PeptGPT
Accelerating Protein Engineering with GPT-4
*A novel way to design proteins*
-Cal Hacks 2023 Judge
-Problem-
Biotech researchers waste valuable time
designing proteins for experiments
-Our Solution-
Use ChatGPT-4 and
Large Language Models (LLMs)
to design proteins
A More Efficient Design Process
Identify Desired Function
Literature Search
Candidate Protein Families
Protein Sequence Generation
Test Protein Folding
Identify Desired Function
Single Fusion Protein Sequence
Protein Folding in ESM2
Usual
timeline:
PeptGPT
timeline:
We make in minutes
what researchers made in weeks
Save Time with AI
Our Design
User enters keyword into GPT-4 to produce Protein Family (PFAM) value
Interpro searches databases for specific protein sequence by PFAM value
Probability statistics assembles each part of a large protein sequence
ESM-2 folds protein sequence
ESM-2 Meta
Our Competitors
overproduce protein sequences,
While we prioritize design by function
Competition
Focus on Protein Design
Cheap
Accurately Generate Proteins
Fast
Easy to Use
AI Gene Circuit Design
AI Protein Design
PeptGPT
✓
✓
✓
✓
✓
✓
✓
✓
✓
Protein Engineering’s Fiscal Value
Market Value (2023)
$3 Billion
Expected Market Value (2033)
$10 Billion
Current Compound Annual Growth (CCAG) rate
13.6%
Project Timeline
Y1: Funding & Networking
Y0: Develop Product
Y2: Market Product
Y4: Company Expansion
Y5: Company Stabilization
Y3: Company Expansion
%
Board of Founders
Nathaniel Sheps,
BS Chemical Engineering Johns Hopkins University (WIP)
Alexander Chow,
BA Computer Science
UC Berkeley (WIP)
Sreenivas Eadara,
MD-PhD Biomedical Engineering Northwestern University (WIP)
Rajashekar Vennavelli,
MS Computer Science Santa Clara University (WIP)
We Need Your Help
With Batch-17’s networking and financial aid,
we can dominate the protein engineering market
PeptGPT