Knowledge-based protein modeling

3PFDB--a database of best representative PSSM profiles (BRPs) of protein families generated using a novel data mining approach

BACKGROUND

Protein families could be related to each other at broad levels that group them as superfamilies. These relationships are harder to detect at the sequence level due to high evolutionary divergence. Sequence searches are strongly directed and influenced by the best representatives of families that are viewed as starting points. PSSMs are useful approximations and mathematical representations of protein alignments, with wide array of applications in bioinformatics approaches like remote homology detection, protein family analysis, detection of new members and evolutionary modelling. Computational intensive searches have been performed using the neural network based sensitive sequence search method called FASSM to identify the Best Representative PSSMs for families reported in Pfam database version 22.

RESULTS

We designed a novel data mining approach for the assessment of individual sequences from a protein family to identify a single Best Representative PSSM profile (BRP) per protein family. Using the approach, a database of protein family-specific best representative PSSM profiles called 3PFDB has been developed. PSSM profiles in 3PFDB are curated using performance of individual sequence as a reference in a rigorous scoring and coverage analysis approach using FASSM. We have assessed the suitability of 10, 85,588 sequences derived from seed or full alignments reported in Pfam database (Version 22). Coverage analysis using FASSM method is used as the filtering step to identify the best representative sequence, starting from full length or domain sequences to generate the final profile for a given family. 3PFDB is a collection of best representative PSSM profiles of 8,524 protein families from Pfam database.

CONCLUSION

Availability of an approach to identify BRPs and a curated database of best representative PSI-BLAST derived PSSMs for 91.4% of current Pfam family will be a useful resource for the community to perform detailed and specific analysis using family-specific, best-representative PSSM profiles. 3PFDB can be accessed using the URL: http://caps.ncbs.res.in/3pfdb.

Extensive conformational searches of 13 representative dipeptides and an efficient method for dipeptide structure determinations based on amino acid conformers

Conformations of peptides are the basis for their property studies and the predictions of peptide structures are highly important in life science but very complex in practice. Here, thorough searches on the potential energy surfaces of 13 representative dipeptides by considering all possible combinations of the bond rotational degrees of freedom are performed using the density functional theory based methods. Careful analyses of the conformers of the 13 dipeptides and the corresponding amino acids reveal the connections between the structures of dipeptide and amino acids. A method for finding all important dipeptide conformers by optimizing a small number of trial structures generated by suitable superposition of the parent amino acid conformations is thus proposed. Applying the method to another eight dipeptides carefully examined by others shows that the new approach is both highly efficient and reliable by providing the most complete ensembles of dipeptide conformers and much improved agreements between the theoretical and experimental IR spectra. The method opens the door for the determination of the stable structures of all dipeptides with a manageable amount of effort. Preliminary result on the applicability of the method to the tripeptide structure determination is also presented. The results are the first step towards proving Anfinsen's hypothesis by revealing the relationships between the structures of the simplest peptide and its constituting amino acids. It implies that the structures of peptides are not only determined by their amino acid sequences, but also closely linked with the amino acid conformations.

Homology modeling and docking analysis of the interaction between polyphenols and mammalian 20S proteasomes

Molecular docking of small ligands to biologically active macromolecules has become a valuable strategy to predict the stability of complexes between potential partners and their binding modes. In this perspective, we applied this computational procedure to rationalize the reported role of polyphenols as inhibitors of the mammalian 20S proteasomes. In particular, polyphenols were shown to modulate each proteasomal activity at different extents both in the constitutive and the inducible enzyme. We performed a flexible molecular docking analysis between a set of polyphenols previously demonstrated to have the highest binding affinity and both the constitutive (from deposited PDB structures) and homology modeled active subunits of the IFN-gamma inducible proteasome, to provide insight into the possible mechanism of interaction. Among the tested polyphenols, (-)-epigallocatechin-3-gallate showed the highest affinity for the proteasome subunits, both in terms of intermolecular energy and predicted equilibrium constants, in particular for beta5 and beta5i subunits (E(total) = -66 kcal/mol, Ki = 81.3 microM and E(Total) = -83.9 kcal/mol, Ki = 0.29 microM, respectively), known to be related to the chymotrypsin-like and BrAAP activities. Collectively, polyphenols showed a higher affinity for the inducible subunits, in agreement with previous in vitro studies. Additionally, different contributions to the interaction energy (van der Waals, electrostatic, H-bond) of proteasome-polyphenols complexes were dissected.

Molecular modeling and characterization of the B. thuringiensis and B. thuringiensis LDC-9 cytolytic proteins

The Cyt toxins are able to lyse a wide range of cell types in vitro, unlike the Cry delta-endotoxins. It exerts its activity by the formation of pores within target cell membranes. The structural information available for Cyt2Aa (PDB id: 1CBY) consists of a single domain in which two outer layers of alpha-helix wrap around a mixed beta-sheet. Beta-barrel was suggested as a possible structure of the pores. Hence, this study seeks to investigate the structural properties of other Cytolytic proteins by predicting the three-dimensional (3D) model using Cyt2Aa as template. The predicted models are expected to be significantly more accurate as all the Cyt proteins showed significant similarity with the template (PDB id: 1CBY). The refined homology models revealed similar secondary structures (alpha-helices and beta-sheets) and tertiary features as Cyt2Aa. The variation in the loop regions of the tertiary structure accounts for the differential toxicity.

