ADMET profiling of geographically diverse phytochemical using chemoinformatic tools

Area of Science:

• Natural Product Chemistry
• Chemoinformatics
• Drug Discovery

Background:

• Phytocompounds offer unique therapeutic potential but often fail drug development due to poor pharmacokinetics.
• Preassessing absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties is crucial for successful drug discovery.
• Limited data exists on ADMET profiles of phytocompounds from India, Brazil, and South Africa.

Purpose of the Study:

• To develop a predictive model for assessing ADMET properties of phytocompounds.
• To identify phytocompounds with favorable ADMET profiles and potential anticancer activity.
• To establish an open-access database (ADMET-BIS) for facilitating drug development.

Main Methods:

• Utilized biologically diverse databases: Phytochemica, SerpentinaDB, SANCDB, and NuBBE_DB.
• Employed chemoinformatic tools including Qikprop, pkCSM, and DataWarrior for ADMET prediction.
• Screened compounds against established pharmacokinetic criteria.

Main Results:

• Identified 24 phytocompounds that satisfy all predicted ADMET properties.
• Discovered five compounds exhibiting potent anticancer activity against tested cancer cell lines.
• Established the ADMET-BIS database, integrating diverse phytocompound data.

Conclusions:

• The ADMET-BIS database provides a valuable resource for identifying drug-like phytocompounds.
• The identified compounds represent promising candidates for further preclinical and clinical development.
• This approach accelerates the drug discovery pipeline by prioritizing compounds with favorable ADMET profiles.