Geometrical Conversion of the EGFR Extracellular Domain by Adiabatic Mapping Combining Normal Mode Analysis of the Elastic Network Model and Energy Optimization.

The activation of epidermal growth factor receptor (EGFR) involves the geometrical conversion of the extracellular domain (ECD) from the tethered to the extended forms with the dynamic rearrangement of the relative positions of four subdomains (SDs); however, this conversion process has not yet been thoroughly understood. We compare the two different forms of the X-ray crystal structures of ECD and simulate the ECD conversion process using adiabatic mapping that combines normal mode analysis of the elastic network model (ENM-NMA) and energy optimization. A comparison of the crystal structures reveals the rigidity of the intradomain geometry of the SD-I and -III backbone regardless of the form. The forward mapping from the tethered to the extended forms retains the intradomain geometry of the SD-I and -III backbone and reveals the trends to rearrange the relative positions of SD-I and -III and to dissociate the C-terminal tail of SD-IV from the hairpin loop in SD-II. The reverse mapping from the extended to the tethered forms complements the promotion of ECD conversion in the presence of epidermal growth factor (EGF).

Residue-residue interactions regulating the Ca2+-induced EF-hand conformation changes in calmodulin.

Calmodulin (CaM) is a Ca2+-binding messenger protein having four Ca2+-binding motifs named 'EF-hand'; the EF-hand motifs undergo a conformation change induced by Ca2+-binding. In order to study how Ca2+-binding induces the conformation change of EF-hand motifs and which residues are involved in the reaction, two 1µ second long MD simulations were independently performed from the apo- and holo-CaM and their structures and interactions were compared. The Ca2+-binding weakens the helix-helix interaction in all EF-hand, however, the holo-CaM MD adopted the close-like form. The correlation coefficients obtained from the two MDs show the residues comprising interactions being involved in their close-open conformation changes; most of these residues are hydrophobic amino acids but some of them are hydrophilic (T34, H107, N111 and Q143). The hydrophilic residues are expected to lock the EF-hands by their side-chains and main-chain carbonyl oxygen of another hydrophobic residue. Furthermore, the interaction pattern of EF-hand3 and 4 are similar to each other. On the other hand, the interaction pattern of EF-hand2 is different from others; its polar residues are expected to play an important role in regulating the EF-hand2 conformation.

Comprehensive analysis of the Co-structures of dipeptidyl peptidase IV and its inhibitor.

BACKGROUND: We comprehensively analyzed X-ray cocrystal structures of dipeptidyl peptidase IV (DPP-4) and its inhibitor to clarify whether DPP-4 alters its general or partial structure according to the inhibitor used and whether DPP-4 has a common rule for inhibitor binding. RESULTS: All the main and side chains in the inhibitor binding area were minimally altered, except for a few side chains, despite binding to inhibitors of various shapes. Some residues (Arg125, Glu205, Glu206, Tyr662 and Asn710) in the area had binding modes to fix a specific atom of inhibitor to a particular spatial position in DPP-4. We found two specific water molecules that were common to 92 DPP-4 structures. The two water molecules were close to many inhibitors, and seemed to play two roles: maintaining the orientation of the Glu205 and Glu206 side chains through a network via the water molecules, and arranging the inhibitor appropriately at the S2 subsite. CONCLUSIONS: Our study based on high-quality resources may provide a necessary minimum consensus to help in the discovery of a novel DPP-4 inhibitor that is commercially useful.

CAB-Align: A Flexible Protein Structure Alignment Method Based on the Residue-Residue Contact Area.

