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Related Concept Videos

Structural Protein Function01:56

Structural Protein Function

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Structural proteins are a category of proteins responsible for functions ranging from cell shape and movement to providing support to major structures such as bones, cartilage, hair, and muscles. This group includes proteins such as collagen, actin, myosin, and keratin.
Collagen, the most abundant protein in mammals, is found throughout the body. In connective tissue, such as skin, ligaments, and tendons, it provides tensile strength and elasticity.  In bones and teeth, it mineralizes to...
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Protein and Protein Structure02:15

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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.
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Structural Joints: Fibrous Joints01:03

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Fibrous joints are a type of joint where the bones are connected by fibrous connective tissue. These joints provide stability and minimal to no movement between the articulating bones. There are three types of fibrous joints.
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Structural Joints: Cartilaginous Joints01:17

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As the name indicates, at a cartilaginous joint, the adjacent bones are united by cartilage, a tough but flexible type of connective tissue. Unlike synovial joints, these types of joints lack a joint cavity and involve bones joined together by either hyaline cartilage or fibrocartilage.
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Structural Joints: Synovial Joints01:16

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Synovial joints are the most common type of joint in the body. A key structural characteristic for a synovial joint is the presence of a joint cavity. This fluid-filled space is where the articulating surfaces of the bones contact each other. Also, unlike fibrous or cartilaginous joints, the articulating bone surfaces at a synovial joint are not directly connected to each other with fibrous connective tissue or cartilage. This gives the bones of a synovial joint the ability to move smoothly...
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Crystallizing Membrane Proteins for Structure Determination using Lipidic Mesophases
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Inferring joint sequence-structural determinants of protein functional specificity.

Andrew F Neuwald1,2, L Aravind3, Stephen F Altschul3

  • 1Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, United States.

Elife
|January 17, 2018
PubMed
Summary

Identifying functional protein networks is challenging. This study introduces a statistical method to detect interacting residues, aiding in the discovery of allosteric sites for drug design.

Keywords:
Bayesian statisticsInitial Cluster Analysiscomputational biologycomputer algorithmsnonesequence analysisstructural analysissystems biology

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Bioinformatics

Background:

  • Detecting subtle, functionally important residues in proteins, such as those involved in allostery and cooperativity, is a significant challenge in molecular biology.
  • Understanding these interactions is crucial for deciphering protein function and for targeted drug development.

Purpose of the Study:

  • To develop and validate a statistical inference method for identifying interacting functional networks within protein families.
  • To reveal previously overlooked sequence-structural features in various protein superfamilies.

Main Methods:

  • Employed statistical inference assuming that distinguishing residues between protein subgroups form functional networks.
  • Utilized two measures of statistical significance: one for identifying divergent subgroups and another for detecting structural interactions of pattern residues.
  • Derived interaction data from atomic coordinates or Direct Coupling Analysis (DCA) scores as surrogates for structural distances.

Main Results:

  • Successfully applied the method to N-acetyltransferases, P-loop GTPases, RNA helicases, synaptojanin-superfamily phosphatases and nucleases, and thymine/uracil DNA glycosylases.
  • Results were congruent with existing biochemical knowledge of these proteins.
  • Uncovered significant sequence-structural features missed by conventional methods.

Conclusions:

  • The developed statistical approach effectively identifies functional residue networks and their interactions.
  • This method offers a powerful tool for uncovering subtle protein mechanisms and can guide the design of allosteric drugs.