Sequence and structure conservation in a protein core

In order to study structural aspects of sequence conservation in families of homologous proteins, we have analyzed structurally aligned sequences of 585 proteins grouped into 128 homologous families. The conservation of a residue in a family is defined as the average residue similarity in a given position of aligned sequences. The residue similarities were expressed in the form of log-odd substitution tables that take into account the environments of amino acids in three-dimensional structures. The protein core is defined as those residues that have less then 7% solvent accessibility. The density of a protein core is described in terms of atom packing, which is investigated as a criterion for residue substitution and conservation. Although there is no significant correlation between sequence conservation and average atom packing around nonpolar residues such as leucine, valine and isoleucine, a significant correlation is observed for polar residues in the protein core. This may be explained by the hydrogen bonds in which polar residues are involved; the better their protection from water access the more stable should be the structure in that position. Proteins 33:358–366, 1998. © 1998 Wiley-Liss, Inc.     

Amyloidogenic sequences in native protein structures

Numerous short peptides have been shown to form β‐sheet amyloid aggregates in vitro. Proteins that contain such sequences are likely to be problematic for a cell, due to their potential to aggregate into toxic structures. We investigated the structures of 30 proteins containing 45 sequences known to form amyloid, to see how the proteins cope with the presence of these potentially toxic sequences, studying secondary structure, hydrogen‐bonding, solvent accessible surface area and hydrophobicity. We identified two mechanisms by which proteins avoid aggregation: Firstly, amyloidogenic sequences are often found within helices, despite their inherent preference to form β structure. Helices may offer a selective advantage, since in order to form amyloid the sequence will presumably have to first unfold and then refold into a β structure. Secondly, amyloidogenic sequences that are found in β structure are usually buried within the protein. Surface exposed amyloidogenic sequences are not tolerated in strands, presumably because they lead to protein aggregation via assembly of the amyloidogenic regions. The use of α‐helices, where amyloidogenic sequences are forced into helix, despite their intrinsic preference for β structure, is thus a widespread mechanism to avoid protein aggregation.     

Reconstructing the protein–water interface

Using molecular dynamics simulations of fully hydrated proteins and analysis of crystal structures contained in the Protein Data Bank, we develop a transferable set of perpendicular radial distribution functions for water molecules around globular proteins. These universal functions may be used to reconstruct the unique three-dimensional solvent density distribution around every individual protein with a modest error. We discuss potential applications of this solvent treatment in protein x-ray crystallographic refinements and in theoretical modeling. We also present a fast, grid-based algorithm for construction of the perpendicular solvent density distributions. © 1998 John Wiley & Sons, Inc. Biopoly 45: 469–478, 1998     

Relative solvent accessible surface area predicts protein conformational changes upon binding

Protein interactions are often accompanied by significant changes in conformation. We have analyzed the relationships between protein structures and the conformational changes they undergo upon binding. Based upon this, we introduce a simple measure, the relative solvent accessible surface area, which can be used to predict the magnitude of binding-induced conformational changes from the structures of either monomeric proteins or bound subunits. Applying this to a large set of protein complexes suggests that large conformational changes upon binding are common. In addition, we observe considerable enrichment of intrinsically disordered sequences in proteins predicted to undergo large conformational changes. Finally, we demonstrate that the relative solvent accessible surface area of monomeric proteins can be used as a simple proxy for protein flexibility. This reveals a powerful connection between the flexibility of unbound proteins and their binding-induced conformational changes, consistent with the conformational selection model of molecular recognition.     

