3D-QSAR studies on triclosan derivatives as Plasmodium falciparum enoyl acyl carrier reductase inhibitors

Structure-Based Design and Pharmacophore-Based Virtual Screening of Combinatorial Library of Triclosan Analogues Active against Enoyl-Acyl Carrier Protein Reductase of Plasmodium falciparum with Favourable ADME Profiles

Cost-effective therapy of neglected and tropical diseases such as malaria requires everlasting drug discovery efforts due to the rapidly emerging drug resistance of the plasmodium parasite. We have carried out computational design of new inhibitors of the enoyl-acyl carrier protein reductase (ENR) of Plasmodium falciparum (PfENR) using computer-aided combinatorial and pharmacophore-based molecular design. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) complexation QSAR model was developed for triclosan-based inhibitors (TCL) and a significant correlation was established between the calculated relative Gibbs free energies of complex formation (∆∆Gcom) between PfENR and TCL and the observed inhibitory potencies of the enzyme (IC50exp) for a training set of 20 known TCL analogues. Validation of the predictive power of the MM-PBSA QSAR model was carried out with the generation of 3D QSAR pharmacophore (PH4). We obtained a reasonable correlation between the relative Gibbs free energy of complex formation ∆∆Gcom and IC50exp values, which explained approximately 95% of the PfENR inhibition data: pIC50exp=-0.0544×∆∆Gcom+6.9336,R2=0.95. A similar agreement was established for the PH4 pharmacophore model of the PfENR inhibition (pIC50exp=0.9754×pIC50pre+0.1596, R2=0.98). Analysis of enzyme-inhibitor binding site interactions suggested suitable building blocks to be used in a virtual combinatorial library of 33,480 TCL analogues. Structural information derived from the complexation model and the PH4 pharmacophore guided us through in silico screening of the virtual combinatorial library of TCL analogues to finally identify potential new TCL inhibitors effective at low nanomolar concentrations. Virtual screening of the library by PfENR-PH4 led to a predicted IC50pre value for the best inhibitor candidate as low as 1.9 nM. Finally, the stability of PfENR-TCLx complexes and the flexibility of the active conformation of the inhibitor for selected top-ranking TCL analogues were checked with the help of molecular dynamics. This computational study resulted in a set of proposed new potent inhibitors with predicted antimalarial effects and favourable pharmacokinetic profiles that act on a novel pharmacological target, PfENR.

Identification of natural products against enoyl-acyl-carrier-protein reductase in malaria via combined pharmacophore modeling, molecular docking and simulations studies

Plasmodium falciparum is counted as one of the deadly species causing malaria. In that respect, enoyl acyl carrier protein reductase is recognized as one of the attractive druggable targets for the identification of antimalarials. Thus, from the structural proteome of ENR, common feature pharmacophores were constructed. To identify the representative models, all the hypotheses were subjected to validation methods, like, test set, enrichment factor, and Güner-Henry method, and the selected representative hypotheses were used to screen out the drug-like natural products. Further, the screened candidates were advanced to molecular docking calculations. Based on the docking score criteria and presence of essential interaction with Tyr277, seven candidates were shortlisted to conduct the HYDE and QSAR assessment. Further, the stability of these complexes was evaluated by employing molecular dynamics simulations, molecular mechanics-generalized born surface area approach-based free binding energy calculations with the residue-wise contribution of PfENR to the total binding free energy of the complex. On comparing the root mean square deviation, and fluctuation plots of the docked candidates with the reference, all the candidates displayed stable behavior, and the same outcome was depicted from the secondary structure element. However, from the free energy calculations, and residue-wise contribution conducted after dynamics, it was observed that out of seven, only five candidates sustain the binding with Tyr277 and cofactor of PfENR. Therefore, in the current work, the hybrid study of screening and stability lead to the identification of five structurally diverse candidates that can be employed for the design of novel antimalarials.Communicated by Ramaswamy H. Sarma.

