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Ligand-Receptor Interactions and Drug Design

Aggeliki Syriopoulou¹, Ioannis Markopoulos², Andreas G Tzakos^3,4

¹Department of Chemistry, Laboratory of Organic Chemistry, National and Kapodistrian University of Athens, Athens, Greece.

Methods in Molecular Biology (Clifton, N.J.)

|March 24, 2021

Summary

This study introduces molecular docking using AutoDock software for drug discovery. It demonstrates docking calf thymus DNA with metal complexes and quercetin to the BcL-xL protein.

Area of Science:

Computational chemistry
Molecular modeling
Drug discovery

Background:

Rational drug design relies on understanding molecular interactions.
Molecular docking predicts ligand-target binding affinity.
AutoDock is a widely used molecular docking suite.

Purpose of the Study:

To provide an introduction to molecular docking using AutoDockTools.
To illustrate the docking process with specific examples.

Main Methods:

Utilized AutoDockTools (a graphical user interface for AutoDock).
Performed molecular docking simulations.
Applied algorithms such as Monte Carlo Simulated Annealing (SA), Genetic Algorithm (GA), and Lamarckian Genetic Algorithm (LGA).

Main Results:

Successfully docked calf thymus DNA with three metal complexes.
Successfully docked the plant flavonoid quercetin to the antiapoptotic protein BcL-xL.
Demonstrated the utility of AutoDock for analyzing metallo-therapeutics and protein-ligand interactions.

Conclusions:

AutoDock is a valuable tool for in silico drug design.
Molecular docking aids in evaluating potential drug candidates like metal complexes and natural compounds.
The described methods facilitate the study of drug-target interactions.

Keywords:

AutoDock DNA Drug design Metal complexes Molecular docking Protein

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