Proteome‐Scale Drug‐Target Interaction Predictions: Approaches and Applications. Issue 11 (18th November 2021)

• Record Type: Journal Article
• Authors: MacKinnon, Stephen Scott; Madani Tonekaboni, S. A.; Windemuth, Andreas
• Is Part Of: Current protocols. Volume 1:Issue 11(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-11-18
• Subjects: artificial intelligence -- drug design -- drug‐target interactions -- polypharmacology -- proteome screening; Life sciences -- Laboratory manuals -- Periodicals; Biology -- Laboratory manuals -- Periodicals; Life sciences -- Technique -- Periodicals; Biology -- Technique -- Periodicals; 570.028
• DOI: 10.1002/cpz1.302
• Languages: English
• ISSNs: 2691-1299

Abstract

Abstract: Drug‐Target interaction predictions are an important cornerstone of computer‐aided drug discovery. While predictive methods around individual targets have a long history, the application of proteome‐scale models is relatively recent. In this overview, we will provide the context required to understand advances in this emerging field within computational drug discovery, evaluate emerging technologies for suitability to given tasks, and provide guidelines for the design and implementation of new drug‐target interaction prediction models. We will discuss the validation approaches used, and propose a set of key criteria that should be applied to evaluate their validity. We note that we find widespread deficiencies in the existing literature, making it difficult to judge the practical effectiveness of some of the techniques proposed from their publications alone. We hope that this review may help remedy this situation and increase awareness of several sources of bias that may enter into commonly used cross‐validation methods. © 2021 Cyclica Inc. Current Protocols published by Wiley Periodicals LLC.