Reconstruction of 3D structures from protein contact maps

The prediction of the protein tertiary structure from solely its residue sequence (the so called Protein Folding Problem) is one of the most challenging problems in Structural Bioinformatics. We focus on the protein residue contact map. When this map is assigned it is possible to reconstruct the 3D structure of the protein backbone. The general problem of recovering a set of 3D coordinates consistent with some given contact map is known as a unit-disk-graph realization problem and it has been recently proven to be NP-Hard. In this paper we describe a heuristic method (COMAR) that is able to reconstruct with an unprecedented rate (3-15 seconds) a 3D model that exactly matches the target contact map of a protein. Working with a non-redundant set of 1760 proteins, we find that the scoring efficiency of finding a 3D model very close to the protein native structure depends on the threshold value adopted to compute the protein residue contact map. Contact maps whose threshold values range from 10 to 18 Ångstroms allow reconstructing 3D models that are very similar to the proteins native structure.     

Prediction of protein coarse contact maps

Prediction of topological representations of proteins that are geometrically invariants can contribute towards the solution of fundamental open problems in structural genomics like folding. In this paper we focus on coarse grained protein contact maps, a representation that describes the spatial neighborhood relation between secondary structure elements such as helices, beta sheets, and random coils. Our methodology is based on searching the graph space. The search algorithm is guided by an adaptive evaluation function computed by a specialized noncausal recursive connectionist architecture. The neural network is trained using candidate graphs generated during examples of successful searches. Our results demonstrate the viability of the approach for predicting coarse contact maps.     

EM-fold: de novo atomic-detail protein structure determination from medium-resolution density maps

Electron density maps of membrane proteins or large macromolecular complexes are frequently only determined at medium resolution between 4?? and 10??, either by cryo-electron microscopy or X-ray crystallography. In these density maps, the general arrangement of secondary structure elements (SSEs) is revealed, whereas their directionality and connectivity remain elusive. We demonstrate that the topology of proteins with up to 250 amino acids can be determined from such density maps when combined with a computational protein folding protocol. Furthermore, we accurately reconstruct atomic detail in loop regions and amino acid side chains not visible in the experimental data. The EM-Fold algorithm assembles the SSEs de novo before atomic detail is added using Rosetta. In a benchmark of 27 proteins, the protocol consistently and reproducibly achieves models with root mean square deviation values <3??.     

Predicting protein three-dimensional structure

The current state of the art in modeling protein structure has been assessed, based on the results of the CASP (Critical Assessment of protein Structure Prediction) experiments. In comparative modeling, improvements have been made in sequence alignment, sidechain orientation and loop building. Refinement of the models remains a serious challenge. Improved sequence profile methods have had a large impact in fold recognition. Although there has been some progress in alignment quality, this factor still limits model usefulness. In ab initio structure prediction, there has been notable progress in building approximately correct structures of 40-60 residue-long protein fragments. There is still a long way to go before the general ab initio prediction problem is solved. Overall, the field is maturing into a practical technology, able to deliver useful models for a large number of sequences.     

High-throughput three-dimensional protein structure determination

In the wake of finished genomic sequencing projects, high-throughput analysis techniques are being developed in various fields of functional genomics. Of special interest in this regard is the three-dimensional structure analysis of proteins by X-ray crystallography and NMR spectroscopy, which has been characterized by distinctly low-throughput in the past. A number of recent advances in instrumentation and software are promising to radically change this situation, leaving the production of suitable protein samples as the sole rate-limiting step in structural analyses.     

核盘菌AROM蛋白的三级结构分析

核盘菌编码AROM蛋白的arom基因已经被克隆测序,本文根据该基因翻译的氨基酸序列用同源模建方法和从头模建方法分析了AROM蛋白各结构域的三级结构和功能位点,以及该蛋白二聚体可能的组装方式。结果表明,核盘菌AROM蛋白的脱氢奎尼酸合酶结构域进一步由N-端含有一个Rossmann折叠的α/β结构域和C-端的α螺旋结构域组成;5-烯醇丙酮酰莽草酸-3-磷酸合酶结构域则由两个相似结构域组成,每个结构域含有不同拷贝数的β折叠和α螺旋;莽草酸激酶结构域的N-端由三个β折叠组成;脱氢奎尼酸酶结构域为(α2β2)3多肽,在N-端有一对反平行的β链,在C-端有loop环;莽草酸脱氢酶结构域含有一个由α/β组成的催化结构域和一个含有Rossmann折叠的NADPH结合结构域。     

Long-range information and physicality constraints improve predicted protein contact maps

Protein topology representations such as residue contact maps are an important intermediate step towards ab initio prediction of protein structure, but the problem of predicting reliable contact maps is far from solved. One of the main pitfalls of existing contact map predictors is that they generally predict unphysical maps, i.e. maps that cannot be embedded into three-dimensional structures or, at best, violate a number of basic constraints observed in real protein structures, such as the maximum number of contacts for a residue. Here, we focus on the problem of learning to predict more "physical" contact maps. We do so by first predicting contact maps through a traditional system (XXStout), and then filtering these maps by an ensemble of artificial neural networks. The filter is provided as input not only the bare predicted map, but also a number of global or long-range features extracted from it. In a rigorous cross-validation test, we show that the filter greatly improves the predicted maps it is input. CASP7 results, on which we report here, corroborate this finding. Importantly, since the approach we present here is fully modular, it may be beneficial to any other ab initio contact map predictor.     

The three-dimensional structure of retinol-binding protein

The complex of retinol with its carrier protein, retinol-binding protein (RBP) has been crystallized and its three-dimensional structure determined using X-ray crystallography. Its most striking feature is an eight-stranded up-and-down beta barrel core that completely encapsulates the retinol molecule. The retinol molecule lies along the axis of the barrel with the beta-ionone ring innermost and the tip of the isoprene tail close to the surface.     

An algorithm to parse segment packing in predicted protein contact maps

Background

The analysis of correlation in alignments generates a matrix of predicted contacts between positions in the structure and while these can arise for many reasons, the simplest explanation is that the pair of residues are in contact in a three-dimensional structure and are affecting each others selection pressure. To analyse these data, A dynamic programming algorithm was developed for parsing secondary structure interactions in predicted contact maps.

Results

The non-local nature of the constraints required an iterated approach (using a “frozen approximation”) but with good starting definitions, a single pass was usually sufficient. The method was shown to be effective when applied to the transmembrane class of protein and error tolerant even when the signal becomes degraded. In the globular class of protein, where the extent of interactions are more limited and more complex, the algorithm still behaved well, classifying most of the important interactions correctly in both a small and a large test case. For the larger protein, this involved examples of the algorithm apportioning parts of a single large secondary structure element between two different interactions.

Conclusions

It is expected that the method will be useful as a pre-processor to coarse-grained modelling methods to extend the range of protein tertiary structure prediction to larger proteins or to data that is currently too ’noisy’ to be used by current residue-based methods.

     

Applying PyRosetta molecular energies to separate properly oriented protein models from mirror models,obtained from contact maps

Reconstructing protein structure based on contact maps leads to two types of models: properly oriented models and mirror models. This is due to the fact that contact maps do not include information on protein chirality. Therefore, both types of model orientations share the same contact map and are geometrically allowed. In this work, we verified the hypothesis that some of the energy terms calculated by PyRosetta could be useful to distinguish between properly oriented and mirror models. We studied 440 models of all-alpha protein domains reconstructed manually from their contact maps, where 50 % of the models were properly oriented and 50 % had mirror orientation. We showed that dihedral angles and energy terms, based on the probability of specific geometrical arrangement of the residues, differed significantly for properly oriented and mirror models.     

Modelling protein three-dimensional structure using tritium planigraphy

We propose the use of data on the topography of the label-accessible surface of a protein molecule obtained by the method of tritium planigraphy as a criterion for choosing the optimal intermediate arrangements of alpha-helices in globular proteins so as to model their three-dimensional structures. This approach has been used for modelling the three-dimensional structure of parvalbumin III from pike. The proposed model has been compared with high-resolution X-ray structural data for a related protein, paryvalbumin from carp. The possibilities and limitations of this approach are discussed.     

