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药物候选物再利用对抗 Epstein-Barr 病毒:虚拟筛选、对接计算、分子动力学和量子力学研究。

Repurposing of drug candidates against Epstein-Barr virus: Virtual screening, docking computations, molecular dynamics, and quantum mechanical study.

机构信息

Computational Chemistry Laboratory, Chemistry Department, Faculty of Science, Minia University, Minia, Egypt.

School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, South Africa.

出版信息

PLoS One. 2024 Nov 15;19(11):e0312100. doi: 10.1371/journal.pone.0312100. eCollection 2024.

Abstract

Epstein-Barr virus (EBV) was the first tumor virus identified in humans, and it is mostly linked to lymphomas and cancers of epithelial cells. Nevertheless, there is no FDA-licensed drug feasible for this ubiquitous EBV viral contagion. EBNA1 (Epstein-Barr nuclear antigen 1) plays several roles in the replication and transcriptional of latent gene expression of the EBV, making it an attractive druggable target for the treatment of EBV-related malignancies. The present study targets EBV viral reactivation and upkeep by inhibiting EBNA1 utilizing a drug-repurposing strategy. To hunt novel EBNA1 inhibitors, a SuperDRUG2 database (> 4,600 pharmaceutical ingredients) was virtually screened utilizing docking computations. In accordance with the estimated docking scores, the most promising drug candidates then underwent MDS (molecular dynamics simulations). Besides, the MM-GBSA approach was applied to estimate the binding affinities between the identified drug candidates and EBNA1. On the basis of MM-GBSA//200 ns MDS, bezitramide (SD000308), glyburide (SD001170), glisentide (SD001159), and glimepiride (SD001156) unveiled greater binding affinities towards EBNA1 compared to KWG, a reference inhibitor, with ΔGbinding values of -44.3, -44.0, -41.7, -40.2, and -32.4 kcal/mol, respectively. Per-residue decomposition analysis demonstrated that LYS477, ASN519, and LYS586 significantly interacted with the identified drug candidates within the EBNA1 binding pocket. Post-dynamic analyses also demonstrated high constancy of the identified drug candidates in complex with EBNA1 throughout 200 ns MDS. Ultimately, electrostatic potential and frontier molecular orbitals analyses were performed to estimate the chemical reactivity of the identified EBNA1 inhibitors. Considering the current outcomes, this study would be an adequate linchpin for forthcoming research associated with the inhibition of EBNA1; however, experimental assays are required to inspect the efficiency of these candidates.

摘要

EB 病毒(EBV)是人类发现的第一种肿瘤病毒,主要与淋巴瘤和上皮细胞癌有关。然而,目前还没有 FDA 批准的药物可用于治疗这种普遍存在的 EBV 病毒感染。EBNA1(EB 病毒核抗原 1)在 EBV 潜伏基因表达的复制和转录中发挥多种作用,使其成为治疗 EBV 相关恶性肿瘤的有吸引力的可成药靶点。本研究通过抑制 EBNA1 利用药物再利用策略靶向 EBV 病毒的再激活和维持。为了寻找新的 EBNA1 抑制剂,利用对接计算对 SuperDRUG2 数据库(>4600 种药物成分)进行了虚拟筛选。根据估计的对接分数,然后对最有前途的候选药物进行 MDS(分子动力学模拟)。此外,还应用 MM-GBSA 方法来估计鉴定的候选药物与 EBNA1 之间的结合亲和力。基于 MM-GBSA//200ns MDS,bezitramide(SD000308)、glyburide(SD001170)、glisentide(SD001159)和 glimepiride(SD001156)与参考抑制剂 KWG 相比,对 EBNA1 具有更高的结合亲和力,ΔGbinding 值分别为-44.3、-44.0、-41.7、-40.2 和-32.4 kcal/mol。残基分解分析表明,LYS477、ASN519 和 LYS586 与 EBNA1 结合口袋内的鉴定候选药物有显著相互作用。动态后分析还表明,在 200ns MDS 过程中,鉴定的候选药物与 EBNA1 复合物的稳定性很高。最后,进行了静电势和前沿分子轨道分析,以估算鉴定的 EBNA1 抑制剂的化学反应性。考虑到目前的结果,本研究将为今后与抑制 EBNA1 相关的研究提供一个充分的关键支撑;然而,需要进行实验测定来检查这些候选药物的效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7228/11567563/c098a4dd6440/pone.0312100.g001.jpg

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