Proteins are flexible, and this flexibility has an essential functional role. Flexibility can be observed in loop regions, rearrangements between secondary structure elements, and conformational changes between entire domains. However, most protein structure alignment methods treat protein structures as rigid bodies. Thus, these methods fail to identify the equivalences of residue pairs in regions with flexibility. In this study, we considered that the evolutionary relationship between proteins corresponds directly to the residue-residue physical contacts rather than the three-dimensional (3D) coordinates of proteins. Thus, we developed a new protein structure alignment method, contact area-based alignment (CAB-align), which uses the residue-residue contact area to identify regions of similarity. The main purpose of CAB-align is to identify homologous relationships at the residue level between related protein structures. The CAB-align procedure comprises two main steps: First, a rigid-body alignment method based on local and global 3D structure superposition is employed to generate a sufficient number of initial alignments. Then, iterative dynamic programming is executed to find the optimal alignment. We evaluated the performance and advantages of CAB-align based on four main points: (1) agreement with the gold standard alignment, (2) alignment quality based on an evolutionary relationship without 3D coordinate superposition, (3) consistency of the multiple alignments, and (4) classification agreement with the gold standard classification. Comparisons of CAB-align with other state-of-the-art protein structure alignment methods (TM-align, FATCAT, and DaliLite) using our benchmark dataset showed that CAB-align performed robustly in obtaining high-quality alignments and generating consistent multiple alignments with high coverage and accuracy rates, and it performed extremely well when discriminating between homologous and nonhomologous pairs of proteins in both single and multi-domain comparisons. The CAB-align software is freely available to academic users as stand-alone software at http://www.pharm.kitasato-u.ac.jp/bmd/bmd/Publications.html.

Molecular recognition study on the binding of calcium to calbindin D9k based on 3D reference interaction site model theory.

Ca(2+)-binding proteins are widely distributed throughout cells and play various important roles. Calbindin D9k is a member of the EF-hand Ca(2+)-binding protein family. In this study, we examined the binding of Ca(2+) to calbindin D9k in terms of the free energy of solvation, as obtained by 3D reference interaction site model theory, which describes the statistical mechanics of liquids. We also investigated the main structural biological factor using spatial decomposition analysis in which the solvation free energy values are decomposed into the residue. We found some characteristic residues that contribute to stabilization of the holo-structure (Ca(2+)-binding structure). These results indicated that, in the holo-structure, these residues are newly exposed to solvent. Subsequently, the gain in solvation free energy, involving a conformational change and exposure to solvent, forms the driving force for binding of the Ca(2+) ion to the EF-hand.

Quality assessment methods for 3D protein structure models based on a residue-residue distance matrix prediction.

In the absence of experimentally determined three dimensional (3D) structures of proteins, the prediction of protein structures using computational methods is a standard alternative approach in bioinformatics. When using the predicted protein models to compute the native structure of an unknown target protein, estimating the actual quality of the protein models is important for selecting the best or near-best model. Moreover, estimates of the differences between the protein models and the native protein structure are obviously useful to end users who can then decide on the utility of the models for their specific problems. This article describes two new single-model quality assessment (QA) programs, pure single-model QA method (psQA) and a template based QA method (tbQA), that we developed. psQA is a pure single-model QA program that uses a neural network method to predict residue-residue distance matrices of the native protein structures. tbQA is a quasi-single-model QA program that mainly uses target-template sequence alignments and template structures. The performance of these two model QA programs was analyzed in a data set of 24022 models for 94 targets from the 10th critical assessment of protein structure prediction (CASP10) experiment.

Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions.

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.

United3D: a protein model quality assessment program that uses two consensus based methods.

In protein structure prediction, such as template-based modeling and free modeling (ab initio modeling), the step that assesses the quality of protein models is very important. We have developed a model quality assessment (QA) program United3D that uses an optimized clustering method and a simple Cα atom contact-based potential. United3D automatically estimates the quality scores (Qscore) of predicted protein models that are highly correlated with the actual quality (GDT_TS). The performance of United3D was tested in the ninth Critical Assessment of protein Structure Prediction (CASP9) experiment. In CASP9, United3D showed the lowest average loss of GDT_TS (5.3) among the QA methods participated in CASP9. This result indicates that the performance of United3D to identify the high quality models from the models predicted by CASP9 servers on 116 targets was best among the QA methods that were tested in CASP9. United3D also produced high average Pearson correlation coefficients (0.93) and acceptable Kendall rank correlation coefficients (0.68) between the Qscore and GDT_TS. This performance was competitive with the other top ranked QA methods that were tested in CASP9. These results indicate that United3D is a useful tool for selecting high quality models from many candidate model structures provided by various modeling methods. United3D will improve the accuracy of protein structure prediction.

LB3D: a protein three-dimensional substructure search program based on the lower bound of a root mean square deviation value.

Searching for protein structure-function relationships using three-dimensional (3D) structural coordinates represents a fundamental approach for determining the function of proteins with unknown functions. Since protein structure databases are rapidly growing in size, the development of a fast search method to find similar protein substructures by comparison of protein 3D structures is essential. In this article, we present a novel protein 3D structure search method to find all substructures with root mean square deviations (RMSDs) to the query structure that are lower than a given threshold value. Our new algorithm runs in O(m + N/m(0.5)) time, after O(N log N) preprocessing, where N is the database size and m is the query length. The new method is 1.8-41.6 times faster than the practically best known O(N) algorithm, according to computational experiments using a huge database (i.e., >20,000,000 C-alpha coordinates).

Community-wide assessment of protein-interface modeling suggests improvements to design methodology.

The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.

New protein structure model evaluation methods that include a side-chain consensus score for the protein modeling.

Selecting the best quality model from a set of predicted structures is one of the most important aspects of protein structure prediction. We have developed model quality assessment programs that select high quality models which account for both the Calpha backbone and side-chain atom positions. The new methods are based on the consensus method with consideration of the side-chain environment of a protein structure and the secondary structure agreement. This Side-chain Environment Consensus (SEC) method is compared with the conventional consensus method, 3D-Jury (Ginalski K. et al., Bioinformatics, 19, 1015-1018 (2003)), which takes into account only the Calpha backbone atoms of the protein model. As the result, it was found that the SEC method selects the models with more accurate positioning of the side-chain atoms than the 3D-Jury method. When the SEC method was used in combination with the 3D-Jury method (3DJ+SEC), models were selected with improved quality both in the Calpha backbone and side-chain atom positions. Moreover, the CIRCLE (CCL) method (Terashi G. et al., Proteins, 69 (Suppl. 8), 98-107 (2007)) based on the 3D-1D profile score has been shown to select the best possible models that are the closest to the native structures from candidate models. Accordingly, the 3DJ+SEC+CCL method, in which CIRCLE is used after reducing the number of candidates by the 3DJ+SEC consensus method, was found to be very effective in selecting high quality models. Thus, the best method (the 3DJ+SEC+CCL method) includes the consensus approaches of the Calpha backbone and the side-chains, the secondary structure agreement and the 3D-1D profile score which corresponds to the free energy-like score in the residues of the protein model. In short, new algorithms are introduced in protein structure evaluation methods that are based on a side-chain consensus score. Additionally, in order to apply the 3DJ+SEC+CCL method and indicate the usefulness of this method, a model of human Cabin1, a protein associated with p53 function and cancer, is created using various internet modeling and alignment servers.

Method for predicting homology modeling accuracy from amino acid sequence alignment: the power function.

We have devised a power function (PF) that can predict the accuracy of a three-dimensional (3D) structure model of a protein using only amino acid sequence alignments. This Power Function (PF) consists of three parts; (1) the length of a model, (2) a homology identity percent value and (3) the agreement rate between PSI-PRED secondary structure prediction and the secondary structure judgment of a reference protein. The PF value is mathematically computed from the execution process of homology search tools, such as FASTA or various BLAST programs, to obtain the amino acid sequence alignments. There is a high correlation between the global distance test-total score (GDT_TS) value of the protein model based upon the PF score and the GDT_TS(MAX) value used as an index of protein modeling accuracy in the international contest Critical Assessment of Techniques for Protein Structure Prediction (CASP). Accordingly, the PF method is valuable for constructing a highly accurate model without wasteful calculations of homology modeling that is normally performed by an iterative method to move the main chain and side chains in the modeling process. Moreover, a model with higher accuracy can be obtained by combining the models ordered by the PF score with models sorted by the size of the CIRCLE score. The CIRCLE software is a 3D-1D program, in which energetic stabilization is estimated based upon the experimental environment of each amino acid residue in the protein solution or protein crystals.

HUMAN FAMSD-BASE: high quality protein structure model database for the human genome using the FAMSD homology modeling method.

Almost all proteins express their biological functions through the structural conformation of their specific amino acid sequences. Therefore, acquiring the three-dimensional structures of proteins is very important to elucidate the role of a particular protein. We had built protein structure model databases, which is called RIKEN FAMSBASE (http://famshelp.gsc.riken.jp/famsbase/). The RIKEN FAMSBASE is a genome-wide protein structure model database that contains a large number of protein models from many organisms. The HUMAN FAMSBASE that is one part of the RIKEN FAMSBASE contains many protein models for human genes, which are significant in the pharmaceutical and medicinal fields. We have now implemented an update of the human protein modeling database consisting of 242918 constructed models against the number of 20743 human protein sequences with an improved modeling method called Full Automatic protein Modeling System Developed (FAMSD). The results of our benchmark test of the FAMSD method indicated that it has an excellent capability to pack amino acid side-chains with correct torsion angles in addition to the main-chain, while avoiding the formation of atom-atom collisions that are not found in experimental structures. This new protein structure model database for human genes, which is named HUMAN FAMSD-BASE, is open to the public as a component part of the RIKEN FAMSBASE at http://mammalia.gsc.riken.jp/human_famsd/. A significant improvement of the HUMAN FAMSD-BASE in comparison with the preceding HUMAN FAMSBASE was verified in the benchmark test of this paper. The HUMAN FAMSD-BASE will have an important impact on the progress of biological science.

