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
大幅提高文件上传限制,最高150M (2024-4-1)

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
酷酷采萱完成签到,获得积分10
1秒前
细腻灯泡完成签到,获得积分10
1秒前
jo发布了新的文献求助10
3秒前
外向的书包完成签到,获得积分10
3秒前
科研通AI2S应助梦月采纳,获得10
3秒前
梧桐之泪完成签到 ,获得积分10
4秒前
aaaaa发布了新的文献求助10
4秒前
一念之间发布了新的文献求助30
4秒前
咖啡豆应助科研通管家采纳,获得10
5秒前
bkagyin应助科研通管家采纳,获得10
5秒前
还没想好昵称完成签到,获得积分10
5秒前
Ava应助科研通管家采纳,获得10
5秒前
HEIKU应助科研通管家采纳,获得10
5秒前
大模型应助科研通管家采纳,获得10
5秒前
wanci应助科研通管家采纳,获得10
5秒前
5秒前
研友_VZG7GZ应助科研通管家采纳,获得10
5秒前
赘婿应助科研通管家采纳,获得20
5秒前
orixero应助科研通管家采纳,获得10
5秒前
所所应助科研通管家采纳,获得10
5秒前
Singularity应助科研通管家采纳,获得20
5秒前
CodeCraft应助科研通管家采纳,获得10
5秒前
科研通AI2S应助科研通管家采纳,获得10
5秒前
HEIKU应助科研通管家采纳,获得10
5秒前
6秒前
HEIKU应助科研通管家采纳,获得30
6秒前
keeptg完成签到 ,获得积分10
6秒前
lotus777完成签到 ,获得积分10
6秒前
freddyyuu完成签到 ,获得积分10
6秒前
7秒前
NIKE112完成签到,获得积分10
8秒前
沐mu完成签到,获得积分10
8秒前
庸人自扰发布了新的文献求助10
9秒前
须臾完成签到,获得积分10
10秒前
bkagyin应助小梦要科研采纳,获得10
10秒前
sheryang完成签到,获得积分10
12秒前
梦月完成签到,获得积分10
12秒前
14秒前
16秒前
i_jueloa完成签到,获得积分10
16秒前
高分求助中
The Oxford Handbook of Social Cognition (Second Edition, 2024) 1050
Kinetics of the Esterification Between 2-[(4-hydroxybutoxy)carbonyl] Benzoic Acid with 1,4-Butanediol: Tetrabutyl Orthotitanate as Catalyst 1000
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Handbook of Qualitative Cross-Cultural Research Methods 600
Chen Hansheng: China’s Last Romantic Revolutionary 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3139963
求助须知:如何正确求助?哪些是违规求助? 2790850
关于积分的说明 7796798
捐赠科研通 2447191
什么是DOI,文献DOI怎么找? 1301745
科研通“疑难数据库(出版商)”最低求助积分说明 626313
版权声明 601194