Marianne Rooman

Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks

MOTIVATION The rational design of proteins with modified properties, through amino acid substitutions, is of crucial importance in a large variety of applications. Given the huge number of possible substitutions, every protein engineering project would benefit strongly from the guidance of in silico methods able to predict rapidly, and with reasonable accuracy, the stability changes resulting from all possible mutations in a protein. RESULTS We exploit newly developed statistical potentials, based on a formalism that highlights the coupling between four protein sequence and structure descriptors, and take into account the amino acid volume variation upon mutation. The stability change is expressed as a linear combination of these energy functions, whose proportionality coefficients vary with the solvent accessibility of the mutated residue and are identified with the help of a neural network. A correlation coefficient of R = 0.63 and a root mean square error of sigma(c) = 1.15 kcal/mol between measured and predicted stability changes are obtained upon cross-validation. These scores reach R = 0.79, and sigma(c) = 0.86 kcal/mol after exclusion of 10% outliers. The predictive power of our method is shown to be significantly higher than that of other programs described in the literature. AVAILABILITY http://babylone.ulb.ac.be/popmusic

Generating and testing protein folds

Prediction of three-dimensional protein structure has become once more the stage of intense activity. New approaches combine methods from computational chemistry and statistical mechanics with sequence alignment procedures and analyses of known structures. A key role is played by effective potentials derived from the database of protein structures, which provide a simpler description of the protein conformation. The novelty in the prediction methods is the use of sequence and structure libraries, which are screened against each other in the search for compatible sequence-structure matches. The ultimate goal is to predict which of the known folds is compatible with a given sequence in the absence of detectable sequence homology. Although this cannot yet be achieved reliably, results obtained so far are very promising, a sign for some that a practical solution to the protein folding problem may be in sight. In ab initio tertiary structure predictions, which do not rely on an existing fold, progress has been slower. Computer experiments with very simple model systems are however providing valuable insight, and developments of smarter strategies for searching conformational space hold promise for the future.

Identification of predictive sequence motifs limited by protein structure data base size

Associations between short amino acid sequence patterns and protein secondary structure classes can be found by searching a data base of known protein structures. Analysis of these associations suggests that secondary structure of proteins can be determined locally by sequence motifs of high predictive value, but at present our ability to find these motifs is limited by the size of the available data bases.

Optimality of the genetic code with respect to protein stability and amino-acid frequencies

BackgroundThe genetic code is known to be efficient in limiting the effect of mistranslation errors. A misread codon often codes for the same amino acid or one with similar biochemical properties, so the structure and function of the coded protein remain relatively unaltered. Previous studies have attempted to address this question quantitatively, by estimating the fraction of randomly generated codes that do better than the genetic code in respect of overall robustness. We extended these results by investigating the role of amino-acid frequencies in the optimality of the genetic code.ResultsWe found that taking the amino-acid frequency into account decreases the fraction of random codes that beat the natural code. This effect is particularly pronounced when more refined measures of the amino-acid substitution cost are used than hydrophobicity. To show this, we devised a new cost function by evaluating in silico the change in folding free energy caused by all possible point mutations in a set of protein structures. With this function, which measures protein stability while being unrelated to the codes structure, we estimated that around two random codes in a billion (109) are fitter than the natural code. When alternative codes are restricted to those that interchange biosynthetically related amino acids, the genetic code appears even more optimal.ConclusionsThese results lead us to discuss the role of amino-acid frequencies and other parameters in the genetic codes evolution, in an attempt to propose a tentative picture of primitive life.

Automatic definition of recurrent local structure motifs in proteins

An automatic procedure for defining recurrent folding motifs in proteins of known structure is described. These motifs are formed by short polypeptide fragments of equal size containing between four and seven residues. The method applies a classical clustering algorithm that operates on distances between selected backbone atoms. In one application, we use it to cluster all protein fragments into only four structural classes. This classification is rough considering the observed diversity of local structures, but comparable in homogeneity to the four classes of secondary structure (alpha-helix, beta-strand, turn and coil). Yet, it discriminates between extended and curved coil and distinguishes beta-bulges from beta-strands. In a second application, the clustering procedure is combined with assignment of backbone dihedral angles to allowed regions in the Ramachandran map. This produces an exhaustive repertoire of highly homogeneous families of structural motifs that contains all the beta-hairpins, beta alpha- and alpha beta-loops previously defined by manual procedures, and new structural families of which two examples, a beta alpha-loop and an alpha-helix beginning, are analyzed in detail. The described automatic procedures should be useful in categorizing structure information in proteins, thereby increasing our ability to analyze relations between structure and sequence.

The fluctuating seven-sphere in eleven-dimensional supergravity

Abstract The full bosonic spectrum of eleven-dimensional supergravity compactified on the seven-sphere is obtained. The spectrum agrees with OSp(4|8) supersymmetry despite the appearance of 294 massless scalars which are not members of the N=8 massless supermultiplet. Negative (mass)2 arises only in the scalar sector with 112 nodes whose common (mass)2 is equal to the threshold value for background stability.

Enhancing the stability and solubility of TEV protease using in silico design

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.

BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations.

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.

Godel metric as a squashed anti-de Sitter geometry

We show that the non-flat factor of the Godel metric belongs to a one-parameter family of (2 + 1)-dimensional geometries that also includes the anti-de Sitter metric. The elements of this family allow a generalization a la Kaluza-Klein of the usual (3 + 1)-dimensional Godel metric. Their lightcones can be viewed as deformations of the anti-de Sitter ones, involving tilting and squashing. This provides a simple geometric picture of the causal structure of these spacetimes, anti-de Sitter geometry appearing as the boundary between causally safe and causally pathological spaces. Furthermore, we construct a global algebraic isometric embedding of these metrics in (4 + 3)- or (3 + 4)-dimensional flat spaces, thereby illustrating in another way the occurrence of the closed timelike curves.

Cation–π/H-bond Stair Motifs at Protein–DNA Interfaces

H-bonds and cation-pi interactions between nucleic acid bases and amino acid side-chains are known to occur often concomitantly at the interface between protein and double-stranded DNA. Here we define and analyze stair-shaped motifs, which simultaneously involve base stacking, H-bond and cation-pi interactions. They consist of two successive bases along the DNA stack, one in cation-pi interaction with an amino acid side-chain that carries a total or partial positive charge, and the other H-bonded with the same side-chain. A survey of 52 high-resolution structures of protein/DNA complexes reveals the occurrence of such motifs in the majority of the complexes, the most frequent of these motifs involving Arg side-chains and G bases. These stair motifs are sometimes part of larger motifs, called multiple stair motifs, which contain several successive stairs; zinc finger proteins for example exhibit up to quadruple stairs. In another kind of stair motif extension, termed cation-pi chain motif, an amino acid side-chain or a nucleic acid base forms simultaneously two cation-pi interactions. Such a motif is observed in several homeodomains, where it involves a DNA base in cation-pi interactions with an Arg in the minor groove and an Asn in the major groove. A different cation-pi chain motif contains an Arg in cation-pi with a G and a Tyr, and is found in ets transcription factors. Still another chain motif is encountered in proteins that expulse a base from the DNA stack and replace it by an amino acid side-chain carrying a net or partial positive charge, which forms cation-pi interactions with the two neighboring bases along the DNA strand. The striking conservation of typical stair and cation-pi chain motifs within families of protein/DNA complexes suggests that they might play a structural and/or functional role and might moreover influence electron migration through the DNA double helix.