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Related Concept Videos

Protein Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...
Conserved Binding Sites01:49

Conserved Binding Sites

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 analyses the...
Protein-protein Interfaces02:04

Protein-protein Interfaces

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 polypeptide...
Protein Folding01:25

Protein Folding

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.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...
Protein Folding01:22

Protein Folding

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Protein Folding01:22

Protein Folding

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Updated: Jun 9, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

PolyProline Predictor: A web server for empirical sequence-based prediction of polyproline II helices.

Rubén López-Sánchez1, David Pantoja-Uceda1, Miguel Mompeán1

  • 1Departamento de Química Física Biológica, Instituto de Química Física "Blas Cabrera"-CSIC, Madrid, Spain.

Protein Science : a Publication of the Protein Society
|June 8, 2026
PubMed
Summary

We developed PolyProline Predictor (PPP), a new tool to identify polyproline II (PPII) helices in proteins. PPP uses sequence similarity to experimentally validated structures, aiding the study of protein function and disorder.

Keywords:
CD spectroscopyNMR spectroscopyRIPK3molecular dynamicsmycobacteria PE_PGRSpolyproline II helixwebserver

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Last Updated: Jun 9, 2026

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

  • Structural Biology
  • Bioinformatics
  • Protein Science

Background:

  • Polyproline II (PPII) helices are crucial left-handed protein structures involved in molecular recognition and signaling.
  • Predicting PPII helices from amino acid sequences is challenging due to subtle determinants and misclassification as random coil.

Purpose of the Study:

  • To introduce PolyProline Predictor (PPP), a web server for sequence-based prediction of PPII helices.
  • To provide an interpretable method for identifying PPII helix propensity, complementing machine learning approaches.

Main Methods:

  • PPP aligns query sequences with a database of experimentally validated PPII helices.
  • The server generates a similarity map sensitive to composition and position.
  • Molecular dynamics simulations and biophysical techniques (CD, NMR) were used for validation.

Main Results:

  • PPP identified conserved PPII motifs in known proteins and predicted them in uncharacterized regions, including glycine-rich proteins and virulence factors.
  • The tool successfully predicted PPII conformations in regions modeled by AlphaFold and experimentally validated in RIPK3.
  • Simulations and spectroscopy confirmed PPII structures in mycobacterial, plant, and RIPK3 proteins.

Conclusions:

  • PPP offers a novel, interpretable approach to predict PPII helix propensity, filling a gap in bioinformatics tools.
  • The findings expand the understanding of PPII helix roles in protein structure, function, and intrinsically disordered regions.
  • This tool facilitates the exploration of PPII helices across proteomes, particularly in low-complexity regions.