Prediction of protein loop geometries in solution

The ability to determine the structure of a protein in solution is a critical tool for structural biology, as proteins in their native state are found in aqueous environments. Using a physical chemistry based prediction protocol, we demonstrate the ability to reproduce protein loop geometries in experimentally derived solution structures. Predictions were run on loops drawn from (1)NMR entries in the Protein Databank (PDB), and from (2) the RECOORD database in which NMR entries from the PDB have been standardized and re-refined in explicit solvent. The predicted structures are validated by comparison with experimental distance restraints, a test of structural quality as defined by the WHAT IF structure validation program, root mean square deviation (RMSD) of the predicted loops to the original structural models, and comparison of precision of the original and predicted ensembles. Results show that for the RECOORD ensembles, the predicted loops are consistent with an average of 95%, 91%, and 87% of experimental restraints for the short, medium and long loops respectively. Prediction accuracy is strongly affected by the quality of the original models, with increases in the percentage of experimental restraints violated of 2% for the short loops, and 9% for both the medium and long loops in the PDB derived ensembles. We anticipate the application of our protocol to theoretical modeling of protein structures, such as fold recognition methods; as well as to experimental determination of protein structures, or segments, for which only sparse NMR restraint data is available.     

Automated method for modeling seven-helix transmembrane receptors from experimental data.

A rule-based automated method is presented for modeling the structures of the seven transmembrane helices of G-protein-coupled receptors. The structures are generated by using a simulated annealing Monte Carlo procedure that positions and orients rigid helices to satisfy structural restraints. The restraints are derived from analysis of experimental information from biophysical studies on native and mutant proteins, from analysis of the sequences of related proteins, and from theoretical considerations of protein structure. Calculations are presented for two systems. The method was validated through calculations using appropriate experimental information for bacteriorhodopsin, which produced a model structure with a root mean square (rms) deviation of 1.87 A from the structure determined by electron microscopy. Calculations are also presented using experimental and theoretical information available for bovine rhodopsin to assign the helices to a projection density map and to produce a model of bovine rhodopsin that can be used as a template for modeling other G-protein-coupled receptors.     

TOUCHSTONE II: a new approach to ab initio protein structure prediction

We have developed a new combined approach for ab initio protein structure prediction. The protein conformation is described as a lattice chain connecting C(alpha) atoms, with attached C(beta) atoms and side-chain centers of mass. The model force field includes various short-range and long-range knowledge-based potentials derived from a statistical analysis of the regularities of protein structures. The combination of these energy terms is optimized through the maximization of correlation for 30 x 60,000 decoys between the root mean square deviation (RMSD) to native and energies, as well as the energy gap between native and the decoy ensemble. To accelerate the conformational search, a newly developed parallel hyperbolic sampling algorithm with a composite movement set is used in the Monte Carlo simulation processes. We exploit this strategy to successfully fold 41/100 small proteins (36 approximately 120 residues) with predicted structures having a RMSD from native below 6.5 A in the top five cluster centroids. To fold larger-size proteins as well as to improve the folding yield of small proteins, we incorporate into the basic force field side-chain contact predictions from our threading program PROSPECTOR where homologous proteins were excluded from the data base. With these threading-based restraints, the program can fold 83/125 test proteins (36 approximately 174 residues) with structures having a RMSD to native below 6.5 A in the top five cluster centroids. This shows the significant improvement of folding by using predicted tertiary restraints, especially when the accuracy of side-chain contact prediction is >20%. For native fold selection, we introduce quantities dependent on the cluster density and the combination of energy and free energy, which show a higher discriminative power to select the native structure than the previously used cluster energy or cluster size, and which can be used in native structure identification in blind simulations. These procedures are readily automated and are being implemented on a genomic scale.     

