Normal-modes-based prediction of protein conformational changes guided by distance constraints

Based on the elastic network model, we develop a novel method that predicts the conformational change of a protein complex given its initial-state crystal structure together with a small set of pairwise distance constraints for the end state. The predicted conformational change, which is a linear combination of multiple low-frequency normal modes that are solved from the elastic network model, is computed as a response displacement induced by a perturbation to the system Hamiltonian that incorporates the given distance constraints. For a list of test cases, we find that the computed response displacement overlaps significantly with the measured conformational changes, when only a handful of pairwise constraints are used (相似文献   

Pseudo-structures for the 20 common amino acids for use in studies of protein conformations by measurements of intramolecular proton-proton distance constraints with nuclear magnetic resonance

"Pseudo-structures" of the 20 common amino acid residues are introduced for use in protein spatial structure determinations, which rely on the use of intramolecular proton-proton distance constraints determined by nuclear Overhauser effects as input for distance geometry calculations. The proposed structures satisfy requirements for the initial structural interpretation of the nuclear magnetic resonance data that arise from the absence of stereospecific assignments and/or limited spectral resolution for certain resonance lines. The pseudo-atoms used as reference points for the experimental distance constraints can be used in conjunction with the real amino acid structures representing the van der Waals' constraints on the spatial molecular structure, or with simplified models in order to reduce the computing time for the distance geometry calculations.     

On the use of distance constraints in protein-protein docking computations

Protein-protein docking (PPD) is a computational process that predicts the structure of a complex of two interacting proteins from their unbound structures. The accuracy of PPD predictions is low, but can be greatly enhanced if experimentally determined distance data are available for incorporation into the prediction. However, the specific effects of distance constraints on PPD predictions are largely uncharacterized. In this study, we systematically simulated the effects of using distance constraints both on a new distance constraint-driven PPD approach, called DPPD, and also, by re-ranking, on a well-established grid-based global search approach. Our results for a PPD benchmark dataset of 84 protein complexes of known structures showed that near 100% docking success rates could be obtained when the number of distance constraints exceeded six, the degrees of freedom of the system, but the success rate was significantly reduced by long distance constraints, large binding-induced conformational changes, and large errors in the distance data. Our results also showed that, under most conditions simulated, even two or three distance constraints were sufficient to achieve a much better success rate than those using a sophisticated physicochemical function to re-rank the results of the global search. Our study provides guidelines for the practical incorporation of experimental distance data to aid PPD predictions.     

Solution structures of the rabbit neutrophil defensin NP-5

Solution structures of the rabbit neutrophil defensin NP-5 have been determined by 1H nuclear magnetic resonance (n.m.r.) spectroscopy and distance geometry techniques. This 33 amino acid peptide is part of the oxygen-independent mammalian defense system against microbial infection. The structures were generated from 107 n.m.r. derived inter-residue proton-proton distance constraints. A distance geometry algorithm was then used to determine the range of structures consistent with these distance constraints. These distance geometry calculations employed an improved algorithm that allowed the chirality constraints to be relaxed on prochiral centers when it was not possible to make stereo-specific assignments of protons on these centers. This procedure gave superior results compared with standard distance geometry methods and also produced structures that were more consistent with the original n.m.r. data. Analysis of the NP-5 structures shows that the overall folding of the peptide backbone is well defined by the n.m.r. distance information but that the side-chain group conformations are generally less well defined.     

Refinement of the NMR structures for acyl carrier protein with scalar coupling data

Structure determination of small proteins using NMR data is most commonly pursued by combining NOE derived distance constraints with inherent constraints based on chemical bonding. Ideally, one would make use of a variety of experimental observations, not just distance constraints. Here, coupling constant constraints have been added to molecular mechanics and molecular dynamics protocols for structure determination in the form of a psuedoenergy function that is minimized in a search for an optimum molecular conformation. Application is made to refinement of a structure for a 77 amino acid protein involved in fatty acid synthesis, Escherichia coli acyl carrier protein (ACP). 54 3JHN alpha coupling constants, 12 coupling constants for stereospecifically assigned side chain protons, and 450 NOE distance constraints were used to calculate the 3-D structure of ACP. A three-step protocol for a molecular dynamics calculation is described, in analogy to the protocol previously used in molecular mechanics calculations. The structures calculated with the molecular mechanics approach and the molecular dynamics approach using a rigid model for the protein show similar molecular energies and similar agreement with experimental distance and coupling constant constraints. The molecular dynamics approach shows some advantage in overcoming local minimum problems, but only when a two-state averaging model for the protein was used, did molecular energies drop significantly.     

