Detection of common three-dimensional substructures in proteins

Hierarchical Structure of Protein Sequence

Most non-communicable diseases are associated with dysfunction of proteins or protein complexes. The relationship between sequence and structure has been analyzed for a long time, and the analysis of the sequences organization in domains and motifs remains an actual research area. Here, we propose a mathematical method for revealing the hierarchical organization of protein sequences. The method is based on the pentapeptide as a unit of protein sequences. Employing the frequency of occurrence of pentapeptides in sequences of natural proteins and a special mathematical approach, this method revealed a hierarchical structure in the protein sequence. The method was applied to 24,647 non-homologous protein sequences with sizes ranging from 50 to 400 residues from the NRDB90 database. Statistical analysis of the branching points of the graphs revealed 11 characteristic values of y (the width of the inscribed function), showing the relationship of these multiple fragments of the sequences. Several examples illustrate how fragments of the protein spatial structure correspond to the elements of the hierarchical structure of the protein sequence. This methodology provides a promising basis for a mathematically-based classification of the elements of the spatial organization of proteins. Elements of the hierarchical structure of different levels of the hierarchy can be used to solve biotechnological and medical problems.

Motions around conserved helical weak spots facilitate GPCR activation

G protein‐coupled receptors (GPCRs) participate in most physiological processes and are important drug targets in many therapeutic areas. Recently, many GPCR X‐ray structures became available, facilitating detailed studies of their sequence‐structure‐mobility‐function relations. We show that the functional role of many conserved GPCR sequence motifs is to create weak spots in the transmembrane helices that provide the structural plasticity necessary for ligand binding and signaling. Different receptor families use different conserved sequence motifs to obtain similar helix irregularities that allow for the same motions upon GPCR activation. These conserved motions come together to facilitate the timely release of the conserved sodium ion to the cytosol. Most GPCR crystal structures could be determined only after stabilization of the transmembrane helices by mutations that remove weak spots. These mutations often lead to diminished binding of agonists, but not antagonists, which logically agrees with the fact that large helix rearrangements occur only upon agonist binding. Upon activation, six of the seven TM helices in GPCRs undergo helix motions and/or deformations facilitated by weak spots in these helices. The location of these weak spots is much more conserved than the sequence motifs that cause them. Knowledge about these weak spots helps understand the activation process of GPCRs and thus helps design medicines.

G protein-coupled receptors of class A harness the energy of membrane potential to increase their sensitivity and selectivity

The human genome contains about 700 genes of G protein-coupled receptors (GPCRs) of class A; these seven-helical membrane proteins are the targets of almost half of all known drugs. In the middle of the helix bundle, crystal structures reveal a highly conserved sodium-binding site, which is connected with the extracellular side by a water-filled tunnel. This binding site contains a sodium ion in those GPCRs that are crystallized in their inactive conformations but does not in those GPCRs that are trapped in agonist-bound active conformations. The escape route of the sodium ion upon the inactive-to-active transition and its very direction have until now remained obscure. Here, by modeling the available experimental data, we show that the sodium gradient over the cell membrane increases the sensitivity of GPCRs if their activation is thermodynamically coupled to the sodium ion translocation into the cytoplasm but decreases it if the sodium ion retreats into the extracellular space upon receptor activation. The model quantitatively describes the available data on both activation and suppression of distinct GPCRs by membrane voltage. The model also predicts selective amplification of the signal from (endogenous) agonists if only they, but not their (partial) analogs, induce sodium translocation. Comparative structure and sequence analyses of sodium-binding GPCRs indicate a key role for the conserved leucine residue in the second transmembrane helix (Leu2.46) in coupling sodium translocation to receptor activation. Hence, class A GPCRs appear to harness the energy of the transmembrane sodium potential to increase their sensitivity and selectivity.

GPU-Based Point Cloud Superpositioning for Structural Comparisons of Protein Binding Sites

In this paper, we present a novel approach to solve the labeled point cloud superpositioning problem for performing structural comparisons of protein binding sites. The solution is based on a parallel evolution strategy that operates on large populations and runs on GPU hardware. The proposed evolution strategy reduces the likelihood of getting stuck in a local optimum of the multimodal real-valued optimization problem represented by labeled point cloud superpositioning. The performance of the GPU-based parallel evolution strategy is compared to a previously proposed CPU-based sequential approach for labeled point cloud superpositioning, indicating that the GPU-based parallel evolution strategy leads to qualitatively better results and significantly shorter runtimes, with speed improvements of up to a factor of 1,500 for large populations. Binary classification tests based on the ATP, NADH, and FAD protein subsets of CavBase, a database containing putative binding sites, show average classification rate improvements from about 92 percent (CPU) to 96 percent (GPU). Further experiments indicate that the proposed GPU-based labeled point cloud superpositioning approach can be superior to traditional protein comparison approaches based on sequence alignments.

