Combining multiple structure and sequence alignments to improve sequence detection and alignment: application to the SH2 domains of Janus kinases.

In this paper, an approach is described that combines multiple structure alignments and multiple sequence alignments to generate sequence profiles for protein families. First, multiple sequence alignments are generated from sequences that are closely related to each sequence of known three-dimensional structure. These alignments then are merged through a multiple structure alignment of family members of known structure. The merged alignment is used to generate a Hidden Markov Model for the family in question. The Hidden Markov Model can be used to search for new family members or to improve alignments for distantly related family members that already have been identified. Application of a profile generated for SH2 domains indicates that the Janus family of nonreceptor protein tyrosine kinases contains SH2 domains. This conclusion is strongly supported by the results of secondary structure-prediction programs, threading calculations, and the analysis of comparative models generated for these domains. One of the Janus kinases, human TYK2, has an SH2 domain that contains a histidine instead of the conserved arginine at the key phosphotyrosine-binding position, betaB5. Calculations of the pK(a) values of the betaB5 arginines in a number of SH2 domains and of the betaB5 histidine in a homology model of TYK2 suggest that this histidine is likely to be neutral around pH 7, thus indicating that it may have lost the ability to bind phosphotyrosine. If this indeed is the case, TYK2 may contain a domain with an SH2 fold that has a modified binding specificity.

Electrostatic contributions to protein-protein interactions: fast energetic filters for docking and their physical basis.

The methods of continuum electrostatics are used to calculate the binding free energies of a set of protein-protein complexes including experimentally determined structures as well as other orientations generated by a fast docking algorithm. In the native structures, charged groups that are deeply buried were often found to favor complex formation (relative to isosteric nonpolar groups), whereas in nonnative complexes generated by a geometric docking algorithm, they were equally likely to be stabilizing as destabilizing. These observations were used to design a new filter for screening docked conformations that was applied, in conjunction with a number of geometric filters that assess shape complementarity, to 15 antibody-antigen complexes and 14 enzyme-inhibitor complexes. For the bound docking problem, which is the major focus of this paper, native and near-native solutions were ranked first or second in all but two enzyme-inhibitor complexes. Less success was encountered for antibody-antigen complexes, but in all cases studied, the more complete free energy evaluation was able to identify native and near-native structures. A filter based on the enrichment of tyrosines and tryptophans in antibody binding sites was applied to the antibody-antigen complexes and resulted in a native and near-native solution being ranked first and second in all cases. A clear improvement over previously reported results was obtained for the unbound antibody-antigen examples as well. The algorithm and various filters used in this work are quite efficient and are able to reduce the number of plausible docking orientations to a size small enough so that a final more complete free energy evaluation on the reduced set becomes computationally feasible.

The role of electrostatic interactions in the regulation of the membrane association of G protein beta gamma heterodimers.

In this paper we report calculations of electrostatic interactions between the transducin (G(t)) betagamma heterodimer (G(t)betagamma) and phospholipid membranes. Although membrane association of G(t)betagamma is due primarily to the hydrophobic penetration into the membrane interior of a farnesyl chain attached to the gamma subunit, structural studies have revealed that there is a prominent patch of basic residues on the surface of the beta subunit surrounding the site of farnesylation that is exposed upon dissociation from the G(t)alpha subunit. Moreover, phosducin, which produces dissociation of G(t)betagamma from membranes, interacts directly with G(t)betagamma and introduces a cluster of acidic residues into this region. The calculations, which are based on the finite difference Poisson-Boltzmann method, account for a number of experimental observations and suggest that charged residues play a role in mediating protein-membrane interactions. Specifically, the calculations predict the following. 1) Favorable electrostatic interactions enhance the membrane partitioning due to the farnesyl group by an order of magnitude although G(t)betagamma has a large net negative charge (-12). 2) This electrostatic attraction positions G(t)betagamma so that residues implicated in mediating the interaction of G(t)betagamma with its membrane-bound effectors are close to the membrane surface. 3) The binding of phosducin to G(t)betagamma diminishes the membrane partitioning of G(t)betagamma by an order of magnitude. 4) Lowering the ionic strength of the solution converts the electrostatic attraction into a repulsion. Sequence analysis and homology model building suggest that our conclusions may be generalized to other Gbetagamma and phosducin isoforms as well.

