Druggability Assessment for Selected Serine Proteases in a Pharmaceutical Industry Setting. (21st September 2020)

• Record Type: Journal Article
• Authors: Wehrhan, Leon; Hillisch, Alexander; Mundt, Stefan; Tersteegen, Adrian; Meier, Katharina
• Is Part Of: ChemMedChem. Volume 15:Number 21(2020)
• Page Start: 2010
• Page End: 2018
• Publication Date: 2020-09-21
• Subjects: druggability -- molecular dynamics simulation -- HTS -- serine proteases; Pharmaceutical chemistry -- Periodicals; 615.19005
• DOI: 10.1002/cmdc.202000425
• Languages: English
• ISSNs: 1860-7179

Abstract

Abstract: Target druggability assessment is an integral part of the early target characterization and selection process in pharmaceutical industry. Here, we investigate a set of five different serine proteases from the blood coagulation cascade. The aim of this study is twofold. Firstly, leveraging the wealth of available in‐house high‐throughput screening (HTS) data, we analyze HTS hit rates and discuss their predictive value for the development of small molecule (SMOL) candidates. Purely structure‐activity relationship (SAR) based druggability ratings are compared with computational protein‐structure based druggability assessments. Secondly, we evaluate the impact of using conformational ensembles from molecular dynamics (MD) simulations instead of single static crystal structures as basis for computational druggability assessments. Based on this study, we recommend incorporating molecular dynamics routinely into the early target characterization process, especially if only a single X‐ray structure is available. Abstract : Target druggability assessment is an integral part of the early target characterization process in pharmaceutical industry. For five serine proteases, we analyzed high‐throughput screening (HTS) data of 1 to 4 million compounds and discussed the predictive value compared to protein‐structure‐based druggability assessments. Because there is no single generally applicable method that provides a complete picture of target druggability, we deduced general recommendations and showed that analyzing conformational variability can give crucial insights for early target characterization.