基于机器学习方法的丙型肝炎病毒聚合酶NS5B非核苷抑制剂的定量构效关系研究

对89 个苯并异噻唑和苯并噻嗪类丙型肝炎病毒(HCV) NS5B聚合酶非核苷抑制剂进行了定量构效关系(QSAR)研究. 采用遗传算法组合偏最小二乘(GA-PLS)和线性逐步回归分析(LSRA)两种特征选择方法选择最优描述符子集, 然后建立多元线性回归和偏最小二乘线性回归模型. 并首次尝试使用遗传算法耦合支持向量机方法(GA-SVM)对两种特征选择方法所选的描述符子集分别建立非线性支持向量机回归模型. 三种机器学习方法所建模型均得到比较满意的预测效果. 采用LSRA所选的6 个描述符建立的三个QSAR模型对于测试集的相关系数为0.958-0.962, GA-SVM法给出最好的预测精度(0.962). 采用GA-PLS所选的7个描述符建立的三个QSAR模型对于测试集的相关系数为0.918-0.960, 偏最小二乘回归模型的结果最好(0.960). 本工作提供了一种有效的方法来预测丙型肝炎病毒抑制剂的生物活性, 该方法也可以扩展到其他类似的定量构效关系研究领域.     

Cheminformatics study of some indole compounds through QSAR modeling,ADME prediction,molecular docking,and molecular dynamic simulation to identify novel inhibitors of HCV NS5B protease

The hepatitis C virus is a viral disease that causes cirrhosis and hepatocellular carcinoma in the liver. Since the virus's discovery, significant therapeutic advances have been made. Notwithstanding, its upsurge necessitates the development of novel approaches to combating this disease. Recent studies have seen a rise in the value of plant compounds in the establishment of novel, efficient, and cost-efficient anti-HCV medications. These factors have motivated us to continuously search for novel, potent anti-HCV inhibitors, ideally with mechanisms different from those used in conventional medicine. Several filtrations processes including ADMET, molecular docking, and molecular dynamics (MD) simulation were used to choose potent hits from plant molecules deposited in the PubChem database. The binding kinetics were explored using MD simulation studies performed for 100 ns using GROMACS-2018.1. which was done to validate and supplement the findings of the virtual screening. The selected hits (with PubChem CID of 3,560,948 and 4,754,183) had preferable molecular traits that suggested they might work well as HCV inhibitors and are term as effective potential hits. The MD study confirmed the stability of the identified hit with a binding energy of ?111.724 ( ± 81.668) kj/mol and mechanisms different from the FDA-approved drug (sofosbuvir) used as a reference with a binding energy of ?106.132 ( ± 78.008) kj/mol. This approach could aid in the establishment and identification of novel inhibitors in pharmaceutical discovery. Experimental assessments could indeed ascertain as to if the identified molecule can be employed as an anti-HCV drug to address the ailment and confirm the reliability of our in-silico studies.     

A 21st century technique for food control: Electronic noses

This work examines the main features of modern electronic noses (e-noses) and their most important applications in food control in this new century. The three components of an electronic nose (sample handling system, detection system, and data processing system) are described. Special attention is devoted to the promising mass spectrometry based e-noses, due to their advantages over the more classical gas sensors. Applications described include process monitoring, shelf-life investigation, freshness evaluation, authenticity assessment, as well as other general aspects of the utilization of electronic noses in food control. Finally, some interesting remarks concerning the strengths and weaknesses of electronic noses in food control are also mentioned.