Top Tweets for #INSILICO
@InSilicoMeds launches a real-world benchmark designed to reveal whether AI can truly discover new medicines – not just ace exams.
https://t.co/WdUqqWhKQj
#longevity #ai #drugdiscovery #insilico #biotech
Insilico Medicine’s VAC platform makes biological age a core variable as it attempts to model cellular change across six biological scales.
https://t.co/aW1pu2HZCF
#longevity #geroscience #insilico #biologicalage #cellularreprogramming
InSilico setzt auf das nächste Milliardenversprechen: Mit KI, Langlebigkeitsmedizin und Mega-Partnerschaften will der Pharmaspezialist die Branche verändern
#InSilico #KI #Biotech #Langlebigkeit #Pharma #EliLilly #Medizin #Aktienmarkt
https://t.co/wgSt7Bc5tb
💥Excited for the publication: "Toward Integrative Biomechanical Models of Osteochondral Tissues: A Multilayered Perspective"
🔗https://t.co/piwJrVObSO
📌 #OsteochondralTissue #Biomechanics #RegenerativeMedicine #CartilageRepair #BiomedicalEngineering #InSilico #JointHealth
🚨 Exciting news! We're editing a Topic in @FrontiersIn Drug Discovery:
📌 "Consensus #InSilico Approaches for Drug Discovery & Bioactive Chemical Space Exploration"
We warmly invite you to submit your work! 🔬💊
🔗https://t.co/GUkzMBPYI0
#DrugDiscovery #Cheminformatics
Insilico is considering a secondary listing in Abu Dhabi in a deal that would make it the first company from outside the Gulf to list shares on a regional exchange https://t.co/o1jWVIMXat
PCだけでできるインシリコ創薬論文紹介２
Network pharmacologyで化合物の疾患の標的候補を絞る創薬研究
📷https://t.co/oyCTnII1Yr
📷https://t.co/LYk0SvQRUk
📷https://t.co/ssBhx3NmGn
#InSilico #創薬 #分子ドッキング #Bioinformatics
Don't miss out https://t.co/FHBdKBN1Co #insilico
⏰ Happening tomorrow in Cambridge at Takeda: How AI is transforming the discovery landscape.
There are only 24 hours left until we kick off the PBSS symposium on "Artificial Intelligence and Machine Learning Shaping the Future of Therapeutic Drug Discovery".
Please join Petrina Kamya, Ph.D. VP and Global Head of AI Platforms at Insilico Medicine, with a symposium focused on Therapeutic #DrugDiscovery, and a featured presentation as well.
See the full agenda and registration details here: https://t.co/lacO5863SW
#InsilicoMedicine #PBSS #BostonBiotech
Eli Lilly, a Big Pharma, just made a $2.75 BILLION bet on #AI. 🤖
Eli Lilly is officially teaming up with #Insilico, and honestly, they are way ahead of the curve.
Their official take? AI it’s actually generating viable targets and pushing molecules straight into the R&D pipeline, massively slashing early discovery time.
Can't wait to see what comes out of this!
#Insilico Medicine and ASKA Pharmaceutical Expand Partnership to Discover Novel Targets for Women's Health https://t.co/iLoaouicQ9
Extreme #geneticvariations in #propofol clearance could be easily compensated for in this #insilico analysis of #TCImodels
https://t.co/fjIouSYmdq
Foreword for #insilico #Modeling #book by #DarshnaJoshi @BenthamScienceP https://t.co/wsBDHQHz3D @Jaipur_Manipal
MolNFT on GenesisL1: The On-Chain Molecular Data Revolution in DeSci
🧬🧬🧬🧬🧬🧬🧬
dApp: https://t.co/vblYBEveN1
#MolNFT #GenesisL1 #Layer1 #DeSci #OpenScience #Bioinformatics #Biology #Medicine #Blockchain #InSilico #NFT
🧬🧬🧬🧬🧬🧬🧬
MolNFT is introducing a breakthrough approach to managing molecular data on the blockchain, catapulting decentralized science (DeSci) into a new era. Built on the EVM-compatible GenesisL1 Layer-1 blockchain, MolNFT transforms how we store, share, and utilize biomolecular information. It has achieved a landmark feat: uploading the entire Protein Data Bank (PDB) dataset — over 229,000 molecular structures and ~1 million sequences — fully on-chain (about 50 GB of data). This makes MolNFT the largest on-chain data repository ever deployed, enabling search, retrieval, and even real-time 3D visualization of molecular NFTs using decentralized infrastructure. The implications for bioinformatics, biomedical research, and in silico studies are profound, as MolNFT merges cutting-edge blockchain technology with the needs of open science.
