RESUMEN
BACKGROUND: The house dust mite (HDM) allergen Der p 13 could be a lipid-binding protein able to activate key innate signaling pathways in the initiation of the allergic response. We investigated the IgE reactivity of recombinant Der p 13 (rDer p 13), its lipid-binding activities, and its capacity to stimulate airway epithelium cells. METHODS: Purified rDer p 13 was characterized by mass spectrometry, circular dichroism, fluorescence-based lipid-binding assays, and in silico structural prediction. IgE-binding activity and allergenic potential of Der p 13 were examined by ELISA, basophil degranulation assays, and in vitro airway epithelial cell activation assays. RESULTS: Protein modeling and biophysical analysis indicated that Der p 13 adopts a ß-barrel structure with a predominately apolar pocket representing a potential binding site for hydrophobic ligands. Fluorescent lipid-binding assays confirmed that the protein is highly selective for ligands and that it binds a fatty acid with a dissociation constant typical of lipid transporter proteins. The low IgE-binding frequency (7%, n = 224) in Thai HDM-allergic patients as well as the limited propensity to activate basophil degranulation classifies Der p 13 as a minor HDM allergen. Nevertheless, the protein with its presumptively associated lipid(s) triggered the production of IL-8 and GM-CSF in respiratory epithelial cells through a TLR2-, MyD88-, NF-kB-, and MAPK-dependent signaling pathway. CONCLUSIONS: Although a minor allergen, Der p 13 may, through its lipid-binding capacity, play a role in the initiation of the HDM-allergic response through TLR2 activation.
Asunto(s)
Alérgenos/inmunología , Antígenos Dermatofagoides/inmunología , Antígenos Dermatofagoides/metabolismo , Proteínas de Unión a Ácidos Grasos/inmunología , Proteínas de Unión a Ácidos Grasos/metabolismo , Inmunidad Innata , Receptor Toll-Like 2/metabolismo , Animales , Antígenos Dermatofagoides/química , Basófilos/inmunología , Basófilos/metabolismo , Proteínas Portadoras/metabolismo , Degranulación de la Célula/inmunología , Dermatophagoides pteronyssinus/inmunología , Proteínas de Unión a Ácidos Grasos/química , Humanos , Inmunoglobulina E/inmunología , Metabolismo de los Lípidos , Modelos Moleculares , Unión Proteica , Conformación Proteica , Mucosa Respiratoria/inmunología , Mucosa Respiratoria/metabolismo , Receptor Toll-Like 2/agonistasRESUMEN
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.
Asunto(s)
Bases de Datos de Proteínas , Conformación Proteica , Proteínas/química , Algoritmos , Biología Computacional , Estadística como Asunto , TermodinámicaRESUMEN
Energy functions are crucial ingredients of protein tertiary structure prediction methods. Assessing the quality of energy functions is therefore of prime importance. It requires the elaboration of a standard evaluation scheme, whose key elements are: i). sets that contain the native and several non-native structures of proteins (decoys) in order to test whether the energy functions display the expected quality features and ii). measures to evaluate the reliability of energy functions. We present here a survey of the recent advances in these two related fields. In a first part, we analyze and review the large number of decoy sets that are available on the web, and we summarize the characteristics of a challenging decoy set. We then discuss how to define the quality of energy functions and review the measures related to it.
Asunto(s)
Modelos Teóricos , Estructura Terciaria de Proteína , Termodinámica , Secuencia de Aminoácidos , Biología Computacional , Bases de Datos Factuales , Modelos Moleculares , Proteínas/química , Proteínas/genética , Proteínas/metabolismoRESUMEN
PoPMuSiC is an efficient tool for rational computer-aided design of single-site mutations in proteins and peptides. Two types of queries can be submitted. The first option allows to estimate the changes in folding free energy for specific point mutations given by the user. In the second option, all possible point mutations in a given protein or protein region are performed and the most stabilizing or destabilizing mutations, or the neutral mutations with respect to thermodynamic stability, are selected. For each sequence position or secondary structure the deviation from the most stable sequence is moreover evaluated, which helps to identify the most suitable sites for the introduction of mutations.