Structural complementarity of distance constraints obtained from chemical cross-linking and amino acid coevolution

The analysis of amino acid coevolution has emerged as a practical method for protein structural modeling by providing structural contact information from alignments of amino acid sequences. In parallel, chemical cross-linking/mass spectrometry (XLMS) has gained attention as a universally applicable method for obtaining low-resolution distance constraints to model the quaternary arrangements of proteins, and more recently even protein tertiary structures. Here, we show that the structural information obtained by XLMS and coevolutionary analysis are effectively complementary: the distance constraints obtained by each method are almost exclusively associated with non-coincident pairs of residues, and modeling results obtained by the combination of both sets are improved relative to considering the same total number of constraints of a single type. The structural rationale behind the complementarity of the distance constraints is discussed and illustrated for a representative set of proteins with different sizes and folds.     

Protein threading with profiles and distance constraints using clique based algorithms

With the advent of experimental technologies like chemical cross-linking, it has become possible to obtain distances between specific residues of a newly sequenced protein. These types of experiments usually are less time consuming than X-ray crystallography or NMR. Consequently, it is highly desired to develop a method that incorporates this distance information to improve the performance of protein threading methods. However, protein threading with profiles in which constraints on distances between residues are given is known to be NP-hard. By using the notion of a maximum edge-weight clique finding algorithm, we introduce a more efficient method called FTHREAD for profile threading with distance constraints that is 18 times faster than its predecessor CLIQUETHREAD. Moreover, we also present a novel practical algorithm NTHREAD for profile threading with Non-strict constraints. The overall performance of FTHREAD on a data set shows that although our algorithm uses a simple threading function, our algorithm performs equally well as some of the existing methods. Particularly, when there are some unsatisfied constraints, NTHREAD (Non-strict constraints threading algorithm) performs better than threading with FTHREAD (Strict constraints threading algorithm). We have also analyzed the effects of using a number of distance constraints. This algorithm helps the enhancement of alignment quality between the query sequence and template structure, once the corresponding template structure is determined for the target sequence.     

Relationship between protein structure and geometrical constraints.

We evaluate to what extent the structure of proteins can be deduced from incomplete knowledge of disulfide bridges, surface assignments, secondary structure assignments, and additional distance constraints. A cost function taking such constraints into account was used to obtain protein structures using a simple minimization algorithm. For small proteins, the approximate structure could be obtained using one additional distance constraint for each amino acid in the protein. We also studied the effect of using predicted secondary structure and surface assignments. The constraints used in this approach typically may be obtained from low-resolution experimental data. When using a cost function based on distances, half of the resulting structures will be mirrored, because the resulting structure and its mirror image will have the same cost. The secondary structure assignments were therefore divided into chirality constraints and distance constraints. Here we report that the problem of mirrored structures, in some cases, can be solved by using a chirality term in the cost function.     

1H NMR assignments of sidechain conformations in proteins using a high-dimensional potential in the simulated annealing calculations

A high-dimensional potential representing distance constraints for stereospecifically assignable diastereotopic proton or methyl pairs was incorporated into the dynamical simulated annealing protocol to calculate structure with stereospecifically determined sidechain conformations. The protocol is tested on nuclear magnetic resonance cross-relaxation data of a trypsin inhibitor from squash seeds, CMTI-I, and compared with two other methods of stereospecific assignment, the floating chirality and coupling constant methods. There is good agreement between the three methods in predicting the same stereospecific assignments. Because the high-dimensional potential uses more relaxed absolute distance constraints and also takes into account the relative distance constraint patterns, it avoids possible overinterpretation of the NOE data.     

Simulated annealing with restrained molecular dynamics using CONGEN: energy refinement of the NMR solution structures of epidermal and type-alpha transforming growth factors.

The new functionality of the program CONGEN (Bruccoleri RE, Karplus M, 1987, Biopolymers 26:137-168; Bassolino-Klimas D et al., 1996, Protein Sci 5:593-603) has been applied for energy refinement of two previously determined solution NMR structures, murine epidermal growth factor (mEGF) and human type-alpha transforming growth factor (hTGF alpha). A summary of considerations used in converting experimental NMR data into distance constraints for CONGEN is presented. A general protocol for simulated annealing with restrained molecular dynamics is applied to generate NMR solution structures using CONGEN together with real experimental NMR data. A total of 730 NMR-derived constraints for mEGF and 424 NMR-derived constraints for hTGF alpha were used in these energy-refinement calculations. Different weighting schemes and starting conformations were studied to check and/or improve the sampling of the low-energy conformational space that is consistent with all constraints. The results demonstrate that loosened (i.e., "relaxed") sets of the EGF and hTGF alpha internuclear distance constraints allow molecules to overcome local minima in the search for a global minimum with respect to both distance restraints and conformational energy. The resulting energy-refined structures of mEGF and hTGF alpha are compared with structures determined previously and with structures of homologous proteins determined by NMR and X-ray crystallography.     

