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Results for “Solvent accessibility”

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PubMed2000

Molecular dynamics simulation of solvated azurin: correlation between surface solvent accessibility and water residence times.

A system containing the globular protein azurin and 3,658 water molecules has been simulated to investigate the influence on water dynamics exerted by a protein surface. Evaluation of water mean residence time for elements having different secondary structure did not show any correlation. Identically, comparison of solvent residence time for atoms having different charge and polarity did not show any clear trend. The main factor influencing water residence time in proximity to a specific site was found to be its solvent accessibility. In detail for atoms belonging to lateral chains and having solvent-accessible surface lower than approximately 16 A(2)a relation is found for which charged and polar atoms are surrounded by water molecules characterized by residence times longer than the non polar ones. The involvement of the low accessible protein atom in an intraprotein hydrogen bond further modulates the length of the water residence time. On the other hand for surfaces having high solvent accessibility, all atoms, independently of their character, are surrounded by water molecules which rapidly exchange with the bulk solvent. Proteins 2000;39:56-67.

Azurin↗

PubMed1980

Solvent accessibility and microenvironment in a bacterial protein proteinase inhibitor SSI (Streptomyces subtilisin inhibitor).

Solvent accessibility (Lee, B. & Richards, F.M. (1971) J. Mol. Biol. 55, 379-400) was calculated for each atom of a bacterial protein proteinase inhibitor SSI (Streptomyces subtilisin inhibitor) based on crystallographic coordinates. Mainly based on this information, various chemical and spectroscopic (UV, Raman, NMR) observations made on the microenvironments of cystines, methionines, tryptophan, histidines, and tyrosines of SSI in solution were evaluated. Crystallographic data and the latter two sets of data were mainly at least qualitatively consistent with each other. These data include (1) the conformation of the two disulfide bridges, (2) the flexibility of the three methionyl side chains, (3) the extent of exposure of the indole ring of a tryptophan, (4) the environment of the two histidines, (5) the environment of the tyrosines, and (6) the hydrogen-deuterium exchangeability of peptide NH's. However, the extents of exposure of tyrosines deduced by solvent perturbation UV difference spectroscopy were significantly larger than those based on solvent accessibility calculations. Possible reasons for this discrepancy are discussed.

Bacterial Proteins↗

PubMed2006

A consensus procedure improving solvent accessibility prediction.

Prediction methods of structural features in 1D represent a useful tool for the understanding of folding, classification, and function of proteins, and, in particular, for 3D structure prediction. Among the structural aspects characterizing a protein, solvent accessibility has received great attention in recent years. The available methods proposed for predicting accessibility have never considered the combination of the results deriving from different methods to construct a consensus prediction able to provide more reliable results. A consensus approach that increases prediction accuracy using three high-performance methods is described. The results of our method for three different protein data sets show that up to 3.0% improvement in prediction accuracy of solvent accessibility may be obtained by a consensus approach. The improvement also extends to the correlation coefficient. Application of our consensus approach to the accessibility prediction using only three prediction methods gives results better than single methods combined for consensus formation. Currently, the scarce availability of predictors with similar parameters defining solvent accessibility hinders the testing of other methods in our consensus procedure.

Amino Acid Sequence↗

PubMed1998

Assessing the impact of secondary structure and solvent accessibility on protein evolution.

Empirically derived models of amino acid replacement are employed to study the association between various physical features of proteins and evolution. The strengths of these associations are statistically evaluated by applying the models of protein evolution to 11 diverse sets of protein sequences. Parametric bootstrap tests indicate that the solvent accessibility status of a site has a particularly strong association with the process of amino acid replacement that it experiences. Significant association between secondary structure environment and the amino acid replacement process is also observed. Careful description of the length distribution of secondary structure elements and of the organization of secondary structure and solvent accessibility along a protein did not always significantly improve the fit of the evolutionary models to the data sets that were analyzed. As indicated by the strength of the association of both solvent accessibility and secondary structure with amino acid replacement, the process of protein evolution-both above and below the species level-will not be well understood until the physical constraints that affect protein evolution are identified and characterized.

Databases, Factual↗

PubMed2005

Predicting protein secondary structure and solvent accessibility with an improved multiple linear regression method.

