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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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Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...
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Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
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The chair conformation is the most stable form of cyclohexane due to the absence of angle and torsional strain. The absence of angle strain is a result of cyclohexane’s bond angle being very close to the ideal tetrahedral bond angle of 109.5° in its chair conformer. Similarly, the torsional strain is also absent owing to the perfectly staggered arrangement of bonds.
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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IMPContact: An Interhelical Residue Contact Prediction Method.

Chao Fang1, Yajie Jia1,2, Lihong Hu1

  • 1School of Information Science and Technology, Northeast Normal University, Changchun 130117, China.

Biomed Research International
|April 21, 2020
PubMed
Summary

Predicting alpha-helix transmembrane protein (αTMP) residue contacts is crucial for understanding protein function. IMPContact, a novel deep learning method using CNNs, accurately identifies these contacts, improving upon existing techniques.

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Area of Science:

  • Biochemistry and Structural Biology
  • Bioinformatics and Computational Biology
  • Protein Science

Background:

  • Alpha-helix transmembrane proteins (αTMPs) are vital for numerous biological functions.
  • Inadequate solved αTMP structures necessitate accurate prediction of residue contacts within transmembrane segments for understanding protein folding and function.
  • Existing machine learning methods for interhelical residue contact prediction face challenges in accuracy.

Purpose of the Study:

  • To develop a novel deep learning-based method, IMPContact, for predicting residue-residue contacts in αTMPs.
  • To leverage convolutional neural networks (CNNs) and specific structural features for improved prediction accuracy.
  • To enhance the understanding of αTMP structure-function relationships through accurate contact prediction.

Main Methods:

  • Proposed IMPContact, a novel method utilizing a convolutional neural network (CNN).
  • Employed four sequence-based, TMP-specific features: evolutionary covariation, predicted topology, residue relative position, and evolutionary conservation.
  • Trained and tested IMPContact on an up-to-date dataset of αTMPs.

Main Results:

  • IMPContact demonstrated superior performance compared to existing peer methods.
  • The method showed higher accuracy in predicting contacts within regular transmembrane helices than irregular ones.
  • Case studies validated the effectiveness of IMPContact in identifying interhelical residue contacts (IHRCs).

Conclusions:

  • IMPContact offers a significant advancement in predicting residue-residue contacts for αTMPs.
  • Deep learning, specifically CNNs, provides a powerful approach to utilize structural knowledge for TMP contact prediction.
  • Accurate IHRC prediction using IMPContact can facilitate further discovery of αTMP functions.