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Full-Text Articles in Other Chemistry
De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian
De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder–Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards …
Cyclic Peptide-Gadolinium Nanocomplexes As Sirna Delivery Tools, Amir Nasrolahi Shirazi, Muhammad Imran Sajid, Dindyal Mandal, David Stickley, Stephanie Nagasawa, Joshua Long, Sandeep Lohan, Keykavous Parang, Rakesh Kumar Tiwari
Cyclic Peptide-Gadolinium Nanocomplexes As Sirna Delivery Tools, Amir Nasrolahi Shirazi, Muhammad Imran Sajid, Dindyal Mandal, David Stickley, Stephanie Nagasawa, Joshua Long, Sandeep Lohan, Keykavous Parang, Rakesh Kumar Tiwari
Pharmacy Faculty Articles and Research
We have recently reported that a cyclic peptide containing five tryptophan, five arginine, and one cysteine amino acids [(WR)5C], was able to produce peptide-capped gadolinium nanoparticles, [(WR)5C]-GdNPs, in the range of 240 to 260 nm upon mixing with an aqueous solution of GdCl3. Herein, we report [(WR)5C]-GdNPs as an efficient siRNA delivery system. The peptide-based gadolinium nanoparticles (50 µM) did not exhibit significant cytotoxicity (~93% cell viability at 50 µM) in human leukemia T lymphoblast cells (CCRF-CEM) and triple-negative breast cancer cells (MDA-MB-231) after 48 h. Fluorescence-activated cell sorting (FACS) analysis indicated …