Peptide toxicity prediction

Methods Mol Biol. 2015;1268:143-57. doi: 10.1007/978-1-4939-2285-7_7.

Abstract

Last decade has witnessed the revival of interest in peptides as potential therapeutics candidates. However, one of the bottlenecks in the success of therapeutic peptides in clinics is their toxicity towards eukaryotic cells. Therefore, considerable efforts have been made over the years both in wet and dry lab to overcome this limitation. With the advances in peptide synthesis, now it is possible to fine-tune the physicochemical properties of peptides by incorporating several chemical modifications and thus to optimize the peptide functionality in order to minimize the toxicity without compromising their therapeutic activity. Also various in silico tools for peptide toxicity prediction and peptide designing have been developed, which facilitates designing of therapeutic peptides with desired toxicity. In this chapter, we have discussed both wet lab and dry lab approaches used to optimize peptide toxicity. More emphasis has been given to describe the in silico method, ToxinPred, to predict the toxicity of peptide and about how to design a peptide or protein with desired toxicity by mutating minimum number of amino acids.

MeSH terms

  • Amino Acids / chemistry*
  • Computational Biology / methods
  • Computer Simulation
  • Databases, Protein
  • Models, Molecular*
  • Mutation
  • Peptides / chemistry*
  • Peptides / toxicity*
  • Software
  • Structure-Activity Relationship

Substances

  • Amino Acids
  • Peptides