CBSF: A New Empirical Scoring Function for Docking Parameterized by Weights of Neural Network

A new CBSF empirical scoring function for the estimation of binding energies between proteins and small molecules is proposed in this report. The final score is obtained as a sum of three energy terms calculated using descriptors based on a simple counting of the interacting protein-ligand atomic pairs. All the required weighting coefficients for this method were derived from a pretrained neural network. The proposed method demonstrates a high accuracy and reproduces binding energies of protein-ligand complexes from the CASF-2016 test set with a standard deviation of 2.063 kcal/mol (1.511 log units) and an average error of 1.682 kcal/mol (1.232 log units). Thus, CBSF has a significant potential for the development of rapid and accurate estimates of the protein-ligand interaction energies

Ab Initio Study Predicts That Enigmatic Isonitrosyl Fluoride Should Be Stable at Low Temperatures yet Unnoticeable Due to Its Photoreactivity

Isonitrosyl fluoride F–ON remains an undetected molecule despite multiple attempts to generate it and successful identification of other isonitrosyl halides (X–ONs) via phototransformations of corresponding X-NOs. We investigated this problem using ab initio methods and found no evidence of instability of F–ON at low temperatures of 8–10 K. Instead, experimental observation of F–ON is likely challenged by the (1) different nature of photoexcitation of F-NO and its quantum yield being lower than those of other X-NOs and (2) the presence of a bright charge-transfer transition in the F–ON spectrum that likely overlaps with the weak band of F-NO used for photoexcitation. Formation of F–ON via symmetry-prohibited photoexcitation of F-NO is followed by its immediate photodecomposition to the charge-transfer excited state and its conversion to F-NO upon de-excitation. Thus, F–ON should be readily observable using non-photochemistry methods such as microwave spectroscopy