Chartier Matthieu, Morency Louis-Philippe, Zylber María Inés, Najmanovich Rafael J
Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Québec, Canada.
Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal, Québec, Canada.
BMC Pharmacol Toxicol. 2017 Apr 28;18(1):18. doi: 10.1186/s40360-017-0128-7.
Promiscuity in molecular interactions between small-molecules, including drugs, and proteins is widespread. Such unintended interactions can be exploited to suggest drug repurposing possibilities as well as to identify potential molecular mechanisms responsible for observed side-effects.
We perform a large-scale analysis to detect binding-site molecular interaction field similarities between the binding-sites of the primary target of 400 drugs against a dataset of 14082 cavities within 7895 different proteins representing a non-redundant dataset of all proteins with known structure. Statistically-significant cases with high levels of similarities represent potential cases where the drugs that bind the original target may in principle bind the suggested off-target. Such cases are further analysed with docking simulations to verify if indeed the drug could, in principle, bind the off-target. Diverse sources of data are integrated to associated potential cross-reactivity targets with side-effects.
We observe that promiscuous binding-sites tend to display higher levels of hydrophobic and aromatic similarities. Focusing on the most statistically significant similarities (Z-score ≥ 3.0) and corroborating docking results (RMSD < 2.0 Å), we find 2923 cases involving 140 unique drugs and 1216 unique potential cross-reactivity protein targets. We highlight a few cases with a potential for drug repurposing (acetazolamide as a chorismate pyruvate lyase inhibitor, raloxifene as a bacterial quorum sensing inhibitor) as well as to explain the side-effects of zanamivir and captopril. A web-interface permits to explore the detected similarities for each of the 400 binding-sites of the primary drug targets and visualise them for the most statistically significant cases.
The detection of molecular interaction field similarities provide the opportunity to suggest drug repurposing opportunities as well as to identify potential molecular mechanisms responsible for side-effects. All methods utilized are freely available and can be readily applied to new query binding-sites. All data is freely available and represents an invaluable source to identify further candidates for repurposing and suggest potential mechanisms responsible for side-effects.
小分子(包括药物)与蛋白质之间的分子相互作用杂乱现象广泛存在。这种非预期的相互作用可用于提示药物重新利用的可能性,以及确定导致观察到的副作用的潜在分子机制。
我们进行了一项大规模分析,以检测400种药物的主要靶点的结合位点与7895种不同蛋白质中的14082个腔穴数据集之间的结合位点分子相互作用场相似性,这些蛋白质代表了所有已知结构蛋白质的非冗余数据集。具有高度相似性的统计学显著案例代表了结合原始靶点的药物原则上可能结合所提示的非靶点的潜在情况。对这些案例进一步进行对接模拟分析,以验证药物实际上是否能原则上结合非靶点。整合多种数据来源,将潜在的交叉反应靶点与副作用相关联。
我们观察到杂乱的结合位点往往表现出更高水平的疏水和芳香相似性。聚焦于统计学上最显著的相似性(Z分数≥3.0)并确证对接结果(均方根偏差<2.0 Å),我们发现了2923个案例,涉及140种独特药物和1216个独特的潜在交叉反应蛋白靶点。我们重点介绍了一些具有药物重新利用潜力的案例(乙酰唑胺作为分支酸丙酮酸裂解酶抑制剂,雷洛昔芬作为细菌群体感应抑制剂),以及解释扎那米韦和卡托普利副作用的案例。一个网络界面允许探索400种主要药物靶点的每个结合位点检测到的相似性,并针对统计学上最显著的案例进行可视化展示。
分子相互作用场相似性的检测为提示药物重新利用机会以及确定导致副作用的潜在分子机制提供了契机。所使用的所有方法均可免费获取,并且可轻松应用于新的查询结合位点。所有数据均可免费获取,是识别更多重新利用候选药物以及提示副作用潜在机制的宝贵资源。