Inter-residue Distances Research Articles

DALIX: Optimal DALI Protein Structure Alignment

We present a mathematical model and exact algorithm for optimally aligning protein structures using the DALI scoring model. This scoring model is based on comparing the interresidue distance matrices of proteins and is used in the popular DALI software tool, a heuristic method for protein structure alignment. Our model and algorithm extend an integer linear programming approach that has been previously applied for the related, but simpler, contact map overlap problem. To this end, we introduce a novel type of constraint that handles negative score values and relax it in a Lagrangian fashion. The new algorithm, which we call DALIX, is applicable to any distance matrix-based scoring scheme. We also review options that allow to consider fewer pairs of interresidue distances explicitly because their large number hinders the optimization process. Using four known data sets of varying structural similarity, we compute many provably score-optimal DALI alignments. This allowed, for the first time, to evaluate the DALI heuristic in sound mathematical terms. The results indicate that DALI usually computes optimal or close to optimal alignments. However, we detect a subset of small proteins for which DALI fails to generate any significant alignment, although such alignments do exist.

Structural Transition of N-Terminal Extension of Cardiac Troponin-I Complexed with Troponin-C caused by PKC-Mediated Phosphorylation, as Revealed by Spin Labeling EPR

Cardiac troponin (cTn) complex consisting of cTnI, cTnC and cTnT is responsible for cardiac mechanotransduction. Aberrent phosophorylation of cTnI by PKC on S42/44 or its phosphorylation mimic mutant S42/44D decreases Ca2+ sensitivity and tension force, consequently generating heart failure. Until now, consequence of cTnI by PKC phosphorylation on molecular level and associated structural mechanisms involved in it are still elusive. Combined with previously published NMR spectra and our bioinformatics analysis, this distinct N-extension of cTnI is strongly shown to be intrinsically disordered. To simulate the possible conformation of this intrinsically disordered region and potential conformational transition caused by PKC when binding with cTnC, Monte Carlo simulation was implemented to explore potential docking sites on cTnC, of which all the predicted structures were evaluated by total and binding energy with the criteria under RosettaCommons software suite. We screened around 10,000 structures for cTnC-I and cTnC-I (S42/44D) complexes, respectively. For cTnC-I complex, flexible N-extension of cTnI docked on N-domain of cTnC, putatively assisting to stabilize the full-open state of cTnC which binds strongly the regulatory region of cTnI to initiate muscle contraction. In contrast, as for cTnC-I (S42/44D), it localized on C-domain of cTnC, thus deficiently to maintain full-open state of cTnC, causing a weak interaction between the regulatory region of cTnI (S42/44D) and cTnC to generate heart failure. To verify our prediction, we are measuring residual mobility and inter-residual distance from spin labels placed on cTnI or cTnI (S42/44D) and cTnC. Preliminary mobility measurement of MSL-labeled cTnC(C84) indicated loose interaction between the regulatory region of cTnI (S42/44D) and cTnC. Measurements on the other sites are in progress.

Conformational Dynamics of Motor Proteins Detected by Electron Spin Resonance

A motor protein moves on a large scale at molecular level. We have used site-directed spin-labeling electron spin resonance (ESR) to detect molecular orientation, residual side-chain mobility and inter-residual distances. Especially, the distances of 8-80 Å can be measured by continuous-wave and recently developed pulse ESR. We applied these techniques to the studies on conformational dynamics of motor proteins, myosin and kinesin, and muscular switch proteins troponin-tropomyosin. In these systems, the flexible elements undergo thermal motion and fluctuate on large scale between distinct structural states during activity.

