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cbirt · 2 months
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The synergy among the Nuffield Department of Medicine and the Department of Statistics at the University of Oxford represents a blend of medical expertise with statistical rigor – “The MolSnapper,” built using deep learning, promptly exploring intricate molecular specificity for proteins in 3D conformations. Unlike previous approaches that rely on costly trial and error, Conditioning Diffusion uses deep learning to navigate the maze of molecular interactions with unprecedented efficiency to provide novel medical research solutions.
Their research bridges the gap by making it less complicated to evolve patterns learned from large molecular datasets for pocket-binding applications. MolSnapper employs a controlled and environmentally friendly producing approach to seamlessly combine 3-D structural insights with expert knowledge, revolutionizing the ligand era in pharmaceutical applications. MolSnapper enables researchers to generate molecules from large datasets by providing personalized instruction and enhanced selection. This differs from conventional structure-based drug design approaches, which are stereotypically proficient on restricted protein molecular data.
Precision is imperative in drug design and discovery. Therefore, MolSnapper authenticates this concept by serving to deliver personalized descriptions specific to the investigator’s requirements. With the potential for drug discovery employing deep learning, the path has been opened for personalized medicine intensive on molecular markers unique to particular diseases.
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Beyond the Microscope: Cryo-EM’s Impact on Accelerating Drug Discovery.
A collaboration between the U.S. National Committees on: Crystallography, Chemistry, CODATA & the Board on Chemical Sciences and Technology.
As part of Advancing Drug Discovery: A Webinar Series of the National Academies of Sciences, Engineering and Medicine, a session on Beyond the Microscope: Cryo-EM’s Impact on Accelerating Drug Discovery will be held on Thursday, November 16th, 2023 at noon (EDT). The 60-minute session will consist a presentation from Sandra Gabelli, Head of Structural biology at Merck & co and formally Executive Director of Protein and Structural Chemistry.
Over the past decade, single particle cryo electron microscopy (cryoEM) has transitioned from a niche technique to a powerful tool for structural biology. This is due, in part, to technological breakthroughs which have made it relatively routine to achieve near molecule formulations for protein targets of pharmacological interest in complex with drug candidates. The pharmaceutical industry has historically relied heavily on X-ray crystallography to enable structure-based drug design (SBDD); however, today cryoEM is playing an ever-increasing role in that process, especially for challenging samples like large multimeric complexes, proteins that are flexible, or proteins that are difficult to express or purify. Dr. Gabelli will describe the strategy and present examples were cryoEM has impacted the pipeline at Merck by enabling biology, guiding SBDD, driving protein engineering of biologics and impacting small molecule formulations with micro ED. Dr. Gabelli will also explore the potential offered by upcoming technological advancements of the technique.Register
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naturalrights-retard · 3 months
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Pfizer knew that no one would agree to being injected with electronic nanotechnology devices, so they lied to us. Pfizer's document states that their COVID-19 mRNA 'vaccines' contain graphene oxide.
KAREN KINGSTON FEB 29, 2024 February 29, 2024: It’s miraculous to see that other influencers are beginning to cover the the use graphene oxide nanoparticles (GNP) and hydrogel not only in the mRNA injections, but also as their use in nearly all industries from cosmetics and industrial filtration systems to multi-species hydrogel meats and vegetables.
Dr. Ana Mihalcea and I did a deep dive on the use of hydrogel, quantum dots, and graphene oxide nanoparticles earlier this year.
Stew Peters and I broke the story of Pfizer’s internal SBDD (structural and biological drug design) document from Gratin, CT, showing the use of graphene-oxide and gold in the creation and manufacturing of the SP-2 spike protein in March of last year. Article below.
March 11, 2023: To say that I was shocked to find this CONFIDENTIAL lab document was released from Pfizer’s Groton Connecticut Discovery Sciences Research and Development lab is the understatement of my 25 year+ career.
I’ve been told experts won’t believe there is nanotechnology or graphene oxide in the mRNA injections because there is no concrete evidence from Pfizer proving graphene oxide is in the shots. Well, now there is.
This internal document is evidence that Pfizer’s mRNA ‘vaccines’ are programmable electronic nanotech devices that are made with graphene oxide.
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nyaaaaaw · 7 years
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SBS Same Bed Different Dreams 2 - “You are my Destiny” Ep airs today 11/20 at 11:10PM KST Zico is a special MC for this episode
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mocimori · 3 years
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mala strawberry 🍓
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subbydingdan · 7 years
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P-there is a button
D-Is the button white?
P-No it is blue
D-Is the button yellow?
