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Related Concept Videos

Protein Folding01:22

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Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
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ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
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The native conformation of a protein is formed by interactions between the side chains of its constituent amino acids. When the amino acids cannot form these interactions, the protein cannot fold by itself and needs chaperones. Notably, chaperones do not relay any additional information required for the folding of polypeptides; the native conformation of a protein is determined solely by its amino acid sequence. Chaperones catalyze protein folding without being a part of the folded protein.
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Related Experiment Video

Updated: Apr 14, 2026

Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding
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iFoldRNA v2: folding RNA with constraints.

Andrey Krokhotin1, Kevin Houlihan1, Nikolay V Dokholyan1

  • 1Department of Biochemistry & Biophysics, University of North Carolina, Chapel Hill, NC, 27599, USA.

Bioinformatics (Oxford, England)
|April 26, 2015
PubMed
Summary

The iFoldRNA server now predicts longer RNA 3D structures using experimental data. This computational approach enhances the accuracy of predicting complex RNA tertiary structures.

Area of Science:

  • Structural biology
  • Computational biology
  • Bioinformatics

Background:

  • Understanding RNA 3D structure is crucial for deciphering RNA function.
  • Experimental determination of RNA structures is complex and time-consuming.
  • Computational prediction methods offer a valuable alternative and complement to experimental approaches.

Purpose of the Study:

  • To present an upgraded iFoldRNA server capable of predicting tertiary structures for longer RNA molecules.
  • To enhance the prediction accuracy by integrating experimental data.
  • To demonstrate the advantages of combining computational methods with experimental information.

Main Methods:

  • Development of a new version of the iFoldRNA server.
  • Incorporation of experimental data, including base-pairing and hydroxyl-radical probing, into the prediction model.

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  • Prediction of tertiary structures for RNA sequences up to several hundred nucleotides.

    • Main Results:

    • The enhanced iFoldRNA server successfully predicts tertiary structures for longer RNA molecules.
    • Integration of experimental data significantly improves prediction accuracy.
    • The server demonstrates a substantial increase in capacity compared to previous versions.

    Conclusions:

    • The upgraded iFoldRNA server provides a powerful tool for predicting RNA 3D structures.
    • Combining computational predictions with experimental data offers a significant benefit for RNA structure analysis.
    • This advancement facilitates a deeper understanding of RNA function through accurate structural insights.