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      ZINC-22—A Free Multi-Billion-Scale Database of Tangible Compounds for Ligand Discovery

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          Abstract

          Purchasable chemical space has grown rapidly into the tens of billions of molecules, providing unprecedented opportunities for ligand discovery but straining the tools that might exploit these molecules at scale. We have therefore developed ZINC-22, a database of commercially accessible small molecules derived from multi-billion-scale make-on-demand libraries. The new database and tools enable analog searching in this vast new space via a facile GUI, CartBlanche, drawing on similarity methods that scale sublinearly in the number of molecules. The new library also uses data organization methods, enabling rapid lookup of molecules and their physical properties, including conformations, partial atomic charges, c Log  P values, and solvation energies, all crucial for molecule docking, which had become slow with older database organizations in previous versions of ZINC. As the libraries have continued to grow, we have been interested in finding whether molecular diversity has suffered, for instance, because certain scaffolds have come to dominate via easy analoging. This has not occurred thus far, and chemical diversity continues to grow with database size, with a log increase in Bemis–Murcko scaffolds for every two-log unit increase in database size. Most new scaffolds come from compounds with the highest heavy atom count. Finally, we consider the implications for databases like ZINC as the libraries grow toward and beyond the trillion-molecule range. ZINC is freely available to everyone and may be accessed at cartblanche22.docking.org, via Globus, and in the Amazon AWS and Oracle OCI clouds.

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          ZINC 15 – Ligand Discovery for Everyone

          Many questions about the biological activity and availability of small molecules remain inaccessible to investigators who could most benefit from their answers. To narrow the gap between chemoinformatics and biology, we have developed a suite of ligand annotation, purchasability, target, and biology association tools, incorporated into ZINC and meant for investigators who are not computer specialists. The new version contains over 120 million purchasable “drug-like” compounds – effectively all organic molecules that are for sale – a quarter of which are available for immediate delivery. ZINC connects purchasable compounds to high-value ones such as metabolites, drugs, natural products, and annotated compounds from the literature. Compounds may be accessed by the genes for which they are annotated as well as the major and minor target classes to which those genes belong. It offers new analysis tools that are easy for nonspecialists yet with few limitations for experts. ZINC retains its original 3D roots – all molecules are available in biologically relevant, ready-to-dock formats. ZINC is freely available at http://zinc15.docking.org.
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            ZINC--a free database of commercially available compounds for virtual screening.

            A critical barrier to entry into structure-based virtual screening is the lack of a suitable, easy to access database of purchasable compounds. We have therefore prepared a library of 727,842 molecules, each with 3D structure, using catalogs of compounds from vendors (the size of this library continues to grow). The molecules have been assigned biologically relevant protonation states and are annotated with properties such as molecular weight, calculated LogP, and number of rotatable bonds. Each molecule in the library contains vendor and purchasing information and is ready for docking using a number of popular docking programs. Within certain limits, the molecules are prepared in multiple protonation states and multiple tautomeric forms. In one format, multiple conformations are available for the molecules. This database is available for free download (http://zinc.docking.org) in several common file formats including SMILES, mol2, 3D SDF, and DOCK flexibase format. A Web-based query tool incorporating a molecular drawing interface enables the database to be searched and browsed and subsets to be created. Users can process their own molecules by uploading them to a server. Our hope is that this database will bring virtual screening libraries to a wide community of structural biologists and medicinal chemists.
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              Ultra-large library docking for discovering new chemotypes

              Despite intense interest in expanding chemical space, libraries of hundreds-of-millions to billions of diverse molecules have remained inaccessible. Here, we investigate structure-based docking of 170 million make-on-demand compounds from 130 well-characterized reactions. The resulting library is diverse, representing over 10.7 million scaffolds otherwise unavailable. The library was docked against AmpC β-lactamase and the D4 dopamine receptor. From the top-ranking molecules, 44 and 549 were synthesized and tested, respectively. This revealed an unprecedented phenolate inhibitor of AmpC, which was optimized to 77 nM, the most potent non-covalent AmpC inhibitor known. Crystal structures of this and other new AmpC inhibitors confirmed the docking predictions. Against D4, hit rates fell monotonically with docking score, and a hit-rate vs. score curve predicted 453,000 D4 ligands in the library. Of 81 new chemotypes discovered, 30 were sub-micromolar, including a 180 pM sub-type selective agonist.
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                Author and article information

                Journal
                J Chem Inf Model
                J Chem Inf Model
                ci
                jcisd8
                Journal of Chemical Information and Modeling
                American Chemical Society
                1549-9596
                1549-960X
                15 February 2023
                27 February 2023
                : 63
                : 4
                : 1166-1176
                Affiliations
                []Department of Pharmaceutical Chemistry, University of California San Francisco , 1700 4th St, Mailcode 2550, San Francisco, California 94158-2330, United States
                []Taras Shevchenko National University of Kyïv , 60 Volodymyrska Street, Kyïv 01601, Ukraine
                [§ ]Chemspace LLC , 85 Chervonotkatska Street, Kyïv 02094, Ukraine
                Author notes
                Author information
                https://orcid.org/0000-0002-1195-6417
                Article
                10.1021/acs.jcim.2c01253
                9976280
                36790087
                8238defe-c99f-475e-acef-638d8bc34427
                © 2023 The Authors. Published by American Chemical Society

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 07 October 2022
                Funding
                Funded by: National Institutes of Health, doi 10.13039/100000002;
                Award ID: GM133836
                Categories
                Article
                Custom metadata
                ci2c01253
                ci2c01253

                Computational chemistry & Modeling
                Computational chemistry & Modeling

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