Future directions in folding: The multi-state nature of protein structure

All possible protein folding intermediates exist in equilibrium with the native protein at native as well as non-native conditions, with occupation determined by their free energy level. The study of these forms can illuminate the fundamental principles of protein structure and folding. Hydrogen exchange methods can be used to detect and characterize these partially unfolded forms at native conditions and as a function of mild denaturant and temperature. This information illuminates the requirements that govern the ability of kinetic and equilibrium methods to study folding intermediates.     

Towards the high-resolution protein structure prediction. Fast refinement of reduced models with all-atom force field

Background  

Although experimental methods for determining protein structure are providing high resolution structures, they cannot keep the pace at which amino acid sequences are resolved on the scale of entire genomes. For a considerable fraction of proteins whose structures will not be determined experimentally, computational methods can provide valuable information. The value of structural models in biological research depends critically on their quality. Development of high-accuracy computational methods that reliably generate near-experimental quality structural models is an important, unsolved problem in the protein structure modeling.     

Advances and challenges in analytical characterization of biotechnology products: mass spectrometry-based approaches to study properties and behavior of protein therapeutics

Biopharmaceuticals are a unique class of medicines due to their extreme structural complexity. The structure of these therapeutic proteins is critically important for their efficacy and safety, and the ability to characterize it at various levels (from sequence to conformation) is critical not only at the quality control stage, but also throughout the discovery and design stages. Biological mass spectrometry (MS) offers a variety of approaches to study structure and behavior of complex protein drugs and has already become a default tool for characterizing the covalent structure of protein therapeutics, including sequence and post-translational modifications. Recently, MS-based methods have also begun enjoying a dramatic growth in popularity as a means to provide information on higher order structure and dynamics of biotechnology products. In particular, hydrogen/deuterium exchange MS and charge state distribution analysis of protein ions in electrospray ionization (ESI) MS offer a convenient way to assess the integrity of protein conformation. Native ESI MS also allows the interactions of protein drugs with their therapeutic targets and other physiological partners to be monitored using simple model systems. MS-based methods are also applied to study pharmacokinetics of biopharmaceutical products, where they begin to rival traditional immunoassays. MS already provides valuable support to all stages of development of biopharmaceuticals, from discovery to post-approval monitoring, and its impact on the field of biopharmaceutical analysis will undoubtedly continue to grow.     

Reliability of assessment of protein structure prediction methods

The reliability of ranking of protein structure modeling methods is assessed. The assessment is based on the parametric Student's t test and the nonparametric Wilcox signed rank test of statistical significance of the difference between paired samples. The approach is applied to the ranking of the comparative modeling methods tested at the fourth meeting on Critical Assessment of Techniques for Protein Structure Prediction (CASP). It is shown that the 14 CASP4 test sequences may not be sufficient to reliably distinguish between the top eight methods, given the model quality differences and their standard deviations. We suggest that CASP needs to be supplemented by an assessment of protein structure prediction methods that is automated, continuous in time, based on several criteria applied to a large number of models, and with quantitative statistical reliability assigned to each characterization.     

Hydrogen exchange: the modern legacy of Linderstrøm-Lang.

This discussion, prepared for the Protein Society's symposium honoring the 100th anniversary of Kaj Linderstrøm-Lang, shows how hydrogen exchange approaches initially conceived and implemented by Lang and his colleagues some 50 years ago are contributing to current progress in structural biology. Examples are chosen from the active protein folding field. Hydrogen exchange methods now make it possible to define the structure of protein folding intermediates in various contexts: as tenuous molten globule forms at equilibrium under destabilizing conditions, in kinetic intermediates that exist for less than one second, and as infinitesimally populated excited state forms under native conditions. More generally, similar methods now find broad application in studies of protein structure, energetics, and interactions. This article considers the rise of these capabilities from their inception at the Carlsberg Labs to their contemporary role as a significant tool of modern structural biology.     

