An approach to identify new antihypertensive agents using Thermolysin as model: In silico study based on QSARINS and docking

Ligand and structure-based discovery of phosphorus-containing compounds as potential metalloproteinase inhibitors

In this study, a methodology is proposed, combining ligand- and structure-based virtual screening tools, for the identification of phosphorus-containing compounds as inhibitors of zinc metalloproteases. First, we use Dragon molecular descriptors to develop a Linear Discriminant Analysis classification model, which is widely validated according to the OECD principles. This model is simple, robust, stable and has good discriminating power. Furthermore, it has a defined applicability domain and it is used for virtual screening of the DrugBank database. Second, docking experiments are carried out on the identified compounds that showed good binding energies to the enzyme thermolysin. Considering the potential toxicity of phosphorus-containing compounds, their toxicological profile is evaluated according to Protox II. Of the five molecules evaluated, two show carcinogenic and mutagenic potential at small LD50, not recommended as drugs, while three of them are classified as non-toxic, and could constitute a starting point for the development of new vasoactive metalloprotease inhibitor drugs. According to molecular dynamics simulation, two of them show stable interactions with the active site maintaining coordination with the metal. A high agreement is evident between QSAR, docking and molecular dynamics results, demonstrating the potentialities of the combination of these tools.

2,4,6-Trimethoxy chalcone derivatives: an integrated study for redesigning novel chemical entities as anticancer agents through QSAR, molecular docking, ADMET prediction, and computational simulation

QSAR, an efficient and successful approach for optimizing lead compounds in drug design, was employed to study a reported series of compounds derived from 2,4,6-trimethoxy chalcone derivatives. The ability of these compounds to inhibit CDK1 was examined, with the help of QSARINS software for model development. The generated QSAR model revealed three significant descriptors, exhibiting strong correlations with impressive statistical values: cross-validation leave-one-out correlation coefficient (Q2LOO) = 0.6663, coefficient of determination (R2) = 0.7863, external validation coefficient (R2ext) = 0.7854, cross-validation leave-many-out correlation coefficient (Q2LMO) = 0.6256, Concordance Correlation Coefficient for cross-validation (CCCcv) = 0.8150, CCCtr = 0.8804, and CCCext = 0.8750. From the key structural findings and the insights gained from the descriptors, ETA_dPsi_A, WTPT-5, and GATS7s, new lead molecules were designed. The designed molecules were then evaluated for their CDK1 inhibitory activity using the three-descriptor model developed in this study. To evaluate their drug likeliness, in-silico ADMET predictions were made using Schrodinger's Software. Molecular docking was carried out to determine the interactions of designed compounds with the target protein. The designed compounds having excellent binding pocket molecular stability and anticancer effectiveness was substantiated by the findings of the molecular dynamics simulation. The results of this work point out important properties and crucial interactions necessary for efficient protein inhibition, suggesting lead candidates for further development as novel anticancer agents.Communicated by Ramaswamy H. Sarma.

The Synergistic Influence of Polyflavonoids from Citrus aurantifolia on Diabetes Treatment and Their Modulation of the PI3K/AKT/FOXO1 Signaling Pathways: Molecular Docking Analyses and In Vivo Investigations

This study was aimed at probing the modulatory influence of polyflavonoids extracted from Citrus aurantifolia, lemon peel extract (LPE-polyflavonoids), on attenuating diabetes mellitus (DM) and its complications. HPLC investigations of the LPE exhibited the incidence of five flavonoids, including diosmin, biochanin A, hesperidin, quercetin, and hesperetin. The in silico impact on ligand-phosphatidylinositol 3-kinase (PI3K) interaction was investigated in terms of polyflavonoid class to explore the non-covalent intakes and binding affinity to the known protein active site. The drug likeness properties and pharmacokinetic parameters of the LPE-polyflavonoids were investigated to assess their bioavailability in relation to Myricetin as a control. Remarkably, the molecular docking studies demonstrated a prominent affinity score of all these agents together with PI3K, implying the potency of the extract to orchestrate PI3K, which is the predominant signal for lessening the level of blood glucose. To verify these findings, in vivo studies were conducted, utilizing diabetic male albino rats treated with LPE-polyflavonoids and other groups treated with hesperidin and diosmin as single flavonoids. Our findings demonstrated that the LPE-polyflavonoids significantly ameliorated the levels of glucose, insulin, glycogen, liver function, carbohydrate metabolizing enzymes, G6Pd, and AGEs compared to the diabetic rats and those exposed to hesperidin and diosmin. Furthermore, the LPE-polyflavonoids regulated the TBARS, GSH, CAT, TNF-α, IL-1β, IL-6, and AFP levels in the pancreatic and hepatic tissues, suggesting their antioxidant and anti-inflammatory properties. In addition, the pancreatic and hepatic GLUT4 and GLUT2 were noticeably increased in addition to the pancreatic p-AKT in the rats administered with the LPE-polyflavonoids compared to the other diabetic rats. Remarkably, the administration of LPE-polyflavonoids upregulated the expression of the pancreatic and hepatic PI3K, AMPK, and FOXO1 genes, emphasizing the efficiency of the LPE in orchestrating all the signaling pathways necessitated to reduce the diabetes mellitus. Notably, the histopathological examinations of the pancreatic and hepatic tissues corroborated the biochemical results. Altogether, our findings accentuated the potential therapeutic role of LPE-polyflavonoids in controlling diabetes mellitus.

