Homology modeling and molecular docking of URAT1 with chemotherapeutic agents in hyperuricemia and gout

Background:PIM-1 is a kinase which has been related to the oncogenic processes like cell survival, proliferation, and multidrug resistance (MDR). This kinase is known for its ability to phosphorylate the main extrusion pump (ABCB1) related to the MDR phenotype.Objective:In the present work, we tested a new mechanistic insight on the AZD1208 (PIM-1 specific inhibitor) under interaction with chemotherapy agents such as Daunorubicin (DNR) and Vincristine (VCR).Materials and Methods:In order to verify a potential cytotoxic effect based on pharmacological synergism, two MDR cell lines were used: Lucena (resistant to VCR) and FEPS (resistant to DNR), both derived from the K562 non-MDR cell line, by MTT analyses. The activity of Pgp was ascertained by measuring accumulation and the directional flux of Rh123. Furthermore, we performed a molecular docking simulation to delve into the molecular mechanism of PIM-1 alone, and combined with chemotherapeutic agents (VCR and DNR).Results:Our in vitro results have shown that AZD1208 alone decreases cell viability of MDR cells. However, co-exposure of AZD1208 and DNR or VCR reverses this effect. When we analyzed the ABCB1 activity AZD1208 alone was not able to affect the pump extrusion. Differently, co-exposure of AZD1208 and DNR or VCR impaired ABCB1 activity, which could be explained by compensatory expression of abcb1 or other extrusion pumps not analyzed here. Docking analysis showed that AZD1208 is capable of performing hydrophobic interactions with PIM-1 ATP- binding-site residues with stronger interaction-based negative free energy (FEB, kcal/mol) than the ATP itself, mimicking an ATP-competitive inhibitory pattern of interaction. On the same way, VCR and DNR may theoretically interact at the same biophysical environment of AZD1208 and also compete with ATP by the PIM-1 active site. These evidences suggest that AZD1208 may induce pharmacodynamic interaction with VCR and DNR, weakening its cytotoxic potential in the ATP-binding site from PIM-1 observed in the in vitro experiments.Conclusion:Finally, the current results could have a pre-clinical relevance potential in the rational polypharmacology strategies to prevent multiple-drugs resistance in human leukemia cancer therapy.

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Structure Guided Molecular Docking Assisted Alignment Dependent 3DQSAR Study on Steroidal Aromatase Inhibitors (SAIs) as Anti-breast Cancer Agents

Letters in Drug Design & Discovery ◽

10.2174/1570180815666181010101024 ◽

2019 ◽

Vol 16 (7) ◽

pp. 808-817 ◽

Cited By ~ 3

Author(s):

Laxmi Banjare ◽

Sant Kumar Verma ◽

Akhlesh Kumar Jain ◽

Suresh Thareja

Keyword(s):

Breast Cancer ◽

Molecular Docking ◽

Aromatase Inhibitors ◽

Direct Synthesis ◽

3D Qsar ◽

Chemotherapeutic Agents ◽

Modeling Tools ◽

Data Set ◽

Wide Range ◽

Steroidal Aromatase Inhibitors

Background: In spite of the availability of various treatment approaches including surgery, radiotherapy, and hormonal therapy, the steroidal aromatase inhibitors (SAIs) play a significant role as chemotherapeutic agents for the treatment of estrogen-dependent breast cancer with the benefit of reduced risk of recurrence. However, due to greater toxicity and side effects associated with currently available anti-breast cancer agents, there is emergent requirement to develop target-specific AIs with safer anti-breast cancer profile. Methods: It is challenging task to design target-specific and less toxic SAIs, though the molecular modeling tools viz. molecular docking simulations and QSAR have been continuing for more than two decades for the fast and efficient designing of novel, selective, potent and safe molecules against various biological targets to fight the number of dreaded diseases/disorders. In order to design novel and selective SAIs, structure guided molecular docking assisted alignment dependent 3D-QSAR studies was performed on a data set comprises of 22 molecules bearing steroidal scaffold with wide range of aromatase inhibitory activity. Results: 3D-QSAR model developed using molecular weighted (MW) extent alignment approach showed good statistical quality and predictive ability when compared to model developed using moments of inertia (MI) alignment approach. Conclusion: The explored binding interactions and generated pharmacophoric features (steric and electrostatic) of steroidal molecules could be exploited for further design, direct synthesis and development of new potential safer SAIs, that can be effective to reduce the mortality and morbidity associated with breast cancer.

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