P-It is BLUE
D-Is the button red?
P-IT IS BLUE
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rurifangirl · 3 years
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Check up ask for when you wake up love! <3
Go and eat something (preferably actual food and not chocolates or sweets or something), drink some water and also give your wrists a break from drawing occasionally (you can't create masterpieces of your wrists hurt 🙄✋)
I love you /p, you're wonderful, you deserve nice things and anyone who says otherwise can choke on a sock <3
Take care of yourself and have a great day my favourite non existent Italian monsterfucker 💜
BAHSJKSKAJDHDJDJDNSPPOOOOPPPP😭😭😭😭
YA CNAT JUSTS SBDD
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AIGHT AIGHT IAHDN
I did eat a snack n drank some peach juice, so I did eat today🤩
I also love ya (/p) and I wish ya also took care of yo self, or else who's gonna simp over Kicho w chaotic or givin em bald Habiba pics?🙄
You're also a wonderful moot and i can't just get over w how sweet n just, overall beautiful ya are
Take also care, my dearest yandere fucker🤍
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kokorochans · 4 years
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Ben here. Can you please give us our username back? My girlfriend is only dating me because of my cute kidcore username and I'm scared of being a cuck. Please respond.
DIDNDNFNFDMSLAKA SNDNFDNZKms sbdd. StOOP
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From all of us to all of you, we wish you a very happy #thanksgiving! We will be closed for business 11/23/17 and re-open with normal hours 11/24/17! #sbdd #shredicated #papershredding #holidays #thankfulthursday #grateful #blessed🙏 #family #business #socal #california #orangecountyca #southbay #southbayla #losangeles #clean #environmentallyfriendly #privacy #identity #identitytheft #protection #security #cybersecurity #equifax #money #igaddict #lajolla #sandiego #venturacounty #instalove #instadaily (at South Bay Document Destruction)
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cbirt · 1 month
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Centuries of scientific invention have been driven by the search for new drugs to fight against diseases. Since medicinal plants became valuable sources of medicine from synthetic chemistry, we have consistently improved our capacity to design molecules with therapeutic potential. However, the traditional drug discovery process is time-consuming, costly, and fraught with challenges. It is here that ETH Zurich Chemists develop DRAGONFLY (Drug-target interActome-based GeneratiON oF noveL biologicallY active molecules), a novel de novo drug design method, promising to make the creation of new therapeutics easier.
The conventional drug discovery pipeline is a slow process involving target identification, hit discovery, lead optimization, and pre-clinical and clinical development. It has produced numerous drugs that have saved millions of lives, but there are limitations.
Sequential Nature: The conventional drug discovery pipeline is a slow process involving target identification, hit discovery, lead optimization, and pre-clinical and clinical development. It has produced numerous drugs that have saved millions of lives, but there are limitations.
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cdxx-frog · 6 years
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SBDD
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nyaaaaaw · 7 years
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SBS Same Bed Different Dreams 2 - You are my Destiny - ZICO Self Cam 
*the ep will air on 171120 11:10pm KST
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subbydingdan · 7 years
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Thank you to all who served! #sbdd #shredicated #papershredding #veteransday #veteransday2017 #patriotic #friday #grateful #la #oc #sandiego #lajolla #igdaily #gardena #torrance #southbay #southbayla #instagood #instamood #igaddict #datadeatruction #identityprotection #databreach #instalove #iphoneonly #thankful #honor #supportourtroops #veterans #honorvets (at South Bay Document Destruction)
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cbirt · 1 year
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Artificial intelligence (AI) has significantly changed the scientific research landscape in recent years, yet structure-based drug development has not been significantly affected. However, a promising development comes from German scientists in the form of the MISATO dataset, a curated collection of protein-ligand complexes, molecular dynamics traces, and electronic properties. This article explores the significance of MISATO and how it can pave the way for powerful AI-based drug discovery tools.
AI predictions, exemplified by AlphaFold 2, have transformed various scientific fields. AlphaFold’s accurate protein structure predictions have brought it close to state-of-the-art experimental data. However, despite these achievements, the field of structure-based drug discovery still faces challenges. Developing new drugs using structural methods is complex, and current approaches suffer from low precision and computational limitations.
To train AI models for structure-based drug discovery, highly curated and precise biomolecule-ligand interaction datasets are crucial. MISATO fills this gap by providing nearly 20,000 experimental structures of protein-ligand complexes, along with molecular dynamics traces and electronic properties. The dataset is carefully refined using semi-empirical quantum mechanics and explicit water simulations, ensuring accuracy and reliability.
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stella01wilson · 4 years
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