Classical and Quantum Molecular Simulations in Drug Design

Dear Colleagues,

Molecular simulation methods in drug design are computational techniques that use mathematical models and algorithms to study the structure, dynamics and interactions of molecules, such as proteins and drugs. It can help understand the molecular mechanisms of drug action, predict the binding affinity and selectivity of drug candidates, optimize drug properties and pharmacokinetics, and discover new drug targets and mechanisms. Some of the common molecular simulation methods in drug design are molecular docking, predicting the preferred orientation and conformation of a drug molecule when it binds to a target protein or receptor; molecular dynamics (MD), simulating the movement and behavior of atoms and molecules over time using Newtonian laws of motion and force fields; Monte Carlo (MC), that uses random sampling to approximate the behavior and outcomes of complex systems, such as drug design, and can help to explore the effects of uncertainty, variability and heterogeneity in drug design, and evaluate the performance and robustness of different design strategies; free energy calculations, estimating the thermodynamic quantity that determines the spontaneity and equilibrium of a molecular process, such as the binding of a drug to a biomolecular target; and quantum mechanics (QM), describing the electronic structure and properties of atoms and molecules using the principles of quantum physics and useful to model chemical reactions.

In this Special Issue, I aim to draw together research papers and reviews from experts in the field of molecular simulation that highlight traditional and new computational methods and strategies to discover and design new drugs.

Dr. Osvaldo Andrade Santos-Filho
Guest Editor

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