Available Instruments for Analyzing Molecular Dynamics Trajectories

Molecular dynamics trajectories are the result of molecular dynamics simulations. Trajectories are sequential snapshots of simulated molecular system which represents atomic coordinates at specific time periods. Based on the definition, in a text format trajectory files are characterized by their simplicity and uselessness. To obtain information from such files, special programs and information processing techniques are applied: from molecular dynamics animation to finding characteristics along the trajectory (versus time). In this review, we describe different programs for processing molecular dynamics trajectories. The performance of these programs, usefulness for analyses of molecular dynamics trajectories, strong and weak aspects are discussed.

On sufficient statistics of least-squares superposition of vector sets

The problem of superposition of two corresponding vector sets by minimizing their sum-of-squares error under orthogonal transformation is a fundamental task in many areas of science, notably structural molecular biology. This problem can be solved exactly using an algorithm whose time complexity grows linearly with the number of correspondences. This efficient solution has facilitated the widespread use of the superposition task, particularly in studies involving macromolecular structures. This article formally derives a set of sufficient statistics for the least-squares superposition problem. These statistics are additive. This permits a highly efficient (constant time) computation of superpositions (and sufficient statistics) of vector sets that are composed from its constituent vector sets under addition or deletion operation, where the sufficient statistics of the constituent sets are already known (that is, the constituent vector sets have been previously superposed). This results in a drastic improvement in the run time of the methods that commonly superpose vector sets under addition or deletion operations, where previously these operations were carried out ab initio (ignoring the sufficient statistics). We experimentally demonstrate the improvement our work offers in the context of protein structural alignment programs that assemble a reliable structural alignment from well-fitting (substructural) fragment pairs. A C++ library for this task is available online under an open-source license.

Discovery of small molecule CD40-TRAF6 inhibitors

The CD154-CD40 receptor complex plays a pivotal role in several inflammatory pathways. Attempts to inhibit the formation of this complex have resulted in systemic side effects. Downstream inhibition of the CD40 signaling pathway therefore seems a better way to ameliorate inflammatory disease. To relay a signal, the CD40 receptor recruits adapter proteins called tumor necrosis factor receptor-associated factors (TRAFs). CD40-TRAF6 interactions are known to play an essential role in several inflammatory diseases. We used in silico, in vitro, and in vivo experiments to identify and characterize compounds that block CD40-TRAF6 interactions. We present in detail our drug docking and optimization pipeline and show how we used it to find lead compounds that reduce inflammation in models of peritonitis and sepsis. These compounds appear to be good leads for drug development, given the observed absence of side effects and their demonstrated efficacy for peritonitis and sepsis in mouse models.

Alpha-bulges in G protein-coupled receptors

Agonist binding is related to a series of motions in G protein-coupled receptors (GPCRs) that result in the separation of transmembrane helices III and VI at their cytosolic ends and subsequent G protein binding. A large number of smaller motions also seem to be associated with activation. Most helices in GPCRs are highly irregular and often contain kinks, with extensive literature already available about the role of prolines in kink formation and the precise function of these kinks. GPCR transmembrane helices also contain many α-bulges. In this article we aim to draw attention to the role of these α-bulges in ligand and G-protein binding, as well as their role in several aspects of the mobility associated with GPCR activation. This mobility includes regularization and translation of helix III in the extracellular direction, a rotation of the entire helix VI, an inward movement of the helices near the extracellular side, and a concerted motion of the cytosolic ends of the helices that makes their orientation appear more circular and that opens up space for the G protein to bind. In several cases, α-bulges either appear or disappear as part of the activation process.

A quantitative measure for protein conformational heterogeneity

Conformational heterogeneity is a defining characteristic of proteins. Intrinsically disordered proteins (IDPs) and denatured state ensembles are extreme manifestations of this heterogeneity. Inferences regarding globule versus coil formation can be drawn from analysis of polymeric properties such as average size, shape, and density fluctuations. Here we introduce a new parameter to quantify the degree of conformational heterogeneity within an ensemble to complement polymeric descriptors. The design of this parameter is guided by the need to distinguish between systems that couple their unfolding-folding transitions with coil-to-globule transitions and those systems that undergo coil-to-globule transitions with no evidence of acquiring a homogeneous ensemble of conformations upon collapse. The approach is as follows: Each conformation in an ensemble is converted into a conformational vector where the elements are inter-residue distances. Similarity between pairs of conformations is quantified using the projection between the corresponding conformational vectors. An ensemble of conformations yields a distribution of pairwise projections, which is converted into a distribution of pairwise conformational dissimilarities. The first moment of this dissimilarity distribution is normalized against the first moment of the distribution obtained by comparing conformations from the ensemble of interest to conformations drawn from a Flory random coil model. The latter sets an upper bound on conformational heterogeneity thus ensuring that the proposed measure for intra-ensemble heterogeneity is properly calibrated and can be used to compare ensembles for different sequences and across different temperatures. The new measure of conformational heterogeneity will be useful in quantitative studies of coupled folding and binding of IDPs and in de novo sequence design efforts that are geared toward controlling the degree of heterogeneity in unbound forms of IDPs.

