Identification of a 1, 8-naphthyridine-containing compound endowed with the inhibition of p53-MDM2/X interaction signaling: a computational perspective.

Various studies have established that molecules specific for MDMX inhibition or optimized for dual inhibition of p53-MDM2/MDMX interaction signaling are more suitable for activating the Tp53 gene in tumor cells. Nevertheless, there are sparse numbers of approved molecules to treat the health consequences brought by the lost p53 functions in tumor cells. Consequently, this study explored the potential of a small molecule ligand containing 1, 8-naphthyridine scaffold to act as a dual inhibitor of p53-MDM2/X interactions using computational methods. The results obtained from quantum mechanical calculations revealed our studied compound entitled CPO is more stable but less reactive compared to standard dual inhibitor RO2443. Like RO2443, CPO also exhibited good non-linear optical properties. The results of molecular docking studies predicted that CPO has a higher potential to inhibit MDM2/MDMX than RO2443. Furthermore, CPO was stable over 50 ns molecular dynamics (MD) simulation in complex with MDM2 and MDMX respectively. On the whole, CPO also exhibited good drug-likeness and pharmacokinetics properties compared to RO2443 and was found with more anti-cancer activity than RO2443 in bioactivity prediction. CPO is anticipated to elevate effectiveness and alleviate drug resistance in cancer therapy. Ultimately, our results provide an insight into the mechanism that underlay the inhibition of p53-MDM2/X interactions by a molecule containing 1, 8-naphthyridine scaffold in its molecular structure.

Therapeutic Study of Cinnamic Acid Derivative for Oxidative Stress Ablation: The Computational and Experimental Answers.

This study aimed to examine the therapeutic activity of the cinnamic acid derivative KAD-7 (N'-(2,4-dichlorobenzylidene)-3-(4-methoxyphenyl) acrylohydrazide) on Fe2+-induced oxidative hepatic injury via experimental and computational models. In addition, the role of ATPase and ectonucleoside triphosphate diphosphohydrolase (ENTPDase) in the coordination of cellular signals is speculated upon to proffer suitable therapeutics for metabolic stress disorder upon their inhibition. While we know little about therapeutics with flexible dual inhibitors for these protein targets, this study was designed to screen KAD-7's (N'-(2,4-dichlorobenzylidene)-3-(4-methoxyphenyl) acrylohydrazide) inhibitory potential for both protein targets. We induced oxidative hepatic damage via the incubation of hepatic tissue supernatant with 0.1 mM FeSO4 for 30 min at 37 °C. We achieved the treatment by incubating the hepatic tissues with KAD-7 under the same conditions. The catalase (CAT), glutathione (GSH), malondialdehyde (MDA), ATPase, and ENTPDase activity were all measured in the tissues. We predicted how the drug candidate would work against ATPase and ENTPDase targets using molecular methods. When hepatic injury was induced, there was a significant decrease in the levels of the GSH, CAT, and ENTPDase (p < 0.05) activities. In contrast, we found a noticeable rise in the MDA levels and ATPase activity. KAD-7 therapy resulted in lower levels of these activities overall (p < 0.05), as compared to the control levels. We found the compound to have a strong affinity for ATPase (-7.1 kcal/mol) and ENTPDase (-7.4 kcal/mol), and a better chemical reactivity than quercetin. It also met all drug-likeness parameters. Our study shows that KAD-7 can protect the liver from damage caused by FeSO4 by reducing oxidative stress and purinergic actions. Our studies indicate that KAD-7 could be developed as a therapeutic option since it can flexibly inhibit both ATPase and ENTPDase.

Multi-regulator of EZH2-PPARs Therapeutic Targets: A Hallmark for Prospective Restoration of Pancreatic Insulin Production and Cancer Dysregulation.

The unexpected rise in cancer and diabetes statistics has been a significant global threat, inciting ongoing research into various biomarkers that can act as innovative therapeutic targets for their management. The recent discovery of how EZH2-PPARs' regulatory function affects the metabolic and signalling pathways contributing to this disease has posed a significant breakthrough, with the synergistic combination of inhibitors like GSK-126 and bezafibrate for treating these diseases. Nonetheless, no findings on other protein biomarkers involved in the associated side effects have been reported. As a result of this virtual study, we identified the gene-disease association, protein interaction networks between EZH2-PPARs and other protein biomarkers regulating pancreatic cancer and diabetes pathology, ADME/Toxicity profiling, docking simulation and density functional theory of some natural products. The results indicated a correlation between obesity and hypertensive disease for the investigated biomarkers. At the same time, the predicted protein network validates the link to cancer and diabetes, and nine natural products were screened to have versatile binding capacity against the targets. Among all natural products, phytocassane A outperforms the standard drugs' (GSK-126 and bezafibrate) in silico validation for drug-likeness profiles. Hence, these natural products were conclusively proposed for additional experimental screening to complement the results on their utility in drug development for diabetes and cancer therapy against the EZH2-PPARs' new target.

