Database algorithm for generating protein backbone and side-chain co-ordinates from a C alpha trace application to model building and detection of co-ordinate errors

CASP6 assessment of contact prediction

Here we present the evaluation results of the Critical Assessment of Protein Structure Prediction (CASP6) contact prediction category. Contact prediction was assessed with standard measures well known in the field and the performance of specialist groups was evaluated alongside groups that submitted models with 3D coordinates. The evaluation was mainly focused on long range contact predictions for the set of new fold targets, although we analyzed predictions for all targets. Three groups with similar levels of accuracy and coverage performed a little better than the others. Comparisons of the predictions of the three best methods with those of CASP5/CAFASP3 suggested some improvement, although there were not enough targets in the comparisons to make this statistically significant.

Mutations in embryonic myosin heavy chain (MYH3) cause Freeman-Sheldon syndrome and Sheldon-Hall syndrome

The genetic basis of most conditions characterized by congenital contractures is largely unknown. Here we show that mutations in the embryonic myosin heavy chain (MYH3) gene cause Freeman-Sheldon syndrome (FSS), one of the most severe multiple congenital contracture (that is, arthrogryposis) syndromes, and nearly one-third of all cases of Sheldon-Hall syndrome (SHS), the most common distal arthrogryposis. FSS and SHS mutations affect different myosin residues, demonstrating that MYH3 genotype is predictive of phenotype. A structure-function analysis shows that nearly all of the MYH3 mutations are predicted to interfere with myosin's catalytic activity. These results add to the growing body of evidence showing that congenital contractures are a shared outcome of prenatal defects in myofiber force production. Elucidation of the genetic basis of these syndromes redefines congenital contractures as unique defects of the sarcomere and provides insights about what has heretofore been a poorly understood group of disorders.

A method for finding candidate conformations for molecular replacement using relative rotation between domains of a known structure

This paper presents a methodology to obtain candidate conformations of multidomain proteins for use in molecular replacement. For each separate domain, the orientational relationship between the template and the target structure is obtained using standard molecular replacement. The orientational relationships of the domains are then used to calculate the relative rotation between the domains in the target conformation by using pose-estimation techniques from the field of robotics and computer vision. With the angle of relative rotation between the domains as a cost function, iterative normal-mode analysis is used to drive the template structure to a candidate conformation that matches the X-ray crystallographic data obtained for the target conformation. The selection of the correct intra-protein domain orientations from among the many spurious maxima in the rotation function (including orientations obtained from domains in symmetry mates rather than within the same copy of the protein) presents a challenge. This problem is resolved by checking R factors of each domain, measuring the absolute value of relative rotation between domains, and evaluating the cost value after each candidate conformation is driven to convergence with iterative NMA. As a validation, the proposed method is applied to three test proteins: ribose-binding protein, lactoferrin and calcium ATPase. In each test case, the orientation and translation of the final candidate conformation in the unit cell are generated correctly from the suggested procedure. The results show that the proposed method can yield viable candidate conformations for use in molecular replacement and can reveal the structural details and pose of the target conformation in the crystallographic unit cell.

In silico strategies for modeling membrane transporter function

Transporter proteins facilitate the transfer of solutes across the cell membrane and have an intricate role in drug absorption, distribution and excretion. Because of their substrate promiscuity, several transporters represent viable pharmacological targets for enhancing drug absorption, preventing drug toxicity or facilitating localized tissue delivery. However, the slow emergence of high-resolution structures for these proteins has hampered the intelligent design of transporter substrates. Nonetheless, currently available functional, as well as structural, data provide an attractive scaffold for generating fusion models that merge substrate-based SARs and protein-based homology structures. The resultant models offer features that extend single modality paradigms in predictive function.

Light Harvesting in Photosystem I Supercomplexes,

In photosynthetic membranes of cyanobacteria, algae, and higher plants, photosystem I (PSI) mediates light-driven transmembrane electron transfer from plastocyanin or cytochrome c6 to the ferredoxin-NADP complex. The oxidoreductase function of PSI is sensitized by a reversible photooxidation of primary electron donor P700, which launches a multistep electron transfer via a series of redox cofactors of the reaction center (RC). The excitation energy for the functioning of the primary electron donor in the RC is delivered via the chlorophyll core antenna in the complex with peripheral light-harvesting antennas. Supermolecular complexes of the PSI acquire remarkably different structural forms of the peripheral light-harvesting antenna complexes, including distinct pigment types and organizational principles. The PSI core antenna, being the main functional unit of the supercomplexes, provides an increased functional connectivity in the chlorophyll antenna network due to dense pigment packing resulting in a fast spread of the excitation among the neighbors. Functional connectivity within the network as well as the spectral overlap of antenna pigments allows equilibration of the excitation energy in the depth of the whole membrane within picoseconds and loss-free delivery of the excitation to primary donor P700 within 20-40 ps. Low-light-adapted cyanobacteria under iron-deficiency conditions extend this capacity via assembly of efficiently energy coupled rings of CP43-like complexes around the PSI trimers. In green algae and higher plants, less efficient energy coupling in the eukaryotic PSI-LHCI supercomplexes is probably a result of the structural adaptation of the Chl a/b binding LHCI peripheral antenna that not only extends the absorption cross section of the PSI core but participates in regulation of excitation flows between the two photosystems as well as in photoprotection.

