title: Molecular quantum similarity-based QSARs for binding affinities of several steroid sets.
abstract: The application of Molecular Quantum Similarity Measures (MQSM) to correlate biological activities for three different sets of steroids is reported. A general protocol for the generation of descriptors is detailed, thus covering molecular superposition, electronic density fitting, and quantum similarity calculation issues. Satisfactory Quantitative Structure-Activity Relationship (QSAR) models (r(2) in [0.69,0.94] and q(2) in [0.59,0.73]), comparable to previous studies, are obtained in all cases, where steroid binding affinities to different enzymes are studied. In this work, MQSM, properly scaled using Carbó Index, are related to activity using a Partial Least Squares routine.
authors.affiliation: Institute of Computational Chemistry, University of Girona, Campus Montilivi, 17071 Girona, Catalonia, Spain.
authors.forename: Xavier
authors.initials: X
authors.lastname: Gironés
authors.forename: Ramon
authors.initials: R
authors.lastname: Carbó-Dorca
mesh_terms: D001141:Aromatase / Q000378:metabolism; D042944:Cholestenone 5 alpha-Reductase; D003198:Computer Simulation; D015195:Drug Design; D006801:Humans; D066298:In Vitro Techniques; D008956:Models, Chemical; D010088:Oxidoreductases / Q000378:metabolism; D021281:Quantitative Structure-Activity Relationship; D011789:Quantum Theory; D013256:Steroids / Q000737:chemistry* / Q000378:metabolism*; D014156:Transcortin / Q000378:metabolism
chemical_list: D013256:Steroids; D014156:Transcortin; D010088:Oxidoreductases; D001141:Aromatase; D042944:Cholestenone 5 alpha-Reductase