Asunto(s)
Mutación Puntual/genética , Ingeniería de Proteínas/métodos , Proteínas/química , Proteínas/genética , Análisis de Secuencia de Proteína/métodos , Diseño Asistido por Computadora , Bases de Datos de Proteínas , Correo Electrónico , Almacenamiento y Recuperación de la Información/métodos , Conformación Proteica , Pliegue de Proteína , Programas Informáticos , Interfaz Usuario-ComputadorRESUMEN
BACKGROUND: The 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. RESULTS: We 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 code's 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. CONCLUSIONS: These results lead us to discuss the role of amino-acid frequencies and other parameters in the genetic code's evolution, in an attempt to propose a tentative picture of primitive life.
Asunto(s)
Aminoácidos/genética , ADN/genética , Código Genético/genética , Proteínas/genética , Sustitución de Aminoácidos , Secuencia de Bases/genética , Metabolismo Energético , Biosíntesis de Proteínas , Conformación Proteica , Pliegue de Proteína , Proteínas/químicaRESUMEN
The location of protein subunits that form early during folding, constituted of consecutive secondary structure elements with some intrinsic stability and favorable tertiary interactions, is predicted using a combination of threading algorithms and local structure prediction methods. Two folding units are selected among the candidates identified in a database of known protein structures: the fragment 15-55 of 434 cro, an all-alpha protein, and the fragment 1-35 of ubiquitin, an alpha/beta protein. These units are further analyzed by means of Monte Carlo simulated annealing using several database-derived potentials describing different types of interactions. Our results suggest that the local interactions along the chain dominate in the first folding steps of both fragments, and that the formation of some of the secondary structures necessarily occurs before structure compaction. These findings led us to define a prediction protocol, which is efficient to improve the accuracy of the predicted structures. It involves a first simulation with a local interaction potential only, whose final conformation is used as a starting structure of a second simulation that uses a combination of local interaction and distance potentials. The root mean square deviations between the coordinates of predicted and native structures are as low as 2-4 A in most trials. The possibility of extending this protocol to the prediction of full proteins is discussed. Proteins 2001;42:164-176.
Asunto(s)
Simulación por Computador , Pliegue de Proteína , Proteínas Represoras/química , Ubiquitinas/química , Secuencia de Aminoácidos , Bases de Datos Factuales , Modelos Moleculares , Datos de Secuencia Molecular , Método de Montecarlo , Fragmentos de Péptidos/química , Conformación Proteica , Proteínas ViralesRESUMEN
A novel tool for computer-aided design of single-site mutations in proteins and peptides is presented. It proceeds by performing in silico all possible point mutations in a given protein or protein region and estimating the stability changes with linear combinations of database-derived potentials, whose coefficients depend on the solvent accessibility of the mutated residues. Upon completion, it yields a list of the most stabilizing, destabilizing or neutral mutations. This tool is applied to mouse, hamster and human prion proteins to identify the point mutations that are the most likely to stabilize their cellular form. The selected mutations are essentially located in the second helix, which presents an intrinsic preference to form beta-structures, with the best mutations being T183-->F, T192-->A and Q186-->A. The T183 mutation is predicted to be by far the most stabilizing one, but should be considered with care as it blocks the glycosylation of N181 and this blockade is known to favor the cellular to scrapie conversion. Furthermore, following the hypothesis that the first helix might induce the formation of hydrophilic beta-aggregates, several mutations that are neutral with respect to the structure's stability but improve the helix hydrophobicity are selected, among which is E146-->L. These mutations are intended as good candidates to undergo experimental tests.
Asunto(s)
Algoritmos , Estabilidad de Enzimas , Mutación/fisiología , Fragmentos de Péptidos/genética , Proteínas PrPSc/genética , Pliegue de Proteína , Secuencia de Aminoácidos , Animales , Cricetinae , Humanos , Ratones , Datos de Secuencia Molecular , Fragmentos de Péptidos/química , Proteínas PrPSc/química , Estructura Secundaria de Proteína , TermodinámicaRESUMEN
The possibility of defining effective potentials from known protein structures, which are sufficiently accurate to be used for protein-structure-prediction purposes, is investigated. Three types of distance potentials and three types of backbone torsion potentials are defined, based on propensities of amino acid pairs to be separated by a given spatial distance or to be associated to a backbone torsion angle domain. Their differences reside in the way the physical correlations between the amino acids and the conformational states are extracted from the bulk interactions due to the presence of many residues in a protein. For the distance potentials, a physical meaning can be associated to the different definitions, given that some of the potentials favor hydrophobic interactions and others favor interactions between oppositely charged residues. The performance of the different torsion and distance potentials in structure prediction procedures, in particular native-fold recognition and evaluation of protein stability changes upon point mutations, is analyzed. It appears to differ according to the specific proteins and protein environments. In particular, one of the distance potentials performs better than the others for membrane proteins and in protein regions involving charged residues, but less well in other protein regions. Furthermore, the dependence of the potentials on the characteristics of the proteins from which they are derived is analyzed. It is shown that the dependence of the potentials on the length, amino acid composition and secondary-structure content of the proteins from the dataset is either very limited or rather strong, according to the type of potential. The results obtained suggest that the main problem limiting the performance of database-derived potentials is their lack of universality: each potential describes with satisfactory accuracy only the interactions present in certain protein environments.
