We note that, DMFF is currently still under active development. Being open-source, we expect it to become an ever-improving useful tool with a community effort. In the near future, more flexible support for the function forms of the FF model, optimization schemes using dynamical properties, interface with more MD engines, are to be developed. All activities The initial structures of the protein and ligands were obtained from the original paper. AMBER99SB force field was used to paramterize the protein. 16 lambdas windows were set and the value of lambdas were adapted on-the-fly. After energy minimization, a standard 5-stage equilibrium protocol was carried out to relax the system with all parameters set to default. Then, 5 ns production simulation was performed and Langevin thermostat and Parrinello-Rahman barostat were adopted to keep the system at 300 K and 1 bar and other parameters were set to default. In the optimization process, steep gradient descent algorithm was used and the learning rate was set to 0.0005.