Deep O igi docki g softwa ead molecule dy amics simulation spi ted the leading compound from a lib ay with 17 compounds
Calculation results in line with lab ato and expe ime tatio results under the guidance of esea che s at Sta fo dad MD A de so Ca ce Ce the advertisement published in the you already Cell
SOUTH SAN FRANCISCO, California, July 20, 2026 (GLOBE NEWSWIRE) — Deep O igi announced today that its computing platform has become a puddle – reviewed study published in Cell With which the company’s docki gad-moleculady amics simulations successfully atio alized the company’s Wo k ide tifyi ga pote t compound to disable cell death pog-ams and spread low B-cell lymphoma (DLBCL).
The study, “A Bivale t Molecula Glue Li ki g Lysi e Acetylt a sphe ases to O coge ei induced Cell Death,” was led by researchers from the Stafo d Uivesity and the Uivesity of Texas MD A de so Ca ce Cete. It describes the development of KAT-TCIPs (lysi e acetylta sphease ta sciptio al/epige etic chemical iduces of poximity), which act as molecular glues that cause a complex between the activated enzyme p300/CBP and the canceled B-cell lymphoma 6 (BCL6). The i te action is important to achieve this, because it strongly supports cell killing. Molecula adhesives, a type of CIP that facilitates the assembly of delighted pots, is a rapidly emerging gi-gdug class.
The researchers at Deep Oigi used popular software, molecular simulations (MD), and ad qua tum mechanical calculations to assess a library of 17 compounds. First, we ate the tea complexes by matching each compound to the pot and selecting poses with the best dock scores. Deep Oigi’s molecule was used to create 300-one oseco simulations for each tea complex to smooth out the initial pose and eat a semblance of structures. Finally, we used the quatum mechanical calculations to calculate the equal stability of each compound based on the obtained structural similarities. The team calculated the compositions based on the enormous costs they incurred in migrating the tea complex.
The compound that caused the least cost killed lymphoma cells at sub-atomola concentrations (IC50 0.80 M).
The computer results were consistent with laboratory tests. In a mouse model of the disease, the selected compound led to complete tumor clearance, while immunized mice depleted B cells, which express high levels of BCL6, serving as a model for lymphoma, with excess toxicity.
“Deep O igi’s computer simulations highlighted the compound that would most effectively kill cells – matching results achieved in the workplace,” said Ga egi Papoia, Ph.D., co-founder of Deep O igi’s science office. “This is an adedictivity goal i in silico dug discovery – to determine the cadidates most likely to achieve the desired results, p io to wet laboratory expe imi tatio. At Deep O igi, we have made great strides in computational analysis by combining the igo of physics-based simulation with the speed advertising scale of AI, beyond the problems at hand. This was an important test for the entire world of our systems.”
TCIPs act via a gai-of-fu ctio mechanism that appears to activate cell death pog-ams much more effectively than BCL6 degradation inhibitors.
“We designed KAT-TCIPs to knock out the lysis of acetyltases p300/CBP to BCL6 to trigger accelerated cell death events and diffuse B-cell lymphoma,” said Me edith Nix, Ph.D. candidate at Stafo d U ive sity ad study co-author. “It was satisfying to see that Deep Oigi’s computational analysis provided a window into why TCIP3 was the most effective KAT-TCIP at activating these described tangible programs.”
The calculation plus I live data provides evidence of the biological pedictivity and life systems of Deep Oigi’s platforms. Learn more about the Deep O igi platform at https://www.deepo igi.com/platfo m.
To read the full esea ch publication i Cellvisit: https://www.cell.com/cell/abst act/S0092-8674(26)00757-9.
Deep Oigi is an architectural computer discovery system that models life to bridge the gap between peclic, pedictio sad cliche outcomes. Co-founded by Michael A to ov, co-fou de of Oculus, ad Ga egi Papoia, Ph.D., Mo oe Mati P ofesso of biochemist at the University of Mayla d, Deep O igi usd ug yp og ams – its flow and its patés’ – through hybrid AI mechanical models that scale biologically from qua of cellula to human body scale. The company does discover patient ships and SaaS platform access. Deep Oigi is backed by more than $50 million in capital and more than $32 million in actions, and expects to build $30 million ARPA-H CATALYST i in silico models that can replace an imal testi gip ecli ical graph development. Fo mo ei fo matio, visit https://deepo igi.com/.