FAMSD: A powerful protein modeling platform that combines alignment methods, homology modeling, 3D structure quality estimation and molecular dynamics.

The prediction of a protein three-dimensional (3D) structure is one of the most important challenges in computational structural biology. We have developed an automatic protein 3D structure prediction method called FAMSD. FAMSD is based on a comparative modeling method which consists of the following four steps: (1) generating and selecting sequence alignments between target and template proteins; (2) constructing 3D structure models based on each selected alignment; (3) selecting the best 3D structure model and (4) refining the selected model. In the FAMSD method, sequence alignment programs such as a series of BLAST programs, SP3 and SPARKS2 programs, the homology modeling program FAMS (Full Automatic Modeling System), the model quality estimation program CIRCLE and the molecular dynamics program APRICOT were used in combination to construct high quality protein models. To assess the FAMSD method we have participated in the 8th Critical Assessment of Techniques for Protein Structure Prediction (CASP8) experiment. The results of our original assessment indicate that the FAMSD method offers excellent capability in packing side-chains with the correct torsion angles while avoiding the formation of atom-atom collisions. Since side-chain packing plays a significant role in defining the biological function of proteins, this method is a valuable resource in biological, pharmaceutical and medicinal research efforts.

Dynamic influence of the two membrane-proximal immunoglobulin-like domains upon the peptide-binding platform domain in class I and class II major histocompatibility complexes: normal mode analysis.

Major histocompatibility complexes (MHCs) mainly fall into class I and class II. The two classes have similar structures, with two membrane-proximal immunoglobulin-like domains and a peptide-binding platform domain, though their organizations are different. We simulated the dynamics of a whole and partial model deficient in either of the two membrane-proximal domains for class I and class II using normal mode analysis. Our study showed that the influence of the two membrane-proximal domains upon the dynamics of the platform domain were decisively different between class II and class I. Both membrane-proximal domains (the alpha2 and beta2 domains) of class II MHC, especially the alpha2 domain, influenced the most important pocket that accommodates a large hydrophobic anchor side chain of the N-terminal side of the bound peptide, though the pocket was not in the alpha2 domain neighborhood. By contrast, the two membrane-proximal domains (the alpha3 and beta2m domains) of class I MHC had little influence upon the most important pocket that accommodates the N-terminal residue of the bound peptide. These results suggest that the two membrane-proximal domains of class II MHC have a greater influence upon peptide-binding than those of class I MHC.

Dynamic interaction among the platform domain and two membrane-proximal immunoglobulin-like domains of class I major histocompatibility complex: normal mode analysis.

Class I major histocompatibility complex (MHC) molecules have three domains, a platform domain and two membrane-proximal immunoglobulin-like domains, an alpha3 domain and a beta2-immunoglobulin (beta2m). To understand the dynamic interactions among the three domains, we simulated the behavior of a partial model deficient in beta2m and another model deficient in the alpha3 domain, by normal mode analysis. As a result, the partial model deficient in beta2m was more flexible in interdomain conformation than the other model. The lowest frequency modes (<2 cm(-1)) observed for the simulations of the partial model deficient in beta2m showed clear interdomain motions as if each domain moved like a rigid body. Such low frequencies and clear interdomain motions were not observed for the simulations of the other model, therefore the interdomain flexibility of the partial model deficient in beta2m may be due to the lowest frequency modes (<2 cm(-1)). These results suggest that beta2m contributes to maintaining the interdomain conformation of class I MHC molecules more than the alpha3 domain does, and may offer convincing evidence to support the notion that the alpha3 domain and beta2m do not have an equal influence on the structural stability of class I MHC molecules.

Bioinformatics based Ligand-Docking and in-silico screening.