OPTIMAL PAIRWISE ALIGNMENT OF FIXED PROTEIN STRUCTURES IN SUBQUADRATIC TIME

The problem of finding an optimal structural alignment for a pair of superimposed proteins is often amenable to the Smith–Waterman dynamic programming algorithm, which runs in time proportional to the product of lengths of the sequences being aligned. While the quadratic running time is acceptable for computing a single alignment of two fixed protein structures, the time complexity becomes a bottleneck when running the Smith–Waterman routine multiple times in order to find a globally optimal superposition and alignment of the input proteins. We present a subquadratic running time algorithm capable of computing an alignment that optimizes one of the most widely used measures of protein structure similarity, defined as the number of pairs of residues in two proteins that can be superimposed under a predefined distance cutoff. The algorithm presented in this article can be used to significantly improve the speed–accuracy tradeoff in a number of popular protein structure alignment methods.

Allostery in the ferredoxin protein motif does not involve a conformational switch

Regulation of protein function via cracking, or local unfolding and refolding of substructures, is becoming a widely recognized mechanism of functional control. Oftentimes, cracking events are localized to secondary and tertiary structure interactions between domains that control the optimal position for catalysis and/or the formation of protein complexes. Small changes in free energy associated with ligand binding, phosphorylation, etc., can tip the balance and provide a regulatory functional switch. However, understanding the factors controlling function in single-domain proteins is still a significant challenge to structural biologists. We investigated the functional landscape of a single-domain plant-type ferredoxin protein and the effect of a distal loop on the electron-transfer center. We find the global stability and structure are minimally perturbed with mutation, whereas the functional properties are altered. Specifically, truncating the L1,2 loop does not lead to large-scale changes in the structure, determined via X-ray crystallography. Further, the overall thermal stability of the protein is only marginally perturbed by the mutation. However, even though the mutation is distal to the iron-sulfur cluster (∼20 Å), it leads to a significant change in the redox potential of the iron-sulfur cluster (57 mV). Structure-based all-atom simulations indicate correlated dynamical changes between the surface-exposed loop and the iron-sulfur cluster-binding region. Our results suggest intrinsic communication channels within the ferredoxin fold, composed of many short-range interactions, lead to the propagation of long-range signals. Accordingly, protein interface interactions that involve L1,2 could potentially signal functional changes in distal regions, similar to what is observed in other allosteric systems.

Algorithms for optimal protein structure alignment

MOTIVATION

Structural alignment is an important tool for understanding the evolutionary relationships between proteins. However, finding the best pairwise structural alignment is difficult, due to the infinite number of possible superpositions of two structures. Unlike the sequence alignment problem, which has a polynomial time solution, the structural alignment problem has not been even classified as solvable.

RESULTS

We study one of the most widely used measures of protein structural similarity, defined as the number of pairs of residues in two proteins that can be superimposed under a predefined distance cutoff. We prove that, for any two proteins, this measure can be optimized for all but finitely many distance cutoffs. Our method leads to a series of algorithms for optimizing other structure similarity measures, including the measures commonly used in protein structure prediction experiments. We also present a polynomial time algorithm for finding a near-optimal superposition of two proteins. Aside from having a relatively low cost, the algorithm for near-optimal solution returns a superposition of provable quality. In other words, the difference between the score of the returned superposition and the score of an optimal superposition can be explicitly computed and used to determine whether the returned superposition is, in fact, the best superposition.

CONTACT

poleksic@cs.uni.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score

BACKGROUND

Protein tertiary structure comparisons are employed in various fields of contemporary structural biology. Most structure comparison methods involve generation of an initial seed alignment, which is extended and/or refined to provide the best structural superposition between a pair of protein structures as assessed by a structure comparison metric. One such metric, the TM-score, was recently introduced to provide a combined structure quality measure of the coordinate root mean square deviation between a pair of structures and coverage. Using the TM-score, the TM-align structure alignment algorithm was developed that was often found to have better accuracy and coverage than the most commonly used structural alignment programs; however, there were a number of situations when this was not true.