We have improved the multiple linear regression (MLR) algorithm for protein secondary structure prediction by combining it with the evolutionary information provided by multiple sequence alignment of PSI-BLAST. On the CB513 dataset, the three states average overall per-residue accuracy, Q(3), reached 76.4%, while segment overlap accuracy, SOV99, reached 73.2%, using a rigorous jackknife procedure and the strictest reduction of eight states DSSP definition to three states. This represents an improvement of approximately 5% on overall per-residue accuracy compared with previous work. The relative solvent accessibility prediction also benefited from this combination of methods. The system achieved 77.7% average jackknifed accuracy for two states prediction based on a 25% relative solvent accessibility mode, with a Mathews' correlation coefficient of 0.548. The improved MLR secondary structure and relative solvent accessibility prediction server is available at http://spg.biosci.tsinghua.edu.cn/.

Algorithms↗

PubMed1999

The bottom line for prediction of residue solvent accessibility.

A simple method of predicting residue solvent accessibilities in proteins is described, with the intention that it should be used as a baseline by which more sophisticated approaches to prediction can be judged. Comparison with existing methods of predicting residue burial reveals that their performance is often little better than that of the baseline method. The problem of comparing different prediction methods is shown to be complicated by the proliferation of different schemes for classifying residue burial.

Algorithms↗

PubMed2004

Metropolis simulations of Met-Enkephalin with solvent-accessible area parametrizations.

We investigate the solvent-accessible area method by means of Metropolis simulations of the brain peptide Met-Enkephalin at 300 K. For the energy function ECEPP/2 nine atomic solvation parameter (ASP) sets are studied. The simulations are compared with one another, with simulations with a distance dependent electrostatic permittivity epsilon(r), and with vacuum simulations (epsilon=2). Parallel tempering and the biased Metropolis techniques RM1 are employed and their performance is evaluated. The measured observables include energy and dihedral probability densities, integrated autocorrelation times, and acceptance rates. Two of the ASP sets turn out to be unsuitable for these simulations. For all other systems selected configurations are minimized in the search for global energy minima, which are found for vacuum and the epsilon(r) system, but for none of the ASP models. Other observables show a remarkable dependence on the ASPs. In particular, we find three ASP sets for which the autocorrelations at 300 K are considerably smaller than those for vacuum simulations.

Journal Article↗

PubMed2004

Analysis of protein solvent accessible surfaces by photochemical oxidation and mass spectrometry.

Protein surfaces are important in most biological processes, including protein-protein interactions, enzymatic catalysis, and protein-ligand binding. We report a method in which hydroxyl radicals generated by a rapid-UV irradiation of a 15% hydrogen peroxide solution were utilized to oxidize specific amino acid side chains of two model proteins (lysozyme, beta-lactoglobulin A), according to the residues' chemical reactivities and the solvent accessibility of the reactive carbons and sulfurs in the residue. Oxidized peptides generated by tryptic digestion were identified by electrospray-Fourier transform mass spectrometry. The specific sites of the stable modification were then identified by reverse-phase liquid chromatography coupled to quadropole ion trap tandem mass spectrometry. The solvent accessibility of the residue was shown to directly affect the rate of oxidation by this method (with the exception of methionine), supporting its use as a rapid measure of the solvent accessibility of specific residues, and in some cases, individual atoms.

Amino Acid Sequence↗

PubMed2002

Prediction of protein solvent accessibility using support vector machines.

A Support Vector Machine learning system has been trained to predict protein solvent accessibility from the primary structure. Different kernel functions and sliding window sizes have been explored to find how they affect the prediction performance. Using a cut-off threshold of 15% that splits the dataset evenly (an equal number of exposed and buried residues), this method was able to achieve a prediction accuracy of 70.1% for single sequence input and 73.9% for multiple alignment sequence input, respectively. The prediction of three and more states of solvent accessibility was also studied and compared with other methods. The prediction accuracies are better than, or comparable to, those obtained by other methods such as neural networks, Bayesian classification, multiple linear regression, and information theory. In addition, our results further suggest that this system may be combined with other prediction methods to achieve more reliable results, and that the Support Vector Machine method is a very useful tool for biological sequence analysis.

Bayes Theorem↗

PubMed1975

Solvent accessibility in folded proteins. Studies of hydrogen exchange in trypsin.

In a native protein, the exchange of a peptide amide proton with solvent occurs by one of two pathways, either directly from the folded protein, or via unfolding, exchange taking place from the unfolded protein. From the thermal unfolding rate constants, the contribution of unfolding to the over-all kinetics as a function of solvent and temperature has been determined. Exchange involving unfolding of the protein is characterized by a high activation energy, in the range of 50 to 60 Cal per mol. The activiation energy (Eapp) of the rates of exchange directly from the folded protein is approximately 20 to 25 Cal per mol. Because for the proton transfer step, Eapp approximately equal to 20 Cal per mol, the activation energy for any contributing protein conformational process(es) is approximately equal to 0 to 5 Cal per mol. Most, if not all, of the peptide amide protons in a folded protein can exchange directly with solvent without the protein unfolding. The number of "slowly" exchanging protons at a given condition of pH and temperature is not related to a discrete structural unit, but rather to the distribution of observed rates within the broader distribution of actual rates. The large attenuation of hydrogen exchange rates in folded proteins, resulting in a distribution of first order rates over 6 orders of magnitude, is primarily due to the effects of restricted solvent accessibility of labile protons in the three-dimensional structure. Any protein conformational process, such as protein fluctuations, invoked to explain the solvent accessibility must be of low activation energy and attenuated by ethanol and other co-solvents (Woodward, C. K., Ellis, L. M., and Rosenberg, A. (1974) J. Biol. Chem. 250, 440-444).

Binding Sites↗

PubMed1995

SMART: a solvent-accessible triangulated surface generator for molecular graphics and boundary element applications.

An algorithm is presented for generating a representation of the solvent-accessible molecular surface as a smooth triangulated manifold. The algorithm, called SMART (SMooth moleculAR surface Triangulator), divides the contact and reentrant portions of the solvent-accessible molecular surface into curvilinear three-sided elements. In contrast to the author's earlier implementation of this general approach [Zauhar, R.J. and Morgan, R.S., J. Comput. Chem., 11 (1990) 603], the SMART algorithm defines elements directly on the appropriate geometric surface types (rather than using interpolation over cubic elements), and has special features to handle highly distorted regions which often appear in deep crevices and internal cavities. While the method is designed for use with boundary element techniques in continuum electrostatics, it can also be applied to the accurate computation of molecular surface areas and volumes, and the generation of shaded surfaces for display with interactive computer graphics.

Algorithms↗

PubMed2003

Improvement in prediction of solvent accessibility by probability profiles.

The capability of predicting folding and conformation of a protein from its primary structure is probably one of the main goals of modern biology. An accurate prediction of solvent accessibility is an intermediate step along this way. A new method for predicting solvent accessibility from single sequence and multiple alignment data is described. The method is based on probability profiles calculated on an amino acid sequence centred on the residue whose accessibility has to be predicted. A profile is constructed for each exposure category considered so as to calculate the probability of a sequence being generated by the different profiles. Prediction accuracy was tested on a variety of protein sets with two- and three-state models. Different thresholds were used according to those adopted by the authors proposing the data sets. The prediction accuracy is significantly improved over existing methods.

Algorithms↗

PubMed1998

Solvent accessibility analysis on the mutants of Hsc70 ATPase fragment.

Molecular chaperones are the cellular proteins which mediate the correct folding of other polypeptides. The concept of 'solvent accessibility' is one of the most powerful tools to understand the structure and stability of protein molecules. The hydrophobic variation of amino acid residues due to point mutations at many active sites of chaperone protein Hsc70 using solvent accessibility analysis is carried out. The numerical indices for several properties of amino acid residues, such as, reduction in accessibility, preference of amino acid residues in interior and surface parts, transfer free energy and the preference of amino acid residues to change their positions (buried/exposed) due to amino acid substitutions for Hsc70 and its mutants were set up. The accessibility of amino acid residues varies much between native and mutant proteins whereas there is no major changes on their conformations. The conformational stability for Hsc70 and its mutants were established and the computed hydrophobic free energy change is around 10 kcal/mol due to single amino acid substitution.

HSP70 Heat-Shock Proteins↗

PubMed2002

NETASA: neural network based prediction of solvent accessibility.

MOTIVATION: Prediction of the tertiary structure of a protein from its amino acid sequence is one of the most important problems in molecular biology. The successful prediction of solvent accessibility will be very helpful to achieve this goal. In the present work, we have implemented a server, NETASA for predicting solvent accessibility of amino acids using our newly optimized neural network algorithm. Several new features in the neural network architecture and training method have been introduced, and the network learns faster to provide accuracy values, which are comparable or better than other methods of ASA prediction. RESULTS: Prediction in two and three state classification systems with several thresholds are provided. Our prediction method achieved the accuracy level upto 90% for training and 88% for test data sets. Three state prediction results provide a maximum 65% accuracy for training and 63% for the test data. Applicability of neural networks for ASA prediction has been confirmed with a larger data set and wider range of state thresholds. Salient differences between a linear and exponential network for ASA prediction have been analysed. AVAILABILITY: Online predictions are freely available at: http://www.netasa.org. Linux ix86 binaries of the program written for this work may be obtained by email from the corresponding author.

Algorithms↗

PubMed1999

PredAcc: prediction of solvent accessibility.

UNLABELLED: PredAcc is a tool for predicting the solvent accessibility of protein residues from the sequence at different relative accessibility levels (0-55%). The prediction rate varies between 70. 7% (for 25% relative accessibility) and 85.7% (for 0% relative accessibility). Amino acids are predicted in four categories: almost certainly hidden and almost certainly exposed with a given a posteriori prediction error, probably hidden and probably exposed otherwise. AVAILABILITY: http://condor.urbb.jussieu.fr/PredAccCfg.html CONTACT: tuffery@urbb.jussieu.fr

Amino Acids↗

PubMed2005

Real value prediction of solvent accessibility in proteins using multiple sequence alignment and secondary structure.

The present study is an attempt to develop a neural network-based method for predicting the real value of solvent accessibility from the sequence using evolutionary information in the form of multiple sequence alignment. In this method, two feed-forward networks with a single hidden layer have been trained with standard back-propagation as a learning algorithm. The Pearson's correlation coefficient increases from 0.53 to 0.63, and mean absolute error decreases from 18.2 to 16% when multiple-sequence alignment obtained from PSI-BLAST is used as input instead of a single sequence. The performance of the method further improves from a correlation coefficient of 0.63 to 0.67 when secondary structure information predicted by PSIPRED is incorporated in the prediction. The final network yields a mean absolute error value of 15.2% between the experimental and predicted values, when tested on two different nonhomologous and nonredundant datasets of varying sizes. The method consists of two steps: (1) in the first step, a sequence-to-structure network is trained with the multiple alignment profiles in the form of PSI-BLAST-generated position-specific scoring matrices, and (2) in the second step, the output obtained from the first network and PSIPRED-predicted secondary structure information is used as an input to the second structure-to-structure network. Based on the present study, a server SARpred (http://www.imtech.res.in/raghava/sarpred/) has been developed that predicts the real value of solvent accessibility of residues for a given protein sequence. We have also evaluated the performance of SARpred on 47 proteins used in CASP6 and achieved a correlation coefficient of 0.68 and a MAE of 15.9% between predicted and observed values.

Amino Acids↗

PubMed2005

A new analytical method for computing solvent-accessible surface area of macromolecules and its gradients.

In the calculation of thermodynamic properties and three-dimensional structures of macromolecules, such as proteins, it is important to have an efficient algorithm for computing the solvent-accessible surface area of macromolecules. Here, we propose a new analytical method for this purpose. In the proposed algorithm we consider the transformation that maps the spherical circles formed by intersection of the atomic surfaces in three-dimensional space onto the circles on a two-dimensional plane, and the problem of computing the solvent-accessible surface area is reduced to the problem of computing the corresponding curve integrals on the plane. This allows to consider only the integrals along the circular trajectories on the plane. The algorithm is suitable for parallelization. Testings on many proteins as well as the comparison to the other analogous algorithms have shown that our method is accurate and efficient.

Algorithms↗

PubMed1997

Predicting differential antigen-antibody contact regions based on solvent accessibility.

A novel computational approach was examined for predicting epitopes from primary structures of the seven immunologically distinct botulinum neurotoxins (BoNT/A-G) and tetanus toxin (TeTX). An artificial neural network [Rost and Sander (1994), Proteins 20, 216] was used to estimate residue solvent accessibilities in multiple aligned sequences. A similar network trained to predict secondary structures was also used to examine this protein family, whose tertiary fold is presently unknown. The algorithm was validated by showing that it was 80% accurate in determining the secondary structure of avian egg-white lysozyme and that it correctly identified highly solvent-exposed residues that correspond to the major contact regions of lysozyme-antibody cocrystals. When sequences of the heavy (H) chains of TeTX and BoNT/A-G were analyzed, this algorithm predicted that the most highly exposed regions were clustered at the sequentially nonconserved N- and C-termini [Lebeda and Olson (1994), Proteins 20, 293]. The secondary structures and the remaining highly solvent-accessible regions were, in contrast, predicted to be conserved. In experiments reported by others, H-chain fragments that induced immunological protection against BoNT/A overlap with these predicted most highly exposed regions. It is also known that the C-terminal halves of the TeTX and BoNT/A H-chains interfere with holotoxin binding to ectoacceptors on nerve endings. Thus, the present results provide a theoretical framework for predicting the sites that could assist in the development of genetically engineered vaccines and that could interact with neurally located toxin ectoacceptors. Finally, because the most highly solvent-exposed regions were not well conserved, it is hypothesized that nonconserved, potential contact sites partially account for the existence of different dominant binding regions for type-specific neutralizing antibodies.

Algorithms↗