Extending the accuracy limits of prediction for side-chain conformations.

Current techniques for the prediction of side-chain conformations on a fixed backbone have an accuracy limit of about 1.0-1.5 A rmsd for core residues. We have carried out a detailed and systematic analysis of the factors that influence the prediction of side-chain conformation and, on this basis, have succeeded in extending the limits of side-chain prediction for core residues to about 0.7 A rmsd from native, and 94 % and 89 % of chi(1) and chi(1+2 ) dihedral angles correctly predicted to within 20 degrees of native, respectively. These results are obtained using a force-field that accounts for only van der Waals interactions and torsional potentials. Prediction accuracy is strongly dependent on the rotamer library used. That is, a complete and detailed rotamer library is essential. The greatest accuracy was obtained with an extensive rotamer library, containing over 7560 members, in which bond lengths and bond angles were taken from the database rather than simply assuming idealized values. Perhaps the most surprising finding is that the combinatorial problem normally associated with the prediction of the side-chain conformation does not appear to be important. This conclusion is based on the fact that the prediction of the conformation of a single side-chain with all others fixed in their native conformations is only slightly more accurate than the simultaneous prediction of all side-chain dihedral angles.

Protein structure prediction.

The prediction of protein structure, based primarily on sequence and structure homology, has become an increasingly important activity. Homology models have become more accurate and their range of applicability has increased. Progress has come, in part, from the flood of sequence and structure information that has appeared over the past few years, and also from improvements in analysis tools. These include profile methods for sequence searches, the use of three-dimensional structure information in sequence alignment and new homology modeling tools, specifically in the prediction of loop and side-chain conformations. There have also been important advances in understanding the physical chemical basis of protein stability and the corresponding use of physical chemical potential functions to identify correctly folded from incorrectly folded protein conformations.

An integrated approach to the analysis and modeling of protein sequences and structures. I. Protein structural alignment and a quantitative measure for protein structural distance.

We have devised and implemented in PrISM (protein informatics system for modeling) a new measure of protein structural relationships, the protein structural distance (PSD). The PSD is designed to describe relationships between protein structures in quantitative rather than descriptive terms and is applicable both when two structures are very similar, and when they are very different. It is calculated with a structural alignment procedure that uses double dynamic programming to align secondary structure elements and an iterative rigid body superposition that minimizes the root-mean-square deviation of C(alpha) atoms. The alignment algorithm, as implemented on a modest workstation, is computationally efficient, allowing for large-scale structural comparisons. PSD scores for more than one and a half million pairs of proteins were calculated and compared to the discrete classification of proteins in the SCOP database. The PSD scores, which were obtained automatically, are in large part consistent with the manually derived classifications in SCOP. Discrepancies do arise, however, due, in part, to the fact that SCOP uses criteria other than structural similarity to derive classifications while the PrISM procedure is exclusively structure based. Analysis of PSD scores suggests that there is a continuous aspect of protein conformation space, even though various classification schemes are extremely useful. The use of a continuous measure for structural distance between all pairs of proteins allows us, as described in the two accompanying papers to derive sequence/structure relationships in a more quantitative way than has previously been possible. An important strength of the approach implemented in PrISM is its ability to address many different kinds of queries interactively, making its structural comparison procedure a convenient computational tool that complements structural classification databases such as SCOP and CATH.

An integrated approach to the analysis and modeling of protein sequences and structures. II. On the relationship between sequence and structural similarity for proteins that are not obviously related in sequence.

