QSAR-derived affinity fingerprints (part 2): modeling performance for potency prediction.

ABSTRACT: Affinity fingerprints report the activity of small molecules across a set of assays, and thus permit to gather information about the bioactivities of structurally dissimilar compounds, where models based on chemical structure alone are often limited, and model complex biological endpoints, such as human toxicity and in vitro cancer cell line sensitivity. Here, we propose to model in vitro compound activity using computationally predicted bioactivity profiles as compound descriptors. To this aim, we apply and validate a framework for the calculation of QSAR-derived affinity fingerprints (QAFFP) using a set of 1360 QSAR models generated using K_i, K_d, IC₅₀ and EC₅₀ data from ChEMBL database. QAFFP thus represent a method to encode and relate compoun

SUBMITTER: Cortes-Ciriano I 

PROVIDER: S-EPMC7339533 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature