Computational insight into the binding of bryostatin 1 with ferritin: implication of natural compounds in Alzheimer’s disease therapeutics

Abstract

Neuronal damage in iron-sensitive brain regions occurs as a result of iron dyshomeostasis. Increased iron levels and iron-related pathogenic triggers are associated with neurodegenerative diseases, including Alzheimer’s disease (AD). Ferritin is a key player involved in iron homeostasis. Major pathological hallmarks of AD are amyloid plaques, neurofibrillary tangles (NFTs) and synaptic loss that lead to cognitive dysfunction and memory loss. Natural compounds persist in being the most excellent molecules in the area of drug discovery because of their different range of therapeutic applications. Bryostatins are naturally occurring macrocyclic lactones that can be implicated in AD therapeutics. Among them, Bryostatin 1 regulates protein kinase C, a crucial player in AD pathophysiology, thus highlighting the importance of bryostatin 1 in AD management. Thus, this study explores the binding mechanism of Bryotstain 1 with ferritin. In this work, the molecular docking calculations revealed that bryostatin 1 has an appreciable binding potential towards ferritin by forming stable hydrogen bonds (H-bonds). Molecular dynamics simulation studies deciphered the binding mechanism and conformational dynamics of ferrritin–bryostatin 1 system. The analyses of root mean square deviation, root mean square fluctuations, R_g, solvent accessible surface area, H-bonds and principal component analysis revealed the stability of the ferritin–bryostatin 1 docked complex throughout the trajectory of 100 ns. Moreover, the free energy landscape analysis advocated that the ferritin–bryostatin 1 complex stabilized to the global minimum. Altogether, the present work delineated the binding of bryostatin 1 with ferritin that can be implicated in the management of AD.

Communicated by Ramaswamy H. Sarma

Keywords:

• Ferritin
• bryostatin 1
• Alzheimer’s disease
• molecular docking
• molecular dynamics simulation
• principal component analyses

Disclosure statement

There is no conflict of interest to declare.

Author contributions

Moyad Shahwan: Conceptualization, writing-review and editing; Fahad A. Alhumaydhi: Data curation, data validation, resources, visualization, software, writing-review and editing; Sharaf E. Sharaf: Data validation, data analysis; writing-review and editing; Badrah S. Alghamdi: Editing, data curation; Saleh Salem Baees: Methodology, investigation, writing-review and editing; Haythum O. Tayeb: Visualization, software, data validation, writing-review and editing; Haythum O. Tayeb: Data validation, software, project administration, writing-original draft, data curation, investigation; Ghluam Md. Ashraf: Visualization, software, writing-review and editing Anas Shamsi: Data curation, supervision, visualization, writing-review and editing, formal analysis, project administration, writing-original draft.

Additional information

Funding

This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under the grant No. (G-302-141-1441). The authors, therefore, acknowledge with thanks DSR for technical and financial support.