Saturday, November 16, 2013

Using canSAR Database to Learn About Cancer Drugs and Targets

Imagine that you heard about a groundbreaking hot new cancer drug on the evening news. And you are curious, and you want to find more about this drug. Where would you turn to? Google? 

Among the search engine hits will be a press release from the company and a multitude of news commentaries and blogposts, all various incarnations of the press release itself. These sources will have a summary of the best results from the Phase 3 clinical trial, promising (maybe self-congratulatory) statements from the CEO or CMO of the company, a paragraph on safety signals and usual disclaimers.

But what if you actually want to know more about the drug target, its biology, chemistry, structural biology, pharmacology, bioactivity (and experimental models) and all kinds of apparently boring (to the investment community) scientific data. 

This "mundane" data is generally scattered in journal articles, conferences abstracts and posters, and patent filings. Now there is an easier way to get a snapshot of this data: via a public database canSAR.

About canSAR

canSAR, developed by the Computational Biology and Chemogenomics Team of Cancer Research UK Cancer (CRUK) Therapeutics Unit at the Institute of Cancer Research (ICR), UK, is a public information portal that brings together multidisciplinary research. 

The canSAR website describes the goal of the database as follows:
"canSAR’s goal is to enable cancer translational research and drug discovery through providing this knowledge to researchers from across different disciplines. It provides a single information portal to answer complex multi-disciplinary 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?"

The public version of canSAR (v1.0) has collected and annotated
  • ~8 million data measurements
  • ~700,000 unique biologically active chemical structures  
  • data for >1,000 cancer cell line models
Future version will also have
  • molecular target data representing the human genome 
  • data for model organisms
The database can be queried for drug (by name or chemical entity), drug target, cell line model, etc.

The results are computer generated 'on the fly' from collaborator databases such as ChEMBL, ROCK and Array Express.

Example: ibrutinib (Imbruvica)

On the canSAR homepage, enter ibrutinib in the search box.

The Output

One of the links towards the right is a stylized "S" which is "compound synopsis. Clicking on this symbol provides 4 sets of data:

  • Compound overview
  • Bioactivity data summary
  • Protein affinity profile
  • Cellline sensitivity profile

Compound overview contains the data that a chemist would love: synonym, molecular formula, IUPAC, standard InChl, SD file, ChEMBL cross-reference, protein target, compounds in the same scaffold, compound lineages.

The last two items on the list are of particular interest to folks in the patent department.

In our example, the protein target is BTK kinase (UniProt ID Q06187).

Clicking on the bioactivity data summary tells us that there are 8 bioactivity data points from biochemical assays. No data was available in canSAR for ADMET or functional assays.

Clicking on the piechart, gives a list of 8 protein targets, IC50 concentrations and journal references as shown below.

Clicking on the protein affinity profile is another way to access the data in the above table. These results show that in addition to the main target, tyrosine protein kinase BTK, this drug also inhibits other kinases at the concentrations shown below:

Affinity of ibrutinib for various tyrosine protein kinases, -Log10(Mol affinity).
  • BTK = 0.5 nM
  • BLK = 0.5 nM
  • BMX = 0.8 nM
  • EGFR = 5.6 M
  • RET = 37 nM
  • LYN = 200 nM
**The information about drug interaction with other kinases is vital to understand off-target effects and potential toxicities of the drug.

Ibrutinib drug target

Finally clicking on the ibrutinib 's drug target link Q06187 provides the following information about its molecular target BTK kinase. 
  • Synopsis overview
  • Domains and structures
  • Drugs and clinical candidates
  • Druggability
  • Chemistry
  • Ligand Efficiency Plot
  • Pathways
  • Family Tree
  • Interaction Network
  • Cellline Data Matrix
  • Gene Expression
  • Gene Copy Number Variation
  • RNA Interference
  • Mutations

BTK kinase is a non-receptor kinase involved in B cell development, differentiation and signaling, 

The last item under synopsis overview is screening and chemistry: "BTK has been screened with 839 compounds (1490 bioactivities), 85 compounds have bioactivities that show binding affinity of <= 500nM (104 bioactivities)." -- what this means is that BTK kinase is a validated target for which several companies may be developing drugs. There is a link to further find out which other compounds may have been tested.

The power of canSAR database

Bissan Al-Lazikani and colleagues, the architects of canSAR database, evaluated a set of 479 cancer-associated genes, of which 46 were not previously considered as cancer targets. This research was published in the January 2013 issue of the Nature Reviews Drug Discovery.
"Selecting the best targets is a key challenge for drug discovery, and achieving this effectively, efficiently and systematically is particularly important for prioritizing candidates from the sizeable lists of potential therapeutic targets that are now emerging from large-scale multi-omics initiatives, such as those in oncology. Here, we describe an objective, systematic, multifaceted computational assessment of biological and chemical space that can be applied to any human gene set to prioritize targets for therapeutic exploration. We use this approach to evaluate an exemplar set of 479 cancer-associated genes, reveal the tension between biological relevance and chemical tractability, and describe major gaps in available knowledge that could be addressed to aid objective decision-making. We also propose drug repurposing opportunities and identify potentially druggable cancer-associated proteins that have been poorly explored with regard to the discovery of small-molecule modulators, despite their biological relevance." By Mishal N. Patel, Mark D. Halling-Brown, Joseph E. Tym, Paul Workman & Bissan Al-Lazikani. Nature Reviews Drug Discovery, January 2013.

Patel MN, Halling-Brown MD, Tym JE, Workman P, & Al-Lazikani B (2013). Objective assessment of cancer genes for drug discovery. Nature reviews. Drug discovery, 12 (1), 35-50 PMID: 23274470

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