Synthesis and binary QSAR study of antitubercular quinolylhydrazides

Recursive Partitioning Analysis and Anti-Tubercular Screening of 3- Aminopyrazine-2-Carbohydrazide Derivatives

Background:

Treating tuberculosis is a challenge due to the development of drug resistance. Hence, it is imperative to develop novel leads having high potency and efficacy to curb drug resistance.

Methods:

The present research work is focused on microwave-assisted synthesis of novel twenty-six 3-amino-N’-benzylidenepyrazine-2-carbohydrazide derivatives (3a-z), where, lyophilization technique was used for isolation of the major intermediate, 3-aminopyrazin-2-carbohydrazide. All synthesized compounds were subjected for anti-tubercular screening against Mycobacterium tuberculosis H37Ra by using XTT Reduction Menadione Assay (XRMA) protocol.

Results:

Out of 26 synthesized compounds, four N’-substitutedbenzaldehyde-3-amino-pyrazine-2- carbohydrazide derivatives viz. 3i, 3j 3v and 3z showed significant activity against M. tuberculosis H37Ra. The compounds 3i, 3j, 3v and 3z showed 99, 98, 92 and 87 % inhibition respectively as compared to 94% inhibition shown by the standard drug rifampicin. The MIC and IC50 values were in the range of 24.3-110 and 5.9-20.8 µg/ml respectively.

Conclusion:

A classification model called Recursive Partitioning (RP) based on binary Quantitative Structure-Activity Relationship (QSAR) was derived for the establishment of structure-activity relationship (SAR). The predictions derived on the basis of RP model were found to be in agreement with anti-tubercular screening data.

Value of p-Value

The goal of this manuscript is to discuss important aspects of external validation of classification and category Quantitative Structure - Activity/Property/Toxicity Relationship QS/A/P/T/R models that to the best of author's knowledge are not addressed in publications. Statistical significance (in terms of p-value) and accuracy of prediction (in terms of Correct Classification Rate (CCR)) of external validation set compounds are among most important characteristics of the models. We assert that in most cases the models built for classification or category response variable should be statistically significant and predictive for each class or category. We show that three thresholds of the number of compounds in each class or category of the external validation sets should be satisfied. 1) The p-value criterion can never be satisfied, if the number of compounds is below the first threshold. 2) If the number of compounds is between the first and the second thresholds, p-value criterion should be used. 3) If it is higher than the third threshold, classification or category accuracy criterion should be used. 4) If the number of compounds is between second and third thresholds, either one or the other criterion should be used depending on the value of p-value. 5) When the number of compounds in the class approaches infinity, the maximum relative error of prediction approaches the relative expected error. The results are of interest in other areas of multidimensional data analysis.

Synthesis, biological evaluation and molecular docking study of some novel indole and pyridine based 1,3,4-oxadiazole derivatives as potential antitubercular agents

A series of indole and pyridine based 1,3,4-oxadiazole derivatives 5a-t were synthesized and evaluated for their in vitro antitubercular activity against Mycobacterium tuberculosis H37Ra (MTB) and Mycobacterium bovis BCG both in active and dormant state. Compounds 5b, 5e, 5g and 5q exhibited very good antitubercular activity. All the newly synthesized compounds 5a-t were further evaluated for anti-proliferative activity against HeLa, A549 and PANC-1 cell lines using modified MTT assay and found to be noncytotoxic. On the basis of cytotoxicity and MIC values against Mycobacterium bovis BCG, selectivity index (SI) of most active compounds 5b, 5e, 5g and 5q was calculated (SI=GI50/MIC) in active and dormant state. Compounds 5b, 5e and 5g demonstrated SI values ⩾10 against all three cell lines and were found to safe for advance screening. Compounds 5a-t were further screened for their antibacterial activity against four bacteria strains to assess their selectivity towards MTB. In addition, the molecular docking studies revealed the binding modes of these compounds in active site of enoyl reductase (InhA), which in turn helped to establish a structural basis of inhibition of mycobacteria. The potency, low cytotoxicity and selectivity of these compounds make them valid lead compounds for further optimization.

Design, Synthesis, and Antimycobacterial Activity of Novel Theophylline-7-Acetic Acid Derivatives With Amino Acid Moieties

The theophylline-7-acetic acid (7-TAA) scaffold is a promising novel lead compound for antimycobacterial activity. Here, we derive a model for antitubercular activity prediction based on 14 7-TAA derivatives with amino acid moieties and their methyl esters. The model is applied to a combinatorial library, consisting of 40 amino acid and methyl ester derivatives of 7-TAA. The best three predicted compounds are synthesized and tested against Mycobacterium tuberculosis H37Rv. All of them are stable, non-toxic against human cells and show antimycobacterial activity in the nanomolar range being 60 times more active than ethambutol.

Prediction on the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase based on gene expression programming

Quantitative structure-activity relationships (QSAR) were developed to predict the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase via heuristic method (HM) and gene expression programming (GEP). The descriptors of 33 pyrrolidine derivatives were calculated by the software CODESSA, which can calculate quantum chemical, topological, geometrical, constitutional, and electrostatic descriptors. HM was also used for the preselection of 5 appropriate molecular descriptors. Linear and nonlinear QSAR models were developed based on the HM and GEP separately and two prediction models lead to a good correlation coefficient (R²) of 0.93 and 0.94. The two QSAR models are useful in predicting the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase during the discovery of new anticancer drugs and providing theory information for studying the new drugs.

Design of novel camphane-based derivatives with antimycobacterial activity

Although tuberculosis (TB) continues to be one of the leading infectious disease killers globally, it is curable and preventable. Despite the existence of safe, well tolerated and effective drugs used in the TB treatment, the interest in new entities, combinations and regimens increases during the last 10 years. Recently, we reported for a new class of anti-TB agents - camphane-based derivatives with nanomolar activity against Mycobacterium tuberculosis strains. The quantitative structure-activity relationship (QSAR) study on 12 compounds revealed several structural requirements for antimycobacterial activity: two hydrogen bond donors, two or three rings and no large branched substituents. Here, we describe the design of a set of nine novel camphane-based derivatives following these requirements. The compounds were synthesized and tested against M. tuberculosis strain H37Rv. Four of them showed activities in the nanomolar range, significantly higher than the activities in the initial set. The QSAR study based on all 21 derivatives pointed to two main structural requirements for anti-TB activity: two hydrogen bond donors and a side chain with aromatic ring.