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Protein Organization01:24

Protein Organization

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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Mutations01:35

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Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
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Analysis of protein missense alterations by combining sequence- and structure-based methods.

Aram Gyulkhandanyan1,2, Alireza R Rezaie3,4, Lubka Roumenina5,6,7

  • 1INSERM U973, Laboratory MTi, University Paris Diderot, Paris, France.

Molecular Genetics & Genomic Medicine
|February 26, 2020
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Summary

Combining computational tools aids in predicting missense variant impacts. However, salt-bridge interactions remain challenging for automated methods, necessitating manual 3D structural analysis for accurate variant effect prediction.

Keywords:
AntithrombinCYPFactor BFactor VIIIPolyPhen-2missense variantsstructural analysisstructural bioinformatics

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • In silico methods are crucial for predicting the phenotypic effects of missense variants.
  • These tools are often sequence-based or structure-based, requiring 3D structural data.
  • Non-variant specific in silico tools can offer additional mechanistic insights.

Purpose of the Study:

  • To evaluate various computational approaches for predicting missense variant impacts.
  • To assess the utility of combining different in silico tools for variant analysis.
  • To identify limitations of current computational methods in predicting variant effects.

Main Methods:

  • Applied a range of computational tools including PolyPhen-2, PopMusic, DUET, and others to 20 known missense variants across different proteins.
  • Utilized both fast computational approaches and web servers for analysis.
  • Included tools not specifically designed for variant analysis to explore broader mechanistic insights.

Main Results:

  • Observed conflicting predictions among different computational methods.
  • Found that combining multiple in silico tools often improved the clarity of potential amino acid substitution impacts.
  • Identified a tendency for tools to fail when modified residues are involved in salt-bridges, even with 3D analysis.

Conclusions:

  • Combining diverse in silico approaches, including general bioinformatics tools, enhances missense variant impact prediction.
  • Automated prediction tools struggle with variants affecting salt-bridge interactions.
  • Interactive 3D structural analysis using molecular graphics software remains essential for clarifying predictions in complex cases.