Construction of a virtual combinatorial library using SMILES strings to discover potential structure-diverse PPAR...

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Pharmacology

Background:

• Peroxisome proliferator-activated receptors (PPARs) are key targets for metabolic diseases.
• Developing novel PPAR modulators requires efficient methods for compound library generation and screening.

Purpose of the Study:

• To construct a large virtual combinatorial library of potential PPAR modulators.
• To identify novel chemical entities as potential drug leads for type 2 diabetes and metabolic diseases.
• To develop a visualized method for generating virtual combinatorial libraries.

Main Methods:

• Construction of a 1,226,625-compound virtual library using SMILES strings based on PPAR modulator structures.
• Application of ADME filters to remove compounds with poor drug-like properties.
• Conversion of the library to SDF and MOL2 formats.
• Docking of the filtered library to PPARgamma using DOCK 4.0.
• Visualization of the library construction method using Visual Basic.net.

Main Results:

• A filtered virtual library of potential PPAR modulators was generated.
• Several novel chemical entities with potential as PPARgamma ligands were identified.
• The developed method facilitates the generation of diverse virtual combinatorial libraries.

Conclusions:

• The study presents an effective computational approach for discovering potential drug leads targeting PPARgamma.
• The methodology aids in the identification of novel therapeutics for type 2 diabetes and related metabolic disorders.
• The visualized library generation technique is adaptable for creating other virtual compound libraries.