Asunto(s)
Proteínas/química , Algoritmos , Aminoácidos/química , Bases de Datos como Asunto , Mutación/genética , Conformación Proteica , Pliegue de ProteínaRESUMEN
For 238 mutations of residues totally or partially buried in the protein core, we estimate the folding free energy changes upon mutation using database-derived potentials and correlate them with the experimentally measured ones. Several potentials are tested, representing different kinds of interactions. Local interactions along the chain are described by torsion potentials, based on propensities of amino acids to be associated with backbone torsion angle domains. Non-local interactions along the sequence are represented by distance potentials, derived from propensities of amino acid pairs or triplets to be at a given spatial distance. We find that for the set of totally buried residues, the best performing potential is a combination of a distance potential and a torsion potential weighted by a factor of 0.4; it yields a correlation coefficient between computed and measured changes in folding free energy of 0.80. For mutations of partially buried residues, the best potential is a combination of a torsion potential and a distance potential weighted by a factor of 0.7, and for the previously analysed mutations of solvent accessible residues, it is a torsion potential taken individually; the respective correlation coefficients reach 0.82 and 0.87. These results show that distance potentials, dominated by hydrophobic interactions, represent best the main interactions stabilizing the protein core, whereas torsion potentials, describing local interactions along the chain, represent best the interactions at the protein surface. The prediction accuracy reached by the distance potentials is, however, lower than that of the torsion potentials. A possible reason for this is that distance potentials would not describe correctly the effect on protein stability due to cavity formation upon mutating a large into a small amino acid. Last but not least, our results indicate that although local interactions, responsible for secondary structure formation, do not dominate in the protein core, they are not negligible for all that. They have a significant weight in the delicate balance between all the interactions that ensure protein stability.
Asunto(s)
Mutación/fisiología , Pliegue de Proteína , Proteínas/química , Animales , Estabilidad de Enzimas , Humanos , Estructura Secundaria de Proteína , Proteínas/genética , Solventes , TermodinámicaRESUMEN
The stability changes in peptides and proteins caused by the substitution of a single amino acid, which can be measured experimentally by the change in folding free energy, are evaluated here using effective potentials derived from known protein structures. The analysis is focused on mutations of residues that are accessible to the solvent. These represent in total 106 mutations, introduced at different sites in barnase, bacteriophage T4 lysozyme and chymotrypsin inhibitor 2, and in a synthetic helical peptide. Assuming that the mutations do not modify the backbone structure, the changes in folding free energies are computed using various types of database-derived potentials and are compared with the measured ones. Distance-dependent residue-residue potentials are found to be inadequate for estimating the stability changes caused by these mutations, as they are dominated by hydrophobic interactions, which do not play an essential role at the protein surface. On the contrary, the potentials based on backbone torsion angle propensities yield quite good results. Indeed, for a subset of 96 out of the 106 mutations, the computed and measured changes in folding free energy correlate with a linear correlation coefficient of 0.87. Moreover, the ten mutations that are excluded from the correlation either seem to cause modifications of the backbone structure or to involve strong hydrophobic interactions, which are atypical for solvent-accessible residues. We find furthermore that raising the ionic strength of the solvent used for measuring the changes in folding free energies improves the correlation, as it tends to mask the electrostatic interactions. When adding to these 106 mutations 44 mutations performed in staphylococcal nuclease and chemotactic protein, which were first discarded because some of them were suspected to affect the backbone conformation or the denatured state, the correlation between measured and computed folding free energy changes remains quite good: the correlation coefficient is 0.86 for 135 out of the 150 mutations. The success of the backbone torsion potentials in predicting stability changes indicates that the approximations made for deriving these potentials are adequate. It suggests moreover that the local interactions along the chain dominate at the protein surface.