Evaluating AutoGrow4 - an open-source toolkit for semi-automated computer-aided drug discovery

Area of Science:

• Computational chemistry
• Medicinal chemistry
• Drug discovery

Background:

• Drug discovery is complex, costly, and has a high failure rate.
• De novo ligand design methods are increasingly popular for exploring chemical space.
• Autogrow4 is open-source software utilizing genetic algorithms and molecular docking for de novo ligand generation.

Purpose of the Study:

• To evaluate the utility and limitations of Autogrow4 for de novo ligand design.
• To review literature applications of Autogrow software from 2009 to present.
• To assess Autogrow4 from pharmacodynamic and pharmacokinetic perspectives.

Main Methods:

• Literature review of Autogrow applications using Scopus database.
• Analysis of Autogrow4's capabilities in generating novel ligands.
• Evaluation of pharmacodynamic and pharmacokinetic implications of generated compounds.

Main Results:

• Autogrow4 is a valuable tool for expert molecular modelers in de novo ligand design.
• The software's open-source nature allows for extensive protocol customization.
• Limitations include restricted control over pharmacokinetic properties and a tendency for high molecular weight outputs.

Conclusions:

• Autogrow4 offers significant advantages for rational and efficient drug design.
• Expert users can leverage its features for generating high-quality compounds.
• Further development may be needed to address pharmacokinetic limitations and molecular weight bias.