Molecular modeling of human BAD and its interaction with PKAc or PP1c

To build up the structure of human BAD (Bcl-2 antagonist of cell death), subsequently combined with PKAc or PP1c (protein phosphatase 1), to investigate the interaction relationship between BAD and its kinase/PTPese at the molecular level. Additionally, it is concerned with the search for all optimal positions and orientations of a set of amino acid residues of BAD, while its binding sites include N-termini (Glu19, Ala27, and Ser34-Lys35), BH3-located helical domain (Arg98-Lys126), and C-termini (Trp154-Ser163 and Ser167-Gln168). The related sites of PKAc are mainly assembled in C-terminal alpha/beta-domain of PKAc, which comprises the KTL motif (47-49), Glu203 residue, a helical region (Asp241-Arg256), and the span from 328 to 333; while the interaction sites with BAD converge at C-terminal beta-domain of PP1c, which includes the DEK motif (166-168), the stretch from 179 to 197 including a helix (Glu184-Arg188), Glu230-Asp242 segment containing Val232-His237 helix, and Glu287-Leu289 loop. In conclusion, analysis of the complex between BAD and PKAc or PP1c provides a novel viewpoint on the structural origins of molecular recognition. And the complex models suggest that BH3 domain of BAD interact with PKAc or PP1c by electrostatic, van der Waals contacts, hydrogen bond and salt bridge. This is helpful for our development and research of some new drugs, especially mimetic BH3 peptides and inspires scientists with BAD complex and molecular mechanism of its integrating glycolysis and apoptosis.

Inferring evolution of fish proteins: the globin case study

Because hemoglobins (Hbs) of all animal species have the same heme group, differences in their properties, including oxygen affinity, electrophoretic mobility, and pH sensitivity, must result from the interaction of the prosthetic group with specific amino acid residues in the primary structure. For this reason, fish globins have been the object of extensive studies in the past few years, not only for their structural characteristics but also because they offer the possibility to investigate the evolutionary history of Hbs in marine and freshwater species living in a large variety of environmental conditions. For such a purpose, phylogenetic analysis of globin sequences can be combined with knowledge of the phylogenetic relationships between species. In addition, Type I functional-divergence analysis is aimed toward predicting the amino acid residues that are more likely responsible for biochemical diversification of different Hb families. These residues, mapped on the three-dimensional Hb structure, can provide insights into functional and structural divergence.

Insights into molecular medicine: development of new diagnostic and prognostic parameters

Molecular medicine leads us towards an understanding of some diseases at the molecular level. Examples are the analysis of immune complexes and receptor-antireceptor compounds used in clinical medicine. Structural changes of some serum proteins occur in inflammation, neoplasia and autoimmunity. The detection and analysis of such structural modifications may offer a new field for the diagnosis, prognosis and therapy of some diseases. Modern medicine requires new technologies with high sensitivity, specificity and applicability. For the first time in Austria we have combined fluorescence correlation spectroscope (FCS), surface enhanced laser desorption ionisation--time of flight (SELDI-TOF) and the molecular modelling and visualization system according to the computer enhanced programs. Experimental and computational methods are combined in such a way that clinical data can be interpreted by theoretical methods at a molecular level or vice versa, the computational output delivers input for new investigations. One method brings us single results. In view of the spectrum of parameters relevant to clinical entities, multiplexing is a new way of development. Since the technologies are new, the scientifically interested reader should be informed about the matters arising.

Ab initio protein fold prediction using evolutionary algorithms: influence of design and control parameters on performance

True ab initio prediction of protein 3D structure requires only the protein primary structure, a physicochemical free energy model, and a search method for identifying the free energy global minimum. Various characteristics of evolutionary algorithms (EAs) mean they are in principle well suited to the latter. Studies to date have been less than encouraging, however. This is because of the limited consideration given to EA design and control parameter issues. A comprehensive study of these issues was, therefore, undertaken for ab initio protein fold prediction using a full atomistic protein model. The performance and optimal control parameter settings of twelve EA designs where first established using a 15-residue polyalanine molecule-design aspects varied include the encoding alphabet, crossover operator, and replacement strategy. It can be concluded that real encoding and multipoint crossover are superior, while both generational and steady-state replacement strategies have merits. The scaling between the optimal control parameter settings and polyalanine size was also identified for both generational and steady-state designs based on real encoding and multipoint crossover. Application of the steady-state design to met-enkephalin indicated that these scalings are potentially transferable to real proteins. Comparison of the performance of the steady state design for met-enkephalin with other ab initio methods indicates that EAs can be competitive provided the correct design and control parameter values are used.

Comparative Modeling of Drug Target Proteins

In this perspective, we begin by describing the comparative protein structure modeling technique and the accuracy of the corresponding models. We then discuss the significant role that comparative prediction plays in drug discovery. We focus on virtual ligand screening against comparative models and illustrate the state of the art by a number of specific examples.

How inaccuracies in protein structure models affect estimates of protein-ligand interactions: computational analysis of HIV-I protease inhibitor binding

The influence of possible inaccuracies that can arise during homology modeling of protein structures used for ligand binding studies were investigated with the molecular mechanics generalized Born surface area (MM-GBSA) method. For this, a family of well-characterized HIV-I protease-inhibitor complexes was used. Validation of MM-GBSA led to a correlation coefficient ranging from 0.72 to 0.93 between calculated and experimental binding free energies DeltaG. All calculated DeltaG values were based on molecular dynamics simulations with explicit solvent. Errors introduced into the protein structure through misplacement of side-chains during rotamer modeling led to a correlation coefficient between DeltaG(calc) and DeltaG(exp) of 0.75 compared with 0.90 for the correctly placed side chains. This is in contrast to homology models for members of the retroviral protease family with template structures ranging in sequence identity between 32% and 51%. For these protein models, the correlation coefficients vary between 0.84 and 0.87, which is considerably closer to the original protein (0.90). It is concluded that HIV-I low sequence identity with the template structure still allows creating sufficiently reliable homology models to be used for ligand-binding studies, although placement of the rotamers is a critical step during the modeling.

HARMONY: a server for the assessment of protein structures

Protein structure validation is an important step in computational modeling and structure determination. Stereochemical assessment of protein structures examine internal parameters such as bond lengths and Ramachandran (varphi,psi) angles. Gross structure prediction methods such as inverse folding procedure and structure determination especially at low resolution can sometimes give rise to models that are incorrect due to assignment of misfolds or mistracing of electron density maps. Such errors are not reflected as strain in internal parameters. HARMONY is a procedure that examines the compatibility between the sequence and the structure of a protein by assigning scores to individual residues and their amino acid exchange patterns after considering their local environments. Local environments are described by the backbone conformation, solvent accessibility and hydrogen bonding patterns. We are now providing HARMONY through a web server such that users can submit their protein structure files and, if required, the alignment of homologous sequences. Scores are mapped on the structure for subsequent examination that is useful to also recognize regions of possible local errors in protein structures. HARMONY server is located at http://caps.ncbs.res.in/harmony/

Advances in homology protein structure modeling

Homology modeling plays a central role in determining protein structure in the structural genomics project. The importance of homology modeling has been steadily increasing because of the large gap that exists between the overwhelming number of available protein sequences and experimentally solved protein structures, and also, more importantly, because of the increasing reliability and accuracy of the method. In fact, a protein sequence with over 30% identity to a known structure can often be predicted with an accuracy equivalent to a low-resolution X-ray structure. The recent advances in homology modeling, especially in detecting distant homologues, aligning sequences with template structures, modeling of loops and side chains, as well as detecting errors in a model, have contributed to reliable prediction of protein structure, which was not possible even several years ago. The ongoing efforts in solving protein structures, which can be time-consuming and often difficult, will continue to spur the development of a host of new computational methods that can fill in the gap and further contribute to understanding the relationship between protein structure and function.

A knowledge-based scoring function based on residue triplets for protein structure prediction

One of the general paradigms for ab initio protein structure prediction involves sampling the conformational space such that a large set of decoy (candidate) structures are generated and then selecting native-like conformations from those decoys using various scoring functions. In this study, based on a physical/geometric approach first suggested by Banavar and colleagues, we formulate a knowledge-based scoring function, which uses the radii of curvature formed among triplets of residues in a protein conformation. By analyzing its performance on various decoy sets, we determine a good set of parameters--the distance cutoff and the number of distance bins--to use for configuring such a function. Furthermore, we investigate the effect of using various approaches for compiling the prior distribution on the performance of the knowledge-based function. Possible extensions to the current form of the residue triplet scoring function are discussed.

A comparative study of available software for high-accuracy homology modeling: from sequence alignments to structural models

An open question in protein homology modeling is, how well do current modeling packages satisfy the dual criteria of quality of results and practical ease of use? To address this question objectively, we examined homology-built models of a variety of therapeutically relevant proteins. The sequence identities across these proteins range from 19% to 76%. A novel metric, the difference alignment index (DAI), is developed to aid in quantifying the quality of local sequence alignments. The DAI is also used to construct the relative sequence alignment (RSA), a new representation of global sequence alignment that facilitates comparison of sequence alignments from different methods. Comparisons of the sequence alignments in terms of the RSA and alignment methodologies are made to better understand the advantages and caveats of each method. All sequence alignments and corresponding 3D models are compared to their respective structure-based alignments and crystal structures. A variety of protein modeling software was used. We find that at sequence identities >40%, all packages give similar (and satisfactory) results; at lower sequence identities (<25%), the sequence alignments generated by Profit and Prime, which incorporate structural information in their sequence alignment, stand out from the rest. Moreover, the model generated by Prime in this low sequence identity region is noted to be superior to the rest. Additionally, we note that DSModeler and MOE, which generate reasonable models for sequence identities >25%, are significantly more functional and easier to use when compared with the other structure-building software.

CHORAL: a differential geometry approach to the prediction of the cores of protein structures

MOTIVATION

Although the cores of homologous proteins are relatively well conserved, amino acid substitutions lead to significant differences in the structures of divergent superfamilies. Thus, the classification of amino acid sequence patterns and the selection of appropriate fragments of the protein cores of homologues of known structure are important for accurate comparative modelling.

RESULTS

CHORAL utilizes a knowledge-based method comprising an amalgam of differential geometry and pattern recognition algorithms to identify conserved structural patterns in homologous protein families. Propensity tables are used to classify and to select patterns that most likely represent the structure of the core for a target protein. In our benchmark, CHORAL demonstrates a performance equivalent to that of MODELLER.

Computational Exploration of the Catalytic Mechanism of Dopamine β-Monooxygenase: Modeling of Its Mononuclear Copper Active Sites

Dopamine hydroxylation by the copper-superoxo, -hydroperoxo, and -oxo species of dopamine beta-monooxygenase (DBM) is investigated using theoretical calculations to identify the active species in its reaction and to reveal the key functions of the surrounding amino acid residues in substrate binding. A 3D model of rat DBM is constructed by homology modeling using the crystal structure of peptidylglycine alpha-hydroxylating monooxygenase (PHM) with a high sequence identity of 30% as a template. In the constructed 3D model, the CuA site in domain 1 is coordinated by three histidine residues, His265, His266, and His336, while the CuB site in domain 2 is coordinated by two histidine residues, His415 and His417, and by a methionine residue, Met490. The three Glu268, Glu369, and Tyr494 residues are suggested to play an important role in the substrate binding at the active site of DBM to enable the stereospecific hydrogen-atom abstraction. Quantum mechanical/molecular mechanical (QM/MM) calculations are performed to determine the structure of the copper-superoxo, -hydroperoxo, and -oxo species in the whole-enzyme model with about 4700 atoms. The reactivity of the three oxidants is evaluated in terms of density-functional-theory calculations with small models extracted from the QM region of the whole-enzyme model.

Checkpoint kinase inhibitors: SAR and radioprotective properties of a series of 2-arylbenzimidazoles

The discovery of a series of novel, potent, and highly selective inhibitors of the DNA damage control kinase chk2 is disclosed. Here we report the first SAR study around inhibitors of this kinase. High-throughput screening of purified human chk2 led to the identification of a novel series of 2-arylbenzimidazole inhibitors of the kinase. Optimization was facilitated using homology models of chk2 and docking of inhibitors, leading to the highly potent 2-arylbenzimidazole 2h (IC(50) 15 nM). Compound 2h is an ATP-competitive inhibitor of chk2 that dose dependently protects human CD4(+) and CD8(+) T-cells from apoptosis due to ionizing radiation. This work suggests that a selective small molecule inhibitor of chk2 could be a useful adjuvant to radiotherapy, increasing the therapeutic window of such treatment.

Structure of glutathione S-transferase of the filarial parasite Wuchereria bancrofti: a target for drug development against adult worm

A three dimensional structural model of Glutathione-S-transferase (GST) of the lymphatic filarial parasite Wuchereria bancrofti (wb) was constructed by homology modeling. The three dimensional X-ray crystal structure of porcine pi-class GST with PDB ID: 2gsr-A chain protein with 42% sequential and functional homology was used as the template. The model of wbGST built by MODELLER6v2 was analyzed by the PROCHECK programs. Ramachandran plot analysis showed that 93.5% of the residues are in the core region followed by 5.4 and 1.1% residues in the allowed and generously allowed regions, respectively. None of the non-glycine residues is in disallowed regions. The PROSA II z-score and the energy graph for the final model further confirmed the quality of the modeled structure. The computationally modeled three-dimensional (3D) structure of wbGST has been submitted to the Protein Data Bank (PDB) (PDB ID: 1SFM and RCSB ID: RCSB021668). 1SFM was used for docking with GST inhibitors by Hex4.2 macromolecular docking using spherical polar Fourier correlations.

Some fundamental aspects of building protein structures from fragment libraries

We have investigated some of the basic principles that influence generation of protein structures using a fragment-based, random insertion method. We tested buildup methods and fragment library quality for accuracy in constructing a set of known structures. The parameters most influential in the construction procedure are bond and torsion angles with minor inaccuracies in bond angles alone causing >6 A CalphaRMSD for a 150-residue protein. Idealization to a standard set of values corrects this problem, but changes the torsion angles and does not work for every structure. Alternatively, we found using Cartesian coordinates instead of torsion angles did not reduce performance and can potentially increase speed and accuracy. Under conditions simulating ab initio structure prediction, fragment library quality can be suboptimal and still produce near-native structures. Using various clustering criteria, we created a number of libraries and used them to predict a set of native structures based on nonnative fragments. Local CalphaRMSD fit of fragments, library size, and takeoff/landing angle criteria weakly influence the accuracy of the models. Based on a fragment's minimal perturbation upon insertion into a known structure, a seminative fragment library was created that produced more accurate structures with fragments that were less similar to native fragments than the other sets. These results suggest that fragments need only contain native-like subsections, which when correctly overlapped, can recreate a native-like model. For fragment-based, random insertion methods used in protein structure prediction and design, our findings help to define the parameters this method needs to generate near-native structures.

A polynomial-time nuclear vector replacement algorithm for automated NMR resonance assignments

High-throughput NMR structural biology can play an important role in structural genomics. We report an automated procedure for high-throughput NMR resonance assignment for a protein of known structure, or of a homologous structure. These assignments are a prerequisite for probing protein-protein interactions, protein-ligand binding, and dynamics by NMR. Assignments are also the starting point for structure determination and refinement. A new algorithm, called Nuclear Vector Replacement (NVR) is introduced to compute assignments that optimally correlate experimentally measured NH residual dipolar couplings (RDCs) to a given a priori whole-protein 3D structural model. The algorithm requires only uniform( 15)N-labeling of the protein and processes unassigned H(N)-(15)N HSQC spectra, H(N)-(15)N RDCs, and sparse H(N)-H(N) NOE's (d(NN)s), all of which can be acquired in a fraction of the time needed to record the traditional suite of experiments used to perform resonance assignments. NVR runs in minutes and efficiently assigns the (H(N),(15)N) backbone resonances as well as the d(NN)s of the 3D (15)N-NOESY spectrum, in O(n(3)) time. The algorithm is demonstrated on NMR data from a 76-residue protein, human ubiquitin, matched to four structures, including one mutant (homolog), determined either by x-ray crystallography or by different NMR experiments (without RDCs). NVR achieves an assignment accuracy of 92-100%. We further demonstrate the feasibility of our algorithm for different and larger proteins, using NMR data for hen lysozyme (129 residues, 97-100% accuracy) and streptococcal protein G (56 residues, 100% accuracy), matched to a variety of 3D structural models. Finally, we extend NVR to a second application, 3D structural homology detection, and demonstrate that NVR is able to identify structural homologies between proteins with remote amino acid sequences using a database of structural models.

SUPFAM: a database of sequence superfamilies of protein domains

BACKGROUND

SUPFAM database is a compilation of superfamily relationships between protein domain families of either known or unknown 3-D structure. In SUPFAM, sequence families from Pfam and structural families from SCOP are associated, using profile matching, to result in sequence superfamilies of known structure. Subsequently all-against-all family profile matches are made to deduce a list of new potential superfamilies of yet unknown structure.

DESCRIPTION

The current version of SUPFAM (release 1.4) corresponds to significant enhancements and major developments compared to the earlier and basic version. In the present version we have used RPS-BLAST, which is robust and sensitive, for profile matching. The reliability of connections between protein families is ensured better than before by use of benchmarked criteria involving strict e-value cut-off and a minimal alignment length condition. An e-value based indication of reliability of connections is now presented in the database. Web access to a RPS-BLAST-based tool to associate a query sequence to one of the family profiles in SUPFAM is available with the current release. In terms of the scientific content the present release of SUPFAM is entirely reorganized with the use of 6190 Pfam families and 2317 structural families derived from SCOP. Due to a steep increase in the number of sequence and structural families used in SUPFAM the details of scientific content in the present release are almost entirely complementary to previous basic version. Of the 2286 families, we could relate 245 Pfam families with apparently no structural information to families of known 3-D structures, thus resulting in the identification of new families in the existing superfamilies. Using the profiles of 3904 Pfam families of yet unknown structure, an all-against-all comparison involving sequence-profile match resulted in clustering of 96 Pfam families into 39 new potential superfamilies.

CONCLUSION

SUPFAM presents many non-trivial superfamily relationships of sequence families involved in a variety of functions and hence the information content is of interest to a wide scientific community. The grouping of related proteins without a known structure in SUPFAM is useful in identifying priority targets for structural genomics initiatives and in the assignment of putative functions. Database URL: http://pauling.mbu.iisc.ernet.in/~supfam.

Tolerance to the substitution of buried apolar residues by charged residues in the homologous protein structures

Occurrence and accommodation of charged amino acid residues in proteins that are structurally equivalent to buried non-polar residues in homologues have been investigated. Using a dataset of 1,852 homologous pairs of crystal structures of proteins available at 2A or better resolution, 14,024 examples of apolar residues in the structurally conserved regions replaced by charged residues in homologues have been identified. Out of 2,530 cases of buried apolar residues, 1,677 of the equivalent charged residues in homologues are exposed and the rest of the charged residues are buried. These drastic substitutions are most often observed in homologous protein pairs with low sequence identity (<30%) and in large protein domains (>300 residues). Such buried charged residues in the large proteins are often located in the interface of sub-domains or in the interface of structural repeats, Beyond 7A of residue depth of buried apolar residues, or less than 4% of solvent accessibility, almost all the substituting charged residues are buried. It is also observed that acidic sidechains have higher preference to get buried than the positively charged residues. There is a preference for buried charged residues to get accommodated in the interior by forming hydrogen bonds with another sidechain than the main chain. The sidechains interacting with a buried charged residue are most often located in the structurally conserved regions of the alignment. About 50% of the observations involving hydrogen bond between buried charged sidechain and another sidechain correspond to salt bridges. Among the buried charged residues interacting with the main chain, positively charged sidechains form hydrogen bonds commonly with main chain carbonyls while the negatively charged residues are accommodated by hydrogen bonding with the main chain amides. These carbonyls and amides are usually located in the loops that are structurally variable among homologous proteins.

Tripeptide analysis of protein structures

BACKGROUND

An efficient building block for protein structure prediction can be tripeptides. 8000 different tripeptides from a dataset of 1220 high resolution (<or= 2.0 degrees A) structures from the Protein Data Bank (PDB) have been looked at, to determine which are structurally rigid and non-rigid. This data has been statistically analyzed, discussed and summarized. The entire data can be utilized for the building of protein structures.

RESULTS

Tripeptides have been classified into three categories: rigid, non-rigid and intermediate, based on the relative structural rigidity between Calpha and Cbeta atoms in a tripeptide. We found that 18% of the tripeptides in the dataset can be classified as rigid, 4% as non-rigid and 78% as intermediate. Many rigid tripeptides are made of hydrophobic residues, however, there are tripeptides with polar side chains forming rigid structures. The bulk of the tripeptides fall in the intermediate class while very small numbers actually fall in the non-rigid class. Structurally all rigid tripeptides essentially form two structural classes while the intermediate and non-rigid tripeptides fall into one structural class. This notion of rigidity and non-rigidity is designed to capture side chain interactions but not secondary structures.

CONCLUSIONS

Rigid tripeptides have no correlation with the secondary structures in proteins and hence this work is complementary to such studies. Tripeptide data may be used to predict plausible structures for oligopeptides and for denovo protein design.

Analysis of structure and function relationships of an autoantigenic peptide of insulin bound to H-2K(d) that stimulates CD8 T cells in insulin-dependent diabetes mellitus

The recognition of MHC-peptide complexes by T cells is governed by structural considerations that are determined by the sequences of the individual components and their interaction with each other. We have studied the function of a highly diabetogenic CD8 T cell clone that is specific for insulin B15-23:H-2K(d). We have then related this to modeled MHC-peptide structures. The native peptide binds poorly to H-2K(d), because of the small glycine residue at peptide position p9 that is incapable of productive interactions with the hydrophobic residues of pocket F. In addition, electrostatic repulsions between the peptide glutamate residue at position 7 and 152D of the MHC molecule heavy chain contribute to the poor binding. However, B chain peptide 15-23 bound to K(d) shows excellent T cell stimulation and the induction of CD8 cytotoxic T cells. Peptide substitution has also shown that p6G is likely to be a T cell antigen receptor interaction site. Our studies have shown that the predictions seen in the models correlate closely with the observed effects in functional assays and provide insight into how this peptide, which would not be predicted to stimulate these cells on H-2K(d) binding studies alone, could activate such highly pathogenic T cells.

PARM: a practical utility for drug design

To accommodate situations in which the 3D structure of the target receptor is not available, we have developed the Pseudo Atomic Receptor Model (PARM) software package. In this article we describe PARM and illustrate its use with three examples: elemenes (potential anticancer drugs), angiotensin converting enzyme inhibitors, and human HIV-1 inhibitors TTD (1,1,3-trioxo-2H, 4H-thieno[3,4-e][1,2,4] thiadiazine derivatives). The results show that PARM can build models with favorable cross-validation statistics (Rcv2 values 0.7-0.9) and give helpful SAR insight. PARM has certain advantages: (a) it can be used for many systems, regardless of whether the 3D structure of the receptor is known; (b) PARM models were demonstrated to be highly statistically reliable; and (c) PARM analyses are robust and reproducible.

High-throughput crystallography for lead discovery in drug design

Knowledge of the three-dimensional structures of protein targets now emerging from genomic data has the potential to accelerate drug discovery greatly. X-ray crystallography is the most widely used technique for protein structure determination, but technical challenges and time constraints have traditionally limited its use primarily to lead optimization. Here, we describe how significant advances in process automation and informatics have aided the development of high-throughput X-ray crystallography, and discuss the use of this technique for structure-based lead discovery.

MODBASE, a database of annotated comparative protein structure models

MODBASE (http://guitar.rockefeller.edu/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on PSI-BLAST, IMPALA and MODELLER. MODBASE uses the MySQL relational database management system for flexible and efficient querying, and the MODVIEW Netscape plugin for viewing and manipulating multiple sequences and structures. It is updated regularly to reflect the growth of the protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different datasets. The largest dataset contains models for domains in 304 517 out of 539 171 unique protein sequences in the complete TrEMBL database (23 March 2001); only models based on significant alignments (PSI-BLAST E-value < 10(-4)) and models assessed to have the correct fold are included. Other datasets include models for target selection and structure-based annotation by the New York Structural Genomics Research Consortium, models for prediction of genes in the Drosophila melanogaster genome, models for structure determination of several ribosomal particles and models calculated by the MODWEB comparative modeling web server.

Free energy force field (FEFF) 3D-QSAR analysis of a set of Plasmodium falciparum dihydrofolate reductase inhibitors

Free energy force field (FEFF) 3D-QSAR analysis was used to construct ligand-receptor binding models for a set of 18 structurally diverse antifolates including pyrimethamine, cycloguanil, methotrexate, aminopterin and trimethoprim, and 13 pyrrolo[2,3-d]pyrimidines. The molecular target ('receptor') used was a 3D-homology model of a specific mutant type of Plasmodium falciparum (Pf) dihydrofolate reductase (DHFR). The dependent variable of the 3D-QSAR models is the IC50 inhibition constant for the specific mutant type of PfDHFR. The independent variables of the 3D-QSAR models (the descriptors) are scaled energy terms of a modified first-generation AMBER force field combined with a hydration shell aqueous solvation model and a collection of 2D-QSAR descriptors often used in QSAR studies. Multiple temperature molecular dynamics simulation (MDS) and the genetic function approximation (GFA) were employed using partial least square (PLS) and multidimensional linear regressions as the fitting functions to develop FEFF 3D-QSAR models for the binding process. The significant FEFF energy terms in the best 3D-QSAR models include energy contributions of the direct ligand-receptor interaction. Some changes in conformational energy terms of the ligand due to binding to the enzyme are also found to be important descriptors. The FEFF 3D-QSAR models indicate some structural features perhaps relevant to the mechanism of resistance of the PfDHFR to current antimalarials. The FEFF 3D-QSAR models are also compared to receptor-independent (RI) 4D-QSAR models developed in an earlier study and subsequently refined using recently developed generalized alignment rules.

Classification of protein disulphide-bridge topologies

The preferential occurrence of certain disulphide-bridge topologies in proteins has prompted us to design a method and a program, KNOT-MATCH, for their classification. The program has been applied to a database of proteins with less than 65% homology and more than two disulphide bridges. We have investigated whether there are topological preferences that can be used to group proteins and if these can be applied to gain insight into the structural or functional relationships among them. The classification has been performed by Density Search and Hierarchical Clustering Techniques, yielding thirteen main protein classes from the superimposition and clustering process. It is noteworthy that besides the disulphide bridges, regular secondary structures and loops frequently become correctly aligned. Although the lack of significant sequence similarity among some clustered proteins precludes the easy establishment of evolutionary relationships, the program permits us to find out important structural or functional residues upon the superimposition of two protein structures apparently unrelated. The derived classification can be very useful for finding relationships among proteins which would escape detection by current sequence or topology-based analytical algorithms.

CODA: a combined algorithm for predicting the structurally variable regions of protein models

CODA, an algorithm for predicting the variable regions in proteins, combines FREAD a knowledge based approach, and PETRA, which constructs the region ab initio. FREAD selects from a database of protein structure fragments with environmentally constrained substitution tables and other rule-based filters. FREAD was parameterized and tested on over 3000 loops. The average root mean square deviation ranged from 0.78 A for three residue loops to 3.5 A for eight residue loops on a nonhomologous test set. CODA clusters the predictions from the two independent programs and makes a consensus prediction that must pass a set of rule-based filters. CODA was parameterized and tested on two unrelated separate sets of structures that were nonhomologous to one another and those found in the FREAD database. The average root mean square deviation in the test set ranged from 0.76 A for three residue loops to 3.09 A for eight residue loops. CODA shows a general improvement in loop prediction over PETRA and FREAD individually. The improvement is far more marked for lengths six and upward, probably as the predictive power of PETRA becomes more important. CODA was further tested on several model structures to determine its applicability to the modeling situation. A web server of CODA is available at http://www-cryst.bioc.cam.ac.uk/~charlotte/Coda/search_coda.html.

Comparative protein structure modeling of genes and genomes

Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. The number of protein sequences that can be modeled and the accuracy of the predictions are increasing steadily because of the growth in the number of known protein structures and because of the improvements in the modeling software. Further advances are necessary in recognizing weak sequence-structure similarities, aligning sequences with structures, modeling of rigid body shifts, distortions, loops and side chains, as well as detecting errors in a model. Despite these problems, it is currently possible to model with useful accuracy significant parts of approximately one third of all known protein sequences. The use of individual comparative models in biology is already rewarding and increasingly widespread. A major new challenge for comparative modeling is the integration of it with the torrents of data from genome sequencing projects as well as from functional and structural genomics. In particular, there is a need to develop an automated, rapid, robust, sensitive, and accurate comparative modeling pipeline applicable to whole genomes. Such large-scale modeling is likely to encourage new kinds of applications for the many resulting models, based on their large number and completeness at the level of the family, organism, or functional network.

PALI-a database of Phylogeny and ALIgnment of homologous protein structures

PALI (release 1.2) contains three-dimensional (3-D) structure-dependent sequence alignments as well as structure-based phylogenetic trees of homologous protein domains in various families. The data set of homologous protein structures has been derived by consulting the SCOP database (release 1.50) and the data set comprises 604 families of homologous proteins involving 2739 protein domain structures with each family made up of at least two members. Each member in a family has been structurally aligned with every other member in the same family (pairwise alignment) and all the members in the family are also aligned using simultaneous super-position (multiple alignment). The structural alignments are performed largely automatically, with manual interventions especially in the cases of distantly related proteins, using the program STAMP (version 4.2). Every family is also associated with two dendrograms, calculated using PHYLIP (version 3.5), one based on a structural dissimilarity metric defined for every pairwise alignment and the other based on similarity of topologically equivalent residues. These dendrograms enable easy comparison of sequence and structure-based relationships among the members in a family. Structure-based alignments with the details of structural and sequence similarities, superposed coordinate sets and dendrograms can be accessed conveniently using a web interface. The database can be queried for protein pairs with sequence or structural similarities falling within a specified range. Thus PALI forms a useful resource to help in analysing the relationship between sequence and structure variation at a given level of sequence similarity. PALI also contains over 653 'orphans' (single member families). Using the web interface involving PSI_BLAST and PHYLIP it is possible to associate the sequence of a new protein with one of the families in PALI and generate a phylogenetic tree combining the query sequence and proteins of known 3-D structure. The database with the web interfaced search and dendrogram generation tools can be accessed at http://pauling.mbu.iisc.ernet. in/ approximately pali.

Recurrent oligomers in proteins: an optimal scheme reconciling accurate and concise backbone representations in automated folding and design studies

A novel scheme is introduced to capture the spatial correlations of consecutive amino acids in naturally occurring proteins. This knowledge-based strategy is able to carry out optimally automated subdivisions of protein fragments into classes of similarity. The goal is to provide the minimal set of protein oligomers (termed "oligons" for brevity) that is able to represent any other fragment. At variance with previous studies in which recurrent local motifs were classified, our concern is to provide simplified protein representations that have been optimised for use in automated folding and/or design attempts. In such contexts, it is paramount to limit the number of degrees of freedom per amino acid without incurring loss of accuracy of structural representations. The suggested method finds, by construction, the optimal compromise between these needs. Several possible oligon lengths are considered. It is shown that meaningful classifications cannot be done for lengths greater than six or smaller than four. Different contexts are considered for which oligons of length five or six are recommendable. With only a few dozen oligons of such length, virtually any protein can be reproduced within typical experimental uncertainties. Structural data for the oligons are made publicly available.

Structure of celiac disease-associated HLA-DQ8 and non-associated HLA-DQ9 alleles in complex with two disease-specific epitopes

The association of celiac disease (CD) with HLA-DQ2 and HLA-DQ8 is indicative of preferential mucosal T cell recognition of gluten fragments bound to either DQ allele. We have recently identified two gluten-derived, HLA-DQ8-restricted T cell stimulatory peptides, one each from gliadin and glutenin, recognized by specific T cell clones derived from the small intestine of CD patients. We have now performed molecular modeling and examined the fine specificity of these peptides in complex with HLA-DQ8. There is only one binding register for both peptides, with glutamine residues at the p1 and p9 anchor positions. Both T cell clones recognize substituted peptides at p1 and p9, but poorly so at p2-p8, especially the gliadin-specific clone. Contrasting patterns of recognition of p9Gln --> Glu peptide variants (both predicted as better DQ8 binders by modeling) were observed: enhancement of recognition for the gliadin peptide, yet complete absence thereof for the glutenin peptide. The double-substituted gliadin peptide variant p1/9Gln --> Glu, which can also arise by pepsin/acid/transglutaminase treatment, shows a considerable increase in sensitivity of recognition, consistent with better binding of this peptide to DQ8, as predicted by energy minimization. Surprisingly, the two native peptides are also recognized by their respective T cell clones in the context of the related molecule HLA-DQ9 (beta57Asp(+)). The p1/9Gln --> Glu gliadin peptide variant is likewise recognized, albeit with a 10-fold lower sensitivity, the first reported p9Glu binding in a beta57Asp(+) MHC II allele. Our results have important implications for the pathogenesis of autoimmune disease and the possible manipulation of aberrant responses thereof.

MODBASE, a database of annotated comparative protein structure models

MODBASE is a queryable database of annotated comparative protein structure models. The models are derived by MODPIPE, an automated modeling pipeline relying on the programs PSI-BLAST and MODELLER. The database currently contains 3D models for substantial portions of approximately 17 000 proteins from 10 complete genomes, including those of Caenorhabditis elegans, Saccharomyces cerevisiae and Escherichia coli, as well as all the available sequences from Arabidopsis thaliana and Homo sapiens. The database also includes fold assignments and alignments on which the models were based. In addition, special care is taken to assess the quality of the models. ModBase is accessible through a web interface at http://guitar.rockefeller.edu/modbase/

Analysis and prediction of inter-strand packing distances between beta-sheets of globular proteins

Any two beta-strands belonging to two different beta-sheets in a protein structure are considered to pack interactively if each beta-strand has at least one residue that undergoes a loss of one tenth or more of its solvent contact surface area upon packing. A data set of protein 3-D structures (determined at 2.5 A resolution or better), corresponding to 428 protein chains, contains 1986 non-identical pairs of beta-strands involved in interactive packing. The inter-axial distance between these is significantly correlated to the weighted sum of the volumes of the interacting residues at the packing interface. This correlation can be used to predict the changes in the inter-sheet distances in equivalent beta-sheets in homologous proteins and, therefore, is of value in comparative modelling of proteins.

"RKKH" peptides from the snake venom metalloproteinase of Bothrops jararaca bind near the metal ion-dependent adhesion site of the human integrin alpha(2) I-domain

Integrin alpha(1)beta(1) and alpha(2)beta(1) are the major cellular receptors for collagen, and collagens bind to these integrins at the inserted I-domain in their alpha subunit. We have previously shown that a cyclic peptide derived from the metalloproteinase domain of the snake venom protein jararhagin blocks the collagen-binding function of the alpha(2) I-domain. Here, we have optimized the structure of the peptide and identified the site where the peptide binds to the alpha(2) I-domain. The peptide sequence Arg-Lys-Lys-His is critical for recognition by the I-domain, and five negatively charged residues surrounding the "metal ion-dependent adhesion site" (MIDAS) of the I-domain, when mutated, show significantly impaired binding of the peptide. Removal of helix alphaC, located along one side of the MIDAS and suggested to be involved in collagen-binding in these I-domains, does not affect peptide binding. This study supports the notion that the metalloproteinase initially binds to the alpha(2) I-domain at a location distant from the active site of the protease, thus blocking collagen binding to the adhesion molecule in the vicinity of the MIDAS, while at the same time leaving the active site free to degrade nearby proteins, the closest being the beta(1) subunit of the alpha(2)beta(1) cell-surface integrin itself.

