Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A statistical mechanical method to optimize energy functions for protein folding.

U Bastolla1, M Vendruscolo, E W Knapp

  • 1Freie Universität Berlin, Department of Biology, Chemistry and Pharmacy, Takustrasse 6, D-14195 Berlin, Germany.

Proceedings of the National Academy of Sciences of the United States of America
|April 13, 2000
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Distinct mechanistic pathways of early tauopathy revealed by <i>MAPT</i> mutations.

bioRxiv : the preprint server for biology·2026
Same author

Bound Ligand Conformer Revealed by Flexible Structure Alignment in Absence of Crystal Structures: Indirect Drug Design Probed for HIV-1 Protease Inhibitors.

Journal of chemical theory and computation·2015
Same author

Rubredoxin Function: Redox Behavior from Electrostatics.

Journal of chemical theory and computation·2015
Same author

mFES: A Robust Molecular Finite Element Solver for Electrostatic Energy Computations.

Journal of chemical theory and computation·2015
Same author

Spatial propagation of protein polymerization.

Physical review letters·2014
Same author

Assessment of the quality of energy functions for protein folding by using a criterion derived with the help of the noisy go model.

Journal of biological physics·2013

This study introduces a novel method for protein folding energy functions, enhancing native state stability and landscape smoothness. The approach successfully stabilizes 92% of X-ray protein structures, improving protein structure prediction.

Area of Science:

  • Computational Biology
  • Biophysics
  • Structural Biology

Background:

  • Protein folding is crucial for biological function.
  • Accurate energy functions are essential for predicting protein structures.
  • Current methods face challenges in accurately modeling complex protein interactions.

Purpose of the Study:

  • To develop a novel method for deriving protein folding energy functions.
  • To maximize the thermodynamic average of overlap with the native state.
  • To assess the effectiveness of the derived energy functions in stabilizing native protein structures.

Main Methods:

  • Derived energy functions by maximizing the thermodynamic average of overlap with the native state.
  • Employed pairwise contact approximation for the energy function.

Related Experiment Videos

  • Generated alternative structures by threading sequences over a database of 1,169 structures.
  • Main Results:

    • The derived energy function stabilizes 92% of 1,013 X-ray structures.
    • Native structures exhibit minimal energy, thermodynamic stability, and smooth energy landscapes.
    • Failures were mainly due to neglecting inter-chain and cofactor interactions, with only nine unexplained cases.

    Conclusions:

    • The developed method effectively derives energy functions that stabilize native protein structures.
    • The approach shows promise for improving protein structure prediction accuracy.
    • Further refinement is needed to account for polychain proteins and cofactor interactions for complete accuracy.