Dihydrofolate reductase inhibitors: a quantitative structure–activity relationship study using 2D-QSAR and 3D-QSAR methods

Deciphering the competitive inhibition of dihydropteroate synthase by 8 marcaptoguanine analogs: enhanced potency in phenylsulfonyl fragments

The emergence of sulfa-drug resistance and reduced efficacy of pterin-based analogs towards Dihydropteroate synthase (DHPS) inhibition dictate a pressing need of developing novel antimicrobial agents for immune-compromised patients. Recently, a series of 8-Marcaptoguanin (8-MG) derivatives synthesized for 6-Hydroxymethyl-7,8-dihydropterin pyrophosphokinase (experimental K_D ∼ 100-.0.36) showed remarkable homology with the pteroic-acid and serve as a template for product antagonism in DHPS. The present work integrates ligand-based drug discovery techniques with structure-based docking, enhanced MD simulation, and MM/PBSA techniques to demonstrate the essential features of 8-MG analogs which make it a potent inhibitor for DHPS. The delicate balance in hydrophilic, hydrophobic substitutions on the 8-MG core is the crucial signature for DHPS inhibition. It is found that the dynamic interactions of active compounds are mainly dominated by consistent hydrogen bonding network with Asp 96, Asn 115, Asp 185, Ser 222, Arg 255 and π-π stacking, π-cation interactions with Phe 190, Lys 221. Further, two new 8-MG compounds containing N-phenylacetamide (compound S1, ΔG_bind-eff = -62.03 kJ/mol) and phenylsulfonyl (compound S3, ΔG_bind-eff = -71.29 kJ/mol) fragments were found to be the most potent inhibitor of DHPS, which stabilize the flexible pABA binding loop, thereby increasing their binding affinity. MM/PBSA calculation shows electrostatic energy contribution to be the principal component in stabilizing the inhibitors in the binding pocket. This fact is further confirmed by the higher energy barrier obtained in umbrella sampling for this class of inhibitors.

In Silico Antiprotozoal Evaluation of 1,4-Naphthoquinone Derivatives against Chagas and Leishmaniasis Diseases Using QSAR, Molecular Docking, and ADME Approaches

Chagas and leishmaniasis are two neglected diseases considered as public health problems worldwide, for which there is no effective, low-cost, and low-toxicity treatment for the host. Naphthoquinones are ligands with redox properties involved in oxidative biological processes with a wide variety of activities, including antiparasitic. In this work, in silico methods of quantitative structure–activity relationship (QSAR), molecular docking, and calculation of ADME (absorption, distribution, metabolism, and excretion) properties were used to evaluate naphthoquinone derivatives with unknown antiprotozoal activity. QSAR models were developed for predicting antiparasitic activity against Trypanosoma cruzi, Leishmania amazonensis, and Leishmania infatum, as well as the QSAR model for toxicity activity. Most of the evaluated ligands presented high antiparasitic activity. According to the docking results, the family of triazole derivatives presented the best affinity with the different macromolecular targets. The ADME results showed that most of the evaluated compounds present adequate conditions to be administered orally. Naphthoquinone derivatives show good biological activity results, depending on the substituents attached to the quinone ring, and perhaps the potential to be converted into drugs or starting molecules.

Combined MD/QTAIM techniques to evaluate ligand-receptor interactions. Scope and limitations

In medicinal chemistry, it is extremely important to evaluate, as accurately as possible, the molecular interactions involved in the formation of different ligand-receptor (L-R) complexes. Evaluating the different molecular interactions by quantum mechanics calculations is not a simple task, since formation of an L-R complex is a dynamic process. In this case, the use of combined techniques of molecular dynamics (MD) and quantum calculations is one the best possible approaches. In this work we report a comparative study using combined MD and QTAIM (Quantum Theory of Atoms In Molecules) calculations for five biological systems with different levels of structural complexity. We have studied Acetylcholinesterase (AChE), D2 Dopamine Receptor (D2DR), beta Secretase (BACE1), Dihydrofolate Reductase (DHFR) and Sphingosine Kinase 1 (SphK1). In these molecular targets, we have analyzed different ligands with diverse structural characteristics. The inhibitory activities of most of them have been previously measured in our laboratory. Our results indicate that QTAIM calculations can be extremely useful for in silico studies. It is possible to obtain very accurate information about the strength of the molecular interactions that stabilize the formation of the different L-R complexes. Better correlations can be obtained between theoretical and experimental data by using QTAIM calculations, allowing us to discriminate among ligands with similar affinities. QTAIM analysis gives fairly accurate information for weak interactions which are not well described by MD simulations. QTAIM study also allowed us to evaluate and determine which parts of the ligand need to be modified in order to increase its interactions with the molecular target. In this study we have discussed the importance of combined MD/QTAIM calculations for this type of simulations, showing their scopes and limitations.

In vitro cytotoxicity and structure-activity relationship approaches of ent-kaurenoic acid derivatives against human breast carcinoma cell line

In this study, ent-kaurenoic acid derivatives were obtained by microbial transformation methodologies and tested against breast cancer cell lines (MCF-7). A multivariate quantitative-structure activity relationship (QSAR) analysis was performed taking into account both microbial transformation derivatives and other analogues previously reported in literature to give some insight into the main features behind the cytotoxic activity displayed by kaurane-type diterpenes against MCF-7 cells. The partial least square regression (PLS) method was employed in the training set and the best PLS model was built with a factor describing 69.92% of variance and three descriptors (logP, ε_HOMO and ε_HOMO-1) selected by the Ordered Predictors Selection (OPS) algorithm. The QSAR model provided reasonable regression (Q² = 0.64, R² = 0.72, SEC = 0.29 and SEV = 0.33). The model was validated by leave-N-out cross-validation, y-randomization and external validation (R²_pred = 0.89 and SEP = 0.27). The selected descriptors indicated that the activity was mainly related to electronic parameters (HOMO and HOMO-1 molecular orbital energies), as well as to logP. These findings suggest that higher activity values are directly related with both higher logP and frontier orbital energy values. The positive relationship between these orbitals and the activity suggests that the ent-kaurenoic acid analogues interaction with the target involves charge displacement, which is entirely consistent with the literature. Based on these findings, three compounds were proposed and one of them was synthesized and tested. The experimental result confirmed the activity predicted by the model.