The effect of deuterium oxide on the stability of the collagen model peptides H‐(Pro‐Pro‐Gly)10‐OH,H‐(Gly‐Pro‐4(R)Hyp)9‐OH,and Type I collagen

The collagen triple helix has a larger accessible surface area per molecular mass than globular proteins, and therefore potentially more water interaction sites. The effect of deuterium oxide on the stability of collagen model peptides and Type I collagen molecules was analyzed by circular dichroism and differential scanning calorimetry. The transition temperatures (T_m) of the protonated peptide (Pro‐Pro‐Gly)₁₀ were 25.4 and 28.7°C in H₂O and D₂O, respectively. The increase of the T_m of (Pro‐Pro‐Gly)₁₀ measured calorimetrically at 1.0°C min^?1 in a low pH solution from the protonated to the deuterated solvent was 5.1°C. The increases of the T_m for (Gly‐Pro‐4(R)Hyp)₉ and pepsin‐extracted Type I collagen were measured as 4.2 and 2.2°C, respectively. These results indicated that the increase in the T_m in the presence of D₂O is comparable to that of globular proteins, and much less than reported previously for collagen model peptides [Gough and Bhatnagar, J Biomol Struct Dyn 1999, 17, 481–491]. These experimental results suggest that the interaction of water molecules with collagen is similar to the interaction of water with globular proteins, when the ratio of collagen to water is very small and collagen is monomerically dispersed in the solvent. © 2009 Wiley Periodicals, Inc. Biopolymers 93: 93–101, 2010. This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com     

Quantification of protein surfaces,volumes and atom-atom contacts using a constrained Voronoi procedure

MOTIVATION: Geometric representations of proteins and ligands, including atom volumes, atom-atom contacts and solvent accessible surfaces, can be used to characterize interactions between and within proteins, ligands and solvent. Voronoi algorithms permit quantification of these properties by dividing structures into cells with a one-to-one correspondence with constituent atoms. As there is no generally accepted measure of atom-atom contacts, a continuous analytical representation of inter-atomic contacts will be useful. Improved geometric algorithms will also be helpful in increasing the speed and accuracy of iterative modeling algorithms. RESULTS: We present computational methods based on the Voronoi procedure that provide rapid and exact solutions to solvent accessible surfaces, volumes, and atom contacts within macromolecules. Furthermore, we define a measure of atom-atom contact that is consistent with the calculation of solvent accessible surfaces, allowing the integration of solvent accessibility and inter-atomic contacts into a continuous measure. The speed and accuracy of the algorithm is compared to existing methods for calculating solvent accessible surfaces and volumes. The presented algorithm has a reduced execution time and greater accuracy compared to numerical and approximate analytical surface calculation algorithms, and a reduced execution time and similar accuracy to existing Voronoi procedures for calculating atomic surfaces and volumes.     

Residue conservation information for generating near-native structures in protein-protein docking

MOTIVATION: Protein-protein docking algorithms typically generate large numbers of possible complex structures with only a few of them resembling the native structure. Recently (Duan et al., Protein Sci, 14:316-218, 2005), it was observed that the surface density of conserved residue positions is high at the interface regions of interacting protein surfaces, except for antibody-antigen complexes, where a lesser number of conserved positions than average is observed at the interface regions. Using this observation, we identified putative interacting regions on the surface of interacting partners and significantly improved docking results by assigning top ranks to near-native complex structures. In this paper, we combine the residue conservation information with a widely used shape complementarity algorithm to generate candidate complex structures with a higher percentage of near-native structures (hits). What is new in this work is that the conservation information is used early in the generation stage and not only in the ranking stage of the docking algorithm. This results in a significantly larger number of generated hits and an improved predictive ability in identifying the native structure of protein-protein complexes. RESULTS: We report on results from 48 well-characterized protein complexes, which have enough residue conservation information from the same 59 benchmark complexes used in our previous work. We compute conservation indices of residue positions on the surfaces of interacting proteins using available homologous sequences from UNIPROT and calculate the solvent accessible surface area. We combine this information with shape-complementarity scores to generate candidate protein-protein complex structures. When compared with pure shape-complementarity algorithms, performed by FTDock, our method results in significantly more hits, with the improvement being over 100% in many instances. We demonstrate that residue conservation information is useful not only in refinement and scoring of docking solutions, but also helpful in enrichment of near-native-structures during the generation of candidate geometries of complex structures.     

