The SPPIDER protein interface recognition server can be used to: (1) predict residues to be at the putative protein interface(s) by considering single protein chain with resolved 3D structure; (2) analyse protein-protein complex with given 3D structural information and identify residues that are being in interchain contact.
NETASA ,a server, for predicting solvent accessibility of amino acids using our newly optimized neural network algorithm. Several new features in the neural network architecture and training method have been introduced, and the network learns faster to provide accuracy values, which are comparable or better than other methods of ASA prediction.
RVP-net is an online program for the prediction of real valued solvent accessibility. All previous methods of accessible surface area (ASA) predictions classify amino acid residues into exposure states and named them buried or exposed based on different thresholds. Real values in some cases were generated by taking the mid points of these state thresholds. This is the first method, which provides a direct prediction of ASA without making exposure categories and achieves results better than 19% mean absolute error.
ASAView is an algorithm, an application and a database of schematic representations of solvent accessibility of amino acid residues within proteins. A characteristic two-dimensional spiral plot of solvent accessibility provides a convenient graphical view of residues in terms of their exposed surface areas. In addition, sequential plots in the form of bar charts are also provided. Online plots of the proteins included in the entire Protein Data Bank (PDB), are provided for the entire protein as well as their chains separately.
WESA is a meta-predictor, based on a Weighted Ensemble of five methods, for Solvent Accessibility of residues, using the protein sequence as input. It has an expected accuracy of 80%. The prediction can be used for structure prediction.