Univ. Grenoble Alpes, CNRS, DPM, 38000, Grenoble, France; Univ. Grenoble Alpes, CNRS, CEA, LCBM, 38000, Grenoble, France.
Univ. Grenoble Alpes, CNRS, DPM, 38000, Grenoble, France.
Eur J Med Chem. 2022 Oct 5;240:114599. doi: 10.1016/j.ejmech.2022.114599. Epub 2022 Jul 11.
Hydrolysis of β-lactam drugs, a major class of antibiotics, by serine or metallo-β-lactamases (SBL or MBL) is one of the main mechanisms for antibiotic resistance. New Delhi Metallo-β-lactamase-1 (NDM-1), an acquired metallo-carbapenemase first reported in 2009, is currently considered one of the most clinically relevant targets for the development of β-lactam-β-lactamase inhibitor combinations active on NDM-producing clinical isolates. Identification of scaffolds that could be further rationally pharmacomodulated to design new and efficient NDM-1 inhibitors is thus urgently needed. Fragment-based drug discovery (FBDD) has become of great interest for the development of new drugs for the past few years and combination of several FBDD strategies, such as virtual and NMR screening, can reduce the drawbacks of each of them independently. Our methodology starting from a high throughput virtual screening on NDM-1 of a large library (more than 700,000 compounds) allowed, after slicing the hit molecules into fragments, to build a targeted library. These hit fragments were included in an in-house untargeted library fragments that was screened by Saturation Transfer Difference (STD) Nuclear Magnetic Resonance (NMR). 37 fragments were finally identified and used to establish a pharmacophore. 10 molecules based on these hit fragments were synthesized to validate our strategy. Indenone 89 that combined two identified fragments shows an inhibitory activity on NDM-1 with a K value of 4 μM.
β-内酰胺类药物(一种主要的抗生素)的水解由丝氨酸或金属β-内酰胺酶(SBL 或 MBL)催化,这是抗生素耐药性的主要机制之一。新德里金属β-内酰胺酶-1(NDM-1)是 2009 年首次报道的一种获得性金属碳青霉烯酶,目前被认为是开发对产 NDM 临床分离株具有活性的β-内酰胺-β-内酰胺酶抑制剂组合的最具临床相关性的靶标之一。因此,迫切需要鉴定可进一步合理药物修饰的支架,以设计新型高效的 NDM-1 抑制剂。片段药物发现(FBDD)在过去几年中成为开发新药的热点,结合几种 FBDD 策略,如虚拟筛选和 NMR 筛选,可以减少它们各自的缺点。我们的方法从对 NDM-1 的高通量虚拟筛选开始,筛选了一个大型文库(超过 70 万种化合物),然后将命中分子切成碎片,构建了一个靶向文库。这些命中片段被包含在一个内部的非靶向文库片段中,该文库片段通过饱和转移差异(STD)核磁共振(NMR)进行筛选。最终确定了 37 个片段,并用于建立药效团。根据这些命中片段合成了 10 种分子来验证我们的策略。结合了两个鉴定片段的茚酮 89 对 NDM-1 表现出 4 μM 的抑制活性。