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Related Concept Videos

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.
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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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Proteins perform many mechanical functions in a cell. These proteins can be classified into two general categories- proteins that generate mechanical forces and proteins that are subjected to mechanical forces. Proteins providing mechanical support to the structure of the cell, such as keratin, are subjected to mechanical force, whereas proteins involved in cell movement and transport of molecules across cell membranes, such as an ion pump, are examples of generating mechanical force. 
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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.
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Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Sequence-based prediction of physicochemical interactions at protein functional sites using a

Min Han1, Yifan Song1, Jiaqiang Qian1

  • 1Department of Physiology and Biophysics, School of Life Science, Fudan University, Shanghai, 200438, People's Republic of China.

BMC Bioinformatics
|June 3, 2018
PubMed
Summary

A new sequence-based method accurately predicts protein functional sites and their physicochemical interactions, aiding drug design. This approach enhances understanding of protein evolution and function.

Keywords:
Domain profile moduleHidden Markov modelPhysicochemical interaction predictionProtein functional site predictionfiDPD

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Area of Science:

  • Biochemistry and Molecular Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Identifying protein functional sites (PFSs) and their associated physicochemical interactions is crucial for understanding protein function and biochemical processes.
  • Existing knowledge-based methods are limited in accurately predicting these physicochemical interactions at PFSs.

Purpose of the Study:

  • To develop and present a novel sequence-based method for predicting physicochemical interactions at PFSs.
  • To provide a tool for rational drug design and side-effect assessment.

Main Methods:

  • Developed a sequence-based method utilizing a functional site and physicochemical interaction-annotated domain profile database (fiDPD).
  • The fiDPD database was constructed using protein domains from the Protein Data Bank.
  • Applied the method to 13 target proteins from the Critical Assessment of Structure Prediction (CASP10/11).

Main Results:

  • Achieved a Matthews correlation coefficient (MCC) of 0.66 for PFS prediction.
  • Obtained an 80% recall in predicting associated physicochemical interactions.
  • Demonstrated that physical interactions at PFSs are conserved during protein evolution.

Conclusions:

  • The developed method offers a valuable sequence-based tool for predicting physicochemical interactions at PFSs.
  • The findings suggest evolutionary conservation of physical interactions at protein functional sites.
  • The tool is freely available for applications in rational drug design and side-effect assessment.