Theoretical design of novel antimalarial agents against P. falciparum strain, Dd2 through the QSAR modeling of synthesized 2'-substituted triclosan derivatives

In an attempt to design compounds with higher antimalarial activities, quantitative structure-activity relationship (QSAR) technique was utilized in the development of a molecular model for some synthesized 2′-substituted triclosan derivatives through a hybrid of the GA-MLR method. The model was found to have excellent statistical parameters (R² = 0.8919, R²_Adj = 0.8728, LOF = 0.2563). The descriptors mean effect (MF) revealed BCUTw-1l, which increases with an increase in molecular weight, to be the most contributive to the antimalarial activity. Consequently, compound 3, with the highest activities (pEC₅₀ = 6.9586) was deployed as the design template. The molecular weight of the template was increasing through substitutions of its atoms at several positions with heavier atoms/groups to increases the descriptor (BCUTw-1l) value. Twelves (12) theoretical derivatives of the template were designed where six of the designed derivatives have better activity than the design template. The most active designed compound, 3L was found to have the highest antimalarial activity (pEC₅₀ = 7.930) than that of the design template.

Prioritization of active antimalarials using structural interaction profile of Plasmodium falciparum enoyl-acyl carrier protein reductase (PfENR)-triclosan derivatives

An empirical relationship between the experimental inhibitory activities of triclosan derivatives and its computationally predicted Plasmodium falciparum enoyl-acyl carrier protein (ACP) reductase (PfENR) dock poses was developed to model activities of known antimalarials. A statistical model was developed using 57 triclosan derivatives with significant measures (r = 0.849, q(2) = 0.619, s = 0.481) and applied on structurally related and structurally diverse external datasets. A substructure-based search on ChEMBL malaria dataset (280 compounds) yielded only two molecules with significant docking energy, whereas eight active antimalarials (EC(50) < 100 nM, tested on 3D7 strain) with better predicted activities (pIC(50) ~ 7) from Open Access Malaria Box (400 compounds) were prioritized. Further, calculations on the structurally diverse rhodanine molecules (known PfENR inhibitors) distinguished actives (experimental IC(50) = 0.035 μM; predicted pIC(50) = 6.568) and inactives (experimental IC(50) = 50 μM; predicted pIC50 = -4.078), which showed that antimalarials possessing dock poses similar to experimental interaction profiles can be used as leads to test experimentally on enzyme assays.

In silico screening for Plasmodium falciparum enoyl-ACP reductase inhibitors

The need for novel therapeutics against Plasmodium falciparum is urgent due to recent emergence of multi-drug resistant malaria parasites. Since fatty acids are essential for both the liver and blood stages of the malarial parasite, targeting fatty acid biosynthesis is a promising strategy for combatting P. falciparum. We present a combined computational and experimental study to identify novel inhibitors of enoyl-acyl carrier protein reductase (PfENR) in the fatty acid biosynthesis pathway. A small-molecule database from ChemBridge was docked into three distinct PfENR crystal structures that provide multiple receptor conformations. Two different docking algorithms were used to generate a consensus score in order to rank possible small molecule hits. Our studies led to the identification of five low-micromolar pyrimidine dione inhibitors of PfENR.

Drug discovery studies on quinoline-based derivatives as potential antimalarial agents

Molecular modelling studies were performed to identify the essential structural requirements of quinoline-based derivatives for improving their antimalarial activity. The developed CoMFA, CoMSIA and HQSAR models for a training set comprising 37 derivatives showed good statistical significance in terms of internal cross validation (q(2)) 0.70, 0.69 and 0.80 and non-cross validation (r(2)) 0.80, 0.79 and 0.80. Also, the predicted r(2) values (r(2)pred) of 0.63, 0.61 and 0.72 for a test set consisting of 12 compounds suggested significant predicting ability of the models. Structural features were correlated in terms of steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor interactions. Furthermore, the bioactive conformation was explored and explained by docking compounds #28, 32 and 40 into the active binding site of lactate dehydrogenase of Plasmodium falciparum. The QSAR models, contour map and docking binding affinity obtained could be successfully utilized as a guiding tool for the design and discovery of novel quinoline-based derivatives with potent antimalarial activity.

Exploring QSAR for Antimalarial Activities and Drug Distribution within Blood of a Series of 4-Aminoquinoline Drugs Using Genetic-MLR

Malaria has been one of the most significant public health problems for centuries. QSAR modeling of the antimalarial activity and blood-to-plasma concentration ratio of Chloroquine and a new series of 4-aminoquinoline derivatives were developed using genetic algorithms with multiple linear regression (GA-MLR) method. We obtained two different models against Chloroquine-sensitive (3D7) and Chloroquine-resistant (W2) strains ofPlasmodium falciparumwith good adjustment levels. Drug distribution in blood, defined as drug blood-to-plasma concentration ratio (Rb), is related to molecular descriptors. Leave-many-out (LMO) andY-randomization methods confirmed the models' robustness.