Network pharmacology and molecular docking-based identification of drug candidates and key targets of Allium sativum for colorectal cancer treatment.

Colorectal cancer (CRC) is a type of cancer with high morbidity and mortality in several developing and developed countries of the world. Its mortality and morbidity are predicted to increase over the next decade, hence, efforts aimed at combating it have remained unabated. In the context of its treatment, the use of chemotherapeutics is often limited by challenges including cost-ineffectiveness, side effects, and drug resistance. Hence, medicinal plants are actively being explored for alternatives. In this study, Allium sativum (A. sativum) was explored for the discovery of key compounds that are worthy of exploration in the context of CRC treatment and the potential mechanism of its anti-CRC effects. The bioactive compounds of A. sativum were retrieved and subjected to drug-likeness and pharmacokinetics properties evaluation, the putative targets of compounds with admirable properties were predicted using PharmMapper while the targets of CRC were retrieved from GeneCards. The interactions between the targets common to both were retrieved from the String database while Cytoscape software was used to visualize and analyze the interactions. Gene set enrichment analysis (GSEA) study revealed the biological processes and pathways A. sativum could potentially restore in CRC. These analyses revealed the key targets via which A. sativum compounds exert their anti-CRC properties, while molecular docking studies of the key compounds against the key targets revealed beta-sitosterol and alpha-bisabolene as the compounds with the highest binding affinity for the key targets. Ultimately, further experimental studies are needed to validate the findings of this study.Communicated by Ramaswamy H. Sarma.

Computer-aided analysis of quercetin mechanism of overcoming docetaxel resistance in docetaxel-resistant prostate cancer.

BACKGROUND: Prostate cancer (PC) is a silent but potent killer among men. In 2018, PC accounted for more than 350, 000 death cases while more than 1.2 million cases were diagnosed. Docetaxel, a chemotherapeutic drug belonging to the taxane family of drugs, is one of the most potent drugs in combating advanced PC. However, PC cells often evolve resistance against the regimen. Hence, necessitating the search for complementary and alternative therapies. Quercetin, a ubiquitous phytocompound with numerous pharmacological properties, has been reported to reverse docetaxel resistance (DR) in docetaxel-resistant prostate cancer (DRPC). Therefore, this study aimed to explore the mechanism via which quercetin reverses DR in DRPC using an integrative functional network and exploratory cancer genomic data analyses. RESULTS: The putative targets of quercetin were retrieved from relevant databases, while the differentially expressed genes (DEGs) in docetaxel-resistant prostate cancer (DRPC) were identified by analysing microarray data retrieved from the Gene Expression Omnibus (GEO) database. Subsequently, the protein-protein interaction (PPI) network of the overlapping genes between the DEGs and quercetin targets was retrieved from STRING, while the hub genes, which represent the key interacting genes of the network, were identified using the CytoHubba plug-in of Cytoscape. The hub genes were further subjected to a comprehensive analysis aimed at identifying their contribution to the immune microenvironment and overall survival (OS) of PC patients, while their alterations in PC patients were also revealed. The biological roles played by the hub genes in chemotherapeutic resistance include the positive regulation of developmental process, positive regulation of gene expression, negative regulation of cell death, and epithelial cell differentiation among others. CONCLUSION: Further analysis revealed epidermal growth factor receptor (EGFR) as the most pertinent target of quercetin in reversing DR in DRPC, while molecular docking simulation revealed an effective interaction between quercetin and EGFR. Ultimately, this study provides a scientific rationale for the further exploration of quercetin as a combinational therapy with docetaxel.

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.

Designing a vaccine-based therapy against Epstein-Barr virus-associated tumors using immunoinformatics approach.

Epstein-Barr virus (EBV) is widely known due to its role in the etiology of infectious mononucleosis. However, it is the first oncovirus that was identified and has been implicated in the etiology of several types of cancers. Globally, EBV infection is associated with more than 200, 000 new cancer cases and 150, 000 deaths yearly. A prophylactic or therapeutic vaccine targeting tumors associated with EBV infection is currently lacking. Therefore, this study aimed to develop a multiepitope-based polyvalent vaccine against EBV-associated tumors using immunoinformatics approach. The latency-associated proteins (LAP) of three strains of the virus were used in this study. Potential epitopes predicted from the proteins were analyzed and selected based on several predicted properties. Thirty viable B-cell and T-cell epitopes were selected and conjugated using various linkers alongside beta-defensin 3 as an adjuvant and pan HLA DR-binding epitope (PADRE) sequence to improve the immunogenicity of the vaccine construct. Molecular docking studies of the vaccine construct against toll-like receptors (TLRs) showed it is capable of inducing immune response via recognition by TLRs while immune simulation studies showed it could induce both cellular and humoral immune responses. Furthermore, molecular dynamics study of the complex formed by the vaccine candidate and TLR-4 showed that the complex was stable. Ultimately, the designed vaccine showed desirable properties based on in silico evaluation; however, experimental studies are needed to validate the efficacy of the vaccine against EBV-associated tumors.

Novel Molecules derived from 3-O-(6-galloylglucoside) inhibit Main Protease of SARS-CoV 2 In Silico.

