Exploring the inhibitory potentials of Momordica charantia bioactive compounds against Keap1-Kelch protein using computational approaches

Computational-based drug design of novel small molecules targeting p53-MDMX interaction

The regulation of the p53 tumor suppressor pathway is critically dependent on the activity of Murine Double Minute 2 (MDM2) and Murine Double Minute X (MDMX) proteins. In certain types of cancer cells, excessive amount of MDMX can poly-ubiquitinate p53, which can result in its degradation, leading to a subsequent reduction in the levels of this protein. Therefore, the design of small-molecule inhibitors targeting the MDMX-p53 interaction has emerged as a promising strategy for cancer therapy. In this study, we employed computational techniques including pharmacophore modeling and molecular docking to identify three potential small molecule inhibitors (CID_25094615, CID_137634453, and CID_25094344) of the MDMX-p53 interaction from a PubChem database. Molecular dynamics of 100000 ps were conducted to assess the stability of the MDMX-inhibitor complexes. Our results showed that all three compounds exhibit stable binding with MDMX, with significantly lower root mean square deviation (RMSD) and fluctuation (RMSF) values than the control ligand, indicating superior stability. Additionally, the three compounds exhibit stronger intermolecular hydrogen bond (HBOND) interactions compared to the control, suggesting stronger stability. Overall, our findings highlight the potential of these compounds as lead candidates for the development of novel anticancer agents that target the MDMX-p53 interaction.Communicated by Ramaswamy H. Sarma.

De novo antioxidant peptide design via machine learning and DFT studies

Antioxidant peptides (AOPs) are highly valued in food and pharmaceutical industries due to their significant role in human function. This study introduces a novel approach to identifying robust AOPs using a deep generative model based on sequence representation. Through filtration with a deep-learning classification model and subsequent clustering via the Butina cluster algorithm, twelve peptides (GP1-GP12) with potential antioxidant capacity were predicted. Density functional theory (DFT) calculations guided the selection of six peptides for synthesis and biological experiments. Molecular orbital representations revealed that the HOMO for these peptides is primarily localized on the indole segment, underscoring its pivotal role in antioxidant activity. All six synthesized peptides exhibited antioxidant activity in the DPPH assay, while the hydroxyl radical test showed suboptimal results. A hemolysis assay confirmed the non-hemolytic nature of the generated peptides. Additionally, an in silico investigation explored the potential inhibitory interaction between the peptides and the Keap1 protein. Analysis revealed that ligands GP3, GP4, and GP12 induced significant structural changes in proteins, affecting their stability and flexibility. These findings highlight the capability of machine learning approaches in generating novel antioxidant peptides.

Anti-diabetic drug discovery using the bioactive compounds of Momordica charantia by molecular docking and molecular dynamics analysis

Diabetes mellitus (DM) is a multifactorial life-threatening endocrine disease characterized by abnormalities in glucose metabolism. It is a chronic metabolic disease that involves multiple enzymes such as α-amylase and α-glucosidases. Inhibition of these enzymes has been identified as a promising method for managing diabetes, and researchers are currently focusing on discovering novel α-amylase and α-glucosidase inhibitors for diabetes therapy. Hence, we have selected 12 bioactive compounds from the Momordica charantia (MC) plant and performed a virtual screening and molecular dynamics investigation to identify natural inhibitors of α-amylase and α-glucosidases. Our in silico result revealed that phytocompound Rutin showed the highest binding affinity against α-amylase (1HNY) enzymes at (-11.68 kcal/mol), followed by Karaviloside II (-9.39), Momordicoside F (-9.19), Campesterol (-9.11. While docking against α-glucosidases (4J5T), Rutin again showed the greatest binding affinity (-11.93 kcal/mol), followed by Momordicine (-9.89), and Campesterol (-8.99). Molecular dynamics (MD) simulation research is currently the gold standard for drug design and discovery. Consequently, we conducted simulations of 100 nanoseconds (ns) to assess the stability of protein-ligand complexes based on parameters like RMSD, RMSF, RG, PCA, and FEL. The significance of our findings indicates that rutin from MC might serve as an effective natural therapeutic agent for diabetes management due to its strongest binding affinities with α-amylase and α-glucosidase enzymes. Further research in animals and humans is essential to validate the efficacy of these drug molecules.Communicated by Ramaswamy H. Sarma.

