Abstract:

Gastroesophageal reflux disease (GERD) affects millions worldwide, causing chronic acid reflux, and can lead to frequent regurgitation and esophageal cancers. While dietary changes are a first-line treatment, current medications often face challenges such as limited efficacy, side effects, recalls, carcinogenicity, or complex synthesis. This project aims to computationally design a drug targeting the Histamine Receptor H2 (HRH2) in the gut as an alternative GERD treatment. Using Schrödinger Maestro and PDB 7UL3, a docking grid based on HRH2 was created to evaluate potential drug candidates. Four existing HRH2 antagonists were docked to establish benchmarks for docking score and pharmacokinetic properties including low CNS activity, reduced oral absorption, and minimal gut-to-blood permeability. A library of 3,057 ligands from the DUD-E database was screened for binding to key receptor amino acids, Asp98 and Asp186, and pharmacokinetic properties. Compounds with 2 or 3 six-membered rings showed the most promising profiles. A scaffold-based approach identified quinolines and azastilbenes as strong candidates. The optimal aza-stilbene demonstrated stronger docking scores, easier synthesis, and better pharmacokinetic properties than that of the quinolines, and in many aspects, better than known HRH2 antagonists. This compound was synthesized using a simple, one-step reaction with benzaldehyde and aniline in water at room temperature. The product was characterized by FTIR. This project demonstrates a new aza-stilbene scaffold that could be employed for new drugs to treat GERD.

Speaker:

Nihar Kummetha, North Carolina School of Science and Mathematics

Nihar Kummetha is an incoming undergraduate student at the University of
Pennsylvania planning to major in Biochemistry and minor in Statistics and Data Science as a
Vagelos Molecular Life Sciences Scholar.