Structure of the snake-venom toxin convulxin

Snake venoms contain a number of proteins that interact with components of the haemostatic system that promote or inhibit events leading to blood- clot formation. The snake- venom protein convulxin ( Cvx) binds glycoprotein ( GP) VI, the platelet receptor for collagen, and triggers signal transduction. Here, the 2.7 Angstrom resolution crystal structure of Cvx is presented. In common with other members of this snake-venom protein family, Cvx is an alphabeta- heterodimer and conforms to the C- type lectin- fold topology. Comparison with other family members allows a set of Cvx residues that form a concave surface to be putatively implicated in GPVI binding. Unlike other family members, with the exception of flavocetin- A ( FL- A), Cvx forms an (alphabeta)(4) tetramer. This oligomeric structure is consistent with Cvx clustering GPVI molecules on the surface of platelets and as a result promoting signal transduction activity. The Cvx structure and the location of the putative binding sites suggest a model for this multimeric signalling assembly.

Protein structure prediction servers at University College London

A number of state-of-the-art protein structure prediction servers have been developed by researchers working in the Bioinformatics Unit at University College London. The popular PSIPRED server allows users to perform secondary structure prediction, transmembrane topology prediction and protein fold recognition. More recent servers include DISOPRED for the prediction of protein dynamic disorder and DomPred for domain boundary prediction.

Rapid protein domain assignment from amino acid sequence using predicted secondary structure

The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (±20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed

The PSIPRED protein structure prediction server

The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method.