Combating the Threat of Anthrax: A Quantitative Structure−Activity Relationship Approach

Molecular modeling toward selective inhibitors of dihydrofolate reductase from the biological warfare agent Bacillus anthracis

In the present work, we applied docking and molecular dynamics techniques to study 11 compounds inside the enzymes dihydrofolate reductase (DHFR) from the biological warfare agent Bacillus anthracis (BaDHFR) and Homo sapiens sapiens (HssDHFR). Six of these compounds were selected for a study with the mutant BaF96IDHFR. Our results corroborated with experimental data and allowed the proposition of a new molecule with potential activity and better selectivity for BaDHFR.

Synthesis and biological evaluation of new rhodanine analogues bearing 2-chloroquinoline and benzo[h]quinoline scaffolds as anticancer agents

Several rhodanine derivatives (9-39) were synthesized for evaluation of their potential as anticancer agents. Villsmeier cyclization to synthesize aza-aromatic aldehydes, rhodanine derivatives preparation and Knoevenagel type of condensation between the rhodanines and aza-aromatic aldehydes are key steps used for the synthesis of 31 compounds. In vitro antiproliferative activity of the synthesized rhodanine derivatives (9-39) was studied on a panel of six human tumor cell lines viz. HGC, MNK-74, MCF-7, MDAMB-231, DU-145 and PC-3 cell lines. Some of the compounds were capable of inhibiting the proliferation of cancer cell lines at a micromolar concentration. Six compounds are found to be potent against HGC cell lines; compound 15 is found to be active against HGC - Gastric, MCF7 - Breast Cancer and DU145 - Prostate Cancer cell lines; compound 39 is potent against MNK-74; four compounds are found to be potent against MCF-7 cell lines; three compounds are active against MDAMB-231; nine compounds are found to be potent against DU-145; three compounds are active against PC-3 cell lines. These compounds constitute a promising starting point for the development of novel and more potent anticancer agents in future.

Hybrid-genetic algorithm based descriptor optimization and QSAR models for predicting the biological activity of Tipranavir analogs for HIV protease inhibition

The prediction of biological activity of a chemical compound from its structural features plays an important role in drug design. In this paper, we discuss the quantitative structure activity relationship (QSAR) prediction models developed on a dataset of 170 HIV protease enzyme inhibitors. Various chemical descriptors that encode hydrophobic, topological, geometrical and electronic properties are calculated to represent the structures of the molecules in the dataset. We use the hybrid-GA (genetic algorithm) optimization technique for descriptor space reduction. The linear multiple regression analysis (MLR), correlation-based feature selection (CFS), non-linear decision tree (DT), and artificial neural network (ANN) approaches are used as fitness functions. The selected descriptors represent the overall descriptor space and account well for the binding nature of the considered dataset. These selected features are also human interpretable and can be used to explain the interactions between a drug molecule and its receptor protein (HIV protease). The selected descriptors are then used for developing the QSAR prediction models by using the MLR, DT and ANN approaches. These models are discussed, analyzed and compared to validate and test their performance for this dataset. All three approaches yield the QSAR models with good prediction performance. The models developed by DT and ANN are comparable and have better prediction than the MLR model. For ANN model, weight analysis is carried out to analyze the role of various descriptors in activity prediction. All the prediction models point towards the involvement of hydrophobic interactions. These models can be useful for predicting the biological activity of new untested HIV protease inhibitors and virtual screening for identifying new lead compounds.

Medical countermeasures to protect humans from anthrax bioterrorism

The deliberate dissemination of Bacillus anthracis spores via the US mail system in 2001 confirmed their potential use as a biological weapon for mass human casualties. This dramatically highlighted the need for specific medical countermeasures to enable the authorities to protect individuals from a future bioterrorism attack. Although vaccination appears to be the most effective and economical form of mass protection, current vaccines have significant drawbacks that justify the immense research effort to develop improved treatment modalities. After eight years and an expenditure of more than $50 billion, only marginal progress has been made in developing effective therapeutics. This article summarizes the most important medical countermeasures that have mostly been developed since the 2001 events, and highlights current problems and possible avenues for future research.

Overcoming tumor drug resistance with C2-modified 10-deacetyl-7-propionyl cephalomannines: a QSAR study

The microtubule-stabilizing taxanes such as paclitaxel and docetaxel are the two most important anticancer drugs currently used in clinics for the treatment of various types of cancers. However, the major common drawbacks of these two drugs are drug resistance, neurotoxicity, substrate for drug transporter P-gp, cross-resistance with other chemotherapeutic agents, low oral bioavailability, and no penetration in the blood-brain barrier (BBB). These limitations have led to the search for new taxane derivatives with improved biological activity. In the present paper, we discuss the quantitative structure-activity relationship (QSAR) studies on a series of C2-modified 10-deacetyl-7-propionyl cephalomannines (IV) with respect to their binding affinities toward beta-tubulin and cytotoxic activities against both drug-sensitive and drug-resistant tumor cells, in which resistance is mediated through either P-gp overexpression or beta-tubulin mutation mechanisms, by the formulation of five QSARs. Hydrophobicity and molar refractivity of the substituents (pi(X) and MR(X)) are found to be the most important determinants for the activity. Parabolic correlations in terms of MR(X) (eqs 2 and 4 ) are encouraging examples in which the optimum values of MR(X) are well-defined. We believe that these two QSAR models may prove to be adequate predictive models that can help to provide guidance in design and synthesis, and subsequently yield very specific cephalomannine derivatives (IV) that may have high biological activities. On the basis of these two QSAR models, 10 cephalomannine analogues (IV-21 to IV-30) are suggested as potential synthetic targets. Internal (cross-validation (q(2)), quality factor (Q), Fischer statistics (F), and Y-randomization) and external validation tests have validated all the QSAR models.

Taxane analogues against lung cancer: a quantitative structure-activity relationship study

Lung cancer is the second most common cancer in both men (after prostate cancer) and women (after breast cancer). The microtubule-stabilizing taxane such as docetaxel is the only agent currently approved for both first- and second-line treatment of advanced non-small cell lung cancer. Although docetaxel has made significant progress in the treatment of lung cancers either using alone or in combination with various novel targeted agents, its use often results in various undesired side-effects. These limitations have led to the search for new taxane derivatives with fewer side-effects, superior pharmacological properties, and improved anticancer activity to maximize the induced benefits for lung cancer patients. Herein, four series of taxane derivatives were used to correlate their inhibitory activities against lung cancer cells with hydrophobic and steric descriptors to gain a better understanding of their chemical-biological interactions. A parabolic correlation with MR(Y) is the most encouraging example, in which the optimum value of this parameter is well defined. On the basis of this quantitative structure-activity relationship model, six compounds (3-23 to 3-28) are suggested as potential synthetic targets. Internal (cross-validation (q(2)), quality factor (Q), Fischer statistics (F ) and Y-randomization) and external validation tests have validated all the quantitative structure-activity relationship models.

Structure-activity relationship studies of a novel series of anthrax lethal factor inhibitors

We report on the identification of a novel small molecule inhibitor of anthrax lethal factor using a high-throughput screening approach. Guided by molecular docking studies, we carried out structure-activity relationship (SAR) studies and evaluated activity and selectivity of most promising compounds in in vitro enzyme inhibition assays and cellular assays. Selected compounds were further analyzed for their in vitro ADME properties, which allowed us to select two compounds for further preliminary in vivo efficacy studies. The data provided represents the basis for further pharmacology and medicinal chemistry optimizations that could result in novel anti-anthrax therapies.