Mapping small molecule binding data to structural domains

Abstract

Background Large-scale bioactivity/SAR Open Data has recently become available, and this has allowed new analyses and approaches to be developed to help address the productivity and translational gaps of current drug discovery. One of the current limitations of these data is the relative sparsity of reported interactions per protein target, and complexities in establishing clear relationships between bioactivity and targets using bioinformatics tools. We detail in this paper the indexing of targets by the structural domains that bind (or are likely to bind) the ligand within a full-length protein. Specifically, we present a simple heuristic to map small molecule binding to Pfam domains. This profiling can be applied to all proteins within a genome to give some indications of the potential pharmacological modulation and regulation of all proteins. Results In this implementation of our heuristic, ligand binding to protein targets from the ChEMBL database was mapped to structural domains as defined by profiles contained within the Pfam-A database. Our mapping suggests that the majority of assay targets within the current version of the ChEMBL database bind ligands through a small number of highly prevalent domains, and conversely the majority of Pfam domains sampled by our data play no currently established role in ligand binding. Validation studies, carried out firstly against Uniprot entries with expert binding-site annotation and secondly against entries in the wwPDB repository of crystallographic protein structures, demonstrate that our simple heuristic maps ligand binding to the correct domain in about 90 percent of all assessed cases. Using the mappings obtained with our heuristic, we have assembled ligand sets associated with each Pfam domain. Conclusions Small molecule binding has been mapped to Pfam-A domains of protein targets in the ChEMBL bioactivity database. The result of this mapping is an enriched annotation of small molecule bioactivity data and a grouping of activity classes following the Pfam-A specifications of protein domains. This is valuable for data-focused approaches in drug discovery, for example when extrapolating potential targets of a small molecule with known activity against one or few targets, or in the assessment of a potential target for drug discovery or screening studies.

Structural and Functional View of Polypharmacology

“…We have provided fundamental support to the idea suggested by previous research that domain families like CATH functional families provide a useful level of abstraction for a systematic understanding of small molecule bioactivity and drug action [15][16][17][18]63,64 . In this work, we conducted further analyses to test whether CATH-FunFams are druggable and have shown that the domains in these families have the potential to be the druggable entities within drug targets.…”

“…As mentioned already above, previous research has shown that drug binding sites are contained within protein domains 17 and that protein domains mediate drug-target interactions 16 . Furthermore, the recurrent identification of domain families in the druggable genome suggests that the conserved sequence properties and functional similarities within a protein family, are associated with conservation of drug binding sites.…”

“…Recent studies have shown that protein domains dominate protein-protein interactions 14 , and mediate the interactions between a drug and its targets [15][16][17] . It has also been shown that they are a major factor in the polypharmacology of approved and experimental drugs 18 , tend to contain binding sites 17 , and that there are privileged druggable protein domains 19 . These results support the idea that a particular structural domain is likely to be the druggable entity in a protein target.…”

Analysis of Individual Protein Regions Provides Novel Insights on Cancer Pharmacogenomics

“…Similar approaches focusing on Pfam protein domains have been used previously to study the molecular mechanisms underlying the pleiotropy of certain genes, especially those related to Mendelian disorders [10] , [11] , and cancer [12] – [14] . In the context of the analysis of drug-related data, PFRs have been mainly used to study phenomena such as polypharmacology or the structural details underlying interactions between drugs and domains [15] , [16] . However, to the best of our knowledge, such PFR-centric analyses have ever been used to study cancer pharmacogenomic datasets.…”

PPDMs—a resource for mapping small molecule bioactivities from ChEMBL to Pfam-A protein domains

“…, 2013 ), and for the establishment of functional relationships between proteins ( Kruger and Overington, 2012 ; Lin et al., 2013 ; van der Horst et al., 2010 ). To add precision to these methods, we have previously proposed a simple mapping heuristic of small molecule bioactivities to protein domains ( Kruger et al. , 2012 ).…”