Flexibility observed in high resolution structures of <Emphasis Type="Italic">Streptomyces aureofaciens</Emphasis> ribonucleases determined by diffraction methods

It has been widely accepted to distinguish between static structures determined by diffraction methods and dynamic structures determined by nuclear magnetic resonance (NMR). The dynamics of NMR structures is demonstrated by an ensemble of a number of overlaid structures. This cannot be seen in one structure determined by diffraction methods. However, it is possible to see the flexibility of a protein molecule in a number of structures of the same protein determined by X-ray techniques which is manifested by different conformations of main-chain. Multiple protein structure determination does not provide identical structures as a result of various factors including flexibility. Overlap of structures of a protein determined at atomic resolution with high accuracy shows that the root-mean-square deviations (rmsd) of main-chain atoms exceed several fold the accuracy of the positional parameters of each structure. Overlap of a number of structures of a protein determined by diffraction methods shows a similar distribution as that determined by NMR. These observations are demonstrated using high resolution structures of Streptomyces aureofaciens ribonucleases, their mutants and complexes with ligands.     

GWYRE: A Resource for Mapping Variants onto Experimental and Modeled Structures of Human Protein Complexes

Rapid progress in structural modeling of proteins and their interactions is powered by advances in knowledge-based methodologies along with better understanding of physical principles of protein structure and function. The pool of structural data for modeling of proteins and protein–protein complexes is constantly increasing due to the rapid growth of protein interaction databases and Protein Data Bank. The GWYRE (Genome Wide PhYRE) project capitalizes on these developments by advancing and applying new powerful modeling methodologies to structural modeling of protein–protein interactions and genetic variation. The methods integrate knowledge-based tertiary structure prediction using Phyre2 and quaternary structure prediction using template-based docking by a full-structure alignment protocol to generate models for binary complexes. The predictions are incorporated in a comprehensive public resource for structural characterization of the human interactome and the location of human genetic variants. The GWYRE resource facilitates better understanding of principles of protein interaction and structure/function relationships. The resource is available at http://www.gwyre.org.     

Electron cryomicroscopy methods.

Electron cryomicroscopy methods comprise a rapidly expanding field providing insights into the structure and function of biological macromolecules and their supramolecular assemblies. The 3.8 A resolution structure of the membrane protein aquaporin, a view of the herpesvirus capsid at 8.5 A and the 10 A resolution structure of the spliceosomal U1 small nuclear ribonucleoprotein complex are three outstanding examples emphasizing the versatility of this technique.     

Protein Extraction and Fingerprinting Optimization of Bacterial Communities in Natural Environment

Recent development in molecular approaches allows access to genetic structure and diversity of indigenous microbial communities. In contrast, the functional analysis of microorganisms in their environment is still hampered by methodological limitations. Analysis of total proteins expressed at the whole community level (metaproteome) has been proposed to characterize the functional structure of microbial communities in their environment. However, developments are still required to perform such analysis. Our aim was to optimize methods to extract and characterize metaproteome of indigenous microbial communities. Experiments were first conducted in monoxenic bacterial cultures, and various methods were examined to define a procedure of protein extraction ensuring an efficient recovery regardless of the taxonomic affiliation of the cells. These developments were next applied to characterize the metaproteome from indigenous bacterial communities in freshwater samples. Bacterial cells were recovered from water using a high-speed density gradient centrifugation method before protein extraction and fingerprinting. The reactivity and sensitivity of this metaproteomic approach were tested by analyzing the variations of protein fingerprints according to perturbations (cadmium or mercury contamination). The genetic structure of the corresponding communities was also characterized by automated ribosomal spacer analysis (ARISA) DNA fingerprinting. Both protein and DNA fingerprints were statistically analyzed. Results obtained showed that the method developed for protein recovery and fingerprinting was efficient, sensitive, and reproducible. Both the functional and genetic structures of the freshwater bacterial community were complex and varied with perturbations. These variations occurred at both population and protein expression levels and were specific to the perturbation applied.     

Ab initio 3-D structure prediction of an artificially designed three-alpha-helix bundle via all-atom molecular dynamics simulations

The rate at which knowledge about genomic sequences and their protein products is produced is increasing much faster than the rate of 3-dimensional protein structure determination by experimental methods, such as X-ray diffraction and nuclear magnetic resonance. One of the major challenges in structural bioinformatics is the conversion of genomic sequences into useful information, such as characterization of protein structure and function. Using molecular dynamics (MD) simulations, we predicted the 3-dimensional structure of an artificially designed three- alpha -helix bundle, called A3, from a fully extended initial conformation, based on its amino acid sequence. The MD protocol enabled us to obtain the secondary, in 1.0 ns, as well as the supersecondary and tertiary structures, in 4.0-10.0 ns, of A3, much faster than previously described for a similar protein system. The structure obtained at the end of the 10.0-ns MD simulation was topologically a three-alpha-helix bundle.     

A comprehensive overview of computational protein disorder prediction methods

Over the past decade there has been a growing acknowledgement that a large proportion of proteins within most proteomes contain disordered regions. Disordered regions are segments of the protein chain which do not adopt a stable structure. Recognition of disordered regions in a protein is of great importance for protein structure prediction, protein structure determination and function annotation as these regions have a close relationship with protein expression and functionality. As a result, a great many protein disorder prediction methods have been developed so far. Here, we present an overview of current protein disorder prediction methods including an analysis of their advantages and shortcomings. In order to help users to select alternative tools under different circumstances, we also evaluate 23 disorder predictors on the benchmark data of the most recent round of the Critical Assessment of protein Structure Prediction (CASP) and assess their accuracy using several complementary measures.     

Topology prediction of Brucella abortus Omp2b and Omp2a porins after critical assessment of transmembrane beta strands prediction by several secondary structure prediction methods

In order to propose a reliable model for Brucella porin topology, several structure prediction methods were evaluated in their ability to predict porin topology. Four porins of known structure were selected as test-cases and their secondary structure delineated. The specificity and sensitivity of 11 methods were separately evaluated. Our critical assessment shows that some secondary structure prediction methods (PHD, Dsc, Sopma) originally designed to predict globular protein structure are useful on porin topology prediction. The overall best prediction is obtained by combining these three "generalist" methods with a transmembrane beta strand prediction technique. This "consensus" method was applied to Brucella porins Omp2b and Omp2a, sharing no sequence homology with any other porin. The predicted topology is a 16-stranded antiparallel beta barrel with Omp2a showing a higher number of negatively charged residue in the exposed loops than Omp2b. Experiments are in progress to validate the proposed topology and the functional hypotheses. The ability of the proposed consensus method to predict topology of complex outer membrane protein is briefly discussed.     

Improved prediction for N-termini of alpha-helices using empirical information

The prediction of the secondary structure of proteins from their amino acid sequences remains a key component of many approaches to the protein folding problem. The most abundant form of regular secondary structure in proteins is the alpha-helix, in which specific residue preferences exist at the N-terminal locations. Propensities derived from these observed amino acid frequencies in the Protein Data Bank (PDB) database correlate well with experimental free energies measured for residues at different N-terminal positions in alanine-based peptides. We report a novel method to exploit this data to improve protein secondary structure prediction through identification of the correct N-terminal sequences in alpha-helices, based on existing popular methods for secondary structure prediction. With this algorithm, the number of correctly predicted alpha-helix start positions was improved from 30% to 38%, while the overall prediction accuracy (Q3) remained the same, using cross-validated testing. Although the algorithm was developed and tested on multiple sequence alignment-based secondary structure predictions, it was also able to improve the predictions of start locations by methods that use single sequences to make their predictions. Furthermore, the residue frequencies at N-terminal positions of the improved predictions better reflect those seen at the N-terminal positions of alpha-helices in proteins. This has implications for areas such as comparative modeling, where a more accurate prediction of the N-terminal regions of alpha-helices should benefit attempts to model adjacent loop regions. The algorithm is available as a Web tool, located at http://rocky.bms.umist.ac.uk/elephant.     

The PSIPRED protein structure prediction server

SUMMARY: The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method. AVAILABILITY: Freely available to non-commercial users at http://globin.bio.warwick.ac.uk/psipred/     

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.     

cGMP-dependent protein kinases: properties, regulation and biological role

The data available in literature on properties, methods of regulation and biological role of cGMP-dependent protein kinases are analyzed and generalized. Evidence on distribution of these enzymes in different tissues and intracellular compartments is presented. Physicochemical properties of cGMP-dependent protein kinases from different sources are analyzed. Peculiarities of their primary structure, regulation of their activity at the expense of autophosphorylation as well as in the presence of the modulator protein, metal ions and other factors are considered. These data permit postulating importance of cGMP-dependent phosphorylation in some physiological and biochemical processes.     

