QSAR Models Guided by Molecular Dynamics Applied to Human Glucokinase Activators

Synthesis of Phosphorus(V)-Substituted Six-Membered N-Heterocycles: Recent Progress and Challenges

Heterocycles functionalized with pentavalent phosphorus are of great importance since they include a great variety of biologically active compounds and pharmaceuticals, advanced materials, and valuable reactive intermediates for organic synthesis. Significant progress in synthesis of P(O)R2-substituted six-membered heterocycles has been made in the past decade. This review covers the synthetic strategies towards aromatic monocyclic six-membered N-heterocycles, such as pyridines, pyridazines, pyrimidines, and pyrazines bearing phosphonates and phosphine oxides, which were reported from 2012 to 2022.

3D-QSAR, Molecular Docking, and MD Simulations of Anthraquinone Derivatives as PGAM1 Inhibitors

PGAM1 is overexpressed in a wide range of cancers, thereby promoting cancer cell proliferation and tumor growth, so it is gradually becoming an attractive target. Recently, a series of inhibitors with various structures targeting PGAM1 have been reported, particularly anthraquinone derivatives. In present study, the structure–activity relationships and binding mode of a series of anthraquinone derivatives were probed using three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, r² = 0.97, q² = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r² = 0.96, q² = 0.82) techniques were performed to produce 3D-QSAR models, which demonstrated satisfactory results, especially for the good predictive abilities. In addition, molecular dynamics (MD) simulations technology was employed to understand the key residues and the dominated interaction between PGAM1 and inhibitors. The decomposition of binding free energy indicated that the residues of F22, K100, V112, W115, and R116 play a vital role during the ligand binding process. The hydrogen bond analysis showed that R90, W115, and R116 form stable hydrogen bonds with PGAM1 inhibitors. Based on the above results, 7 anthraquinone compounds were designed and exhibited the expected predictive activity. The study explored the structure–activity relationships of anthraquinone compounds through 3D-QSAR and molecular dynamics simulations and provided theoretical guidance for the rational design of new anthraquinone derivatives as PGAM1 inhibitors.

QSAR analysis of sodium glucose co-transporter 2 (SGLT2) inhibitors for anti-hyperglycaemic lead development

QSAR (Quantitative Structure Activity Relationship) modelling was performed on a dataset of 90 sodium-dependent glucose cotransporter 2 (SGLT2) inhibitors. The quantitative and explicative evaluations revealed some of the subtle and distinguished structural features that are responsible for the inhibitory potency of these compounds against SGLT2, such as less possible number of ring carbons at 8 Å from the lipophilic atoms in the molecule (fringClipo8A) and more possible value for the sum of the partial charges of the lipophilic atoms present within seven bonds from the donor atoms (lipo_don_7Bc). Multivariate GA-MLR (genetic algorithm-multi linear regression) and thorough validation methodology out-turned a statistically robust QSAR model with a very high predictability shown from various statistical parameters. A QSAR model with r² = 0.83, F = 51.54, Q²_LOO = 0.79, Q²_LMO = 0.79, CCC_cv = 0.88, Q²Fⁿ = 0.76-0.81, r²_ext = 0.77, CCC_ext = 0.85, and with RMSE_tr < RMSE_cv was proposed. This QSAR model will assist synthetic chemists in the development of the SGLT2 inhibitors as the antidiabetic leads.

Application of machine learning methods for the development of antidiabetic drugs

Diabetes is a chronic non-communicable disease caused by several different routes, which has attracted increasing attention. In order to speed up the development of new selective drugs, machine learning (ML) technology has been applied in the process of diabetes drug development, which opens up a new blueprint for drug design. This review provides a comprehensive portrayal of the application of ML in antidiabetic drug use.

