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Issue 7, 2009
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The BAD project: data mining, database and prediction of protein adsorption on surfaces

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Abstract

Protein adsorption at solid–liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable—the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Graphical abstract: The BAD project: data mining, database and prediction of protein adsorption on surfaces

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Publication details

The article was received on 06 Aug 2008, accepted on 28 Nov 2008 and first published on 24 Dec 2008


Article type: Paper
DOI: 10.1039/B813475H
Citation: Lab Chip, 2009,9, 891-900
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    The BAD project: data mining, database and prediction of protein adsorption on surfaces

    E. N. Vasina, E. Paszek, D. V. Nicolau, Jr and D. V. Nicolau, Lab Chip, 2009, 9, 891
    DOI: 10.1039/B813475H

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