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:
My work focuses on the use of homology models for ligand discovery at targets without known structure. I am working to evaluate the information gained from each piece of input data and to standardize the method of applying virtual drug screens at novel targets. I have a particular focus on orphan G-protein coupled receptors.
My work focuses on using large-scale docking to discover ligands with designed polypharmacology or selectivity. I am also interested in leveraging the power of large-scale docking to identify novel analgesics for non-opioid targets.
Virtual docking screens of rapidly expanding chemical libraries enable the identification of novel ligands offering new insight into biological processes and innovative therapeutic leads. Careful calibration of protein models and critical analysis of docking results determine the success of a docking campaign. My research focuses on the application and development of large-scale docking techniques. Additional computational tools such as molecular dynamics simulations are employed to prepare and fine-tune protein structures for docking. Of particular interest are G protein-coupled receptors involved in pain sensation.
Shuo Gu graduated from Hong Kong University of Science and Technology, where he studied protein-ligand interaction using molecular dynamics simulations. He is currently a postdoc in Shoichet lab, working on deorphanization of G protein-coupled receptors, part of the Illuminating The Druggable Genome.
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.
Purchasable chemical space is growing rapidly. We are docking these ever increasing databases. I am exploring what happens to docking when we go to larger and larger databases. I am also working on developing analysis tools for the large-scale docking.
Small-molecule aggregates can be a major source of false positives in early drug discovery. I am working on identifying potential aggregators in drug-repurposing libraries, focusing on drugs with relevance to the SARS-CoV-2 global pandemic. I am also working on further understanding the mechanism of action involved in these aggregate-protein interactions.
My research focuses on novel ligand discovery for orphan and therapeutic GPCRs. Using large-scale docking, a library of hundreds-of-millions of make-on-demand molecules are docked against crystal structures and homology models of target receptors. Top-ranking molecules are tested experimentally. Active molecules are optimized using structure-based drug design methods.
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.
My work in lab focuses on the use of protein crystallography and enzymology to test predictions emerging from large scale docking against AmpC beta-lactamase. Docking screens will also be used for new compound discovery against biologically relevant target like GPCR.
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.
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.
I am a joint graduate student in the Shoichet and Manglik Labs in the Pharmaceutical Sciences and Pharmacogenomics PhD program at UCSF. My background is in synthetic organic chemistry and natural product chemoenzymatic synthesis. I received my bachelor of science from Saint Mary's College of Califonia, and subsequently participated in the NIH PREP at Case Western Reserve University before matriculating at UCSF. I am interested in the pharmacology and structural biology of GPCR-mediated nociception. My work involves structure based design of novel analgesics targeting G-protein coupled receptors.
I am working on methods development in molecular docking including the incorporation of water energies, and calculation of relative binding free energy with higher levels of theory. I will then apply the methods to predict new ligands in both model systems and G Protein-coupled receptors (GPCRs).