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Related Concept Videos

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Nucleic Acid Structure01:25

Nucleic Acid Structure

The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA has a double-helix structure. The...
Protein Organization01:24

Protein Organization

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.
The primary structure of a protein is its amino acid sequence.
Protein Organization01:13

Protein Organization

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Updated: May 21, 2026

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

Genomics-aided structure prediction.

Joanna I Sułkowska1, Faruck Morcos, Martin Weigt

  • 1Center for Theoretical Biological Physics, University of California at San Diego, La Jolla, CA 92093-0374, USA.

Proceedings of the National Academy of Sciences of the United States of America
|June 14, 2012
PubMed
Summary
This summary is machine-generated.

We present a new framework using genomic data for protein structure prediction. This method integrates direct coupling analysis (DCA) with local structural information to accurately fold proteins.

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Last Updated: May 21, 2026

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Area of Science:

  • Computational biology
  • Structural biology
  • Genomics

Background:

  • Protein structure prediction is crucial for understanding biological function.
  • Existing methods often struggle with accuracy and scalability.
  • Genomic sequence data offers a rich source of evolutionary information.

Purpose of the Study:

  • To develop a novel theoretical framework for protein structure prediction.
  • To leverage genomic sequence information and co-evolutionary data.
  • To improve the accuracy and efficiency of protein folding predictions.

Main Methods:

  • Modified structure-based models incorporating constraints from direct coupling analysis (DCA).
  • Estimation of non-local contacts from co-evolving genomic sequences.
  • A hybrid method (DCA-fold) combining DCA contacts with local secondary structure information.

Main Results:

  • The DCA-fold method successfully predicts protein structures.
  • Achieved high-resolution protein folding in the range of 1-3 Å.
  • Demonstrated the effectiveness of integrating evolutionary and local structural data.

Conclusions:

  • Genomic sequence information can be effectively exploited for protein structure prediction.
  • The DCA-fold method provides an accurate and efficient approach to protein folding.
  • This framework advances the field of computational structural biology.