In silico design of solid binding peptides as molecular building blocks in technology and medicine

NANO 32

Ram Samudrala, ram@compbio.washington.edu1, Ersin Emre Oren, eeoren@u.washington.edu, Candan Tamerler2, and Mehmet Sarikaya, sarikaya@u.washington.edu2. (1) Microbiology, University of Washington, Health Sciences, Seattle, WA 98195, (2) GEMSEC, Department of Materials Science and Engineering, University of Washington, 302C Roberts Hall, Box 352120, Seattle, WA 98195
The understanding of the relationships between the solid-binding peptide sequences and their binding affinities or specificities will enable further design of novel peptides with selected properties of interest both in engineering and medicine. We developed a bioinformatics approach that performs all-against-all comparisons of in vivo selected peptides that were categorized for their binding affinity and scores the alignments using sequence similarity scoring matrices that optimize the similarities within strong-binding peptide sequences. We demonstrate the novel approach by classifying various material-binding peptides and computationally designing new sequences with specific material affinities. Verifications of binding of these knowledge-based designed peptides confirm our predictions with high accuracy. We further show that our approach is a general one and can be used to design new sequences that bind to a given solid, or multiple solids, with predictable and enhanced affinity, and demonstrate their implementation in wide range of areas including nanoinorganic synthesis, targeted assembly of quantum dots and enzymes, and development of functional molecular scaffolds.