Determining relevant features to recognize electron density patterns in x-ray protein crystallography

High-throughput computational methods in X-ray protein crystallography are indispensable to meet the goals of structural genomics. In particular, automated interpretation of electron density maps, especially those at mediocre resolution, can significantly speed up the protein structure determination process. TEXTAL(TM) is a software application that uses pattern recognition, case-based reasoning and nearest neighbor learning to produce reasonably refined molecular models, even with average quality data. In this work, we discuss a key issue to enable fast and accurate interpretation of typically noisy electron density data: what features should be used to characterize the density patterns, and how relevant are they? We discuss the challenges of constructing features in this domain, and describe SLIDER, an algorithm to determine the weights of these features. SLIDER searches a space of weights using ranking of matching patterns (relative to mismatching ones) as its evaluation function. Exhaustive search being intractable, SLIDER adopts a greedy approach that judiciously restricts the search space only to weight values that cause the ranking of good matches to change. We show that SLIDER contributes significantly in finding the similarity between density patterns, and discuss the sensitivity of feature relevance to the underlying similarity metric.

Refinement of protein cores and protein–peptide interfaces using a potential scaling approach

Refinement of side chain conformations in protein model structures and at the interface of predicted protein-protein or protein-peptide complexes is an important step during protein structural modelling and docking. A common approach for side chain prediction is to assume a rigid protein main chain for both docking partners and search for an optimal set of side chain rotamers to optimize the steric fit. However, depending on the target-template similarity in the case of comparative protein modelling and on the accuracy of an initially docked complex, the main chain template structure is only an approximation of a realistic target main chain. An inaccurate rigid main chain conformation can in turn interfere with the prediction of side chain conformations. In the present study, a potential scaling approach (PS-MD) during a molecular dynamics (MD) simulation that also allows the inclusion of explicit solvent has been used to predict side chain conformations on semi-flexible protein main chains. The PS-MD method converges much faster to realistic protein-peptide interface structures or protein core structures than standard MD simulations. Depending on the accuracy of the protein main chain, it also gives significantly better results compared with the standard rotamer search method.

Backbone solution structures of proteins using residual dipolar couplings: application to a novel structural genomics target

Structural genomics (or proteomics) activities are critically dependent on the availability of high-throughput structure determination methodology. Development of such methodology has been a particular challenge for NMR based structure determination because of the demands for isotopic labeling of proteins and the requirements for very long data acquisition times. We present here a methodology that gains efficiency from a focus on determination of backbone structures of proteins as opposed to full structures with all sidechains in place. This focus is appropriate given the presumption that many protein structures in the future will be built using computational methods that start from representative fold family structures and replace as many as 70% of the sidechains in the course of structure determination. The methodology we present is based primarily on residual dipolar couplings (RDCs), readily accessible NMR observables that constrain the orientation of backbone fragments irrespective of separation in space. A new software tool is described for the assembly of backbone fragments under RDC constraints and an application to a structural genomics target is presented. The target is an 8.7 kDa protein from Pyrococcus furiosus, PF1061, that was previously not well annotated, and had a nearest structurally characterized neighbor with only 33% sequence identity. The structure produced shows structural similarity to this sequence homologue, but also shows similarity to other proteins, which suggests a functional role in sulfur transfer. Given the backbone structure and a possible functional link this should be an ideal target for development of modeling methods.

Structure prediction of a multi-domain EF-hand Ca2+ binding protein by PROPAINOR

PROPAINOR is a new algorithm developed for ab initio prediction of the 3D structures of proteins using knowledge-based nonparametric multivariate statistical methods. This algorithm is found to be most efficient in terms of computational simplicity and prediction accuracy for single-domain proteins as compared to other ab initio methods. In this paper, we have used the algorithm for the atomic structure prediction of a multi-domain (two-domain) calcium-binding protein, whose solution structure has been deposited in the PDB recently (PDB ID: 1JFK). We have studied the sensitivity of the predicted structure to NMR distance restraints with their incorporation as an additional input. Further, we have compared the predicted structures in both these cases with the NMR derived solution structure reported earlier. We have also validated the refined structure for proper stereochemistry and favorable packing environment with good results and elucidated the role of the central linker.

SCRATCH: a protein structure and structural feature prediction server

SCRATCH is a server for predicting protein tertiary structure and structural features. The SCRATCH software suite includes predictors for secondary structure, relative solvent accessibility, disordered regions, domains, disulfide bridges, single mutation stability, residue contacts versus average, individual residue contacts and tertiary structure. The user simply provides an amino acid sequence and selects the desired predictions, then submits to the server. Results are emailed to the user. The server is available at .

EVAcon: a protein contact prediction evaluation service

Here we introduce EVAcon, an automated web service that evaluates the performance of contact prediction servers. Currently, EVAcon is monitoring nine servers, four of which are specialized in contact prediction and five are general structure prediction servers. Results are compared for all newly determined experimental structures deposited into PDB (∼5–50 per week). EVAcon allows for a precise comparison of the results based on a system of common protein subsets and the commonly accepted evaluation criteria that are also used in the corresponding category of the CASP assessment. EVAcon is a new service added to the functionality of the EVA system for the continuous evaluation of protein structure prediction servers. The new service is accesible from any of the three EVA mirrors: PDG (CNB-CSIC, Madrid) (); CUBIC (Columbia University, NYC) (); and Sali Lab (UCSF, San Francisco) ().

Formation of Native and Non-native Interactions in Ensembles of Denatured ACBP Molecules from Paramagnetic Relaxation Enhancement Studies

Paramagnetic relaxation enhancement measurements in the denatured state of ACBP have provided distance restraints that have been used in computer simulations to determine the conformational ensembles representing the denatured states of ACBP under a variety of conditions. A detailed comparison of the residual structure in the denatured state of ACBP under these different conditions has enabled us to infer that regions in the N and C-terminal parts of the protein sequence have a high tendency to interact in the unfolded state under physiological conditions. By comparing the structural features in the denatured states with those in the transition state for folding we also provided new insights into the mechanism of formation of the native state of this protein.

