linkstream2 microblog

Sequenced genomes reveal mutations that disable single genes and can point to new drugs.

Ewen Callaway

28 October 2014 Corrected:
29 October 2014

http://www.nature.com/news/geneticists-tap-human-knockouts-1.16239

You should also read the Corrections to this article
http://www.nature.com/news/geneticists-tap-human-knockouts-1.16239#/correction1

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The poster child for human-knockout efforts is a new class of drugs that block a gene known as PCSK9 (see Nature 496, 152–155; 2013). The gene was discovered in French families with extremely high cholesterol levels in the early 2000s. But researchers soon found that people with rare mutations that inactivate one copy ofPCSK9 have low cholesterol and rarely develop heart disease. The first PCSK9-blocking drugs should hit pharmacies next year, with manufacturers jostling for a share of a market that could reach US$25 billion in five years.

“I think there are hundreds more stories like PCSK9 out there, maybe even thousands,” in which a drug can mimic an advantageous
loss-of-function mutation, says Eric Topol, director of the Scripps Translational Science Institute in La Jolla, California. Mark Gerstein, a bio­informatician at Yale University in New Haven, Connecticut, predicts that human knockouts will be especially useful for identifying drugs that treat diseases of ageing. “You could imagine there’s a gene that is beneficial to you as a 25-year-old, but the thing is not doing a good job for you when you’re 75.”

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Server for predicting damaging missense #mutations
http://www.nature.com/nmeth/journal/v7/n4/full/nmeth0410-248.html Polyphen2 uses both structure & sequence (eg ASA & conservation)

http://www.ncbi.nlm.nih.gov/pubmed/20354512

Polyphen2 includes both structural and sequence features to predict the effect of nonsynonymous substitutions on protein function. Similar to many other methods, Polyphen2 uses evolutionary conservation as one of the features to identify functionally important residues. Integration of 3D-structure, membrane-specific features (PHAT matrix for TM regions) and other features such as protein-domain and active-site are the strengths of Polyphen2 compared to other sequence-based software making it a good tool for prediction.

http://www.broadinstitute.org/oncotator
https://github.com/broadinstitute/oncotator

Useful listing of data sources, viz:

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Protein Annotations

Site-specific protein annotations from UniProt.
Druggable target data from DrugBank.
Functional impact predictions from PolyPhen-2.

Cancer Annotations

Observed cancer mutation frequency annotations from COSMIC.
Cancer gene and mutation annotations from the Cancer Gene Census. Significant amplification/deletion region annotations from Tumorscape and theTCGA Copy Number Portal.
Overlapping Oncomap mutations from the Cancer Cell Line Encyclopedia. Significantly mutated gene annotations aggregated from published MutSiganalyses. Cancer gene annotations from the Familial Cancer Database.
Human DNA Repair Gene annotations from Wood et al.

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Uses bamboo testing software
https://www.atlassian.com/software/bamboo

Variant Association Tools for Quality Control and Analysis of Large-Scale Sequence and Genotyping Array Data

http://www.cell.com/ajhg/abstract/S0002-9297(14)00176-1

vs

http://papers.gersteinlab.org/papers/vat