Sharma Avantika, Rishi Praveen, Gautam Ankur, Gautam Vikas, Tewari Rupinder
Department of Microbial Biotechnology, Panjab University, Chandigarh, 160014, India.
Department of Microbiology, Panjab University, Chandigarh, 160014, India.
J Microbiol Biotechnol. 2015 Oct 2. doi: 10.4014/jmb.1508.08064.
To control the infection caused by a multi-drug resistant bacterial pathogen, Acinetobacter baumannii, antimicrobial peptides (AMPs) are being considered as a viable option because of their broad range of antimicrobial activity and non-specific mode of action. However, high cost of synthesis of AMPs has led to the development of several computational tools to predict the biological and physicochemical properties of AMPs. In the present study, a comparative analysis has been done between in vitro activity of seven anti-Acinetobacter α-helical peptides with in silico prediction tools for studying antimicrobial related properties of AMPs. Database of Antimicrobial Activity and Structure of Peptides (DBAASP) and two algorithms, Support Vector Machine (SVM) and Random Forest (RF) of another server, Collection of Antimicrobial Peptides (CAMP) were compared with in vitro results of AMP/non-AMP nature of anti-Acinetobacter peptides. The results of the influence of biophysical properties of peptides on their antimicrobial activity suggested that amphipathicity is more important than spatial arrangement and charge of α-helical peptides. No correlation was observed between the MIC50 values and the hydropathy of AMPs. Based on the present study, it is suggested that with further refinements in the available servers/algorithms for correctly predicting the antimicrobial nature of the peptides, in silico tools can be used to assist the development of new antimicrobial agents.
为了控制由多重耐药细菌病原体鲍曼不动杆菌引起的感染，抗菌肽（AMPs）因其广泛的抗菌活性和非特异性作用方式而被视为一种可行的选择。然而，抗菌肽合成成本高昂，这促使人们开发了多种计算工具来预测抗菌肽的生物学和物理化学性质。在本研究中，对七种抗鲍曼不动杆菌α-螺旋肽的体外活性与用于研究抗菌肽抗菌相关性质的计算机预测工具进行了比较分析。将抗菌肽活性与结构数据库（DBAASP）以及另一服务器抗菌肽数据库（CAMP）中的两种算法，即支持向量机（SVM）和随机森林（RF），与抗鲍曼不动杆菌肽的AMP/非AMP性质的体外结果进行了比较。肽的生物物理性质对其抗菌活性影响的结果表明，两亲性比α-螺旋肽的空间排列和电荷更为重要。未观察到MIC50值与抗菌肽亲水性之间的相关性。基于本研究，建议随着现有服务器/算法在正确预测肽的抗菌性质方面的进一步完善，计算机工具可用于辅助新型抗菌剂的开发。
