Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability.

ABSTRACT: This study aims at improving upon existing activity predictions methods by augmenting chemical structure fingerprints with bio-activity based fingerprints derived from high-throughput screening (HTS) data (HTSFPs) and thereby showcasing the benefits of combining different descriptor types. This type of descriptor would be applied in an iterative screening scenario for more targeted compound set selection. The HTSFPs were generated from HTS data obtained from PubChem and combined with an ECFP4 structural fingerprint. The bioactivity-structure hybrid (BaSH) fingerprint was benchmarked against the individual ECFP4 and HTSFP fingerprints. Their performance was evaluated via retrospective analysis of a subset of the PubChem HTS data. Results showed that the BaSH fingerprint has improved predict

SUBMITTER: Laufkotter O 

PROVIDER: S-EPMC6686534 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature