canSAR: updated cancer research and drug discovery knowledgebase

Abstract

canSAR (http://cansar.icr.ac.uk) is a public integrative cancer-focused knowledgebase for the support of cancer translational research and drug discovery. Through the integration of biological, pharmacological, chemical, structural biology and protein network data, it provides a single information portal to answer complex multidisciplinary questions including--among many others--what is known about a protein, in which cancers is it expressed or mutated, and what chemical tools and cell line models can be used to experimentally probe its activity? What is known about a drug, its cellular sensitivity profile and what proteins is it known to bind that may explain unusual bioactivity? Here we describe major enhancements to canSAR including new data, improved search and browsing capabilities and new target, cancer cell line, protein family and 3D structure summaries and tools.

Figure 1.

Global keyword searching: (a) the single global search capability that enables keyword searches to be performed across (b) genes and proteins, (c) cell lines (d) 3D structures and (e) compounds. The results are displayed in tabular forms with icons representing the availability of data such as cancer mutations and bioactive chemical probes. The user can sort the results based on these data. (f) New browsing functionality that allows exploring canSAR’s content through browsing genes and proteins, protein families, 3D structures or drugs and compounds. For example, (g) protein families have a summary feature where the user can sort and select families based on the types of data available. (h) Molecular targets, compounds and cell lines may be browsed by name.

Figure 2.

(a) The molecular target wiki page provides a complete, human readable, summary of the data stored for a particular protein and contains links to more in-depth data. The header icons indicate the types of information that are available, such as mutations, 3D structures and bioactivities as well as showing if the protein is an approved drug target. Detailed information such as drugs, (b) domain and protein 3D-structure availability, (c) druggability prediction using three alternative approaches as well as (d) tumor-tissue and cell line gene expression and mutation can be explored in detail and linked through to original sources. (e) Protein interaction networks are annotated with the chemogenomic data summaries from canSAR enabling exploration of deregulated and/or druggable network members. (f) Cell line data matrix provides a single view on mutation, expression, copy number variation and RNAi studies, where available, in one tabular summary.

Figure 3.

The new Cell Line synopsis summarizes the data stored about particular cell lines. (a) The overview page presents the highlights including a banner of icons indicating availability and status of different data such as mutations, bioactivities, RNAi and gene expression. All data can be explored in detail including (b) reported mutations, (c) listing of ‘genetically’ similar cell lines based on mutational status, (d) highest and lowest expressed genes and (e) drug sensitivity profiles compiled from different sources.

Figure 4.

The Protein Family synopsis summarizes the data held about a particular family, including the number of druggable members, the number of members that have bioactive compounds and those members that are known to have mutations in cancer. These are linked directly to the full chemical bioactivity data and their publications and full mutation data as well as other annotation. All subfamilies and individual proteins can be reached through an interactive family tree.

Figure 5.

Snapshots of some components of canSAR-3D. (a) The 3D explorer shows all structures available for a target (in this case EGFR) and allows filtering based on the availability of bound drugs (as shown) or other ligands, and on structure-based druggability. (b) Ligand interaction maps, 3D structural inspection and (c) superpositions viewers are available and all are linked seamlessly to chemical bioactivity and protein, genetic and functional data.