Oligomerization of Hantavirus N protein: C-terminal alpha-helices interact to form a shared hydrophobic space

The structure of the nucleocapsid protein of bunyaviruses has not been defined. Earlier we have shown that Tula hantavirus N protein oligomerization is dependent on the C-terminal domains. Of them, the helix-loop-helix motif was found to be an essential structure. Computer modeling predicted that oligomerization occurs via helix protrusions, and the shared hydrophobic space formed by amino acids residues 380-IILLF-384 in the first helix and 413-LI-414 in the second helix is responsible for stabilizing the interaction. The model was validated by two approaches. First, analysis of the oligomerization capacity of the N protein mutants performed with the mammalian two-hybrid system showed that both preservation of the helix structure and formation of the shared hydrophobic space are crucial for the interaction. Second, oligomerization was shown to be a prerequisite for the granular pattern of transiently expressed N protein in transfected cells. N protein trimerization was supported by three-dimensional reconstruction of the N protein by electron microscopy after negative staining. Finally, we discuss how N protein trimerization could occur.

Structure of human POT1 bound to telomeric single-stranded DNA provides a model for chromosome end-protection

The POT1 (protection of telomeres 1) protein binds the single-stranded overhang at the ends of chromosomes in diverse eukaryotes. It is essential for chromosome end-protection in the fission yeast Schizosaccharomyces pombe, and it is involved in regulation of telomere length in human cells. Here, we report the crystal structure at a resolution of 1.73 A of the N-terminal half of human POT1 (hPOT1) protein bound to a telomeric single-stranded DNA (ssDNA) decamer, TTAGGGTTAG, the minimum tight-binding sequence indicated by in vitro binding assays. The structure reveals that hPOT1 contains two oligonucleotide/ oligosaccharide-binding (OB) folds; the N-terminal OB fold binds the first six nucleotides, resembling the structure of the S. pombe Pot1pN-ssDNA complex, whereas the second OB fold binds and protects the 3' end of the ssDNA. These results provide an atomic-resolution model for chromosome end-capping.

Solving and analyzing side-chain positioning problems using linear and integer programming

MOTIVATION

Side-chain positioning is a central component of homology modeling and protein design. In a common formulation of the problem, the backbone is fixed, side-chain conformations come from a rotamer library, and a pairwise energy function is optimized. It is NP-complete to find even a reasonable approximate solution to this problem. We seek to put this hardness result into practical context.

RESULTS

We present an integer linear programming (ILP) formulation of side-chain positioning that allows us to tackle large problem sizes. We relax the integrality constraint to give a polynomial-time linear programming (LP) heuristic. We apply LP to position side chains on native and homologous backbones and to choose side chains for protein design. Surprisingly, when positioning side chains on native and homologous backbones, optimal solutions using a simple, biologically relevant energy function can usually be found using LP. On the other hand, the design problem often cannot be solved using LP directly; however, optimal solutions for large instances can still be found using the computationally more expensive ILP procedure. While different energy functions also affect the difficulty of the problem, the LP/ILP approach is able to find optimal solutions. Our analysis is the first large-scale demonstration that LP-based approaches are highly effective in finding optimal (and successive near-optimal) solutions for the side-chain positioning problem.

Rational engineering of enzyme stability

During the past 15 years there has been a continuous flow of reports describing proteins stabilized by the introduction of mutations. These reports span a period from pioneering rational design work on small enzymes such as T4 lysozyme and barnase to protein design, and directed evolution. Concomitantly, the purification and characterization of naturally occurring hyperstable proteins has added to our understanding of protein stability. Along the way, many strategies for rational protein stabilization have been proposed, some of which (e.g. entropic stabilization by introduction of prolines or disulfide bridges) have reasonable success rates. On the other hand, comparative studies and efforts in directed evolution have revealed that there are many mutational strategies that lead to high stability, some of which are not easy to define and rationalize. Recent developments in the field include increasing awareness of the importance of the protein surface for stability, as well as the notion that normally a very limited number of mutations can yield a large increase in stability. Another development concerns the notion that there is a fundamental difference between the "laboratory stability" of small pure proteins that unfold reversibly and completely at high temperatures and "industrial stability", which is usually governed by partial unfolding processes followed by some kind of irreversible inactivation process (e.g. aggregation). Provided that one has sufficient knowledge of the mechanism of thermal inactivation, successful and efficient rational stabilization of enzymes can be achieved.

Improved side-chain prediction accuracy using an ab initio potential energy function and a very large rotamer library

Accurate prediction of the placement and comformations of protein side chains given only the backbone trace has a wide range of uses in protein design, structure prediction, and functional analysis. Prediction has most often relied on discrete rotamer libraries so that rapid fitness of side-chain rotamers can be assessed against some scoring function. Scoring functions are generally based on experimental parameters from small-molecule studies or empirical parameters based on determined protein structures. Here, we describe the NCN algorithm for predicting the placement of side chains. A predominantly first-principles approach was taken to develop the potential energy function incorporating van der Waals and electrostatics based on the OPLS parameters, and a hydrogen bonding term. The only empirical knowledge used is the frequency of rotameric states from the PDB. The rotamer library includes nearly 50,000 rotamers, and is the most extensive discrete library used to date. Although the computational time tends to be longer than most other algorithms, the overall accuracy exceeds all algorithms in the literature when placing rotamers on an accurate backbone trace. Considering only the most buried residues, 80% of the total residues tested, the placement accuracy reaches 92% for chi(1), and 83% for chi(1 + 2), and an overall RMS deviation of 1 A. Additionally, we show that if information is available to restrict chi(1) to one rotamer well, then this algorithm can generate structures with an average RMS deviation of 1.0 A for all heavy side-chains atoms and a corresponding overall chi(1 + 2) accuracy of 85.0%.

