Flexophore, a New Versatile 3D Pharmacophore Descriptor That Considers Molecular Flexibility
Overview
Medical Informatics
Authors
Affiliations
A novel pharmacophore descriptor Flexophore is presented, which considers molecular flexibility when comparing descriptor similarities. The descriptor is a complete reduced graph of the underlying molecule. Its nodes are represented by enhanced MM2 atom types, while the edge descriptions encode the molecular flexibility by means of a histogram of node distances in a diverse conformer distribution. For comparing two descriptor nodes, a statistical function derived from the Cambridge Crystallographic Database is implemented. To assess the capability of the descriptor to describe the bioactivity space, 350 test data sets with 1000 molecules each are compiled. The data sets were spiked with molecules active on one of 18 different targets. In 175 of the 350 data sets, all molecules chemically similar to the query molecules were removed. Virtual screening on these data sets showed that the Flexophore descriptor detects active molecules despite chemical dissimilarity, whereas the results for the screening of the complete data sets show enrichments comparable to chemical fingerprint descriptors. The diversity analysis of the enriched compounds demonstrates that the Flexophore descriptor describes the chemical space orthogonal to chemical fingerprint descriptors.
Virtual screening: hope, hype, and the fine line in between.
Nada H, Meanwell N, Gabr M Expert Opin Drug Discov. 2025; 20(2):145-162.
PMID: 39862145 PMC: 11844436. DOI: 10.1080/17460441.2025.2458666.
Machine Learning-Assisted Drug Repurposing Framework for Discovery of Aurora Kinase B Inhibitors.
Ion G, Nitulescu G, Mihai D Pharmaceuticals (Basel). 2025; 18(1.
PMID: 39861075 PMC: 11768374. DOI: 10.3390/ph18010013.
Consensus screening for a challenging target: the quest for P-glycoprotein inhibitors.
Governa P, Biagi M, Manetti F, Forli S RSC Med Chem. 2024; 15(2):720-732.
PMID: 38389870 PMC: 10880898. DOI: 10.1039/d3md00649b.
Evaluation of the Topology Space of DNA-Encoded Libraries.
Weigel 3rd W, Montoya A, Franzini R J Chem Inf Model. 2023; 63(15):4641-4653.
PMID: 37493573 PMC: 11092675. DOI: 10.1021/acs.jcim.3c01008.
New Insights on the Activity and Selectivity of MAO-B Inhibitors through In Silico Methods.
Pacureanu L, Bora A, Crisan L Int J Mol Sci. 2023; 24(11).
PMID: 37298535 PMC: 10253494. DOI: 10.3390/ijms24119583.