Denovo Sciences develops a platform that utilizes Reinforcement Learning algorithms to design and optimize chemical structures without the need for training datasets. This technology enables exploration of chemical space and the rational design of multitarget chemical structures.

Denovo Sciences

Denovo Sciences | 925 followers on LinkedIn. A deep technology company that creates novel therapeutics using state-of-the-art AI technologies. | A deep technology company that creates novel therapeutics using state-of-the-art AI technologies.

Antiviral Drug Hunter; Co-Founder and CEO of Denovo Sciences

Hovakim Zakaryan

Computer-Aided Drug Design

Smbat Gevorgyan

Irina Tirosyan

Co-Founder at Denovo Sciences

Mher Matevosyan

Congratulations to Demis Hassabis , John Jumper , and David Baker on being awarded the Nobel Prize in Chemistry! Your groundbreaking work in computational biology and artificial intelligence has truly revolutionized the field. A special note of gratitude to Demis Hassabis, whose pioneering work in deep reinforcement learning at Google DeepMind has been a significant source of inspiration for Denovo Sciences . Thank you for pushing the boundaries of science and technology. #NobelPrize #Chemistry #DeepMind #AI #ReinforcementLearning #ProteinFolding #DenovoSciences

Due to regional instability, some flights have been canceled, which has led to the postponement of Marco Vignuzzi 's scheduled lecture. The new date and time will be announced. Stay tuned for updates, and thank you for your understanding.

📢 Here is a new offline lecture by our esteemed collaborator and renowned scientist, Marco Vignuzzi ! Do not miss this unique opportunity to gain fascinating insights into the Achilles heel of viruses. 🗓️ Date: October 4 🕑 Time: 14:00 (GMT+4) 📍 Location: National Academy of Sciences (Yerevan, Armenia) Please mark your calendars and join us for this fantastic lecture!

We witness incredible growth in the chemical space for small molecules, with over 37 billion molecules now available for HTS and virtual screening. With this huge chemical space, the need for novel tools to discover truly innovative molecules has never been more crucial. Our cutting-edge AI-based platform not only allows us to effectively navigate in this complex chemical space but also identifies new "chemical islands" that meet essential drug-like criteria for each specific target, even when data for targets is scarce.

Join us at DataFest to hear from our co-founder and CTO, Mher Matevosyan . He will speak about our proprietary platform for small molecule drug discovery and present a compelling case study on influenza viruses. Do not miss this opportunity to learn more about our innovative technology!

Despite the rise of biologics and gene therapies, small molecules remain the preferred modality for many diseases. Their flexible modes of action, long shelf-life, and potential for combination therapy continue to make them invaluable in addressing medical needs. With the advent of new technologies, such as those pioneered by our company, the exploration of the vast small molecule chemical space is now more efficient and effective than ever before in the 120-year history of small molecule drug discovery.

Our co-founder Hovakim Zakaryan gave an insightful interview on the cutting-edge computational drug discovery approaches we use at Denovo Sciences. He focused on how we leverage deep reinforcement learning to tackle drug discovery, even when data is limited. Do not miss this interview! https://lnkd.in/esjzU2Vw

Excited to share our latest research on SARS-CoV-2 Mpro enzyme crystallographic structures! Our team has analyzed over 300 high-resolution structures available in the Protein Data Bank (PDB) and showed that not all are suitable for virtual screening or computational drug design. Minor amino acid flips in the binding pockets of some structures significantly hinder the performance of various docking programs. This comprehensive study highlights the critical importance of selecting the correct PDB structures to positively impact the entire drug discovery process. Learn more about our findings here: https://lnkd.in/gvafD9zU

We're thrilled to announce the next speaker in our drug discovery lecture series! Tudor Oprea, MD PhD will present a lecture titled "Drug Discovery and Repurposing in the LLM era". Everyone interested is invited to register via the following link: https://lnkd.in/gbbh_nSK The lecture is scheduled for April 30th at 6:00 PM (GMT+4). The number of the participants is limited. Upon registration, you'll automatically receive an invitation to add the event to your calendar. If you don't receive it, please don't hesitate to email us at info@denovosciences.ai ____________________ Tudor I. Oprea is a digital drug hunter with three decades of experience in artificial intelligence and knowledge management in target and drug discovery. Three of the drugs he co-invented reached clinical trials, including R-ketorolac which he repurposed for ovarian cancer. His validated machine learning models cover diseases, targets and chemicals, and he has made significant contributions in disease and chemical biology. Oprea co-created DrugCentral and Pharos two open-source platforms. Tudor is now CEO at Expert Systems Inc (San Diego, CA) and Professor Emeritus of Medicine, UNM Health Sciences Center (Albuquerque, NM).

Mark your calendars for the third lecture in our drug discovery series, featuring Dr. Ruben Abagyan, Professor at the Skaggs School of Pharmacy and Pharmaceutical Sciences, UC San Diego and Founder of MolSoft LLC. The lecture topic is: “Drugs ex machina: from science and computers to novel therapeutics”. Everyone interested is invited to register through this link: https://lnkd.in/ehvbxXwh The lecture is scheduled for March 28th at 6:00 PM (GMT+4). Registration will close on March 27th. Upon registration, you will automatically receive an invitation to the event on your calendar. If you encounter any issues with receiving the invitation, please feel free to email us at info@denovosciences.ai . ------------ Ruben Abagyan is a Professor at the Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego and founder of MolSoft LLC. After training in physics and math at MPTI, and receiving his PhD in Biophysics at MSU, he developed a breakthrough approach in molecular modeling and ligand docking in the European Institute of Molecular Biology in Heidelberg, Germany, as a staff scientist; moved to the Skirball Institute of New York University as an Associate Professor of Biochemistry and Mathematics; founded MolSoft; became Director of Computational Chemistry at the Novartis Institute in La Jolla, and spent 10 years as a Professor at the Scripps Research Institute. He published over 340 articles and chapters that have been cited over 44,230 times, achieving H-index of 99. He has been serving on high profile international review and advisory panels in European Research Counsel, Switzerland, Hong Kong, UK, US, and several boards of directors. He also received CapCure awards, UCSD teaching excellence awards, top 1% most performing and cited faculty, and Princess Diana award and medal. The modeling, docking, and ligand screening software, ICM-pro or its FOCUS version co-developed with the Novartis team, was successfully used for over 25 years by the chemists and biologists in big pharma, biotech and academia, and contributed to the discovery of several drugs.

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