Decentralizing Molecular Databases on GenesisL1
MolNFT (Molecular NFT) is essentially a decentralized storage system for molecular data, implemented as a collection of NFT smart contracts on the GenesisL1 blockchain. GenesisL1 is a novel Layer-1 blockchain (built with Cosmos SDK and Ethermint for EVM compatibility) tailored for scientific and data-intensive applications. Unlike typical NFTs that might point to off-chain files, MolNFT actually stores data directly on-chain. In fact, the entire RCSB Protein Data Bank — a central repository of 3D biomolecular structures — has been “NFT-ized” and written into GenesisL1’s ledger. Every protein or nucleic acid structure from the PDB is represented as an ERC-721 token, with all its metadata and even coordinate data immutably recorded on the blockchain.
This design ensures the data is immutable (once uploaded, it cannot be altered or deleted unnoticed) and censorship-resistant (no single entity can block access to it), key principles for decentralized science. Researchers and enthusiasts worldwide can query the blockchain to obtain a molecule’s data, confident that it is authentic and will persist as long as the network exists. By decentralizing vital scientific repositories in this way, MolNFT and GenesisL1 are laying the groundwork for open collaboration and knowledge sharing that transcends traditional gatekeepers.
A 50 GB Smart Contract
The Protein Data Bank is a cornerstone of structural biology, containing decades of experimentally determined biomolecular structures.
MolNFT’s crowning achievement is getting this entire trove on-chain. Approximately 229,000 PDB structures (plus about one million sequences) have been written into GenesisL1’s state, for a total of about 50 gigabytes of data — widely regarded as the largest smart contract data deployments ever.
Each PDB entry — whether it’s a protein or a DNA fragment structure — has been minted as a Molecular NFT. Crucially, the data for each NFT lives in the blockchain state replicated by GenesisL1 nodes worldwide, removing reliance on any external file server or IPFS link. Despite the massive data volume, MolNFT’s design enables surprisingly fast retrieval. Searching for a structure by its ID or keyword can be nearly as quick as traditional web-based services, thanks to efficient compression and the blockchain’s inherent data replication.
Smart Contracts and Novel NFT Architecture
MolNFT leverages a sophisticated smart contract architecture to manage this vast trove of data. At its core are extended ERC-721 smart contracts (the standard for NFTs) that handle large payloads. A single NFT token in MolNFT represents a distinct molecular entry (e.g., a specific PDB structure). Because blockchain storage has practical size limits, MolNFT employs a hierarchical parent–child NFT structure:
Parent NFT: Represents a full entry, e.g. a primary PDB record.
Child NFTs: Store data fragments (such as chunks of the BCIF structure file).
The contract provides functions like getCombinedData to reconstruct the entire molecule from child tokens. Metadata (e.g., title, authors, resolution) and binary data (3D coordinates, sequences) are all stored immutably in the chain’s state. From a user’s perspective, retrieving the data for an on-chain molecule no longer depends on off-chain URLs or IPFS gateways.
GLAST: Web3 Bioinformatics in Action
Hosting large datasets on-chain is only half the challenge; effective search and analysis are equally crucial. Enter GLAST, the Global Local Alignment Search Tool of GenesisL1, which provides local sequence alignment akin to BLAST, but for any type of data including recorded on chain metadata.
GLAST uses Whoosh for indexing metadata and Parasail for local alignment.
It exposes REST endpoints for text-based queries (e.g., searching titles, sources, or authors) and sequence alignment across millions of on-chain entries.
