http://babylone.ulb.ac.be/popmusic

BackgroundThe rational design of modified proteins with controlled stability is of extreme importance in a whole range of applications, notably in the biotechnological and environmental areas, where proteins are used for their catalytic or other functional activities. Future breakthroughs in medical research may also be expected from an improved understanding of the effect of naturally occurring disease-causing mutations on the molecular level.ResultsPoPMuSiC-2.1 is a web server that predicts the thermodynamic stability changes caused by single site mutations in proteins, using a linear combination of statistical potentials whose coefficients depend on the solvent accessibility of the mutated residue. PoPMuSiC presents good prediction performances (correlation coefficient of 0.8 between predicted and measured stability changes, in cross validation, after exclusion of 10% outliers). It is moreover very fast, allowing the prediction of the stability changes resulting from all possible mutations in a medium size protein in less than a minute. This unique functionality is user-friendly implemented in PoPMuSiC and is particularly easy to exploit. Another new functionality of our server concerns the estimation of the optimality of each amino acid in the sequence, with respect to the stability of the structure. It may be used to detect structural weaknesses, i.e. clusters of non-optimal residues, which represent particularly interesting sites for introducing targeted mutations. This sequence optimality data is also expected to have significant implications in the prediction and the analysis of particular structural or functional protein regions. To illustrate the interest of this new functionality, we apply it to a dataset of known catalytic sites, and show that a much larger than average concentration of structural weaknesses is detected, quantifying how these sites have been optimized for function rather than stability.ConclusionThe freely available PoPMuSiC-2.1 web server is highly useful for identifying very rapidly a list of possibly relevant mutations with the desired stability properties, on which subsequent experimental studies can be focused. It can also be used to detect sequence regions corresponding to structural weaknesses, which could be functionally important or structurally delicate regions, with obvious applications in rational protein design.

The ability of proteins to establish highly selective interactions with a variety of (macro)molecular partners is a crucial prerequisite to the realization of their biological functions. The availability of computational tools to evaluate the impact of mutations on protein–protein binding can therefore be valuable in a wide range of industrial and biomedical applications, and help rationalize the consequences of non-synonymous single-nucleotide polymorphisms. BeAtMuSiC (http://babylone.ulb.ac.be/beatmusic) is a coarse-grained predictor of the changes in binding free energy induced by point mutations. It relies on a set of statistical potentials derived from known protein structures, and combines the effect of the mutation on the strength of the interactions at the interface, and on the overall stability of the complex. The BeAtMuSiC server requires as input the structure of the protein–protein complex, and gives the possibility to assess rapidly all possible mutations in a protein chain or at the interface, with predictive performances that are in line with the best current methodologies.

We propose a novel and flexible derivation scheme of statistical, database-derived, potentials, which allows one to take simultaneously into account specific correlations between several sequence and structure descriptors. This scheme leads to the decomposition of the total folding free energy of a protein into a sum of lower order terms, thereby giving the possibility to analyze independently each contribution and clarify its significance and importance, to avoid overcounting certain contributions, and to deal more efficiently with the limited size of the database. In addition, this derivation scheme appears as quite general, for many previously developed potentials can be expressed as particular cases of our formalism. We use this formalism as a framework to generate different residue-based energy functions, whose performances are assessed on the basis of their ability to discriminate genuine proteins from decoy models. The optimal potential is generated as a combination of several coupling terms, measuring correlations between residue types, backbone torsion angles, solvent accessibilities, relative positions along the sequence, and interresidue distances. This potential outperforms all tested residue-based potentials, and even several atom-based potentials. Its incorporation in algorithms aiming at predicting protein structure and stability should therefore substantially improve their performances.

The ability to rationally increase the stability and solubility of recombinant proteins has long been a goal of biotechnology and has significant implications for biomedical research. Poorly soluble enzymes, for example, result in the need for larger reaction volumes, longer incubation times, and more restricted reaction conditions, all of which increase the cost and have a negative impact on the feasibility of the process. Rational design is achieved here by means of the PoPMuSiC program, which performs in silico predictions of stability changes upon single-site mutations. We have used this program to increase the stability of the tobacco etch virus (TEV) protein. TEV is a 27-kDa nuclear inclusion protease with stringent specificity that is commonly used for the removal of solubility tags during protein purification protocols. However, while recombinant TEV can be produced in large quantities, a limitation is its relatively poor solubility (generally ;1 mg/mL), which means that large volumes and often long incubation times are required for efficient cleavage. Following PoPMuSiC analysis of TEV, five variants predicted to be more stable than the wild type were selected for experimental analysis of their stability, solubility, and activity. Of these, two were found to enhance the solubility of TEV without compromising its functional activity. In addition, a fully active double mutant was found to remain soluble at concentrations in excess of 40 mg/mL. This modified TEV appears thus as an interesting candidate to be used in recombinant protein technology.Keywords: TEV protease; stability; protein engineering; protein purification; in silico design Recombinant proteins and peptides have an almost endless list of applications in biotechnology, biomedicine, and drug development. However, the limited stability and solubility of recombinant proteins can severely reduce their usefulness (Cabrita and Bottomley 2004;Chow et al. 2006). Thus a primary objective and a significant challenge in the biotechnology sector is the ability to increase through mutagenesis, the stability and solubility of proteins and peptides without affecting their activity. Two types of approaches can be used to guide the selection of appropriate mutations. The first is directed evolution experiments, where the protein is subjected to random mutagenesis and then screened for the chosen property (Roodveldt et al. 2005;van den Berg et al. 2006). The second approach, used here on the protease TEV, exploits bioinformatics programs to rationally design mutants presenting the required properties.The 27-kDa C-type cysteine protease of the tobacco etch virus (TEV) is commonly used to remove solubility tags from either the N or C termini of recombinant 3 These authors contributed equally to this work. Reprint requests to: Stephen Bottomley, Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Monash University, Clayton 3800, Australia; e-mail: steve.bottomley@med. monash.edu.au; fax: 61-3-99054699.Article published online...

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side chain sampling and backbone relaxation, and evaluated packing, electrostatic and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of methodological improvement.

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The goal of controlling protein thermostability is tackled here through establishing, by in silico analyses, the relative weight of residue-residue interactions in proteins as a function of temperature. We have designed for that purpose a (melting-) temperature-dependent, statistical distance potential, where the interresidue distances are computed between the side-chain geometric centers or their functional centers. Their separate derivation from proteins of either high or low thermal resistance reveals the interactions that contribute most to stability in different temperature ranges. Thermostabilizing interactions include salt bridges and cation-pi interactions (especially those involving arginine), aromatic interactions, and H-bonds between negatively charged and some aromatic residues. In contrast, H-bonds between two polar noncharged residues or between a polar noncharged residue and a negatively charged residue are relatively less stabilizing at high temperatures. An important observation is that it is necessary to consider both repulsive and attractive interactions in overall thermostabilization, as the degree of repulsion may also vary with temperature. These temperature-dependent potentials are not only useful for the identification of meso- and thermostabilizing pair interactions, but also exhibit predictive power, as illustrated by their ability to predict the melting temperature of a protein based on the melting temperature of homologous proteins.