MacrolactoneDB is a central repository of macrolactones and their bioactivities. It enables machine learning to inform synthetic biology and medicinal chemistry efforts for designing new/better drugs. Our new paper in Nature Scientific Reports is the result of a collaboration with Phyo Phyo Kyaw Zin and Sean Ekins (Collaborations Pharmaceuticals).

Excited to announce our latest publication and collaboration with the Fourches group in the NC State Chemistry, “SIME: synthetic insight-based macrolide enumerator to generate the V1B library of 1 billion macrolides”. This advance allows in silico libraries of macrolides to be constructed based on the knowledge of polyketide biosynthesis. It’s a first step towards the generation of new bioactive macrolides by combining synthetic biology and computational chemistry.