Biomedical subjects

Frederic Rousseau

Publications and source records attributed to Frederic Rousseau.

18 recordsLinked to original sources

PubMed2025

FoldX force field revisited, an improved version.

MOTIVATION: The FoldX force field was originally validated with a database of 1000 mutants at a time when there were few high-resolution structures. Here, we have manually curated a database of 5556 mutants affecting protein stability, resulting in 2484 highly confident mutations denominated FoldX stability dataset (FSD), represented in non-redundant X-ray structures with <2.5 Å resolution, not involving duplicates, metals, or prosthetic groups. Using this database, we have created a new version of the FoldX force field by introducing pi stacking, pH dependency for all charged residues, improving aromatic-aromatic interactions, modifying the Ncap contribution and α-helix dipole, recalibrating the side-chain entropy of methionine, adjusting the H-bond parameters, and modifying the solvation contribution of tryptophan and others. RESULTS: These changes have led to significant improvements for the prediction of specific mutants involving the above residues/interactions and a statistically significant increase of FoldX predictions, as well as for the majority of the 20 aa. Removing all training sets data from FSD [Validation FoldX Stability Dataset (VFSD) dataset] resulted in improved predictions from R = 0.693 (RMSE = 1.277 kcal/mol) to R = 0.706 (RMSE = 1.252 kcal/mol) when compared with the previously released version. FoldX achieves 95% accuracy considering an error of ±0.85 kcal/mol in prediction and an area under the curve = 0.78 for the VFSD, predicting the sign of the energy change upon mutation. AVAILABILITY AND IMPLEMENTATION: FoldX versions 4.1 and 5.1 are freely available for academics at https://foldxsuite.crg.eu/.

Databases, Protein↗

PubMed2006

Domain swapping in p13suc1 results in formation of native-like, cytotoxic aggregates.

The field of protein aggregation has been occupied mainly with the study of beta-strand self-association that occurs as a result of misfolding and leads to the formation of toxic protein aggregates and amyloid fibers. However, some of these aggregates retain native-like structural and enzymatic properties suggesting mechanisms other than beta-strand assembly. p13suc1 is a small protein that can exist as a monomer or a domain-swapped dimer. Here, we show that, under native conditions, p13suc1 forms three-dimensional domain-swapped aggregates, and that these aggregates are cytotoxic. Thus, toxicity of protein aggregates is not only associated with beta-rich assemblies and amyloid fibers, involving non-native interactions, but it can be induced by oligomeric misassembly that maintains predominantly native-like interactions.

Animals↗

PubMed2006

PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes.

We have developed a web tool, PupaSuite, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect, specifically oriented to help in the design of large-scale genotyping projects. PupaSuite uses a collection of data on SNPs from heterogeneous sources and a large number of pre-calculated predictions to offer a flexible and intuitive interface for selecting an optimal set of SNPs. It improves the functionality of PupaSNP and PupasView programs and implements new facilities such as the analysis of user's data to derive haplotypes with functional information. A new estimator of putative effect of polymorphisms has been included that uses evolutionary information. Also SNPeffect database predictions have been included. The PupaSuite web interface is accessible through http://pupasuite.bioinfo.cipf.es and through http://www.pupasnp.org.

Algorithms↗

PubMed2006

SNPeffect v2.0: a new step in investigating the molecular phenotypic effects of human non-synonymous SNPs.

UNLABELLED: Single nucleotide polymorphisms (SNPs) constitute the most fundamental type of genetic variation in human populations. About 75 000 of these reported variations cause an amino acid change in the translated protein. An important goal in genomic research is to understand how this variability affects protein function, and whether or not particular SNPs are associated to disease susceptibility. Accordingly, the SNPeffect database uses sequence- and structure-based bioinformatics tools to predict the effect of non-synonymous SNPs on the molecular phenotype of proteins. SNPeffect analyses the effect of SNPs on three categories of functional properties: (1) structural and thermodynamic properties affecting protein dynamics and stability (2) the integrity of functional and binding sites and (3) changes in posttranslational processing and cellular localization of proteins. The search interface of the database can be used to search specifically for polymorphisms that are predicted to cause a change in one of these properties. Now based on the Ensembl human databases, the SNPeffect database has been remodeled to better fit an automatically updatable structure. The current edition holds the molecular phenotype of 74 567 nsSNPs in 23 426 proteins. AVAILABILITY: SNPeffect can be accessed through http://snpeffect.vib.be.

Algorithms↗

PubMed2006

Protein aggregation and amyloidosis: confusion of the kinds?