Determination of an ensemble of structures representing the denatured state of the bovine acyl-coenzyme a binding protein

The denatured state of a protein contains important information about the determinants of the folding process. By combining site-directed spin-labeling NMR experiments and restrained computer simulations, we have determined ensembles of conformations that represent the denatured state of the bovine acyl-coenzyme A binding protein (ACBP) at three different concentrations of guanidine hydrochloride. As the experimentally determined distance information corresponds to weighted averages over a broad ensemble of structures, we applied the experimental restraints to a system of noninteracting replicas of the protein by using a Monte Carlo sampling scheme. This procedure permits us to sample ensembles of conformations that are compatible with the experimental data and thus to obtain information regarding the distribution of structures in the denatured state. Our results show that the denatured state of ACBP is highly heterogeneous. The high sensitivity of the computational method that we present, however, enabled us to identify long-range interactions between two regions, located near the N- and C-termini, that include both native and non-native elements. The preferential formation of these contacts suggests that the sequence-dependent patterns of helical propensity and hydrophobicity are important determinants of the structure in the denatured state of ACBP.

CAFASP3 in the spotlight of EVA

We have analysed fold recognition, secondary structure and contact prediction servers from CAFASP3. This assessment was carried out in the framework of the fully automated, web-based evaluation server EVA. Detailed results are available at http://cubic.bioc.columbia.edu/eva/cafasp3/. We observed that the sequence-unique targets from CAFASP3/CASP5 were not fully representative for evaluating performance. For all three categories, we showed how careless ranking might be misleading. We compared methods from all categories to experts in secondary structure and contact prediction and homology modellers to fold recognisers. While the secondary structure experts clearly outperformed all others, the contact experts appeared to outperform only novel fold methods. Automatic evaluation servers are good at getting statistics right and at using these to discard misleading ranking schemes. We challenge that to let machines rule where they are best might be the best way for the community to enjoy the tremendous benefit of CASP as a unique opportunity for brainstorming.

Addition of side chains to a known backbone with defined side-chain centroids

An automatic procedure is proposed for adding side chains to a protein backbone; it is based on optimization of a simplified energy function for peptide side chains, given its backbone and positions of side-chain centroids. The energy is expressed as a sum of the energies of interaction between side chains, and a harmonic penalty function accounting for the preservation of the positions of the C(alpha) atoms and the side-chain centroids. The energy of side-chain interactions is calculated with the soft-sphere ECEPP/3 potential. A Monte Carlo search is carried out to explore all possible side-chain orientations within a fixed backbone and side-chain centroid positions. The initial, usually extended, side-chain conformations are taken directly from the ECEPP/3 database. The procedure was tested on six experimental (X-ray or NMR) structures: immunoglobulin binding protein (PDB code 1IGD, an alpha+beta-protein); transcription factor PML (PDB code 1BOR, a 49-104 fragment of the ring finger domain, predominantly beta-protein); bovine pancreatic trypsin inhibitor (crystal form II) (PDB code 1BPI, an alpha+beta-protein); the monomer of human deoxyhemoglobin (PDB code 1BZ0, an alpha-helical structure); chain A of alcohol dehydrogenase from Drosophila lebanonensis (PDB code 1A4U); as well as on the 10-55 portion of the B domain of staphylococcal protein A (PDB code 1BDD). In all cases except 1BPI, the data for the algorithm (i.e. the backbone or C(alpha) coordinates and the positions of side-chain centroids) were taken from the experimental structures. For protein A, the C(alpha) coordinates and positions of side-chain centroids were also taken from the 1.9-A-resolution model predicted by the UNRES force field. In all comparisons with experimental structures, complete side-chain geometry was reconstructed with a root-mean-square (RMS) deviation of approximately 0.6-0.9 A from the heavy atoms when complete backbone and side-chain-centroid coordinates were used in reconstruction, or approximately 1.0 A when the C(alpha) and centroid coordinates were used.

Structures and relative free energies of partially folded states of proteins

The ability of proteins to fold to well defined compact structures is one of the most remarkable examples of the effect of natural selection on biological molecules. To understand their properties, including the stability, the mechanism of folding, and the possibilities of misfolding and association, it is necessary to know the protein free energy landscape. We use NMR data as restraints in a Monte Carlo sampling procedure to determine the ensemble of structures populated by human alpha-lactalbumin in the presence of increasing concentrations of urea. The ensembles of structures that represent the partially folded states of the protein show that two structural cores, corresponding to portions of the alpha and beta domains of the native protein, are preserved even when the native-like interactions that define their existence are substantially weakened. Analysis of the network of residual contacts reveals the presence of a complex interface region between the two structural cores and indicates that the development of specific interactions within this interface is the key step in achieving the native structure. The relative probabilities of the conformations determined from the NMR data are used to construct a coarse-grained free energy landscape for alpha-lactalbumin in the absence of urea. The form of the landscape, together with the existence of distinct cores, supports the concept that robustness and modularity are the properties that make possible the folding of complex proteins.

Crystal structure of the Citrobacter freundii dihydroxyacetone kinase reveals an eight-stranded alpha-helical barrel ATP-binding domain

Dihydroxyacetone kinases are a sequence-conserved family of enzymes, which utilize two different phosphoryldonors, ATP in animals, plants and some bacteria, and a multiphosphoprotein of the phosphoenolpyruvate carbohydrate phosphotransferase system in bacteria. Here we report the 2.5-A crystal structure of the homodimeric Citrobacter freundii dihydroxyacetone kinase complex with an ATP analogue and dihydroxyacetone. The N-terminal domain consists of two alpha/beta-folds with a molecule of dihydroxyacetone covalently bound in hemiaminal linkage to the N epsilon 2 of His-220. The C-terminal domain consists of a regular eight-helix alpha-barrel. The eight helices form a deep pocket, which includes a tightly bound phospholipid. Only the lipid headgroup protrudes from the surface. The nucleotide is bound on the top of the barrel across from the entrance to the lipid pocket. The phosphate groups are coordinated by two Mg2+ ions to gamma-carboxyl groups of aspartyl residues. The ATP binding site does not contain positively charged or aromatic groups. Paralogues of dihydroxyacetone kinase also occur in association with transcription regulators and proteins of unknown function pointing to biological roles beyond triose metabolism.

