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Multidimensional Replica Exchange simulations for Efficient constant pH and Redox Potential Molecular Dynamics
Vinícius Wilian D. Cruzeiro, Adrian E. Roitberg
Efficient computational methods that are capable of supporting experimental measures obtained at constant values of pH and redox potential are important tools as they serve to, amo…
Transferable Molecular Charge Assignment Using Deep Neural Networks
Ben Nebgen, Nick Lubbers, Justin S. Smith +6
We use HIP-NN, a neural network architecture that excels at predicting molecular energies, to predict atomic charges. The charge predictions are accurate over a wide range of molec…
Redox potential replica exchange molecular dynamics at constant pH in AMBER: Implementation and validation
Vinicius Wilian D. Cruzeiro, Marcos S. Amaral, Adrian E. Roitberg
Redox processes are important in chemistry, with applications in biomedicine, chemical analysis, among others. As many redox experiments are also performed at a fixed value of pH,…
ANI-1: A data set of 20M off-equilibrium DFT calculations for organic molecules
Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg
One of the grand challenges in modern theoretical chemistry is designing and implementing approximations that expedite ab initio methods without loss of accuracy. Machine learning…
ANI-1: An extensible neural network potential with DFT accuracy at force field computational cost
Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg
Deep learning is revolutionizing many areas of science and technology, especially image, text and speech recognition. In this paper, we demonstrate how a deep neural network (NN) t…