Methyl α-D-mannopyranoside (MAM) is a naturally occurring carbohydrate derivative that has gained attention in drug discovery due to its potential therapeutic applications, particularly as an antifungal agent. In this study, we employed a computational approach to investigate the interactions between MAM and two Candida albicans antifungal proteins, 1IYL and 1AI9, through molecular docking simulations. Furthermore, we performed a PASS (Prediction of Activity Spectra for Substances) analysis to predict MAM potential biological activities, explored the pharmacokinetic properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles, and optimized the MAM using the density functional theory (DFT) method. The molecular docking results revealed favorable binding interactions between MAM and the active sites of the 1IYL and 1AI9 proteins, suggesting potential antifungal activity. Additionally, the ADMET profiles indicated low toxicity and suitable drug-like properties, such as moderate metabolic stability and minimal risk of adverse effects. Furthermore, DFT optimization was performed to investigate the molecular geometry and electronic properties of MAM. The optimization results provided valuable information on the stability and reactivity of MAM, enabling a better understanding of its chemical behavior and potential modifications for enhanced activity. Finally, PASS prediction was employed to evaluate MAM's potential biological activities beyond its antifungal properties. The analysis revealed several potential activities, including antibacterial, antiviral, and immunomodulatory effects, expanding the scope for future research and therapeutic applications. In conclusion, this computational study sheds light on the molecular interactions, pharmacokinetic properties, ADMET profiles, DFT optimization, and PASSES predictions of MAM. These findings highlight the potential of MAM as a promising antifungal agent with favorable pharmacological properties.

This research aims to know and analyze the direct and indirect impacts of service quality and ticket price policy on trust and also its impact on the passenger loyalty of Soekarno-Hatta Airport Train, Cengkareng, Indonesia. The main problems are that the service quality provided by Soekarno-Hatta Airport Train is not maximal and that the ticket price of the Soekarno-Hatta Airport Train is relatively expensive because the passengers still have to use another transportation mode to go to the station. This research uses a quantitative approach with Structural Equation Modelling, assisted by the Lisrel program with a sample of as many as 150 passengers. The results of this research prove that service quality and ticket price policy have both direct and indirect impacts on passenger loyalty through the mediation of passenger trust. The key finding is that the policymakers can take advantage of the findings of this research, especially the crucial aspects in the questionnaires on service quality and ticket price policy which are considered not optimal by the passengers of Soekarno-Hatta Airport Train. So, passenger loyalty can be enhanced through the improvement of service quality and ticket price policy supported by passenger trust.