Computational prediction of structure-activity relationships for the binding of aminocyclitols to β-glucocerebrosidase

Computational insights for predicting the binding and selectivity of peptidomimetic plasmepsin IV inhibitors against cathepsin D

Plasmepsins (Plms) are aspartic proteases involved in the degradation of human hemoglobin by P. falciparum and are essential for the survival and growth of the parasite. Therefore, Plm enzymes are reported as an important antimalarial drug target. Herein, we have applied molecular docking, molecular dynamics (MD) simulations, and binding free energy with the Linear Interaction Energy (LIE) approach to investigate the binding of peptidomimetic PlmIV inhibitors with a particular focus on understanding their selectivity against the human Asp protease cathepsin D (CatD). The residual decomposition analysis results suggest that amino acid differences in the subsite S3 of PlmIV and CatD are responsible for the higher selectivity of the 5a inhibitor. These findings yield excellent agreement with experimental binding data and provide new details regarding van der Waals and electrostatic interactions of subsite residues as well as structural properties of the PlmIV and CatD systems.

Computational Analysis of Triazole-Based Kojic Acid Analogs as Tyrosinase Inhibitors by Molecular Dynamics and Free Energy Calculations

Molecular docking, molecular dynamics (MD) simulations and the linear interaction energy (LIE) method were used here to predict binding modes and free energy for a set of 1,2,3-triazole-based KA analogs as potent inhibitors of Tyrosinase (TYR), a key metalloenzyme of the melanogenesis process. Initially, molecular docking calculations satisfactorily predicted the binding mode of evaluated KA analogs, where the KA part overlays the crystal conformation of the KA inhibitor into the catalytic site of TYR. The MD simulations were followed by the LIE method, which reproduced the experimental binding free energies for KA analogs with an r² equal to 0.97, suggesting the robustness of our theoretical model. Moreover, the van der Waals contributions performed by some residues such as Phe197, Pro201, Arg209, Met215 and Val218 are responsible for the binding recognition of 1,2,3-triazole-based KA analogs in TYR catalytic site. Finally, our calculations provide suitable validation of the combination of molecular docking, MD, and LIE approaches as a powerful tool in the structure-based drug design of new and potent TYR inhibitors.

Evaluating the Performance of a Non-Bonded Cu2+ Model Including Jahn-Teller Effect into the Binding of Tyrosinase Inhibitors

Tyrosinase (TYR) is a metalloenzyme classified as a type-3 copper protein, which is involved in the synthesis of melanin through a catalytic process beginning with the conversion of the amino acid l-Tyrosine (l-Tyr) to l-3,4-dihydroxyphenylalanine (l-DOPA). It plays an important role in the mechanism of melanogenesis in various organisms including mammals, plants, and fungi. Herein, we used a combination of computational molecular modeling techniques including molecular dynamic (MD) simulations and the linear interaction energy (LIE) model to evaluate the binding free energy of a set of analogs of kojic acid (KA) in complex with TYR. For the MD simulations, we used a dummy model including the description of the Jahn–Teller effect for Cu²⁺ ions in the active site of this enzyme. Our results show that the LIE model predicts the TYR binding affinities of the inhibitor in close agreement to experimental results. Overall, we demonstrate that the classical model provides a suitable description of the main interactions between analogs of KA and Cu²⁺ ions in the active site of TYR.

Aflatoxin B₁⁻Formamidopyrimidine DNA Adducts: Relationships between Structures, Free Energies, and Melting Temperatures

Thermal stabilities of DNA duplexes containing Gua (g), α- (a) or β-anomer of formamidopyrimidine-N7-9-hydroxy-aflatoxin B₁ (b) differ markedly (T_m: a<g<b), but the underlying molecular origin of this experimentally observed phenomenon is yet to be identified and determined. Here, by employing explicit-solvent molecular dynamics simulations coupled with free-energy calculations using a combined linear-interaction-energy/linear-response-approximation approach, we explain the quantitative differences in Tm in terms of three structural features (bulkiness, order, and compactness) and three energetical contributions (non-polar, electrostatic, and preorganized-electrostatic), and thus advance the current understanding of the relationships between structures, free energies, and thermal stabilities of DNA double helices.

