310copilot

310ai’s Copilot is a #Text2Protein platform using AI to assist researchers. Try Copilot via the link below or message us if you have any questions.

[kooshiar @kooshiar]

#ScientificBreakthrough: AI-designed protein targets heart failure mechanism. First demonstration of a new, lab-verified protein designed to target cellular energy depletion in heart failure.
Experimental validation confirms successful synthesis, improved stability, and confirmed ATP binding affinity.

[310copilot @310copilot]

From idea to design, docking, and analysis—run protein models and design new functions with a single English sentence.

For example, here we create 3 caffeine-responsive sequences, dock them, and analyze the results—all in one step.

[310copilot @310copilot]

Instead of spending extra time learning various services and tools, you can find, visualize, and dock molecules on a single platform by entering text prompts in just a few minutes.
See the detailed script at the link below:
https://t.co/ijUiKlGH3x
#pymol #diffdock

[310copilot @310copilot]

Instead of installing software and writing code, you can visualize molecules on 310Copilot directly by entering text prompts.
#ProteinDesign #MolecularVisualization

[310copilot @310copilot]

1. ‘Find 1pxx’
2. ‘Make it green and hide ligands and small molecules.’
Using similar prompts, you can customize visualizations to remove ligands, highlight binding sites, or isolate key structural features for focused analysis.
#ProteinDesign

[310copilot @310copilot]

In this video, you can see how Muhammad Kurniawan, a scientist in this field, is using the 310ai #Text2Protein platform - Copilot - to improve his research outcomes.
#ProteinDesign

[310copilot @310copilot]

With Copilot, you can chat to describe a protein’s function, generate its 3D structure, and find similar structures with their amino acid sequences.
#proteindesign

[310copilot @310copilot]

310ai's Copilot has unified these tools into one platform, and we’ve recently seen remarkable progress and incredible research using them. It’s inspiring to witness how combined knowledge and AI collaboration move us toward a world without disease-related deaths.
#drugdiscovery

[Vega Shah @dr_alphalyrae]

Big day today - @nvidia is open-sourcing the BioNeMo Framework, a toolkit of programming resources, libraries, and AI models designed for drug discovery. This release equips academic labs and biotech companies with advanced tools for protein design, small molecule generation, and even custom model development. Built with GPU optimization in mind, BioNeMo is tailored to speed biochemistry predictive modeling, and we think this is an impactful step ahead in computer-aided drug discovery https://t.co/Y4vMAnrIDI

[Adaptyv Bio @adaptyvbio]

Check out how @310ai__ has experimentally validated their AI-designed proteins in our lab!

[kooshiar @kooshiar]

AI-Generated Proteins Achieve 84% Expression Success in the Lab.

https://t.co/HebMePuWNU

[Kathy Y. Wei, Ph.D. @KathyYWei1]

Molecular docking in 35 seconds ⏲

Try: https://t.co/Q253S7SGzl
Learn: https://t.co/UblNUqn8kj

[kooshiar @kooshiar]

This protein is fully designed by AI

Prompt: "This protein aids in organizing cell projections and regulating cell metabolism and division, particularly through its SH2 domain"

How do we know if it is good? 👇

[310copilot @310copilot]

One platform for designing an infinite variety of proteins.
#Proteinengineer

[310copilot @310copilot]

After designing a protein in your research on Copilot, you can write ‘Send to Lab’ to see the results in the real world.
#ProteinDesign

[310.ai @310ai__]

Seamlessly go from idea to result with 310 Copilot + @adaptyvbio

1️⃣ Describe the protein you want in words.
2️⃣ Use AI to bring your vision to life.
3️⃣ Send to the lab and get results!

Example: https://t.co/KTDZScGREP

[310copilot @310copilot]

In this video, you can see how Muhammad Kurniawan, a scientist in this field, is using the 310ai #Text2Protein platform - Copilot - to improve his research outcomes.
#ProteinDesign

[310copilot @310copilot]

If we used #TMalign, comparing available protein structures would take 10,000 years on a 1,000-core cluster. But now, with #Foldseek, we can find structural similarities in seconds.

[310copilot @310copilot]

5. Finding Protein By its #PDB ID: This way helps you explore detailed 3D structural data essential for structural biology and computational modeling.

[310copilot @310copilot]

🧵You can find a #protein in various ways within seconds by writing a prompt on 310Copilot:

1. Finding Protein by its Structure Similarities: Structural searches offer insights into 3D conformations, interactions, #DrugDesign, and functional predictions.

[310copilot @310copilot]

4. Finding Protein by its #UniProt ID: Using UniProt IDs provides access to precise, curated protein information for reliable scientific analysis.