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Related Concept Videos

Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

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Related Experiment Video

Updated: May 25, 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

Lanthipeptide structure prediction and design with Rosetta.

Claiborne W Tydings1, Rocco Moretti2, Jens Meiler3

  • 1Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States; Institute of Chemical Biology, Vanderbilt University, Nashville, TN, United States.

Methods in Enzymology
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

Lanthipeptides show promise for drug discovery due to their bioactivity and engineerability. This study introduces Rosetta software tools for modeling and designing these complex peptides, aiding structure-activity relationship studies.

Keywords:
AntibioticsLanthipeptidesPeptidesProtein protein interaction inhibitors

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Drug Discovery

Background:

  • Lanthipeptides are ribosomally synthesized peptides with diverse bioactivities, including antibacterial properties.
  • Their engineerability makes them attractive candidates for therapeutic applications.
  • A gap exists in computational tools for lanthipeptide modeling, hindering structure-activity relationship (SAR) studies and rational design.

Purpose of the Study:

  • To introduce computational modeling tools for lanthipeptides within the Rosetta software suite.
  • To enable structure prediction and design of lanthipeptides using established protein modeling methodologies.
  • To facilitate a deeper understanding of lanthipeptide SAR and advance rational drug design.

Main Methods:

  • Integration of lanthipeptide modeling capabilities into the Rosetta software.
  • Application of Rosetta's established algorithms for protein and peptide modeling.
  • Development of a tutorial to guide users through lanthipeptide modeling and design processes.

Main Results:

  • Rosetta now supports the modeling of lanthipeptides, including their unique post-translational modifications.
  • The enhanced Rosetta suite allows for lanthipeptide structure prediction and computational design.
  • A tutorial is provided to demonstrate the practical application of these new tools.

Conclusions:

  • The addition of lanthipeptide modeling to Rosetta bridges a critical gap in computational tools for this peptide class.
  • This advancement will accelerate research into lanthipeptide SAR and facilitate the rational design of novel lanthipeptide-based therapeutics.
  • The availability of these tools is expected to significantly impact the field of lanthipeptide drug discovery.