Thiazolidinedione-triazole conjugates: design, synthesis and probing of the α-amylase inhibitory potential

Aim: The primary objective of this investigation was the synthesis, spectral interpretation and evaluation of the α-amylase inhibition of rationally designed thiazolidinedione-triazole conjugates (7a-7aa). Materials & methods: The designed compounds were synthesized by stirring a mixture of thiazolidine-2,4-dione, propargyl bromide, cinnamaldehyde and azide derivatives in polyethylene glycol-400. The α-amylase inhibitory activity of the synthesized conjugates was examined by integrating in vitro and in silico studies. Results: The investigated derivatives exhibited promising α-amylase inhibitory activity, with IC50 values ranging between 0.028 and 0.088 μmol ml-1. Various computational approaches were employed to get detailed information about the inhibition mechanism. Conclusion: The thiazolidinedione-triazole conjugate 7p, with IC50 = 0.028 μmol ml-1, was identified as the best hit for inhibiting α-amylase.

Parsing structural fragments of thiazolidin-4-one based α-amylase inhibitors: A combined approach employing in vitro colorimetric screening and GA-MLR based QSAR modelling supported by molecular docking, molecular dynamics simulation and ADMET studies

α-Amylase (EC.3.2.1.1) is a ubiquitous digestive endoamylase. The abrupt rise in blood glucose levels due to the hydrolysis of carbohydrates by α-amylase at a faster rate is one of the main reasons for type 2 diabetes. The inhibitors prevent the action of digestive enzymes, slowing the digestion of carbs and eventually assisting in the management of postprandial hyperglycemia. In the course of developing α-amylase inhibitors, we have screened 2-aryliminothiazolidin-4-one based analogs for their in vitro α-amylase inhibitory potential and employed various in silico approaches for the detailed exploration of the bioactivity. The DNSA bioassay revealed that compounds 5c, 5e, 5h, 5j, 5m, 5o and 5t were more potent than the reference drug (IC₆₀ value = 22.94 ± 0.24 μg mL^-1). The derivative 5o with -NO₂ group at both the rings was the most potent analog with an IC₆₀ value of 19.67 ± 0.20 μg mL^-1 whereas derivative 5a with unsubstituted aromatic rings showed poor inhibitory potential with an IC₆₀ value of 33.40 ± 0.15 μg mL^-1. The reliable QSAR models were developed using the QSARINS software. The high value of R²_ext = 0.9632 for model IM-9 showed that the built model can be applied to predict the α-amylase inhibitory activity of the untested molecules. A consensus modelling approach was also employed to test the reliability and robustness of the developed QSAR models. Molecular docking and molecular dynamics were employed to validate the bioassay results by studying the conformational changes and interaction mechanisms. A step further, these compounds also exhibited good ADMET characteristics and bioavailability when tested for in silico pharmacokinetics prediction parameters.

Theoretical Evaluation of Novel Thermolysin Inhibitors from Bacillus thermoproteolyticus. Possible Antibacterial Agents

The search for new antibacterial agents that could decrease bacterial resistance is a subject in continuous development. Gram-negative and Gram-positive bacteria possess a group of metalloproteins belonging to the MEROPS peptidase (M4) family, which is the main virulence factor of these bacteria. In this work, we used the previous results of a computational biochemistry protocol of a series of ligands designed in silico using thermolysin as a model for the search of antihypertensive agents. Here, thermolysin from Bacillus thermoproteolyticus, a metalloprotein of the M4 family, was used to determine the most promising candidate as an antibacterial agent. Our results from docking, molecular dynamics simulation, molecular mechanics Poisson-Boltzmann (MM-PBSA) method, ligand efficiency, and ADME-Tox properties (Absorption, Distribution, Metabolism, Excretion, and Toxicity) indicate that the designed ligands were adequately oriented in the thermolysin active site. The Lig783, Lig2177, and Lig3444 compounds showed the best dynamic behavior; however, from the ADME-Tox calculated properties, Lig783 was selected as the unique antibacterial agent candidate amongst the designed ligands.

Evaluation of new antihypertensive drugs designed in silico using Thermolysin as a target

The search for new therapies for the treatment of Arterial hypertension is a major concern in the scientific community. Here, we employ a computational biochemistry protocol to evaluate the performance of six compounds (Lig783, Lig1022, Lig1392, Lig2177, Lig3444 and Lig6199) to act as antihypertensive agents. This protocol consists of Docking experiments, efficiency calculations of ligands, molecular dynamics simulations, free energy, pharmacological and toxicological properties predictions (ADME-Tox) of the six ligands against Thermolysin. Our results show that the docked structures had an adequate orientation in the pocket of the Thermolysin enzymes, reproducing the X-ray crystal structure of Inhibitor-Thermolysin complexes in an acceptable way. The most promising candidates to act as antihypertensive agents among the series are Lig2177 and Lig3444. These compounds form the most stable ligand-Thermolysin complexes according to their binding free energy values obtained in the docking experiments as well as MM-GBSA decomposition analysis calculations. They present the lowest values of Ki, indicating that these ligands bind strongly to Thermolysin. Lig2177 was oriented in the pocket of Thermolysin in such a way that both OH of the dihydroxyl-amino groups to establish hydrogen bond interactions with Glu146 and Glu166. In the same way, Lig3444 interacts with Asp150, Glu143 and Tyr157. Additionally, Lig2177 and Lig3444 fulfill all the requirements established by Lipinski Veber and Pfizer 3/75 rules, indicating that these compounds could be safe compounds to be used as antihypertensive agents. We are confident that our computational biochemistry protocol can be used to evaluate and predict the behavior of a broad range of compounds designed in silicoagainst a protein target.