Dimitri Gilis

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

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.

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.

A conserved cysteine residue is involved in disulfide bond formation between plant plasma membrane aquaporin monomers.

AQPs (aquaporins) are conserved in all kingdoms of life and facilitate the rapid diffusion of water and/or other small solutes across cell membranes. Among the different plant AQPs, PIPs (plasma membrane intrinsic proteins), which fall into two phylogenetic groups, PIP1 and PIP2, play key roles in plant water transport processes. PIPs form tetramers in which each monomer acts as a functional channel. The intermolecular interactions that stabilize PIP oligomer complexes and are responsible for the resistance of PIP dimers to denaturating conditions are not well characterized. In the present study, we identified a highly conserved cysteine residue in loop A of PIP1 and PIP2 proteins and demonstrated by mutagenesis that it is involved in the formation of a disulfide bond between two monomers. Although this cysteine seems not to be involved in regulation of trafficking to the plasma membrane, activity, substrate selectivity or oxidative gating of ZmPIP1s (Zm is Zea mays), ZmPIP2s and hetero-oligomers, it increases oligomer stability under denaturating conditions. In addition, when PIP1 and PIP2 are co-expressed, the loop A cysteine of ZmPIP1;2, but not that of ZmPIP2;5, is involved in the mercury sensitivity of the channels.

The first peptides: the evolutionary transition between prebiotic amino acids and early proteins.

The issues we attempt to tackle here are what the first peptides did look like when they emerged on the primitive earth, and what simple catalytic activities they fulfilled. We conjecture that the early functional peptides were short (3-8 amino acids long), were made of those amino acids, Gly, Ala, Val and Asp, that are abundantly produced in many prebiotic synthesis experiments and observed in meteorites, and that the neutralization of Asps negative charge is achieved by metal ions. We further assume that some traces of these prebiotic peptides still exist, in the form of active sites in present-day proteins. Searching these proteins for prebiotic peptide candidates led us to identify three main classes of motifs, bound mainly to Mg(2+) ions: D(F/Y)DGD corresponding to the active site in RNA polymerases, DGD(G/A)D present in some kinds of mutases, and DAKVGDGD in dihydroxyacetone kinase. All three motifs contain a DGD submotif, which is suggested to be the common ancestor of all active peptides. Moreover, all three manipulate phosphate groups, which was probably a very important biological function in the very first stages of life. The statistical significance of our results is supported by the frequency of these motifs in todays proteins, which is three times higher than expected by chance, with a P-value of 3 x 10(-2). The implications of our findings in the context of the appearance of life and the possibility of an experimental validation are discussed.

Sequence-structure signals of 3D domain swapping in proteins

Three-dimensional domain swapping occurs when two or more identical proteins exchange identical parts of their structure to generate an oligomeric unit. It affects proteins with diverse sequences and structures, and is expected to play important roles in evolution, functional regulation and even conformational diseases. Here, we search for traces of domain swapping in the protein sequence, by means of algorithms that predict the structure and stability of proteins using database-derived potentials. Regions whose sequences are not optimal with regard to the stability of the native structure, or showing marked intrinsic preferences for non-native conformations in absence of tertiary interactions are detected in most domain-swapping proteins. These regions are often located in areas crucial in the swapping process and are likely to influence it on a kinetic or thermodynamic level. In addition, cation-pi interactions are frequently observed to zip up the edges of the interface between intertwined chains or to involve hinge loop residues, thereby modulating stability. We end by proposing a set of mutations altering the swapping propensities, whose experimental characterization would contribute to refine our in silico derived hypotheses.

In Vitro and In Silico Design of α1-antitrypsin Mutants with Different Conformational Stabilities

Alpha(1)-antitrypsin, a protein belonging to the serine protease inhibitor (serpin) superfamily, is characterized by the ability to undergo dramatic conformational changes leading to inactive polymers. Serpin polymerization, which causes a range of diseases such as emphysema, thrombosis and dementia, occurs through a process in which the reactive center loop residues of one serpin molecule insert into the A beta-sheet of another. PoPMuSiC, a program that uses database-derived mean force potentials to predict changes in folding free energy resulting from single-site mutations, was used to modulate rationally the polymerization propensity of alpha(1)-antitrypsin. This was accomplished by generating mutants with a stabilized active form and destabilized polymerized form, or the converse. Of these mutants, five were expressed and characterized experimentally. In agreement with the predictions, three of them, K331F, K331I and K331V, were shown to stabilize the active form and decrease the polymerization rate, and one of them, S330R, to destabilize the active form and to increase polymerization. Only one mutant (K331T) did not display the expected behavior. Thus, strikingly, the adjacent positions 330 and 331, which are located at the beginning of the beta-strand next to the additionally inserted beta-strand in the polymerized form, have opposite effects on the conformational change. These residues therefore appear to play a key role in inducing or preventing such conformational change.

