Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China.
School of Life Sciences, Beijing Institute of Technology, Beijing 100081, China.
Molecules. 2022 Dec 10;27(24):8773. doi: 10.3390/molecules27248773.
Mitochondrial aldehyde dehydrogenase (ALDH2) is a potential target for the treatment of substance use disorders such as alcohol addiction. Here, we adopted computational methods of molecular dynamics (MD) simulation, docking, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis to perform a virtual screening of FDA-approved drugs, hitting potent inhibitors against ALDH2. Using MD-derived conformations as receptors, butenafine (net charge = +1 ) and olaparib ( = 0) were selected as promising compounds with a low toxicity and a binding strength equal to or stronger than previously reported potent inhibitors of daidzin and CVT-10216. A few negatively charged compounds were also hit from the docking with the Autodock Vina software, while the MM-PBSA analysis yielded positive binding energies (unfavorable binding) for these compounds, mainly owing to electrostatic repulsion in association with a negatively charged receptor ( = -6 for ALDH2 plus the cofactor NAD). This revealed a deficiency of the Vina scoring in dealing with strong charge-charge interactions between binding partners, due to its built-in protocol of not using atomic charges for electrostatic interactions. These observations indicated a requirement of further verification using MD and/or MM-PBSA after docking prediction. The identification of key residues for the binding implied that the receptor residues at the bottom and entrance of the substrate-binding hydrophobic tunnel were able to offer additional interactions with different inhibitors such as π-π, π-alkyl, van der Waals contacts, and polar interactions, and that the rational use of these interactions is beneficial to the design of potent inhibitors against ALDH2.
线粒体乙醛脱氢酶(ALDH2)是治疗物质使用障碍(如酒精成瘾)的潜在靶点。在这里,我们采用分子动力学(MD)模拟、对接和分子力学泊松-玻尔兹曼表面面积(MM-PBSA)分析的计算方法,对 FDA 批准的药物进行虚拟筛选,以找到针对 ALDH2 的有效抑制剂。使用 MD 衍生的构象作为受体,丁萘芬(净电荷 = +1)和奥拉帕利( = 0)被选为具有低毒性和与先前报道的大豆苷和 CVT-10216 的有效抑制剂相当或更强的有前途的化合物。一些带负电荷的化合物也通过 Autodock Vina 软件的对接被击中,而 MM-PBSA 分析为这些化合物产生了正的结合能(不利的结合),这主要是由于与带负电荷的受体(ALDH2 加辅因子 NAD 的 = -6)的静电排斥。这表明 Vina 评分在处理结合物之间的强电荷-电荷相互作用方面存在缺陷,这是由于其内置协议不使用原子电荷进行静电相互作用。这些观察结果表明,在对接预测后,需要进一步使用 MD 和/或 MM-PBSA 进行验证。对结合关键残基的鉴定表明,底物结合疏水性隧道底部和入口处的受体残基能够与不同的抑制剂(如π-π、π-烷基、范德华接触和极性相互作用)提供额外的相互作用,并且合理利用这些相互作用有利于设计针对 ALDH2 的有效抑制剂。