Prediction of three-dimensional structure and mapping of conformational epitopes of envelope glycoprotein of Japanese encephalitis virus

Japanese encephalitis virus (JEV), a mosquito-borne flavivirus, is an important human pathogen. The envelope glycoprotein (Egp), a major structural antigen, is responsible for viral haemagglutination and eliciting neutralising antibodies. The three-dimensional structure of the Egp of JEV was predicted using the knowledge-based homology modeling approach and X-ray structure data of the Egp of tick-borne encephalitis virus as a template (Rey et al., 1995). In the initial stages of optimisation, a distance-dependent dielectric constant of 4r(ij) was used to simulate the solvent effect. The predicted structure was refined by solvating the protein in a 10-A layer of water by explicitly considering 4867 water molecules. Four independent structure evaluation methods report this structure to be acceptable stereochemically and geometrically. The Egp of JEV has an extended structure with seven beta-sheets, two alpha-helices, and three domains. The water-solvated structure was used to delineate conformational and sequential epitopes. These results document the importance of tertiary structure in understanding the antigenic properties of flaviviruses in general and JEV in particular. The conformational epitope prediction method could be used to identify conformational epitopes on any protein antigen with known three-dimensional structure. This is one of the largest proteins whose three-dimensional structure has been predicted using an homology modeling approach and water as a solvent.

Progress in protein structure prediction: assessment of CASP3

The third comparative assessment of techniques of protein structure prediction (CASP3) was held during 1998. This is a blind trial in which structures are predicted prior to having knowledge of the coordinates, which are then revealed to enable the assessment. Three sections at the meeting evaluated different methodologies - comparative modelling, fold recognition and ab initio methods. For some, but not all of the target coordinates, high quality models were submitted in each of these sections. There have been improvements in prediction techniques since CASP2 in 1996, most notably for ab initio methods.

A homology modeling method of an icosahedral viral capsid: inclusion of surrounding protein structures

A methodological development is presented for homology modeling of an icosahedrally symmetric assembly of proteins. In the method, a main-chain structure of an asymmetric unit of a protein assembly is constructed and structure refinement is performed, taking the surrounding symmetry-related proteins into consideration with rotational symmetry boundary conditions. To test the procedure, three models of a poliovirus capsid were constructed with different modeling conditions based on the X-ray structure of a rhinovirus capsid. Model S and model N were constructed with and without considering surrounding proteins, respectively. Model N2 was obtained by refinement in rotational symmetry boundary conditions of the structure of model N. The three models were compared with the X-ray structure of a poliovirus capsid. Root mean square deviations and C alpha distances indicate that model S is the most accurate. Examination of the intermolecular short contacts indicates that model S and model N2 are superior to model N, because they do not make severe intermolecular short contacts. Symmetric intermolecular interactions are important for both the structural fragment search and energy minimization to predict better loop structures. The programs developed in this study are thus valuable in homology modeling of an icosahedral viral capsid.

Analysis of interactive packing of secondary structural elements in alpha/beta units in proteins

An alpha-helix and a beta-strand are said to be interactively packed if at least one residue in each of the secondary structural elements loses 10% of its solvent accessible contact area on association with the other secondary structural element. An analysis of all such 5,975 nonidentical alpha/beta units in protein structures, defined at < or = 2.5 A resolution, shows that the interaxial distance between the alpha-helix and the beta-strand is linearly correlated with the residue-dependent function, log[(V/nda)/n-int], where V is the volume of amino acid residues in the packing interface, nda is the normalized difference in solvent accessible contact area of the residues in packed and unpacked secondary structural elements, and n-int is the number of residues in the packing interface. The beta-sheet unit (beta u), defined as a pair of adjacent parallel or antiparallel hydrogen-bonded beta-strands, packing with an alpha-helix shows a better correlation between the interaxial distance and log(V/nda) for the residues in the packing interface. This packing relationship is shown to be useful in the prediction of interaxial distances in alpha/beta units using the interacting residue information of equivalent alpha/beta units of homologous proteins. It is, therefore, of value in comparative modeling of protein structures.

Homology modeling of cephalopod lens S-crystallin: a natural mutant of sigma-class glutathione transferase with diminished endogenous activity

The soluble S-crystallin constitutes the major lens protein in cephalopods. The primary amino acid sequence of S-crystallin shows an overall 41% identity with the digestive gland sigma-class glutathione transferase (GST) of cephalopod. However, the lens S-crystallin fails to bind to the S-hexylglutathione affinity column and shows very little GST activity in the nucleophilic aromatic substitution reaction between GSH and 1-chloro-2,4-dinitrobenzene. When compared with other classes of GST, the S-crystallin has an 11-amino acid residues insertion between the conserved alpha4 and alpha5 helices. Based on the crystal structure of squid sigma-class GST, a tertiary structure model for the octopus lens S-crystallin is constructed. The modeled S-crystallin structure has an overall topology similar to the squid sigma-class GST, albeit with longer alpha4 and alpha5 helical chains, corresponding to the long insertion. This insertion, however, makes the active center region of S-crystallin to be in a more closed conformation than the sigma-class GST. The active center region of S-crystallin is even more shielded and buried after dimerization, which may explain for the failure of S-crystallin to bind to the immobilized-glutathione in affinity chromatography. In the active site region, the electrostatic potential surface calculated from the modeled structure is quite different from that of squid GST. The positively charged environment, which contributes to stabilize the negatively charged Meisenheimer complex, is altered in S-crystallin probably because of mutation of Asn99 in GST to Asp101 in S-crystallin. Furthermore, the important Phe106 in authentic GST is changed to His108 in S-crystallin. Combining the topological differences as revealed by computer graphics and sequence variation at these structurally relevant residues provide strong structural evidences to account for the much decreased GST activity of S-crystallin as compared with the authentic GST of the digestive gland.