Ray Rajdeep, Shenoy Gautham G, Kumar T N V Ganesh
Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Curr Comput Aided Drug Des. 2021;17(2):281-293. doi: 10.2174/1573409916666200302115432.
Tuberculosis is one of the leading causes of deaths due to infectious disease worldwide. There is an urgent need for developing new drugs due to the rising incidents of drug resistance. Previously, triazole molecules showing antitubercular activity, were reported. Various computational tools pave the way for a rational approach to understanding the structural importance of these compounds in inhibiting the growth of Mycobacterium Tuberculosis.
The aim of this study is to develop and compare two different QSAR models based on a set of previously reported triazole molecules and use the best one for gaining structural insights into those molecules.
In this current study, two separate models were made with CoMFA and CoMSIA descriptors based on a dataset of triazole molecules showing antitubercular activity. Several one dimensional (1D) descriptors were added to each of the models and the validation results and contour data generated from them were compared. The best model was analysed to give a detailed understanding of the triazole molecules and their role in the antitubercular activity.
The r, q, predicted r and SEP (Standard error of prediction) for the CoMFA model were 0.866, 0.573, 0.119 and 0.736 respectively and for the CoMSIA model, the r, q, predicted r and SEP were calculated to be 0.998, 0.634, 0.013 and 0.869 respectively. Although both the QSAR models produced acceptable internal and external validation scores, but the CoMSIA results were significantly better. The CoMSIA contours also provided a better match than CoMFA with most of the features of the active compound 30b. Hence, the CoMSIA model was chosen and its contours were explored for gaining structural insights into the triazole molecules.
The CoMSIA contours helped us understand the role of several atoms and groups of the triazole molecules in their biological activity. The possibilities for substitution in the triazole compounds that would enhance the activity were also analyzed. Thus, this study paves the way for designing new antitubercular drugs in future.
结核病是全球因传染病导致死亡的主要原因之一。由于耐药性事件不断增加,迫切需要开发新药。此前,有报道称三唑分子具有抗结核活性。各种计算工具为合理理解这些化合物在抑制结核分枝杆菌生长中的结构重要性铺平了道路。
本研究的目的是基于一组先前报道的三唑分子开发并比较两种不同的定量构效关系(QSAR)模型,并使用最佳模型深入了解这些分子的结构。
在本研究中,基于一组显示抗结核活性的三唑分子数据集,使用比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)描述符构建了两个独立的模型。将几个一维(1D)描述符添加到每个模型中,并比较它们产生的验证结果和等高线数据。对最佳模型进行分析,以详细了解三唑分子及其在抗结核活性中的作用。
CoMFA模型的r、q、预测r和预测标准误(SEP)分别为0.866、0.573、0.119和0.736,CoMSIA模型的r、q、预测r和SEP分别计算为0.998、0.634、0.013和0.869。虽然两个QSAR模型都产生了可接受的内部和外部验证分数,但CoMSIA结果明显更好。CoMSIA等高线也比CoMFA与活性化合物30b的大多数特征更匹配。因此,选择了CoMSIA模型,并探索其等高线以深入了解三唑分子的结构。
CoMSIA等高线帮助我们了解了三唑分子中几个原子和基团在其生物活性中的作用。还分析了三唑化合物中可能增强活性的取代可能性。因此,本研究为未来设计新的抗结核药物铺平了道路。