Recent years have witnessed major advances in our understanding of the structural basis of protein aggregation on several fronts. Firstly, high-resolution structural information that remained elusive for many years was provided by a series of studies of amyloid fibers using NMR, X-ray crystallography and electron microscopy, thereby confirming earlier models based on lower resolution observations. Secondly, studies of the sequence determinants of protein aggregation culminated in the development of computer algorithms that predict aggregation-prone sequences with good accuracy, allowing the design of mutations that reduce aggregation. Thirdly, based on the first results from such predictions and on statistical analysis of naturally occurring aggregating sequences, a picture is emerging in which aggregation-prone sequences are capped by gatekeeper residues that oppose aggregation. In addition to their aggregation-opposing function, it seems that gatekeeper residues are also important in determining chaperone selectivity for strongly aggregating regions. Finally, recent computational and experimental work shows that preventing aggregation does not necessarily mean that amyloid formation is prevented and vice versa. Thus, although aggregation and amyloidosis correlate to a certain extent, they are different processes and should be treated as such.

Algorithms↗

PubMed2005

How evolutionary pressure against protein aggregation shaped chaperone specificity.

As protein aggregation is potentially lethal, control of protein conformation by molecular chaperones is essential for cellular organisms. This is especially important during protein expression and translocation, since proteins are then unfolded and therefore most susceptible to form non-native interactions. Using TANGO, a statistical mechanics algorithm to predict protein aggregation, we here analyse the aggregation propensities of 28 complete proteomes. Our results show that between 10% and 20% of the residues in these proteomes are within aggregating protein segments and that this represents a lower limit for the aggregation tendency of globular proteins. Further, we show that not only evolution strongly pressurizes aggregation downwards by minimizing the amount of strongly aggregating sequences but also by selectively capping strongly aggregating hydrophobic protein sequences with arginine, lysine and proline. These residues are strongly favoured at these positions as they function as gatekeepers that are most efficient at opposing aggregation. Finally, we demonstrate that the substrate specificity of different unrelated chaperone families is geared by these gatekeepers. Chaperones face the difficulty of having to combine substrate affinity for a broad range of hydrophobic sequences and selectivity for those hydrophobic sequences that aggregate most strongly. We show that chaperones achieve these requirements by preferentially binding hydrophobic sequences that are capped by positively charged gatekeeper residues. In other words, targeting evolutionarily selected gatekeepers allows chaperones to prioritize substrate recognition according to aggregation propensity.

Algorithms↗

PubMed2005

Prediction of water and metal binding sites and their affinities by using the Fold-X force field.

The empirical force field Fold-X was developed previously to allow rapid free energy calculations in proteins. Here, we present an enhanced version of the force field allowing prediction of the position of structural water molecules and metal ions, together called single atom ligands. Fold-X picks up 76% of water molecules found to interact with two or more polar atoms of proteins in high-resolution crystal structures and predicts their position to within 0.8 A on average. The prediction of metal ion-binding sites have success rates between 90% and 97% depending on the metal, with an overall standard deviation on the position of binding of 0.3-0.6 A. The following metals were included in the force field: Mg2+, Ca2+, Zn2+, Mn2+, and Cu2+. As a result, the current version of Fold-X can accurately decorate a protein structure with biologically important ions and water molecules. Additionally, the free energy of binding of Ca2+ and Zn2+ (i.e., the natural logarithm of the dissociation constant) and its dependence on ionic strength correlate reasonably well with the experimental data available in the literature, allowing one to discriminate between high- and low-affinity binding sites. Importantly, the accuracy of the energy prediction presented here is sufficient to efficiently discriminate between Mg2+, Ca2+, and Zn2+ binding.

Biophysics↗

PubMed2005

The FoldX web server: an online force field.

FoldX is an empirical force field that was developed for the rapid evaluation of the effect of mutations on the stability, folding and dynamics of proteins and nucleic acids. The core functionality of FoldX, namely the calculation of the free energy of a macromolecule based on its high-resolution 3D structure, is now publicly available through a web server at http://foldx.embl.de/. The current release allows the calculation of the stability of a protein, calculation of the positions of the protons and the prediction of water bridges, prediction of metal binding sites and the analysis of the free energy of complex formation. Alanine scanning, the systematic truncation of side chains to alanine, is also included. In addition, some reporting functions have been added, and it is now possible to print both the atomic interaction networks that constitute the protein, print the structural and energetic details of the interactions per atom or per residue, as well as generate a general quality report of the pdb structure. This core functionality will be further extended as more FoldX applications are developed.

Databases, Protein↗

PubMed2005

Recognizing and defining true Ras binding domains II: in silico prediction based on homology modelling and energy calculations.