Analysis of accessible surface of residues in proteins

We analyzed the total, hydrophobic, and hydrophilic accessible surfaces (ASAs) of residues from a nonredundant bank of 587 3D structure proteins. In an extended fold, residues are classified into three families with respect to their hydrophobicity balance. As expected, residues lose part of their solvent-accessible surface with folding but the three groups remain. The decrease of accessibility is more pronounced for hydrophobic than hydrophilic residues. Amazingly, Lysine is the residue with the largest hydrophobic accessible surface in folded structures. Our analysis points out a clear difference between the mean (other studies) and median (this study) ASA values of hydrophobic residues, which should be taken into consideration for future investigations on a protein-accessible surface, in order to improve predictions requiring ASA values. The different secondary structures correspond to different accessibility of residues. Random coils, turns, and beta-structures (outside beta-sheets) are the most accessible folds, with an average of 30% accessibility. The helical residues are about 20% accessible, and the difference between the hydrophobic and the hydrophilic residues illustrates the amphipathy of many helices. Residues from beta-sheets are the most inaccessible to solvent (10% accessible). Hence, beta-sheets are the most appropriate structures to shield the hydrophobic parts of residues from water. We also show that there is an equal balance between the hydrophobic and the hydrophilic accessible surfaces of the 3D protein surfaces irrespective of the protein size. This results in a patchwork surface of hydrophobic and hydrophilic areas, which could be important for protein interactions and/or activity.     

Real-SPINE: an integrated system of neural networks for real-value prediction of protein structural properties

Proteins can move freely in three-dimensional space. As a result, their structural properties, such as solvent accessible surface area, backbone dihedral angles, and atomic distances, are continuous variables. However, these properties are often arbitrarily divided into a few classes to facilitate prediction by statistical learning techniques. In this work, we establish an integrated system of neural networks (called Real-SPINE) for real-value prediction and apply the method to predict residue-solvent accessibility and backbone psi dihedral angles of proteins based on information derived from sequences only. Real-SPINE is trained with a large data set of 2640 protein chains, sequence profiles generated from multiple sequence alignment, representative amino-acid properties, a slow learning rate, overfitting protection, and predicted secondary structures. The method optimizes more than 200,000 weights and yields a 10-fold cross-validated Pearson's correlation coefficient (PCC) of 0.74 between predicted and actual solvent accessible surface areas and 0.62 between predicted and actual psi angles. In particular, 90% of 2640 proteins have a PCC value greater than 0.6 between predicted and actual solvent-accessible surface areas. The results of Real-SPINE can be compared with the best reported correlation coefficients of 0.64-0.67 for solvent-accessible surface areas and 0.47 for psi angles. The real-SPINE server, executable programs, and datasets are freely available on http://sparks.informatics.iupui.edu.     

Folding of Globular Proteins by Energy Minimization and Monte Carlo Simulations with Hydrophobic Surface Area Potentials

We describe an efficient method to calculate analytically the solvent accessible surface areas and their gradients in proteins for empirical force field calculations on serial and parallel computers. In an application to the small three helix bundle protein Er-10, energy minimizations and Monte Carlo simulations were performed with the empirical ECEPP/2 force field, which was extended by a protein solvent interaction term. We show that the NMR structure is stable when refined with the force field including the protein solvent interaction term, but large structural deviations are observed in energy minimization in vacuo. When we started from random structures with preformed helices and maintained the helical segments by dihedral angle constraints, the final structures with the lowest energies resembled the native form. The root-mean-square deviations for the backbone atoms of the three helices compared to the experimentally determined structure was 3 Å to 4 Å.     

IMPALA: A simple restraint field to simulate the biological membrane in molecular structure studies

The lipid bilayer is crucial for the folding of integral membrane proteins. This article presents an empirical method to account for water–lipid interfaces in the insertion of molecules interacting with bilayers. The interactions between the molecule and the bilayer are described by restraint functions designed to mimic the membrane effect. These functions are calculated for each atom and are proportional to the accessible surface of the latter. The membrane is described as a continuous medium whose properties are varying along the axis perpendicular to the bilayer plane. The insertion is analyzed by a Monte Carlo procedure applied to the restraint functions. The method was successfully applied to small α peptides of known configurations. It provides insights of the behaviors of the peptide dynamics that cannot be obtained with statistical approaches (e.g., hydropathy analysis). Proteins 30:357–371, 1998. © 1998 Wiley-Liss, Inc.     

