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Moldrug explores the chemical space using structural modifications suggested by the CReM library and by optimizing an adaptable fitness function with a genetic algorithm. Moldrug is complemented by Moldrug-Dashboard, a cross-platform and user-friendly graphical interface tailored for the analysis of Moldrug simulations. To illustrate Moldrug, we designed new potential inhibitors targeting the main protease (M<jats:sup>Pro<\/jats:sup>) of SARS-CoV-2 by optimizing a consensus fitness function that balances binding affinity, drug-likeness, and synthetic accessibility. The designed molecules exhibited high chemical diversity. A subset of the designed molecules were ranked using MM\/GBSA and alchemical binding free energy calculations, revealing predicted affinities as low as <jats:inline-formula>\n              <jats:alternatives>\n                <jats:tex-math>$$-10\\,~\\hbox {kcal}\\,\\hbox {mol}^{-1}$$<\/jats:tex-math>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mrow>\n                    <mml:mo>-<\/mml:mo>\n                    <mml:mn>10<\/mml:mn>\n                    <mml:mspace\/>\n                    <mml:mspace\/>\n                    <mml:mtext>kcal<\/mml:mtext>\n                    <mml:mspace\/>\n                    <mml:msup>\n                      <mml:mtext>mol<\/mml:mtext>\n                      <mml:mrow>\n                        <mml:mo>-<\/mml:mo>\n                        <mml:mn>1<\/mml:mn>\n                      <\/mml:mrow>\n                    <\/mml:msup>\n                  <\/mml:mrow>\n                <\/mml:math>\n              <\/jats:alternatives>\n            <\/jats:inline-formula>. Moldrug is distributed as a Python package under the Apache 2.0 license. It offers pre-configured multi-parameter fitness functions for molecular design, while being highly adaptable for integrating functionalities from external software. Documentation and tutorials are available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/moldrug.rtfd.io\/\" ext-link-type=\"uri\">https:\/\/moldrug.rtfd.io<\/jats:ext-link>.<\/jats:p>","DOI":"10.1186\/s13321-025-01022-3","type":"journal-article","created":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T13:58:30Z","timestamp":1748267910000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations"],"prefix":"10.1186","volume":"17","author":[{"given":"Alejandro","family":"Mart\u00ednez Le\u00f3n","sequence":"first","affiliation":[]},{"given":"Benjamin","family":"Ries","sequence":"additional","affiliation":[]},{"given":"Jochen S.","family":"Hub","sequence":"additional","affiliation":[]},{"given":"Aniket","family":"Magarkar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,26]]},"reference":[{"key":"1022_CR1","doi-asserted-by":"publisher","first-page":"113705","DOI":"10.1016\/j.ejmech.2021.113705","volume":"224","author":"VT Sabe","year":"2021","unstructured":"Sabe VT, Ntombela T, Jhamba LA, Maguire GE, Govender T, Naicker T, Kruger HG (2021) Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: a review. 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