This hybrid model combines on-chain data storage (MolNFT) with off-chain indexing (Whoosh) and alignment (Parasail), allowing rapid queries without sacrificing decentralization.
Researchers can thus perform sequence similarity searches against the entire MolNFT database, referencing the exact immutable dataset on GenesisL1. This bridges the gap between decentralized data hosting and real bioinformatics utility.
Significance for Decentralized Science
MolNFT and GenesisL1 represent more than just a novel NFT application; they address real needs for DeSci and scientific data management:
Open Access and Collaboration: Anyone can query the same on-chain dataset, removing barriers like institutional logins or paywalls.
Immutability and Integrity: Once published, data cannot be covertly changed or deleted. This fosters reproducibility in biomedical research.
Decentralized Preservation: The ledger is globally replicated, guarding valuable datasets from single points of failure or censorship.
Comparable Performance: Proper compression and partial indexing enable retrieval speeds on par with centralized solutions, but without the single-server bottleneck.
These qualities open up new forms of in silico research, enabling scientists to reference exact data with zero trust in any central authority.
Visionary Use Cases
Beyond publicly open data, MolNFT also supports encrypted on-chain storage for IP NFT use cases:
Institutions or biotech firms can store confidential or pre-patent structures in encrypted form.
At the right time (e.g., after a patent filing), owners can unlock or sell the decryption key.
This fosters a new model of licensing and monetizing molecular data, bridging on-chain immutability with controlled data disclosure.
Scientists can host proprietary or encrypted IP NFTs for unpublished data, enabling them to reveal or sell access at the opportune moment, e.g. for patent purposes, collaborative deals, or open-sourcing an invention.
Conclusion
MolNFT’s on-chain molecular data repository is a bold illustration of how blockchain can transcend typical cryptocurrency use cases and directly serve scientific progress. Storing the entire Protein Data Bank (and more) on the EVM-compatible GenesisL1 blockchain, combined with advanced search/analysis tools like GLAST, heralds a new frontier where bioinformatics NFTs underpin truly decentralized science.
By allowing DeSci researchers, institutions, and blockchain enthusiasts to store, search, and potentially monetize large-scale molecular data entirely on-chain, MolNFT unlocks:
Sustainable Access: Free from reliance on central servers.
Robust Data Integrity: Guaranteed by the blockchain’s immutable ledger.
Licensing and IP Potential: Through encrypted or unlockable IP NFTs.
Ultimately, MolNFT exemplifies how layer1 blockchains and smart contracts can revolutionize not just finances or collectibles, but the very heart of biomedical research, bioinformatics, and in silico studies. By merging the unstoppable resilience of a public blockchain with the creativity of open science, MolNFT paves the way for a future where global collaboration and innovation are limited only by our imagination.
dApp: https://t.co/vblYBEveN1
🔊 Breaking News: Insilico Medicine and Zhejiang Hisun Pharmaceutical Co Ltd Nominate a Preclinical Candidate Just 8 Months After Forming a Strategic Collaboration
Read more about the exciting milestone below!
#Insilico #Hisun #AI #AIDrugDiscovery #DrugDiscovery
https://t.co/YihwCBbfpt
InSilico Medicine made its debut on the Hong Kong Stock Exchange. The announcement showed that the share price was HK$24.05, with a total of 94.6905 million shares issued, in board lots of 500 shares, raising net proceeds of approximately HK$2.026 billion.
This is the highest-funded Hong Kong-listed biotech IPO this year. #IPO #HKSE https://t.co/jtLQ7akOu7
🧪🍄 #Antidote lead vs deadliest #mushroom
Nat Commun ’23: ICG (approved med dye) found via #InSilico drug scr. to blunt α-amanitin tox. from #DeathCap.
Validated in human cells, liver organoids & mice; early dosing key.
#Toxicology #MushroomPoisoning #AmanitaPhalloides
Thanks a lot @MDAndersonNews Public Relations for highlighting our work “#InSilico #DigitalTwins of #BoneMetastasis Enable Investigation of Tumor Progression and Therapy Response”, published in @CR_AACR , in the #ResearchHighlights!
https://t.co/ZQ7gwHNpk2
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