Target-specific compound selectivity for multi-target drug discovery and repurposing

Most drug molecules modulate multiple target proteins, leading either to therapeutic effects or unwanted side effects. Such target promiscuity partly contributes to high attrition rates and leads to wasted costs and time in the current drug discovery process, and makes the assessment of compound sel...

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Main Authors: Tianduanyi Wang, Otto I. Pulkkinen, Tero Aittokallio
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Pharmacology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fphar.2022.1003480/full
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author Tianduanyi Wang
Tianduanyi Wang
Otto I. Pulkkinen
Otto I. Pulkkinen
Otto I. Pulkkinen
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
author_facet Tianduanyi Wang
Tianduanyi Wang
Otto I. Pulkkinen
Otto I. Pulkkinen
Otto I. Pulkkinen
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
author_sort Tianduanyi Wang
collection DOAJ
description Most drug molecules modulate multiple target proteins, leading either to therapeutic effects or unwanted side effects. Such target promiscuity partly contributes to high attrition rates and leads to wasted costs and time in the current drug discovery process, and makes the assessment of compound selectivity an important factor in drug development and repurposing efforts. Traditionally, selectivity of a compound is characterized in terms of its target activity profile (wide or narrow), which can be quantified using various statistical and information theoretic metrics. Even though the existing selectivity metrics are widely used for characterizing the overall selectivity of a compound, they fall short in quantifying how selective the compound is against a particular target protein (e.g., disease target of interest). We therefore extended the concept of compound selectivity towards target-specific selectivity, defined as the potency of a compound to bind to the particular protein in comparison to the other potential targets. We decompose the target-specific selectivity into two components: 1) the compound’s potency against the target of interest (absolute potency), and 2) the compound’s potency against the other targets (relative potency). The maximally selective compound-target pairs are then identified as a solution of a bi-objective optimization problem that simultaneously optimizes these two potency metrics. In computational experiments carried out using large-scale kinase inhibitor dataset, which represents a wide range of polypharmacological activities, we show how the optimization-based selectivity scoring offers a systematic approach to finding both potent and selective compounds against given kinase targets. Compared to the existing selectivity metrics, we show how the target-specific selectivity provides additional insights into the target selectivity and promiscuity of multi-targeting kinase inhibitors. Even though the selectivity score is shown to be relatively robust against both missing bioactivity values and the dataset size, we further developed a permutation-based procedure to calculate empirical p-values to assess the statistical significance of the observed selectivity of a compound-target pair in the given bioactivity dataset. We present several case studies that show how the target-specific selectivity can distinguish between highly selective and broadly-active kinase inhibitors, hence facilitating the discovery or repurposing of multi-targeting drugs.
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spelling doaj.art-7739dbb562b244c7a7c875207817ce802022-12-22T03:50:22ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122022-09-011310.3389/fphar.2022.10034801003480Target-specific compound selectivity for multi-target drug discovery and repurposingTianduanyi Wang0Tianduanyi Wang1Otto I. Pulkkinen2Otto I. Pulkkinen3Otto I. Pulkkinen4Tero Aittokallio5Tero Aittokallio6Tero Aittokallio7Tero Aittokallio8Tero Aittokallio9Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, FinlandDepartment of Computer Science, Aalto University, Espoo, FinlandInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, FinlandHelsinki Institute for Information Technology (HIIT), Department of Computer Science, University of Helsinki, Helsinki, FinlandDepartment of Mathematics and Statistics and InFLAMES Research Flagship, University of Turku, Turku, FinlandInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, FinlandHelsinki Institute for Information Technology (HIIT), Department of Computer Science, University of Helsinki, Helsinki, FinlandDepartment of Mathematics and Statistics and InFLAMES Research Flagship, University of Turku, Turku, FinlandInstitute for Cancer Research, Department of Cancer Genetics, Oslo University Hospital, Oslo, NorwayOslo Centre for Biostatistics and Epidemiology (OCBE), Faculty of Medicine, University of Oslo, Oslo, NorwayMost drug molecules modulate multiple target proteins, leading either to therapeutic effects or unwanted side effects. Such target promiscuity partly contributes to high attrition rates and leads to wasted costs and time in the current drug discovery process, and makes the assessment of compound selectivity an important factor in drug development and repurposing efforts. Traditionally, selectivity of a compound is characterized in terms of its target activity profile (wide or narrow), which can be quantified using various statistical and information theoretic metrics. Even though the existing selectivity metrics are widely used for characterizing the overall selectivity of a compound, they fall short in quantifying how selective the compound is against a particular target protein (e.g., disease target of interest). We therefore extended the concept of compound selectivity towards target-specific selectivity, defined as the potency of a compound to bind to the particular protein in comparison to the other potential targets. We decompose the target-specific selectivity into two components: 1) the compound’s potency against the target of interest (absolute potency), and 2) the compound’s potency against the other targets (relative potency). The maximally selective compound-target pairs are then identified as a solution of a bi-objective optimization problem that simultaneously optimizes these two potency metrics. In computational experiments carried out using large-scale kinase inhibitor dataset, which represents a wide range of polypharmacological activities, we show how the optimization-based selectivity scoring offers a systematic approach to finding both potent and selective compounds against given kinase targets. Compared to the existing selectivity metrics, we show how the target-specific selectivity provides additional insights into the target selectivity and promiscuity of multi-targeting kinase inhibitors. Even though the selectivity score is shown to be relatively robust against both missing bioactivity values and the dataset size, we further developed a permutation-based procedure to calculate empirical p-values to assess the statistical significance of the observed selectivity of a compound-target pair in the given bioactivity dataset. We present several case studies that show how the target-specific selectivity can distinguish between highly selective and broadly-active kinase inhibitors, hence facilitating the discovery or repurposing of multi-targeting drugs.https://www.frontiersin.org/articles/10.3389/fphar.2022.1003480/fulldrug selectivitydrug repurposingdrug discovery and developmentkinase inhibition activitypolypharmacological effects
spellingShingle Tianduanyi Wang
Tianduanyi Wang
Otto I. Pulkkinen
Otto I. Pulkkinen
Otto I. Pulkkinen
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
Tero Aittokallio
Target-specific compound selectivity for multi-target drug discovery and repurposing
Frontiers in Pharmacology
drug selectivity
drug repurposing
drug discovery and development
kinase inhibition activity
polypharmacological effects
title Target-specific compound selectivity for multi-target drug discovery and repurposing
title_full Target-specific compound selectivity for multi-target drug discovery and repurposing
title_fullStr Target-specific compound selectivity for multi-target drug discovery and repurposing
title_full_unstemmed Target-specific compound selectivity for multi-target drug discovery and repurposing
title_short Target-specific compound selectivity for multi-target drug discovery and repurposing
title_sort target specific compound selectivity for multi target drug discovery and repurposing
topic drug selectivity
drug repurposing
drug discovery and development
kinase inhibition activity
polypharmacological effects
url https://www.frontiersin.org/articles/10.3389/fphar.2022.1003480/full
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