Herein, molecular modeling techniques were used with the main goal to obtain candidates from a drug database as potential targets to be used against SARS-CoV-2. This novel coronavirus, responsible by the COVID-19 outbreak since the end of 2019, became a challenge since there is not vaccine for this disease. The first step in this investigation was to solvate the isolated S-protein in water for molecular dynamics (MD) simulation, being observed a transition from “up” to “down” conformation of receptor-binding domain (RBD) of the S-protein with angle of 54.3 and 43.0 degrees, respectively. The RBD region was more exposed to the solvent and to the possible drugs due to its enhanced surface area. From the equilibrated MD structure, virtual screening by docking calculations were performed using a library contained 9091 FDA approved drugs. Among them, 24 best-scored ligands (14 traditional herbal isolate and 10 approved drugs) with the binding energy below –8.1 kcal/mol were selected as potential candidates to inhibit the SARS-CoV-2 S-protein, preventing the human cell infection and their replication. For instance, the ivermectin drug (present in our list of promise candidates) was recently used successful to control viral replication in vitro. MD simulations were performed for the three best ligands@S-protein complexes and the binding energies were calculated using the MM/PBSA approach. Overall, it is highlighted an important strategy, some key residues, and chemical groups which may be considered on clinical trials for COVID-19 outbreak. Graphical Abstract

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

The effectiveness of antibiotics is greatly enhanced by their ability to target invasive organisms involved in the ancient evolutionary battle between hosts and pathogens.