Cutoff Scanning Matrix (CSM): structural classification and function prediction by protein inter-residue distance patterns

BackgroundThe unforgiving pace of growth of available biological data has increased the demand for efficient and scalable paradigms, models and methodologies for automatic annotation. In this paper, we present a novel structure-based protein function prediction and structural classification method: Cutoff Scanning Matrix (CSM). CSM generates feature vectors that represent distance patterns between protein residues. These feature vectors are then used as evidence for classification. Singular value decomposition is used as a preprocessing step to reduce dimensionality and noise. The aspect of protein function considered in the present work is enzyme activity. A series of experiments was performed on datasets based on Enzyme Commission (EC) numbers and mechanistically different enzyme superfamilies as well as other datasets derived from SCOP release 1.75.ResultsCSM was able to achieve a precision of up to 99% after SVD preprocessing for a database derived from manually curated protein superfamilies and up to 95% for a dataset of the 950 most-populated EC numbers. Moreover, we conducted experiments to verify our ability to assign SCOP class, superfamily, family and fold to protein domains. An experiment using the whole set of domains found in last SCOP version yielded high levels of precision and recall (up to 95%). Finally, we compared our structural classification results with those in the literature to place this work into context. Our method was capable of significantly improving the recall of a previous study while preserving a compatible precision level.ConclusionsWe showed that the patterns derived from CSMs could effectively be used to predict protein function and thus help with automatic function annotation. We also demonstrated that our method is effective in structural classification tasks. These facts reinforce the idea that the pattern of inter-residue distances is an important component of family structural signatures. Furthermore, singular value decomposition provided a consistent increase in precision and recall, which makes it an important preprocessing step when dealing with noisy data.

A Protocol for Computer-Based Protein Structure and Function Prediction

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.

A protocol for computer-based protein structure and function prediction.

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.

Early stages of the recovery stroke in myosin II studied by molecular dynamics simulations

The recovery stroke is a key step in the functional cycle of muscle motor protein myosin, during which pre-recovery conformation of the protein is changed into the active post-recovery conformation, ready to exersice force. We study the microscopic details of this transition using molecular dynamics simulations of atomistic models in implicit and explicit solvent. In more than 2 μs of aggregate simulation time, we uncover evidence that the recovery stroke is a two-step process consisting of two stages separated by a time delay. In our simulations, we directly observe the first stage at which switch II loop closes in the presence of adenosine triphosphate at the nucleotide binding site. The resulting configuration of the nucleotide binding site is identical to that detected experimentally. Distribution of inter-residue distances measured in the force generating region of myosin is in good agreement with the experimental data. The second stage of the recovery stroke structural transition, rotation of the converter domain, was not observed in our simulations. Apparently it occurs on a longer time scale. We suggest that the two parts of the recovery stroke need to be studied using separate computational models.

Analyses of Protein Sequences Using Inter-Residue Average Distance Statistics to Study Folding Processes and the Significance of Their Partial Sequences

One of the goals of molecular bioinformatics is decoding amino acid sequences to extract information on the principles of protein folding. However, this is difficult to perform with standard bioinformatics techniques such as multiple sequence alignment and so on. Thus, we propose a technique based on inter-residue average distance statistics to make predictions regarding the protein folding mechanisms of amino acid sequences. Our method involves constructing a kind of predicted contact map called an Average Distance Map (ADM) based on average distance statistics to pinpoint regions of possible folding nuclei for proteins. Only information on the amino acid sequence of a given protein is required for the present method. In this article, we summarize the results of studies using our method to analyze how specific protein sequences affect folding properties. In particular, we present studies on proteins in the phage lysozyme, such as the globin, fatty acid binding protein-like, and the cupredoxin-like fold families. In the present review, we characterize the 3D architectures of these proteins through the properties of the protein ADMs. Furthermore, we combine the information on the conserved residues within the regions predicted by the ADMs with our results obtained so far. Such information may help identify the folding characteristics of each protein. We discuss this possibility in the present review.

