Unknown

Dataset Information

0

Prediction of intracellular exposure bridges the gap between target- and cell-based drug discovery.

ABSTRACT: Inadequate target exposure is a major cause of high attrition in drug discovery. Here, we show that a label-free method for quantifying the intracellular bioavailability (Fic) of drug molecules predicts drug access to intracellular targets and hence, pharmacological effect. We determined Fic in multiple cellular assays and cell types representing different targets from a number of therapeutic areas, including cancer, inflammation, and dementia. Both cytosolic targets and targets localized in subcellular compartments were investigated. Fic gives insights on membrane-permeable compounds in terms of cellular potency and intracellular target engagement, compared with biochemical potency measurements alone. Knowledge of the amount of drug that is locally available to bind intracellular targets provides a powerful tool for compound selection in early drug discovery.

SUBMITTER: Mateus A 

PROVIDER: S-EPMC5544291 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

Json Xml
altmetric image

Publications

Prediction of intracellular exposure bridges the gap between target- and cell-based drug discovery.

Mateus André A   Gordon Laurie J LJ   Wayne Gareth J GJ   Almqvist Helena H   Axelsson Hanna H   Seashore-Ludlow Brinton B   Treyer Andrea A   Matsson Pär P   Lundbäck Thomas T   West Andy A   Hann Michael M MM   Artursson Per P  

Proceedings of the National Academy of Sciences of the United States of America 20170712 30

Inadequate target exposure is a major cause of high attrition in drug discovery. Here, we show that a label-free method for quantifying the intracellular bioavailability (F<sub>ic</sub>) of drug molecules predicts drug access to intracellular targets and hence, pharmacological effect. We determined F<sub>ic</sub> in multiple cellular assays and cell types representing different targets from a number of therapeutic areas, including cancer, inflammation, and dementia. Both cytosolic targets and ta  ...[more]

Similar Datasets

Transcriptomics A Deep Learning based Efficacy Prediction System for Drug Discovery
2023-03-31 | GSE165175 | GEO
Unknown Accelerating Drug Discovery by Early Protein Drug Target Prediction Based on a Multi-Fingerprint Similarity Search.
| S-EPMC6631269 | biostudies-literature
Transcriptomics A Deep Learning based Efficacy Prediction System for Drug Discovery [Trametinib]
2023-03-31 | GSE165174 | GEO
Transcriptomics A Deep Learning based Efficacy Prediction System for Drug Discovery [Perillen]
2023-03-31 | GSE165173 | GEO
Unknown Quantifiable peptide library bridges the gap for proteomics based biomarker discovery and validation on breast cancer.
| S-EPMC10238494 | biostudies-literature
Transcriptomics A Deep Learning based Efficacy Prediction System for Drug Discovery [Chikusetsusaponin IV]
2023-03-31 | GSE165171 | GEO
Unknown Computational Discovery of Putative Leads for Drug Repositioning through Drug-Target Interaction Prediction.
| S-EPMC5125559 | biostudies-literature
Unknown Ballgown bridges the gap between transcriptome assembly and expression analysis.
| S-EPMC4792117 | biostudies-literature
Unknown Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics.
| S-EPMC6547493 | biostudies-literature
Unknown Similarity-Based Methods and Machine Learning Approaches for Target Prediction in Early Drug Discovery: Performance and Scope.
| S-EPMC7279241 | biostudies-literature