Discrete restraint-based protein modeling and the Calpha-trace problem

We present a novel de novo method to generate protein models from sparse, discretized restraints on the conformation of the main chain and side chain atoms. We focus on Calpha-trace generation, the problem of constructing an accurate and complete model from approximate knowledge of the positions of the Calpha atoms and, in some cases, the side chain centroids. Spatial restraints on the Calpha atoms and side chain centroids are supplemented by constraints on main chain geometry, phi/xi angles, rotameric side chain conformations, and inter-atomic separations derived from analyses of known protein structures. A novel conformational search algorithm, combining features of tree-search and genetic algorithms, generates models consistent with these restraints by propensity-weighted dihedral angle sampling. Models with ideal geometry, good phi/xi angles, and no inter-atomic overlaps are produced with 0.8 A main chain and, with side chain centroid restraints, 1.0 A all-atom root-mean-square deviation (RMSD) from the crystal structure over a diverse set of target proteins. The mean model derived from 50 independently generated models is closer to the crystal structure than any individual model, with 0.5 A main chain RMSD under only Calpha restraints and 0.7 A all-atom RMSD under both Calpha and centroid restraints. The method is insensitive to randomly distributed errors of up to 4 A in the Calpha restraints. The conformational search algorithm is efficient, with computational cost increasing linearly with protein size. Issues relating to decoy set generation, experimental structure determination, efficiency of conformational sampling, and homology modeling are discussed.

A graph-theory algorithm for rapid protein side-chain prediction

Fast and accurate side-chain conformation prediction is important for homology modeling, ab initio protein structure prediction, and protein design applications. Many methods have been presented, although only a few computer programs are publicly available. The SCWRL program is one such method and is widely used because of its speed, accuracy, and ease of use. A new algorithm for SCWRL is presented that uses results from graph theory to solve the combinatorial problem encountered in the side-chain prediction problem. In this method, side chains are represented as vertices in an undirected graph. Any two residues that have rotamers with nonzero interaction energies are considered to have an edge in the graph. The resulting graph can be partitioned into connected subgraphs with no edges between them. These subgraphs can in turn be broken into biconnected components, which are graphs that cannot be disconnected by removal of a single vertex. The combinatorial problem is reduced to finding the minimum energy of these small biconnected components and combining the results to identify the global minimum energy conformation. This algorithm is able to complete predictions on a set of 180 proteins with 34342 side chains in <7 min of computer time. The total chi(1) and chi(1 + 2) dihedral angle accuracies are 82.6% and 73.7% using a simple energy function based on the backbone-dependent rotamer library and a linear repulsive steric energy. The new algorithm will allow for use of SCWRL in more demanding applications such as sequence design and ab initio structure prediction, as well addition of a more complex energy function and conformational flexibility, leading to increased accuracy.

Specific binding of dehydroepiandrosterone to the N terminus of the microtubule-associated protein MAP2

The effect of neurosteroids is mediated through their membrane or nuclear receptors. However, no dehydroepiandrosterone (DHEA)-specific receptors have been evidenced so far in the brain. In this paper, we showed by isothermal titration calorimetry that the DHEA specifically binds to the dendritic brain microtubule-associated protein MAP2C with an association constant of 2.7 x 10(7) m-1 and at a molar ratio of 1:1. By partial tryptic digestions and mass spectrometry analysis, we found that the binding involved the N-terminal region of MAP2C. Interestingly, MAP2C displays homologies with 17 beta-hydroxysteroid dehydrogenase 1, an enzyme required for estrogen synthesis. Based on these sequence homologies and on the x-ray structure of the DHEA-binding pocket of 17 beta-hydroxysteroid dehydrogenase 1, we modeled the complex of DHEA with MAP2C. The binding of DHEA to MAP2C involved specific hydrogen bonds that orient the steroid into the pocket. This work suggests that DHEA can directly influence brain plasticity via MAP2C binding. It opens interesting ways for understanding the role of DHEA in the brain.

A mechanism of covalent substrate binding in the x-ray structure of subunit K of the Escherichia coli dihydroxyacetone kinase

Dihydroxyacetone (Dha) kinases are homologous proteins that use different phosphoryl donors, a multiphosphoryl protein of the phosphoenolpyruvate-dependent carbohydrate:phosphotransferase system in bacteria, ATP in animals, plants, and some bacteria. The Dha kinase of Escherichia coli consists of three subunits, DhaK and DhaL, which are colinear to the ATP-dependent Dha kinases of eukaryotes, and the multiphosphoryl protein DhaM. Here we show the crystal structure of the DhaK subunit in complex with Dha at 1.75 A resolution. DhaK is a homodimer with a fold consisting of two six-stranded mixed beta-sheets surrounded by nine alpha-helices and a beta-ribbon covering the exposed edge strand of one sheet. The core of the N-terminal domain has an alpha/beta fold common to subunits of carbohydrate transporters and transcription regulators of the phosphoenolpyruvate-dependent carbohydrate:phosphotransferase system. The core of the C-terminal domain has a fold similar to the C-terminal domain of the cell-division protein FtsZ. A molecule of Dha is covalently bound in hemiaminal linkage to the N epsilon 2 of His-230. The hemiaminal does not participate in covalent catalysis but is the chemical basis for discrimination between short-chain carbonyl compounds and polyols. Paralogs of Dha kinases occur in association with transcription regulators of the TetR/QacR and the SorC families, pointing to their biological role as sensors in signaling.

