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Protein Families02:47

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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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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.
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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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GoFDR: A sequence alignment based method for predicting protein functions.

Qingtian Gong1, Wei Ning1, Weidong Tian2

  • 1State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai 200433, PR China.

Methods (San Diego, Calif.)
|August 17, 2015
PubMed
Summary
This summary is machine-generated.

GoFDR is a new method that accurately predicts protein functions using Gene Ontology (GO) terms and sequence alignments. It outperforms existing methods and aids in annotating and characterizing proteins.

Keywords:
Function predictionFunctional discriminating residues (FDRs)GO annotationPSI-BLAST alignmentRaw score adjustment

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Accurate protein function prediction is crucial for understanding biological systems.
  • Existing sequence-based methods have limitations in predicting Gene Ontology (GO) functions.
  • The Critical Assessment of Function Annotation (CAFA) project highlights the need for improved protein function prediction tools.

Purpose of the Study:

  • To develop and evaluate GoFDR, a novel method for predicting GO-based protein functions.
  • To assess GoFDR's performance against existing sequence-based prediction methods.
  • To apply GoFDR to the human proteome for expanding functional annotations.

Main Methods:

  • GoFDR utilizes multiple sequence alignments (MSAs) generated by PSI-BLAST as input.
  • Identifies functionally discriminating residues (FDRs) specific to GO terms.
  • Constructs position-specific scoring matrices (PSSMs) for FDRs to score query sequences.
  • Converts raw scores to probability scores using a pre-trained score-to-probability table.

Main Results:

  • GoFDR demonstrated superior performance compared to three other sequence-based methods in a benchmark study of 18,520 sequences.
  • GoFDR was recognized as a top-performing method in the CAFA2 project's preliminary evaluation.
  • High-confidence predictions from GoFDR significantly expanded the functional annotations of the human proteome.

Conclusions:

  • GoFDR is a highly effective tool for predicting GO-based protein functions.
  • The method offers significant value for annotating newly sequenced genomes and characterizing proteins of interest.
  • GoFDR advancements contribute to the broader field of protein function annotation and bioinformatics.