SkelGen: a general tool for structure-based de novo ligand design

Area of Science:

• Computational chemistry
• Drug discovery
• Medicinal chemistry

Background:

• The pharmaceutical industry faces declining productivity, driving innovation in drug design.
• In silico structure-based design utilizes molecular fragments for novel drug candidate development.
• SkelGen is an in silico tool exemplifying this fragment-based approach.

Purpose of the Study:

• To review the SkelGen algorithm for in silico drug design.
• To assess SkelGen's capability in identifying chemically diverse fragments for drug targets.
• To evaluate SkelGen's performance in de novo structure-based drug design.

Main Methods:

• The SkelGen algorithm was employed for fragment identification and de novo compound design.
• The methodology involved structure-based design targeting DNA gyrase and the estrogen receptor.
• Partial protein flexibility was incorporated during the design process for the estrogen receptor.

Main Results:

• SkelGen successfully identified chemically diverse fragments with potential binding affinity for DNA gyrase.
• The first purely de novo structure-based design yielded five compounds active against the estrogen receptor at micromolar levels.
• The algorithm's ability to handle partial protein flexibility in design was demonstrated.

Conclusions:

• SkelGen represents a promising in silico approach for fragment-based and de novo drug design.
• The algorithm shows potential for developing diverse drug candidates targeting various biological receptors.
• Future developments in de novo design algorithms are expected to significantly impact drug discovery.