Lead optimization of Allium sativum L. compounds for PTP1B inhibition in diabetes treatment: in silico molecular docking and dynamics simulation.

Protein tyrosine phosphatase 1B (PTP1B) has been identified as a promising drug target for the development of diabetes medications via an inhibition mechanism. Using a computational approach, this study investigates the binding mechanism of lead optimized natural compounds from Allium sativum against the human PTP1B. The molecular docking, induced-fit docking, and binding free energy calculations were analyzed using Schrödinger Suite 2021-2. MD simulation, and gene enrichment analysis was achieved via the Desmond module of Schrödinger to identify best compounds as inhibitors against PTP1B in diabetes management. The docking scores of the lead optimized compounds were good; 5280443_121 from apigenin had the best binding score of -9.345 kcal/mol, followed by 5280443_129 with a binding score of -9.200 kcal/mol, and 5280863_177 from kaempferol had a binding score of -8.528 kcal/mol, followed by 5280863_462 with a binding score of -8.338 kcal/mol. The top two lead optimized compounds, docked better than the standard PTP1B inhibitor (-7.155 kcal/mol), suggesting them as potent inhibitors than the standard PTP1B inhibitor. The outcomes of the induced-fit docking were consistent with the increased binding affinity used in the Glide computation of the five conformed poses between the derivatives (5280443_121, 5280443_129, 5280863_177, and 5280863_462) and the protein (PTP1B). Based on the binding fee energies (MM-GBSA), the lead optimized compounds from kaempferol exhibited more stability than those from apigenin. In the pharmacophore development, all the models exhibit good results across the different metrics. The best performing model with five of five matches on a 1.34 and 1.33 phase score was DDRRR_1, DDRRR_2, and DDDRR_1. The average BEDROC value (= 160.9) was 1, while the average EF 1% value across all models was 101. There were no substantial conformational modifications during the MD simulation process, indicating that the apigenin derivatives (5280443_121) was stable in the protein's active site in 100 ns. IGF1R, EGFR, INSR, PTPN1, SRC, JAK2, GRB2, BCAR1, and IRS1 are among the 11 potential targets found in the protein-protein interaction (PPI) of A. sativum against PTP1B that may be important in A. sativum's defense against PTP1B. Sixty-four (64) pathways were found by KEGG pathway enrichment analysis to be potentially involved in the anti-PTP1B of A. sativum. Consequently, data obtained indicates the effectiveness of the in silico studies in identifying potential lead compounds in A. sativum against PTP1B target.Communicated by Ramaswamy H. Sarma.

Predictive hybrid paradigm for cytotoxic activity of 1,3,4-thiadiazole derivatives as CDK6 inhibitors against human (MCF-7) breast cancer cell line and its structural modifications: rational for novel cancer therapeutics.

The dysregulation of cyclin-CDK6 interactions has been implicated in human breast cancer, providing a rationale for more therapeutic options. Recently, ATP-competitive inhibitors have been employed for managing breast cancer. These molecules, like most natural CDKs inhibitors, potently bind in the ATP-binding site of CDK6 to regulate trans-activation. Nonetheless, only a few numbers of these molecules are approved to mitigate breast cancer, thus, ensuring that the search for more selective inhibitors continues. In this study, we attempted to establish the selective predictive models for identifying potent CDK6 inhibitors against a human breast cancer cell-line using a dataset of fifty-two 1,3,4-thiadiazole derivatives. The significant eight descriptor hybrid QSAR models generated exhibited encouraging statistical attributes including R2> 0.70, Q2LOO > 0.70, Q2LMO > 0.60, Qfn2 > 0.6. Furthermore, the study designed new compounds based on the activity and structural basis for selectivity of compounds for CDK6. While demonstrating good potency and modest selectivity, the compound C16, which showed significantly high activity of 5.5607 µM and binding energy value of -9.0 Kcal/mol, was used as template for compounds design to generate 10 novel series of 1,3,4-thiadiazole analogues containing benzisoselenazolone scaffolds, with significant pharmacological activity and better selectivity for CDK6. By our rationale, four of the designed compounds (C16b, C16h, C16i, and C16j) with activity values of 6.2584 µM, 6.7812 µM, 6.4717 µM, and 6.2666 µM respectively, and binding affinities of -10.0 kcal/mol, -9.9 kcal/mol, -9.9 kcal/mol, and -9.9 kcal/mol respectively, may emerge as therapeutic options for breast cancer treatment after extensive in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

