Therapeutic Potential of Simvastatin: Cellular Mechanism, Binding Energetics, and Resistance Developments
Statins are a class of hypolipidemic agents that have been shown to promote osteogenic differentiation through enhanced alveolar bone recovery, inserted osseointegration, and cartilage regeneration. This review uses Molecular Docking (MD) simulations and additional Computer- Aided Drug Design (CADD) methods to present the state of the art in statin therapy. Furthermore, several studies have shown that factors such as limited overall absorption, metabolism in the first pass, and systemic side effects are among those that affect the oral administration of statins. In addition, these variables include susceptibility to efflux mechanisms, drug permeability, dissolution percentage, aqueous solubility, initial metabolism, and pre-systemic metabolism. Additionally examined are the pharmacokinetics of the statin and <i>in vivo</i> mechanisms of action. As a result of the numerous problems associated with the consumption of statins, including their low total bioavailability, first-pass metabolism, low aqueous solubility, and systemic adverse reactions, a non-oral mode of administration was looked into for this crucial and primary class of pharmacokinetic agents. However, to optimize bioavailability and minimize side effects, more research is required.
Authors
- Saurabh Srivastava (ORCID: https://orcid.org/0000-0003-4610-1790)
- Rishabha Malviya (ORCID: https://orcid.org/0000-0003-2874-6149)
- Deependra Pratap Singh (ORCID: https://orcid.org/0000-0002-8897-7777)
- Sonali Sundaram
- Sathvik Belagodu Sridhar (ORCID: https://orcid.org/0000-0002-9100-2508)
- Shristy Verma (ORCID: https://orcid.org/0009-0009-0399-0648)
- Safia Obaidur Rab
Institutions
- Galgotias University (IN)
- Nilai University (MY)
- KPJ Healthcare University
- Graphic Era University (IN)
- King Khalid University (SA)
- Ras al-Khaimah Medical and Health Sciences University (AE)
Publication Details
- Journal
- Current Topics in Medicinal Chemistry
- Published
- 2025-02-04
- DOI
- https://doi.org/10.2174/0115680266327892241223052456
- Citations
- 1
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 1.50