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Protein Adsorption on Solid Surfaces: Data Mining, Database, Molecular Surface-Derived Properties, and Semiempirical

Matthew Cho1, Zahra Mahmoodi1, Prasad Shetty1

  • 1Faculty of Engineering, Department of Bioengineering, McGill University, Montreal, Quebec H3A 0C3, Canada.

ACS Applied Materials & Interfaces
|May 24, 2024
PubMed
Summary

A new database and machine learning analysis reveal key factors influencing protein adsorption on surfaces. This work provides semiempirical relationships to predict protein adsorption for diverse applications.

Keywords:
Langmuir isothermatomic hydrophobicitydatabasemolecular surfacemultilinear regression with breakpointprotein adsorption

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Area of Science:

  • Biomaterials Science
  • Surface Chemistry
  • Biophysics

Background:

  • Protein adsorption on surfaces is crucial for many applications but difficult to predict.
  • Existing measurement techniques have limitations in capturing the complexity of this process.

Purpose of the Study:

  • To develop a predictive model for protein adsorption.
  • To identify key parameters influencing protein adsorption on different surfaces.
  • To create a comprehensive database for protein adsorption data.

Main Methods:

  • Collected and organized four decades of protein adsorption data into the Biomolecular Adsorption Database.
  • Quantified protein shape and physicochemical properties using the ProMS program.
  • Applied machine learning and piecewise linear regression to analyze adsorption data.
  • Developed semiempirical relationships for predicting protein adsorption on hydrophilic and hydrophobic surfaces.

Main Results:

  • Machine learning identified different modulating parameters for hydrophobic and hydrophilic surfaces.
  • Semiempirical relationships accurately predicted protein adsorption based on various factors.
  • Extrapolation errors to new proteins correlated with protein structural dissimilarity.

Conclusions:

  • The developed database and predictive models offer a powerful tool for understanding and controlling protein adsorption.
  • This research facilitates the optimization of protein adsorption in fields like diagnostics, pharmaceuticals, biomaterials, and food industries.