Predicting Plasmodium falciparum kinase inhibitors from antimalarial medicinal herbs using computational modeling approach

Malaria remains a significant public health challenge, with resistance to available drugs necessitating the development of novel therapies targeting invasion-dependent proteins. Plasmodium falciparum calcium-dependent protein kinase 1 (PfCDPK-1) is essential for host erythrocyte invasion and parasite asexual development. This study screened a library of 490 compounds using computational methods to identify potential PfCDPK-1 inhibitors. Three compounds; 17-hydroxyazadiradione, Picracin, and Epicatechin-gallate derived from known antimalarial botanicals, showed potent inhibitory effects on PfCDPK-1. These compounds exhibited better binding affinities (-8.8, -9.1, -9.3 kCal/mol respectively), pharmacokinetics, and physicochemical properties than the purported inhibitory standard of PfCDPK-1, Purfalcamine. Molecular dynamics simulations (50 ns) and molecular mechanics analyses confirmed the stability and binding rigidity of these compounds at the active pocket of PfCDPK-1. The results suggest that these compounds are promising pharmacological targets with potential therapeutic effects for malaria treatment/management without undesirable side effects. Therefore, this study provides new insights into the development of effective antimalarial agents targeting invasion-dependent proteins, which could help combat the global malaria burden.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00175-z.

Promising disruptors of p53-MDM2 dimerization from some medicinal plant phytochemicals: a molecular modeling study

Cancer is a major global health issue that has a high mortality rate. p53, which functions as a tumor suppressor, is critical in preventing tumor development by regulating the cell cycle and inducing apoptosis in damaged cells. However, the tumor suppressor function of p53 is effectively inhibited by its direct interaction with the hydrophobic cleft of MDM2 protein via multiple mechanisms As a result, restoring p53 activity by blocking the p53-MDM2 protein-protein interaction has been proposed as a compelling therapeutic strategy for cancer treatment. The use of molecular docking and phytochemical screening procedures are appraised to inhibit MDM2's hydrophobic cleft and disrupt the p53-MDM2 interaction. For this purpose, a library of 51 bioactive compounds from 10 medicinal plants was compiled and subjected to structure-based virtual screening. Out of these, only 3 compounds (Atalantoflavone, Cudraxanthone 1, and Ursolic acid) emerged as promising inhibitors of MDM2-p53 based on their binding affinities (-9.1 kcal/mol, -8.8 kcal/mol, and -8.8 kcal/mol respectively) when compared to the standard (-8.8 kcal/mol). Moreover, these compounds showed better pharmacokinetic and drug-like profiling than the standard inhibitor (Chromonotriazolopyrimidine 1). Finally, the 100 ns MD simulation analysis confirmed no significant perturbation in the conformational dynamics of the simulated binary complexes when compared to the standard. In particular, Ursolic acid was found to satisfy the molecular enumeration the most compared to the other inhibitors. Our overall molecular modeling finding shows why these compounds may emerge as potent arsenals for cancer therapeutics. Nonetheless, extensive experimental and clinical research is needed to augment their use in clinics.Communicated by Ramaswamy H. Sarma.

GCMS fingerprints and phenolic extracts of Allium sativum inhibit key enzymes associated with type 2 diabetes

Objectives

Inhibition of carbohydrate digestion enzymes (α-amylase and α-glucosidase) has been reported in studies as a therapeutic approach for the management or treatment of type 2 diabetes mellitus, owing to its potential to decrease postprandial hyperglycemia. The anti-diabetic potential of Allium sativum (also known as garlic) against diabetes mellitus has been established. Therefore, in this study, we assessed the antidiabetic potential of A. sativum using in vitro enzyme assays after which we explored computational modelling approach using the quantified GC-MS identities to unravel the key bioactive compounds responsible for the anti-diabetic potential.

Methods

We used in vitro enzyme inhibition assays (α-amylase and α-glucosidase) to evaluate antidiabetic potential and subsequently performed gas chromatography-mass spectroscopy (GC-MS) to identify and quantify the bioactive compounds of the plant extract. The identified bioactive compounds were subjected to in silico docking and pharmacokinetic assessment.

Results

A. sativum phenolic extract showed high dose-dependent inhibition of α-amylase and α-glucosidase (p < 0.05). Interestingly, the extract inhibited α-glucosidase with a half maximal inhibitory concentration of 53.75 μg/mL, a value higher than that obtained for the standard acarbose. Docking simulation revealed that morellinol and phentolamine were the best binders of α-glucosidase, with mean affinity values of -7.3 and -7.1 kcal/mol, respectively. These compounds had good affinity toward active site residues of the enzyme, and excellent drug-like and pharmacokinetic properties supporting clinical applications.

Conclusions

Our research reveals the potential of A. sativum as a functional food for the management of type 2 diabetes, and suggests that morellinol and phentolamine may be the most active compounds responsible for this anti-diabetic prowess. Therefore these compounds require further clinical asessment to demonstrate their potential for drug development.

