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Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
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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.

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Protein Membrane Overlay Assay: A Protocol to Test Interaction Between Soluble and Insoluble Proteins in vitro
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Published on: August 14, 2011

PROSO II--a new method for protein solubility prediction.

Pawel Smialowski1, Gero Doose, Phillipp Torkler

  • 1Department of Genome Oriented Bioinformatics, Technische Universität Muenchen, Freising, Germany. pawelsm@gmail.com

The FEBS Journal
|April 28, 2012
PubMed
Summary

Predicting protein solubility is crucial for biotechnology. PROSO II, a new machine learning model, accurately forecasts protein solubility using sequence data and an extensive dataset, improving protein production efficiency.

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Organic Solvent-Based Protein Precipitation for Robust Proteome Purification Ahead of Mass Spectrometry

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Area of Science:

  • Biotechnology
  • Computational Biology
  • Protein Engineering

Background:

  • Efficient production of active proteins via heterologous expression in Escherichia coli is vital for science and industry.
  • Protein solubility, a key factor in expression success, is intrinsically linked to the amino acid sequence.
  • Accurate prediction of protein solubility from sequence is therefore highly valuable for optimizing recombinant protein production.

Purpose of the Study:

  • To develop and present PROSO II, a novel machine learning-based model for enhanced protein solubility prediction.
  • To improve the accuracy and coverage of solubility predictions by leveraging new classification methods and a large experimental dataset.

Main Methods:

  • PROSO II employs a two-layered classification structure.
  • The primary layer combines a Parzen window model for sequence similarity and a logistic regression classifier for amino acid k-mer composition.
  • The secondary layer uses a logistic regression classifier integrating outputs from the primary layer.

Main Results:

  • The model was trained on an unprecedented dataset of 82,000 proteins, five times larger than previously used datasets.
  • PROSO II achieved state-of-the-art performance on a holdout set, with 75.4% accuracy, a Matthew's correlation coefficient of 0.39, 0.731 sensitivity, and 0.759 specificity.
  • The PROSO II server demonstrated superior results compared to existing protein solubility prediction methods.

Conclusions:

  • PROSO II represents a substantial advancement in predicting protein solubility, driven by advanced machine learning techniques and the largest available experimental dataset.
  • The PROSO II server offers improved accuracy and coverage, facilitating more efficient recombinant protein production.
  • The PROSO II tool is accessible at http://mips.helmholtz-muenchen.de/prosoII for broader scientific application.