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However, these synthesizability approaches are disconnected from the reality of small laboratory drug design, where building block resources are limited, thus making the notion of in-house synthesizability with already available resources highly desirable. In this work, we show a successful in-house\n                    <jats:italic>de novo<\/jats:italic>\n                    drug design workflow generating active and in-house synthesizable ligands of monoglyceride lipase (MGLL). First, we demonstrate the successful transfer of CASP from 17.4 million commercial building blocks to a small laboratory setting of roughly 6000 building blocks with only a decrease of \u201312% in CASP success when accepting two reaction-steps longer synthesis routes on average. Next, we present a rapidly retrainable in-house synthesizability score, successfully capturing our in-house synthesizability without relying on external building block resources. We show that including our in-house synthesizability score in a multi-objective\n                    <jats:italic>de novo<\/jats:italic>\n                    drug design workflow, alongside a simple QSAR model, provides thousands of potentially active and easily in-house synthesizable molecules. Finally, we experimentally evaluate the synthesis and biochemical activity of three\n                    <jats:italic>de novo<\/jats:italic>\n                    candidates using their CASP-suggested synthesis routes employing only in-house building blocks. We find one candidate with evident activity, suggesting potential new ligand ideas for MGLL inhibitors while showcasing the usefulness of our in-house synthesizability score for\n                    <jats:italic>de novo<\/jats:italic>\n                    drug design.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Scientific contribution<\/jats:bold>\n                    Our core scientific contribution is the introduction of in-house\n                    <jats:italic>de novo<\/jats:italic>\n                    drug design, which enables the practical application of generative methods in small laboratories by utilizing a limited stock of available building blocks. Our fast-to-adapt workflow for in-house synthesizability scoring requires minimal computational retraining costs while supporting a high diversity of generated structures. We highlight the practicality of our approach through a comprehensive in-vitro case study that relies entirely on in-house resources, including in-silico generation, synthesis planning, and activity evaluation.\n                  <\/jats:p>","DOI":"10.1186\/s13321-024-00910-4","type":"journal-article","created":{"date-parts":[[2025,3,29]],"date-time":"2025-03-29T12:18:54Z","timestamp":1743250734000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Generate what you can make: achieving in-house synthesizability with readily available resources in de novo drug design"],"prefix":"10.1186","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6639-1508","authenticated-orcid":false,"given":"Alan Kai","family":"Hassen","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8771-1731","authenticated-orcid":false,"given":"Martin","family":"\u0160\u00edcho","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0625-0967","authenticated-orcid":false,"given":"Yorick J.","family":"van Aalst","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8313-0019","authenticated-orcid":false,"given":"Mirjam C. 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