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低数据情况下的药物发现:利用计算流程发现新型SARS-CoV-2 Nsp14甲基转移酶抑制剂

Drug Discovery in Low Data Regimes: Leveraging a Computational Pipeline for the Discovery of Novel SARS-CoV-2 Nsp14-MTase Inhibitors.

作者信息

Nigam AkshatKumar, Hurley Matthew F D, Li Fengling, Konkoľová Eva, Klíma Martin, Trylčová Jana, Pollice Robert, Çinaroğlu Süleyman Selim, Levin-Konigsberg Roni, Handjaya Jasemine, Schapira Matthieu, Chau Irene, Perveen Sumera, Ng Ho-Leung, Ümit Kaniskan H, Han Yulin, Singh Sukrit, Gorgulla Christoph, Kundaje Anshul, Jin Jian, Voelz Vincent A, Weber Jan, Nencka Radim, Boura Evzen, Vedadi Masoud, Aspuru-Guzik Alán

机构信息

Department of Computer Science, Stanford University.

Department of Genetics, Stanford University.

出版信息

bioRxiv. 2024 Jan 13:2023.10.03.560722. doi: 10.1101/2023.10.03.560722.

Abstract

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to significant global morbidity and mortality. A crucial viral protein, the non-structural protein 14 (nsp14), catalyzes the methylation of viral RNA and plays a critical role in viral genome replication and transcription. Due to the low mutation rate in the nsp region among various SARS-CoV-2 variants, nsp14 has emerged as a promising therapeutic target. However, discovering potential inhibitors remains a challenge. In this work, we introduce a computational pipeline for the rapid and efficient identification of potential nsp14 inhibitors by leveraging virtual screening and the NCI open compound collection, which contains 250,000 freely available molecules for researchers worldwide. The introduced pipeline provides a cost-effective and efficient approach for early-stage drug discovery by allowing researchers to evaluate promising molecules without incurring synthesis expenses. Our pipeline successfully identified seven promising candidates after experimentally validating only 40 compounds. Notably, we discovered NSC620333, a compound that exhibits a strong binding affinity to nsp14 with a dissociation constant of 427 ± 84 nM. In addition, we gained new insights into the structure and function of this protein through molecular dynamics simulations. We identified new conformational states of the protein and determined that residues Phe367, Tyr368, and Gln354 within the binding pocket serve as stabilizing residues for novel ligand interactions. We also found that metal coordination complexes are crucial for the overall function of the binding pocket. Lastly, we present the solved crystal structure of the nsp14-MTase complexed with SS148 (PDB:8BWU), a potent inhibitor of methyltransferase activity at the nanomolar level (IC value of 70 ± 6 nM). Our computational pipeline accurately predicted the binding pose of SS148, demonstrating its effectiveness and potential in accelerating drug discovery efforts against SARS-CoV-2 and other emerging viruses.

摘要

由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)病毒引起的2019冠状病毒病(COVID-19)大流行已导致全球大量发病和死亡。一种关键的病毒蛋白,非结构蛋白14(nsp14),催化病毒RNA的甲基化,并在病毒基因组复制和转录中起关键作用。由于不同SARS-CoV-2变体的nsp区域突变率较低,nsp14已成为一个有前景的治疗靶点。然而,发现潜在抑制剂仍然是一项挑战。在这项工作中,我们引入了一个计算流程,通过利用虚拟筛选和美国国立癌症研究所(NCI)开放化合物库(该库为全球研究人员提供250,000种可免费获取的分子)来快速有效地识别潜在的nsp14抑制剂。所引入的流程为早期药物发现提供了一种经济高效的方法,使研究人员能够在不产生合成费用的情况下评估有前景的分子。我们的流程在仅对40种化合物进行实验验证后成功鉴定出7种有前景的候选物。值得注意的是,我们发现了化合物NSC620333,它与nsp14表现出很强的结合亲和力,解离常数为427±84 nM。此外,我们通过分子动力学模拟对该蛋白的结构和功能有了新的认识。我们确定了该蛋白的新构象状态,并确定结合口袋内的苯丙氨酸367、酪氨酸368和谷氨酰胺354残基作为新型配体相互作用的稳定残基。我们还发现金属配位络合物对结合口袋的整体功能至关重要。最后,我们展示了与SS148复合的nsp14甲基转移酶的解析晶体结构(蛋白质数据银行编号:8BWU),SS148是一种在纳摩尔水平具有强效甲基转移酶活性抑制作用的抑制剂(IC值为70±6 nM)。我们的计算流程准确预测了SS148的结合姿态,证明了其在加速针对SARS-CoV-2和其他新兴病毒的药物发现工作中的有效性和潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75be/10798300/71f1f5fc8ee0/nihpp-2023.10.03.560722v3-f0001.jpg

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