Many biological functions are mediated by protein-protein interactions (PPIs), often involving specific structural modules, such as SH2 domains. Inhibition of PPIs is a pharmaceutical strategy of growing importance. However, a major challenge in the design of PPI inhibitors is the large interface involved in these interactions, which, in many cases, makes inhibition by small organic molecules ineffective. Peptides, which cover a wide range of dimensions and can be opportunely designed to mimic protein sequences at PPI interfaces, represent a valuable alternative to small molecules. Computational techniques able to predict the binding affinity of peptides for the target domain or protein represent a crucial stage in the workflow for the design of peptide-based drugs. This chapter describes a protocol to obtain the potential of mean force (PMF) for peptide-SH2 domain binding, starting from umbrella sampling (US) molecular dynamics (MD) simulations. The PMF profiles can be effectively used to predict the relative standard binding free energies of different peptide sequences.

Calligari, P., Stella, L., Bocchinfuso, G. (2023). Computational Evaluation of Peptide–Protein Binding Affinities: Application of Potential of Mean Force Calculations to SH2 Domains. In Teresa Carlomagno, Maja Köhn (a cura di), SH2 Domains : Functional Modules and Evolving Tools in Biology (pp. 113-133). Springer [10.1007/978-1-0716-3393-9_7].

Computational Evaluation of Peptide–Protein Binding Affinities: Application of Potential of Mean Force Calculations to SH2 Domains

Calligari, Paolo;Stella, Lorenzo;Bocchinfuso, Gianfranco
2023-01-01

Abstract

Many biological functions are mediated by protein-protein interactions (PPIs), often involving specific structural modules, such as SH2 domains. Inhibition of PPIs is a pharmaceutical strategy of growing importance. However, a major challenge in the design of PPI inhibitors is the large interface involved in these interactions, which, in many cases, makes inhibition by small organic molecules ineffective. Peptides, which cover a wide range of dimensions and can be opportunely designed to mimic protein sequences at PPI interfaces, represent a valuable alternative to small molecules. Computational techniques able to predict the binding affinity of peptides for the target domain or protein represent a crucial stage in the workflow for the design of peptide-based drugs. This chapter describes a protocol to obtain the potential of mean force (PMF) for peptide-SH2 domain binding, starting from umbrella sampling (US) molecular dynamics (MD) simulations. The PMF profiles can be effectively used to predict the relative standard binding free energies of different peptide sequences.
2023
Settore CHIM/02
English
Rilevanza internazionale
Capitolo o saggio
Molecular dynamics simulations
Peptide design
Potential of mean force
Protein–protein interactions
Relative standard binding free energy
Umbrella sampling
Calligari, P., Stella, L., Bocchinfuso, G. (2023). Computational Evaluation of Peptide–Protein Binding Affinities: Application of Potential of Mean Force Calculations to SH2 Domains. In Teresa Carlomagno, Maja Köhn (a cura di), SH2 Domains : Functional Modules and Evolving Tools in Biology (pp. 113-133). Springer [10.1007/978-1-0716-3393-9_7].
Calligari, P; Stella, L; Bocchinfuso, G
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/357965
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