Strategy for supplementing structure calculations using limited data with hydrophobic distance restraints

Introductory biochemistry texts often note that the fold of a protein is completely defined when the dihedral angles phi and psi are known for each amino acid. This assertion was examined with torsion angle dynamics and simulated annealing (TAD/SA) calculations of protein G using only dihedral angle restraints. When all dihedral angles were restrained to within 1 degrees of the values of the X-ray structure, the TAD/SA structures gave a backbone root mean square deviation to the target of 4 A. Factors that contributed to divergence from the correct solution include deviations of peptide bonds from planarity, internal conflicts resulting from the nonuniform energies of different phi, psi combinations, and relaxation to extended conformations in the absence of long-range constraints. Simulations including hydrogen-bond restraints showed that even a few long-range contacts constrain the fold better than a complete set of accurate dihedral restraints. A procedure is described for TAD/SA calculations using hydrogen-bond restraints, idealized dihedral restraints for residues in regular secondary structures, and "hydrophobic distance restraints" derived from the positions of hydrophobic residues in the amino acid sequence. The hydrogen-bond restraints are treated as inviolable, whereas violated hydrophobic restraints are removed following reduction of restraint upper bounds from 2 to 1 times the predicted radius of gyration. The strategy was tested with simulated restraints from X-ray structures of proteins from different fold classes and NMR data for cold shock protein A that included only backbone chemical shifts and hydrogen bonds obtained from a long-range HNCO experiment.     

Solution-state structure by NMR of zinc-substituted rubredoxin from the marine hyperthermophilic archaebacterium Pyrococcus furiosus.

The three-dimensional solution-state structure is reported for the zinc-substituted form of rubredoxin (Rd) from the marine hyperthermophilic archaebacterium Pyrococcus furiosus, an organism that grows optimally at 100 degrees C. Structures were generated with DSPACE by a hybrid distance geometry (DG)-based simulated annealing (SA) approach that employed 403 nuclear Overhauser effect (NOE)-derived interproton distance restraints, including 67 interresidue, 124 sequential (i-j = 1), 75 medium-range (i-j = 2-5), and 137 long-range (i-j > 5) restraints. All lower interproton distance bounds were set at the sum of the van Der Waals radii (1.8 A), and upper bounds of 2.7 A, 3.3 A, and 5.0 A were employed to represent qualitatively observed strong, medium, and weak NOE cross peak intensities, respectively. Twenty-three backbone-backbone, six backbone-sulfur (Cys), two backbone-side chain, and two side chain-side chain hydrogen bond restraints were include for structure refinement, yielding a total of 436 nonbonded restraints, which averages to > 16 restraints per residue. A total of 10 structures generated from random atom positions and 30 structures generated by molecular replacement using the backbone coordinates of Clostridium pasteurianum Rd converged to a common conformation, with the average penalty (= sum of the square of the distance bounds violations; +/- standard deviation) of 0.024 +/- 0.003 A2 and a maximum total penalty of 0.035 A2. Superposition of the backbone atoms (C, C alpha, N) of residues A1-L51 for all 40 structures afforded an average pairwise root mean square (rms) deviation value (+/- SD) of 0.42 +/- 0.07 A. Superposition of all heavy atoms for residues A1-L51, including those of structurally undefined external side chains, afforded an average pairwise rms deviation of 0.72 +/- 0.08 A. Qualitative comparison of back-calculated and experimental two-dimensional NOESY spectra indicate that the DG/SA structures are consistent with the experimental spectra. The global folding of P. furiosus Zn(Rd) is remarkably similar to the folding observed by X-ray crystallography for native Rd from the mesophilic organism C. pasteurianum, with the average rms deviation value for backbone atoms of residues A1-L51 of P. furiosus Zn(Rd) superposed with respect to residues K2-V52 of C. pasteurianum Rd of 0.77 +/- 0.06 A. The conformations of aromatic residues that compose the hydrophobic cores of the two proteins are also similar. However, P. furiosus Rd contains several unique structural elements, including at least four additional hydrogen bonds and three potential electrostatic interactions.(ABSTRACT TRUNCATED AT 400 WORDS)     

RECOORD: a recalculated coordinate database of 500+ proteins from the PDB using restraints from the BioMagResBank