RESULTS

To further improve structure alignment quality, the Fr-TM-align algorithm has been developed where aligned fragment pairs are used to generate the initial seed alignments that are then refined using dynamic programming to maximize the TM-score. For the assessment of the structural alignment quality from Fr-TM-align in comparison to other programs such as CE and TM-align, we examined various alignment quality assessment scores such as PSI and TM-score. The assessment showed that the structural alignment quality from Fr-TM-align is better in comparison to both CE and TM-align. On average, the structural alignments generated using Fr-TM-align have a higher TM-score (~9%) and coverage (~7%) in comparison to those generated by TM-align. Fr-TM-align uses an exhaustive procedure to generate initial seed alignments. Hence, the algorithm is computationally more expensive than TM-align.

CONCLUSION

Fr-TM-align, a new algorithm that employs fragment alignment and assembly provides better structural alignments in comparison to TM-align. The source code and executables of Fr-TM-align are freely downloadable at: http://cssb.biology.gatech.edu/skolnick/files/FrTMalign/.

CLePAPS: fast pair alignment of protein structures based on conformational letters

Fast, efficient, and reliable algorithms for pairwise alignment of protein structures are in ever-increasing demand for analyzing the rapidly growing data on protein structures. CLePAPS is a tool developed for this purpose. It distinguishes itself from other existing algorithms by the use of conformational letters, which are discretized states of 3D segmental structural states. A letter corresponds to a cluster of combinations of the three angles formed by Calpha pseudobonds of four contiguous residues. A substitution matrix called CLESUM is available to measure the similarity between any two such letters. CLePAPS regards an aligned fragment pair (AFP) as an ungapped string pair with a high sum of pairwise CLESUM scores. Using CLESUM scores as the similarity measure, CLePAPS searches for AFPs by simple string comparison. The transformation which best superimposes a highly similar AFP can be used to superimpose the structure pairs under comparison. A highly scored AFP which is consistent with several other AFPs determines an initial alignment. CLePAPS then joins consistent AFPs guided by their similarity scores to extend the alignment by several "zoom-in" iteration steps. A follow-up refinement produces the final alignment. CLePAPS does not implement dynamic programming. The utility of CLePAPS is tested on various protein structure pairs.

Prediction of interaction sites from apo 3D structures when the holo conformation is different

The predictability of catalytic and binding sites from apo structures is addressed for proteins that undergo significant conformational change upon binding. Theoretical microscopic titration curves (THEMATICS), an electrostatics-based method for the prediction of functional sites, is performed on a test set of 24 proteins with both apo and holo structures available. For 23 of these 24 proteins (96%), THEMATICS predicts the correct catalytic or binding site for both the apo and holo forms. For only one of the 24 proteins, THEMATICS makes the correct prediction for the holo structure but fails for the apo structure. The metrics used by THEMATICS to identify functional residues generally are larger in absolute value for the functional residues in the holo forms compared to the corresponding residues in the apo forms. However, even in the apo forms, these identifying metrics are still statistically significantly larger for functional residues than for residues not involved in catalysis or binding. This indicates that some of the unusual electrostatic properties of functional residues are preserved in the apo conformation. Evidence is presented that certain residues immediately surrounding the active catalytic and binding residues impart functionally important chemical and electrostatic properties to the active residues. At least parts of these microenvironments exist in the unbound conformations, such that THEMATICS is able to distinguish the functional residues even in the apo structures.

A simple method of identifying symmetric substructures of proteins

Accurate identifications of internal symmetric substructures of proteins are needed in protein evolution study and protein design. To overcome the difficulties met by previous methods, here we propose a simple quantitative one by using a similarity matrix plus Pearson's correlation analysis. The distance root-mean-square deviation (dRMSD) is used to measure the similarity of two substructures in a protein. We applied this method to the proteins of the beta-propeller, jelly roll, and beta-trefoil families and the results show that this method cannot only detect the internal repetitive structures in proteins effectively, but also can identify their locations easily.

Multiple crystal structures of actin dimers and their implications for interactions in the actin filament

Multiple crystal structures are reported of cross-linked actin dimers. Interactions that are conserved across crystal structures suggest detailed interactions that are likely to be present in F-actin filaments.

