Poster - #UCLA-65 - Keywords: Virtual Ligand Screening Computer-aided Drug Discovery COVID-19 Induced Respiratory Distress

V-SYNTHES 2.0 – A New Approach for the Screening Giga-Scale Space in Computer-aided Drug Design and Its Usefulness in Finding Novel Therapeutics Against Acute Respiratory Distress Syndrome Caused by COVID-19

Antonina L. Nazarova^a, Arman A. Sadybekov^a, Anastasiia V. Sadybekov^a, Yurii S. Morozb, Andrew J. Shepherd^c, Vsevolod Katritch^a
aDepartment of Quantitative and Computational Biology, Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, CA, USA
^bKiev National Taras Shevchenko University, ChemSpace, Ukraine
^cDepartment of Symptom Research, Division of Internal Medicine, MD Anderson Cancer Center, The University of Texas, TX, USA

ABSTRACT:
V-SYNTHES 2.0 – A New Approach for the Screening Giga-Scale Space in Computer-aided Drug Design and Its Usefulness in Finding Novel Therapeutics Against Acute Respiratory Distress Syndrome Caused by COVID-19 Antonina L. Nazarova (a) (presenter), Arman A. Sadybekov (a), Anastasiia V. Sadybekov (a), Andrew J. Shepherd (b), Vsevolod Katritch (a) (a)Department of Quantitative and Computational Biology, Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, CA 90089-3502, USA (b)Department of Symptom Research, Division of Internal Medicine, MD Anderson Cancer Center, The University of Texas, TX 77030, USA In recent years the chemical space of REadily AvailabLe (“REAL”) drug-like compounds has increased to 1015 compounds and continues to grow rapidly. However, the compound libraries used in high-throughput and virtual ligand screenings remain limited to 1-10 Mln compounds. The newly developed virtual synthone hierarchical enumeration screening (V-SYNTHES) approach in the Katritch Lab enabled first time comprehensive screening of Giga-scale space of 11 Bln compounds, while performing docking of only 1Mln compounds.1 Here we present the next version of V-SYNTHES – V-SYNTHES 2.0, that is completely automated and allows access to the largest up-to-date REAL Space library of now 21 billion compounds.2 As it is in the parent V-SYNTHES, the efficiency of this approach relies on the pre-docking of a Minimally Enumerated Library (MEL) of fragment-based compounds. Each MEL fragment represents a combination of one REAL reaction scaffold and one corresponding synthon. If selected, the MEL fragment is enumerated into a set of full ligands, some of which may become hit candidates if they show a high docking score and adequate location inside the target receptor. The selection of high-scoring MEL fragments with favorable receptor-ligand interactions is a crucial step of V-SYNTHES but was completely manual and required an extensive input from the user. In the V-SYNTHES 2.0, the developed CapSelect tool streamlines and automates the selection of potentially promising high-scoring MEL fragments with favorable receptor-ligand interactions, i.e., fragments with sufficient space to grow during enumeration. The CapSelect tool, now applied to a much bigger REAL Space library (21 Bln)3 is a key part of the V-SYNTHES 2.0 version, that demonstrated ~100 to ~1000-fold enrichment in computational benchmarks and is already being applied to hit discovery for several therapeutic targets. In particular, V-SYNTHES 2.0 has been successfully applied for searching agonists of the angiotensin type 2 receptor (AT2R) as novel therapeutics against the COVID-19 Induced Respiratory Distress. As a result of V-SYNTHES 2.0 screening, 107 hits of promising AT2R agonists were selected, synthesized, and tested in an AT2 functional assay. 30 compounds showed more than 50% activation at a 10mM concentration, with 7 revealing more than 80%. The activity assays are currently ongoing. 1. Sadybekov, A. A.; Sadybekov, A. V.; Liu, Y.; Iliopoulos-Tsoutsouvas, C.; Huang, X.-P.; Pickett, J.; Houser, B.; Patel, N.; Tran, N. K.; Tong, F.; Zvonok, N.; Jain, M. K.; Savych, O.; Radchenko, D. S.; Nikas, S. P.; Petasis, N. A.; Moroz, Y. S.; Roth, B. L.; Makriyannis, A.; Katritch, V., Synthon-based ligand discovery in virtual libraries of over 11 billion compounds. Nature 2021, 452-459. 2. Nazarova, A. L.; Sadybekov, A. A.; Sadybekov, A. V.; Katritch, V., V-SYNTHES 2.0 – A New Approach for the Screening Giga-Scale Space in Computer-aided Drug Design. USC Department of Quantitative and Computational Biology Annual Retreat, 2021, Ventura, CA (invited). 3. Grygorenko, O. O.; Radchenko, D. S.; Dziuba, I.; Chuprina, A.; Gubina, K. E.; Moroz, Y. S., Generating Multibillion Chemical Space of Readily Accessible Screening Compounds. iScience 2020, 23 (11).