Quantitative structure-activity relationships for cycloguanil analogs as PfDHFR inhibitors using mathematical molecular descriptors

Hybrid PABA-glutamic acid conjugated 1,3,5-triazine derivatives: Design, synthesis, and antimalarial activity screening targeting Plasmodium falciparum dihydro folate reductase enzyme

Despite the successful reduction in the malaria health burden in recent years, it continues to remain a significant global health problem mainly because of the emerging resistance to first-line treatments. Also because of the disruption in malaria prevention services during the COVID-19 pandemic, there was an increase in malaria cases in 2021 compared to 2020. Hence, the present study outlined the in silico study, synthesis, and antimalarial evaluation of 1,3,5-triazine hybrids conjugated with PABA-glutamic acid. Docking study revealed higher binding energy compared to the originally bound ligand WR99210, predominant hydrogen bond interaction, and involvement of key amino acid residues, like Arg122, Ser120, and Arg59. Fourteen compounds were synthesized using traditional and microwave synthesis. The in vitro antimalarial evaluation against chloroquine-sensitive 3D7 and resistant Dd2 strain of Plasmodium falciparum showed a high to moderate activity range. Compounds C1 and B4 showed high efficacy against both strains and a further study revealed that compound C1 is non-cytotoxic against the HEK293 cell line with no acute oral toxicity. In vivo, study was performed for the most potent antimalarial compound C1 to optimize the research work and found to be effectively suppressing parasitemia of Plasmodium berghei strain in the Swiss albino mice model.

Consensus QSPR modelling for the prediction of cellular response and fibrinogen adsorption to the surface of polymeric biomaterials

In the current study, we have developed predictive quantitative structure-activity relationship (QSAR) models for cellular response (foetal rate lung fibroblast proliferation) and protein adsorption (fibrinogen adsorption (FA)) on the surface of tyrosine-derived biodegradable polymers designed for tissue engineering purpose using a dataset of 66 and 40 biodegradable polymers, respectively, employing two-dimensional molecular descriptors. Best four individual models have been selected for each of the endpoints. These models are developed using partial least squares regression with a unique combination of six and four descriptors for cellular response and protein adsorption, respectively. The generated models were strictly validated using internal and external metrics to determine the predictive ability and robustness of proposed models. Subsequently, the validated individual models for each response endpoints were used for the generation of 'intelligent' consensus models ( http://teqip.jdvu.ac.in/QSAR_Tools/DTCLab/ ) to improve the quality of predictions for the external data set. These models may help in prediction of virtual polymer libraries for rational design/optimization for properties relevant to biomedical applications prior to their synthesis.

Application of molecular docking and PSO-SVR intelligent approaches in antimalarial activity prediction of enantiomeric cycloguanil analogues

A series of antifolate compounds, i.e. 1-(4-chlorophenyl)-6,6-dimethyl-1,3,5-triazine-2,4-diamine, or cycloguanil analogues, have shown effective inhibiting properties against Plasmodium falciparum dihydrofolate reductase (PfDHFR). In this work, the stereoselectivity of PfDHFR to the R and S enantiomer of cycloguanil analogues was obtained from molecular docking calculations and integrated into QSAR study to obtain a more accurate prediction model. Results indicate that PfDHFR can bind to cycloguanil analogues in the R and S enantiomers. Cycloguanil analogues with alkyl chain substituent prefer the R enantiomer over S because they do not experience steric hindrance with the Phe58 side chain, while cycloguanil analogues with phenol chain substituent prefer the S enantiomer over R because they do not experience steric hindrance with Leu46 and Met55 side chains. Particle swarm optimization and support vector regression were used to select relevant descriptors and generate the effective prediction model, with a high statistical significance level (r²_training = 0.941; r²_test = 0.884).

Exploring PfDHFR reaction surface: A combined molecular dynamics and QM/MM analysis

The substrate to the enzyme PfDHFR (Plasmodium falciparum Dihydrofolate Reductase) is a small molecule dihydrofolate (DHF), it gets converted to tetrahydrofolate (THF) in the active site of the enzyme. The PfDHFR reaction surface involves the protonation of DHF to DHFP as an initial step before the catalytic conversion. The binding affinities of all these species (DHF, DHFP and THF) contribute to the mechanism of DHFR catalytic action. Molecular dynamics (MD) simulations and Quantum Mechanics/Molecular Mechanics (QM/MM) analysis were performed to evaluate the binding affinity and molecular recognition interactions of the substrate DHF/DHFP and the product THF, in the active site of wild-type PfDHFR (wtPfDHFR). The binding affinities of the cofactor NADPH/NADP⁺ were also estimated in all the three complexes. The molecular dynamics (MD) simulations of the substrate, product and cofactor in the cavities of wtPfDHFR revealed the variation of the atomic level interactions during the course of the catalytic conversion. It was found that the DHFP binds very strongly to the PfDHFR active site and pulls the cofactor NADPH closer to itself. The QM/MM analysis revealed that the binding energy of DHFP (-59.82 kcal/mol) and NADPH (-100.24 kcal/mol) in DHFP-wtPfDHFR complex, is higher in comparison to the binding energy of DHF (-38.67 kcal/mol) and NADPH (-77.53 kcal/mol) in DHF-wtPfDHFR complex and the binding energy of THF (-30.72 kcal/mol) and NADP⁺ (-73.72 kcal/mol) in THF-wtPfDHFR complex. The hydride ion donor-acceptor distance (DAD) analysis was also carried out. This combined MD and QM/MM analysis revealed that the protonation of DHF increases the proximity between the substrate and the cofactor, thus facilitates the reaction profile of PfDHFR.

