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Protein Organization01:24

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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
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Lattice energy represents the energy released when gaseous cations and anions combine to form an ionic solid, reflecting the strength of electrostatic interactions within the crystal. This process is fundamentally governed by Coulombic attraction between oppositely charged ions, where the potential energy varies inversely with the interionic distance and directly with the product of ionic charges. As ions approach one another, the electrostatic energy becomes increasingly negative, indicating a...
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Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
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A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Lattices for ab initio protein structure prediction.

Ciro Leonardo Pierri1, Anna De Grassi, Antonio Turi

  • 1Department of Pharmaco-Biology, University of Bari, Va E. Orabona, Bari, Italy. ciroleopierri@gmail.com

Proteins
|April 25, 2008
PubMed
Summary

This study evaluates lattice models for protein folding. Optimized direction vectors significantly improve lattice performance for predicting protein structures, outperforming models with higher coordination numbers alone.

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Area of Science:

  • Computational biology
  • Biophysics
  • Protein structure prediction

Background:

  • The protein folding problem is crucial for understanding protein function.
  • Lattice models offer a computationally efficient approach to protein structure prediction compared to off-lattice methods.
  • The accuracy of lattice models is limited by the choice of lattice and direction vectors.

Purpose of the Study:

  • To systematically screen and evaluate the predictive power of various lattice models for protein folding.
  • To compare classic and newly proposed lattices using a set of 42 diverse protein crystal structures.
  • To determine the key factors influencing the performance of lattice-based protein structure prediction.

Main Methods:

  • Coarse-grained modeling of protein backbones on periodic lattices using No Reverse Self Avoiding Walks.
  • Systematic screening of 18 lattices (7 classic, 11 new) against 42 protein crystal structures.
  • Comparison of simulated models with known protein tertiary structures to assess lattice fitness.

Main Results:

  • A fitness scale was established for all analyzed lattices.
  • Increased coordination number and degrees of freedom are necessary but not sufficient for optimal lattice performance.
  • The development and testing of a superior set of direction vectors significantly enhanced lattice predictive power.

Conclusions:

  • The choice of direction vectors is critical for the accuracy of lattice-based protein folding models.
  • Optimized direction vectors provide a substantial improvement in predicting protein tertiary structures.
  • This research offers a refined approach to lattice selection for efficient and accurate protein structure prediction.