Shoichet receives DeLano Award for Computational Biosciences
Given annually by the American Society for Biochemistry and Molecular Biology (ASBMB), the DeLano Award honors a scientist “for the most accessible and innovative development or application of computer technology to enhance research in the life sciences at the molecular level.”
The award will be formally presented at the society’s annual meeting in Chicago in April 2017, where Shoichet will also present a lecture. ASBMB is a 110-year-old 12,000-member organization that publishes several major scientific journals.
Writing in support of Shoichet’s nomination, fellow scientists lauded him as “the preeminent computational biochemist of his generation” and “the most influential academic in computational drug discovery today.”
Indeed, his influence in the burgeoning field is reflected in the more than 20,000 citations that his 160 peer-reviewed papers have received in others’ scientific publications. Computational biology uses software to predict and analyze molecular interactions, thus aiding the process of new drug discovery.
Shoichet’s work: from DOCK to SEA
Shoichet’s award-winning computational biology work began with his doctoral work under School emeritus faculty member Tack Kuntz, PhD, in the 1980s. The Kuntz Lab pioneered computational drug discovery via molecular docking and developed DOCK, the first widely used program.
In docking, a computer program virtually screens the 3D structures and other attributes of small molecules and ranks the strength with which they bind to key sites on protein molecules. The ultimate goal is to use such binders (ligands) to therapeutically alter the target molecule’s behavior, such as inhibiting the activity of an enzyme required by a virus or of a protein gone awry in cancers, autoimmune, or neurodegenerative diseases.
Over the ensuing decades and 14 versions, “Brian has systematically and actively advanced DOCK in many important directions, [ensuring that] it and its derivatives remain a critical universal computational tool used across the spectrum of drug discovery,” wrote Ken Dill, PhD, in supporting Shoichet’s award nomination. Dill is a former School faculty member and now a faculty member and director of the Laufer Center for Physical and Quantitative Biology at Stony Brook University.
By way of examples from just the past year or so, the Shoichet Lab—working closely with collaborators conducting physical experiments—has applied computational docking to projects that include:
- Discovering a new opioid drug candidate that blocks pain as effectively as morphine in mice, without triggering dangerous side effects and apparently without addictive properties. Using the atomic-level structure of the mu-opioid receptor determined by Nobel laureate Brian Kobilka, MD, of the Stanford School of Medicine, Shoichet Lab researchers docked millions of molecules in myriad orientations to find compounds that were then optimized and tested in mice. This work was in collaboration with Bryan Roth, MD, PhD, of the University of North Carolina School of Medicine, and others.
- Developing molecular probes that reveal the biological functions of key cell membrane proteins, so they can potentially be targeted by drugs. More than one of four drugs work by binding G-protein coupled receptors (GPCRs)—such as the above-noted opioid receptors. But there are at least 120 GPCRs, dubbed “orphans,” whose roles in health and disease remain unknown. The Shoichet Lab, again collaborating with the Roth group at UNC, demonstrated a generalizable approach to determining such orphan receptors’ functions by discovering a molecule (out of millions screened via docking) that selectively activated a specific orphan GPCR, which was found to suppress fear conditioning in mice.
- Investigating the role of certain enzymes discovered in humans in the past decade, which are thought to promote tumors by altering gene activity in prostate, colon, and breast cancers. This work pioneered using docking results for fragments—less complex molecules—to subsequently design small molecules. Working with the lab of department colleague Danica Fujimori, PhD, Shoichet lab researchers performed 1.5 trillion computer-calculated combinations of more than 600,000 fragments with the target’s catalytic site to help develop selective inhibitors for enzymes with few previously known ligands.
In addition to using biophysical docking to discover new drug leads and molecular probes, Shoichet took a different computational tack, working with department colleagues Michael Keiser, PhD, and John Irwin, PhD, to develop the Similarity Ensemble Approach (SEA). SEA statistically relates proteins based on the chemical similarity of their ligands. Its applications include the prediction of ligands’ off-target activities ranging from the adverse (e.g., side effects, drug interactions) to potential new treatment uses for approved medications.
Multiplying impact via accessible tools
Notably in keeping with the Delano Award’s spirit and criteria, Shoichet has made a special effort, working in particular with department colleague John Irwin, PhD, to make tools for predicting protein-ligand interaction readily accessible to the wider scientific and drug discovery community. These include:
- ZINC: A free online database of more than 35 million commercially available compounds for virtual screening in ready-to-dock, 3D formats. It receives more than 2 million visits each year.
“The importance of ZINC in both academic and commercial drug discovery is hard to overstate,” says Jacobson. “ZINC is far-and-away the dominant resource, because it is free, easy to use, useful, and well supported.”
- DUD and DUD-E: A free database, drawn from ZINC, that provides challenging decoys (i.e, Database of Useful Decoys—Enhanced) to help benchmark and evaluate molecular docking programs.
The site “has played a key role in providing broadly accepted standards in the field,” says Jacobson. “Previously, there was a profusion of different docking test sets of widely varying quality and difficulty, making it challenging to evaluate claims and progress in the field.”
- DOCK Blaster: A tool designed to provide those without expert training in molecular docking the ability to discover and rank potential ligands from the ZINC database for a particular protein.
- SEA: An online tool to search large compound databases and predict ligand targets. (The method has been cited in scientific papers nearly 1,300 times since its introduction in 2007.)
As Jacobson concluded in his award nomination letter, “While Brian’s incisive intellect and technical sophistication have clearly been critical factors in the huge impact he has had, I would argue that his generosity of spirit has been equally important, multiplying his impact through his many collaborations and service to the scientific community.”
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