A novel prediction approach for antimalarial activities of Trimethoprim, Pyrimethamine, and Cycloguanil analogues using extremely randomized trees

Malaria is still one of the most serious diseases in tropical regions. This is due in part to the high resistance against available drugs for the inhibition of parasites, Plasmodium, the cause of the disease. New potent compounds with high clinical utility are urgently needed. In this work, we created a novel model using a regression tree to study structure-activity relationships and predict the inhibition constant, K_i of three different antimalarial analogues (Trimethoprim, Pyrimethamine, and Cycloguanil) based on their molecular descriptors. To the best of our knowledge, this work is the first attempt to study the structure-activity relationships of all three analogues combined. The most relevant descriptors and appropriate parameters of the regression tree are harvested using extremely randomized trees. These descriptors are water accessible surface area, Log of the aqueous solubility, total hydrophobic van der Waals surface area, and molecular refractivity. Out of all possible combinations of these selected parameters and descriptors, the tree with the strongest coefficient of determination is selected to be our prediction model. Predicted K_i values from the proposed model show a strong coefficient of determination, R²=0.996, to experimental K_i values. From the structure of the regression tree, compounds with high accessible surface area of all hydrophobic atoms (ASA_H) and low aqueous solubility of inhibitors (Log S) generally possess low K_i values. Our prediction model can also be utilized as a screening test for new antimalarial drug compounds which may reduce the time and expenses for new drug development. New compounds with high predicted K_i should be excluded from further drug development. It is also our inference that a threshold of ASA_H greater than 575.80 and Log S less than or equal to -4.36 is a sufficient condition for a new compound to possess a low K_i.

Ligand binding studies, preliminary structure-activity relationship and detailed mechanistic characterization of 1-phenyl-6,6-dimethyl-1,3,5-triazine-2,4-diamine derivatives as inhibitors of Escherichia coli dihydrofolate reductase

Gram-negative bacteria are implicated in the causation of life-threatening hospital-acquired infections. They acquire rapid resistance to multiple drugs and available antibiotics. Hence, there is the need to discover new antibacterial agents with novel scaffolds. For the first time, this study explores the 1,3,5-triazine-2,4-diamine and 1,2,4-triazine-2,4-diamine group of compounds as potential inhibitors of Escherichia coli DHFR, a pivotal enzyme in the thymidine and purine synthesis pathway. Using differential scanning fluorimetry, DSF, fifteen compounds with various substitutions on either the 3rd or 4th positions on the benzene group of 6,6-dimethyl-1-(benzene)-1,3,5-triazine-2,4-diamine were shown to bind to the enzyme with varying affinities. Then, the dose dependence of inhibition by these compounds was determined. Preliminary quantitative structure-activity relationship analysis and docking studies implicate the alkyl linker group and the sulfonyl fluoride group in increasing the potency of inhibition. 4-[4-[3-(4,6-diamino-2,2-dimethyl-1,3,5-triazin-1-yl)phenyl]butyl]benzenesulfonyl fluoride (NSC120927), the best hit from the study and a molecule with no reported inhibition of E. coli DHFR, potently inhibits the enzyme with a Ki value of 42.50 ± 5.34 nM, followed by 4-[6-[4-(4,6-diamino-2,2-dimethyl-1,3,5-triazin-1-yl)phenyl]hexyl]benzenesulfonyl fluoride (NSC132279), with a Ki value of 100.9 ± 12.7 nM. Detailed kinetic characterization of the inhibition brought about by five small-molecule hits shows that these inhibitors bind to the dihydrofolate binding site with preferential binding to the NADPH-bound binary form of the enzyme. Furthermore, in search of novel diaminotriazine scaffolds, it is shown that lamotrigine, a 1,2,4-triazine-3,5-diamine and a sodium-ion channel blocker class of antiepileptic drug, also inhibits E. coli DHFR. This is the first comprehensive study on the binding and inhibition brought about by diaminotriazines of a gram-negative prokaryotic enzyme and provides valuable insights into the SAR as an aid to the discovery of novel antibiotics.

Receptor-based QSAR study for a series of 3,3-disubstituted-5-aryl oxindoles and 6-aryl benzimidazol-2-ones derivatives as progesterone receptor inhibitors

Receptor-based comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of 54 progesterone receptor (PR) inhibitors. The established CoMFA model from the training set gives statistically significant results with the cross-validated q (2) of 0.534 and non-cross-validated [Formula: see text] of 0.947. The best CoMSIA model was derived by the combination of steric field and hydrophobic field with a q (2) of 0.615 and [Formula: see text] of 0.954. A test set of 18 compounds was used to validate the predictive ability of the two models. The predicted correlation coefficients [Formula: see text] are 0.681 and 0.677 for CoMFA and CoMSIA models, respectively. Based on the CoMFA maps, the key structural characters of progesterone receptor inhibitors are identified. Moreover, the binding modes of oxindoles and benzimidazol-2-ones are also given by the quantum mechanical/molecular mechanical (QM/MM) calculations. This may provide useful information for drug design.