We report a novel method, ChooseLD (CHOOse biological information Semi-Empirically on the Ligand Docking), which uses simulated annealing (SA) based on bioinformatics for protein-ligand flexible docking. The fingerprint alignment score (FPAScore) value is used to determine the docking conformation of the ligand. This method includes the matching of chemical descriptors such as fingerprints (FPs) and the root mean square deviation (rmsd) calculation of the coordinates of atoms of the chemical descriptors. Here, the FPAScore optimization for the translation and rotation of a rigid body is performed using the Metropolis Monte Carlo method. Our ChooseLD method will find wide application in the field of biochemistry and medicine to improve the search for new drugs targeting various proteins implicated in diseases.

Fams-ace: a combined method to select the best model after remodeling all server models.

During Critical Assessment of Protein Structure Prediction (CASP7, Pacific Grove, CA, 2006), fams-ace was entered in the 3D coordinate prediction category as a human expert group. The procedure can be summarized by the following three steps. (1) All the server models were refined and rebuilt utilizing our homology modeling method. (2) Representative structures were selected from each server, according to a model quality evaluation, based on a 3D1D profile score (like Verify3D). (3) The top five models were selected and submitted in the order of the consensus-based score (like 3D-Jury). Fams-ace is a fully automated server and does not require human intervention. In this article, we introduce the methodology of fams-ace and discuss the successes and failures of this approach during CASP7. In addition, we discuss possible improvements for the next CASP.

The SKE-DOCK server and human teams based on a combined method of shape complementarity and free energy estimation.

We participated in rounds 6-12 of the critical assessment of predicted interaction (CAPRI) contest as the SKE-DOCK server and human teams. The SKE-DOCK server is based on simple geometry docking and a knowledge base scoring function. The procedure is summarized in the following three steps: (1) protein docking according to shape complementarity, (2) evaluating complex models, and (3) repacking side-chain of models. The SKE-DOCK server did not make use of biological information. On the other hand, the human team tried various intervention approaches. In this article, we describe in detail the processes of the SKE-DOCK server, together with results and reasons for success and failure. Good predicted models were obtained for target 25 by both the SKE-DOCK server and human teams. When the modeled receptor proteins were superimposed on the experimental structures, the smallest Ligand-rmsd values corresponding to the rmsd between the model and experimental structures were 3.307 and 3.324 A, respectively. Moreover, the two teams obtained 4 and 2 acceptable models for target 25. The overall result for both the SKE-DOCK server and human teams was medium accuracy for one (Target 25) out of nine targets.

Topology of AspT, the aspartate:alanine antiporter of Tetragenococcus halophilus, determined by site-directed fluorescence labeling.

The gram-positive lactic acid bacterium Tetragenococcus halophilus catalyzes the decarboxylation of L-aspartate (Asp) with release of L-alanine (Ala) and CO(2). The decarboxylation reaction consists of two steps: electrogenic exchange of Asp for Ala catalyzed by an aspartate:alanine antiporter (AspT) and intracellular decarboxylation of the transported Asp catalyzed by an L-aspartate-beta-decarboxylase (AspD). AspT belongs to the newly classified aspartate:alanine exchanger family (transporter classification no. 2.A.81) of transporters. In this study, we were interested in the relationship between the structure and function of AspT and thus analyzed the topology by means of the substituted-cysteine accessibility method using the impermeant, fluorescent, thiol-specific probe Oregon Green 488 maleimide (OGM) and the impermeant, nonfluorescent, thiol-specific probe [2-(trimethylammonium)ethyl]methanethiosulfonate bromide. We generated 23 single-cysteine variants from a six-histidine-tagged cysteineless AspT template. A cysteine position was assigned an external location if the corresponding single-cysteine variant reacted with OGM added to intact cells, and a position was assigned an internal location if OGM labeling required cell lysis. The topology analyses revealed that AspT has a unique topology; the protein has 10 transmembrane helices (TMs), a large hydrophilic cytoplasmic loop (about 180 amino acids) between TM5 and TM6, N and C termini that face the periplasm, and a positively charged residue (arginine 76) within TM3. Moreover, the three-dimensional structure constructed by means of the full automatic modeling system indicates that the large hydrophilic cytoplasmic loop of AspT possesses a TrkA_C domain and a TrkA_C-like domain and that the three-dimensional structures of these domains are similar to each other even though their amino acid sequences show low similarity.