A study on separation of the protein structural types in amino acid sequence feature spaces.
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ABSTRACT:
SUBMITTER: Wan X
PROVIDER: S-EPMC6927603 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND: Protein destabilization is a common mechanism by which amino acid substitutions cause human diseases. Although several machine learning methods have been reported for predicting protein stability changes upon amino acid substitutions, the previous studies did not utilize relevant sequence features representing biological knowledge for classifier construction. RESULTS: In this study, a new machine learning method has been developed for sequence feature-based prediction of protein stability changes upon amino acid substitutions. Support vector machines were trained with data from experimental studies on the free energy change of protein stability upon mutations. To construct accurate classifiers, twenty sequence features were examined for input vector encoding. It was shown that classifier performance varied significantly by using different sequence features. The most accurate classifier in this study was constructed using a combination of six sequence features. This classifier achieved an overall accuracy of 84.59% with 70.29% sensitivity and 90.98% specificity. CONCLUSIONS: Relevant sequence features can be used to accurately predict protein stability changes upon amino acid substitutions. Predictive results at this level of accuracy may provide useful information to distinguish between deleterious and tolerant alterations in disease candidate genes. To make the classifier accessible to the genetics research community, we have developed a new web server, called MuStab (http://bioinfo.ggc.org/mustab/).
| S-EPMC2975416 | biostudies-literature
Project description:Rationally and efficiently modifying the amino-acid sequence of proteins to control their ability to undergo liquid-liquid phase separation (LLPS) on demand is not only highly desirable, but can also help to elucidate which protein features are important for LLPS. Here, we propose a computational method that couples a genetic algorithm to a sequence-dependent coarse-grained protein model to evolve the amino-acid sequences of phase-separating intrinsically disordered protein regions (IDRs), and purposely enhance or inhibit their capacity to phase-separate. We validate the predicted critical solution temperatures of the mutated sequences with ABSINTH, a more accurate all-atom model. We apply the algorithm to the phase-separating IDRs of three naturally occurring proteins, namely FUS, hnRNPA1 and LAF1, as prototypes of regions that exist in cells and undergo homotypic LLPS driven by different types of intermolecular interaction, and we find that the evolution of amino-acid sequences towards enhanced LLPS is driven in these three cases, among other factors, by an increase in the average size of the amino acids. However, the direction of change in the molecular driving forces that enhance LLPS (such as hydrophobicity, aromaticity and charge) depends on the initial amino-acid sequence. Finally, we show that the evolution of amino-acid sequences to modulate LLPS is strongly coupled to the make-up of the medium (e.g. the presence or absence of RNA), which may have significant implications for our understanding of phase separation within the many-component mixtures of biological systems.
| S-EPMC8415608 | biostudies-literature
Project description:In this paper, we use network approaches to analyze the relations between protein sequence features for the top hierarchical classes of CATH and SCOP. We use fundamental connectivity measures such as correlation (CR), normalized mutual information rate (nMIR), and transfer entropy (TE) to analyze the pairwise-relationships between the protein sequence features, and use centrality measures to analyze weighted networks constructed from the relationship matrices. In the centrality analysis, we find both commonalities and differences between the different protein 3D structural classes. Results show that all top hierarchical classes of CATH and SCOP present strong non-deterministic interactions for the composition and arrangement features of Cystine (C), Methionine (M), Tryptophan (W), and also for the arrangement features of Histidine (H). The different protein 3D structural classes present different preferences in terms of their centrality distributions and significant features.
| S-EPMC8006989 | biostudies-literature
Project description:Statistical analysis was carried out on large set of naturally occurring human amino acid variations, and it was demonstrated that there is a preference for some amino acid substitutions to be associated with diseases. At an amino acid sequence level, it was shown that the disease-causing variants frequently involve drastic changes in amino acid physicochemical properties of proteins such as charge, hydrophobicity, and geometry. Structural analysis of variants involved in diseases and being frequently observed in human population showed similar trends: disease-causing variants tend to cause more changes in hydrogen bond network and salt bridges as compared with harmless amino acid mutations. Analysis of thermodynamics data reported in the literature, both experimental and computational, indicated that disease-causing variants tend to destabilize proteins and their interactions, which prompted us to investigate the effects of amino acid mutations on large databases of experimentally measured energy changes in unrelated proteins. Although the experimental datasets were linked neither to diseases nor exclusory to human proteins, the observed trends were the same: amino acid mutations tend to destabilize proteins and their interactions. Having in mind that structural and thermodynamics properties are interrelated, it is pointed out that any large change in any of them is anticipated to cause a disease.