Determining the three-dimensional fold of a protein from approximate constraints

We propose a new approach for calculating the three-dimensional (3D) structure of a protein from distance and dihedral angle constraints derived from experimental data. We suggest that such constraints can be obtained from experiments such as tritium planigraphy, chemical or enzymatic cleavage of the polypeptide chain, paramagnetic perturbation of nuclear magnetic resonance (NMR) spectra, measurement of hydrogen-exchange rates, mutational studies, mass spectrometry, and electron paramagnetic resonance. These can be supplemented with constraints from theoretical prediction of secondary structures and of buried/exposed residues. We report here distance geometry calculations to generate the structures of a test protein Staphylococcal nuclease (STN), and the HIV-1 rev protein (REV) of unknown structure. From the available 3D atomic coordinates of STN, we set up simulated data sets consisting of varying number and quality of constraints, and used our group's Self Correcting Distance Geometry (SECODG) program DIAMOD to generate structures. We could generate the correct tertiary fold from qualitative (approximate) as well as precise distance constraints. The root mean square deviations of backbone atoms from the native structure were in the range of 2.0 A to 8.3 A, depending on the number of constraints used. We could also generate the correct fold starting from a subset of atoms that are on the surface and those that are buried. When we used data sets containing a small fraction of incorrect distance constraints, the SECODG technique was able to detect and correct them. In the case of REV, we used a combination of constraints obtained from mutagenic data and structure predictions. DIAMOD generated helix-loop-helix models, which, after four self-correcting cycles, populated one family exclusively. The features of the energy-minimized model are consistent with the available data on REV-RNA interaction. Our method could thus be an attractive alternative for calculating protein 3D structures, especially in cases where the traditional methods of X-ray crystallography and multidimensional NMR spectroscopy have been unsuccessful.     

A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction

The principal bottleneck in protein structure prediction is the refinement of models from lower accuracies to the resolution observed by experiment. We developed a novel constraints‐based refinement method that identifies a high number of accurate input constraints from initial models and rebuilds them using restrained torsion angle dynamics (rTAD). We previously created a Bayesian statistics‐based residue‐specific all‐atom probability discriminatory function (RAPDF) to discriminate native‐like models by measuring the probability of accuracy for atom type distances within a given model. Here, we exploit RAPDF to score (i.e., filter) constraints from initial predictions that may or may not be close to a native‐like state, obtain consensus of top scoring constraints amongst five initial models, and compile sets with no redundant residue pair constraints. We find that this method consistently produces a large and highly accurate set of distance constraints from which to build refinement models. We further optimize the balance between accuracy and coverage of constraints by producing multiple structure sets using different constraint distance cutoffs, and note that the cutoff governs spatially near versus distant effects in model generation. This complete procedure of deriving distance constraints for rTAD simulations improves the quality of initial predictions significantly in all cases evaluated by us. Our procedure represents a significant step in solving the protein structure prediction and refinement problem, by enabling the use of consensus constraints, RAPDF, and rTAD for protein structure modeling and refinement. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Three-dimensional structure of acyl carrier protein determined by NMR pseudoenergy and distance geometry calculations

Distance constraints from two-dimensional NMR cross-relaxation data are used to derive a three-dimensional structure for acyl carrier protein from Escherichia coli. Several approaches to structure determination are explored. The most successful proves to be an approach that combines the early stages of a distance geometry program with energy minimization in the presence of NMR constraints represented as pseudopotentials. Approximately 450 proton to proton distance constraints including 50 long-range constraints were included in these programs. Starting structures were generated at random by the distance geometry program and energies minimized by a molecular mechanics module to give final structures. Seven of the structures were deemed acceptable on the basis of agreement with experimentally determined distances. Root-mean-square deviations from the mean of these structures for backbone atoms range from 2 to 3 A. All structures show three roughly parallel helices with hydrophobic residues facing inward and hydrophilic residues facing outward. A hydrophobic cleft is recognizable and is identified as a likely site for acyl chain binding.     

