IDPs (labeled as train in Table ) for optimizing the hydrophobicity parameters, and a test set consisting of 10 IDPs (labeled as test in Table ) for evaluating the accuracy of the optimized hydrophobicity parameters. For each IDP in the training set, the 100,000 We optimize the hydrophobicity parameters θ by maximizing the average log-likelihood function of all IDPs in the training set. These optimized hydrophobicity parameters are denoted as θ 1 . Using θ 1 , we run temperature replica exchange MD simulations with the same settings as before for all IDPs. The canonical ensemble at 300 K with the optimized hydrophobicity parameters θ 1 is denoted as Z 1 . The simulated R g values derived from the ensemble Z 1 are compared with the experimental R g values, as illustrated in Fig. and 1c for the training and test IDPs, respectively. Compared to the initial hydrophobicity parameters θ 0 , the optimized parameters θ 1 significantly improve the agreement between the simulated and experimental R g values for both the training and test IDPs (Fig. ).