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Our capability to mine these newly generated libraries also lags their growth. That is why fragment-based approaches that utilize on-demand virtual combinatorial libraries are gaining popularity in drug discovery. These <jats:italic>\u00e0 la carte<\/jats:italic> libraries utilize synthetic blocks found to be effective binders in parts of target protein pockets and a variety of reliable chemistries to connect them. There is, however, no data on the potential impact of the chemistries used for making on-demand libraries on the hit rates during virtual screening. There are also no rules to guide in the selection of these synthetic methods for production of custom libraries. We have used the SAVI (Synthetically Accessible Virtual Inventory) library, constructed using 53 reliable reaction types (transforms), to evaluate the impact of these chemistries on docking hit rates for 40 well-characterized protein pockets. The data shows that the virtual hit rates differ significantly for different chemistries with cross coupling reactions such as Sonogashira, Suzuki\u2013Miyaura, Hiyama and Liebeskind\u2013Srogl coupling producing the highest hit rates. Virtual hit rates appear to depend not only on the property of the formed chemical bond but also on the diversity of available building blocks and the scope of the reaction. The data identifies reactions that deserve wider use through increasing the number of corresponding building blocks and suggests the reactions that are more effective for pockets with certain physical and hydrogen bond-forming properties.<\/jats:p>","DOI":"10.1007\/s10822-024-00562-4","type":"journal-article","created":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T10:02:14Z","timestamp":1715853734000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Correlation of protein binding pocket properties with hits\u2019 chemistries used in generation of ultra-large virtual libraries"],"prefix":"10.1007","volume":"38","author":[{"given":"Robert X.","family":"Song","sequence":"first","affiliation":[]},{"given":"Marc C.","family":"Nicklaus","sequence":"additional","affiliation":[]},{"given":"Nadya I.","family":"Tarasova","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,16]]},"reference":[{"key":"562_CR1","doi-asserted-by":"publisher","first-page":"e766","DOI":"10.1002\/ctm2.766","volume":"12","author":"AL Nazarova","year":"2022","unstructured":"Nazarova AL, Katritch V (2022) It all clicks together: in silico drug discovery becoming mainstream. 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