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Input a protein sequence + the residue positions to target → potent motif-specific binders in seconds! 🪄 Introducing our newest version of moPPIt! Experimentally validated for domain- and IDR-specific binding, as well as receptor inhibition and CAR-T cell design! 🧫 📜: 🤗: 🧵👇

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The history of Fibonacci's clock is quite intriguing, as it combines the fascinating world of mathematics with the practical application of timekeeping. The clock is named after Leonardo Fibonacci, also known as Leonardo of Pisa, an Italian mathematician from the Middle Ages. Fibonacci is most famous for introducing the Hindu-Arabic numeral system to the Western world and for his work in the Fibonacci sequence. However, the Fibonacci clock we know today is not a direct creation of Leonardo Fibonacci. The modern Fibonacci clock is a tribute to his mathematical genius and the beauty of the Fibonacci sequence. The clock's design is based on the sequence, with each number represented by a specific color or pattern. The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding ones, starting with 0 and 1. The sequence goes as follows: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, and so on. The sequence appears in many natural phenomena, such as the arrangement of leaves on a stem, the spiral patterns of a pinecone, and the growth of a nautilus shell. The Fibonacci clock is a unique timepiece that displays the time using the Fibonacci sequence. The clock face is divided into sections that correspond to the numbers in the sequence. The time is shown by illuminating specific sections of the clock face, with each section representing a different unit of time. For example, one section might represent hours, another minutes, and another seconds.

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Today, we expand zero-shot drug design beyond binding to the design of multifunctional medicines, the intracellular proteome, and state-of-the-art atomic precision with our model, JAM-2. In a new report (below), we show: 1. The first drug-grade, fully computationally designed multispecific antibodies against five peptide-MHCs: Routine picomolar T-cell activation/cell-killing EC50s, >100-fold selectivity, and drug-like developability 2. The first fully generatively designed, drug-grade dual-variant KRAS G12 multispecifics: They recruit primary T-cells from human donors to kill G12V and G12C presenting cells at pM to single-digit-nM potency, completely sparing wild-type. 3. Atomic accuracy, from sequence alone: Angstrom-level agreement between Cryo-EM and JAM-2 de novo designs, requiring only target sequences (not structure) as input. 4. Unrivaled speed with an AI-native in-house wet lab: Designed, built, and tested five programs in one parallelized campaign, end-to-end in-house in ~6 weeks. 5. A higher validation bar for AI-generated drug candidates: In a field increasingly rife with hype and uneven standards of proof, we provide the highest quality public wet-lab validation of AI-designed antibodies to date. We share experimental methods in full, and invite folks to adopt and build on these standards. Truly individualized therapies will be the most important contribution of AI in drug design. These advances help accelerate this future.

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