Improved estimation of structure predictor quality

Background  

Methods that can automatically assess the quality of computationally predicted protein structures are important, as they enable the selection of the most accurate structure from an ensemble of predictions. Assessment methods that determine the quality of a predicted structure by comparing it against the various structures predicted by different servers have been shown to outperform approaches that rely on the intrinsic characteristics of the structure itself.     

Assessment of methods for amino acid matrix selection and their use on empirical data shows that ad hoc assumptions for choice of matrix are not justified

Background  

In recent years, model based approaches such as maximum likelihood have become the methods of choice for constructing phylogenies. A number of authors have shown the importance of using adequate substitution models in order to produce accurate phylogenies. In the past, many empirical models of amino acid substitution have been derived using a variety of different methods and protein datasets. These matrices are normally used as surrogates, rather than deriving the maximum likelihood model from the dataset being examined. With few exceptions, selection between alternative matrices has been carried out in an ad hoc manner.     

Splitting statistical potentials into meaningful scoring functions: Testing the prediction of near-native structures from decoy conformations

Background  

Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both.     

Ab initio modeling of small proteins by iterative TASSER simulations

Background  

Predicting 3-dimensional protein structures from amino-acid sequences is an important unsolved problem in computational structural biology. The problem becomes relatively easier if close homologous proteins have been solved, as high-resolution models can be built by aligning target sequences to the solved homologous structures. However, for sequences without similar folds in the Protein Data Bank (PDB) library, the models have to be predicted from scratch. Progress in the ab initio structure modeling is slow. The aim of this study was to extend the TASSER (threading/assembly/refinement) method for the ab initio modeling and examine systemically its ability to fold small single-domain proteins.     

An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem

Background  

The protein folding problem is a fundamental problems in computational molecular biology and biochemical physics. Various optimisation methods have been applied to formulations of the ab-initio folding problem that are based on reduced models of protein structure, including Monte Carlo methods, Evolutionary Algorithms, Tabu Search and hybrid approaches. In our work, we have introduced an ant colony optimisation (ACO) algorithm to address the non-deterministic polynomial-time hard (NP-hard) combinatorial problem of predicting a protein's conformation from its amino acid sequence under a widely studied, conceptually simple model – the 2-dimensional (2D) and 3-dimensional (3D) hydrophobic-polar (HP) model.     

Comparative modelling by restraint-based conformational sampling

Background  

Although comparative modelling is routinely used to produce three-dimensional models of proteins, very few automated approaches are formulated in a way that allows inclusion of restraints derived from experimental data as well as those from the structures of homologues. Furthermore, proteins are usually described as a single conformer, rather than an ensemble that represents the heterogeneity and inaccuracy of experimentally determined protein structures. Here we address these issues by exploring the application of the restraint-based conformational space search engine, RAPPER, which has previously been developed for rebuilding experimentally defined protein structures and for fitting models to electron density derived from X-ray diffraction analyses.     

A conformation ensemble approach to protein residue-residue contact

Background

Protein residue-residue contact prediction is important for protein model generation and model evaluation. Here we develop a conformation ensemble approach to improve residue-residue contact prediction. We collect a number of structural models stemming from a variety of methods and implementations. The various models capture slightly different conformations and contain complementary information which can be pooled together to capture recurrent, and therefore more likely, residue-residue contacts.

Results

We applied our conformation ensemble approach to free modeling targets from both CASP8 and CASP9. Given a diverse ensemble of models, the method is able to achieve accuracies of. 48 for the top L/5 medium range contacts and. 36 for the top L/5 long range contacts for CASP8 targets (L being the target domain length). When applied to targets from CASP9, the accuracies of the top L/5 medium and long range contact predictions were. 34 and. 30 respectively.

Conclusions

When operating on a moderately diverse ensemble of models, the conformation ensemble approach is an effective means to identify medium and long range residue-residue contacts. An immediate benefit of the method is that when tied with a scoring scheme, it can be used to successfully rank models.     

FlexSnap: Flexible Non-sequential Protein Structure Alignment

Background  

Proteins have evolved subject to energetic selection pressure for stability and flexibility. Structural similarity between proteins that have gone through conformational changes can be captured effectively if flexibility is considered. Topologically unrelated proteins that preserve secondary structure packing interactions can be detected if both flexibility and Sequential permutations are considered. We propose the FlexSnap algorithm for flexible non-topological protein structural alignment.     

Structural motifs recurring in different folds recognize the same ligand fragments

Background  

The structural analysis of protein ligand binding sites can provide information relevant for assigning functions to unknown proteins, to guide the drug discovery process and to infer relations among distant protein folds. Previous approaches to the comparative analysis of binding pockets have usually been focused either on the ligand or the protein component. Even though several useful observations have been made with these approaches they both have limitations. In the former case the analysis is restricted to binding pockets interacting with similar ligands, while in the latter it is difficult to systematically check whether the observed structural similarities have a functional significance.     

dConsensus: a tool for displaying domain assignments by multiple structure-based algorithms and for construction of a consensus assignment

Background  

Partitioning of a protein into structural components, known as domains, is an important initial step in protein classification and for functional and evolutionary studies. While the systematic assignments of domains by human experts exist (CATH and SCOP), the introduction of high throughput technologies for structure determination threatens to overwhelm expert approaches. A variety of algorithmic methods have been developed to expedite this process, allowing almost instant structural decomposition into domains. The performance of algorithmic methods can approach 85% agreement on the number of domains with the consensus reached by experts. However, each algorithm takes a somewhat different conceptual approach, each with unique strengths and weaknesses. Currently there is no simple way to automatically compare assignments from different structure-based domain assignment methods, thereby providing a comprehensive understanding of possible structure partitioning as well as providing some insight into the tendencies of particular algorithms. Most importantly, a consensus assignment drawn from multiple assignment methods can provide a singular and presumably more accurate view.     

