Discovery of Novel and Potent Inhibitors Against Mutational Variants of IDH1 Protein for Glioma Therapy: A Fragment-Based Approach

异柠檬酸脱氢酶 IDH1 生物信息学 计算生物学 胶质瘤 药物发现 药品 化学 生物 基因 生物化学 药理学 遗传学 突变体
作者
Poornimaa Murali,K. Ramanathan
出处
期刊:Journal of computational biophysics and chemistry [World Scientific]
卷期号:22 (01): 43-61 被引量:1
标识
DOI:10.1142/s2737416523500023
摘要

Somatic mutations in the isoenzymes of isocitrate dehydrogenases (IDHs) account for the pathogenesis of various malignancies including gliomas. To date, ivosidenib is the only FDA-approved drug candidate widely used to target mutated isocitrate dehydrogenase 1 (mIDH1). However, the impotence of the existing drug to evade the blood barrier remains an obstacle to harness ivosidenib as therapeutics against glioma. Thus, in this study, we elucidate a fragment-based drug discovery strategy to design novel lead molecules against the mIDH1 protein. Initially, a fragment library was constructed using 27 known mIDH1 inhibitors from the literature. The vast chemical classes of constructed library consisting of 1109 fragments were then used for breeding. A total of 18,000 breed compounds were generated and the resultant compounds were scrutinized based on the breed score ([Formula: see text]) and Tanimoto coefficient ([Formula: see text]). The binding affinity and the energetics of the resultant molecules (2069) were investigated using molecular docking and MM-GBSA calculations. Eventually, the compounds with higher affinity were included in the mutational analysis incorporating the second site mutations namely IDH1 S280F and IDH1 R119P . The bioavailability analysis and toxicity profiling were carried out for screened hybrid molecules. The pipeline of the integrated in-silico approach identified hybrid 209, hybrid 237 and hybrid 504 as the drug-like candidates against the mutational variants of mIDH1 protein. Interestingly, all three compounds exhibited greater binding affinity and better brain penetrating capability. The machine learning-based anti-cancerous sensitivity prediction tool affirmed the inhibitory effect of the resultant hits against various glioma cell lines. In the end, the structural stability of the screened molecules was examined using the molecular dynamic simulation study for a stipulated time of 100[Formula: see text]ns. Indeed, this evidence speculates that the identified hybrid molecules could serve as important leads for the management of glioma in the near future.
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