ChemBioServer 2.0: an advanced web server for filtering, clustering and networking of chemical compounds facilitating both drug discovery and repurposing
Creators
- 1. Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Ilisia, 15784 Athens, Greece and Bioinformatics Department, The Cyprus Institute of Neurology and Genetics, 2370 Nicosia, Cyprus
- 2. Biomedical Research Foundation Academy of Athens, 115 27 Athens, Greece
- 3. Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK, 5Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SA, UK, 6Wellcome Trust–Medical Research Council Cambridge Stem Cell Institute, Cambridge CB2 0AW, UK,
- 4. Greek Research and Technology Network, S.A., 11523 Athens, Greece
- 5. Bioinformatics Department, The Cyprus Institute of Neurology and Genetics, 2370 Nicosia, Cyprus and The Cyprus School of Molecular Medicine, 2370 Nicosia, Cyprus
Description
ChemBioServer 2.0 is the advanced sequel of a web server for filtering, clustering and networking of chemical compound libraries facilitating both drug discovery and repurposing. It provides researchers the ability to (i) browse and visualize compounds along with their physicochemical and toxicity properties, (ii) perform property-based filtering of compounds, (iii) explore compound libraries for lead optimization based on perfect match substructure search, (iv) re-rank virtual screening results to achieve selectivity for a protein of interest against different protein members of the same family, selecting only those compounds that score high for the protein of interest, (v) perform clustering among the compounds based on their physicochemical properties providing representative compounds for each cluster, (vi) construct and visualize a structural similarity network of compounds providing a set of network analysis metrics, (vii) combine a given set of compounds with a reference set of compounds into a single structural similarity network providing the opportunity to infer drug repurposing due to transitivity, (viii) remove compounds from a network based on their similarity with unwanted substances (e.g. failed drugs) and (ix) build custom compound mining pipelines.
Availability and implementation
Files
chembioserver2.0.pdf
Files
(212.8 kB)
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