Assessing the Performance of GOLD, Glide and MM-GBSA on a Dataset of Hydrazide-hydrazone-based Tuberculostatics

Abstract

Background: Tuberculosis is considered a global health problem; hence, the screening and synthesis of novel tuberculostatic drugs are a necessity. Molecular docking could drastically reduce the time of hit identification; however, initial validation is required to reduce the false-positive results. Objective: Assessment of several searching and scoring algorithms for a custom dataset of hydrazidehydrazone- based tuberculostatics was conducted to obtain a reliable docking protocol for future virtual screening. Methods: Modification in the scoring functions, size of the grid space, and presence of active waters of a GOLD 5.3 docking protocol was conducted. Subsequently, side-chain flexibility and ensemble docking were carried out to assess the role of protein flexibility in the correlation coefficient. In addition, docking simulations with Glide and free binding energy calculations with MM-GBSA were implemented. The Pearson correlation coefficient between the experimental and the acquired in silico data was calculated after each work step. The major interactions between the top-scored ligands and the active site of 2X22 were visualized applying Discovery Studio. Results: An optimized GOLD 5.3 docking protocol led to a drastically enhanced Pearson correlation coefficient of the training set, from 0.461 to 0.823, as well as an excellent pairwise correlation coefficient in the test set - 0,8405. Interestingly, the Glide docking scores and the free binding energy calculations with MM-GBSA did not achieve reliable results. During the visualization of the top-ranked compounds, it was observed that Lys165 played a major role in the formation of stable complexes. Conclusion: It could be concluded that the performance of the optimized GOLD 5.3 docking protocol demonstrated significantly higher reliability against the hydrazide-hydrazone dataset when compared to Glide docking simulations and MM-GBSA free binding energy calculations. The results could be utilized for future virtual screenings.