Reinstating apoptosis using putative Bcl-xL natural product inhibitors: Molecular docking and ADMETox profiling investigations

Objectives

While a fine balance in the pro-apoptotic and anti-apoptotic family members of the B-cell lymphoma-2 (Bcl-2) protein family represents a normal signaling profile, a tilt in balance towards anti-apoptotic family members has fortified different forms of cancers with survival advantage and resistance against treatment. Induction of apoptosis is a key therapeutic approach in cancer drug discovery, and the inhibition of the anti-apoptotic B cell lymphoma extra-large (Bcl-xL) is a long-standing clinical target for cancer therapy. In this study, we combined computer-aided approaches to report putative binders for this target.

Methods

Before our virtual screening campaign, we conducted a redocking experiment strategy of the x-ray bound inhibitor of the Bcl-xL protein with some of the available docking software at our disposal to determine the software with the best efficiency for this screening. iGEMDOCK emerged to reproduce the x-ray crystallographic information and was used to dock the library of ligand, which was developed from diverse literature reporting compounds with anti-apoptotic profiles through the Bcl-2 family.

Results

Of the compounds in the library, alpha-mangostin and oubain scored as hits with binding energy values of -123.025 kcal/mol and -122.271 kcal/mol, respectively, which is more than -120.8 kcal/mol observed by the standard.

Conclusions

These compounds revealed a more binding affinity potential than ABT-737, which is a standard inhibitor of the protein. In addition, these scaffolds not only interact with relevant and hotspot residues for the inhibition of Bcl-xL but also possess good pharmacokinetic and excellent toxicity, an endpoint that should be considered for further testing and drug development.

Integrated virtual screening and molecular dynamics simulation revealed promising drug candidates of p53-MDM2 interaction

In the vast majority of malignancies, the p53 tumor suppressor pathway is compromised. In some cancer cells, high levels of MDM2 polyubiquitinate p53 and mark it for destruction, thereby leading to a corresponding downregulation of the protein. MDM2 interacts with p53 via its hydrophobic pocket, and chemical entities that block the dimerization of the protein-protein complex can restore p53 activity. Thus far, only a few chemical compounds have been reported as potent arsenals against p53-MDM2. The Protein Data Bank has crystallogaphic structures of MDM2 in complex with certain compounds. Herein, we have exploited one of the complexes in the identification of new p53-MDM2 antagonists using a hierarchical virtual screening technique. The initial stage was to compile a targeted library of structurally appropriate compounds related to a known effective inhibitor, Nutlin 2, from the PubChem database. The identified 57 compounds were subjected to virtual screening using molecular docking to discover inhibitors with high binding affinity for MDM2. Consequently, five compounds with higher binding affinity than the standard emerged as the most promising therapeutic candidates. When compared to Nutlin 2, four of the drug candidates (CID_140017825, CID_69844501, CID_22721108, and CID_22720965) demonstrated satisfactory pharmacokinetic and pharmacodynamic profiles. Finally, MD simulation of the dynamic behavior of lead-protein complexes reveals the stability of the complexes after a 100,000 ps simulation period. In particular, when compared to the other three leads, overall computational modeling found CID_140017825 to be the best pharmacological candidate. Following thorough experimental trials, it may emerge as a promising chemical entity for cancer therapy.

Exploration of the Interactions between Maltase–Glucoamylase and Its Potential Peptide Inhibitors by Molecular Dynamics Simulation

Diabetes mellitus, a chronic metabolic disorder, represents a serious threat to human health. The gut enzyme maltase–glucoamylase (MGAM) has attracted considerable attention as a potential therapeutic target for the treatment of type 2 diabetes. Thus, developing novel inhibitors of MGAM holds the promise of improving clinical management. The dipeptides, Thr-Trp (TW) and Trp-Ala (WA), are known inhibitors of MGAM; however, studies on how they interact with MGAM are lacking. The work presented here explored these interactions by utilizing molecular docking and molecular dynamics simulations. Results indicate that the active center of the MGAM could easily accommodate the flexible peptides. Interactions involving hydrogen bonds, cation-π, and hydrophobic interactions are predicted between TW/WA and residues including Tyr1251, Trp1355, Asp1420, Met1421, Glu1423, and Arg1510 within MGAM. The electrostatic energy was recognized as playing a dominant role in both TW-MGAM and WA-MGAM systems. The binding locations of TW/WA are close to the possible acid-base catalytic residue Asp1526 and might be the reason for MGAM inhibition. These findings provide a theoretical structural model for the development of future inhibitors.