| Autor: |
Bryce K. Allen, Meghana M. Kulkarni, Brian Chamberlain, Timothy Dwight, Cheryl Koh, Ramya Samant, Finith Jernigan, Jamie Rice, Dazhi Tan, Stella Li, Kristen Marino, Huang Huang, Evan Chiswick, Bethany Tesar, Sam Sparks, Zhixiong Lin, T. Dwight McGee, István Kolossváry, Charles Lin, Sharon Shechter, Holly Soutter, Cecilia Bastos, Mohammed Taimi, Sujen Lai, Alicia Petrin, Tracy Kane, Steven Swann, Humphrey Gardner, Christopher Winter, Woody Sherman |
| Rok vydání: |
2022 |
| DOI: |
10.1101/2022.05.23.493001 |
| Popis: |
The protein STING (stimulator of interferon genes) is a central regulator of the innate immune system and plays an important role in antitumor immunity by inducing the production of cytokines such as type I interferon (IFN). Activation of STING stems from the selective recognition of endogenous cyclic dinucleotides (CDNs) by the large, polar, and flexible binding site, thus posing challenges to the design of small molecule agonists with drug-like physicochemical properties. In this work we present the design of SNX281, a small molecule STING agonist that functions through a unique self-dimerizing mechanism in the STING binding site, where the ligand dimer approximates the size and shape of a cyclic dinucleotide while maintaining drug-like small molecule properties. SNX281 exhibits systemic exposure, STING-mediated cytokine release, strong induction of type I IFN, potent in vivo antitumor activity, durable immune memory, and single-dose tumor elimination in mouse models via a Cmax-driven pharmacologic response. Bespoke computational methods – a combination of quantum mechanics, molecular dynamics, binding free energy simulations, and artificial intelligence – were developed during the course of the project to design SNX281 by explicitly accounting for the unique self-dimerization mechanism and the large-scale conformational change of the STING protein upon activation. Over the course of the project, we explored millions of virtual molecules while synthesizing and testing only 208 molecules in the lab. This work highlights the value of a multifaceted computationally-driven approach anchored by methods tailored to address target-specific problems encountered along the project progression from initial hit to the clinic. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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