Solution conformation of proteinase inhibitor IIA from bull seminal plasma by 1H nuclear magnetic resonance and distance geometry

A determination of the solution conformation of the proteinase inhibitor IIA from bull seminal plasma (BUSI IIA) is described. Two-dimensional nuclear Overhauser enhancement spectroscopy (NOESY) was used to obtain a list of 202 distance constraints between individually assigned hydrogen atoms of the polypeptide chain, to identify the positions of the three disulfide bridges, and to locate the single cis peptide bond. Supplementary geometric constraints were derived from the vicinal spin-spin couplings and the locations of certain hydrogen bonds, as determined by nuclear magnetic resonance (n.m.r.). Using a new distance geometry program (DISGEO) which is capable of computing all-atom structures for proteins the size of BUSI IIA, five conformers were computed from the NOE distance constraints alone, and another five were computed with the supplementary constraints included. Comparison of the different structures computed from the n.m.r. data among themselves and with the crystal structures of two homologous proteins shows that the global features of the conformation of BUSI IIA (i.e. the overall dimensions of the molecule and the threading of the polypeptide chain) were well-defined by the available n.m.r. data. In the Appendix, we describe a preliminary energy refinement of the structure, which showed that the constraints derived from the n.m.r. data are compatible with a low energy spatial structure.     

Optimal bundling of transmembrane helices using sparse distance constraints

We present a two-step approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only sparse distance constraints, such as those derived from chemical cross-linking, dipolar EPR and FRET experiments. In Step 1, using an algorithm, we developed, the conformational space of membrane protein folds matching a set of distance constraints is explored to provide initial structures for local conformational searches. In Step 2, these structures refined against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. We begin by describing the statistical analysis of the solved membrane protein structures from which the theoretical portion of the penalty function was derived. We then describe the penalty function, and, using a set of six test cases, demonstrate that it is capable of distinguishing helical bundles that are close to the native bundle from those that are far from the native bundle. Finally, using a set of only 27 distance constraints extracted from the literature, we show that our method successfully recovers the structure of dark-adapted rhodopsin to within 3.2 A of the crystal structure.     

Optimization of interatomic angle geometry in torsion angle space

Summary Interatomic angle constraints are usually specified as distance constraints in torsion angle distance geometry. Such an approach is inaccurate and often inadequate. We provide a direct definition of the inter-atomic angle constraint term, which can be incorporated in the target function. The first derivative of this term with respect to the torsion angle has been described for all possible cases. This feature has been implemented in the nucleic acid distance geometry program TANDY [Ajay Kumar et al. (1991)J. Biomol NMR,1, 363–378], and has been tested on base pairing in the DNA fragment, d(AT)₂. The results clearly indicate the need and adequacy of such angle constraints. Other applications that would also benefit from this technique have been identified.     

Conformation of [Cd7]-metallothionein-2 from rat liver in aqueous solution determined by nuclear magnetic resonance spectroscopy

The three-dimensional structure of [Cd7]-metallothionein-2 from rat liver was determined in aqueous solution, using nuclear magnetic resonance spectrometry and distance geometry calculations. The experimental data provided proton-proton distance constraints from measurements of nuclear Overhauser effects, constraints on the geometry of the metal-cysteine clusters determined by heteronuclear correlation spectroscopy, and dihedral angle constraints derived from both coupling constants and nuclear Overhauser effects. The structure calculations were performed with the program DISMAN. As in previous studies with rabbit liver metallothionein-2a, the structure calculations were performed separately for the alpha and beta-domains containing the 4 and 3-metal clusters, respectively, since no interdomain constraints were found. For both domains, the global polypeptide fold, the location of polypeptide secondary structure elements, the architecture of the metal-sulfur cluster and the local chirality of the metal co-ordination are very similar to the solution structure of rabbit metallothionein-2a, but show considerable difference relative to the crystal structure of rat metallothionein-2.     