Here, we discuss the relationship between protein sequence and protein structural similarity. It is established that a protein structural distance (PSD) of 2.0 is a threshold above which two proteins are unlikely to have a detectable pairwise sequence relationship. A precise correlation is established between the level of sequence similarity, defined by a normalized Smith-Waterman score, and the probability that two proteins will have a similar structure (defined by pairwise PSD<2). This correlation can be used in evaluating the likelihood for success in a comparative modeling procedure. We establish the existence of a correlation between sequence and structural similarity for pairs of proteins that are related in structure but whose sequence relationship is not detectable using standard pairwise sequence alignments. Although it is well known that there is a close relationship between sequence and structural similarity for pairwise sequence identities greater than about 30 %, there has been little discussion as to the possible existence of such a relationship for pairs of proteins in or below the twilight zone of sequence similarity (<25 % pairwise sequence identity). Possible implications of our results for the evolution of protein structure are discussed.

An integrated approach to the analysis and modeling of protein sequences and structures. III. A comparative study of sequence conservation in protein structural families using multiple structural alignments.

The information required to generate a protein structure is contained in its amino acid sequence, but how three-dimensional information is mapped onto a linear sequence is still incompletely understood. Multiple structure alignments of similar protein structures have been used to investigate conserved sequence features but contradictory results have been obtained, due, in large part, to the absence of subjective criteria to be used in the construction of sequence profiles and in the quantitative comparison of alignment results. Here, we report a new procedure for multiple structure alignment and use it to construct structure-based sequence profiles for similar proteins. The definition of "similar" is based on the structural alignment procedure and on the protein structural distance (PSD) described in paper I of this series, which offers an objective measure for protein structure relationships. Our approach is tested in two well-studied groups of proteins; serine proteases and Ig-like proteins. It is demonstrated that the quality of a sequence profile generated by a multiple structure alignment is quite sensitive to the PSD used as a threshold for the inclusion of proteins in the alignment. Specifically, if the proteins included in the aligned set are too distant in structure from one another, there will be a dilution of information and patterns that are relevant to a subset of the proteins are likely to be lost. In order to understand better how the same three-dimensional information can be encoded in seemingly unrelated sequences, structure-based sequence profiles are constructed for subsets of proteins belonging to nine superfolds. We identify patterns of relatively conserved residues in each subset of proteins. It is demonstrated that the most conserved residues are generally located in the regions where tertiary interactions occur and that are relatively conserved in structure. Nevertheless, the conservation patterns are relatively weak in all cases studied, indicating that structure-determining factors that do not require a particular sequential arrangement of amino acids, such as secondary structure propensities and hydrophobic interactions, are important in encoding protein fold information. In general, we find that similar structures can fold without having a set of highly conserved residue clusters or a well-conserved sequence profile; indeed, in some cases there is no apparent conservation pattern common to structures with the same fold. Thus, when a group of proteins exhibits a common and well-defined sequence pattern, it is more likely that these sequences have a close evolutionary relationship rather than the similarities having arisen from the structural requirements of a given fold.

Association entropy in adsorption processes.

The association of two species to form a bound complex, e.g., the binding of a ligand to a protein or the adsorption of a peptide on a lipid membrane, involves an entropy loss, reflecting the conversion of free translational and rotational degrees of freedom into bound motions. Previous theoretical estimates of the standard entropy change in bimolecular binding processes, DeltaS(o), have been derived from the root-mean-square fluctuations in protein crystals, suggesting DeltaS(o) approximately -50 e.u., i.e., TDeltaS degrees approximately -25 kT = -15 kcal/mol. In this work we focus on adsorption, rather than binding processes. We first present a simple statistical-thermodynamic scheme for calculating the adsorption entropy, including its resolution into translational and rotational contributions, using the known distance-orientation dependent binding (adsorption) potential. We then utilize this scheme to calculate the free energy of interaction and entropy of pentalysine adsorption onto a lipid membrane, obtaining TDeltaS(o) approximately -1.7 kT approximately -1.3 kcal/mol. Most of this entropy change is due to the conversion of one free translation into a bound motion, the rest arising from the confinement of two rotational degrees of freedom. The smaller entropy loss in adsorption compared to binding processes arises partly because a smaller number of degrees of freedom become restricted, but mainly due to the fact that the binding potential is much "softer."

