Pharmacoinformatics-based identification of potential bioactive compounds against Ebola virus protein VP24

埃博拉病毒 对接(动物) VP40型 自动停靠 病毒学 埃博拉病毒 病毒 药物发现 病毒蛋白 小分子 计算生物学 生物 医学 生物信息学 生物信息学 生物化学 基因 护理部
作者
Samuel K. Kwofie,Emmanuel Broni,Joshua Teye,Erasmus Quansah,Ibrahim Issah,Michael D. Wilson,Whelton A. Miller,Elvis K. Tiburu,Joseph Humphrey Kofi Bonney
出处
期刊:Computers in Biology and Medicine [Elsevier]
卷期号:113: 103414-103414 被引量:31
标识
DOI:10.1016/j.compbiomed.2019.103414
摘要

The impact of Ebola virus disease (EVD) is devastating with concomitant high fatalities. Currently, various drugs and vaccines are at different stages of development, corroborating the need to identify new therapeutic molecules. The VP24 protein of the Ebola virus (EBOV) plays a key role in the pathology and replication of the EVD. The VP24 protein interferes with the host immune response to viral infections and promotes nucleocapsid formation, thus making it a viable drug target. This study sought to identify putative lead compounds from the African flora with potential to inhibit the activity of the EBOV VP24 protein using pharmacoinformatics and molecular docking. An integrated library of 7675 natural products originating from Africa obtained from the AfroDB and NANPDB databases, as well as known inhibitors were screened against VP24 (PDB ID: 4M0Q) utilising AutoDock Vina after energy minimization using GROMACS. The top 19 compounds were physicochemically and pharmacologically profiled using ADMET Predictor™, SwissADME and DataWarrior. The mechanisms of binding between the molecules and EBOV VP24 were characterised using LigPlot+. The performance of the molecular docking was evaluated by generating a receiver operating characteristic (ROC) by screening known inhibitors and decoys against EBOV VP24. The prediction of activity spectra for substances (PASS) and machine learning-based Open Bayesian models were used to predict the anti-viral and anti-Ebola activity of the molecules, respectively. Four natural products, namely, ZINC000095486070, ZINC000003594643, ZINC000095486008 and sarcophine were found to be potential EBOV VP24-inhibitiory molecules. The molecular docking results showed that ZINC000095486070 had high binding affinity of −9.7 kcal/mol with EBOV VP24, which was greater than those of the known VP24-inhibitors used as standards in the study including Ouabain, Nilotinib, Clomiphene, Torimefene, Miglustat and BCX4430. The area under the curve of the generated ROC for evaluating the performance of the molecular docking was 0.77, which was considered acceptable. The predicted promising molecules were also validated using induced-fit docking with the receptor using Schrödinger and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The molecules had better binding mechanisms and were pharmacologically profiled to have plausible efficacies, negligible toxicity as well as suitable for designing anti-Ebola scaffolds. ZINC000095486008 and sarcophine (NANPDB135) were predicted to possess anti-viral activity, while ZINC000095486070 and ZINC000003594643 to be anti-Ebola compounds. The identified compounds are potential inhibitors worthy of further development as EBOV biotherapeutic agents. The scaffolds of the compounds could also serve as building blocks for designing novel Ebola inhibitors.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
共享精神应助早早采纳,获得10
1秒前
脑洞疼应助早早采纳,获得10
1秒前
今后应助早早采纳,获得10
1秒前
丘比特应助早早采纳,获得10
1秒前
今后应助早早采纳,获得10
1秒前
情怀应助早早采纳,获得10
1秒前
Orange应助早早采纳,获得10
2秒前
汉堡包应助早早采纳,获得10
2秒前
小二郎应助早早采纳,获得10
2秒前
完美世界应助早早采纳,获得10
2秒前
Wynter发布了新的文献求助10
2秒前
赴汤蹈火鸡面完成签到 ,获得积分10
2秒前
慕青应助非也的非也采纳,获得10
2秒前
xhc发布了新的文献求助10
4秒前
4秒前
科研小白完成签到,获得积分10
5秒前
iieee发布了新的文献求助10
5秒前
Ava应助杜du采纳,获得10
6秒前
7秒前
wanci应助YJH采纳,获得10
8秒前
11秒前
CodeCraft应助尹恩惠采纳,获得30
12秒前
MORNING发布了新的文献求助10
12秒前
非也的非也完成签到,获得积分20
12秒前
13秒前
SciGPT应助星星采纳,获得10
13秒前
1282941496完成签到,获得积分10
13秒前
doni发布了新的文献求助10
14秒前
Amir_Sc1完成签到,获得积分10
14秒前
ttcc发布了新的文献求助10
15秒前
15秒前
15秒前
16秒前
混分的三百块完成签到,获得积分10
16秒前
iieee完成签到,获得积分20
18秒前
小明完成签到,获得积分0
19秒前
凉皮儿发布了新的文献求助10
19秒前
21秒前
YJH发布了新的文献求助10
21秒前
汉堡包应助iieee采纳,获得10
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Fermented Coffee Market 2000
微纳米加工技术及其应用 500
Constitutional and Administrative Law 500
PARLOC2001: The update of loss containment data for offshore pipelines 500
Critical Thinking: Tools for Taking Charge of Your Learning and Your Life 4th Edition 500
Vertebrate Palaeontology, 5th Edition 420
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5289331
求助须知:如何正确求助?哪些是违规求助? 4441004
关于积分的说明 13826177
捐赠科研通 4323262
什么是DOI,文献DOI怎么找? 2373137
邀请新用户注册赠送积分活动 1368528
关于科研通互助平台的介绍 1332411