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Statistical prediction of protein structural, localization and functional properties by the analysis of its fragment mass distributions after proteolytic cleavage.

ABSTRACT: Structural, localization and functional properties of unknown proteins are often being predicted from their primary polypeptide chains using sequence alignment with already characterized proteins and consequent molecular modeling. Here we suggest an approach to predict various structural and structure-associated properties of proteins directly from the mass distributions of their proteolytic cleavage fragments. For amino-acid-specific cleavages, the distributions of fragment masses are determined by the distributions of inter-amino-acid intervals in the protein, that in turn apparently reflect its structural and structure-related features. Large-scale computer simulations revealed that for transmembrane proteins, either ?-helical or ? -barrel secondary structure could be predicted with about 90% accuracy after thermolysin cleavage. Moreover, 3/4 intrinsically disordered proteins could be correctly distinguished from proteins with fixed three-dimensional structure belonging to all four SCOP structural classes by combining 3-4 different cleavages. Additionally, in some cases the protein cellular localization (cytosolic or membrane-associated) and its host organism (Firmicute or Proteobacteria) could be predicted with around 80% accuracy. In contrast to cytosolic proteins, for membrane-associated proteins exhibiting specific structural conformations, their monotopic or transmembrane localization and functional group (ATP-binding, transporters, sensors and so on) could be also predicted with high accuracy and particular robustness against missing cleavages.

SUBMITTER: Bogachev MI

PROVIDER: S-EPMC4770285 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Statistical prediction of protein structural, localization and functional properties by the analysis of its fragment mass distributions after proteolytic cleavage.

Bogachev Mikhail I MI Kayumov Airat R AR Markelov Oleg A OA Bunde Armin A

Scientific reports 20160229

Structural, localization and functional properties of unknown proteins are often being predicted from their primary polypeptide chains using sequence alignment with already characterized proteins and consequent molecular modeling. Here we suggest an approach to predict various structural and structure-associated properties of proteins directly from the mass distributions of their proteolytic cleavage fragments. For amino-acid-specific cleavages, the distributions of fragment masses are determine ...[more]

PMID: 26924271

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Project description:The atomic-level structural properties of proteins, such as bond lengths, bond angles, and torsion angles, have been well studied and understood based on either chemistry knowledge or statistical analysis. Similar properties on the residue-level, such as the distances between two residues and the angles formed by short sequences of residues, can be equally important for structural analysis and modeling, but these have not been examined and documented on a similar scale. While these properties are difficult to measure experimentally, they can be statistically estimated in meaningful ways based on their distributions in known proteins structures. Residue-level structural properties including various types of residue distances and angles are estimated statistically. A software package is built to provide direct access to the statistical data for the properties including some important correlations not previously investigated. The distributions of residue distances and angles may vary with varying sequences, but in most cases, are concentrated in some high probability ranges, corresponding to their frequent occurrences in either ?-helices or ?-sheets. Strong correlations among neighboring residue angles, similar to those between neighboring torsion angles at the atomic-level, are revealed based on their statistical measures. Residue-level statistical potentials can be defined using the statistical distributions and correlations of the residue distances and angles. Ramachandran-like plots for strongly correlated residue angles are plotted and analyzed. Their applications to structural evaluation and refinement are demonstrated. With the increase in both number and quality of known protein structures, many structural properties can be derived from sets of protein structures by statistical analysis and data mining, and these can even be used as a supplement to the experimental data for structure determinations. Indeed, the statistical measures on various types of residue distances and angles provide more systematic and quantitative assessments on these properties, which can otherwise be estimated only individually and qualitatively. Their distributions and correlations in known protein structures show their importance for providing insights into how proteins may fold naturally to various residue-level structures.

Project description:BACKGROUND:Neuronal cell loss contributes to the pathology of acute and chronic neurodegenerative diseases, including Alzheimer's disease (AD). It remains crucial to identify molecular mechanisms sensitizing neurons to various insults and cell death. To date, the multifunctional, autophagy-related protein Beclin 1 has been shown to be both necessary and sufficient for neuronal integrity in neurodegenerative models associated with protein aggregation. Interestingly, besides its role in cellular homeostasis, Beclin 1 has also been ascribed a role in apoptosis. This makes it critical to elucidate whether Beclin 1 regulates neuronal death and survival across neurodegenerative conditions independent of protein clearance. Here, we provide experimental evidence for a direct functional link between proteolytic cleavage of Beclin 1 and apoptotic neuronal cell loss in two independent models of neurodegeneration in vivo. METHODS:Proteolytic cleavage of Beclin 1 was characterized in lysates of human AD brain samples. We developed viral tools allowing for the selective neuronal expression of the various Beclin 1 forms, including Beclin 1 cleavage products as well as a cleavage-resistant form. The effect of these Beclin 1 forms on survival and integrity of neurons was examined in models of acute and chronic neurodegeneration in vitro and in vivo. Markers of neuronal integrity, neurodegeneration and inflammation were further assessed in a Kainic acid-based mouse model of acute excitotoxic neurodegeneration and in a hAPP-transgenic mouse model of AD following perturbation of Beclin 1 in the susceptible CA1 region of the hippocampus. RESULTS:We find a significant increase in caspase-mediated Beclin 1 cleavage fragments in brain lysates of human AD patients and mimic this phenotype in vivo using both an excitotoxic and hAPP-transgenic mouse model of neurodegeneration. Surprisingly, overexpression of the C-terminal cleavage-fragment exacerbated neurodegeneration in two distinct models of degeneration. Local inhibition of caspase activity ameliorated neurodegeneration after excitotoxic insult and prevented Beclin 1 cleavage. Furthermore, overexpression of a cleavage-resistant form of Beclin 1 in hippocampal neurons conferred neuroprotection against excitotoxic and Amyloid beta-associated insults in vivo. CONCLUSIONS:Together, these findings indicate that the cleavage state of Beclin 1 determines its functional involvement in both neurodegeneration and neuroprotection. Hence, manipulating the cleavage state of Beclin 1 may represent a therapeutic strategy for preventing neuronal cell loss across multiple forms of neurodegeneration.

Dataset Information

Statistical prediction of protein structural, localization and functional properties by the analysis of its fragment mass distributions after proteolytic cleavage.

Publications

Statistical prediction of protein structural, localization and functional properties by the analysis of its fragment mass distributions after proteolytic cleavage.

Similar Datasets

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