Computational Methods in Cooperation with Experimental Approaches to Design Protein Tyrosine Phosphatase 1B Inhibitors in Type 2 Diabetes Drug Design: A Review of the Achievements of This Century.
Mara Ibeth Campos-AlmazánAlicia Hernández-CamposRafael CastilloErick Sierra-CamposMónica Valdez-SolanaClaudia Avitia-DomínguezAlfredo Téllez ValenciaPublished in: Pharmaceuticals (Basel, Switzerland) (2022)
Protein tyrosine phosphatase 1B (PTP1B) dephosphorylates phosphotyrosine residues and is an important regulator of several signaling pathways, such as insulin, leptin, and the ErbB signaling network, among others. Therefore, this enzyme is considered an attractive target to design new drugs against type 2 diabetes, obesity, and cancer. To date, a wide variety of PTP1B inhibitors that have been developed by experimental and computational approaches. In this review, we summarize the achievements with respect to PTP1B inhibitors discovered by applying computer-assisted drug design methodologies (virtual screening, molecular docking, pharmacophore modeling, and quantitative structure-activity relationships (QSAR)) as the principal strategy, in cooperation with experimental approaches, covering articles published from the beginning of the century until the time this review was submitted, with a focus on studies conducted with the aim of discovering new drugs against type 2 diabetes. This review encourages the use of computational techniques and includes helpful information that increases the knowledge generated to date about PTP1B inhibition, with a positive impact on the route toward obtaining a new drug against type 2 diabetes with PTP1B as a molecular target.
Keyphrases
- type diabetes
- molecular docking
- glycemic control
- insulin resistance
- cardiovascular disease
- molecular dynamics simulations
- molecular dynamics
- drug induced
- healthcare
- papillary thyroid
- adverse drug
- protein protein
- skeletal muscle
- body mass index
- high resolution
- systematic review
- adipose tissue
- physical activity
- weight loss
- randomized controlled trial
- mass spectrometry
- transcription factor
- social media
- high fat diet induced
- pi k akt
- endoplasmic reticulum stress