虚拟筛选
分子动力学
分子力学
力场(虚构)
生物信息学
计算生物学
药物发现
对接(动物)
药品
药物重新定位
化学
生物
生物信息学
药理学
计算机科学
计算化学
医学
生物化学
基因
人工智能
护理部
作者
Anushka Mitra,Shibambika Manna,Raima Kundu,Ditipriya Hazra,Amlan Roychowdhury
标识
DOI:10.1109/tcbb.2022.3233670
摘要
Epitranscriptomic modification is a dynamic modification of RNAs. Epitranscriptomic writer proteins are methyltransferases, such as METTL3 and METTL16. The up regulation of METTL3 have been found to be linked to different cancers and targeting METTL3 is an effective way to reduce tumour progression. Drug development against METTL3 is an active field of research. METTL16, SAM dependent methyltransferase, is another writer protein, that has been found to be upregulated in hepatocellular carcinoma and gastric cancer. In this pioneering study METTL16 has been targeted for virtual drug screening for the very first time using brute force strategy to identify a drug molecule that could be repurposed for the treatment of the disease caused. An unbiased library of the commercially available drug molecules has been used for screening using a multipoint validation process developed for this work, which includes molecular docking, ADMET analysis, protein-ligand interaction analysis, Molecular Dynamics Simulation, binding energy calculation via Molecular Mechanics Poisson-Boltzmann Surface Area method. Upon the in-silico screening of over 650 drugs the authors have found NIL and VXL passed the validation process. The data strongly indicates the potency of these two drugs in the treatment of disease where METTL16 needs to be inhibited.
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