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Integrating DNA-encoded chemical libraries with virtual combinatorial library screening: Optimizing a PARP10 inhibitor

Institution:	1. Department of Medicinal Chemistry, Skaggs College of Pharmacy, University of Utah, 30 S 2000 E, Salt Lake City, UT 84112, USA;2. Department of Chemistry, McDaniel College, 2 College Hill, Westminster, MD 21157, USA;3. Center for Integrative Chemical Biology and Drug Discovery, UNC Eshelman School of Pharmacy, 301 Pharmacy Lane, University of North Carolina, Chapel Hill, NC 27599, USA;1. State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Zhang Jiang Hi-Tech Park, Pudong, Shanghai 201203, China;2. University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China;1. Discovery Sciences, Pfizer, Eastern Point Rd, Groton, CT, 06340, USA;2. Lead Generation Unit, HitGen Inc, Building 6, Tianfu International Bio-Town, No. 8, Huigu 1st East Road, Shuangliu District, Chengdu, Sichuan, 610000, China;3. Structural Biology, Pfizer, 3200 Walnut Rd, Boulder, CO, 80301, USA;1. McDaniel College, 2 College Hill, Westminster, MD 21157, United States;2. Karolinska Institutet, Department of Medical Biochemistry and Biophysics, Scheeles väg 2, S-17177 Stockholm, Sweden;3. Stevenson University, 1525 Greenspring Valley Rd, Stevenson, MD 21153, United States;1. Department of Organic Chemistry, NCCR Chemical Biology, University of Geneva, Switzerland;2. Current affiliation: Departement of Life and Health Science University of Nicosia, Cyprus;3. Current affiliation: Lonza AG, Visp, Switzerland;4. Current affiliation: PerkinElmer SAS, Villebon-sur-Yvette, France;1. Biocenter Oulu and Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland;2. Department of Pharmaceutical Sciences, University of Perugia, 06123, Perugia, Italy;3. Institute of Biochemistry and Molecular Biology, RWTH Aachen University, 52074, Aachen, Germany

Abstract:	Two critical steps in drug development are 1) the discovery of molecules that have the desired effects on a target, and 2) the optimization of such molecules into lead compounds with the required potency and pharmacokinetic properties for translation. DNA-encoded chemical libraries (DECLs) can nowadays yield hits with unprecedented ease, and lead-optimization is becoming the limiting step. Here we integrate DECL screening with structure-based computational methods to streamline the development of lead compounds. The presented workflow consists of enumerating a virtual combinatorial library (VCL) derived from a DECL screening hit and using computational binding prediction to identify molecules with enhanced properties relative to the original DECL hit. As proof-of-concept demonstration, we applied this approach to identify an inhibitor of PARP10 that is more potent and druglike than the original DECL screening hit.

Keywords:	DNA-encoded chemical libraries Computer-guided drug discovery Poly-(ADP-ribose) polymerase Hit-to-lead development Virtual combinatorial libraries
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