| S-EPMC4409542 | biostudies-literature
Project description:There are more than 500 amino acid substitutions in each human genome, and bioinformatics tools irreplaceably contribute to determination of their functional effects. We have developed feature-based algorithm for the detection of mutations outside conserved functional domains (CFDs) and compared its classification efficacy with the most commonly used phylogeny-based tools, PolyPhen-2 and SIFT. The new algorithm is based on the informational spectrum method (ISM), a feature-based technique, and statistical analysis. Our dataset contained neutral polymorphisms and mutations associated with myeloid malignancies from epigenetic regulators ASXL1, DNMT3A, EZH2, and TET2. PolyPhen-2 and SIFT had significantly lower accuracies in predicting the effects of amino acid substitutions outside CFDs than expected, with especially low sensitivity. On the other hand, only ISM algorithm showed statistically significant classification of these sequences. It outperformed PolyPhen-2 and SIFT by 15% and 13%, respectively. These results suggest that feature-based methods, like ISM, are more suitable for the classification of amino acid substitutions outside CFDs than phylogeny-based tools.
| S-EPMC3855963 | biostudies-literature
Project description:Cytoplasmic streaming with extremely high velocity (∼70 μm s-1) occurs in cells of the characean algae (Chara). Because cytoplasmic streaming is caused by myosin XI, it has been suggested that a myosin XI with a velocity of 70 μm s-1, the fastest myosin measured so far, exists in Chara cells. However, the velocity of the previously cloned Chara corallina myosin XI (CcXI) was about 20 μm s-1, one-third of the cytoplasmic streaming velocity in Chara Recently, the genome sequence of Chara braunii has been published, revealing that this alga has four myosin XI genes. We cloned these four myosin XI (CbXI-1, 2, 3, and 4) and measured their velocities. While the velocities of CbXI-3 and CbXI-4 motor domains (MDs) were similar to that of CcXI MD, the velocities of CbXI-1 and CbXI-2 MDs were 3.2 times and 2.8 times faster than that of CcXI MD, respectively. The velocity of chimeric CbXI-1, a functional, full-length CbXI-1 construct, was 60 μm s-1 These results suggest that CbXI-1 and CbXI-2 would be the main contributors to cytoplasmic streaming in Chara cells and show that these myosins are ultrafast myosins with a velocity 10 times faster than fast skeletal muscle myosins in animals. We also report an atomic structure (2.8-Å resolution) of myosin XI using X-ray crystallography. Based on this crystal structure and the recently published cryo-electron microscopy structure of acto-myosin XI at low resolution (4.3-Å), it appears that the actin-binding region contributes to the fast movement of Chara myosin XI. Mutation experiments of actin-binding surface loops support this hypothesis.
| S-EPMC8872768 | biostudies-literature
Project description:BackgroundGenomic variations may cause deleterious effects on protein functionality and perturb biological processes. Elucidating the effects of variations is critical for developing novel treatment strategies for diseases of genetic origin. Computational approaches have been aiding the work in this field by modeling and analyzing the mutational landscape. However, new approaches are required, especially for accurate representation and data-centric analysis of sequence variations.MethodIn this study, we propose ASCARIS (Annotation and StruCture-bAsed RepresentatIon of Single amino acid variations), a method for the featurization (i.e., quantitative representation) of single amino acid variations (SAVs), which could be used for a variety of purposes, such as predicting their functional effects or building multi-omics-based integrative models. ASCARIS utilizes the direct and spatial correspondence between the location of the SAV on the sequence/structure and 30 different types of positional feature annotations (e.g., active/lipidation/glycosylation sites; calcium/metal/DNA binding, inter/transmembrane regions, etc.), along with structural features and physicochemical properties. The main novelty of this method lies in constructing reusable numerical representations of SAVs via functional annotations.ResultsWe statistically analyzed the relationship between these features and the consequences of variations and found that each carries information in this regard. To investigate potential applications of ASCARIS, we trained variant effect prediction models that utilize our SAV representations as input. We carried out an ablation study and a comparison against the state-of-the-art methods and observed that ASCARIS has a competing and complementary performance against widely-used predictors. ASCARIS can be used alone or in combination with other approaches to represent SAVs from a functional perspective. ASCARIS is available as a programmatic tool at https://github.com/HUBioDataLab/ASCARIS and as a web-service at https://huggingface.co/spaces/HUBioDataLab/ASCARIS.