State-of-the-art methods based on CNS and CYANA were used to recalculate the nuclear magnetic resonance (NMR) solution structures of 500+ proteins for which coordinates and NMR restraints are available from the Protein Data Bank. Curated restraints were obtained from the BioMagResBank FRED database. Although the original NMR structures were determined by various methods, they all were recalculated by CNS and CYANA and refined subsequently by restrained molecular dynamics (CNS) in a hydrated environment. We present an extensive analysis of the results, in terms of various quality indicators generated by PROCHECK and WHAT_CHECK. On average, the quality indicators for packing and Ramachandran appearance moved one standard deviation closer to the mean of the reference database. The structural quality of the recalculated structures is discussed in relation to various parameters, including number of restraints per residue, NOE completeness and positional root mean square deviation (RMSD). Correlations between pairs of these quality indicators were generally low; for example, there is a weak correlation between the number of restraints per residue and the Ramachandran appearance according to WHAT_CHECK (r = 0.31). The set of recalculated coordinates constitutes a unified database of protein structures in which potential user- and software-dependent biases have been kept as small as possible. The database can be used by the structural biology community for further development of calculation protocols, validation tools, structure-based statistical approaches and modeling. The RECOORD database of recalculated structures is publicly available from http://www.ebi.ac.uk/msd/recoord.     

Improvement of comparative modeling by the application of conserved motifs amongst distantly related proteins as additional restraints

Protein comparative modeling has useful applications in large-scale structural initiatives and in rational design of drug targets in medicinal chemistry. The reliability of a homology model is dependent on the sequence identity between the query and the structural homologue used as a template for modeling. Here, we present a method for the utilization and conservation of important structural features of template structures by providing additional spatial restraints in comparative modeling programs like MODELLER. We show that root mean square deviation at C(alpha) positions between the model and the corresponding experimental structure and the quality of the models can be significantly improved for distantly related systems by utilizing additional spatial restraints of the template structures. We demonstrate the influence of such approaches to homology modeling during distant relationships in understanding functional properties of protein such as ligand binding using cytochrome P450 as an example.     

Solution structure of the DNA binding domain of AraC protein

We report the solution structure of the DNA binding domain of the Escherichia coli regulatory protein AraC determined in the absence of DNA. The 20 lowest energy structures, determined on the basis of 1507 unambiguous nuclear Overhauser restraints and 180 angle restraints, are well resolved with a pair wise backbone root mean square deviation of 0.7 Å. The protein, free of DNA, is well folded in solution and contains seven helices arranged in two semi‐independent sub domains, each containing one helix‐turn‐helix DNA binding motif, joined by a 19 residue central helix. This solution structure is discussed in the context of extensive biochemical and physiological data on AraC and with respect to the DNA‐bound structures of the MarA and Rob homologs. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Improving fragment quality for de novo structure prediction

De novo structure prediction can be defined as a search in conformational space under the guidance of an energy function. The most successful de novo structure prediction methods, such as Rosetta, assemble the fragments from known structures to reduce the search space. Therefore, the fragment quality is an important factor in structure prediction. In our study, a method is proposed to generate a new set of fragments from the lowest energy de novo models. These fragments were subsequently used to predict the next‐round of models. In a benchmark of 30 proteins, the new set of fragments showed better performance when used to predict de novo structures. The lowest energy model predicted using our method was closer to native structure than Rosetta for 22 proteins. Following a similar trend, the best model among top five lowest energy models predicted using our method was closer to native structure than Rosetta for 20 proteins. In addition, our experiment showed that the C‐alpha root mean square deviation was improved from 5.99 to 5.03 Å on average compared to Rosetta when the lowest energy models were picked as the best predicted models. Proteins 2014; 82:2240–2252. © 2014 Wiley Periodicals, Inc.     

Ab initio folding simulation of Trpcage by replica exchange with hybrid Hamiltonian

Replica-exchange molecular dynamics simulations with hybrid Hamiltonian in explicit solvent were performed to study the folding of a designed 20-residue miniprotein, Trpcage, from a fully extended structure. During the simulations several folding/unfolding events happened. In the folded states the majority of experimentally observed NMR NOE restraints are satisfied. The folded structures have root mean squared deviation of 2.0 A with respect to the NMR structures considering all heavy atoms. The free-energy surface constructed by the hybrid Hamiltonian simulations is similar to the one built by a standard replica-exchange simulation which started from the native structure. Consistent with previous experimental observation, a pre-existing hydrophobic collapse in the unfolded state is detected by investigating the desolvation behavior of Trpcage. At room temperature, an intermediate state featured by a misfolded core, a nearly formed alpha-helix segment and an absence of 3(10)-helix is found. The replica exchange with hybrid Hamiltonian method is shown here to be capable of resolving the folding picture of the miniprotein.     

