Luan Carvalho Martins

Abstract Transient hypocalcemia is a common complication of total thyroidectomy. This study aimed to evaluate whether machine learning (ML)-based models could enhance early risk prediction and support a robust clinical decision support system for hypocalcemia.

Abstract There is considerable interest in screening ultralarge chemical libraries for ligand discovery, both empirically and computationally1,2,3,4. Efforts have focused on readily synthesizable molecules, inevitably leaving many chemotypes unexplored. Here we investigate structure-based docking of a bespoke virtual library of tetrahydropyridines—a scaffold that is poorly sampled by a general billion-molecule virtual library but is well suited to many aminergic G-protein-coupled receptors.

Chagas disease remains a major health problem in South America, and throughout the world. The two drugs clinically available for its treatment have limited efficacy and cause serious adverse effects. Cruzain is an established therapeutic target of Trypanosoma cruzi, the protozoan that causes Chagas disease. Our group recently identified a competitive cruzain inhibitor (compound 1) with an IC  = 15 µM that is also more synthetically accessible than the previously reported lead, compound 2.