Recent Developments in Medicinal Chemistry of Allosteric Activators of Human Glucokinase for Type 2 Diabetes Mellitus Therapeutics

BACKGROUND

Glucokinase (GK), a cytoplasmic enzyme catalyzes the metabolism of glucose to glucose- 6-phosphate with the help of ATP and aids in the controlling of blood glucose levels within the normal range in humans. In pancreatic β-cells, it plays a chief role by controlling the glucose-stimulated secretion of insulin and in liver hepatocyte cells, it controls the metabolism of carbohydrates. GK acts as a promising drug target for the pharmacological treatment of patients with type 2 diabetes mellitus (T2DM) as it plays an important role in the control of carbohydrate metabolism.

METHODS

Data used for this review was based on the search from several science databases as well as various patent databases. The main data search terms used were allosteric GK activators, diabetes mellitus, type 2 diabetes, glucokinase, glucokinase activators and human glucokinase.

RESULTS

This article discusses an overview of T2DM, the biology of GK, the role of GK in T2DM, recent updates in the development of small molecule GK activators reported in recent literature, mechanism of action of GK activators and their clinical status.

CONCLUSION

GK activators are the novel class of pharmacological agents that enhance the catalytic activity of GK enzyme and display their antihyperglycemic effects. Broad diversity of chemical entities including benzamide analogues, carboxamides, acrylamides, benzimidazoles, quinazolines, thiazoles, pyrimidines, pyridines, orotic acid amides, amino acid derivatives, amino phosphates and urea derivatives have been synthesized in past two decades as potent allosteric activators of GK. Presently, the pharmaceutical companies and researchers are focusing on the design and development of liver-selective GK activators for preventing the possible adverse effects associated with GK activators for the long-term treatment of T2DM.

Studies on the IC50 of Metabolically Stable 1-(3,3-diphenylpropyl)- piperidinyl Amides and Ureas as Human CCR5 Receptor Antagonists Based on QSAR

Background:

In this study, modulators of human Chemotactic cytokine receptor 5 (CCR5) were described using a quantitative structure-activity relationship model (QSAR). This model was based on the molecule’s chemical structure.

Methods::

All 56 compounds of CCR5 receptor antagonists were randomly separated into two sets, 43 were reserved for training and the other 13 for testing. In the course of this study, molecular models were drawn using ChemDraw software. By means of Hyperchem software as well as optimized with both AM1 (semi-empirical self-consistent-field molecular orbital) and MM+ (molecular mechanics plus force field), molecular models were described through numerous descriptors using CODESSA software.

Results:

Linear models were obtained by Heuristic Method (HM) software and nonlinear models were obtained using APS software with optimal descriptor combinations used to build linear QSAR models, involving a group of selected descriptors. As a result, values of the above two different sets were shown to result from 0.82 in testing and 0.86 in training in HM while 0.83 in testing and 0.88 in training in Gene Expression Programming (GEP).

Conclusion:

From this method, the activity of molecules could be predicted, and the molecular structure could be changed to alter its IC50, avoiding the testing of large numbers of compounds.

Detection of Chemical Weapon Agents Using Spectroscopic Probes: A Computational Study

