Biomedical subjects

Alex Gutteridge

Publications and source records attributed to Alex Gutteridge.

6 recordsLinked to original sources

PubMed2006

MIMOX: a web tool for phage display based epitope mapping.

BACKGROUND: Phage display is widely used in basic research such as the exploration of protein-protein interaction sites and networks, and applied research such as the development of new drugs, vaccines, and diagnostics. It has also become a promising method for epitope mapping. Research on new algorithms that assist and automate phage display based epitope mapping has attracted many groups. Most of the existing tools have not been implemented as an online service until now however, making it less convenient for the community to access, utilize, and evaluate them. RESULTS: We present MIMOX, a free web tool that helps to map the native epitope of an antibody based on one or more user supplied mimotopes and the antigen structure. MIMOX was coded in Perl using modules from the Bioperl project. It has two sections. In the first section, MIMOX provides a simple interface for ClustalW to align a set of mimotopes. It also provides a simple statistical method to derive the consensus sequence and embeds JalView as a Java applet to view and manage the alignment. In the second section, MIMOX can map a single mimotope or a consensus sequence of a set of mimotopes, on to the corresponding antigen structure and search for all of the clusters of residues that could represent the native epitope. NACCESS is used to evaluate the surface accessibility of the candidate clusters; and Jmol is embedded to view them interactively in their 3D context. Initial case studies show that MIMOX can reproduce mappings from existing tools such as FINDMAP and 3DEX, as well as providing novel, rational results. CONCLUSION: A web-based tool called MIMOX has been developed for phage display based epitope mapping. As a publicly available online service in this area, it is convenient for the community to access, utilize, and evaluate, complementing other existing programs. MIMOX is freely available at http://web.kuicr.kyoto-u.ac.jp/~hjian/mimox.

Bacteriophages↗

PubMed2005

Understanding nature's catalytic toolkit.

Enzymes catalyse numerous reactions in nature, often causing spectacular accelerations in the catalysis rate. One aspect of understanding how enzymes achieve these feats is to explore how they use the limited set of residue side chains that form their 'catalytic toolkit'. Combinations of different residues form 'catalytic units' that are found repeatedly in different unrelated enzymes. Most catalytic units facilitate rapid catalysis in the enzyme active site either by providing charged groups to polarize substrates and to stabilize transition states, or by modifying the pKa values of other residues to provide more effective acids and bases. Given recent efforts to design novel enzymes, the rise of structural genomics and subsequent efforts to predict the function of enzymes from their structure, these units provide a simple framework to describe how nature uses the tools at her disposal, and might help to improve techniques for designing and predicting enzyme function.

Amino Acids↗

PubMed2005

Effective function annotation through catalytic residue conservation.

Because of the extreme impact of genome sequencing projects, protein sequences without accompanying experimental data now dominate public databases. Homology searches, by providing an opportunity to transfer functional information between related proteins, have become the de facto way to address this. Although a single, well annotated, close relationship will often facilitate sufficient annotation, this situation is not always the case, particularly if mutations are present in important functional residues. When only distant relationships are available, the transfer of function information is more tenuous, and the likelihood of encountering several well annotated proteins with different functions is increased. The consequence for a researcher is a range of candidate functions with little way of knowing which, if any, are correct. Here, we address the problem directly by introducing a computational approach to accurately identify and segregate related proteins into those with a functional similarity and those where function differs. This approach should find a wide range of applications, including the interpretation of genomics/proteomics data and the prioritization of targets for high-throughput structure determination. The method is generic, but here we concentrate on enzymes and apply high-quality catalytic site data. In addition to providing a series of comprehensive benchmarks to show the overall performance of our approach, we illustrate its utility with specific examples that include the correct identification of haptoglobin as a nonenzymatic relative of trypsin, discrimination of acid-d-amino acid ligases from a much larger ligase pool, and the successful annotation of BioH, a structural genomics target.

Amino Acid Sequence↗

PubMed2004

Conformational changes observed in enzyme crystal structures upon substrate binding.

The theory of induced fit predicts that enzymes undergo conformational changes as they bind their substrate. We have analysed the structures of 60 different enzymes to see if conformational changes are observed between the apo form, and the substrate (or substrate analog) bound form. In each enzyme the residues responsible for catalysis and substrate binding are known and are examined to see how the active site area is affected by conformational changes. Surprisingly, we find that induced fit motions in most enzymes is very small (usually 1 A RMSD between the apo and substrate-bound forms across the whole protein). We also find that there is a significant difference between the motions undergone by the binding residues and those undergone by the catalytic residues. The binding residues tend to exhibit larger backbone motions, but both binding and catalytic residues show the same, considerable, amount of side-chain flexibility. Knowing the extent of induced fit in enzymes is important for our understanding of the principles of enzyme catalysis and also for improving ligand docking and structural template searching.

Apoenzymes↗

PubMed2004

Conformational change in substrate binding, catalysis and product release: an open and shut case?

The role of conformational change in substrate binding, catalysis and product release is reviewed for 11 enzymes, for which crystal structures are available for the apo, substrate- and product-bound states. The extent of global conformational changes is measured, and the movements of the functional regions involved in catalysis and ligand binding are compared to the rest of the structure. We find that most of these enzymes undergo relatively small amounts of conformational change and particularly small changes in catalytic residue geometry, usually less than 1 A. In some enzymes there is significant movement of the binding residues, usually on surface loops.

Catalysis↗

PubMed2003

Using a neural network and spatial clustering to predict the location of active sites in enzymes.

Structural genomics projects aim to provide a sharp increase in the number of structures of functionally unannotated, and largely unstudied, proteins. Algorithms and tools capable of deriving information about the nature, and location, of functional sites within a structure are increasingly useful therefore. Here, a neural network is trained to identify the catalytic residues found in enzymes, based on an analysis of the structure and sequence. The neural network output, and spatial clustering of the highly scoring residues are then used to predict the location of the active site.A comparison of the performance of differently trained neural networks is presented that shows how information from sequence and structure come together to improve the prediction accuracy of the network. Spatial clustering of the network results provides a reliable way of finding likely active sites. In over 69% of the test cases the active site is correctly predicted, and a further 25% are partially correctly predicted. The failures are generally due to the poor quality of the automatically generated sequence alignments. We also present predictions identifying the active site, and potential functional residues in five recently solved enzyme structures, not used in developing the method. The method correctly identifies the putative active site in each case. In most cases the likely functional residues are identified correctly, as well as some potentially novel functional groups.

Algorithms↗