Bioinformatics Research Group, Biotechnology Department, University of the Western Cape, Cape Town, 7535, South Africa.
Environmental Biotechnology Laboratory, Biotechnology Department, University of the Western Cape, Cape Town, 7535, South Africa.
BMC Mol Cell Biol. 2020 Nov 20;21(1):82. doi: 10.1186/s12860-020-00328-4.
Pneumonia ranks as one of the main infectious sources of mortality among kids under 5 years of age, killing 2500 a day; late research has additionally demonstrated that mortality is higher in the elderly. A few biomarkers, which up to this point have been distinguished for its determination lack specificity, as these biomarkers fail to build up a differentiation between pneumonia and other related diseases, for example, pulmonary tuberculosis and Human Immunodeficiency Infection (HIV). There is an inclusive global consensus of an improved comprehension of the utilization of new biomarkers, which are delivered in light of pneumonia infection for precision identification to defeat these previously mentioned constraints. Antimicrobial peptides (AMPs) have been demonstrated to be promising remedial specialists against numerous illnesses. This research work sought to identify AMPs as biomarkers for three bacterial pneumonia pathogens such as Streptococcus pneumoniae, Klebsiella pneumoniae, Acinetobacter baumannii using in silico technology. Hidden Markov Models (HMMER) was used to identify putative anti-bacterial pneumonia AMPs against the identified receptor proteins of Streptococcus pneumoniae, Klebsiella pneumoniae, and Acinetobacter baumannii. The physicochemical parameters of these putative AMPs were computed and their 3-D structures were predicted using I-TASSER. These AMPs were subsequently subjected to docking interaction analysis against the identified bacterial pneumonia pathogen proteins using PATCHDOCK.
The in silico results showed 18 antibacterial AMPs which were ranked based on their E values with significant physicochemical parameters in conformity with known experimentally validated AMPs. The AMPs also bound the pneumonia receptors of their respective pathogens sensitively at the extracellular regions.
The propensity of these AMPs to bind pneumonia pathogens proteins justifies that they would be potential applicant biomarkers for the recognizable detection of these bacterial pathogens in a point-of-care POC pneumonia diagnostics. The high sensitivity, accuracy, and specificity of the AMPs likewise justify the utilization of HMMER in the design and discovery of AMPs for disease diagnostics and therapeutics.
肺炎是导致 5 岁以下儿童死亡的主要感染源之一,每天有 2500 名儿童因此死亡;最近的研究还表明,老年人的死亡率更高。一些生物标志物已经被确定,但是这些生物标志物缺乏特异性,因为它们无法区分肺炎和其他相关疾病,例如肺结核和人类免疫缺陷病毒(HIV)感染。人们普遍认识到需要更好地理解利用新的生物标志物,这些标志物是基于肺炎感染而确定的,可以更准确地识别这些先前存在的限制。抗菌肽(AMPs)已被证明是对抗多种疾病的有前途的治疗专家。本研究旨在使用计算技术鉴定肺炎链球菌、肺炎克雷伯菌和鲍曼不动杆菌三种细菌性肺炎病原体的 AMPs 作为生物标志物。隐马尔可夫模型(HMMER)用于鉴定针对肺炎链球菌、肺炎克雷伯菌和鲍曼不动杆菌已识别受体蛋白的潜在抗肺炎 AMPs。计算了这些潜在 AMPs 的物理化学参数,并使用 I-TASSER 预测了它们的 3-D 结构。随后使用 PATCHDOCK 将这些 AMPs 针对已识别的细菌性肺炎病原体蛋白进行对接相互作用分析。
计算结果显示了 18 种具有抗菌活性的 AMPs,它们根据 E 值进行了排序,并且具有与已知经实验验证的 AMPs 一致的显著物理化学参数。这些 AMPs 还在其各自病原体的肺炎受体的细胞外区域敏感地结合。
这些 AMPs 结合肺炎病原体蛋白的倾向证明,它们将是用于在即时护理(POC)肺炎诊断中识别这些细菌病原体的潜在候选生物标志物。AMP 具有高灵敏度、准确性和特异性,这也证明了 HMMER 在疾病诊断和治疗中用于 AMP 设计和发现的适用性。