The structure of actin in its monomeric form is known at high resolution, while the structure of filamentous F-actin is only understood at considerably lower resolution. Knowing pre­cisely how the monomers of actin fit together would lead to a deeper understanding of the dynamic behavior of the actin filament. Here, a series of crystal structures of actin dimers are reported which were prepared by cross-linking in either the longitudinal or the lateral direction in the filament state. Laterally cross-linked dimers, comprised of monomers belonging to different protofilaments, are found to adopt configurations in crystals that are not related to the native structure of filamentous actin. In contrast, multiple structures of longitudinal dimers consistently reveal the same interface between monomers within a single protofilament. The re­appearance of the same longitudinal interface in multiple crystal structures adds weight to arguments that the interface visualized is similar to that in actin filaments. Highly conserved atomic interactions involving residues 199–205 and 287–291 are highlighted.

ProCKSI: a decision support system for Protein (structure) Comparison, Knowledge, Similarity and Information

Background

We introduce the decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information (ProCKSI). ProCKSI integrates various protein similarity measures through an easy to use interface that allows the comparison of multiple proteins simultaneously. It employs the Universal Similarity Metric (USM), the Maximum Contact Map Overlap (MaxCMO) of protein structures and other external methods such as the DaliLite and the TM-align methods, the Combinatorial Extension (CE) of the optimal path, and the FAST Align and Search Tool (FAST). Additionally, ProCKSI allows the user to upload a user-defined similarity matrix supplementing the methods mentioned, and computes a similarity consensus in order to provide a rich, integrated, multicriteria view of large datasets of protein structures.

Results

We present ProCKSI's architecture and workflow describing its intuitive user interface, and show its potential on three distinct test-cases. In the first case, ProCKSI is used to evaluate the results of a previous CASP competition, assessing the similarity of proposed models for given targets where the structures could have a large deviation from one another. To perform this type of comparison reliably, we introduce a new consensus method. The second study deals with the verification of a classification scheme for protein kinases, originally derived by sequence comparison by Hanks and Hunter, but here we use a consensus similarity measure based on structures. In the third experiment using the Rost and Sander dataset (RS126), we investigate how a combination of different sets of similarity measures influences the quality and performance of ProCKSI's new consensus measure. ProCKSI performs well with all three datasets, showing its potential for complex, simultaneous multi-method assessment of structural similarity in large protein datasets. Furthermore, combining different similarity measures is usually more robust than relying on one single, unique measure.

Conclusion

Based on a diverse set of similarity measures, ProCKSI computes a consensus similarity profile for the entire protein set. All results can be clustered, visualised, analysed and easily compared with each other through a simple and intuitive interface.

ProCKSI is publicly available at for academic and non-commercial use.

Amino Acids in the Second Transmembrane Helix of the Lhca4 Subunit Are Important for Formation of Stable Heterodimeric Light-harvesting Complex LHCI-730

Photosynthetic light-harvesting complexes (LHCs) are assembled from apoproteins (Lhc proteins) and non-covalently attached pigments. Despite a considerable amino acid sequence identity, these proteins differ in their oligomerization behavior. To identify the amino acid residues determining the heterodimerization of Lhca1 and Lhca4 to form LHCI-730, we mutated the poorly conserved second transmembrane helix of the two subunits. Mutated genes were expressed in Escherichia coli and the resultant proteins were refolded in vitro and subsequently analyzed by gel electrophoresis. Replacement of the entire second helix in Lhca4 by the one of Lhca3 abolished heterodimerization, whereas it had no effect in Lhca1. Individual replacement of three amino acid clusters in Lhca4 that deviate from the corresponding sequence of Lhca3, demonstrated their contribution to Lhca1-Lhca4 dimerization. Further dissection by mutation of individual amino acid residues in Lhca4 showed the importance of a serine, phenylalanine, and histidine (S88, F95, H99) for LHCI-730 assembly. Alignment of consensus sequences of the Lhc proteins demonstrated that these amino acids are predominantly unique in Lhca4 at the relevant positions. Construction of a homology model based on the high-resolution structure of LHCII and superimposing these models onto the photosystem I structure suggested an orientation of S88, F95, and H99 toward the third transmembrane helix of Lhca1. Since some of the amino acids are too far apart from their nearest neighbors in Lhca1 for a direct interaction, different modes of interaction are discussed. Finally, by quantifying chlorophylls bound to monomeric LHC obtained with the H99 mutant, we identified this amino acid as a further chlorophyll binding site.

The prokaryotic antecedents of the ubiquitin-signaling system and the early evolution of ubiquitin-like beta-grasp domains

A systematic analysis of prokaryotic ubiquitin-related beta-grasp fold proteins provides new insights into the Ubiquitin family functional history.

