id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-104122-klvx927g	Tayfuroglu, Omer	An Accurate Free Energy Method for Solvation of Organic Compounds and Binding to Proteins	2020-05-28		.txt	text/plain	2408	160	46	The method is adopted from ANI-1ccx neural network potentials (Machine Learning) for the Atomic Simulation Environment (ASE) and predicts the single point energies at the accuracy of CCSD(T)/CBS level for the entire configurational space that is sampled by Molecular Dynamics (MD) simulations. [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] More sophisticated methods to calculate the potential binding free energy of inhibitor candidate to the protein ranges from post molecular dynamics simulations such as Molecular 57 Recently several models using active learning such as ANI-1, 58 ANI-1x 59 and ANI-1cxx 60 Here, we introduce a new strategy to estimate free energies of solvation of small organic compounds and binding to proteins in explicit solvent using single end-state MD simulations. The method is adopted from ANI-1ccx neural network potentials (Machine Learning) for the The insertion of the ligand to an environment of solvent (solvation free energy) or receptor (binding free energy) can be defined by a coupling parameter, λ.	./cache/cord-104122-klvx927g.txt	./txt/cord-104122-klvx927g.txt