A Reverse Engineering Approach to Optimize Chemical Synergy Between Target and Phenotype: Bridging the Cancer and...

Area of Science:

• Drug discovery and development
• Computational chemistry
• Pharmacology

Background:

• Linking drug mechanism of action (MoA) to disease phenotypes is a major challenge in pharmaceutical research.
• Phenotypic and target-based screening are primary methods for identifying drug candidates.
• Existing methods often require direct biochemical assays for target validation.

Purpose of the Study:

• To present a reverse engineering approach for identifying drug candidates from phenotypic screening data.
• To bypass the need for direct biochemical assays by using a reference drug's MoA as a template.
• To enable cross-linking of therapeutic indications by transferring drug-target knowledge.

Main Methods:

• Developed an in silico protocol to select compounds sharing a reference drug's target profile.
• Utilized pharmacophore patterns and molecular envelop constraints to ensure similar MoA.
• Applied the approach to identify anti-malarial compounds using a cancer drug (BIX-01294) as a reference.

Main Results:

• The in silico protocol successfully identified general cytotoxic compounds with novel chemical classes.
• Selected compounds exhibited a similar MoA to the reference drug, inhibiting human histone lysine methyltransferase (HKMT).
• The method facilitated drug discovery for malaria by leveraging knowledge from cancer research.

Conclusions:

• The reverse engineering approach effectively identifies drug candidates by inferring MoA from phenotypic data and reference drugs.
• This method is valuable for drug discovery in indications where target-based assays are difficult or unavailable.
• It allows for the transfer of drug-target knowledge between different therapeutic areas, such as cancer and malaria.