Analysis of the Local Sequences of Folding Sites in β Sandwich Proteins with Inter-Residue Average Distance Statistics

The sequences of azurin and titin,  sandwich proteins, are analyzed based on inter-residue average distance statistics. A kind of predicted contact map based on inter-residue average distance statistics (Average Distance Map, ADM) is used to pinpoint regions of possible compact regions for two proteins. We compare predicted compact regions with the positions of the residues with experimental high  values for these proteins reported in the literature. The results reveal that the regions predicted by ADMs correspond to the positions of residues with the high  value. Furthermore, we perform random sampling of 3D conformations using these protein sequences with a potential derived from inter-residue average distance statistics. It is demonstrated that the residues with highest contact frequency during the simulations quali- tatively correspond to the residues with the highest  values for these proteins. Importantly, analysis with inter-residue av- erage distance statistics predicts the properties of folding processes of the  sandwich proteins starting from only sequence information.

Algorithm engineering for optimal alignment of protein structure distance matrices

Protein structural alignment is an important problem in computational biology. In this paper, we present first successes on provably optimal pairwise alignment of protein inter-residue distance matrices, using the popular dali scoring function. We introduce the structural alignment problem formally, which enables us to express a variety of scoring functions used in previous work as special cases in a unified framework. Further, we propose the first mathematical model for computing optimal structural alignments based on dense inter-residue distance matrices. We therefore reformulate the problem as a special graph problem and give a tight integer linear programming model. We then present algorithm engineering techniques to handle the huge integer linear programs of real-life distance matrix alignment problems. Applying these techniques, we can compute provably optimal dali alignments for the very first time.

Generating Global Protein Dynamics with Structure-From-FRET

The remarkable specificity and diversity of protein function are consequences of native conformational fluctuations, and more specifically transitions between conformational substates. Experimentally, these dynamics are increasingly resolvable (with high temporal detail) using single molecule Forster Resonance Energy Transfer (smFRET) methods, which can capture rare structural extensions not discernible with bulk methods. Still, even with multiple fluorophore-pairs, dye-separation trajectories lack the atomistic detail of crystallographic or NMR-based methods, and, at present, merging smFRET data with high-resolution structural data remains problematic. Moreover, many functionally-relevant transitions proceed within timescales far beyond those accessible to current molecular dynamics approaches. We address this common tradeoff between detail and sampling by posing the following inference problem: given a single dynamic distance constraint, what is the most likely protein structure? For a solution, our Kalman-filter-inspired approach, Structure-from-FRET, generates an atomistic protein trajectory most likely responsible for the observed smFRET distance constraint: a statistical inference inverse problem. As a general analysis and visualization tool, we apply the method to the model hinge protein adenylate kinase. Millisecond-resolution FRET efficiencies indicate approximate Lid/Core distance traces, which constrain inference of global protein geometry. Resultant trajectories span extended temporal (seconds) and conformational (tens of Angstroms) scales, without imposed potentials or perturbations between reference states. Here, the inter-residue distances constrain a state-space estimation with backbone atom coordinates as variables. Experimental (constraint) uncertainty is explicitly considered and each update step maximizes spatial information from previous ‘frames’. We compare generated trajectories against those from interpolative or elastic network approaches, but also with known PDB structures and long run MD simulations. Results suggest Structure-from-FRET is reliable for modeling novel biocatalysts, inhibitor targets, or other proteins for which multiple structures or atomistic simulations are unavailable.

2H1624 The study of the folding units in the TIM-Barrel fold based on the inter-residue average distance statistics(Protein: Property 3,The 48th Annual Meeting of the Biophysical Society of Japan)

2H1624 The study of the folding units in the TIM-Barrel fold based on the inter-residue average distance statistics(Protein: Property 3,The 48th Annual Meeting of the Biophysical Society of Japan)

On protein structure alignment under distance constraint

In this paper we study the protein structure comparison problem where each protein is modeled as a sequence of 3D points, and a contact edge is placed between every two of these points that are sufficiently close. Given two proteins represented this way, our problem is to find a subset of points from each protein, and a bijective matching of points between these two subsets, with the objective of maximizing either (A) the size of the subsets (the LCP problem), or (B) the number of edges that exist simultaneously in both subsets (the CMO problem), under the requirement that only points within a specified proximity can be matched. It is known that the general CMO problem (without the proximity requirement) is hard to approximate. However, with the proximity requirement, it is known that if a minimum inter-residue distance is imposed on the input, approximate solutions can be efficiently obtained. In this paper we mainly show that the CMO problem under these conditions: (1) is NP-hard, but (2) allows a PTAS. The rest of this paper shows algorithms for the LCP problem which improve on known results.

