Dataset Information

MFSPSSMpred: identifying short disorder-to-order binding regions in disordered proteins based on contextual local evolutionary conservation.

ABSTRACT: BACKGROUND: Molecular recognition features (MoRFs) are short binding regions located in longer intrinsically disordered protein regions. Although these short regions lack a stable structure in the natural state, they readily undergo disorder-to-order transitions upon binding to their partner molecules. MoRFs play critical roles in the molecular interaction network of a cell, and are associated with many human genetic diseases. Therefore, identification of MoRFs is an important step in understanding functional aspects of these proteins and in finding applications in drug design. RESULTS: Here, we propose a novel method for identifying MoRFs, named as MFSPSSMpred (Masked, Filtered and Smoothed Position-Specific Scoring Matrix-based Predictor). Firstly, a masking method is used to calculate the average local conservation scores of residues within a masking-window length in the position-specific scoring matrix (PSSM). Then, the scores below the average are filtered out. Finally, a smoothing method is used to incorporate the features of flanking regions for each residue to prepare the feature sets for prediction. Our method employs no predicted results from other classifiers as input, i.e., all features used in this method are extracted from the PSSM of sequence only. Experimental results show that, comparing with other methods tested on the same datasets, our method achieves the best performance: achieving 0.004~0.079 higher AUC than other methods when tested on TEST419, and achieving 0.045~0.212 higher AUC than other methods when tested on TEST2012. In addition, when tested on an independent membrane proteins-related dataset, MFSPSSMpred significantly outperformed the existing predictor MoRFpred. CONCLUSIONS: This study suggests that: 1) amino acid composition and physicochemical properties in the flanking regions of MoRFs are very different from those in the general non-MoRF regions; 2) MoRFs contain both highly conserved residues and highly variable residues and, on the whole, are highly locally conserved; and 3) combining contextual information with local conservation information of residues facilitates the prediction of MoRFs.

SUBMITTER: Fang C

PROVIDER: S-EPMC3853019 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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MFSPSSMpred: identifying short disorder-to-order binding regions in disordered proteins based on contextual local evolutionary conservation.

Fang Chun C Noguchi Tamotsu T Tominaga Daisuke D Yamana Hayato H

BMC bioinformatics 20131004

<h4>Background</h4>Molecular recognition features (MoRFs) are short binding regions located in longer intrinsically disordered protein regions. Although these short regions lack a stable structure in the natural state, they readily undergo disorder-to-order transitions upon binding to their partner molecules. MoRFs play critical roles in the molecular interaction network of a cell, and are associated with many human genetic diseases. Therefore, identification of MoRFs is an important step in und ...[more]

PMID: 24093637

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Project description:The landscape of the human genome consists of millions of short islands of conservation that are 100% conserved across multiple vertebrate genomes (termed "bricks"), the majority of which are located in noncoding regions. Several hundred thousand bricks are deeply conserved reaching the genomes of amphibians and fish. Deep phylogenetic conservation of noncoding DNA has been reported to be strongly associated with the presence of gene regulatory elements, introducing bricks as a proxy to the functional noncoding landscape of the human genome. Here, we report a significant overrepresentation of bricks in the promoters of transcription factors and developmental genes, where the high level of phylogenetic conservation correlates with an increase in brick overrepresentation. We also found that the presence of a brick dictates a predisposition to evolutionary constraint, with only 0.7% of the amniota brick central nucleotides being diverged within the primate lineage--an 11-fold reduction in the divergence rate compared with random expectation. Human single-nucleotide polymorphism (SNP) data explains only 3% of primate-specific variation in amniota bricks, thus arguing for a widespread fixation of brick mutations within the primate lineage and prior to human radiation. This variation, in turn, might have been utilized as a driving force for primate- and hominoid-specific adaptation. We also discovered a pronounced deviation from the evolutionary predisposition in the human lineage, with over 20-fold increase in the substitution rate at brick SNP sites over expected values. In addition, contrary to typical brick mutations, brick variation commonly encountered in the human population displays limited, if any, signatures of negative selection as measured by the minor allele frequency and population differentiation (F-statistical measure) measures. These observations argue for the plasticity of gene regulatory mechanisms in vertebrates--with evidence of strong purifying selection acting on the gene regulatory landscape of the human genome, where widespread advantageous mutations in putative regulatory elements are likely utilized in functional diversification and adaptation of species.

Project description:The focus of the computational structural biology community has taken a dramatic shift over the past one-and-a-half decades from the classical protein structure prediction problem to the possible understanding of intrinsically disordered proteins (IDP) or proteins containing regions of disorder (IDPR). The current interest lies in the unraveling of a disorder-to-order transitioning code embedded in the amino acid sequences of IDPs/IDPRs. Disordered proteins are characterized by an enormous amount of structural plasticity which makes them promiscuous in binding to different partners, multi-functional in cellular activity and atypical in folding energy landscapes resembling partially folded molten globules. Also, their involvement in several deadly human diseases (e.g. cancer, cardiovascular and neurodegenerative diseases) makes them attractive drug targets, and important for a biochemical understanding of the disease(s). The study of the structural ensemble of IDPs is rather difficult, in particular for transient interactions. When bound to a structured partner, an IDPR adapts an ordered conformation in the complex. The residues that undergo this disorder-to-order transition are called protean residues, generally found in short contiguous stretches and the first step in understanding the modus operandi of an IDP/IDPR would be to predict these residues. There are a few available methods which predict these protean segments from their amino acid sequences; however, their performance reported in the literature leaves clear room for improvement. With this background, the current study presents 'Proteus', a random forest classifier that predicts the likelihood of a residue undergoing a disorder-to-order transition upon binding to a potential partner protein. The prediction is based on features that can be calculated using the amino acid sequence alone. Proteus compares favorably with existing methods predicting twice as many true positives as the second best method (55 vs. 27%) with a much higher precision on an independent data set. The current study also sheds some light on a possible 'disorder-to-order' transitioning consensus, untangled, yet embedded in the amino acid sequence of IDPs. Some guidelines have also been suggested for proceeding with a real-life structural modeling involving an IDPR using Proteus.

Dataset Information

MFSPSSMpred: identifying short disorder-to-order binding regions in disordered proteins based on contextual local evolutionary conservation.

Publications

MFSPSSMpred: identifying short disorder-to-order binding regions in disordered proteins based on contextual local evolutionary conservation.

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