Organophosphorus compounds are organic compounds widely employed in agriculture as well as in chemical weapons. The use in agriculture is due to their insecticidal properties. However, in chemical warfare, the use of organophosphorus is associated with acetylcholinesterase inhibition, which promotes the cholinergic syndromes. In this line, the fast detection of this class of compound is crucial for the determination of environmental exposure. This improved detection will naturally allow for more prompt courses of treatment depending on the contaminant findings. In this perspective, the dipyrrinone oxime (1) was employed for the detection of organophosphorus compounds that are employed as nerve agents, such as cyclosarin, sarin, soman, diethyl chlorophosphate, diisopropylfluorophosphate, 2-(dimethylamino)ethyl N,N-dimethylphosphoramidofluoridate, O-ethyl-S-[2-(diethylamino)ethyl]methylphosphonothioate, O-ethyl-S-[2(diisopropylamino)ethyl] methylphosphonothioate, and O,O-diethyl-S-[2-(diethylamino)ethyl] phosphorothioate, through fluorescent emission. The thermodynamics and kinetic parameters as well as spectroscopic properties of the complexes formed for 1 and all organophosphorus compounds previously cited were investigated by means of theoretical calculations. From our findings, only the diethyl chlorophosphate, 2-(dimethylamino)ethyl N,N-dimethylphosphoramidofluoridate, and O,O-diethyl-S-[2-(diethylamino)ethyl] phosphorothioate emitted fluorescence in the hexane, toluene, chloroform, dichloromethane, methanol, acetonitrile, water, and dimethyl sulfoxide solvents. The study of the absorption wavelength with the most polar solvent showed higher values compared to apolar solvents. In the same solvent, for instance, soman in hexane showed the lowest absorption wavelength value, 324.5 nm, and DCP the highest value, 330.8 nm. This behavior was observed in other tested solvents. The thermodynamic parameters indicate negative Gibbs free energy (ΔG) values for the O-ethyl-S-[2(diisopropylamino)ethyl] methylphosphonothioate with 1 reaction. On the other hand, the sarin and cyclosarin revealed the lowest Gibbs free energy (ΔG‡) values, being kinetically favorable and presenting more reactivity.

QSAR-based molecular signatures of prenylated (iso)flavonoids underlying antimicrobial potency against and membrane-disruption in Gram positive and Gram negative bacteria

Prenylated flavonoids and isoflavonoids are phytochemicals with remarkable antibacterial activity. In this study, 30 prenylated (iso)flavonoids were tested against Listeria monocytogenes and Escherichia coli (the latter in combination with an efflux pump inhibitor). Minimum inhibitory concentrations of the most active compounds ranged between 6.3–15.0 µg/mL. Quantitative structure-activity relationships (QSAR) analysis was performed and linear regression models were proposed with R² between 0.77–0.80, average R²_m between 0.70–0.75, Q²_LOO between 0.66–0.69, and relatively low amount of descriptors. Shape descriptors (related to flexibility and globularity), together with hydrophilic/hydrophobic volume and surface area descriptors, were identified as important molecular characteristics related to activity. A 3D pharmacophore model explaining the effect of the prenyl position on the activity of compounds was developed for each bacterium. These models predicted active compounds with an accuracy of 71–88%. With regard to the mode of action, good antibacterial prenylated (iso)flavonoids with low relative hydrophobic surface area caused remarkable membrane permeabilization, whereas those with higher relative hydrophobic surface area did not. Based on the QSAR and membrane permeabilization studies, the mode of action of antibacterial prenylated (iso)flavonoids was putatively rationalized.

A comparative study on the binary and ternary mixture toxicity of antibiotics towards three bacteria based on QSAR investigation

Antibiotics have become common pollutants in the environment. In most cases, the antibiotics in the environment exist as mixtures, posing joint effects on the organisms. Therefore, the mixture toxicity of the antibiotics can better reflect their environmental risks. In this paper, three types of commonly used antibiotics, i.e., sulfonamides (SAs), SA potentiators (SAPs) and tetracyclines (TCs) were investigated for their binary and tertiary mixture toxicity on three bacteria, Escherichia coli (E. coli), Vibrio fischeri (V. fischeri) and Bacillus subtilis (B.subtilis). It was found that SA-SAP mixtures and SA-SAP-TC mixtures presented synergetic effects on the three bacteria, while SA-TC and SAP-TC mixtures showed antagonistic effects. QSAR investigation suggested that the actual concentration ratio of the components in a mixture could vary a lot from the designed concentration ratio; moreover, the TCs in the ternary mixtures altered the toxic ratio of SAs and SAPs, which lead to the varying joint effects of the ternary mixtures on different bacteria. The present research proposes a novel idea for the mechanistic study of the mixture toxicity, both theoretically and methodologically; and the QSAR studies provide a reference for the prediction of the mixture toxicity, which could be helpful to the risk assessment on joint exposure to antibiotic mixtures.