Targeting p53-MDM2 interactions to identify small molecule inhibitors for cancer therapy: beyond "Failure to rescue".

At present, disrupting p53-MDM2 interactions through small molecule ligands is a promising approach to safe treatment and management of human cancer. Tumor cells unlike the normal cells, are rapidly evolving affecting the efficacy of many approved anti-cancer agents due to drug resistance. Therefore, identifying a potential anticancer compound is crucial. Pharmacophore based virtual screening, followed by molecular docking, ADMET evaluation, and molecular dynamics studies against MDM2 protein was investigated to identify potential ligands that may act as inhibitors. The model (AHRR_1) with survival score (4.176) was selected among the top ranked generated Pharmacophore hypothesis. Validation of the model hypothesis by an external dataset of actives and inactive compounds produced significant validation attributes including; AUC = 0.85, BEDROC = 0.56 at α = 20.0, RIE = 8.18, AUAC = 0.88, and EF of 6.2 at the top 2% of the dataset. The model was use for screening the ZINC database, and the top 1375 hits satisfying the model hypothesis were subjected to molecular docking studies to understand the molecular and structural basis of selectivity of compounds for MDM2 protein. A sub-set of 25 compounds with binding energy lower than the reference inhibitors were evaluated for pharmacokinetic properties. Four compounds (ZINC02639178, ZINC06752762, ZINC38933175, and ZINC77969611) showed the most desired pharmacokinetic profile. Lastly, investigation of the dynamic behaviour of leads-protein complexes through MD simulation showed similar RMSD, RMSF, and H-bond occupancy profile compared to a reference inhibitor, suggesting stability throughout the simulation time. However, ZINC02639178 was found to satisfy the molecular enumeration the most compared to the other three leads. It may emerge as potential treatment option after extensive experimental studies. Communicated by Ramaswamy H. Sarma.

In silico design and validation of a highly degenerate primer pair: a systematic approach.

BACKGROUND: The techniques of amplifying genetic materials have enabled the extensive study of several biological activities outside the biological milieu of living systems. More recently, this approach has been extended to amplify population of genes, from evolutionarily related gene family for detection and evaluation of microbial consortial with several unique potentialities (e.g., enzymatic degradability). Conceivably, primer mixtures containing substitutions of different bases at specific sites (degenerate primers) have enabled the amplification of these genes in PCR reaction. However, the degenerate primer design problem (DPD) is a constraint to designing this kind of primer. To date, different algorithms now exist to solve various versions of DPD problem, many of which, only few addresses and satisfy the criteria to design primers that can extensively cover high through-put sequences while striking the balance between specificity and efficiency. The highly degenerate primer (HYDEN) design software program primarily addresses this variant of DPD problem termed "maximum coverage-degenerate primer design (MC-DPD)" and its heuristics have been substantiated for optimal efficiency from significant successes in PCR. In spite of the premium presented for designing degenerate primers, literature search has indicated relatively little use of its heuristics. This has been thought to result from the complexity of the program since it is run only by command-line, hence limiting its accessibility. To solve this problem, researchers have optionally considered the manual design of degenerate primers or design through software programs that provides accessibility through a graphical user interface (GUI). Realizing this, we have attempted in this study to provide a user-friendly approach for researchers with little or no background in bioinformatics to design degenerate primers using HYDEN RESULTS: Virtual Tests of our designed degenerate primer pair through in silico PCR substantiated the correspondence between efficiency and coverage with the target sequences as pre-defined by the initial HYDEN output, thereby validating the potentials of HYDEN to effectively solve the MC-DPD problem. Additionally, the designed primer-pair mechanistically amplified all sequences used as a positive control with no amplification observed in the negative controls. CONCLUSION: In this study, we provided a turnkey protocol to simplify the design of degenerate primers using the heuristics of the HYDEN software program.