Molecular simulations study of novel 1,4-dihydropyridines derivatives with a high selectivity for Cav3.1 calcium channel

1,4-Dihydropyridines (DHPs) have been developed to treat hypertension, angina, and nerve system disease. They are thought to mainly target the L-type calcium channels, but low selectivity prompts them to block Cav1.2 and Cav3.1 channels simultaneously. Recently, some novel DHPs with different hydrophobic groups have been synthesized and among them M12 has a higher selectivity for Cav3.1. However, the structural information about Cav3.1-DHPs complexes is not available in the experiment. Thus, we combined homology modeling, molecular docking, molecular dynamics simulations, and binding free energy calculations to quantitatively elucidate the inhibition mechanism of DHPs. The calculated results indicate that our model is in excellent agreement with experimental results. On the basis of conformational analysis, we identify the main interactions between DHPs and calcium channels and further elaborate on the different selectivity of ligands from the micro perspective. In conjunction with energy distribution, we propose that the binding sites of Cav3.1-DHPs is characterized by several interspersed hydrophobic amino acid residues on the IIIS6 and IVS6 segments. We also speculate the favorable function groups on prospective DHPs. Besides, our model provides important information for further mutagenesis experiments.

Toward an optimal docking and free energy calculation scheme in ligand design with application to COX-1 inhibitors

Cyclooxygenase-1 (COX-1) is one of the main targets of most pain-relieving pharmaceuticals. Although the enzyme is well characterized, it is known to be a difficult target for automated molecular docking and scoring. We collected from the literature a structurally diverse set of 45 nonsteroidal anti-inflammatory drugs (NSAIDs) and COX-2-selective inhibitors (coxibs) with a wide range of binding affinities for COX-1. The binding of this data set to a homology model of human COX-1 was analyzed with different combinations of molecular docking algorithms, scoring functions, and the linear interaction energy (LIE) method for estimating binding affinities. It is found that the computational protocols for estimation of binding affinities are extremely sensitive to the initial orientations of the ligands in the binding pocket. To overcome this limitation, we propose a systematic exploration of docking poses using the LIE calculations as a postscoring function. This scheme yields predictions in excellent agreement with experiment, with a mean unsigned error of 0.9 kcal/mol for binding free energies and structures of high quality. A significant improvement of the results is also seen when averaging over experimental data from several independent measurements.

Computational analysis of human OGA structure in complex with PUGNAc and NAG-thiazoline derivatives

The substitution of serine and threonine residues in nucleocytoplasmic proteins with 2-acetamido-2-deoxy-β-D-glucopyranose (O-GlcNAc) residues is an essential post-translational modification found in many multicellular eukaryotes. O-glycoprotein 2-acetamino-2-deoxy-β-D-glucopyranosidase (O-GlcNAcase) hydrolyzes O-GlcNAc residues from post-translationally modified serine/threonine residues of nucleocytoplasmic protein. O-GlcNAc has been implicated in several disease states such as cancer, Alzheimer's disease, and type II diabetes. For this paper, a model of the human O-GlcNAcase (hOGA) enzyme based on the X-ray structures of bacterial Clostridium perfringens (CpNagJ) and Bacteroides thetaiotaomicrometer (BtOGA) homologues has been generated through molecular homology modeling. In addition, molecular docking, molecular dynamics (MD) simulations, and Linear Interaction Energy (LIE) were employed to determine the bind for derivatives of two potent inhibitors: O-(2-acetamido-2-deoxy-D-glucopyranosylidene)amino-N-phenylcarbamate (PUGNAc) and 1,2-dideoxy-2'-methyl-R-D-glucopyranoso-[2,1-d]-Δ2'-thiazoline (NAG-thiazoline), with hOGA. The results show that the binding free energy calculations using the Linear Interaction Energy (LIE) are correlated with inhibition constant values. Therefore, the model of the human O-GlcNAcase (hOGA) obtained here may be used as a target for rational design of new inhibitors.

Characterization of the homodimerization interface and functional hotspots of the CXCR4 chemokine receptor

The recent crystallographic structures of the human chemokine CXC Receptor 4 (CXCR4) provide experimental evidence of a human G Protein-Coupled Receptor (GPCR) dimer in atomic detail. The CXCR4 homodimers reveal an unexpected dimerization mode involving transmembrane helices TM5 and TM6, which is examined here using all-atom molecular dynamics (MD) simulations in the physiological environment of a lipid bilayer. The bacteriophage T4 lysozyme (T4L), which was fused to the crystallized protein but absent in our simulations, is found to slightly affect the observed relative position of the protomers in the two dimers studied here, and consequently some rearrangements of the dimerization interface are proposed. In addition, the simulations provide further evidence about the role of the two stabilizing single point mutations introduced to crystallize the receptor. Finally, this work analyzes the structural and dynamic role of key residues involved both in ligand binding and in the infection process of HIV. In particular, the different side chain conformations of His113(3.39) are found to influence the dynamics of the surrounding functional hotspot region being evaluated both in the presence and in the absence of the co-crystallized ligand IT1t. The analysis reported here adds valuable knowledge for future structure-based drug design (SBDD) efforts on this pharmacological target.

3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors

Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (r = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating "Hypo1", it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high GOLD fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC(50)) data thus successfully validating "Hypo1" by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors.