Using diffusion distances for flexible molecular shape comparison

Background  

Many molecules are flexible and undergo significant shape deformation as part of their function, and yet most existing molecular shape comparison (MSC) methods treat them as rigid bodies, which may lead to incorrect shape recognition.     

A comparative study of protein synthesis in <Emphasis Type="Italic">in vitro</Emphasis> systems: from the prokaryotic reconstituted to the eukaryotic extract-based

Background  

Cell-free protein synthesis is not only a rapid and high throughput technology to obtain proteins from their genes, but also provides an in vitro platform to study protein translation and folding. A detailed comparison of in vitro protein synthesis in different cell-free systems may provide insights to their biological differences and guidelines for their applications.     

Comparative Analysis of Protein Structure Alignments

Background  

Several methods are currently available for the comparison of protein structures. These methods have been analysed regarding the performance in the identification of structurally/evolutionary related proteins, but so far there has been less focus on the objective comparison between the alignments produced by different methods.     

PocketMatch: A new algorithm to compare binding sites in protein structures

Background  

Recognizing similarities and deriving relationships among protein molecules is a fundamental requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison.     

An aggregate analysis of many predicted structures to reduce errors in protein structure comparison caused by conformational flexibility

Background

Conformational flexibility creates errors in the comparison of protein structures. Even small changes in backbone or sidechain conformation can radically alter the shape of ligand binding cavities. These changes can cause structure comparison programs to overlook functionally related proteins with remote evolutionary similarities, and cause others to incorrectly conclude that closely related proteins have different binding preferences, when their specificities are actually similar. Towards the latter effort, this paper applies protein structure prediction algorithms to enhance the classification of homologous proteins according to their binding preferences, despite radical conformational differences.

Methods

Specifically, structure prediction algorithms can be used to "remodel" existing structures against the same template. This process can return proteins in very different conformations to similar, objectively comparable states. Operating on close homologs exploits the accuracy of structure predictions on closely related proteins, but structure prediction is often a nondeterministic process. Identical inputs can generate subtly different models with very different binding cavities that make structure comparison difficult. We present a first method to mitigate such errors, called "medial remodeling", that examines a large number of predicted structures to eliminate extreme models of the same binding cavity.

Results

Our results, on the enolase and tyrosine kinase superfamilies, demonstrate that remodeling can enable proteins in very different conformations to be returned to states that can be objectively compared. Structures that would have been erroneously classified as having different binding preferences were often correctly classified after remodeling, while structures that would have been correctly classified as having different binding preferences almost always remained distinct. The enolase superfamily, which exhibited less sequential diversity than the tyrosine kinase superfamily, was classified more accurately after remodeling than the tyrosine kinases. Medial remodeling reduced errors from models with unusual perturbations that distort the shape of the binding site, enhancing classification accuracy.

Conclusions

This paper demonstrates that protein structure prediction can compensate for conformational variety in the comparison of protein-ligand binding sites. While protein structure prediction introduces new uncertainties into the structure comparison problem, our results indicate that unusual models can be ignored through an analysis of many models, using techniques like medial remodeling. These results point to applications of protein structure comparison that extend beyond existing crystal structures.

     

A simple dependence between protein evolution rate and the number of protein-protein interactions

Background  

It has been shown for an evolutionarily distant genomic comparison that the number of protein-protein interactions a protein has correlates negatively with their rates of evolution. However, the generality of this observation has recently been challenged. Here we examine the problem using protein-protein interaction data from the yeast Saccharomyces cerevisiae and genome sequences from two other yeast species.     

Multiple evidence for the role of an Ovate-like gene in determining fruit shape in pepper

Background  

Grafting is a widely used technique contributing to sustainable and ecological production of many vegetables, but important fruit quality characters such as taste, aroma, texture and shape are known for years to be affected by grafting in important vegetables species including pepper. From all the characters affected, fruit shape is the most easily observed and measured. From research in tomato, fruit shape is known to be controlled by many QTLs but only few of them have larger effect on fruit shape variance. In this study we used pepper cultivars with different fruit shape to study the role of a pepper Ovate-like gene, CaOvate, which encodes a negative regulator protein that brings significant changes in tomato fruit shape.     

Ab initio and homology based prediction of protein domains by recursive neural networks

Background  

Proteins, especially larger ones, are often composed of individual evolutionary units, domains, which have their own function and structural fold. Predicting domains is an important intermediate step in protein analyses, including the prediction of protein structures.     

<Emphasis Type="Italic">In vivo</Emphasis>analysis of interactions between GFP-labeled microfilaments and plastid stromules

Background  

Plastid stromules are stroma-filled tubules that extend from the surface of plastids in higher plants and allow the exchange of protein molecules between plastids. These structures are highly dynamic; stromules change both their shape and position in the cytoplasm very rapidly. Previous studies with microfilament inhibitors indicated that stromule shape and movement are dependent on the actin cytoskeleton. To learn more about the nature of the interactions of stromules and the cytoskeleton, we imaged fluorescently-labeled microfilaments and plastids.     

An efficient algorithm for protein structure comparison using elastic shape analysis

Background

Protein structure comparison play important role in in silico functional prediction of a new protein. It is also used for understanding the evolutionary relationships among proteins. A variety of methods have been proposed in literature for comparing protein structures but they have their own limitations in terms of accuracy and complexity with respect to computational time and space. There is a need to improve the computational complexity in comparison/alignment of proteins through incorporation of important biological and structural properties in the existing techniques.

Results

An efficient algorithm has been developed for comparing protein structures using elastic shape analysis in which the sequence of 3D coordinates atoms of protein structures supplemented by additional auxiliary information from side-chain properties are incorporated. The protein structure is represented by a special function called square-root velocity function. Furthermore, singular value decomposition and dynamic programming have been employed for optimal rotation and optimal matching of the proteins, respectively. Also, geodesic distance has been calculated and used as the dissimilarity score between two protein structures. The performance of the developed algorithm is tested and found to be more efficient, i.e., running time reduced by 80–90 % without compromising accuracy of comparison when compared with the existing methods. Source codes for different functions have been developed in R. Also, user friendly web-based application called ProtSComp has been developed using above algorithm for comparing protein 3D structures and is accessible free.

Conclusions

The methodology and algorithm developed in this study is taking considerably less computational time without loss of accuracy (Table 2). The proposed algorithm is considering different criteria of representing protein structures using 3D coordinates of atoms and inclusion of residue wise molecular properties as auxiliary information.

     

The LabelHash algorithm for substructure matching

Background  

There is an increasing number of proteins with known structure but unknown function. Determining their function would have a significant impact on understanding diseases and designing new therapeutics. However, experimental protein function determination is expensive and very time-consuming. Computational methods can facilitate function determination by identifying proteins that have high structural and chemical similarity.     

Screening of transgenic proteins expressed in transgenic food crops for the presence of short amino acid sequences identical to potential,IgE – binding linear epitopes of allergens

Background  

Transgenic proteins expressed by genetically modified food crops are evaluated for their potential allergenic properties prior to marketing, among others by identification of short identical amino acid sequences that occur both in the transgenic protein and allergenic proteins. A strategy is proposed, in which the positive outcomes of the sequence comparison with a minimal length of six amino acids are further screened for the presence of potential linear IgE-epitopes. This double track approach involves the use of literature data on IgE-epitopes and an antigenicity prediction algorithm.     

EVEREST: automatic identification and classification of protein domains in all protein sequences

Background  

Proteins are comprised of one or several building blocks, known as domains. Such domains can be classified into families according to their evolutionary origin. Whereas sequencing technologies have advanced immensely in recent years, there are no matching computational methodologies for large-scale determination of protein domains and their boundaries. We provide and rigorously evaluate a novel set of domain families that is automatically generated from sequence data. Our domain family identification process, called EVEREST (EVolutionary Ensembles of REcurrent SegmenTs), begins by constructing a library of protein segments that emerge in an all vs. all pairwise sequence comparison. It then proceeds to cluster these segments into putative domain families. The selection of the best putative families is done using machine learning techniques. A statistical model is then created for each of the chosen families. This procedure is then iterated: the aforementioned statistical models are used to scan all protein sequences, to recreate a library of segments and to cluster them again.     

Neutral evolution of Protein-protein interactions: a computational study using simple models

Background  

Protein-protein interactions are central to cellular organization, and must have appeared at an early stage of evolution. To understand better their role, we consider a simple model of protein evolution and determine the effect of an explicit selection for Protein-protein interactions.     

ROC and confusion analysis of structure comparison methods identify the main causes of divergence from manual protein classification

Background  

Current classification of protein folds are based, ultimately, on visual inspection of similarities. Previous attempts to use computerized structure comparison methods show only partial agreement with curated databases, but have failed to provide detailed statistical and structural analysis of the causes of these divergences.     

Different effects of the probe summarization algorithms PLIER and RMA on high-level analysis of Affymetrix exon arrays

Background  

Alternative splicing is an important mechanism that increases protein diversity and functionality in higher eukaryotes. Affymetrix exon arrays are a commercialized platform used to detect alternative splicing on a genome-wide scale. Two probe summarization algorithms, PLIER (Probe Logarithmic Intensity Error) and RMA (Robust Multichip Average), are commonly used to compute gene-level and exon-level expression values. However, a systematic comparison of these two algorithms on their effects on high-level analysis of the arrays has not yet been reported.     

The evaluation of the factors that cause aggregation during recombinant expression in E. coli is simplified by the employment of an aggregation-sensitive reporter

Background  

The yields of soluble recombinant proteins expressed in bacteria are often low due to the tendency of the heterologous proteins to form aggregates. Therefore, aggregation reporters have been envisaged to simplify the comparison among different expression conditions and to speed up the identification of suitable protocols that improve the solubility. The probe we used is composed by an IbpAB promoter specifically activated by protein aggregates fused to a sequence coding the β-galactosidase, the activity of which becomes, therefore, indicative of the aggregation degree.     

Improving protein structure similarity searches using domain boundaries based on conserved sequence information

Background  

The identification of protein domains plays an important role in protein structure comparison. Domain query size and composition are critical to structure similarity search algorithms such as the Vector Alignment Search Tool (VAST), the method employed for computing related protein structures in NCBI Entrez system. Currently, domains identified on the basis of structural compactness are used for VAST computations. In this study, we have investigated how alternative definitions of domains derived from conserved sequence alignments in the Conserved Domain Database (CDD) would affect the domain comparisons and structure similarity search performance of VAST.