Considering the large number of putative Ras effector proteins, it is highly desirable to develop computational methods to be able to identify true Ras binding molecules. Based on a limited sequence homology among members of the Ras association (RA) and Ras binding (RB) sub-domain families of the ubiquitin super-family, we have built structural homology models of Ras proteins in complex with different RA and RB domains, using the FOLD-X software. A critical step in our approach is to use different templates of Ras complexes, in order to account for the structural variation among the RA and RB domains. The homology models are validated by predicting the effect of mutating hot spot residues in the interface, and residues important for the specificity of interaction with different Ras proteins. The FOLD-X calculated energies of the best-modelled complexes are in good agreement with previously published experimental data and with new data reported here. Based on these results, we can establish energy thresholds above, or below which, we can predict with 96% confidence that a RA/RB domain will or will not interact with Ras. This study shows the importance of in depth structural analysis, high quality force-fields and modelling for correct prediction. Our work opens the possibility of genome-wide prediction for this protein family and for others, where there is enough structural information.

Amino Acid Sequence↗

PubMed2005

SNPeffect: a database mapping molecular phenotypic effects of human non-synonymous coding SNPs.

Single nucleotide polymorphisms (SNPs) are an increasingly important tool for genetic and biomedical research. However, the accumulated sequence information on allelic variation is not matched by an understanding of the effect of SNPs on the functional attributes or 'molecular phenotype' of a protein. Towards this aim we developed SNPeffect, an online resource of human non-synonymous coding SNPs (nsSNPs) mapping phenotypic effects of allelic variation in human genes. SNPeffect contains 31 659 nsSNPs from 12 480 human proteins. The current release of SNPeffect incorporates data on protein stability, integrity of functional sites, protein phosphorylation and glycosylation, subcellular localization, protein turnover rates, protein aggregation, amyloidosis and chaperone interaction. The SNP entries are accessible through both a search and browse interface and are linked to most major biological databases. The data can be displayed as detailed descriptions of individual SNPs or as an overview of all SNPs for a given protein. SNPeffect will be regularly updated and can be accessed at http://snpeffect.vib.be/.

Alleles↗

PubMed2005

A systems biology perspective on protein structural dynamics and signal transduction.

The functional dynamics of signal transduction through protein interaction networks are determined both by network topology and by the signal processing properties of component proteins. In order to understand the emergent properties of signal transduction networks in terms of information processing, storage and decision making, we not only need to map the so-called 'interactome' but, perhaps more importantly, we also have to understand how the structural dynamics of constituent proteins shape non-linear responses through cooperativity and allostery. Several in silico methods have been developed to identify networks of cooperative residues in proteins and help infer their mode of action. Applying this type of analysis to important classes of modular signal transduction domains should, in principle, allow the function of these proteins to be abstracted in terms of their information processing characteristics, permitting better comprehension of the systemic properties of biological networks.

Binding Sites↗

PubMed2004

Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins.

We have developed a statistical mechanics algorithm, TANGO, to predict protein aggregation. TANGO is based on the physico-chemical principles of beta-sheet formation, extended by the assumption that the core regions of an aggregate are fully buried. Our algorithm accurately predicts the aggregation of a data set of 179 peptides compiled from the literature as well as of a new set of 71 peptides derived from human disease-related proteins, including prion protein, lysozyme and beta2-microglobulin. TANGO also correctly predicts pathogenic as well as protective mutations of the Alzheimer beta-peptide, human lysozyme and transthyretin, and discriminates between beta-sheet propensity and aggregation. Our results confirm the model of intermolecular beta-sheet formation as a widespread underlying mechanism of protein aggregation. Furthermore, the algorithm opens the door to a fully automated, sequence-based design strategy to improve the aggregation properties of proteins of scientific or industrial interest.

Algorithms↗

PubMed2004

A comparative study of the relationship between protein structure and beta-aggregation in globular and intrinsically disordered proteins.

A growing number of proteins are being identified that are biologically active though intrinsically disordered, in sharp contrast with the classic notion that proteins require a well-defined globular structure in order to be functional. At the same time recent work showed that aggregation and amyloidosis are initiated in amino acid sequences that have specific physico-chemical properties in terms of secondary structure propensities, hydrophobicity and charge. In intrinsically disordered proteins (IDPs) such sequences would be almost exclusively solvent-exposed and therefore cause serious solubility problems. Further, some IDPs such as the human prion protein, synuclein and Tau protein are related to major protein conformational diseases. However, this scenario contrasts with the large number of unstructured proteins identified, especially in higher eukaryotes, and the fact that the solubility of these proteins is often particularly good. We have used the algorithm TANGO to compare the beta aggregation tendency of a set of globular proteins derived from SCOP and a set of 296 experimentally verified, non-redundant IDPs but also with a set of IDPs predicted by the algorithms DisEMBL and GlobPlot. Our analysis shows that the beta-aggregation propensity of all-alpha, all-beta and mixed alpha/beta globular proteins as well as membrane-associated proteins is fairly similar. This illustrates firstly that globular structures possess an appreciable amount of structural frustration and secondly that beta-aggregation is not determined by hydrophobicity and beta-sheet propensity alone. We also show that globular proteins contain almost three times as much aggregation nucleating regions as IDPs and that the formation of highly structured globular proteins comes at the cost of a higher beta-aggregation propensity because both structure and aggregation obey very similar physico-chemical constraints. Finally, we discuss the fact that although IDPs have a much lower aggregation propensity than globular proteins, this does not necessarily mean that they have a lower potential for amyloidosis.

