The impetuous advance of computing power and the evolution of the theoretical and algorithmic fields have significantly impacted biomolecular simulations, enabling long-timescale molecular dynamics (MD) studies on ever larger and more realistic biological systems. However, the massive data generated poses new challenges, fostering the integration of classical simulative approaches with advanced approaches for analyzing simulations and leveraging this knowledge for drug design. This chapter explores applications of MD simulations across key areas: (i) the study of allosteric regulation; (ii) the investigation of interactions and regulation in large assemblies; and (iii) Ligand regulation of function and interactions and ligand design. These methodologies are described as actionable tools to expand the molecular diversity space of chemical tools for chemical biology and medicinal chemistry.

Investigating allostery with atomistic biomolecular simulations

Moroni, Elisabetta;Colombo, Giorgio
2025

Abstract

The impetuous advance of computing power and the evolution of the theoretical and algorithmic fields have significantly impacted biomolecular simulations, enabling long-timescale molecular dynamics (MD) studies on ever larger and more realistic biological systems. However, the massive data generated poses new challenges, fostering the integration of classical simulative approaches with advanced approaches for analyzing simulations and leveraging this knowledge for drug design. This chapter explores applications of MD simulations across key areas: (i) the study of allosteric regulation; (ii) the investigation of interactions and regulation in large assemblies; and (iii) Ligand regulation of function and interactions and ligand design. These methodologies are described as actionable tools to expand the molecular diversity space of chemical tools for chemical biology and medicinal chemistry.
2025
Istituto di Scienze e Tecnologie Chimiche "Giulio Natta" - SCITEC - Sede Secondaria Milano - Via M. Bianco
9780128096338
Molecular simulations; Dynamics; Molecular recognition; Drug design; Protein function; Sampling; AI
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/562450
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