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Homology Modelling, Docking-based Virtual Screening, ADME Properties, and Molecular Dynamics Simulation for Identification of Probable Type II Inhibitors of AXL Kinase

广告 对接(动物) 同源建模 化学 分子动力学 虚拟筛选 计算生物学 分子模型 激酶 同源(生物学) 组合化学 立体化学 生物化学 计算化学 氨基酸 生物 体外 护理部 医学
作者
Heena R. Bhojwani,Urmila J. Joshi
出处
期刊:Letters in Drug Design & Discovery [Bentham Science Publishers]
卷期号:19 (3): 214-241 被引量:1
标识
DOI:10.2174/1570180818666211004102043
摘要

Background: AXL kinase is an important member of the TAM family for kinases which is involved in most cancers. Considering its role in different cancers due to its pro-tumorigenic effects and its involvement in the resistance, it has gained importance recently. Majority of research carried out is on Type I inhibitors and limited studies have been carried out for Type II inhibitors. Taking this into consideration, we have attempted to build Homology models to identify the Type II inhibitors for the AXL kinase. Methods: Homology Models for DFG-out C-helix-in/out state were developed using SWISS Model, PRIMO, and Prime. These models were validated by different methods and further evaluated for stability by molecular dynamics simulation using Desmond software. Selected models PED1-EB and PEDI1-EB were used for the docking-based virtual screening of four compound libraries using Glide software. The hits identified were subjected to interaction analysis and shortlisted compounds were subjected to Prime MM-GBSA studies for energy calculation. These compounds were also docked in the DFG-in state to check for binding and elimination of any compounds that may not be Type II inhibitors. The Prime energies were calculated for these complexes as well and some compounds were eliminated. ADMET studies were carried out using Qikprop. Some selected compounds were subjected to molecular dynamics simulation using Desmond for evaluating the stability of the complexes. Results: Out of 78 models inclusive of both DFG-out C-helix-in and DFG-out C-helix-out, 5 models were identified after different types of evaluation as well as validation studies. 1 model representing each type (PED1-EB and PEDI1-EB) was selected for the screening studies. The screening studies resulted in the identification of 29 compounds from the screen on PED1-EB and 10 compounds from the screen on PEDI1-EB. Hydrogen bonding interactions with Pro621, Met623, and Asp690 were observed for these compounds primarily. In some compounds, hydrogen bonding with Leu542, Glu544, Lys567, and Asn677 as well as pi-pi stacking interactions with either Phe622 or Phe691 were also seen. 4 compounds identified from PED1-EB screen were subjected to molecular dynamics simulation and their interactions were found to be consistent during the simulation. 2 compounds identified from PEDI1-EB screen were also subjected to the simulation studies, however, their interactions with Asp690 were not observed for a significant time and in both cases differed from the docked pose. Conclusion: Multiple models of DFG-out conformations of AXL kinase were built, validated and used for virtual screening. Different compounds were identified in the virtual screening, which may possibly act as Type II inhibitors for AXL kinase. Some more experimental studies can be done to validate these findings in future. This study will play a guiding role in the further development of the newer Type II inhibitors of the AXL kinase for the probable treatment of cancer.
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