title: Identification of novel natural compound inhibitors for human complement component 5a receptor by homology modeling and virtual screening.
abstract: Neuropathic pain and inflammatory pain are two common types of pathological pain in human health problems. To date, normal painkillers are only partially effective in treating such pain, leading to a tremendous demand to develop new chemical entities to combat pain and inflammation. A promising pharmacological treatment is to control signal transduction via the inflammatory mediator-coupled receptor protein C5aR by finding antagonists to inhibit C5aR activation. Here, we report the first computational study on the identification of non-peptide natural compound inhibitors for C5aR by homology modeling and virtual screening. Our study revealed a novel natural compound inhibitor Acteoside with better docking scores than all four existing non-peptidic natural compounds. The MM-GBSA binding free energy calculations confirmed that Acteoside has a decrease of ~39 kcal/mol in the free energy of binding compared to the strongest binding reference compound. Main contributions to the higher affinity of Acteoside to C5aR are the exceptionally strong lipophilic interaction, enhanced electrostatics and hydrogen bond interactions. Detailed analysis on the physiochemical properties of Acteoside suggests further directions in lead optimization. Taken together, our study proposes that Acteoside is a potential lead molecule targeting the C5aR allosteric site and provides helpful information for further experimental studies.
authors: E11-4025, Faculty of Science and Technology (FST), University of Macau, Avenida da Universidade, Taipa, Macau, China.
authors: Faraz
authors: F
authors: Shaikh
authors: E11-4025, Faculty of Science and Technology (FST), University of Macau, Avenida da Universidade, Taipa, Macau, China.
authors: Shirley W I
authors: SW
authors: Siu
keywords: C5aR; Homology modeling; MM-GBSA; Molecular docking; Natural compound inhibitor; Virtual screening