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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
Peptides quantitative structure-function relationships: an automated mutation strategy to design peptides and
M Adenot1, C Sarrauste de Menthière, A Chavanieu
1Centre de Biochimie Structurale, CNRS UMR 9955, INSERM U 414, Faculté de Pharmacie 15, Montpellier, France.
Journal of Molecular Graphics & Modelling
|June 7, 2000
Summary
This study introduces a quantitative method for designing peptide analogs using substitution matrices, enhancing drug discovery by enabling rational amino acid changes for improved biological activity and drug properties.
Area of Science:
- Biochemistry
- Medicinal Chemistry
- Computational Biology
Background:
- Current peptide analog design lacks quantitative basis for amino acid substitutions.
- Substitution matrices offer potential for biologically constrained design.
Purpose of the Study:
- To develop a quantitative strategy for rational amino acid substitution in peptides and proteins.
- To create a chemically derived substitution matrix applicable to both coded and non-coded amino acids.
Main Methods:
- Computed a chemically derived substitution matrix analogous to PAM 250.
- Developed an automated sequence mutation (ASM) strategy for constrained mutations.
- Applied the matrix to quantitative structure-function relationship (QSAR) studies.
Main Results:
- Demonstrated that substitution matrices provide quantitative constraints for biological activity.
- Extended matrix applicability to non-coded amino acids used in peptide modification.
- Showcased the utility of ASM in generating biologically relevant mutations.
Conclusions:
- Substitution matrices offer a quantitative framework for rational peptide and protein design.
- This approach facilitates the development of pharmaceutical drugs with improved properties like oral bioavailability and conformational stability.
