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基于计算机的减法蛋白质组学和分子对接方法用于鉴定针对D39菌株的新型抑制剂

In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against Strain D39.

作者信息

Shami Ashwag, Alharbi Nada K, Al-Saeed Fatimah A, Alsaegh Aiman A, Al Syaad Khalid M, Abd El-Rahim Ibrahim H A, Mostafa Yasser Sabry, Ahmed Ahmed Ezzat

机构信息

Department of Biology, College of Sciences, Princess Nourah Bint Abdulrahman University, Riyadh 11617, Saudi Arabia.

Research Centre, Department of Biology, College of Science, King Khalid University, Abha 61413, Saudi Arabia.

出版信息

Life (Basel). 2023 May 4;13(5):1128. doi: 10.3390/life13051128.

Abstract

is a notorious Gram-positive pathogen present asymptomatically in the nasophayrnx of humans. According to the World Health Organization (W.H.O), pneumococcus causes approximately one million deaths yearly. Antibiotic resistance in is raising considerable concern around the world. There is an immediate need to address the major issues that have arisen as a result of persistent infections caused by . In the present study, subtractive proteomics was used in which the entire proteome of the pathogen consisting of 1947 proteins is effectively decreased to a finite number of possible targets. Various kinds of bioinformatics tools and software were applied for the discovery of novel inhibitors. The CD-HIT analysis revealed 1887 non-redundant sequences from the entire proteome. These non-redundant proteins were submitted to the BLASTp against the human proteome and 1423 proteins were screened as non-homologous. Further, databases of essential genes (DEGG) and J browser identified almost 171 essential proteins. Moreover, non-homologous, essential proteins were subjected in KEGG Pathway Database which shortlisted six unique proteins. In addition, the subcellular localization of these unique proteins was checked and cytoplasmic proteins were chosen for the druggability analysis, which resulted in three proteins, namely DNA binding response regulator (SPD_1085), UDP-N-acetylmuramate-L-alanine Ligase (SPD_1349) and RNA polymerase sigma factor (SPD_0958), which can act as a promising potent drug candidate to limit the toxicity caused by . The 3D structures of these proteins were predicted by Swiss Model, utilizing the homology modeling approach. Later, molecular docking by PyRx software 0.8 version was used to screen a library of phytochemicals retrieved from PubChem and ZINC databases and already approved drugs from DrugBank database against novel druggable targets to check their binding affinity with receptor proteins. The top two molecules from each receptor protein were selected based on the binding affinity, RMSD value, and the highest conformation. Finally, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses were carried out by utilizing the SWISS ADME and Protox tools. This research supported the discovery of cost-effective drugs against . However, more in vivo/in vitro research should be conducted on these targets to investigate their pharmacological efficacy and their function as efficient inhibitors.

摘要

是一种臭名昭著的革兰氏阳性病原体,无症状地存在于人类鼻咽部。根据世界卫生组织(WHO)的数据,肺炎球菌每年导致约100万人死亡。其抗生素耐药性在全球引起了相当大的关注。迫切需要解决因肺炎球菌持续感染而出现的主要问题。在本研究中,采用了消减蛋白质组学方法,其中由1947种蛋白质组成的病原体全蛋白质组被有效地减少到有限数量的可能靶点。应用了各种生物信息学工具和软件来发现新型抑制剂。CD-HIT分析从全蛋白质组中揭示了1887个非冗余序列。这些非冗余蛋白质与人类蛋白质组进行BLASTp比对,筛选出1423个非同源蛋白质。此外,必需基因数据库(DEGG)和J浏览器确定了近171个必需蛋白质。此外,将非同源的必需蛋白质提交到KEGG通路数据库,筛选出六种独特蛋白质。此外,检查了这些独特蛋白质的亚细胞定位,并选择细胞质蛋白质进行成药分析,结果得到三种蛋白质,即DNA结合反应调节因子(SPD_1085)、UDP-N-乙酰胞壁酸-L-丙氨酸连接酶(SPD_1349)和RNA聚合酶sigma因子(SPD_0958),它们可作为有前景的有效药物候选物,以限制肺炎球菌引起的毒性。利用同源建模方法,通过瑞士模型预测了这些蛋白质的三维结构。随后,使用PyRx软件0.8版本进行分子对接,以筛选从PubChem和ZINC数据库中检索到的植物化学物质库以及来自DrugBank数据库的已批准药物,针对新型可成药靶点检查它们与受体蛋白的结合亲和力。根据结合亲和力、RMSD值和最高构象,从每个受体蛋白中选择前两个分子。最后,利用SWISS ADME和Protox工具进行吸收、分布、代谢、排泄和毒性(ADMET)分析。本研究支持发现针对肺炎球菌的经济有效的药物。然而,应对这些靶点进行更多的体内/体外研究,以研究它们的药理功效及其作为有效抑制剂的功能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8f8/10224061/7ad39e35dabb/life-13-01128-g001.jpg

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