Membrane binding of peptides containing both basic and aromatic residues. Experimental studies with peptides corresponding to the scaffolding region of caveolin and the effector region of MARCKS.

We have studied the binding of peptides containing both basic and aromatic residues to phospholipid vesicles. The peptides caveolin(92-101) and MARCKS(151-175) both contain five aromatic residues, but have 3 and 13 positive charges, respectively. Our results show the aromatic residues insert into the bilayer and anchor the peptides weakly to vesicles formed from the zwitterionic lipid phosphatidylcholine (PC). Incorporation of a monovalent acidic lipid (e.g., phosphatidylserine, PS) into the vesicles enhances the binding of both peptides via nonspecific electrostatic interactions. As predicted from application of the Poisson-Boltzmann equation to atomic models of the peptide and membranes, the enhancement is larger (e.g., 10(4)- vs 10-fold for 17% PS) for the more basic MARCKS(151-175). Replacing the five Phe with five Ala residues in MARCKS(151-175) decreases the binding to 10:1 PC/PS vesicles only slightly (6-fold). This result is also consistent with the predictions of our theoretical model: the loss of the attractive hydrophobic energy is partially compensated by a decrease in the repulsive Born/desolvation energy as the peptide moves away from the membrane surface. Incorporating multivalent phosphatidylinositol 4, 5-bisphosphate (PIP(2)) into PC vesicles produces dramatically different effects on the membrane binding of the two peptides: 1% PIP(2) enhances caveolin(92-101) binding only 3-fold, but increases MARCKS(151-175) binding 10(4)-fold. The strong interaction between the effector region of MARCKS and PIP(2) has interesting implications for the cellular function of MARCKS.

Electrostatic aspects of protein-protein interactions.

Structural and mutational analyses reveal a central role for electrostatic interactions in protein-protein association. Experiment and theory both demonstrate that clusters of charged and polar residues that are located on protein-protein interfaces may enhance complex stability, although the total effect of electrostatics is generally net destabilizing. The past year also witnessed significant progress in our understanding of the effect of electrostatics on protein association kinetics, specifically in the characterization of a partially desolvated encounter complex.

Free energy determinants of tertiary structure and the evaluation of protein models.

We develop a protocol for estimating the free energy difference between different conformations of the same polypeptide chain. The conformational free energy evaluation combines the CHARMM force field with a continuum treatment of the solvent. In almost all cases studied, experimentally determined structures are predicted to be more stable than misfolded "decoys." This is due in part to the fact that the Coulomb energy of the native protein is consistently lower than that of the decoys. The solvation free energy generally favors the decoys, although the total electrostatic free energy (sum of Coulomb and solvation terms) favors the native structure. The behavior of the solvation free energy is somewhat counterintuitive and, surprisingly, is not correlated with differences in the burial of polar area between native structures and decoys. Rather. the effect is due to a more favorable charge distribution in the native protein, which, as is discussed, will tend to decrease its interaction with the solvent. Our results thus suggest, in keeping with a number of recent studies, that electrostatic interactions may play an important role in determining the native topology of a folded protein. On this basis, a simplified scoring function is derived that combines a Coulomb term with a hydrophobic contact term. This function performs as well as the more complete free energy evaluation in distinguishing the native structure from misfolded decoys. Its computational efficiency suggests that it can be used in protein structure prediction applications, and that it provides a physically well-defined alternative to statistically derived scoring functions.

Electrostatic properties of membranes containing acidic lipids and adsorbed basic peptides: theory and experiment.