The ongoing pandemic caused by the severe acute respiratory syndrome 2 (SARS-CoV 2) has led to more than 168 million confirmed cases with 3.5 million deaths as at 28th May, 2021 across 218 countries. The virus has a cysteine protease called main protease (Mpro) which is significant to it life cycle, tagged as a suitable target for novel antivirals. In this computer-assisted study, we designed 100 novel molecules through an artificial neural network-driven platform called LigDream (https://playmolecule.org/LigDream/) using 3-O-(6-galloylglucoside) as parent molecule for design. Druglikeness screening of the molecules through five (5) different rules was carried out, followed by a virtual screening of those molecules without a single violation of the druglike rules using AutoDock Vina against Mpro. The in silico pharmacokinetic features were predicted and finally, quantum mechanics/molecular mechanics (QM/MM) study was carried out using Molecular Orbital Package 2016 (MOPAC2016) on the overall hit compound with controls to determine the stability and reactivity of the lead molecule. The findings showed that eight (8) novel molecules violated none of the druglikeness rules of which three (3) novel molecules (C33, C35 and C54) showed the utmost binding affinity of -8.3 kcal/mol against Mpro; C33 showed a good in silico pharmacokinetic features with acceptable level of stability and reactively better than our controls based on the quantum chemical descriptors analysis. However, there is an urgent need to carry out more research on these novel molecules for the fight against the disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11696-021-01899-y.

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.

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.

Newly designed compounds from scaffolds of known actives as inhibitors of survivin: computational analysis from the perspective of fragment-based drug design.

Survivin is an apoptosis suppressing protein linked to different forms of cancer. As it stands, there are no approved drugs for the inhibition of survivin in cancer cells despite a number of promising compounds in clinical trials. This study designed a new set of compounds from fragments of active survivin inhibitors to potentiate their binding with survivin at BIR domain. Three hundred and five (305) fragments made from eight potent inhibitors of survivin were reconstructed to form a new set of compounds. The compounds were optimized using R group enumeration and bioisostere replacement after extensive docking analysis. The optimised compounds were filtered by a validated pharmacophore model to reveal how well they are aligned to the pharmacophore sites. Molecular docking of the well aligned compounds revealed the top-scoring compounds; and these compounds were compared with the eight inhibitors used as template for fragment-based design on the basis of binding affinity (rigid and flexible docking), predicted pIC50 and intermolecular interactions. The electronic behaviours (global descriptors, HOMO/LUMO, molecular electrostatic potential and Fukui functions) of newly designed compounds were calculated to investigate their reactivity and atomic sites prone to neutrophilic/electrophilic attack. The nine newly designed compounds had better rigid and flexible docking scores, free energy of binding and intermolecular interactions with survivin at BIR domain than the eight active inhibitors. Based on frontier molecular orbitals, OPE-3 was found to be the most reactive and less stable compound (0.13194 eV), followed by OPE-4 and OPE-9. The global descriptive parameters showed that OPE-3 had highest softness value (7.5245 eV) while OPE-8 recorded the maximum hardness value (0.08486 eV). The well-validated QSAR model also showed that OPE-3, OPE-7 and OPE-8 had the most significant bioactivity of all the inhibitors. This study thus provides new insight into the design of compounds capable of modulating the activity of survivin. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-021-00108-8.

Molecular docking studies of some selected gallic acid derivatives against five non-structural proteins of novel coronavirus.

BACKGROUND: The World Health Organization has recently declared a new coronavirus disease (COVID-19) a pandemic and a global health emergency. The pressure to produce drugs and vaccines against the ongoing pandemic has resulted in the use of some drugs such as azithromycin, chloroquine (sulfate and phosphate), hydroxychloroquine, dexamethasone, favipiravir, remdesivir, ribavirin, ivermectin, and lopinavir/ritonavir. However, reports from some of the clinical trials with these drugs have proved detrimental on some COVID-19 infected patients with side effects more of which cardiomyopathy, cardiotoxicity, nephrotoxicity, macular retinopathy, and hepatotoxicity have been recently reported. Realizing the need for potent and harmless therapeutic compounds to combat COVID-19, we attempted in this study to find promising therapeutic compounds against the imminent threat of this virus. In this current study, 16 derivatives of gallic acid were docked against five selected non-structural proteins of SARS-COV-2 known to be a good target for finding small molecule inhibitors against the virus, namely, nsp3, nsp5, nsp12, nsp13, and nsp14. All the protein crystal structures and 3D structures of the small molecules (16 gallic acid derivatives and 3 control drugs) were retrieved from the Protein database (PDB) and PubChem server respectively. The compounds with lower binding energy than the control drugs were selected and subjected to pharmacokinetics screening using AdmetSAR server. RESULTS: 4-O-(6-galloylglucoside) gave binding energy values of - 8.4, - 6.8, - 8.9, - 9.1, and - 7.5 kcal/mol against Mpro, nsp3, nsp12, nsp13, and nsp15 respectively. Based on the ADMET profile, 4-O-(6-galloylglucoside) was found to be metabolized by the liver and has a very high plasma protein binding. CONCLUSION: The result of this study revealed that 4-O-(6-galloylglucoside) could be a promising inhibitor against these SAR-Cov-2 proteins. However, there is still a need for further molecular dynamic simulation, in vivo and in vitro studies to support these findings.

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.