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clepp

@cl2pp

Leveraging entropy a post at a time. Co-Founder & CPO @bioprotocol

Katılım Ağustos 2018
2.1K Takip Edilen2.3K Takipçiler
Bio Protocol
Bio Protocol@BioProtocol·
Some stakers aren't seeing $PEPTAI rewards. We're identifying affected wallets now. Users who claimed immediately are missing ~20% and we're auditing and distributing manually. No action needed and corrections push directly to wallets. Thank you for your understanding!
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Paul Kohlhaas bio/acc
Paul Kohlhaas bio/acc@paulkhls·
🧵1/9 If you're in peptide design, one static snapshot can make a candidate look like a sure thing. Lock it into the receptor in a frozen model, the scores light up. Let the atoms move for a few nanoseconds, half the time the pose drifts right out. That gap is where most early-stage peptide programs lose money. PeptAI is a built to catch it before any candidate hits synthesis, and accelerate open R&D at agentic velocity
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Bio Protocol
Bio Protocol@BioProtocol·
Say hello to @peptai_, a fleet of autonomous AI agents for peptide drug discovery, now live on @base Each agent targets a single receptor, runs the full nine-gate pipeline 24/7, and pays for its own wet-lab experiments via x402.
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Bio Protocol
Bio Protocol@BioProtocol·
Beach Science started as an experiment in agentic research. In under 8 weeks, 59 AI agents and 55 researchers generated 6,134 hypotheses in public. The experiment worked. And now it's evolving. The generation part works. Most of the 6,134 hypotheses sat without review. A few moved forward, but only because a specific person noticed them and manually pushed them through. A few things still don't exist: → A shared place where humans and agents actually work together. Interest and conviction stay invisible everywhere else. → Small capital that can find small science. The payment rails are in place (x402, @molecule_sci, @bioprotocol). The layer that routes them to specific experiments still has to be built. → A way for the best ideas to actually surface. Right now, strong claims and weak ones look the same in the feed. Beach Science is evolving into the layer where strong claims attract collaborators, build conviction, and reach capital without waiting on someone to push them through. Claim, conviction, and capital collapsed into a single motion. Everything posted on @sciencebeach__ carries forward. More on this soon.
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BioAIDevs
BioAIDevs@BioAIDevs·
Most "literature review" tools search one database and hand you the top 10 options. The Literature Agent inside BIOS synthesizes scientific knowledge through a three-stage pipeline. First, it expands your research question into optimized queries across seven sources in parallel: ArXiv, PubMed, CrossRef, Semantic Scholar, Google Scholar, ClinicalTrials. gov, and UniProt. Next, a two-stage re-ranking process - combining embedding similarity with LLM-based relevance scoring - surfaces the most relevant papers from hundreds of candidates. Two modes support different workflows. > Fast mode returns ranked results with key excerpts in seconds, using only metadata. > Deep mode downloads full-text PDFs, chunks them for semantic search, and produces executive summaries with inline citations and structured evidence tables, typically completing in one to two minutes. The result is a literature review that the agent has actually read.
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PeptAI
PeptAI@peptai_·
Introducing PeptAI: Autonomous Agents for Peptide Drug Discovery x.com/i/broadcasts/1…
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Bio Protocol
Bio Protocol@BioProtocol·
Bio was featured in @Bankless on how AI is rewriting the DeSci equation. @peptai_, our AI agent for peptide drug discovery, designed a novel peptide for ADHD in 24 hours. Wet lab validation of the peptide ran under $1,500. Pharma reaches the same decision point after millions of dollars and years of work. BIOS, our AI scientist, coordinates specialized subagents for literature search and data analysis. Built to accelerate scientific discovery. Drug development has always been gated at the earliest stage by capital, not science. Our goal is a self-sustaining DeSci network where AI agents and communities finance and execute science end to end. Bio sits at the center of this shift. Link to the article in the comments ↓
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DeSci.Berlin
DeSci.Berlin@DeSciBerlin·
Renowned longevity scientist Aubrey de Grey will speak at DeSci Berlin on June 18! @aubreydegrey is the founder of LEV Foundation, focusing on combating aging through molecular and cellular repair. His talk, "AI x Longevity: Can Agents Solve Aging?", will explore whether AI agents can accelerate the path to longevity escape velocity.
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PeptAI
PeptAI@peptai_·
Most drugs start as a guess. A researcher picks a molecule, tests it, waits weeks for results, adjusts, tries again. For every drug that reaches patients, thousands of candidates failed somewhere in that process. Peptides are a class of medicines that can target diseases with high precision. The problem is finding the right one. There are millions of possible candidates. Testing them manually takes months. PeptAI runs that search autonomously. Give it a protein target. It sources candidates, puts each one through quality checks, and surfaces only what passes every test. The ones that make it through go to a real lab. What used to take months runs in the background.
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clepp@cl2pp·
Love seeing sustainable fashion backed by actual science hitting the streets. Huge props to @hempydotscience and @valley_dao for shipping something tangible like this. If you’re into that (or just want a comfy hoodie with real biotech cred), check it out: biofy.xyz/products/hempy…
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clepp@cl2pp·
Really like the design and the cut. It’s comfortable. The only minor thing is that the print on the back could be a bit stronger, but I still like it.
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clepp@cl2pp·
Received and unboxed my @hempydotscience hoodie today. Really excited about finally trying this product coming out of @valley_dao. Hempy promises to turn hemp into premium, breathable, lifelong clothing with their HEMPKNIT™ biotech. Enzyme-softened fibers that give hemp a cotton-like feel while using far less water and land than cotton.
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clepp@cl2pp·
It’s been exciting to see all the different lego pieces coming together over the past month. Agents allow for autonomous iteration on structured processes. Bioinformatics tools become steps in the process. Having crafted the process with quality-control gates, subagents can be tasked with targeting different receptors to come up with high-quality options to test in wet labs. Agents financed and pay for tools with USDC. Data is anchored on-chain via @Molecule_sci labs.
PeptAI@peptai_

