Todd Sullivan, Ph. D.
Office Location
I obtained my Bachelor of Science in Chemistry from the University of Connecticut. I worked in the industry for a short period as an analytical chemist at Boehringer Ingelheim and later obtained my Ph.D. from Stony Brook University in organic medicinal chemistry. While at Stony Brook, I discovered a new class of antibacterial compounds to target Mycobacterium tuberculosis. These compounds were active in a mouse model of a bioterrorist target Francisella tularensis. At Yale University, I completed a post-doctoral position and eventually became an assistant research scientist. While at Yale, I worked on designing and synthesizing (22 steps) bifunctional inhibitors to target an enzyme in human immunodeficiency virus (HIV). My research focuses on drug discovery using computer aided design. Specifically, we use software called Molecular Operating Environment (MOE) to help design compounds to target enzymes that are in drug resistant bacteria. The goal of the project is to design inhibitors/drugs to target these enzymes and treat the patient.
Degrees and Certifications
- Ph.D., Organic-Medicinal Chemistry, Stony Brook University
- M.S., Organic-Medicinal Chemistry, Stony Brook University
- B.S., Chemistry, University of Connecticut
Teaching Responsibilities
- CH 103: Introduction to Forensic Chemistry
- CH 119: General, Organic & Biochemistry Lab
- CH 120: Drugs and Their Implications to Society
- CH 201: Introduction to Biochemistry Clinical Nutrition
- CH 221: Organic Chemistry I
- CH 222: Organic Chemistry II
- CH 223: Organic Chemistry I Lab
- CH 224: Organic Chemistry II Lab
- CH 326 and CH 526: Medicinal Chemistry and Pharmacology
- CH 341: Biochemistry I
- CH 353 and CH 557: Instrumental Analysis Lab
- CH 534, NMR: Organic Structure Determination
- CH 534L, NMR: Organic Structure Determination Lab
- CH 590: Chemical Info: Sources & Tech
Research Interests
Virtual Screening of Different beta-lactamases enzymes and ClpP protease enzymes from Staphylococcus aureus to identify Pharmaceutical Hits
Antibiotic resistance is a major global threat, killing millions annually and jeopardizing modern medicine because bacteria evolve to resist drugs designed to treat them. Beta-lactamases are enzymes produced by bacteria that afford multi-resistance to beta-lactam antibiotics. Beta-lactamase confers antibiotic resistance by changing the antibiotics' structure. We are also investigating a protease ClpP (Caseinolytic peptidase P) that is in S. aureus maintaining protein homeostasis. The allosteric sites of both enzymes are also being investigated. Here, we describe the use of Virtual screens with multiple criteria and different crystal structures for identifying novel beta-lactamase and protease ClpP inhibitors. Utilizing Molecular Operating Environment (MOE) as the software for our virtual screens. Our virtual screen model evaluates compounds that can be purchased for less than one-hundred dollars, therefore they can eventually be evaluated in vitro and in vivo. The Virtual Screen model that we employ uses multiple poses of the virtual compounds evaluating them via multiple criteria. Two different models of the active site are utilized. Then an excel Pivot table is used to identify the duplicates with the logic, being the more times, a virtual compound appears with a good score it may be of interest to test in vitro. We also use the MOE filter tool also used to reveal the compounds with the highest score. ADME studies are being performed on our top theoretical pharmaceutical hits. We have identified ractopamine and a rexinoid inhibitor both are repurposed drugs, as a 50 µM inhibitor in vitro against beta-lactamase. We think a novel method of identifying pharmaceutical hits has been revealed. The hope is to treat the patient with a Beta-lactamase inhibitor and then the normal penicillin like drug. ClpP protease is a new drug target, and we are hoping to discover novel inhibitors. Preliminary results appear encouraging, providing hope that novel drug candidates will be identified and that our computational workflow will prove useful on other pharmaceutical targets.
