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cryptoceo

@cryptoceo_

Labor omnia vincit Finding bangers, never financial advise - informational tg @thecryptoceo alpha @chiefexecclub

Katılım Şubat 2021
674 Takip Edilen3.1K Takipçiler
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cryptoceo
cryptoceo@cryptoceo_·
Put simply, people like new narratives, and peptides is the hottest narrative in the world right now thanks to glucagon-like peptide-1 receptor agonists [GLP-1s]. GLP1s have effectively de-risked the entire category, and JFK Jr loosening the regs this summer will go some way to further de-risk. Alongside this, AI is rapidly increasing peptide development. One project using agents right now for peptide discovery + actual connections to wetlabs [step prior to clinical trials] is $FOLD, a recent BIO Hackathon winner. What most people miss is that peptides already have demand, it just isn’t structured. Biohackers, clinics and longevity communities are actively experimenting in real time, but outcomes are fragmented, anecdotal and mostly lost. There’s no system capturing what works, feeding it back into discovery and improving over time. Demand for this exists but data is limited. This is the gap that @clarity_proto fill. Traditional biotech doesn’t really solve this either. It’s slow, capital intensive and optimised for billion dollar drugs, whereas peptides often sit in an awkward middle ground, too early, too niche or not patentable enough to attract serious funding. As a result, a lot of potential discovery simply never compounds because no one is capturing the learnings in a continuous loop. Clarity is going after that gap, starting with neurologics. Focusing on neurodegenerative diseases like dementia gives them a high signal entry point, where protein misfolding and peptide interaction are well understood and measurable. Neurologics is just the starting point, this same system will soon be applied to all and any peptides from longevity, performance, metabolic health and beyond. Clarity will be the infra for a much broader peptide discovery system. The model is simple: 1. AI discovers peptides 2. Best candidates get surfaced -> wetlabs/trials 3. Products get distributed for real-world use 4. Usage generates data 5. Data feeds back into the model Basically, how you go from "biohacking products" to a compounding discovery engine through the fusion of GPUs x AI agents x protein folding x wetlabs.
cryptoceo@cryptoceo_

Peptides is the narrative of 2026 Significant capital already sits in bio protocol, but a 24/7 automated peptide pipeline exists at ~300k fdv > agents running 24/7 > peptides designed + scored > real outputs already live > product layer + distribution planned > provisional ip protections underway > recent hackathon winner Tldr: a live, ai-driven peptide research platform Or simply: github for peptides Hard to see this staying here if it executes

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cryptoceo retweetledi
BassMan
BassMan@BassManTV·
people overcomplicate the $NOCK vision. it’s really just this. all at once.
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Bitman
Bitman@BitmanTW·
Collected a list of DeSci × Biotech gems under 100k mcap Will share it soon
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Blockinator
Blockinator@theblockinator·
DeSci is one of the few areas trying something different funding research, coordinating scientists, owning data messy and not obvious but that’s usually how new things start
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cryptoceo
cryptoceo@cryptoceo_·
@watchingmarkets $FOLD >won Bio Protocol’s hackathon >24/7 automated peptide pipeline >real connections to wetlabs >up ftw @ pumpfun hackathon >Eli Lilly’s pumped 300M into VitaDAO small cap, same could happen here for Bio’s small cap >1M market cap Peptide summer x.com/clarity_proto/…
Clarity Protocol@clarity_proto

Major update to Clarity Protocol We just shipped a full computational peptide discovery pipeline. Here's what that means: 1/ Clarity now has 6 autonomous AI agents running 24/7. The newest one mines bioactivity databases for known protein binders, designs novel candidate peptides targeting aggregation-prone regions, and scores them through multi-property drug-likeness filters. 2/ Every candidate peptide gets structural binding prediction; a computational measure of how strongly it binds the target protein. First batch scored in the "strong binding" range. These are computational predictions, not experimental results, but they tell us which candidates are worth testing in a real lab. 3/ The complex prediction daemon now processes protein-protein interaction jobs end-to-end. Queue a complex → structure prediction runs → results pushed to production. Currently predicting interaction structures relevant to Alzheimer's. 4/ 50+ folds across 13 proteins. Hundreds of candidate peptides designed and scored. Each one goes through bioactivity validation, structural analysis, and multi-gate screening. All visible on clarityprotocol.io. Some may still be processing. The next milestone is experimental validation; synthesizing top candidates and running real binding assays. The computational pipeline prioritizes what's worth testing. *A note on IP: All candidate peptide sequences on clarityprotocol.io are now redacted behind coded identifiers (CP-TAU-001, CP-SOD1-002, etc.). We show binding strength tiers, drug-likeness assessments, and target regions, but not the actual sequences. Raw data is stored locally and protected. If you're a researcher or wetlab interested in collaboration, reach out directly. We take IP seriously while keeping the platform open. *Filing for provisional patent *Architecture graph generalized to protect our methods

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Market Watcher
Market Watcher@watchingmarkets·
When a narrative is not yet well understood and lacks clear large cap leaders for benchmarking, fomo and speculation take over. Capital turns more aggressive while uncertainty around ceilings and valuation frameworks makes pricing these assets inefficient. That’s how the AI meta started before producing billion dollar runners. Same conditions could easily repeat here. DeSci x Biotech x Peptides
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crypto - popseye (papovic) 🛸 🏠 🍄
I'm 50/50 on the whole peptide narrative bcos I feel its a bit more similar to robotics where web3 makes no sense except as a gambling avenue unlike AI agents. That being said its taken the world by storm and there's not many projects out there other than $BIO but theres quite some emissions with this and its a weird chart (big pumps then a huge dump which you can probably infer whats going on) and still can't move too much despite a lot of shills But at least its something interesting of a narrative so will observe
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cryptoceo
cryptoceo@cryptoceo_·
@cryptoskullx I see Crossbridge DAO (VitaDAO project) just got a $300M investment from Eli Lilly, IMHO @clarity_proto could be the Crossbridge DAO of Bio Protocol. DMs always open if you want to discuss further solana:2TfSKMphshQ8zFLMJuGsw2iotSdGHLhYYPM4uy1opump x.com/clarity_proto/…
cryptoceo tweet media
Clarity Protocol@clarity_proto

Major update to Clarity Protocol We just shipped a full computational peptide discovery pipeline. Here's what that means: 1/ Clarity now has 6 autonomous AI agents running 24/7. The newest one mines bioactivity databases for known protein binders, designs novel candidate peptides targeting aggregation-prone regions, and scores them through multi-property drug-likeness filters. 2/ Every candidate peptide gets structural binding prediction; a computational measure of how strongly it binds the target protein. First batch scored in the "strong binding" range. These are computational predictions, not experimental results, but they tell us which candidates are worth testing in a real lab. 3/ The complex prediction daemon now processes protein-protein interaction jobs end-to-end. Queue a complex → structure prediction runs → results pushed to production. Currently predicting interaction structures relevant to Alzheimer's. 4/ 50+ folds across 13 proteins. Hundreds of candidate peptides designed and scored. Each one goes through bioactivity validation, structural analysis, and multi-gate screening. All visible on clarityprotocol.io. Some may still be processing. The next milestone is experimental validation; synthesizing top candidates and running real binding assays. The computational pipeline prioritizes what's worth testing. *A note on IP: All candidate peptide sequences on clarityprotocol.io are now redacted behind coded identifiers (CP-TAU-001, CP-SOD1-002, etc.). We show binding strength tiers, drug-likeness assessments, and target regions, but not the actual sequences. Raw data is stored locally and protected. If you're a researcher or wetlab interested in collaboration, reach out directly. We take IP seriously while keeping the platform open. *Filing for provisional patent *Architecture graph generalized to protect our methods

