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Video: Shoichet, channeling William F. Buckley, offers a vigorous defense of docking and high-throughput screening for the graduate student retreat (interviewed by Emily Crawford, channeling Steven Colbert).
Podcast: Shoichet, in a public interview, tries desperately to sound less confused than he actually is.
Recent reviews, book chapters, and papers:
I use novel physical, computational, and chemical approaches to improve the scoring function in molecular docking. I design, implement and validate the scoring function of molecular docking by adding corrections to the calculation of van der Waals forces and entropic effect. The new scoring function in molecular docking will help to predict the binding affinity between the protein and ligand. In turn, this will help to identify novel small molecules that bind to a protein target of interest and therefore are useful starting points for drug discovery.
Ultra-large library docking enables researchers to find an ever-increasing amount of high-affinity virtual screening hits for structure-based drug discovery. My work revolves around developing new ways to prioritize hit compounds on the basis of maximally exploring chemical space with analogues, and developing algorithms to enable this prioritization. I have an additional research interest in neuropsychiatric conditions, and make use of virtual screening in order to identify potential compounds capable of altering behavioural phenotype.
As the sizes of make-on-demand libraries are growing to the scale of tens of billions of molecules and beyond, it is becoming increasingly difficult to explicitly DOCK libraries of this size. I am using machine learning and cheminformatic algorithms to develop chemical space exploration techniques that are capable of efficiently traversing libraries of this size in the pursuit of new active chemical matter.
My research focuses on structure-guided discovery of novel ligands targeting GPCRs involved in metabolic diseases and the application of ultra-large library docking methods.
Virtual screening has become somewhat a proven and well-appreciated computational method for hits identification and optimization. My research focuses on the application of ultra-large library docking techniques and the discovery of novel ligands against GPCRs involved in pain and other CNS disorders, as well as for COVID-19.
My research focuses on high-throughput virtual screening of macrocyclic compounds through molecular docking. Macrocycles are molecules with rings containing twelve or more atoms. These large rings often allow for structural preorganization and making extended contacts with target proteins, thus making macrocycles particularly interesting in the context of drug discovery.
My work focuses on virtual screening campaigns for a variety of clinically significant targets, including those involved in the progression of COVID-19, HIV, and cancer. I am also developing methods to expedite ultra-large screening campaigns and create an automated pipeline for tuning docking parameters. The goal is to keep pace with growing compound libraries and minimize manual labor in the preparation of screening campaigns.
Signal transduction is one of the most essential biological processes in all living organisms. G protein-coupled receptors (GPCRs) constitute the largest and most diverse family of cell surface receptors in the human genome, responsible for communicating messages between the cell's external and internal environments. A primary goal of my research is to integrate advancements in both our understanding of GPCR structure and in structure-based docking techniques, to realize the potential in targeting novel GPCR binding sites for drug discovery, as well as applying these techniques for exploring the functions of orphan GPCRs.
My project uses computational based molecular docking, an approach widely used for drug discovery. My interest has two foci: first, I am testing the impact of new, multi-billion compound libraries that the lab has introduced to the field, to discover new drug candidates by using a model system, and I am applying those new libraries to, in particular, discover new drug leads for a GPCR, which is involved in several genetic and metabolic diseases, and for which new drug leads are much wanted. In the future, I hope to expand my knowledge on pharmaceutical and medicinal chemistry and combine my background in structural biology and biochemistry to discover new chemical probes for mechanistic studies on membrane proteins.
GPCR dynamics play a central role in their activation mechanism. I am investigating fast computational methods to predict the function of novel ligands based on how they perturb the dynamics of active and inactive GPCR states. I am also working on heuristics to help in prioritizing subsets of the make-on-demand libraries as they keep on growing exponentially.
My overarching scientific interest lies in developing computer models to speed up basic and translational science discovery. In the lab, I develop drug discovery methods that scale independently to dockable library size. One approach is to work at the building block level, which makes up the shared base moieties in dockable libraries. The ultimate goal is to match the results of full library docking, but at a fraction of the time and resources.
Phospholipidosis and aggregation are two major confounds in early drug discovery. In addition to screening drugs and hit compounds, I work to further clarify their characteristics and mechanisms of these phenomena. My overarching goal is to apply my background in natural products biochemistry and neuroscience to diverse aspects of small molecule drug discovery.
As a biophysics student in the Shoichet lab, I aim to adapt computational methods to screen for ligands which bind in unconventional ways.
Publications:
Cater, R.J., ... Pepe, J., et al. Structural basis of omega-3 fatty acid transport across the blood–brain barrier. Nature 595, 315–319 (2021). https://doi.org/10.1038/s41586-021-03650-9 Nygaard, R., ... Pepe, J., et al. Structural basis of peptidoglycan synthesis by E. coli RodA-PBP2 complex. Nat Commun 14, 5151 (2023). https://doi.org/10.1038/s41467-023-40483-8 Smith, M. S., ... Pepe, J., et al. Docking for molecules that bind in a symmetric stack with SymDOCK. bioRxiv (2023). https://www.biorxiv.org/content/10.1101/2023.10.27.564400v1
My research interests include the development and application of computational drug design methods with an emphasis on structure-based and fragment-based strategies. Currently, I am involved in projects that aim to discover novel ligands for the SARS-CoV-2 macrodomain, as well as, the cannabinoid receptor, CB2.
Current biophysical models can predict protein-ligand binding affinities, but the connection between ligand binding and receptor activation remains unclear. In collaboration with
Using MD-sampled energies in Flexible Receptor DOCK to improve drug discovery for T4 lysozyme and SARS-CoV-2 NSP3 Mac1, with applications to selectivity.
I am the lab manager extraordinaire for both the Shoichet and Manglik Labs with expertise in protein biochemistry. I received my BS in Chemistry at the University of Kansas where I honed my skills in the outer-membrane focused lab of Joanna Slusky before venturing to the GPCR world. With a passion for scientific research and a meticulous attention to detail, I play a pivotal role in ensuring the smooth operation of our cutting-edge research. I facilitate the day-to-day activities, coordinate equipment, and assist lab members in achieving their scientific goals.
My work focuses on using large-scale molecular docking coupled with chemoinformatic methods to identify novel modulators of non-opioid pain signaling. I am particularly interested in the translation of in silico docking hits to in vitro and in vivo models, with an emphasis on understanding the pharmacodynamic effects of novel ligands at different levels of complexity. I use my graduate training in pharmaceutical sciences and molecular interactions as well as my undergraduate training in neuroscience to understand these complex systems.
The rapid growth of purchasable chemical space has been dominated by compounds formed via a handful of reactions, leaving many scaffolds with proven biological relevancy out of virtual databases. My work focuses on using advancements in organic synthesis to diversify synthetically tractable virtual libraries. I am also interested in how these underexplored chemotypes can be used as tools to improve ligand discovery and understand complex biological systems. My undergraduate experience in organic chemistry and graduate training in the UCSF Chemistry and Chemical Biology program inform my work.
My research focuses on developing a benchmarking system for evaluating free energy calculation methods in lead compound optimization, applying implicit solvent models in hit picking. I also work with Elissa Fink on using large-scale docking to discover ligands with designed polypharmacology or selectivity.
My research interests lie in the field of structure-based drug discovery, with a focus on G protein-coupled receptors and other diseases-related proteins. GPCRs play a crucial role in physiology and pathogenesis, and approximately 30% of approved drugs target GPCRs. My work involves using docking techniques to identify potential ligands for GPCRs and try to predict the efficacy of them. I am also working on a project that develops analogs for novel compounds. Through my work, I aim to contribute to the development of novel therapeutics for a wide range of diseases.