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Computational study on natural compounds inhibitor of c-Myc.

ABSTRACT: To screen and identify ideal leading compounds from a drug library (ZINC15 database) with potential inhibition effect against c-Myc to contribute to medication design and development.A series of computer-aided virtual screening techniques were performed to identify potential inhibitors of c-Myc. LibDock from the software Discovery Studio was used to do a structure-based screening after ADME (absorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was utilized to show the binding affinity and potential mechanism between ligands and c-Myc. Stability of the ligand-receptor complex was analyzed by molecular dynamic simulation at the end of the research.Compounds with more interactive energy which are confirmed to be the potential inhibitors for c-Myc were identified from the ZINC15 databases. Additionally, those compounds are also anticipated with fewer ames mutagenicity, rodent carcinogenicity, nondevelopmental toxic potential, and tolerant with cytochrome p450 2D6(CYP2D6). Dynamic simulation analysis also revealed that the very compounds had more favorable potential energy compared with 10058-F4(ZINC12406714). Furthermore, we prove that those compounds are stable and can exist in natural conditions.This study demonstrates that the compounds are potential therapeutic inhibitors for c-Myc. These compounds are safe and stable for drug candidates and may play a critical role in c-Myc inhibitor development.

SUBMITTER: Ren J

PROVIDER: S-EPMC7738058 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Computational study on natural compounds inhibitor of c-Myc.

Ren Junan J Huangfu Yuhao Y Ge Junliang J Wu Bo B Li Weihang W Wang Xinhui X Zhao Liyan L

Medicine 20201201 50

To screen and identify ideal leading compounds from a drug library (ZINC15 database) with potential inhibition effect against c-Myc to contribute to medication design and development.A series of computer-aided virtual screening techniques were performed to identify potential inhibitors of c-Myc. LibDock from the software Discovery Studio was used to do a structure-based screening after ADME (absorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was utilized ...[more]

PMID: 33327259

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Project description:Ebola virus (EBOV) is one of the most lethal pathogens that can infect humans. The Ebola viral protein VP35 (EBOV VP35) inhibits host IFN-α/β production by interfering with host immune responses to viral invasion and is thus considered as a plausible drug target. The aim of this study was to identify potential novel lead compounds against EBOV VP35 using computational techniques in drug discovery. The 3D structure of the EBOV VP35 with PDB ID: 3FKE was used for molecular docking studies. An integrated library of 7675 African natural product was pre-filtered using ADMET risk, with a threshold of 7 and, as a result, 1470 ligands were obtained for the downstream molecular docking using AutoDock Vina, after an energy minimization of the protein via GROMACS. Five known inhibitors, namely, amodiaquine, chloroquine, gossypetin, taxifolin and EGCG were used as standard control compounds for this study. The area under the curve (AUC) value, evaluating the docking protocol obtained from the receiver operating characteristic (ROC) curve, generated was 0.72, which was considered to be acceptable. The four identified potential lead compounds of NANPDB4048, NANPDB2412, ZINC000095486250 and NANPDB2476 had binding affinities of -8.2, -8.2, -8.1 and -8.0 kcal/mol, respectively, and were predicted to possess desirable antiviral activity including the inhibition of RNA synthesis and membrane permeability, with the probable activity (Pa) being greater than the probable inactivity (Pi) values. The predicted anti-EBOV inhibition efficiency values (IC50), found using a random forest classifier, ranged from 3.35 to 11.99 μM, while the Ki values ranged from 0.97 to 1.37 μM. The compounds NANPDB4048 and NANPDB2412 had the lowest binding energy of -8.2 kcal/mol, implying a higher binding affinity to EBOV VP35 which was greater than those of the known inhibitors. The compounds were predicted to possess a low toxicity risk and to possess reasonably good pharmacological profiles. Molecular dynamics (MD) simulations of the protein-ligand complexes, lasting 50 ns, and molecular mechanisms Poisson-Boltzmann surface area (MM-PBSA) calculations corroborated the binding affinities of the identified compounds and identified novel critical interacting residues. The antiviral potential of the molecules could be confirmed experimentally, while the scaffolds could be optimized for the design of future novel anti-EBOV chemotherapeutics.

Project description:BACKGROUND:The current standard care therapy for hepatitis C virus (HCV) infection consists of two regimes, namely interferon-based and interferon-free treatments. The treatment through the combination of ribavirin and pegylated interferon is expensive, only mildly effective, and is associated with severe side effects. In 2011, two direct-acting antiviral (DAA) drugs, boceprevir and telaprevir, were licensed that have shown enhanced sustained virologic response (SVR) in phase III clinical trial, however, these interferon-free treatments are more sensitive to HCV genotype 1 infection. The variable nature of HCV, and the limited number of inhibitors developed thus aim in expanding the repertoire of available drug targets, resulting in targeting the virus assembly therapeutically. AIM:We conducted this study to predict the 3D structure of the p7 protein from the HCV genotypes 3 and 4. Approximately 63 amino acid residues encoded in HCV render this channel sensitive to inhibitors, making p7 a promising target for novel therapies. HCV p7 protein forms a small membrane known as viroporin, and is essential for effective self-assembly of large channels that conduct cation assembly and discharge infectious virion particles. METHOD:In this study, we screened drugs and flavonoids known to disrupt translation and production of HCV proteins, targeted against the active site of p7 residues of HCV genotype 3 (GT3) (isolatek3a) and HCV genotype 4a (GT4) (isolateED43). Furthermore, we conducted a quantitative structure-activity relationship and docking interaction study. RESULTS:The drug NB-DNJ formed the highest number of hydrogen bond interactions with both modeled p7 proteins with high interaction energy, followed by BIT225. A flavonoid screen demonstrated that Epigallocatechin gallate (EGCG), nobiletin, and quercetin, have more binding modes in GT3 than in GT4. Thus, the predicted p7 protein molecule of HCV from GT3 and GT4 provides a general avenue to target structure-based antiviral compounds. CONCLUSIONS:We hypothesize that the inhibitors of viral p7 identified in this screen may be a new class of potent agents, but further confirmation in vitro and in vivo is essential. This structure-guided drug design for both GT3 and GT4 can lead to the identification of drug-like natural compounds, confirming p7 as a new target in the rapidly increasing era of HCV.

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Computational study on natural compounds inhibitor of c-Myc.

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Computational study on natural compounds inhibitor of c-Myc.

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