Index-based similarity search for protein structure databases

We propose new methods for finding similarities in protein structure databases. These methods extract feature vectors on triplets of SSEs (Secondary Structure Elements) of proteins. The feature vectors are then indexed using a multidimensional index structure. Our first technique considers the problem of finding proteins similar to a given query protein in a protein dataset. It quickly finds promising proteins using the index structure. These proteins are then aligned to the query protein using a popular pairwise alignment tool such as VAST. We also develop a novel statistical model to estimate the goodness of a match using the SSEs. Our second technique considers the problem of joining two protein datasets to find an all-to-all similarity. Experimental results show that our techniques improve the pruning time of VAST 3 to 3.5 times, while keeping the sensitivity similar. Our technique can also be incorporated with DALI and CE to improve their running times by a factor of 2 and 2.7 respectively. The software is available online at http://bioserver.cs.ucsb.edu/.     

A topological algorithm for identification of structural domains of proteins

Background  

Identification of the structural domains of proteins is important for our understanding of the organizational principles and mechanisms of protein folding, and for insights into protein function and evolution. Algorithmic methods of dissecting protein of known structure into domains developed so far are based on an examination of multiple geometrical, physical and topological features. Successful as many of these approaches are, they employ a lot of heuristics, and it is not clear whether they illuminate any deep underlying principles of protein domain organization. Other well-performing domain dissection methods rely on comparative sequence analysis. These methods are applicable to sequences with known and unknown structure alike, and their success highlights a fundamental principle of protein modularity, but this does not directly improve our understanding of protein spatial structure.     

What are the baselines for protein fold recognition?

MOTIVATION: What constitutes a baseline level of success for protein fold recognition methods? As fold recognition benchmarks are often presented without any thought to the results that might be expected from a purely random set of predictions, an analysis of fold recognition baselines is long overdue. Given varying amounts of basic information about a protein-ranging from the length of the sequence to a knowledge of its secondary structure-to what extent can the fold be determined by intelligent guesswork? Can simple methods that make use of secondary structure information assign folds more accurately than purely random methods and could these methods be used to construct viable hierarchical classifications? EXPERIMENTS PERFORMED: A number of rapid automatic methods which score similarities between protein domains were devised and tested. These methods ranged from those that incorporated no secondary structure information, such as measuring absolute differences in sequence lengths, to more complex alignments of secondary structure elements. Each method was assessed for accuracy by comparison with the Class Architecture Topology Homology (CATH) classification. Methods were rated against both a random baseline fold assignment method as a lower control and FSSP as an upper control. Similarity trees were constructed in order to evaluate the accuracy of optimum methods at producing a classification of structure. RESULTS: Using a rigorous comparison of methods with CATH, the random fold assignment method set a lower baseline of 11% true positives allowing for 3% false positives and FSSP set an upper benchmark of 47% true positives at 3% false positives. The optimum secondary structure alignment method used here achieved 27% true positives at 3% false positives. Using a less rigorous Critical Assessment of Structure Prediction (CASP)-like sensitivity measurement the random assignment achieved 6%, FSSP-59% and the optimum secondary structure alignment method-32%. Similarity trees produced by the optimum method illustrate that these methods cannot be used alone to produce a viable protein structural classification system. CONCLUSIONS: Simple methods that use perfect secondary structure information to assign folds cannot produce an accurate protein taxonomy, however they do provide useful baselines for fold recognition. In terms of a typical CASP assessment our results suggest that approximately 6% of targets with folds in the databases could be assigned correctly by randomly guessing, and as many as 32% could be recognised by trivial secondary structure comparison methods, given knowledge of their correct secondary structures.     

蛋白质共进化分析研究进展

一些对蛋白质活性很重要的残基在进化过程中是高度保守的,另有一些残基通过共进化来维持蛋白质结构和功能上的稳定。由于共进化残基分析可在未知蛋白质结构时,仅依据序列推断残基间的相互作用,因此在蛋白质结构和功能预测上具有重要的研究意义。当前分析共进化残基的方法主要有基于相关系数的方法、基于微扰理论的方法、参数检验法等。然而,由于存在蛋白质系统进化的背景干扰,目前共进化残基分析的精度仍有待进一步提高。本文概述了蛋白质共进化分析的方法及其研究进展,并对其发展趋势进行了预测。