Towards optimal alignment of protein structure distance matrices

Structural alignments of proteins are important for identification of structural similarities, homology detection and functional annotation. The structural alignment problem is well studied and computationally difficult. Many different scoring schemes for structural similarity as well as many algorithms for finding high-scoring alignments have been proposed. Algorithms using contact map overlap (CMO) as scoring function are currently the only practical algorithms able to compute provably optimal alignments. We propose a new mathematical model for the alignment of inter-residue distance matrices, building upon previous work on maximum CMO. Our model includes all elements needed to emulate various scoring schemes for the alignment of protein distance matrices. The algorithm that we use to compute alignments is practical only for sparse distance matrices. Therefore, we propose a more effective scoring function, which uses a distance threshold and only positive structural scores. We show that even under these restrictions our approach is in terms of alignment accuracy competitive with state-of-the-art structural alignment algorithms, whereas it additionally either proves the optimality of an alignment or returns bounds on the optimal score. Our novel method is freely available and constitutes an important promising step towards truly provably optimal structural alignments of proteins. An executable of our program PAUL is available at http://planet-lisa.net/.

Isotope Signatures Allow Identification of Chemically Cross-Linked Peptides by Mass Spectrometry: A Novel Method to Determine Interresidue Distances in Protein Structures through Cross-Linking

Knowledge of protein structures and protein-protein interactions is essential for understanding of biological processes. Recent advances in protein cross-linking and mass spectrometry (MS) have shown significant potential to contribute to this area. Here we report a novel method to rapidly and accurately identify cross-linked peptides based on their unique isotope signature when digested in the presence of H(2)(18)O. This method overcomes the need for specially synthesized cross-linkers and/or multiple MS runs required by other techniques. We validated our method by performing a "blind" analysis of 5 proteins/complexes of known structure. Side chain repacking calculations using Rosetta show that 17 of our 20 positively identified cross-links fit the published atomic structures. The remaining 3 cross-links are likely due to protein aggregation. The accuracy and rapid throughput of our workflow will advance the use of protein cross-linking in structural biology.

GroEL-induced topological dislocation of a substrate protein β-sheet core: a solution EPR spin–spin distance study

The Hsp60-type chaperonin GroEL assists in the folding of the enzyme human carbonic anhydrase II (HCA II) and protects it from aggregation. This study was aimed to monitor conformational rearrangement of the substrate protein during the initial GroEL capture (in the absence of ATP) of the thermally unfolded HCA II molten-globule. Single- and double-cysteine mutants were specifically spin-labeled at a topological breakpoint in the β-sheet rich core of HCA II, where the dominating antiparallel β-sheet is broken and β-strands 6 and 7 are parallel. Electron paramagnetic resonance (EPR) was used to monitor the GroEL-induced structural changes in this region of HCA II during thermal denaturation. Both qualitative analysis of the EPR spectra and refined inter-residue distance calculations based on magnetic dipolar interaction show that the spin-labeled positions F147C and K213C are in proximity in the native state of HCA II at 20°C (as close as ∼8Å), and that this local structure is virtually intact in the thermally induced molten-globule state that binds to GroEL. In the absence of GroEL, the molten globule of HCA II irreversibly aggregates. In contrast, a substantial increase in spin-spin distance (up to >20Å) was observed within minutes, upon interaction with GroEL (at 50 and 60°C), which demonstrates a GroEL-induced conformational change in HCA II. The GroEL binding-induced disentanglement of the substrate protein core at the topological break-point is likely a key event for rearrangement of this potent aggregation initiation site, and hence, this conformational change averts HCA II misfolding.

