Research Paper Volume 12, Issue 9 pp 8523—8535
Computational study of novel natural inhibitors targeting aminopeptidase N(CD13)
- 1 Clinical College, Jilin University, Changchun, China
- 2 Hepatopancreatobiliary Medicine Department, Jilin University First Hospital, Changchun, China
- 3 Department of Neurosurgery, The Xuanwu Hospital Capital Medical University, Changchun, Beijing, China
- 4 Department of Orthopedics, The First Hospital of Jilin University, Changchun, China
- 5 Department of Orthopaedic Surgery, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
- 6 Department of Oncology, the First Hospital of Jilin University, Changchun, China
- 7 The Laboratory of Cancer Precision Medicine, The First Hospital of Jilin University, Changchun, China
- 8 Department of Oncology, The First Hospital of Jilin University, Changchun, China
Received: November 10, 2019 Accepted: April 17, 2020 Published: May 9, 2020https://doi.org/10.18632/aging.103155
How to Cite
Copyright © 2020 Ge et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Objectives: To screen and identify ideal leading compounds from a drug library (ZINC15 database) with potential inhibition of aminopeptidase N(CD13) to contribute to medication design and development.
Results: Two novel natural compounds, ZINC000000895551 and ZINC000014820583, from the ZINC15 database were found to have a higher binding affinity and more favorable interaction energy binding with CD13 with less rodent carcinogenicity, Ames mutagenicity, and non-inhibition with cytochrome P-450 2D6. Molecular dynamics simulation analysis suggested that the 2 complexes, ZINC000000895551-CD13 and ZINC000014820583-CD13, have favorable potential energy, and exist stably in the natural circumstances.
Conclusion: This study discovered that ZINC000000895551 and ZINC000014820583 were ideal leading compounds to be inhibitions targeting to CD13. These compounds were selected as safe drug candidates as CD13 target medication design and improvement.
Materials and Method: Potential inhibitors of CD13 were identified using a series of computer-aided structural and chemical virtual screening techniques. Structure-based virtual screening was carried out to calculate LibDock scores, followed by analyzing their absorption, distribution, metabolism, and excretion and toxicity predictions. Molecule docking was employed to reveal binding affinity between the selected compounds and CD13. Molecular dynamics simulation was applied to evaluate stability of the ligand-CD13 complex under natural environment.