A virtual library of small molecules mimicking dipeptides

Area of Science:

• Medicinal Chemistry
• Computational Drug Discovery
• Chemical Biology

Background:

• Virtual combinatorial libraries accelerate drug discovery by predicting synthetic reactions and enabling virtual screening of vast chemical spaces.
• Targeting proteins that bind small peptides is a key area in drug development.

Purpose of the Study:

• To generate a novel small-molecule dipeptide mimic library for targeting peptide-binding proteins.
• To synthesize and evaluate compounds from this library for biological activity.

Main Methods:

• In silico reaction of amino acid mimics to create a virtual library of 2,036,819 unique dipeptide mimics.
• Docking calculations to identify potential drug candidates.
• Synthesis and in vitro testing of selected compounds against WDR5 and histamine receptors (H1-H4).

Main Results:

• A library of 2,036,819 unique dipeptide mimics was computationally generated.
• Two compounds were synthesized and tested.
• The synthesized compounds exhibited the highest potency against the histamine H3 receptor, with dissociation constants (Ki) in the two-digit micromolar range.

Conclusions:

• The study successfully generated and validated a virtual dipeptide mimic library for drug discovery.
• The synthesized compounds demonstrate potential as leads for targeting the histamine H3 receptor.
• This approach highlights the utility of virtual screening and combinatorial library generation in identifying novel bioactive molecules.