Background

Ubiquitin (Ub)-mediated signaling is one of the hallmarks of all eukaryotes. Prokaryotic homologs of Ub (ThiS and MoaD) and E1 ligases have been studied in relation to sulfur incorporation reactions in thiamine and molybdenum/tungsten cofactor biosynthesis. However, there is no evidence for entire protein modification systems with Ub-like proteins and deconjugation by deubiquitinating enzymes in prokaryotes. Hence, the evolutionary assembly of the eukaryotic Ub-signaling apparatus remains unclear.

Results

We systematically analyzed prokaryotic Ub-related β-grasp fold proteins using sensitive sequence profile searches and structural analysis. Consequently, we identified novel Ub-related proteins beyond the characterized ThiS, MoaD, TGS, and YukD domains. To understand their functional associations, we sought and recovered several conserved gene neighborhoods and domain architectures. These included novel associations involving diverse sulfur metabolism proteins, siderophore biosynthesis and the gene encoding the transfer mRNA binding protein SmpB, as well as domain fusions between Ub-like domains and PIN-domain related RNAses. Most strikingly, we found conserved gene neighborhoods in phylogenetically diverse bacteria combining genes for JAB domains (the primary de-ubiquitinating isopeptidases of the proteasomal complex), along with E1-like adenylating enzymes and different Ub-related proteins. Further sequence analysis of other conserved genes in these neighborhoods revealed several Ub-conjugating enzyme/E2-ligase related proteins. Genes for an Ub-like protein and a JAB domain peptidase were also found in the tail assembly gene cluster of certain caudate bacteriophages.

Conclusion

These observations imply that members of the Ub family had already formed strong functional associations with E1-like proteins, UBC/E2-related proteins, and JAB peptidases in the bacteria. Several of these Ub-like proteins and the associated protein families are likely to function together in signaling systems just as in eukaryotes.

FAMCS: finding all maximal common substructures in proteins

Finding the common substructures shared by two proteins is considered as one of the central issues in computational biology because of its usefulness in understanding the structure-function relationship and application in drug and vaccine design. In this paper, we propose a novel algorithm called FAMCS (Finding All Maximal Common Substructures) for the common substructure identification problem. Our method works initially at the protein secondary structural element (SSE) level and starts with the identification of all structurally similar SSE pairs. These SSE pairs are then merged into sets using a modified Apriori algorithm, which will test the similarity of various sets of SSE pairs incrementally until all the maximal sets of SSE pairs that deemed to be similar are found. The maximal common substructures of the two proteins will be formed from these maximal sets. A refinement algorithm is also proposed to fine tune the alignment from the SSE level to the residue level. Comparison of FAMCS with other methods on various proteins shows that FAMCS can address all four requirements and infer interesting biological discoveries.

Optimal clustering for detecting near-native conformations in protein docking

Clustering is one of the most powerful tools in computational biology. The conventional wisdom is that events that occur in clusters are probably not random. In protein docking, the underlying principle is that clustering occurs because long-range electrostatic and/or desolvation forces steer the proteins to a low free-energy attractor at the binding region. Something similar occurs in the docking of small molecules, although in this case shorter-range van der Waals forces play a more critical role. Based on the above, we have developed two different clustering strategies to predict docked conformations based on the clustering properties of a uniform sampling of low free-energy protein-protein and protein-small molecule complexes. We report on significant improvements in the automated prediction and discrimination of docked conformations by using the cluster size and consensus as a ranking criterion. We show that the success of clustering depends on identifying the appropriate clustering radius of the system. The clustering radius for protein-protein complexes is consistent with the range of the electrostatics and desolvation free energies (i.e., between 4 and 9 Angstroms); for protein-small molecule docking, the radius is set by van der Waals interactions (i.e., at approximately 2 Angstroms). Without any a priori information, a simple analysis of the histogram of distance separations between the set of docked conformations can evaluate the clustering properties of the data set. Clustering is observed when the histogram is bimodal. Data clustering is optimal if one chooses the clustering radius to be the minimum after the first peak of the bimodal distribution. We show that using this optimal radius further improves the discrimination of near-native complex structures.

The URMS-RMS hybrid algorithm for fast and sensitive local protein structure alignment

We present an efficient and sensitive hybrid algorithm for local structure alignment of a pair of 3D protein structures. The hybrid algorithm employs both the URMS (unit-vector root mean squared) metric and the RMS metric. Our algorithm searches efficiently the transformation space using a fast screening protocol; initial transformations (rotations) are identified using the URMS algorithm. These rotations are then clustered and an RMS-based dynamic programming algorithm is invoked to find the maximal local similarities for representative rotations of the clusters. Statistical significance of the alignments is estimated using a model that accounts for both the score of the match and the RMS. We tested our algorithm over the SCOP classification of protein domains. Our algorithm performs very well; its main advantages are that (1) it combines the advantages of the RMS and the URMS metrics, (2) it searches extensively the transformation space, (3) it detects complex similarities and structural repeats, and (4) its results are symmetric. The software is available for download at biozon.org/ftp/software/urms/.