Selection for the compactness of highly expressed genes in <Emphasis Type="Italic">Gallus gallus</Emphasis>

Background  

Coding sequence (CDS) length, gene size, and intron length vary within a genome and among genomes. Previous studies in diverse organisms, including human, D. Melanogaster, C. elegans, S. cerevisiae, and Arabidopsis thaliana, indicated that there are negative relationships between expression level and gene size, CDS length as well as intron length. Different models such as selection for economy model, genomic design model, and mutational bias hypotheses have been proposed to explain such observation. The debate of which model is a superior one to explain the observation has not been settled down. The chicken (Gallus gallus) is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. As D. Melanogaster, chicken has a larger effective population size, selection for chicken genome is expected to be more effective in increasing protein synthesis efficiency. Therefore, in this study the chicken was used as a model organism to elucidate the interaction between gene features and expression pattern upon selection pressure.     

A computational survey of candidate exonic splicing enhancer motifs in the model plant <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis>

Background  

Algorithmic approaches to splice site prediction have relied mainly on the consensus patterns found at the boundaries between protein coding and non-coding regions. However exonic splicing enhancers have been shown to enhance the utilization of nearby splice sites.     

Evaluation of 3D-Jury on CASP7 models

Background  

3D-Jury, the structure prediction consensus method publicly available in the Meta Server , was evaluated using models gathered in the 7 ^th round of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7). 3D-Jury is an automated expert process that generates protein structure meta-predictions from sets of models obtained from partner servers.     

Identification of consensus RNA secondary structures using suffix arrays

Background  

The identification of a consensus RNA motif often consists in finding a conserved secondary structure with minimum free energy in an ensemble of aligned sequences. However, an alignment is often difficult to obtain without prior structural information. Thus the need for tools to automate this process.     

A <Emphasis Type="Italic">Bacillus thuringiensis</Emphasis> isolation method utilizing a novel stain,low selection and high throughput produced atypical results

Background  

Bacillus thuringiensis is a bacterium known for producing protein crystals with insecticidal properties. These toxins are widely sought after for controlling agricultural pests due to both their specificity and their applicability in transgenic plants. There is great interest in isolating strains with improved or novel toxin characteristics, however isolating B. thuringiensis from the environment is time consuming and yields relatively few isolates of interest. New approaches to B. thuringiensis isolation have been, and continue to be sought. In this report, candidate B. thuringiensis isolates were recovered from environmental samples using a combination of a novel stain, high throughput and reduced selection. Isolates were further characterized by SDS-PAGE, light microscopy, PCR, probe hybridization, and with selected isolates, DNA sequencing, bioassay or Electron Microscopy.     

Gene ontology based transfer learning for protein subcellular localization

Background  

Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology.     

Fast optimization of statistical potentials for structurally constrained phylogenetic models

Background  

Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC) models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms.     

The chaperone DnaK controls the fractioning of functional protein between soluble and insoluble cell fractions in inclusion body-forming cells

Background  

The molecular mechanics of inclusion body formation is still far from being completely understood, specially regarding the occurrence of properly folded, protein species that exhibit natural biological activities. We have here comparatively explored thermally promoted, in vivo protein aggregation and the formation of bacterial inclusion bodies, from both structural and functional sides. Also, the status of the soluble and insoluble protein versions in both aggregation systems have been examined as well as the role of the main molecular chaperones GroEL and DnaK in the conformational quality of the target polypeptide.     

A structural model for the adduct between cytochrome c and cytochrome c oxidase

An ensemble of structural models of the adduct between cytochrome c and cytochrome c oxidase from Paracoccus denitrificans has been calculated based on the experimental data from site-directed mutagenesis and NMR experiments that have accumulated over the last years of research on this system. The residues from each protein that are at the protein–protein interface have been identified by the above experimental work, and this information has been converted in a series of restraints explicitly used in calculations. It is found that a single static structural model cannot satisfy all experimental data simultaneously. Therefore, it is proposed that the adduct exists as a dynamic ensemble of different orientations in equilibrium, and may be represented by a combination or average of the various limiting conformations calculated here. The equilibrium involves both conformations that are competent for electron transfer and conformations that are not. Long-range recognition of the partners is driven by non-specific electrostatic interactions, while at shorter distances hydrophobic contacts tune the reciprocal orientation. Electron transfer from cytochrome bc ₁ to cytochrome c oxidase is mediated through cytochrome c experiencing multiple encounters with both of its partners, only part of which are productive. The number of encounters, and thus the electron transfer rate, may be increased by the formation of a cytochrome bc ₁–cytochrome c oxidase supercomplex and/or (in human) by increasing the concentration of the two enzymes in the membrane space. Protein Data Bank Accession numbers The coordinates of the five best structural models for each of the four clusters have been deposited in the Protein Data Bank (PDB ID 1ZYY).     

Using equilibrium frequencies in models of sequence evolution

Background  

The f factor is a new parameter for accommodating the influence of both the starting and ending states in the rate matrices of "generalized weighted frequencies" (+gwF) models for sequence evolution. In this study, we derive an expected value for f, starting from a nearly neutral model of weak selection, and then assess the biological interpretation of this factor with evolutionary simulations.