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Related Concept Videos

Protein Organization01:24

Protein Organization

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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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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
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NMRFAM-SDF: a protein structure determination framework.

Hesam Dashti1, Woonghee Lee1, Marco Tonelli1

  • 1National Magnetic Resonance Facility at Madison, Biochemistry Department, University of Wisconsin-Madison, 433 Babcock Drive, Madison, WI, USA.

Journal of Biomolecular NMR
|April 23, 2015
PubMed
Summary
This summary is machine-generated.

This study presents NMRFAM-SDF, a comprehensive framework for automated protein structure determination using Nuclear Magnetic Resonance (NMR). It simplifies the process and validates each step to manage errors in complex protein structures.

Keywords:
ADAPT-NMRARECAAutomated protein structure determination frameworkCASD-NMRNon-uniform samplingPINEPONDEROSA-C/SValidation

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Biophysics

Background:

  • Automated Nuclear Magnetic Resonance (NMR) structure determination is computationally intensive, requiring optimization of data collection, chemical shift assignment, and calculation steps.
  • Previous efforts have addressed discrete computational and algorithmic aspects, but a comprehensive solution with robust validation remains a challenge.
  • Error propagation in complex protein structures can significantly degrade the accuracy of automated structure determination.

Purpose of the Study:

  • To introduce a complete framework for protein structure determination using NMR, encompassing data acquisition to final structure calculation.
  • To simplify the structure determination process for non-experts while maintaining flexibility through modular validation.
  • To enable the assessment of error propagation throughout the structure determination pipeline.

Main Methods:

  • Development of the NMRFAM-Structure Determination Framework (NMRFAM-SDF), a modular software suite.
  • Integration of validation protocols for each discrete step of the NMR structure determination process.
  • Framework covers the entire workflow from NMR data acquisition to structure calculation.

Main Results:

  • NMRFAM-SDF provides a unified approach to automated protein structure determination.
  • The framework includes modules for validating individual steps, aiding in error assessment.
  • Designed to enhance usability for non-NMR specialists and maintain flexibility for experts.

Conclusions:

  • NMRFAM-SDF offers a robust and validated framework for NMR-based protein structure determination.
  • The framework addresses the need for error assessment, particularly for complex protein structures.
  • The NMRFAM-SDF software and its components are publicly available for download.