Algorithms↗

PubMed2003

Intermediates control domain swapping during folding of p13suc1.

The 13-kDa protein p13(suc1) has two folded states, a monomer and a structurally similar domain-swapped dimer formed by exchange of a beta-strand. The refolding reaction of p13(suc1) is multiphasic, and in this paper we analyze the kinetics as a function of denaturant and protein concentration and compare the behavior of wild type and a set of mutants previously designed with dimerization propensities that span 9 orders of magnitude. We show that the folding reactions of wild type and all mutants produce the monomer predominantly despite their very different equilibrium behavior. However, the addition of low concentrations of denaturant in the refolding buffer leads to thermodynamic control of the folding reaction with products that correspond to the wild type and mutant equilibrium dimerization propensities. We present evidence that the kinetic control in the absence of urea arises because of the population of the folding intermediates. Intermediates are usually considered to be detrimental to folding because they slow down the reaction; however, our work shows that intermediates buffer the monomeric folding pathway against the effect of mutations that favor the nonfunctional, dimeric state at equilibrium.

Binding Sites↗

PubMed2003

The unfolding story of three-dimensional domain swapping.

Three-dimensional domain swapping is the event by which a monomer exchanges part of its structure with identical monomers to form an oligomer where each subunit has a similar structure to the monomer. The accumulating number of observations of this phenomenon in crystal structures has prompted speculation as to its biological relevance. Domain swapping was originally proposed to be a mechanism for the emergence of oligomeric proteins and as a means for functional regulation, but also to be a potentially harmful process leading to misfolding and aggregation. We highlight experimental studies carried out within the last few years that have led to a much greater understanding of the mechanism of domain swapping and of the residue- and structure-specific features that facilitate the process. We discuss the potential biological implications of domain swapping in light of these findings.

Animals↗

PubMed2002

Surfing on protein folding energy landscapes.

Explore the source record for details and available documents.

Animals↗

PubMed2002

Folding and association of the human cell cycle regulatory proteins ckshs1 and ckshs2.

The two human proteins ckshs1 and ckshs2 are each 79 amino acids in length and consist of a four-stranded beta-sheet capped at one end by two alpha-helices. They are members of the cks family of essential cell cycle regulatory proteins that can adopt two native states, a monomer and a domain-swapped dimer formed by exchange of a C-terminal beta-strand. ckshs1 and ckshs2 both have marginal thermodynamic stability (the free energies of unfolding at 25 degrees C are 3.0 and 2.5 kcal/mol, respectively) and low kinetic stability (the rates of unfolding in water are approximately 1 s(-1)). Refolding of their denatured states to the monomeric forms of the proteins is slowed by transient oligomerization that is likely to occur via domain swapping. The folding behavior of ckshs1 and ckshs2 is markedly different from that of suc1, the cks protein from Schizosaccharomyces pombe, but the domain swapping propensities are similar. The greater thermodynamic and kinetic stability of suc1 and the population of a folding intermediate are most likely a consequence of its larger size (113 residues). The similarity in the domain swapping propensities, despite the contrast in other biophysical properties, may be attributable to the common double-proline motif in the hinge loop that connects the swapped domain to the rest of the protein. The motif was shown previously for suc1 to control the equilibrium between the monomer and the domain-swapped dimer. Finally, according to our model, the kinetic barrier separating the monomer and the domain-swapped dimer arises because the protein must unfold for beta-strand exchange to occur. Consistent with this, interconversion between the two states is much faster in the human proteins than it is for suc1, reflecting the faster unfolding rates of the former.

CDC2-CDC28 Kinases↗

PubMed2002

The structure of the transition state for folding of domain-swapped dimeric p13suc1.

suc1 has two native states, a monomer and a domain-swapped dimer, in which one molecule exchanges a beta strand with an identical partner. Thus, monomer and dimer have the same structures but are topologically distinct. Importantly, residues that exchange are part of the folding nucleus of the monomer and therefore forming these interactions in the dimer would be expected to incur a large entropic cost. Here we present the transition state for folding/unfolding of domain-swapped dimeric suc1 and compare it with its monomeric counterpart. The same overall structure is observed in the two transition states but the phi values are consistently higher for the domain-swapped dimer. Thus, a greater entropic penalty for bringing together the key interactions in the dimer is overcome by mobilizing more contacts in the transition state, thereby achieving a greater enthalpic gain.

Cell Cycle Proteins↗