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CryptoSkull 💀 ze last bull standing
All I know is these cheap altcoin opportunities won’t stay like this for long. I’ve seen 3 bears and multiple sideways and downtrend phases like this. They all resolved into new ATHs. You’re in a market where -50% drawdowns are part of the game. Bitcoin is down -50% and we’re still here. Manipulated or not, doesn’t matter. It’s about playing the game long-term. Always has been. If you don’t have the cojones to buy and hold with conviction go flip Pokémon cards for $30 profits. Crypto isn’t for the fainthearted. Never was. The real ones are still here. And we’re going to win together. Spirit is high. Portfolios will follow. Much love to all the homies still ballin 🫡
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cryptoceo
cryptoceo@cryptoceo_·
@Whale_AI_net @clarity_proto Expanding into all verticals long term too: longevity, performance, etc. The work-loop $fold are using can be applied to any peptide
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WhaleAI 🐳
WhaleAI 🐳@Whale_AI_net·
🧬 $FOLD — @clarity_proto A DeSci project running an autonomous protein folding pipeline for Alzheimer's, Parkinson's, ALS, and FTD research. The system uses AlphaFold to continuously predict 3D structures of newly discovered protein variants, compare them against wild-type proteins, identify destabilized regions, and generate AI-powered research summaries — all without human intervention. Everything is published publicly as it's produced. 55M people live with dementia today. 0 cures exist. The global cost is $1.3T/year and rising. The founder built this after watching family members develop dementia and realizing that idle home computers could be put to work on the problem. The goal: make distributed protein folding research more accessible and automated so more people contribute.
WhaleAI 🐳 tweet mediaWhaleAI 🐳 tweet media
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cryptoceo
cryptoceo@cryptoceo_·
@zendiu1 Thank you bud Not gonna swerve the BIO hackathon winner at 1M $FOLD
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cryptoceo
cryptoceo@cryptoceo_·
Put simply, people like new narratives, and peptides is the hottest narrative in the world right now thanks to glucagon-like peptide-1 receptor agonists [GLP-1s]. GLP1s have effectively de-risked the entire category, and JFK Jr loosening the regs this summer will go some way to further de-risk. Alongside this, AI is rapidly increasing peptide development. One project using agents right now for peptide discovery + actual connections to wetlabs [step prior to clinical trials] is $FOLD, a recent BIO Hackathon winner. What most people miss is that peptides already have demand, it just isn’t structured. Biohackers, clinics and longevity communities are actively experimenting in real time, but outcomes are fragmented, anecdotal and mostly lost. There’s no system capturing what works, feeding it back into discovery and improving over time. Demand for this exists but data is limited. This is the gap that @clarity_proto fill. Traditional biotech doesn’t really solve this either. It’s slow, capital intensive and optimised for billion dollar drugs, whereas peptides often sit in an awkward middle ground, too early, too niche or not patentable enough to attract serious funding. As a result, a lot of potential discovery simply never compounds because no one is capturing the learnings in a continuous loop. Clarity is going after that gap, starting with neurologics. Focusing on neurodegenerative diseases like dementia gives them a high signal entry point, where protein misfolding and peptide interaction are well understood and measurable. Neurologics is just the starting point, this same system will soon be applied to all and any peptides from longevity, performance, metabolic health and beyond. Clarity will be the infra for a much broader peptide discovery system. The model is simple: 1. AI discovers peptides 2. Best candidates get surfaced -> wetlabs/trials 3. Products get distributed for real-world use 4. Usage generates data 5. Data feeds back into the model Basically, how you go from "biohacking products" to a compounding discovery engine through the fusion of GPUs x AI agents x protein folding x wetlabs.
cryptoceo@cryptoceo_

Peptides is the narrative of 2026 Significant capital already sits in bio protocol, but a 24/7 automated peptide pipeline exists at ~300k fdv > agents running 24/7 > peptides designed + scored > real outputs already live > product layer + distribution planned > provisional ip protections underway > recent hackathon winner Tldr: a live, ai-driven peptide research platform Or simply: github for peptides Hard to see this staying here if it executes

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Captain ☄️
Captain ☄️@CaptainNFA·
$SCAM Altman is sending 🥱 Just tapped $9M as Elon Musk’s case against OpenAI kicks off The Elon meta is going crazy again Might be time to lock back in… the trenches are starting to heal 👀
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