Abstract
Metabolic and signaling mechanisms in mammalian cells are facilitated by the transportation of L-arginine (Arg) across the plasma membrane through cationic amino acid transporter (CAT) proteins. Due to a lack of argininosuccinate synthase (ASS) activity in various tumor cells such as acute myeloid leukemia, acute lymphocytic leukemia, and chronic lymphocytic leukemia, these tumor entities are arginine-auxotrophic and therefore depend on the uptake of the amino acid arginine. Cationic amino acid transporter-1 (CAT-1) is the leading arginine importer expressed in the aforementioned tumor entities. Hence, in the present study, to investigate the transportation mechanism of arginine in CAT-1, we performed molecular dynamics (MD) simulation methods on the modeled human CAT-1. The MM-PBSA approach was conducted to determine the critical residues interacting with arginine within the corresponding binding site of CAT-1. In addition, we found out that the water molecules have the leading role in forming the transportation channel within CAT-1. The conductive structure of CAT-1 was formed only when the water molecules were continuously distributed across the channel. Steered molecular dynamics (SMD) simulation approach showed various energy barriers against arginine transportation through CAT-1, especially while crossing the bottlenecks of the related channel. These findings at the molecular level might shed light on identifying the crucial amino acids in the binding of arginine to eukaryotic CATs and also provide fundamental insights into the arginine transportation mechanisms through CAT-1. Understanding the transportation mechanism of arginine is essential to developing CAT-1 blockers, which can be potential medications for some types of cancers.
Communicated by Ramaswamy H. Sarma
Acknowledgments
We are especially grateful to Dr. Babak Afshin-pour, from VeridianML, for providing us High-Performance Computer facility for this study.
Data availability statement
Homology modeling of CAT-1 was performed using MODELLER v10.20. The preliminary docking study was done by adopting AutoDock VINA, version 1.1.2. MD simulations were performed adopting the GROMACS package. CHARMM-GUI web server was further adopted in the preparation of parameters and input for MD simulations. The tunnels and channels were detected by CAVER web server, version 1.1. The preparation of the structure and the analysis of trajectories were performed by adopting the built-in tools in the GROMACS package, Chimerax, and VMD software. The full workflow is reported in the ‘Computational Methods’ section of the manuscript.
Disclosure statement
The authors report there are no competing interests to declare.