Identification of CYP1B1-specific candidate inhibitors using combination ofin silicoscreening, integrated knowledge-based filtering, and molecular dynamics simulations

Multiple machine learning, molecular docking, and ADMET screening approach for identification of selective inhibitors of CYP1B1

Cytochrome P4501B1 is a ubiquitous family protein that is majorly overexpressed in tumors and is responsible for biotransformation-based inactivation of anti-cancer drugs. This inactivation marks the cause of resistance to chemotherapeutics. In the present study, integrated in-silico approaches were utilized to identify selective CYP1B1 inhibitors. To achieve this objective, we initially developed different machine learning models corresponding to two isoforms of the CYP1 family i.e. CYP1A1 and CYP1B1. Subsequently, small molecule databases including ChemBridge, Maybridge, and natural compound library were screened from the selected models of CYP1B1 and CYP1A1. The obtained CYP1B1 inhibitors were further subjected to molecular docking and ADMET analysis. The selectivity of the obtained hits for CYP1B1 over the other isoforms was also judged with molecular docking analysis. Finally, two hits were found to be the most stable which retained key interactions within the active site of CYP1B1 after the molecular dynamics simulations. Novel compound with CYP-D9 and CYP-14 IDs were found to be the most selective CYP1B1 inhibitors which may address the issue of resistance. Moreover, these compounds can be considered as safe agents for further cell-based and animal model studies.Communicated by Ramaswamy H. Sarma.

A computational study on the interactions between a layered imine-based COF structure and selected anticancer drugs

The covalent organic frameworks (COFs) are important materials in drug delivery. Herein, the interactions between an imine-based COF with selected commercially available anticancer drugs are studied. Molecular dynamics (MD) simulation studies were used. The studies were carried out in four different temperatures to find out the impact of the temperature on the binding free energies between the drugs and COF structure. It was found that the effect of temperature on binding free energy is ignorable. Between the hydrogen bonding, electrostatic, and van der Waals interactions, the last one is the most important one to keep the drug and COF next to each other. Also, the van der Waals interaction is keeping the layers of COF next to each other to create cavities. The cavities can be loaded with different drugs and the system can be used in drug delivery systems. Based on the obtained results, the drugs that are more lipophilic prefer to adhere more strongly to the COF in comparison with hydrophilic drugs.

Potential role of CYP1B1 in the development and treatment of metabolic diseases

Cytochrome P450 1B1 (CYP1B1), a member of CYP superfamily, is expressed in liver and extrahepatic tissues carries out the metabolism of numerous xenobiotics, including metabolic activation of polycyclic aromatic hydrocarbons. Surprisingly, CYP1B1 was also shown to be important in regulating endogenous metabolic pathways, including the metabolism of steroid hormones, fatty acids, melatonin, and vitamins. CYP1B1 and nuclear receptors including peroxisome proliferator-activated receptors (PPARs), estrogen receptor (ER), and retinoic acid receptors (RAR) contribute to the maintenance of the homeostasis of these endogenous compounds. Many natural flavonoids and synthetic stilbenes show inhibitory activity toward CYP1B1 expression and function, notably isorhamnetin and 2,4,3',5'-tetramethoxystilbene. Accumulating evidence indicates that modulation of CYP1B1 can decrease adipogenesis and tumorigenesis, and prevent obesity, hypertension, atherosclerosis, and cancer. Therefore, it may be feasible to consider CYP1B1 as a therapeutic target for the treatment of metabolic diseases.