Thermo- and Mesostabilizing Protein Interactions Identified by Temperature-Dependent Statistical Potentials

The goal of controlling protein thermostability is tackled here through establishing, by in silico analyses, the relative weight of residue-residue interactions in proteins as a function of temperature. We have designed for that purpose a (melting-) temperature-dependent, statistical distance potential, where the interresidue distances are computed between the side-chain geometric centers or their functional centers. Their separate derivation from proteins of either high or low thermal resistance reveals the interactions that contribute most to stability in different temperature ranges. Thermostabilizing interactions include salt bridges and cation- π interactions (especially those involving arginine), aromatic interactions, and H-bonds between negatively charged and some aromatic residues. In contrast, H-bonds between two polar noncharged residues or between a polar noncharged residue and a negatively charged residue are relatively less stabilizing at high temperatures. An important observation is that it is necessary to consider both repulsive and attractive interactions in overall thermostabilization, as the degree of repulsion may also vary with temperature. These temperature-dependent potentials are not only useful for the identification of meso- and thermostabilizing pair interactions, but also exhibit predictive power, as illustrated by their ability to predict the melting temperature of a protein based on the melting temperature of homologous proteins.

Resonance Assignment and Three-Dimensional Structure Determination of a Human α-Defensin, HNP-1, by Solid-State NMR

Human α-defensins [human neutrophil peptides (HNPs)] are immune defense mini-proteins that act by disrupting microbial cell membranes. Elucidating the three-dimensional (3D) structures of HNPs in lipid membranes is important for understanding their mechanisms of action. Using solid-state NMR (SSNMR), we have determined the 3D structure of HNP-1 in a microcrystalline state outside the lipid membrane, which provides benchmarks for structure determination and comparison with the membrane-bound state. From a suite of two-dimensional and 3D magic-angle spinning experiments, 13C and 15N chemical shifts that yielded torsion angle constraints were obtained, while inter-residue distances were obtained to restrain the 3D fold. Together, these constraints led to the first high-resolution SSNMR structure of a human defensin. The SSNMR structure has close similarity to the crystal structures of the HNP family, with the exception of the loop region between the first and second β-strands. The difference, which is partially validated by direct torsion angle measurements of selected loop residues, suggests possible conformational variation and flexibility of this segment of the protein, which may regulate HNP interaction with the phospholipid membrane of microbial cells.

2P020 残基間平均距離統計に基づくフェレドキシン様フォールドのフォールディング機構の解析(蛋白質-構造,第48回日本生物物理学会年会)

2P020 残基間平均距離統計に基づくフェレドキシン様フォールドのフォールディング機構の解析(蛋白質-構造,第48回日本生物物理学会年会)

RigidFinder: A fast and sensitive method to detect rigid blocks in large macromolecular complexes

Advances in structure determination have made possible the analysis of large macromolecular complexes (some with nearly 10,000 residues, such as GroEL). The large-scale conformational changes associated with these complexes require new approaches. Historically, a crucial component of motion analysis has been the identification of moving rigid blocks from the comparison of different conformations. However, existing tools do not allow consistent block identification in very large structures. Here, we describe a novel method, RigidFinder, for such identification of rigid blocks from different conformations-across many scales, from large complexes to small loops. RigidFinder defines rigidity in terms of blocks, where inter-residue distances are conserved across conformations. Distance conservation, unlike the averaged values (e.g., RMSD) used by many other methods, allows for sensitive identification of motions. A further distinguishing feature of our method, is that, it is capable of finding blocks made from nonconsecutive fragments of multiple polypeptide chains. In our implementation, we utilize an efficient quasi-dynamic programming search algorithm that allows for real-time application to very large structures. RigidFinder can be used at a dedicated web server (http://rigidfinder.molmovdb.org). The server also provides links to examples at various scales such as loop closure, domain motions, partial refolding, and subunit shifts. Moreover, here we describe the detailed application of RigidFinder to four large structures: Pyruvate Phosphate Dikinase, T7 RNA polymerase, RNA polymerase II, and GroEL. The results of the method are in excellent agreement with the expert-described rigid blocks.