Populations of hydrophobic amino acids within protein globular domains: Identification of conserved “topohydrophobic” positions

The 3D structural comparison of families of divergent homologous domains revealed two main populations of hydrophobic amino acids, one with a low and the other with a significantly higher mean solvent accessibility, allowing two regions of the core of protein globular domains to be distinguished. The side chains of hydrophobic amino acids in topologically conserved positions (positions in the structural alignment where only hydrophobic amino acids are found), which we call topohydrophobic positions, are considerably less dispersed than those of the other amino acids (hydrophobic or not). Mean distances between gravity centers of amino acids in topohydrophobic positions are significantly shorter than those for non-topohydrophobic positions and show that the corresponding amino acids are almost all in direct contact in the inner core of globular domains. This study also showed that the small number of topohydrophobic positions is a characteristic of the structural differences between proteins of a family. This criterion is independent of the sequence identity between the sequences and of the root-mean-square distance between their corresponding structures. Using sensitive sequence alignment processes it will be possible, for many protein families, to identify topohydrophobic positions from sequences only. Proteins 33:329–342, 1998. © 1998 Wiley-Liss, Inc.     

Structure prediction of a complex between the chromosomal protein HMG-D and DNA

Non-histone chromosomal proteins are an important part of nuclear structure and function due to their ability to interact with DNA to form and modulate chromatin structure and regulate gene expression. However, the understanding of the function of chromosomal proteins at the molecular level has been hampered by the lack of structures of chromosomal protein–DNA complexes. We have carried out a molecular dynamics modeling study to provide insight into the mode of DNA binding to the chromosomal HMG-domain protein, HMG-D. Three models of a complex of HMG-D bound to DNA were derived through docking the protein to two different DNA fragments of known structure. Molecular dynamics simulations of the complexes provided data indicating the most favorable model. This model was further refined by molecular dynamics simulation and extensively analyzed. The structure of the corresponding HMG-D-DNA complex exhibits many features seen in the NMR structures of the sequence-specific HMG-domain-DNA complexes, lymphoid enhancer factor 1 (LEF-1) and testis determining factor (SRY). The model reveals differences from these known structures that suggest how chromosomal proteins bind to many different DNA sequences with comparable affinity. Proteins 30:113–135, 1998. © 1998 Wiley-Liss, Inc.     

InterProSurf: a web server for predicting interacting sites on protein surfaces

A new web server, InterProSurf, predicts interacting amino acid residues in proteins that are most likely to interact with other proteins, given the 3D structures of subunits of a protein complex. The prediction method is based on solvent accessible surface area of residues in the isolated subunits, a propensity scale for interface residues and a clustering algorithm to identify surface regions with residues of high interface propensities. Here we illustrate the application of InterProSurf to determine which areas of Bacillus anthracis toxins and measles virus hemagglutinin protein interact with their respective cell surface receptors. The computationally predicted regions overlap with those regions previously identified as interface regions by sequence analysis and mutagenesis experiments. AVAILABILITY: The InterProSurf web server is available at http://curie.utmb.edu/     

Improving the accuracy of protein pKa calculations: Conformational averaging versus the average structure

Several methods for including the conformational flexibility of proteins in the calculation of titration curves are compared. The methods use the linearized Poisson-Boltzmann equation to calculate the electrostatic free energies of solvation and are applied to bovine pancreatic trypsin inhibitor (BPTI) and hen egg-white lysozyme (HEWL). An ensemble of conformations is generated by a molecular dynamics simulation of the proteins with explicit solvent. The average titration curve of the ensemble is calculated in three different ways: an average structure is used for the pK_a calculation; the electrostatic interaction free energies are averaged and used for the pK_a calculation; and the titration curve for each structure is calculated and the curves are averaged. The three averaging methods give very similar results and improve the pK_a values to approximately the same degree. This suggests, in contrast to implications from other work, that the observed improvement of pK_a values in the present studies is due not to averaging over an ensemble of structures, but rather to the generation of a single properly averaged structure for the pK_a calculation. Proteins 33:145–158, 1998. © 1998 Wiley-Liss, Inc.     

