridge, Massachusetts, United States, 02139"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,7,13]]},"reference":[{"key":"2026072709093705300_cit1","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1021\/jacs.5b08707","article-title":"Evolution\nof C\u2013H Bond Functionalization from Methane to Methodology","volume":"138","author":"Hartwig","year":"2016","journal-title":"J. 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Sci."},{"key":"2026072709093705300_cit29","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1038\/s43588-024-00616-5","article-title":"Directional\nMultiobjective Optimization\nof Metal Complexes at the Billion-System Scale","volume":"4","author":"Kneiding","year":"2024","journal-title":"Nat. Comput. Sci."},{"key":"2026072709093705300_cit30","doi-asserted-by":"publisher","first-page":"4836","DOI":"10.1021\/acs.jctc.2c00468","article-title":"Exploiting Ligand Additivity for\nTransferable Machine\nLearning of Multireference Character across Known Transition Metal\nComplex Ligands","volume":"18","author":"Duan","year":"2022","journal-title":"J. Chem. Theory Comput."},{"key":"2026072709093705300_cit31","doi-asserted-by":"publisher","first-page":"6858","DOI":"10.1021\/cr900053k","article-title":"Recent\nDevelopments in the Methods and Applications of the Bond Valence Model","volume":"109","author":"Brown","year":"2009","journal-title":"Chem. 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