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Full-Text Articles in Computational Chemistry
An Ion-Neutral Reaction To Form Cyanobenzene And Ethynylbenzene In Titan’S Atmosphere, Rachel M. Huchmala, Vincent J. Esposito
An Ion-Neutral Reaction To Form Cyanobenzene And Ethynylbenzene In Titan’S Atmosphere, Rachel M. Huchmala, Vincent J. Esposito
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
The ion-neutral reaction between cyanoacetylene (HC3N) and phenyl anion (C6H5–) leads to the formation of cyanobenzene (C6H5CN) and the ethynyl anion (C2H–) via a submerged, exothermic pathway. Through a different mechanism, the same two reactants also form ethynylbenzene (C6H5C2H) and CN–. These new reactions can be a foundation for the production of substituted benzenes using molecules currently present on Saturn’s largest moon, Titan. Cyclic aromatic molecules like C6H5CN and C6H5 …
Spectroscopy And Photochemistry Of The Astrochemical Molecules Sicp And Alcp, Vincent J. Esposito, Tarek Trabelsi, Rebecca Firth, Ryan C. Fortenberry, Joseph S. Francisco
Spectroscopy And Photochemistry Of The Astrochemical Molecules Sicp And Alcp, Vincent J. Esposito, Tarek Trabelsi, Rebecca Firth, Ryan C. Fortenberry, Joseph S. Francisco
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Through characterization of the electronic excited-state topology, linear-SiCP is predicted to be photostable in the UV region, whereas linear-AlCP is predicted to undergo photodissociation to form Al+CP products after absorption of light in the 200–250 nm range, representing a catalytic process for freeing aluminum molecules from a solid dust grain. Both SiCP and AlCP are predicted to have electronic transitions with large absorption cross sections (∼10–17 cm2) and to undergo fluorescence from bound excited states. The total electronic absorption spectrum is provided to inform electronic spectroscopy experiments. Silicon (SiC) and aluminum (Al2O3) dust …
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 …