A method for simultaneous alignment of multiple protein structures

Here, we present MultiProt, a fully automated highly efficient technique to detect multiple structural alignments of protein structures. MultiProt finds the common geometrical cores between input molecules. To date, most methods for multiple alignment start from the pairwise alignment solutions. This may lead to a small overall alignment. In contrast, our method derives multiple alignments from simultaneous superpositions of input molecules. Further, our method does not require that all input molecules participate in the alignment. Actually, it efficiently detects high scoring partial multiple alignments for all possible number of molecules in the input. To demonstrate the power of MultiProt, we provide a number of case studies. First, we demonstrate known multiple alignments of protein structures to illustrate the performance of MultiProt. Next, we present various biological applications. These include: (1) a partial alignment of hinge-bent domains; (2) identification of functional groups of G-proteins; (3) analysis of binding sites; and (4) protein-protein interface alignment. Some applications preserve the sequence order of the residues in the alignment, whereas others are order-independent. It is their residue sequence order-independence that allows application of MultiProt to derive multiple alignments of binding sites and of protein-protein interfaces, making MultiProt an extremely useful structural tool.

A family-based approach reveals the function of residues in the nuclear receptor ligand-binding domain

Literature studies, 3D structure data, and a series of sequence analysis techniques were combined to reveal important residues in the structure and function of the ligand-binding domain of nuclear hormone receptors. A structure-based multiple sequence alignment allowed for the seamless combination of data from many different studies on different receptors into one single functional model. It was recently shown that a combined analysis of sequence entropy and variability can divide residues in five classes; (1) the main function or active site, (2) support for the main function, (3) signal transduction, (4) modulator or ligand binding and (5) the rest. Mutation data extracted from the literature and intermolecular contacts observed in nuclear receptor structures were analyzed in view of this classification and showed that the main function or active site residues of the nuclear receptor ligand-binding domain are involved in cofactor recruitment. Furthermore, the sequence entropy-variability analysis identified the presence of signal transduction residues that are located between the ligand, cofactor and dimer sites, suggesting communication between these regulatory binding sites. Experimental and computational results agreed well for most residues for which mutation data and intermolecular contact data were available. This allows us to predict the role of the residues for which no functional data is available yet. This study illustrates the power of family-based approaches towards the analysis of protein function, and it points out the problems and possibilities presented by the massive amounts of data that are becoming available in the "omics era". The results shed light on the nuclear receptor family that is involved in processes ranging from cancer to infertility, and that is one of the more important targets in the pharmaceutical industry.

Approximate protein structural alignment in polynomial time

Alignment of protein structures is a fundamental task in computational molecular biology. Good structural alignments can help detect distant evolutionary relationships that are hard or impossible to discern from protein sequences alone. Here, we study the structural alignment problem as a family of optimization problems and develop an approximate polynomial-time algorithm to solve them. For a commonly used scoring function, the algorithm runs in O(n(10)/epsilon(6)) time, for globular protein of length n, and it detects alignments that score within an additive error of epsilon from all optima. Thus, we prove that this task is computationally feasible, although the method that we introduce is too slow to be a useful everyday tool. We argue that such approximate solutions are, in fact, of greater interest than exact ones because of the noisy nature of experimentally determined protein coordinates. The measurement of similarity between a pair of protein structures used by our algorithm involves the Euclidean distance between the structures (appropriately rigidly transformed). We show that an alternative approach, which relies on internal distance matrices, must incorporate sophisticated geometric ingredients if it is to guarantee optimality and run in polynomial time. We use these observations to visualize the scoring function for several real instances of the problem. Our investigations yield insights on the computational complexity of protein alignment under various scoring functions. These insights can be used in the design of scoring functions for which the optimum can be approximated efficiently and perhaps in the development of efficient algorithms for the multiple structural alignment problem.

A structural study for the optimisation of functional motifs encoded in protein sequences

Background

A large number of PROSITE patterns select false positives and/or miss known true positives. It is possible that – at least in some cases – the weak specificity and/or sensitivity of a pattern is due to the fact that one, or maybe more, functional and/or structural key residues are not represented in the pattern. Multiple sequence alignments are commonly used to build functional sequence patterns. If residues structurally conserved in proteins sharing a function cannot be aligned in a multiple sequence alignment, they are likely to be missed in a standard pattern construction procedure.