The interaction of heptalysine with vesicles formed from mixtures of the acidic lipid phosphatidylserine (PS) and the zwitterionic lipid phosphatidylcholine (PC) was examined experimentally and theoretically. Three types of experiments showed that smeared charge theories (e.g., Gouy-Chapman-Stern) underestimate the membrane association when the peptide concentration is high. First, the zeta potential of PC/PS vesicles in 100 mM KCl solution increased more rapidly with heptalysine concentration (14.5 mV per decade) than predicted by a smeared charge theory (6.0 mV per decade). Second, changing the net surface charge density of vesicles by the same amount in two distinct ways produced dramatically different effects: the molar partition coefficient decreased 1000-fold when the mole percentage of PS was decreased from 17% to 4%, but decreased only 10-fold when the peptide concentration was increased to 1 microM. Third, high concentrations of basic peptides reversed the charge on PS and PC/PS vesicles. Calculations based on finite difference solutions to the Poisson-Boltzmann equation applied to atomic models of heptalysine and PC/PS membranes provide a molecular explanation for the observations: a peptide adsorbing to the membrane in the presence of other surface-adsorbed peptides senses a local potential more negative than the average potential. The biological implications of these "discreteness-of-charge" effects are discussed.

Calculating the electrostatic properties of RNA provides new insights into molecular interactions and function.

Solutions to the nonlinear Poisson-Boltzmann equation were used to obtain the electrostatic potentials of RNA molecules that have known three-dimensional structures. The results are described in terms of isopotential contours and surface electrostatic potential maps. Both representations have unexpected features: 'cavities' within isopotential contours and areas of enhanced negative potential on molecular surfaces. Intriguingly, the sites of unusual electrostatic features correspond to functionally important regions, suggesting that electrostatic properties play a key role in RNA recognition and stabilization. These calculations reveal that the electrostatic potentials generated by RNA molecules have a variety of functionally important characteristics that cannot be discerned by simple visual inspection of the molecular structure.

Protein folding: from the levinthal paradox to structure prediction.

This article is a personal perspective on the developments in the field of protein folding over approximately the last 40 years. In addition to its historical aspects, the article presents a view of the principles of protein folding with particular emphasis on the relationship of these principles to the problem of protein structure prediction. It is argued that despite much that is new, the essential elements of our current understanding of protein folding were anticipated by researchers many years ago. These elements include the recognition of the central importance of the polypeptide backbone as a determinant of protein conformation, hierarchical protein folding, and multiple folding pathways. Important areas of progress include a detailed characterization of the folding pathways of a number of proteins and a fundamental understanding of the physical chemical forces that determine protein stability. Despite these developments, fold prediction algorithms still encounter difficulties in identifying the correct fold for a given sequence. This may be due to the possibility that the free energy differences between at least a few alternate conformations of many proteins are not large. Significant progress in protein structure prediction has been due primarily to the explosive growth of sequence and structural databases. However, further progress is likely to depend in part on the ability to combine information available from databases with principles and algorithms derived from physical chemical studies of protein folding. An approach to the integration of the two areas is outlined with specific reference to the PrISM program that is a fully integrated sequence/structural-analysis/fold-recognition/homology model building software system.

Sequence to structure alignment in comparative modeling using PrISM.

PrISM (Protein Informatics System for Modeling) is a protein analysis and modeling system in which informatics, alignment, modeling, and assessment modules are integrated in a computational environment where protein analysis and modeling protocols can be designed and assessed interactively. It can then be used automatically and repetitively in response to a variety of protein analysis and modeling problems. PrISM was used to predict a single model for each of the 43 targets in the CASP3 experiment. In this paper, we present results for 13 target sequences, which we consider to be comparative modeling targets with clearly related structural templates. We emphasize the problem of aligning a target sequence to a template structure with various alignment methods. When more than one alignment method and/or parameter set are applied, the final alignment is chosen on the basis of a model ranking system also used in PrISM's fold recognition module. Advanced sequence-template alignment procedures in PrISM are useful in some cases when standard pairwise dynamic programming algorithm fail to make any reasonable global alignment. The same procedures, however, failed in other cases, corresponding to remotely related query-template pairs that involved extensive insertions and deletions.

Improving macromolecular electrostatics calculations.