Flanking domain stability modulates the aggregation kinetics of a polyglutamine disease protein.

Spinocerebellar Ataxia Type 3 (SCA3) is one of nine polyglutamine (polyQ) diseases that are all characterized by progressive neuronal dysfunction and the presence of neuronal inclusions containing aggregated polyQ protein, suggesting that protein misfolding is a key part of this disease. Ataxin‐3, the causative protein of SCA3, contains a globular, structured N‐terminal domain (the Josephin domain) and a flexible polyQ‐containing C‐terminal tail, the repeat‐length of which modulates pathogenicity. It has been suggested that the fibrillogenesis pathway of ataxin‐3 begins with a non‐polyQ‐dependent step mediated by Josephin domain interactions, followed by a polyQ‐dependent step. To test the involvement of the Josephin domain in ataxin‐3 fibrillogenesis, we have created both pathogenic and nonpathogenic length ataxin‐3 variants with a stabilized Josephin domain, and have both stabilized and destabilized the isolated Josephin domain. We show that changing the thermodynamic stability of the Josephin domain modulates ataxin‐3 fibrillogenesis. These data support the hypothesis that the first stage of ataxin‐3 fibrillogenesis is caused by interactions involving the non‐polyQ containing Josephin domain and that the thermodynamic stability of this domain is linked to the aggregation propensity of ataxin‐3.

Evidence that interaction between conserved residues in transmembrane helices 2, 3 and 7 are crucial for human VPAC1 receptor activation.

The VPAC1 receptor belongs to family B of G protein-coupled receptors (GPCR-B) and is activated upon binding of the vasoactive intestinal peptide (VIP). Despite the recent determination of the structure of the N terminus of several members of this receptor family, little is known about the structure of the transmembrane (TM) region and about the molecular mechanisms leading to activation. In the present study, we designed a new structural model of the TM domain and combined it with experimental mutagenesis experiments to investigate the interaction network that governs ligand binding and receptor activation. Our results suggest that this network involves the cluster of residues Arg188 in TM2, Gln380 in TM7, and Asn229 in TM3. This cluster is expected to be altered upon VIP binding, because Arg188 has been shown previously to interact with Asp3 of VIP. Several point mutations at positions 188, 229, and 380 were experimentally characterized and were shown to severely affect VIP binding and/or VIP-mediated cAMP production. Double mutants built from reciprocal residue exchanges exhibit strong cooperative or anticooperative effects, thereby indicating the spatial proximity of residues Arg188, Gln380, and Asn229. Because these residues are highly conserved in the GPCR-B family, they can moreover be expected to have a general role in mediating function.

Mn/Fe superoxide dismutase interaction fingerprints and prediction of oligomerization and metal cofactor from sequence

Fe‐ and Mn‐containing superoxide dismutase (sod) enzymes are closely related and similar in both amino acid sequence and structure, but differ in their mode of oligomerization and in their specificity for the Fe or Mn cofactor. The goal of the present work is to identify and analyze the sequence and structure characteristics that ensure the cofactor specificities and the oligomerization modes. For that purpose, 374 sod sequences and 17 sod crystal structures were collected and aligned. These alignments were searched for residues and inter‐residue interactions that are conserved within the whole sod family, or alternatively, that are specific to a given sod subfamily sharing common characteristics. This led us to define key residues and inter‐residue interaction fingerprints in each subfamily. The comparison of these fingerprints allows, on a rational basis, the design of mutants likely to modulate the activity and/or specificity of the target sod, in good agreement with the available experimental results on known mutants. The key residues and interaction fingerprints are furthermore used to predict if a novel sequence corresponds to a sod enzyme, and if so, what type of sod it is. The predictions of this fingerprint method reach much higher scores and present much more discriminative power than the commonly used method that uses pairwise sequence comparisons. Proteins 2008.