Solution structure of [d(GTATATAC)]2 via restrained molecular dynamics simulations with nuclear magnetic resonance constraints derived from relaxation matrix analysis of two-dimensional nuclear Overhauser effect experiments

Two-dimensional nuclear Overhauser effect (2D NOE) spectra have been used as the experimental basis for determining the solution structure of the duplex [d(GTATATAC)]2 employing restrained molecular dynamics (rMD) simulations. The MARDIGRAS algorithm has been employed to construct a set of 233 interproton distance constraints via iterative complete relaxation matrix analysis utilizing the peak intensities from the 2D NOE spectra obtained for different mixing times and model structures. The upper and lower bounds for each of the constraints, defining size of a flat-well potential function term used in the rMD simulations, were conservatively chosen as the largest or smallest value calculated by MARDIGRAS. Three different starting models were utilized in several rMD calculations: energy-minimized A-DNA, B-DNA, and a structure containing wrinkled D-DNA in the interior. Considerable effort was made to define the appropriate force constants to be employed with the NOE terms in the AMBER force field, using as criteria the average constraints deviation, the constraints violation energy and the total energy. Of the 233 constraints, one was generated indirectly, but proved to be crucial in defining the structure: the cross-strand A5-H2 A5-H2 distance. As those two protons resonate isochronously for the self-complementary duplex, the distance cannot be determined directly. However, the general pattern of 2D NOE peak intensities, spin-lattice relaxation time (T1) values, and 31P nuclear magnetic resonance spectra lead to use of the A3-H2 A7-H2 distance for A5-H2 A5-H2 as well. Five rMD runs, with different random number seeds, were made for each of the three starting structures with the full distance constraint set. The average structure from all 15 runs and the five-structure averages from each starting structure were all quite similar. Two rMD runs for each starting structure were made with the A5-H2 A5-H2 constraint missing. The average of these six rMD runs revealed differences in structure, compared to that with the full set of constraints, primarily for the middle two base-pairs involving the missing cross-strand constraint but global deviations also were found. Conformational analysis of the resulting structures revealed that the inner four to six base-pairs differed in structure from the termini. Furthermore, an alternating structure was suggested with features alternating for the A-T and T-A steps.     

Determination of the complete three-dimensional structure of the trypsin inhibitor from squash seeds in aqueous solution by nuclear magnetic resonance and a combination of distance geometry and dynamical simulated annealing

The complete three-dimensional structure of the trypsin inhibitor from seeds of the squash Cucurbita maxima in aqueous solution was determined on the basis of 324 interproton distance constraints, 80 non-nuclear Overhauser effect distances, and 22 hydrogen-bonding constraints, supplemented by 27 phi backbone angle constraints derived from nuclear magnetic resonance measurements. The nuclear magnetic resonance input data were converted to the distance constraints in a semiquantitative manner after a sequence specific assignment of 1H spectra was obtained using two-dimensional nuclear magnetic resonance techniques. Stereospecific assignments were obtained for 17 of the 48 prochiral centers of the squash trypsin inhibitor using the floating chirality assignment introduced at the dynamical simulated annealing stage of the calculations. A total of 34 structures calculated by a hybrid distance geometry-dynamical simulated annealing method exhibit well-defined positions for both backbone and side-chain atoms. The average atomic root-mean-square difference between the individual structures and the minimized mean structure is 0.35(+/- 0.08) A for the backbone atoms and 0.89(+/- 0.17) A for all heavy atoms. The precision of the structure determination is discussed and correlated to the experimental input data.     

Solution structure of murine epidermal growth factor determined by NMR spectroscopy and refined by energy minimization with restraints.

The solution structure of murine epidermal growth factor (mEGF) at pH 3.1 and a temperature of 28 degrees C has been determined from NMR data, using distance geometry calculations and restrained energy minimization. The structure determination is based on 730 conformational constraints derived from NMR data, including 644 NOE-derived upper bound distance constraints, constraints on the ranges of 32 dihedral angles based on measurements of vicinal coupling constants, and 54 upper and lower bound constraints associated with nine hydrogen bonds and the three disulfide bonds. The distance geometry interpretation of the NMR data is based on previously published sequence-specific 1H resonance assignments [Montelione et al. (1988) Biochemistry 27, 2235-2243], supplemented here with individual assignments for some side-chain amide, methylene, and isopropyl methyl protons. The molecular architecture of mEGF is the same as that described previously [Montelione et al. (1987) Proc. Natl. Acad. Sci. U.S.A. 84, 5226-5230], but the structure is overall more precisely determined by a more extensive set of NMR constraints. Analysis of proton NMR line widths, amide proton exchange rates, and side-chain 3J(H alpha-H beta) coupling constants provides evidence for internal motion in several regions of the mEGF molecule. Because mEGF is one member of a large family of homologous growth factors and protein domains for which X-ray crystal structures are not yet available, the atomic coordinates resulting from the present structure refinement (which we have deposited in the Brookhaven Protein Data Bank) are important data for understanding the structures of EGF-like proteins and for further detailed comparisons of these structures with mEGF.