Peptide drug discovery now has an autonomous pipeline. A tool takes an input and returns an output. A sequence goes in, a structure comes back. The decision of what to do with it, whether the structure is good enough, what to run next, whether the candidate advances, stays with the researcher. An agent uses tools. It evaluates the output against a defined threshold, decides whether the candidate passes or fails, and triggers the next step without waiting for a human to interpret the result. @peptai_ is built as a fleet of agents. Each agent targets a specific receptor and runs the full 9-gate pipeline: source novel candidates, calibrate the quality gates, run the computational analysis, and hand survivors to wet lab. Today: GLP-1R (35 candidates advancing), KISS1R (2 out of 10 candidates advanced to G9): Every agent runs 9 gates: > G0: Pulls ChEMBL binding data for known agonists and non-binders, sets the per-gate baseline. > G1-G3: AlphaFold and Boltz2. Structure quality, binding poses, contact conservation. > G4-G5: PRODIGY for affinity, LiteFold's MD for stability. > G6-G8: PROSPERousPlus, PlifePred, OpenSol, and ToxinPred3. Proteolytic stability, solubility, aggregation, off-target safety. > G9: Wet lab handoff with @adaptyvbio. The goal is to have synthesis paid machine-to-machine via x402. Only sequences that clear all G1 through G8 earn a synthesis recommendation. G9 is wet lab only and cannot be computationally overridden. Every gate decision is published openly on Molecule Labs. PeptAI is experimental and actively evolving. Gates, tools, and thresholds change as the pipeline learns.

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BioAIDevs
BioAIDevs@BioAIDevs·
Not all research is the same. Here's a quick guide to choosing between Steering, Smart, and Autonomous Deep Research modes on BIOS ↓ > Steering Mode (~20 min / 1 credit): Use it for sensitive experiments, early-stage hypothesis work, or when you want BIOS as a co-pilot. → One iteration at a time → You approve every step → Full control over direction > Smart Mode (~60 min / 5 credits): Best for collaborative deep dives. Use it for literature reviews, competitive analysis, or any research that benefits from iterative refinement with your input. → Up to 5 iterations → Checkpoints after each cycle → You stay in the loop > Autonomous Mode (~8 hours / 20 credits): Best when you want results, not a workflow. Great for large-scale data synthesis, long-horizon research tasks, or when time is the bottleneck. → Up to 20 iterations → Runs until convergence → You review the output, not every step
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Bio Protocol
Bio Protocol@BioProtocol·
Drug-naive ADHD patients show measurably lower orexin-A/B levels. OX2R is the receptor that drives arousal and attention. No approved drug activates it. Every orexin therapy on the market does the opposite. @BioProtocol's scientific team and @peptai_ developed OX2R-004, a selective peptide agonist targeting exactly this gap, and ran it through the full 8-gate computational pipeline over 24 hours on @BioProtocol infrastructure. It cleared most gates: Clean binding geometry, zero immunogenicity signals, toxicity score 0.0. Two known failure points remain but both have standard peptide engineering fixes. First wet-lab validation costs $500. Traditional pharma spends years and tens of millions to reach this same checkpoint. The modality is open, the biology is solid, and the barrier to entry just collapsed.
Paul Kohlhaas bio/acc@paulkhls

🧵 Over 24 hours, our scientific team and AI scientist infrastructure developed a novel peptide agonist to potentially treat ADHD. Below is our paper for a pre-IND computational feasibility assessment for OX2R-004: an 18-residue peptide agonist designed as a selective OX2R agonist for ADHD. Why this matters? No approved orexin agonists exist anywhere. All marketed orexin drugs are dual OX1R/OX2R antagonists for insomnia. Clinical-stage ones are small molecules for narcolepsy only. We did this with @peptai_ a novel full 8-gate computational pipeline in one shot developed by @BioProtocol community 👇

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Keşfet

@peptai_ @Tcalledpresence @BioProtocol @base @molecule_sci @bioprotocol @sciencebeach__ @Bankless