Digestive lipases: from three-dimensional structure to physiology

Human gastric lipase (HGL) is a lipolytic enzyme that is secreted by the chief cells located in the fundic part of the stomach. HGL plays an important role in lipid digestion, since it promotes the subsequent hydrolytic action of pancreatic lipase in duodenal lumen. Physiological studies have shown that HGL is able of acting not only in the highly acid stomach environment but also in the duodenum in synergy with human pancreatic lipase (HPL). Recombinant HGL (r-HGL) was expressed in the baculovirus/insect cell system in the form of an active protein with a molecular mass of 45 kDa. The specific activities of r-HGL were found to be similar to that of the native enzyme when tested on various triacylglycerol (TG) substrates. The 3-D structure of r-HGL was the first solved within the mammalian acid lipase family. This globular enzyme (379 residues) shows a new feature, different from the other known lipases structures, which consists of a core domain having the alpha/beta hydrolase fold and a cap domain including a putative 'lid' of 30 residues covering the active site of the lipase (closed conformation). HPL is the major lipolytic enzyme involved in the digestion of dietary TG. HPL is a 50 kDa glycoprotein which is directly secreted as an active enzyme. HPL was the first mammalian lipase to be solved structurally, and it revealed the presence of two structural domains: a large N-terminal domain (residues 1-336) and a smaller C-terminal domain (residues 337-449). The large N-terminal domain belongs to the alpha/beta hydrolase fold and contains the active site. A surface loop called the lid domain (C237-C261) covers the active site in the closed conformation of the lipase. The 3-D structure of the lipase-procolipase complex illustrates how the procolipase might anchor the lipase at the interface in the presence of bile salts: procolipase binds to the C-terminal domain of HPL and exposes the hydrophobic tips of its fingers at the opposite site of its lipase-binding domain. These hydrophobic tips help to bring N-terminal domain into close conformation with the interface where the opening of the lid domain probably occurs. As a result of all these conformational changes, the open lid and the extremities of the procolipase form an impressive continuous hydrophobic plateau, extending over more than 50 A. This surface might able to interact strongly with a lipid-water interface. The biochemical, histochemical and clinical studies as well as the 3-D structures obtained will be a great help for a better understanding of the structure-function relationships of digestive lipases.     

DeepTracer-ID: De novo protein identification from cryo-EM maps

The recent revolution in cryo-electron microscopy (cryo-EM) has made it possible to determine macromolecular structures directly from cell extracts. However, identifying the correct protein from the cryo-EM map is still challenging and often needs additional sequence information from other techniques, such as tandem mass spectrometry and/or bioinformatics. Here, we present DeepTracer-ID, a server-based approach to identify the candidate protein in a user-provided organism de novo from a cryo-EM map, without the need for additional information. Our method first uses DeepTracer to generate a protein backbone model that best represents the cryo-EM map, and this model is then searched against the library of AlphaFold2 predictions for all proteins in the given organism. This method is highly accurate and robust for high-resolution cryo-EM maps: in all 13 experimental maps tested blindly, DeepTracer-ID identified the correct proteins as the top candidates. Eight of the maps were of known structures, while the other five unpublished maps were validated by prior protein annotation and careful inspection of the model refined into the map. The program also showed promising results for both homomeric and heteromeric protein complexes. This platform is possible because of the recent breakthroughs in large-scale three-dimensional protein structure prediction.     

Predicting absolute contact numbers of native protein structure from amino acid sequence

The contact number of an amino acid residue in a protein structure is defined by the number of C(beta) atoms around the C(beta) atom of the given residue, a quantity similar to, but different from, solvent accessible surface area. We present a method to predict the contact numbers of a protein from its amino acid sequence. The method is based on a simple linear regression scheme and predicts the absolute values of contact numbers. When single sequences are used for both parameter estimation and cross-validation, the present method predicts the contact numbers with a correlation coefficient of 0.555 on average. When multiple sequence alignments are used, the correlation increases to 0.627, which is a significant improvement over previous methods. In terms of discrete states prediction, the accuracies for 2-, 3-, and 10-state predictions are, respectively, 71.4%, 54.1%, and 18.9% with residue type-dependent unbiased thresholds, and 76.3%, 59.2%, and 21.8% with residue type-independent unbiased thresholds. The difference between accessible surface area and contact number from a prediction viewpoint and the application of contact number prediction to three-dimensional structure prediction are discussed.     

The effect of backbone on the small-world properties of protein contact maps

In the last years, small-world behavior has been extensively described for proteins, when they are represented by the undirected graph defined by the inter-residue protein contacts. By adopting this representation it was possible to compute the average clustering coefficient (C) and characteristic path length (L) of protein structures, and their values were found to be similar to those of graphs characterized by small-world topology. In this comment, we analyze a large set of non-redundant protein structures (1753) and show that by randomly mimicking the protein collapse, the covalent structure of the protein chain significantly contributes to the small-world behavior of the inter-residue contact graphs. When protein graphs are generated, imposing constraints similar to those induced by the backbone connectivity, their characteristic path lengths and clustering coefficients are indistinguishable from those computed using the real contact maps showing that L and C values cannot be used for 'protein fingerprinting'. Moreover we verified that these results are independent of the selected protein representations, residue composition and protein secondary structures.     

Giant coronary aneurysms: three-dimensional reconstruction

A 31 year old man was referred for the evaluation of chest pain. Cardiac CT reconstruction revealed multiple calcified giant coronary aneurysms. Most likely this patient suffered from subclinical Kawasaki’s disease in his childhood.

Electronic supplementary material

The online version of this article (doi:10.1007/s12471-011-0150-0) contains supplementary material, which is available to authorized users.     

VoroMQA: Assessment of protein structure quality using interatomic contact areas

In the absence of experimentally determined protein structure many biological questions can be addressed using computational structural models. However, the utility of protein structural models depends on their quality. Therefore, the estimation of the quality of predicted structures is an important problem. One of the approaches to this problem is the use of knowledge‐based statistical potentials. Such methods typically rely on the statistics of distances and angles of residue‐residue or atom‐atom interactions collected from experimentally determined structures. Here, we present VoroMQA (Voronoi tessellation‐based Model Quality Assessment), a new method for the estimation of protein structure quality. Our method combines the idea of statistical potentials with the use of interatomic contact areas instead of distances. Contact areas, derived using Voronoi tessellation of protein structure, are used to describe and seamlessly integrate both explicit interactions between protein atoms and implicit interactions of protein atoms with solvent. VoroMQA produces scores at atomic, residue, and global levels, all in the fixed range from 0 to 1. The method was tested on the CASP data and compared to several other single‐model quality assessment methods. VoroMQA showed strong performance in the recognition of the native structure and in the structural model selection tests, thus demonstrating the efficacy of interatomic contact areas in estimating protein structure quality. The software implementation of VoroMQA is freely available as a standalone application and as a web server at http://bioinformatics.lt/software/voromqa . Proteins 2017; 85:1131–1145. © 2017 Wiley Periodicals, Inc.     

Evolution of protein specificity: insights from ancestral protein reconstruction

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FRASystem: fault tolerant system using agents in distributed computing systems

In this paper, we present a fault tolerant and recovery system called FRASystem (Fault Tolerant & Recovery Agent System) using multi-agent in distributed computing systems. Previous rollback-recovery protocols were dependent on an inherent communication and an underlying operating system, which caused a decline of computing performance. We propose a rollback-recovery protocol that works independently on an operating system and leads to an increasing portability and extensibility. We define four types of agents: (1) a recovery agent performs a rollback-recovery protocol after a failure, (2) an information agent constructs domain knowledge as a rule of fault tolerance and information during a failure-free operation, (3) a facilitator agent controls the communication between agents, (4) a garbage collection agent performs garbage collection of the useless fault tolerance information. Since agent failures may lead to inconsistent states of a system and a domino effect, we propose an agent recovery algorithm. A garbage collection protocol addresses the performance degradation caused by the increment of saved fault tolerance information in a stable storage. We implemented a prototype of FRASystem using Java and CORBA and experimented the proposed rollback-recovery protocol. The simulations results indicate that the performance of our protocol is better than previous rollback-recovery protocols which use independent checkpointing and pessimistic message logging without using agents. Our contributions are as follows: (1) this is the first rollback-recovery protocol using agents, (2) FRASystem is not dependent on an operating system, and (3) FRASystem provides a portability and extensibility.