The degree of evolutionary conservation of an amino acid in a protein or a nucleic acid in DNA/RNA reflects a balance between its natural tendency to mutate and the overall need to retain the structural integrity and function of the macromolecule. The ConSurf web server (http://consurf.tau.ac.il), established over 15 years ago, analyses the evolutionary pattern of the amino/nucleic acids of the macromolecule to reveal regions that are important for structure and/or function. Starting from a query sequence or structure, the server automatically collects homologues, infers their multiple sequence alignment and reconstructs a phylogenetic tree that reflects their evolutionary relations. These data are then used, within a probabilistic framework, to estimate the evolutionary rates of each sequence position. Here we introduce several new features into ConSurf, including automatic selection of the best evolutionary model used to infer the rates, the ability to homology-model query proteins, prediction of the secondary structure of query RNA molecules from sequence, the ability to view the biological assembly of a query (in addition to the single chain), mapping of the conservation grades onto 2D RNA models and an advanced view of the phylogenetic tree that enables interactively rerunning ConSurf with the taxa of a sub-tree.

It is informative to detect highly conserved positions in proteins and nucleic acid sequence/structure since they are often indicative of structural and/or functional importance. ConSurf (http://consurf.tau.ac.il) and ConSeq (http://conseq.tau.ac.il) are two well-established web servers for calculating the evolutionary conservation of amino acid positions in proteins using an empirical Bayesian inference, starting from protein structure and sequence, respectively. Here, we present the new version of the ConSurf web server that combines the two independent servers, providing an easier and more intuitive step-by-step interface, while offering the user more flexibility during the process. In addition, the new version of ConSurf calculates the evolutionary rates for nucleic acid sequences. The new version is freely available at: http://consurf.tau.ac.il/.

Key amino acid positions that are important for maintaining the 3D structure of a protein and/or its function(s), e.g. catalytic activity, binding to ligand, DNA or other proteins, are often under strong evolutionary constraints. Thus, the biological importance of a residue often correlates with its level of evolutionary conservation within the protein family. ConSurf () is a web-based tool that automatically calculates evolutionary conservation scores and maps them on protein structures via a user-friendly interface. Structurally and functionally important regions in the protein typically appear as patches of evolutionarily conserved residues that are spatially close to each other. We present here version 3.0 of ConSurf. This new version includes an empirical Bayesian method for scoring conservation, which is more accurate than the maximum-likelihood method that was used in the earlier release. Various additional steps in the calculation can now be controlled by a number of advanced options, thus further improving the accuracy of the calculation. Moreover, ConSurf version 3.0 also includes a measure of confidence for the inferred amino acid conservation scores.

A set of examples is available at http://consurf.tau.ac.il under 'GALLERY'.

Rate4Site estimates the rate of evolution of amino acid sites using the maximum likelihood (ML) principle. The ML estimate of the rates considers the topology and branch lengths of the phylogenetic tree, as well as the underlying stochastic process. To demonstrate its potency, we study the Src SH2 domain. Like previously established methods, Rate4Site detected the SH2 peptide-binding groove. Interestingly, it also detected inter-domain interactions between the SH2 domain and the rest of the Src protein that other methods failed to detect.

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org.

We measured directly the binding of Lys3, Lys5, and Lys7 to vesicles containing acidic phospholipids. When the vesicles contain 33% acidic lipids and the aqueous solution contains 100 mM monovalent salt, the standard Gibbs free energy for the binding of these peptides is 3, 5, and 7 kcal/mol, respectively. The binding energies decrease as the mol% of acidic lipids in the membrane decreases and/or as the salt concentration increases. Several lines of evidence suggest that these hydrophilic peptides do not penetrate the polar headgroup region of the membrane and that the binding is mainly due to electrostatic interactions. To calculate the binding energies from classical electrostatics, we applied the nonlinear Poisson-Boltzmann equation to atomic models of the phospholipid bilayers and the basic peptides in aqueous solution. The electrostatic free energy of interaction, which arises from both a long-range coulombic attraction between the positively charged peptide and the negatively charged lipid bilayer, and a short-range Born or image charge repulsion, is a minimum when approximately 2.5 A (i.e., one layer of water) exists between the van der Waals surfaces of the peptide and the lipid bilayer. The calculated molar association constants, K, agree well with the measured values: K is typically about 10-fold smaller than the experimental value (i.e., a difference of about 1.5 kcal/mol in the free energy of binding). The predicted dependence of K (or the binding free energies) on the ionic strength of the solution, the mol% of acidic lipids in the membrane, and the number of basic residues in the peptide agree very well with the experimental measurements. These calculations are relevant to the membrane binding of a number of important proteins that contain clusters of basic residues.

The ConSeq methodology, a description of its performance in a set of five well-documented proteins, a comparison to other methods, and the outcome of its application to a set of 111 proteins of unknown function, are presented at http://conseq.bioinfo.tau.ac.il/ under 'OVERVIEW', 'VALIDATION', 'COMPARISON' and 'PREDICTIONS', respectively.