Vijay Pande, a general partner at Andreessen Horowitz with a focus on biotechnologies, joins Judy Savitskaya, a bio deal partner specializing in virology. They delve into groundbreaking machine learning methods for antibiotic discovery, particularly the novel antibiotic Halicin. The conversation reveals the potential to combat antibiotic resistance. Savitskaya also shares insights on the coronavirus structures, linking them to past SARS research and discussing their implications for vaccine development and viral entry mechanisms.
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insights INSIGHT
Antibiotic Development Challenges
Scientific challenges and business obstacles hinder antibiotic development.
Innovative antibiotics are reserved for severe cases, limiting their profitability.
insights INSIGHT
Deep Learning for Antibiotic Discovery
Deep learning models can predict antibiotic effectiveness without preset chemical structure info.
This allows for identifying novel drug structures, unlike traditional methods that yield similar molecules.
insights INSIGHT
Halicin's Properties
Halicin disrupts bacterial pH balance, a novel mechanism.
It effectively inhibits various pathogens, including E. coli and C. diff, and eliminates persistent cells.
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Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein
Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein
David Wiesler
Alexandra Walls
Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation
Nianshuang Wang
Barney Graham
Jory Goldsmith
Olubukola Abiona
Kizzmekia Corbett
Ching-Lin Hsieh
Jason McLellan
Daniel Wrapp
This research paper presents a 3.5-angstrom-resolution cryo-electron microscopy structure of the 2019-nCoV spike glycoprotein in its prefusion conformation. The study highlights the protein's structure and its implications for understanding how the virus binds to host cells, which is crucial for developing vaccines and therapeutic antibodies. The findings also show that the 2019-nCoV spike protein binds more tightly to the ACE2 receptor than the SARS-CoV spike protein.
A Deep Learning Approach to Antibiotic Discovery
A Deep Learning Approach to Antibiotic Discovery
Andres Cubillos-Ruiz
Emma Chory
Tommi Jaakkola
Anush Chiappino-Pepe
James Collins
Lindsey Carfrae
Shawn French
George Church
Kevin Yang
Eric Brown
Wengong Jin
Regina Barzilay
Nina Donghia
Victoria Tran
Craig MacNair
Zohar Bloom-Ackermann
Kyle Swanson
Ian Andrews
Ahmed Badran
Jonathan Stokes
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:
a16z Podcast 