Separating true positive predicted residue contacts from false positive ones in mainly alpha proteins, using constrained Metropolis MC simulations

We present a method that significantly improves the accuracy of predicted proximal residue pairs in protein molecules. Computational methods for predicting pairs of amino acids that are distant in the protein sequence but close in the protein 3D structure can benefit attempts to in silico recognize the fold of a protein molecule. Unfortunately, currently available methods suffer from low predictive accuracy. In this work, we use Monte Carlo simulations to fold protein molecules with proximal pair predictions used as additional energy constraints. To test our methods, we study molecules with known tertiary structures. With Monte Carlo, we generate ensembles of structures for each set of residues constraints. The distribution of the root mean square deviation of the folded structures from the known native structure reveals clear information about the accuracy of the constraint sets used. With recursive substitutions of constraints, false positive predictions are identified and filtered out and significant improvements in accuracy are observed.     

Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact restraints

To improve tertiary structure predictions of more difficult targets, the next generation of TASSER, TASSER_2.0, has been developed. TASSER_2.0 incorporates more accurate side-chain contact restraint predictions from a new approach, the composite-sequence method, based on consensus restraints generated by an improved threading algorithm, PROSPECTOR_3.5, which uses computationally evolved and wild-type template sequences as input. TASSER_2.0 was tested on a large-scale, benchmark set of 2591 nonhomologous, single domain proteins ≤200 residues that cover the Protein Data Bank at 35% pairwise sequence identity. Compared with the average fraction of accurately predicted side-chain contacts of 0.37 using PROSPECTOR_3.5 with wild-type template sequences, the average accuracy of the composite-sequence method increases to 0.60. The resulting TASSER_2.0 models are closer to their native structures, with an average root mean-square deviation of 4.99 Å compared to the 5.31 Å result of TASSER. Defining a successful prediction as a model with a root mean-square deviation to native <6.5 Å, the success rate of TASSER_2.0 (TASSER) for Medium targets (targets with good templates/poor alignments) is 74.3% (64.7%) and 40.8% (35.5%) for the Hard targets (incorrect templates/alignments). For Easy targets (good templates/alignments), the success rate slightly increases from 86.3% to 88.4%.     

Assembly of protein structure from sparse experimental data: An efficient Monte Carlo model

A new, efficient method for the assembly of protein tertiary structure from known, loosely encoded secondary structure restraints and sparse information about exact side chain contacts is proposed and evaluated. The method is based on a new, very simple method for the reduced modeling of protein structure and dynamics, where the protein is described as a lattice chain connecting side chain centers of mass rather than Cαs. The model has implicit built-in multibody correlations that simulate short- and long-range packing preferences, hydrogen bonding cooperativity and a mean force potential describing hydrophobic interactions. Due to the simplicity of the protein representation and definition of the model force field, the Monte Carlo algorithm is at least an order of magnitude faster than previously published Monte Carlo algorithms for structure assembly. In contrast to existing algorithms, the new method requires a smaller number of tertiary restraints for successful fold assembly; on average, one for every seven residues as compared to one for every four residues. For example, for smaller proteins such as the B domain of protein G, the resulting structures have a coordinate root mean square deviation (cRMSD), which is about 3 Å from the experimental structure; for myoglobin, structures whose backbone cRMSD is 4.3 Å are produced, and for a 247-residue TIM barrel, the cRMSD of the resulting folds is about 6 Å. As would be expected, increasing the number of tertiary restraints improves the accuracy of the assembled structures. The reliability and robustness of the new method should enable its routine application in model building protocols based on various (very sparse) experimentally derived structural restraints. Proteins 32:475–494, 1998. © 1998 Wiley-Liss, Inc.     

Application of statistical potentials to protein structure refinement from low resolution ab initio models

Recently ab initio protein structure prediction methods have advanced sufficiently so that they often assemble the correct low resolution structure of the protein. To enhance the speed of conformational search, many ab initio prediction programs adopt a reduced protein representation. However, for drug design purposes, better quality structures are probably needed. To achieve this refinement, it is natural to use a more detailed heavy atom representation. Here, as opposed to costly implicit or explicit solvent molecular dynamics simulations, knowledge-based heavy atom pair potentials were employed. By way of illustration, we tried to improve the quality of the predicted structures obtained from the ab initio prediction program TOUCHSTONE by three methods: local constraint refinement, reduced predicted tertiary contact refinement, and statistical pair potential guided molecular dynamics. Sixty-seven predicted structures from 30 small proteins (less than 150 residues in length) representing different structural classes (alpha, beta, alpha;/beta) were examined. In 33 cases, the root mean square deviation (RMSD) from native structures improved by more than 0.3 A; in 19 cases, the improvement was more than 0.5 A, and sometimes as large as 1 A. In only seven (four) cases did the refinement procedure increase the RMSD by more than 0.3 (0.5) A. For the remaining structures, the refinement procedures changed the structures by less than 0.3 A. While modest, the performance of the current refinement methods is better than the published refinement results obtained using standard molecular dynamics.     