Results

Here we present a new procedure aimed at improving the sensitivity and/ or specificity of poorly-performing patterns. The procedure can be summarised as follows: 1. residues structurally conserved in different proteins, that are true positives for a pattern, are identified by means of a computational technique and by visual inspection. 2. the sequence positions of the structurally conserved residues falling outside the pattern are used to build extended sequence patterns. 3. the extended patterns are optimised on the SWISS-PROT database for their sensitivity and specificity. The method was applied to eight PROSITE patterns. Whenever structurally conserved residues are found in the surface region close to the pattern (seven out of eight cases), the addition of information inferred from structural analysis is shown to improve pattern selectivity and in some cases selectivity and sensitivity as well. In some of the cases considered the procedure allowed the identification of functionally interesting residues, whose biological role is also discussed.

Conclusion

Our method can be applied to any type of functional motif or pattern (not only PROSITE ones) which is not able to select all and only the true positive hits and for which at least two true positive structures are available. The computational technique for the identification of structurally conserved residues is already available on request and will be soon accessible on our web server. The procedure is intended for the use of pattern database curators and of scientists interested in a specific protein family for which no specific or selective patterns are yet available.

Solution NMR structure and backbone dynamics of the PsaE subunit of photosystem I from Synechocystis sp. PCC 6803

PsaE is a small peripheral subunit of photosystem I (PSI) that is very accessible to the surrounding medium. It plays an essential role in optimizing the interactions with the soluble electron acceptors of PSI, ferredoxin and flavodoxin. The solution structure of PsaE from the cyanobacterium Synechocystis sp. PCC 6803 has been investigated by NMR with a special emphasis on its protein dynamic properties. PsaE is characterized by a well-defined central core that consists of a five-stranded beta-sheet (+1, +1, +1, -4x). Four loops (designated the A-B, B-C, C-D, and D-E loops) connect these beta-strands, the overall resulting structure being that of an SH3-like domain. As compared to previously determined PsaE structures, conformational differences are observed in the first three loops. The flexibility of the loops was investigated using (15)N relaxation experiments. This flexibility is small in amplitude for the A-B and B-C loops, but is large for the C-D loop, particularly in the region corresponding to the missing sequence of Nostoc sp. PCC 8009. The plasticity of the connecting loops in the free subunit is compared to that when bound to the PSI and discussed in relation to the insertion process and the function(s) of PsaE.

A new method to detect related function among proteins independent of sequence and fold homology

A new method has been developed to detect functional relationships among proteins independent of a given sequence or fold homology. It is based on the idea that protein function is intimately related to the recognition and subsequent response to the binding of a substrate or an endogenous ligand in a well-characterized binding pocket. Thus, recognition of similar ligands, supposedly linked to similar function, requires conserved recognition features exposed in terms of common physicochemical interaction properties via the functional groups of the residues flanking a particular binding cavity. Following a technique commonly used in the comparison of small molecule ligands, generic pseudocenters coding for possible interaction properties were assigned for a large sample set of cavities extracted from the entire PDB and stored in the database Cavbase. Using a particular query cavity a series of related cavities of decreasing similarity is detected based on a clique detection algorithm. The detected similarity is ranked according to property-based surface patches shared in common by the different clique solutions. The approach either retrieves protein cavities accommodating the same (e.g. co-factors) or closely related ligands or it extracts proteins exhibiting similar function in terms of a related catalytic mechanism. Finally the new method has strong potential to suggest alternative molecular skeletons in de novo design. The retrieval of molecular building blocks accommodated in a particular sub-pocket that shares similarity with the pocket in a protein studied by drug design can inspire the discovery of novel ligands.

Comparing protein structures: a Gaussian-based approach to the three-dimensional structural similarity of proteins

This study describes a new method for comparing three-dimensional protein structures based on an optimal alignment of their steric fields. The method is based upon the use of spherical Gaussian functions located on individual atoms. This representation generates a flexible description of the underlying fold geometry of proteins that can be adjusted by changing the 'width' of the Gaussians. Reducing the width sharpens the representation and leads to a more 'atomlike' description; increasing the width creates a fuzzier representation that preserves the general shape features of the chain fold but with a consequent loss in atomic resolution. The width used in this study is based upon the features of individual atoms and provides a representation that is quite robust with respect to the variety of geometric features typically encountered in the alignment process. In addition, a post-alignment analysis is performed that generates sequence alignments from the corresponding structure alignments. An example, based on five mammalian and fungal matrix metalloproteinase crystal structures (human fibroblast collagenase, neutrophil collagenase, stromelysin, astacin, and adamalysin), illustrates a number of features of the Gaussian-based approach.