Extending the structure of an ABC transporter to atomic resolution: modeling and simulation studies of MsbA

Molecular modeling and simulation approaches have been use to generate a complete model of the prokaryotic ABC transporter MsbA from Escherichia coli, starting from the low-resolution structure-based Calpha trace (PDB code 1JSQ). MsbA is of some biomedical interest as it is homologous to mammalian transporters such as P-glycoprotein and TAP. The quality of the MsbA model is assessed using a combination of molecular dynamics simulations and static structural analysis. These results suggest that the approach adopted for MsbA may be of general utility for generating all atom models from low-resolution crystal structures of membrane proteins. Molecular dynamics simulations of the MsbA model inserted in a fully solvated octane slab (a membrane mimetic environment) reveal that while the monomer is relatively stable, the dimer is unstable and undergoes significant conformational drift on a nanosecond time scale. This suggests that the MsbA crystal dimer may not correspond to the MsbA dimer in vivo. An alternative model of the dimer is discussed in the context of available experimental data.

Ab initio construction of polypeptide fragments: efficient generation of accurate, representative ensembles

We describe a novel method to generate ensembles of conformations of the main-chain atoms [N, C(alpha), C, O, Cbeta] for a sequence of amino acids within the context of a fixed protein framework. Each conformation satisfies fundamental stereo-chemical restraints such as idealized geometry, favorable phi/psi angles, and excluded volume. The ensembles include conformations both near and far from the native structure. Algorithms for effective conformational sampling and constant time overlap detection permit the generation of thousands of distinct conformations in minutes. Unlike previous approaches, our method samples dihedral angles from fine-grained phi/psi state sets, which we demonstrate is superior to exhaustive enumeration from coarse phi/psi sets. Applied to a large set of loop structures, our method samples consistently near-native conformations, averaging 0.4, 1.1, and 2.2 A main-chain root-mean-square deviations for four, eight, and twelve residue long loops, respectively. The ensembles make ideal decoy sets to assess the discriminatory power of a selection method. Using these decoy sets, we conclude that quality of anchor geometry cannot reliably identify near-native conformations, though the selection results are comparable to previous loop prediction methods. In a subsequent study (de Bakker et al.: Proteins 2003;51:21-40), we demonstrate that the AMBER forcefield with the Generalized Born solvation model identifies near-native conformations significantly better than previous methods.

Crystal structure of ribosomal protein L30e from the extreme thermophile Thermococcus celer: thermal stability and RNA binding

We report here the high-resolution crystal structure of the ribosomal protein L30e from the hyperthermophilic archaeon Thermococcus celer determined at cryo-temperature. When it is compared with its mesophilic homologue, L30e from yeast, a number of structural features that can enhance thermostability are revealed. Disordered residues corresponding to a large RNA-binding loop in yeast L30e are well structured in the T. celer protein. The overall charge of T. celer L30e is near neutral, whereas that of the yeast homologue is highly positive. This is the result of an increase in the number of acidic residues at the expense of polar residues, Asn, Ser, and Thr. Extensive ion pair networks are found on the molecular surface. Exposed nonpolar surface areas are reduced in the T. celer protein. Its side chain atoms preferably form hydrogen bonds with main chain atoms. Taken together, these factors contribute to high protein stability. The roles of well-conserved L30e residues are studied and found to be important in defining a very compact overall structure and in maintaining the structure of the RNA binding site. By comparing it with the yeast homologue, we also identified the residues that are responsible for RNA binding and built a model to illustrate how L30e binds to an RNA kink turn motif.

Efficient conformational sampling of local side-chain flexibility

Side-chain flexibility of ligand-binding sites needs to be considered in the rational design of novel inhibitors. We have developed a method to generate conformational ensembles that efficiently sample local side-chain flexibility from a single crystal structure. The rotamer-based approach is tested here for the S1' pocket of human collagenase-1 (MMP-1), which is known to undergo conformational changes in multiple side-chains upon binding of certain inhibitors. First, a raw ensemble consisting of a large number of conformers of the S1' pocket was generated using an exhaustive search of rotamer combinations on a template crystal structure. A combination of principal component analysis and fuzzy clustering was then employed to successfully identify a core ensemble consisting of a low number of representatives from the raw ensemble. The core ensemble contained geometrically diverse conformers of stable nature, as indicated in several cases by a relative energy lower than that of the minimised template crystal structure. Through comparisons with X-ray crystallography and NMR structural data we show that the core ensemble occupied a conformational space similar to that observed under experimental conditions. The synthetic inhibitor RS-104966 is known to induce a conformational change in the side-chains of the S1' pocket of MMP-1 and could not be docked in the template crystal structure. However, the experimental binding mode was reproduced successfully using members of the core ensemble as the docking target, establishing the usefulness of the method in drug design.

A short regulatory domain restricts glycerol transport through yeast Fps1p

The controlled export of solutes is crucial for cellular adaptation to hypotonic conditions. In the yeast Saccharomyces cerevisiae glycerol export is mediated by Fps1p, a member of the major intrinsic protein (MIP) family of channel proteins. Here we describe a short regulatory domain that restricts glycerol transport through Fps1p. This domain is required for retention of cellular glycerol under hypertonic stress and hence acquisition of osmotolerance. It is located in the N-terminal cytoplasmic extension close to the first transmembrane domain. Several residues within that domain and its precise position are critical for channel control while the proximal residues 13-215 of the N-terminal extension are not required. The sequence of the regulatory domain and its position are perfectly conserved in orthologs from other yeast species. The regulatory domain has an amphiphilic character, and structural predictions indicate that it could fold back into the membrane bilayer. Remarkably, this domain has structural similarity to the channel forming loops B and E of Fps1p and other glycerol facilitators. Intragenic second-site suppressor mutations of the sensitivity to high osmolarity conferred by truncation of the regulatory domain caused diminished glycerol transport, confirming that elevated channel activity is the cause of the osmosensitive phenotype.

