BackgroundMany 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.ResultsIn 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.ConclusionsWe 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.
Ten years of experience with molecular class-specific information systems (MCSIS) such as with the hand-curated G protein-coupled receptor database (GPCRDB) or the semiautomatically generated nuclear receptor database has made clear that a wide variety of questions can be answered when protein-related data from many different origins can be flexibly combined. MCSISes revolve around a multiple sequence alignment (MSA) that includes "all" available sequences from the entire superfamily, and it has been shown at many occasions that the quality of these alignments is the most crucial aspect of the MCSIS approach. We describe here a system called 3DM that can automatically build an entire MCSIS. 3DM bases the MSA on a multiple structure alignment, which implies that the availability of a large number of superfamily members with a known three-dimensional structure is a requirement for 3DM to succeed well. Thirteen MCSISes were constructed and placed on the Internet for examination. These systems have been instrumental in a large series of research projects related to enzyme activity or the understanding and engineering of specificity, protein stability engineering, DNA-diagnostics, drug design, and so forth.
Aligning the haystack to expose the needle: The 3DM method was used to generate a comprehensive database of the α/β‐hydrolase fold enzyme superfamily. This database facilitates the analysis of structure–function relationships and enables novel insights into this superfamily to be made. In addition high‐quality libraries for protein engineering can be easily designed.
Correlated mutation analyses (CMA) on multiple sequence alignments are widely used for the prediction of the function of amino acids. The accuracy of CMA-based predictions is mainly determined by the number of sequences, by their evolutionary distances, and by the quality of the alignments. These criteria are best met in structure-based sequence alignments of large super-families. So far, CMA-techniques have mainly been employed to study the receptor interactions. The present work shows how a novel CMA tool, called Comulator, can be used to determine networks of functionally related residues in enzymes. These analyses provide leads for protein engineering studies that are directed towards modification of enzyme specificity or activity. As proof of concept, Comulator has been applied to four enzyme super-families: the isocitrate lyase/phoshoenol-pyruvate mutase super-family, the hexokinase super-family, the RmlC-like cupin super-family, and the FAD-linked oxidases super-family. In each of those cases networks of functionally related residue positions were discovered that upon mutation influenced enzyme specificity and/or activity as predicted. We conclude that CMA is a powerful tool for redesigning enzyme activity and selectivity.
Sucrose phosphorylase is a promising biocatalyst for the glycosylation of a wide variety of acceptor molecules, but its low thermostability is a serious drawback for industrial applications. In this work, the stability of the enzyme from Bifidobacterium adolescentis has been significantly improved by a combination of smart and rational mutagenesis. The former consists of substituting the most flexible residues with amino acids that occur more frequently at the corresponding positions in related sequences, while the latter is based on a careful inspection of the enzyme's crystal structure to promote electrostatic interactions. In this way, a variant enzyme could be created that contains six mutations and whose half-life at the industrially relevant temperature of 60 °C has more than doubled compared with the wild-type enzyme. An increased stability in the presence of organic co-solvents could also be observed, although these effects were most noticeable at low temperatures.
Genetic disorders are often caused by nonsynonymous nucleotide changes in one or more genes associated with the disease. Specific amino acid changes, however, can lead to large variability of phenotypic expression. For many genetic disorders this results in an increasing amount of publications describing phenotype-associated mutations in disorder-related genes. Keeping up with this stream of publications is essential for molecular diagnostics and translational research purposes but often impossible due to time constraints: there are simply too many articles to read. To help solve this problem, we have created Mutator, an automated method to extract mutations from full-text articles. Extracted mutations are crossreferenced to sequence data and a scoring method is applied to distinguish false-positives. To analyze stored and new mutation data for their (potential) effect we have developed Validator, a Web-based tool specifically designed for DNA diagnostics. Fabry disease, a monogenetic gene disorder of the GLA gene, was used as a test case. A structure-based sequence alignment of the alpha-amylase superfamily was used to validate results. We have compared our data with existing Fabry mutation data sets obtained from the HGMD and Swiss-Prot databases. Compared to these data sets, Mutator extracted 30% additional mutations from the literature.
CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity. This finding allows to assign a function to residues for which no data is available yet in the literature. A mutant library was designed to mutate residues observed in a group of co-evolving residues predicted to be involved in enantioselectivity, but for which no literature data is available yet. The resulting set of mutations indeed showed many instances of increased enantioselectivity.
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