Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces

H Venselaar, TAH Te Beek, RKP Kuipers… - BMC …, 2010 - Springer
H Venselaar, TAH Te Beek, RKP Kuipers, ML Hekkelman, G Vriend
BMC bioinformatics, 2010Springer
Background Many newly detected point mutations are located in protein-coding regions of
the human genome. Knowledge of their effects on the protein's 3D structure provides insight
into the protein's mechanism, can aid the design of further experiments, and eventually can
lead to the development of new medicines and diagnostic tools. Results In this article we
describe HOPE, a fully automatic program that analyzes the structural and functional effects
of point mutations. HOPE collects information from a wide range of information sources …
Background
Many newly detected point mutations are located in protein-coding regions of the human genome. Knowledge of their effects on the protein's 3D structure provides insight into the protein's mechanism, can aid the design of further experiments, and eventually can lead to the development of new medicines and diagnostic tools.
Results
In this article we describe HOPE, a fully automatic program that analyzes the structural and functional effects of point mutations. HOPE collects information from a wide range of information sources including calculations on the 3D coordinates of the protein by using WHAT IF Web services, sequence annotations from the UniProt database, and predictions by DAS services. Homology models are built with YASARA. Data is stored in a database and used in a decision scheme to identify the effects of a mutation on the protein's 3D structure and function. HOPE builds a report with text, figures, and animations that is easy to use and understandable for (bio)medical researchers.
Conclusions
We tested HOPE by comparing its output to the results of manually performed projects. In all straightforward cases HOPE performed similar to a trained bioinformatician. The use of 3D structures helps optimize the results in terms of reliability and details. HOPE's results are easy to understand and are presented in a way that is attractive for researchers without an extensive bioinformatics background.
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