The Three-Dimensional NMR Solution Structure of α-Cobratoxin at pH 7.5 and Conformational Differences With the NMR Solution Structure at pH 3.2

Abstract The 3D solution structure of α-cobratoxin, a neurotoxin purified from the Naja naja siamensis snake venom, has been determined by Nuclear Magnetic Resonance spectroscopy, in conjunction with distance geometry and restrained molecular dynamics, at pH 7.5. A total of 490 distance restraints were obtained from NOE intensities and 25 φ dihedral angle restraints deduced from J- coupling data. The generated structures are well defined with root mean square deviations from a geometrical mean structure of 0.107 ± 0.036 nm for the backbone atoms and 0.128 ±0.073 nm for the side-chain atoms (considering residues 1 to 66 minus 26 to 35). A comparison between the generated structures at pH 7.5 and the mean NMR solution structure at pH 3.2 revealed that the 3D structure of α-cobratoxin is more compact at neutral pH. This major difference is mainly due to the pH-dependant conformational variations of three residues His(18), Thr(44) and Thr(59).     

Bhageerath: an energy based web enabled computer software suite for limiting the search space of tertiary structures of small globular proteins

We describe here an energy based computer software suite for narrowing down the search space of tertiary structures of small globular proteins. The protocol comprises eight different computational modules that form an automated pipeline. It combines physics based potentials with biophysical filters to arrive at 10 plausible candidate structures starting from sequence and secondary structure information. The methodology has been validated here on 50 small globular proteins consisting of 2-3 helices and strands with known tertiary structures. For each of these proteins, a structure within 3-6 A RMSD (root mean square deviation) of the native has been obtained in the 10 lowest energy structures. The protocol has been web enabled and is accessible at http://www.scfbio-iitd.res.in/bhageerath.     

Recoverable one-dimensional encoding of three-dimensional protein structures

One-dimensional (1D) structures of proteins such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it is still not clear whether a given set of 1D structures contains sufficient information for recovering the underlying 3D structure. Here we show that the 3D structure of a protein can be recovered from a set of three types of 1D structures, namely, secondary structure, contact number and residue-wise contact order which is introduced here for the first time. Using simulated annealing molecular dynamics simulations, the structures satisfying the given native 1D structural restraints were sought for 16 proteins of various structural classes and of sizes ranging from 56 to 146 residues. By selecting the structures best satisfying the restraints, all the proteins showed a coordinate RMS deviation of <4 A from the native structure, and, for most of them, the deviation was even <2 A. The present result opens a new possibility to protein structure prediction and our understanding of the sequence-structure relationship.     

Solution structure of long neurotoxin NTX-1 from the venom of Naja naja oxiana by 2D-NMR spectroscopy.

The NMR solution structures of NTX-1 (PDB code 1W6B and BMRB 6288), a long neurotoxin isolated from the venom of Naja naja oxiana, and the molecular dynamics simulation of these structures are reported. Calculations are based on 1114 NOEs, 19 hydrogen bonds, 19 dihedral angle restraints and secondary chemical shifts derived from 1H to 13C HSQC spectrum. Similar to other long neurotoxins, the three-finger like structure shows a double and a triple stranded beta-sheet as well as some flexible regions, particularly at the tip of loop II and the C-terminal tail. The solution NMR and molecular dynamics simulated structures are in good agreement with root mean square deviation values of 0.23 and 1 A for residues involved in beta-sheet regions, respectively. The overall fold in the NMR structure is similar to that of the X-ray crystallography, although some differences exist in loop I and the tip of loop II. The most functionally important residues are located at the tip of loop II and it appears that the mobility and the local structure in this region modulate the binding of NTX-1 and other long neurotoxins to the nicotinic acetylcholine receptor.