Scientist II

My name is Shubhankar Dutta, PhD,  and I have been a professional medicinal chemist since 2020, although I have been a quintessential organic chemist since 2005. I received PhD in 2017 from the University of Kentucky at Lexington, UKY, under the guidance of Prof. Robert B. Grossman. Total synthesis of 7-epi-clusianone was the PhD dissertation topic. Before graduating from UKY, I interned for a one-year in GSK at King of Prussia to understand the science of drug making. The quest for drug-making led me to UCSF for a postdoc in Prof. Dr. Michelle Arkin’s group. If I can describe the GSK stint as the foundation of my understanding of drug discovery, UCSF is the first floor on that foundation, where I first encountered how disease biology influences SAR. During my postdoctoral time, I have been productive, working on three covalent drug discovery projects, which produced later 2 papers and 2 patents. In 2020, when the pandemic stalled the world, I joined Sanford Burnham Prebys (SBP) Medical Discovery Institute as a scientist. Dr. Steve Olson was the director of medicinal chemistry then, and I started a new project: cMYC inhibitor design for treating medulloblastoma in young children. CPCCG, a part of SBP, works like a small biotech company, where we have several projects for drug discovery, and I have also worked on multiple projects. CMYC inhibitor design was such a project that I worked till the end of it—almost 4 years. Using the phenotypic assay, we aimed to develop a brain-penetrant small molecule that could inhibit cMYC. When I was in GSK, I heard several discussions about how solving one problem in medicinal chemistry led to another; in the cMYC project I experienced personally—we got rid of AhR agonism, but the brain penetrance went down, and promiscuity went up. Unfortunately, we had to pause because of the toxicity issue, but I am thrilled that we have been trying to put the cMYC inhibitor. I am an avid learner of new tools in the drug discovery field. Like many other disciplines, Bioinformatics and molecular modeling are two areas where medicinal chemistry is leapfrogging. I try to be ahead of time, so I use MOE and Maestro for my understanding of drug-target interaction but also resort to quantum mechanics calculations, which I need to be more proficient in to find the putative binding mode and its physiological relevance. Single-point energy calculation in Gaussian has emboldened my understanding of the rationale behind the Pi-Pi interactions—and how it can be used to tackle the hERG problem in SAR development. I always embrace new technologies to advance my understanding of drug discovery. Therefore, deepmirror, an AI tool, and Stardrop have become my mainstay in projects where I must design new analogs. In a nutshell, I enjoy the vicissitudes of drug discovery.