Electrostatic interactions play a key role in many aspects of protein engineering. Consequently, much effort has been put into the design of software for calculating electrostatic fields around macromolecules. We show that optimization of hydrogen bonding networks can improve both the results of pK(a) calculations and the results of electrostatic calculations performed by commonly used programs such as DelPhi. Further optimization can often be achieved by flipping the side chains of asparagine, histidine and glutamine around their chi2, chi2 and chi3 torsion angles, respectively, when this improves the local hydrogen bonding network. These optimizations are applied to some well characterized proteins: BPTI, hen egg white lysozyme and superoxide dismutase. A search for flipped residues in the PDB revealed that significant improvements in electrostatic calculations in or near the active site of enzymes can be expected for about one quarter of all enzymes in the PDB.

Electrostatic contributions to the stability of hyperthermophilic proteins.

Electrostatic contributions to the folding free energy of several hyperthermophilic proteins and their mesophilic homologs are calculated. In all the cases studied, electrostatic interactions are more favorable in the hyperthermophilic proteins. The electrostatic free energy is found not to be correlated with the number of ionizable amino acid residues, ion pairs or ion pair networks in a protein, but rather depends on the location of these groups within the protein structure. Moreover, due to the large free energy cost associated with burying charged groups, buried ion pairs are found to be destabilizing unless they undergo favorable interactions with additional polar groups, including other ion pairs. The latter case involves the formation of stabilizing ion pair networks as is observed in a number of proteins. Ion pairs located on the protein surface also provide stabilizing interactions in a number of cases. Taken together, our results suggest that many hyperthermophilic proteins enhance electrostatic interactions through the optimum placement of charged amino acid residues within the protein structure, although different design strategies are used in different cases. Other physical mechanisms are also likely to contribute, however optimizing electrostatic interactions offers a simple means of enhancing stability without disrupting the core residues characteristic of different protein families.

GRASS: a server for the graphical representation and analysis of structures.

GRASS (Graphical Representation and Analysis of Structures Server), a new web-based server, is described. GRASS exploits many of the features of the GRASP program and is designed to provide interactive molecular graphics and quantitative analysis tools with a simple interface over the World-Wide Web. Using GRASS, it is now possible to view many surface features of biological macromolecules on either standard workstations used in macromolecular analysis or personal computers. The result is a World-Wide Web-based, platform-independent, easily used tool for macromolecular visualization and structure analysis.

Structural determinants of trypsin affinity and specificity for cationic inhibitors.

The binding free energies of four inhibitors to bovine beta-trypsin are calculated. The inhibitors use either ornithine, lysine, or arginine to bind to the S1 specificity site. The electrostatic contribution to binding free energy is calculated by solving the finite difference Poisson-Boltzmann equation, the contribution of nonpolar interactions is calculated using a free energy-surface area relationship and the loss of conformational entropy is estimated both for trypsin and ligand side chains. Binding free energy values are of a reasonable magnitude and the relative affinity of the four inhibitors for trypsin is correctly predicted. Electrostatic interactions are found to oppose binding in all cases. However, in the case of ornithine- and lysine-based inhibitors, the salt bridge formed between their charged group and the partially buried carboxylate of Asp189 is found to stabilize the complex. Our analysis reveals how the molecular architecture of the trypsin binding site results in highly specific recognition of substrates and inhibitors. Specifically, partially burying Asp189 in the inhibitor-free enzyme decreases the penalty for desolvation of this group upon complexation. Water molecules trapped in the binding interface further stabilize the buried ion pair, resulting in a favorable electrostatic contribution of the ion pair formed with ornithine and lysine side chains. Moreover, all side chains that form the trypsin specificity site are partially buried, and hence, relatively immobile in the inhibitor-free state, thus reducing the entropic cost of complexation. The implications of the results for the general problem of recognition and binding are considered. A novel finding in this regard is that like charged molecules can have electrostatic contributions to binding that are more favorable than oppositely charged molecules due to enhanced interactions with the solvent in the highly charged complex that is formed.