Thermodynamic additivity of sequence variations

An algorithm for creating high affinity peptides without large libraries or structural information

Matthew P. Greving, Paul E. Belcher, Chris Diehnelt, Maria J. Gonzalez-Moa, Jack Emery, Jinglin Fu, Stephen Johnston, Neal Woodbury

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Background: There is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information. Methodology/PrincipalFindings:Based on the principle of additivity, we have developed an algorithm for generating high affinity peptide ligands. In this algorithm, point-variations in a lead sequence are screened and combined in a systematic manner to achieve additive binding energies. To demonstrate this approach, low-affinity lead peptides for multiple protein targets were identified from sparse random sequence space and optimized to high affinity in just two chemical steps. In one example, a TNF-a binding peptide with Kd =90 nM and high target specificity was generated. The changes in binding energy associated with each variation were generally additive upon combining variations, validating the basis of the algorithm. Interestingly, cooperativity between point-variations was not observed, and in a few specific cases, combinations were less than energetically additive. Conclusions/Significance: By using this additivity algorithm, peptide ligands with high affinity for protein targets were generated. With this algorithm, one of the highest affinity TNF-a binding peptides reported to date was produced. Most importantly, high affinity was achieved from small, chemically-synthesized libraries without the need for structural information at any time during the process. This is significantly different than protein mutagenesis, directed evolution, or fragment-based design approaches, which rely on large libraries and/or structural guidance. With this algorithm, high affinity/specificity peptide ligands can be developed rapidly, inexpensively, and in an entirely chemical manner.

Original languageEnglish (US)
Article numbere15432
JournalPLoS One
Volume5
Issue number11
DOIs
StatePublished - 2010

Fingerprint

Thermodynamics
thermodynamics
Libraries
peptides
Peptides
Mutagenesis
Ligands
Binding energy
mutagenesis
Proteins
proteins
peptide libraries
Peptide Library
energy
sequence diversity
ligands

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Thermodynamic additivity of sequence variations : An algorithm for creating high affinity peptides without large libraries or structural information. / Greving, Matthew P.; Belcher, Paul E.; Diehnelt, Chris; Gonzalez-Moa, Maria J.; Emery, Jack; Fu, Jinglin; Johnston, Stephen; Woodbury, Neal.

In: PLoS One, Vol. 5, No. 11, e15432, 2010.

Research output: Contribution to journalArticle

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