Sorin Avram1, Ramona Curpan2, Alina Bora2, Cristian Neanu2, Liliana Halip3. 1. Department of Computational Chemistry, Institute of Chemistry Timisoara of Romanian Academy, 24 Mihai Viteazu Blvd, Timişoara, Timiş, 300223, România. sorin_avram@acad-icht.tm.edu.ro. 2. Department of Computational Chemistry, Institute of Chemistry Timisoara of Romanian Academy, 24 Mihai Viteazu Blvd, Timişoara, Timiş, 300223, România. 3. Department of Computational Chemistry, Institute of Chemistry Timisoara of Romanian Academy, 24 Mihai Viteazu Blvd, Timişoara, Timiş, 300223, România. lili.ostopovici@acad-icht.tm.edu.ro.
Abstract
PURPOSE: The growing amount of heterogeneous bioactivity data requires effective strategies to assess the promiscuity/selectivity of small-molecules and aid drug discovery. In the current study, we aim to evaluate the potential of assay profiles (APs, i.e., unique combinations of assay-related features describing how activity determinations were performed and reported) in molecular promiscuity analysis. METHODS: Using PubChem bioactivity data, we computed for all Molecular Libraries Small Molecule Repository (MLSMR library) compounds the frequency of hits score (FoH, i.e., the ratio between the number of times the compound was found active and the number of times it was tested), which were subsequently fit into 32 theoretical APs. The promiscuity of drugs and non-drugs was compared at different levels of test results. RESULTS: We found 8 dominant APs, indicating that compounds tested in more than ten assays (or against ten targets) and found active at least once tend to reach near to maximum hit rates in scientific literature and confirmatory assays (e.g., 95% of the drugs show FoH scores >0.93). Primary and high-throughput screening testing results in very low hit rates (e.g., 95% of the compounds show FoH scores <0.11), promoting a different perspective of promiscuity. In general, drugs exert higher promiscuity compared to non-drugs. Targets and classes of drugs are also discussed within the main APs. CONCLUSION: APs contain relevant features and are suited for big data promiscuity analysis. The activity data of the main APs are freely available on www.chembioinf.ro .
PURPOSE: The growing amount of heterogeneous bioactivity data requires effective strategies to assess the promiscuity/selectivity of small-molecules and aid drug discovery. In the current study, we aim to evaluate the potential of assay profiles (APs, i.e., unique combinations of assay-related features describing how activity determinations were performed and reported) in molecular promiscuity analysis. METHODS: Using PubChem bioactivity data, we computed for all Molecular Libraries Small Molecule Repository (MLSMR library) compounds the frequency of hits score (FoH, i.e., the ratio between the number of times the compound was found active and the number of times it was tested), which were subsequently fit into 32 theoretical APs. The promiscuity of drugs and non-drugs was compared at different levels of test results. RESULTS: We found 8 dominant APs, indicating that compounds tested in more than ten assays (or against ten targets) and found active at least once tend to reach near to maximum hit rates in scientific literature and confirmatory assays (e.g., 95% of the drugs show FoH scores >0.93). Primary and high-throughput screening testing results in very low hit rates (e.g., 95% of the compounds show FoH scores <0.11), promoting a different perspective of promiscuity. In general, drugs exert higher promiscuity compared to non-drugs. Targets and classes of drugs are also discussed within the main APs. CONCLUSION:APs contain relevant features and are suited for big data promiscuity analysis. The activity data of the main APs are freely available on www.chembioinf.ro .
Entities:
Keywords:
assay profiles; big data; database mining; molecular promiscuity; polypharmacology
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