| S-EPMC10562615 | biostudies-literature
Project description:PrDOS is a server that predicts the disordered regions of a protein from its amino acid sequence (http://prdos.hgc.jp). The server accepts a single protein amino acid sequence, in either plain text or FASTA format. The prediction system is composed of two predictors: a predictor based on local amino acid sequence information and one based on template proteins. The server combines the results of the two predictors and returns a two-state prediction (order/disorder) and a disorder probability for each residue. The prediction results are sent by e-mail, and the server also provides a web-interface to check the results.
| S-EPMC1933209 | biostudies-literature
Project description:The gene encoding the African swine fever virus protein p12, which is involved in virus attachment to the host cell, has been mapped and sequenced in the genome of the Vero-adapted virus strain BA71V. The determination of the N-terminal amino acid sequence and the hybridization of oligonucleotide probes derived from this sequence to cloned restriction fragments allowed the mapping of the gene in fragment EcoRI-O, located in the central region of the viral genome. The DNA sequence of an EcoRI-XbaI fragment showed an open reading frame which is predicted to encode a polypeptide of 61 amino acids. The expression of this open reading frame in rabbit reticulocyte lysates and in Escherichia coli gave rise to a 12-kDa polypeptide that was immunoprecipitated with a monoclonal antibody specific for protein p12. The hydrophilicity profile indicated the existence of a stretch of 22 hydrophobic residues in the central part that may anchor the protein in the virus envelope. Three forms of the protein with apparent molecular masses of 17, 12, and 10 kDa in sodium dodecyl sulfate-polyacrylamide gel electrophoresis have been observed, depending on the presence of 2-mercaptoethanol and alkylation with 4-vinylpyridine, indicating that disulfide bonds are responsible for the multimerization of the protein. This result was in agreement with the existence of a cysteine-rich domain in the C-terminal region of the predicted amino acid sequence. The protein was synthesized at late times of infection, and no posttranslational modifications such as glycosylation, phosphorylation, or fatty acid acylation were detected.
| S-EPMC241171 | biostudies-other
Project description:The LcrV protein is a multifunctional virulence factor and protective antigen of the plague bacterium and is generally conserved between the epidemic strains of Yersinia pestis. We investigated the diversity in the LcrV sequences among non-epidemic Y. pestis strains which have a limited virulence in selected animal models and for humans. Sequencing of lcrV genes from 19 Y. pestis strains belonging to different phylogenetic groups (subspecies) showed that the LcrV proteins possess four major variable hotspots at positions 18, 72, 273, and 324-326. These major variations, together with other minor substitutions in amino acid sequences, allowed us to classify the LcrV alleles into five sequence types (A-E). We observed that the strains of different Y. pestis "subspecies" can have the same type of LcrV, including that conserved in epidemic strains, and different types of LcrV can exist within the same natural plague focus. Therefore, the phenomenon of "selective virulence" characteristic of the strains of the microtus biovar is unlikely to be the result of polymorphism of the V antigen. The LcrV polymorphisms were structurally analyzed by comparing the modeled structures of LcrV from all available strains. All changes except one occurred either in flexible regions or on the surface of the protein, but local chemical properties (i.e. those of a hydrophobic, hydrophilic, amphipathic, or charged nature) were conserved across all of the strains. Polymorphisms in flexible and surface regions are likely subject to less selective pressure, and have a limited impact on the structure. In contrast, the substitution of tryptophan at position 113 with either glutamic acid or glycine likely has a serious influence on the regional structure of the protein, and these mutations might have an effect on the function of LcrV. The polymorphisms at positions 18, 72 and 273 were accountable for differences in the oligomerization of LcrV.
| S-EPMC2818281 | biostudies-literature