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

Abstract

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.

Figure 1

Overview of HOPE's process flow. The user submits a sequence and a mutation. HOPE will first collect information from a wide range of information sources. These sources include: WHAT IF for structural calculations on either the PDB file or a homology model that was build by YASARA, HSSP for conservation scores, DAS-servers for sequence-based predictions and Uniprot for sequence annotations. The data is stored in HOPE's information system. The data is combined with the known properties of the amino acids in a decision schedule. The result is a report shown on the HOPE website that will focus on the effect of the submitted mutation on the 3D-structure of the protein. The text and figures can be used in articles and publications.

Figure 2

HOPE's input screen. The user can submit a sequence of interest and indicate the mutated residue with two simple mouse-clicks. In this example HOPE will analyze a leucine to proline mutation on position 25 of the plant protein Crambin.

Figure 3

The two zones of sequence alignment identity that indicate the likelihood of adopting similar structures. Two aligned sequences are highly likely to have similar folds if their length and percentage sequence identity fall in the region above the threshold (black line). HOPE will build a homology model when the identity between the template and submitted sequence falls in this zone. In case the sequence identity is less than 5% above this threshold (grey line) HOPE will build a model but will also warn that the model is based on a template with low identity. The region below the threshold (indicated with a cross) indicates the zone where inference of structural similarity cannot be made, thus making it difficult to determine if model building will be possible. (Figure free after Sander and Schneider [25]).

Figure 4

Example of HOPE's output. A simplified example of HOPE's output. A) Explanation of the used method (structure, modelling or predictions) and links to the relevant databases. B) Text and pictures that explain the differences between the wild-type and mutant residue. (Text is left out of this figure for clarity.) C) Paragraph of the report explaining the effect of the mutation on contacts made by the residue, a disulfid bond in this case. It contains a link to the wiki-entry "cysteine" and "disulfid bond". D) Images/animations that show the effect of the mutation on the structure.

Figure 5

Detailed overview of HOPE's components. HOPE's input consists of the sequence and the mutation. The sequence is used for a BLAST search against the databases. Using the accession code (and PDB-file if available) HOPE can collect information from a series of information sources: WHAT IF calculations on the PDB-file or homology model built by YASARA, annotations in the Uniprot database, HSSP conservation scores and sequence-based predictions by DAS-servers. The information is combined in a decision scheme and a report is generated. This report is illustrated with pictures and animations and difficult keywords are linked to our own online dictionary.