Potentially highly potent drugs for 2019-nCoV

Duc Duy Nguyen; Kaifu Gao; Jiahui Chen; Rui Wang; Guo-Wei Wei

MathPose, a 3D pose predictor which converts SMILES strings into 3D poses with references of target molecules, was the top performer in D3R Grand Challenge 4 in predicting the poses of 24 beta-secretase 1 (BACE) binders [23] . For one SMILES string, around 1000 3D structures can be generated by a common docking software tool, i.e., GLIDE [27] . Moreover, a selected set of known complexes is re-docked by the three docking software packages mentioned above to generate at 100 decoy complexes per input ligand as a machine learning training set. The machine learning labels will be the calculated root mean squared deviations (RMSDs) between the decoy and native structures for this training set. Furthermore, MathDL models will be set up and applied to select the top-ranked pose for the given ligand. Additionally, the top poses will be fed into the MathDL for druggable proprieties evaluation.