The a16z Show
Journal Club: Finding New Antibiotics with Machine Learning, What Coronavirus Structures Tell Us
· Summarized
Key takeaways
- Machine learning represents a revolutionary approach in drug discovery, showcasing the potential to identify new antibiotics that could combat antibiotic resistance.
- Halicin, the newly identified antibiotic, demonstrates a unique mechanism of action, opening doors for further development despite the challenges faced in the antibiotic market.
- Understanding the structural differences of spike proteins between SARS-CoV and SARS-CoV-2 is crucial for developing effective treatments and vaccines against COVID-19.
- The presence of a furin cleavage site in the spike protein of SARS-CoV-2 may play a significant role in its heightened infectivity compared to earlier SARS strains.
- The contrasting results between studies on antibody recognition of SARS-CoV-2 and SARS-CoV underscore the complexity of immune response and warrant further investigation.
Summary
Novel Antibiotic Discovery Using Machine Learning
In the first segment, Lauren Richardson, along with A16Z partners Vijay Pandey and Andy Tran, discusses a groundbreaking paper on using machine learning to discover new antibiotics, focusing on a compound called Halicin. This paper describes a deep learning model trained on two large datasets to predict the likelihood of various compounds inhibiting E. coli. Halicin not only showed effective antibiotic properties but also represented a new mechanism of action distinct from existing antibiotics, addressing the critical issue of antibiotic resistance. The conversation highlights the complexities involved in antibiotic development, combining both scientific challenges and business considerations, ultimately emphasizing the potential for machine learning to democratize drug discovery.
Understanding SARS-CoV-2 through Structural Biology
In the second part, Judy Savitskaya joins Lauren to delve into two key articles about the novel coronavirus, SARS-CoV-2. They discuss the importance of the spike protein's structure for viral entry into host cells and its implications for vaccine and drug design. Both papers reveal similarities and differences between the spike proteins of SARS-CoV and SARS-CoV-2, notably regarding the presence of a unique furin cleavage site in the newer virus, which may enhance its infectivity. The contrasting findings about antibody effectiveness against these spike proteins highlight the evolving nature of research in understanding COVID-19's mechanisms and treatment strategies, underscoring the rapidly advancing field of virology.
Sponsors
- A16Z Podcast · This inaugural episode covers recent advances from the scientific literature -- what papers we’re reading, and why they matter from our perspective at the intersection of biology & technology for bio journal club.
Show notes
a16z Journal Club (part of the a16z Podcast), curates and covers recent advances from the scientific literature -- what papers we’re reading, and why they matter from our perspective at the intersection of biology & technology (for bio journal club). This inaugural episode covers 2 different topics, in discussion with Lauren Richardson:
0:26 #1 identifying new antibiotics through a novel machine-learning based approach -- a16z general partner Vijay Pande and bio deal partner Andy Tran discuss the business of pharma; the specific methods/ how it works; and other applications for deep learning in drug discovery and development based on this paper:
- "A Deep Learning Approach to Antibiotic Discovery" in Cell (February 2020), by Jonathan Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andres Cubillos-Ruiz, Nina Donghia, Craig MacNair, Shawn French, Lindsey Carfrae, Zohar Bloom-Ackermann, Victoria Tran, Anush Chiappino-Pepe, Ahmed Badran, Ian Andrews, Emma Chory, George Church, Eric Brown, Tommi Jaakkola, Regina Barzilay, James Collins
11:43 #2 characterizing the novel coronavirus causing the COVID-19 pandemic -- a16z bio deal partner Judy Savitskaya shares what we can learn from the protein structures; the relationship to the 2002-2004 SARS epidemic; and more based on these two research articles:
- "Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein" in Cell (April 2020), by Alexandra Walls, Young-Jun Park, M. Tortorici, Abigail Wall, Andrew McGuire, David Veesler
- "Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation" in Science (March 2020), by Daniel Wrapp, Nianshuang Wang, Kizzmekia Corbett, Jory Goldsmith, Ching-Lin Hsieh, Olubukola Abiona, Barney Graham, Jason McLellan
You can find these episodes at a16z.com/journalclub.
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