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Related Concept Videos

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.
The primary structure of a protein is its amino acid sequence....
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Protein Organization01:13

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Overview
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Conserved Binding Sites01:49

Conserved Binding Sites

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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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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Protein and Protein Structure02:15

Protein and Protein Structure

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Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
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Protein-protein Interfaces02:04

Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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Benchmarking Methods of Protein Structure Alignment.

Janan Sykes1, Barbara R Holland2, Michael A Charleston2

  • 1School of Natural Sciences, University of Tasmania, Hobart, Australia. janan.sykes@utas.edu.au.

Journal of Molecular Evolution
|July 30, 2020
PubMed
Summary
This summary is machine-generated.

Protein Structure Alignment (PSA) methods were evaluated for classifying and clustering protein domains. SP-AlignNS excelled in classification, with some hybrid methods showing superior performance in both tasks.

Keywords:
BenchmarkingClassificationClusteringProtein structure alignment

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Area of Science:

  • Structural Bioinformatics
  • Computational Biology
  • Biochemistry

Background:

  • Protein function is intrinsically linked to its structure and amino acid sequence.
  • Accurate protein structure alignment is crucial for understanding protein domain relationships and biological function.
  • Numerous protein structure alignment (PSA) methods exist, employing diverse techniques.

Purpose of the Study:

  • To evaluate the efficacy of various PSA methods in identifying protein domains with varying structural similarities.
  • To assess the utility of PSA methods for clustering protein domains into known structural groups.
  • To provide insights for researchers selecting or developing PSA tools.

Main Methods:

  • Comprehensive investigation of eighteen distinct PSA methods.
  • Separation of alignment algorithms from similarity scoring functions to assess their independent effectiveness.
  • Evaluation of method performance in both classification (identifying similar pairs) and clustering (grouping domains).

Main Results:

  • SP-AlignNS (non-sequential) demonstrated superior performance in protein domain classification.
  • SP-AlignNS was also among the top performers for domain clustering.
  • Hybrid combinations of algorithms and scores, even when mismatched, sometimes outperformed native methods in classification and clustering.

Conclusions:

  • The study offers a large-scale independent assessment of PSA method capabilities.
  • SP-AlignNS is recommended for protein domain classification tasks.
  • The effectiveness of PSA methods can be influenced by the interplay between alignment algorithms and scoring functions, suggesting potential for novel hybrid approaches.