Use of quantitative structure-property relationships to predict the folding ability of model proteins

We investigate the folding of a 125-bead heteropolymer model for proteins subject to Monte Carlo dynamics on a simple cubic lattice. Detailed study of a few sequences revealed a folding mechanism consisting of a rapid collapse followed by a slow search for a stable core that served as the transition state for folding to a near-native intermediate. Rearrangement from the intermediate to the native state slowed folding further because it required breaking native-like local structure between surface monomers so that those residues could condense onto the core. We demonstrate here the generality of this mechanism by a statistical analysis of a 200 sequence database using a method that employs a genetic algorithm to pick the sequence attributes that are most important for folding and an artificial neural network to derive the corresponding functional dependence of folding ability on the chosen sequence attributes [quantitative structure-property relationships (QSPRs)]. QSPRs that use three sequence attributes yielded substantially more accurate predictions than those that use only one. The results suggest that efficient search for the core is dependent on both the native state's overall stability and its amount of kinetically accessible, cooperative structure, whereas rearrangement from the intermediate is facilitated by destabilization of contacts between surface monomers. Implications for folding and design are discussed. Proteins 33:177–203, 1998. © 1998 Wiley-Liss, Inc.     

A linear function for the approximation of accessible surface area of proteins

Since the solvent accessible surface area of proteins has been utilized as an important factor in the prediction of their thermodynamic properties, a simple and analytical method for its determination would contribute to protein structure prediction and analysis methods. We report the development of a simple and analytical method for the estimation of the accessible surface area of protein, consisting of linear functions of distances between unified atoms. While our formulation was much simpler than previously developed methods, it showed comparable performance, with the mean relative error on total solvent accessible surface area of 0.49 and 2.16% for 89 denatured and native protein structures, respectively. Moreover, the partial derivatives of accessible surface area to the position of unified atoms could also be derived in a simpler form.     

Hydrophobic patches on protein subunit interfaces: Characteristics and prediction

Hydrophobic patches, defined as clusters of neighboring apolar atoms deemed accessible on a given protein surface, have been investigated on protein subunit interfaces. The data were taken from known tertiary structures of multimeric protein complexes. Amino acid composition and preference, patch size distribution, and patch contact complementarity across associating subunits were examined and compared with hydrophobic patches found on the solvent-accessible surface of the multimeric complexes. The largest or second largest patch on the accessible surface of the entire subunit was involved in multimeric interfaces in 90% of the cases. These results should prove useful for subunit design and engineering as well as for prediction of subunit interface regions. Proteins 28:333–343, 1997. © 1997 Wiley-Liss, Inc.     

PredRSA: a gradient boosted regression trees approach for predicting protein solvent accessibility

Protein solvent accessibility prediction is a pivotal intermediate step towards modeling protein tertiary structures directly from one-dimensional sequences. It also plays an important part in identifying protein folds and domains. Although some methods have been presented to the protein solvent accessibility prediction in recent years, the performance is far from satisfactory. In this work, we propose PredRSA, a computational method that can accurately predict relative solvent accessible surface area (RSA) of residues by exploring various local and global sequence features which have been observed to be associated with solvent accessibility. Based on these features, a novel and efficient approach, Gradient Boosted Regression Trees (GBRT), is first adopted to predict RSA. Experimental results obtained from 5-fold cross-validation based on the Manesh-215 dataset show that the mean absolute error (MAE) and the Pearson correlation coefficient (PCC) of PredRSA are 9.0 % and 0.75, respectively, which are better than that of the existing methods. Moreover, we evaluate the performance of PredRSA using an independent test set of 68 proteins. Compared with the state-of-the-art approaches (SPINE-X and ASAquick), PredRSA achieves a significant improvement on the prediction quality. Our experimental results show that the Gradient Boosted Regression Trees algorithm and the novel feature combination are quite effective in relative solvent accessibility prediction. The proposed PredRSA method could be useful in assisting the prediction of protein structures by applying the predicted RSA as useful restraints.