QSAR, docking, ADMET, and system pharmacology studies on tormentic acid derivatives for anticancer activity

To explore the anticancer compounds from tormentic acid derivatives, a quantitative structure-activity relationship (QSAR) model was developed by the multiple linear regression methods. The developed QSAR model yielded a high activity-descriptors relationship accuracy of 94% referred by regression coefficient (r² = .94) and a high activity prediction accuracy of 91%. The QSAR study indicates that chemical descriptors, chiV5, T_T_Cl_7, T_2_T_4, SsCH3count, and Epsilon3 are significantly correlated with anticancer activity. This validated model was further been used for virtual screening and thus identification of new potential breast cancer inhibitors. Lipinski's rule of five, ADMET risk and synthetic accessibility are used to filter false positive hits. Filtered compounds were then docked to identify the possible target binding pocket, to obtain a set of aligned ligand poses and to prioritize the predicted active compounds. The scrutinized compounds, as well as their metabolites, were predicted and analyzed for different pharmacokinetics parameters such as absorption, distribution, metabolism, excretion, and toxicity. Finally, the top-ranked compound NB-12 was evaluated by system pharmacology approach. Later studied the metabolic networks, disease biomarker networks, pathway maps, drug-target networks and generate significant gene networks. The strategy applied in this research work may act as a framework for rational design of potential anticancer drugs.

Probing the influence of carboxyalkyl groups on the molecular flexibility and the charge density of apigenin derivatives

Apigenin is an important flavonoids due to its antidiabetic bioactivity. It was reported experimentally that the 7-substituent derivative of apigenin has higher biological activity than 4'- and 5-substituted derivatives while introducing sole carboxyalkyl group -(CH₂)₇COOH into the parent structure. Molecular docking studies indicated that the other two derivatives have lower binding affinities than the 7-substituent derivative (-7.52 kcal mol^-1), which is considered to be a better inhibitor than the parent molecule. Almost all of the carbon atoms and oxygen atoms are coplaner for all three molecules in solution phase, however, all carboxyalkyl groups bend inside into the parent molecules in the active site, and the jagged geometries of the carbon chains are destroyed correspondingly. In addition, most of the electron densities of the chemical bonds for all molecules are decreased, especially the 7-substituent derivative. In contrast, most of the Laplacian values for three molecules are increased in the active site, which suggests that the charge densities at the bond critical point (bcp) are much more depleted than the solution phase. Dipole moments of derivatives are all increased in the active site, suggesting strong intermolecular interactions. After interacting with the S. cerevisiae α-glucosidase, only the 7-substituent derivative has the lowest energy gap ΔE _HOMO-LUMO, which indicates the lowest stability and the highest inhibition activity. Graphical abstract Probing the influence of carboxyalkyl groups on the molecular flexibility and the charge density of apigenin derivatives.

Comparison of the molecular interactions of 7'-carboxyalkyl apigenin derivatives with S. cerevisiae α-glucosidase

As one of the most investigated flavonoids, apigenin, is considered to be a strong α-glucosidase inhibitor. However, the clinical utility of apigenin is limited due to its low solubility. It was reported that the solubility and biological activity can be improved by introducing sole carboxyalkyl group into apigenin, especially the 7'-substitution. With the increase of length of the alkyl chain in carboxyalkyl group, B ring of the apigenin derivative is embedded much more deeply into the binding cavity while the carboxyalkyl stretches to the neighboring cavity. All of the terminal carboxyl groups form hydrogen bonding interactions easily with the surrounding polar amino acids, such as His239, Ser244, Arg312 and Asp349. Thus, the electron density values of the carbonyl in the carboxyl group become higher than the solution status due to the strong molecular interactions. In fact, electron densities of most of the chemical bonds are decreased after molecular docking procedure. On compared with the solution phase, however, dipole moments of most of these molecules are increased, and their vectors are reoriented distinctly in the active sites. It is noticed that all of the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) are distributed throughout the whole parent apigenin ring in solution phase, whereas the disappeared situation happened on the B rings of some molecules (II-IV) in the active site, leading to higher energy gaps.