Beyond the rotamer library: genetic algorithm combined with the disturbing mutation process for upbuilding protein side-chains

The disturbing genetic algorithm, incorporating the disturbing mutation process into the genetic algorithm flow, has been developed to extend the searching space of side-chain conformations and to improve the quality of the rotamer library. Moreover, the growing generation amount idea, simulating the real situation of the natural evolution, is introduced to improve the searching speed. In the calculations using the pseudo energy scoring function of the root mean squared deviation, the disturbing genetic algorithm method has been shown to be highly efficient. With the real energy function based on AMBER force field, the program has been applied to rebuilding side-chain conformations of 25 high-quality crystallographic structures of single-protein and protein-protein complexes. The averaged root mean standard deviation of atom coordinates in side-chains and veracities of the torsion angles of chi(1) and chi(1) + chi(2) are 1.165 A, 88.2 and 72.9% for the buried residues, respectively, and 1.493 A, 79.2 and 64.7% for all residues, showing that the method has equal precision to the program SCWRL, whereas it performs better in the prediction of buried residues and protein-protein interfaces. This method has been successfully used in redesigning the interface of the Basnase-Barstar complex, indicating that it will have extensive application in protein design, protein sequence and structure relationship studies, and research on protein-protein interaction.

Peptide backbone reconstruction using dead-end elimination and a knowledge-based forcefield

A novel, yet simple and automated, protocol for reconstruction of complete peptide backbones from C(alpha) coordinates only is described, validated, and benchmarked. The described method collates a set of possible backbone conformations for each set of residue triads from a structural library derived from the PDB. The optimal permutation of these three residue segments of backbone conformations is determined using the dead-end elimination (DEE) algorithm. Putative conformations are evaluated using a pairwise-additive knowledge-based forcefield term and a fragment overlap term. The protocol described in this report is able to restore the full backbone coordinates to within 0.2-0.6 A of the actual crystal structure from C(alpha) coordinates only. In addition, it is insensitive to errors in the input C(alpha) coordinates with RMSDs of 3.0 A, and this is illustrated through application to deliberately distorted C(alpha) traces. The entire process, as described, is rapid, requiring of the order of a few minutes for a typical protein on a typical desktop PC. Approximations enable this to be reduced to a few seconds, although this is at the expense of prediction accuracy. This compares very favorably to previously published methods, being sufficiently fast for general use and being one of the most accurate methods. Because the method is not restricted to the reconstruction from only C(alpha) coordinates, reconstruction based on C(beta) coordinates is also demonstrated.

The European Bioinformatics Institute's data resources

As the amount of biological data grows, so does the need for biologists to store and access this information in central repositories in a free and unambiguous manner. The European Bioinformatics Institute (EBI) hosts six core databases, which store information on DNA sequences (EMBL-Bank), protein sequences (SWISS-PROT and TrEMBL), protein structure (MSD), whole genomes (Ensembl) and gene expression (ArrayExpress). But just as a cell would be useless if it couldn't transcribe DNA or translate RNA, our resources would be compromised if each existed in isolation. We have therefore developed a range of tools that not only facilitate the deposition and retrieval of biological information, but also allow users to carry out searches that reflect the interconnectedness of biological information. The EBI's databases and tools are all available on our website at www.ebi.ac.uk.

An efficient method for reconstructing protein backbones from alpha-carbon coordinates

We present an approach for building protein backbones from alpha-carbon (Calpha) coordinates. The approach is analytical and based on the information of favored regions in the Ramachandran map. The backbone construction consists of three parts: prediction of (phi, psi) angle pairs from the Calpha trace, generation of atomic coordinates with these (phi, psi) angles, and refinement by subsequent energy minimization. Tests on several known protein structures show that the root mean square deviations in reconstructed backbones are 0.25-0.48 A for coordinates and 14-34 degrees for phi and psi angles. The results indicate that our method is one of the best methods proposed in terms of accuracy. It has also been revealed that the approach is not only robust against errors in Calpha coordinates but is also capable of providing equivalent or more reasonable models compared to other known methods. Furthermore, backbone structures were found to be built accurately by using the (phi, psi) angles from a different structure of the same protein. This suggests that the approach could be effective and useful in homology modeling studies.

BRCA2 function in DNA binding and recombination from a BRCA2-DSS1-ssDNA structure

Mutations in the BRCA2 (breast cancer susceptibility gene 2) tumor suppressor lead to chromosomal instability due to defects in the repair of double-strand DNA breaks (DSBs) by homologous recombination, but BRCA2's role in this process has been unclear. Here, we present the 3.1 angstrom crystal structure of a approximately 90-kilodalton BRCA2 domain bound to DSS1, which reveals three oligonucleotide-binding (OB) folds and a helix-turn-helix (HTH) motif. We also (i) demonstrate that this BRCA2 domain binds single-stranded DNA, (ii) present its 3.5 angstrom structure bound to oligo(dT)9, (iii) provide data that implicate the HTH motif in dsDNA binding, and (iv) show that BRCA2 stimulates RAD51-mediated recombination in vitro. These findings establish that BRCA2 functions directly in homologous recombination and provide a structural and biochemical basis for understanding the loss of recombination-mediated DSB repair in BRCA2-associated cancers.

Ab initio protein structure prediction via a combination of threading, lattice folding, clustering, and structure refinement

A combination of sequence comparison, threading, lattice, and off-lattice Monte Carlo (MC) simulations and clustering of MC trajectories was used to predict the structure of all (but one) targets of the CASP4 experiment on protein structure prediction. Although this method is automated and is operationally the same regardless of the level of uniqueness of the query proteins, here we focus on the more difficult targets at the border of the fold recognition and new fold categories. For a few targets (T0110 is probably the best example), the ab initio method produced more accurate models than models obtained by the fold recognition techniques. For the most difficult targets from the new fold categories, substantial fragments of structures have been correctly predicted. Possible improvements of the method are briefly discussed.

Core side-chain packing and backbone conformation in Lpp-56 coiled-coil mutants

Native proteins exhibit precise geometric packing of atoms in their hydrophobic interiors. Nonetheless, controversy remains about the role of core side-chain packing in specifying and stabilizing the folded structures of proteins. Here we investigate the role of core packing in determining the conformation and stability of the Lpp-56 trimerization domain. The X-ray crystal structures of Lpp-56 mutants with alanine substitutions at two and four interior core positions reveal trimeric coiled coils in which the twist of individual helices and the helix-helix spacing vary significantly to achieve the most favored superhelical packing arrangement. Introduction of each alanine "layer" into the hydrophobic core destabilizes the superhelix by 1.4 kcal mol(-1). Although the methyl groups of the alanine residues pack at their optimum van der Waals contacts in the coiled-coil trimer, they provide a smaller component of hydrophobic interactions than bulky hydrophobic side-chains to the thermodynamic stability. Thus, specific side-chain packing in the hydrophobic core of coiled coils are important determinants of protein main-chain conformation and stability.

Energy-based reconstruction of a protein backbone from its alpha-carbon trace by a Monte-Carlo method

An automatic procedure is proposed for reconstruction of a protein backbone from its C(alpha)-trace; it is based on optimization of a simplified energy function of a peptide backbone, given its alpha-carbon trace. The energy is expressed as a sum of the energies of interaction between backbone peptide groups that are not neighbors in the sequence, the energies of local interactions within all amino acid residues, and a harmonic penalty function accounting for the conservation of standard bond angles. The energy of peptide group interactions is calculated using the assumption that each peptide group acts as a point dipole. For local interaction energy, use is made of a two-dimensional Fourier series expansion of the energies of model terminally blocked amino acid residues, calculated with the Empirical Conformational Energy Program for Peptides (ECEPP/3) force field in the angles lambda((1)) and lambda((2)) defining the rotation of peptide groups adjacent to a C(alpha) carbon atom about the corresponding C(alpha) em leader C(alpha) virtual-bond axes. To explore all possible rotations of peptide groups within a fixed C(alpha)-trace, a Monte Carlo search is carried out. The initial lambda angles are calculated by aligning the dipoles of the peptide groups that are close in space, subject to the condition of favorable local interactions. After the Monte Carlo search is accomplished with the simplified energy function, the energy of the structure is minimized with the ECEPP/3 force field, with imposition of distance constraints corresponding to the initial C(alpha)-trace geometry. The procedure was tested on model alpha-helices and beta-sheets, as well as on the crystal structure of the immunoglobulin binding protein (PDB code: 1IGD, an alpha/beta protein). In all cases, complete backbone geometry was reconstructed with a root-mean-square (rms) deviation of 0.5 A from the all-atom target structure.

Ab initio protein structure prediction

Steady progress has been made in the field of ab initio protein folding. A variety of methods now allow the prediction of low-resolution structures of small proteins or protein fragments up to approximately 100 amino acid residues in length. Such low-resolution structures may be sufficient for the functional annotation of protein sequences on a genome-wide scale. Although no consistently reliable algorithm is currently available, the essential challenges to developing a general theory or approach to protein structure prediction are better understood. The energy landscapes resulting from the structure prediction algorithms are only partially funneled to the native state of the protein. This review focuses on two areas of recent advances in ab initio structure prediction-improvements in the energy functions and strategies to search the caldera region of the energy landscapes.

Side-chain modeling with an optimized scoring function

Modeling side-chain conformations on a fixed protein backbone has a wide application in structure prediction and molecular design. Each effort in this field requires decisions about a rotamer set, scoring function, and search strategy. We have developed a new and simple scoring function, which operates on side-chain rotamers and consists of the following energy terms: contact surface, volume overlap, backbone dependency, electrostatic interactions, and desolvation energy. The weights of these energy terms were optimized to achieve the minimal average root mean square (rms) deviation between the lowest energy rotamer and real side-chain conformation on a training set of high-resolution protein structures. In the course of optimization, for every residue, its side chain was replaced by varying rotamers, whereas conformations for all other residues were kept as they appeared in the crystal structure. We obtained prediction accuracy of 90.4% for chi(1), 78.3% for chi(1 + 2), and 1.18 A overall rms deviation. Furthermore, the derived scoring function combined with a Monte Carlo search algorithm was used to place all side chains onto a protein backbone simultaneously. The average prediction accuracy was 87.9% for chi(1), 73.2% for chi(1 + 2), and 1.34 A rms deviation for 30 protein structures. Our approach was compared with available side-chain construction methods and showed improvement over the best among them: 4.4% for chi(1), 4.7% for chi(1 + 2), and 0.21 A for rms deviation. We hypothesize that the scoring function instead of the search strategy is the main obstacle in side-chain modeling. Additionally, we show that a more detailed rotamer library is expected to increase chi(1 + 2) prediction accuracy but may have little effect on chi(1) prediction accuracy.