ArticleBioorganic & medicinal chemistry letters2010
The Privileged Chemical Space Predictor (PCSP): a computer program that identifies privileged chemical space from screens of modularly assembled chemical libraries.
Article in Bioorganic & medicinal chemistry letters, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Selective Small Molecule Recognition of RNA Base Pairs.ACS combinatorial science · 2018Article
- Characterization and in vitro activity of a branched peptide boronic acid that interacts with HIV-1 RRE RNA.Bioorganic & medicinal chemistry · 2016Article
- HIV-1 drug discovery: targeting folded RNA structures with branched peptides.Organic & biomolecular chemistry · 2015Article
- Targeting folded RNA: a branched peptide boronic acid that binds to a large surface area of HIV-1 RRE RNA.Organic & biomolecular chemistry · 2013Article
- Probing a 2-aminobenzimidazole library for binding to RNA internal loops via two-dimensional combinatorial screening.ACS chemical biology · 2012Article
- Identifying the preferred RNA motifs and chemotypes that interact by probing millions of combinations.Nature communications · 2012Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Modularly assembled combinatorial libraries are often used to identify ligands that bind to and modulate the function of a protein or a nucleic acid. Much of the data from screening these compounds, however, is not efficiently utilized to define structure-activity relationships (SAR). If SAR data are accurately constructed, it can enable the design of more potent binders. Herein, we describe a computer program called Privileged Chemical Space Predictor (PCSP) that statistically determines SAR from high-throughput screening (HTS) data and then identifies features in small molecules that predispose them for binding a target. Features are scored for statistical significance and can be utilized to design improved second generation compounds or more target-focused libraries. The program's utility is demonstrated through analysis of a modularly assembled peptoid library that previously was screened for binding to and inhibiting a group I intron RNA from the fungal pathogen Candida albicans.
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Registered trials
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