Dataset Information

Exploring the Binding Interaction of Raf Kinase Inhibitory Protein With the N-Terminal of C-Raf Through Molecular Docking and Molecular Dynamics Simulation.

ABSTRACT: Protein-protein interactions are indispensable physiological processes regulating several biological functions. Despite the availability of structural information on protein-protein complexes, deciphering their complex topology remains an outstanding challenge. Raf kinase inhibitory protein (RKIP) has gained substantial attention as a favorable molecular target for numerous pathologies including cancer and Alzheimer's disease. RKIP interferes with the RAF/MEK/ERK signaling cascade by endogenously binding with C-Raf (Raf-1 kinase) and preventing its activation. In the current investigation, the binding of RKIP with C-Raf was explored by knowledge-based protein-protein docking web-servers including HADDOCK and ZDOCK and a consensus binding mode of C-Raf/RKIP structural complex was obtained. Molecular dynamics (MD) simulations were further performed in an explicit solvent to sample the conformations for when RKIP binds to C-Raf. Some of the conserved interface residues were mutated to alanine, phenylalanine and leucine and the impact of mutations was estimated by additional MD simulations and MM/PBSA analysis for the wild-type (WT) and constructed mutant complexes. Substantial decrease in binding free energy was observed for the mutant complexes as compared to the binding free energy of WT C-Raf/RKIP structural complex. Furthermore, a considerable increase in average backbone root mean square deviation and fluctuation was perceived for the mutant complexes. Moreover, per-residue energy contribution analysis of the equilibrated simulation trajectory by HawkDock and ANCHOR web-servers was conducted to characterize the key residues for the complex formation. One residue each from C-Raf (Arg398) and RKIP (Lys80) were identified as the druggable "hot spots" constituting the core of the binding interface and corroborated by additional long-time scale (300 ns) MD simulation of Arg398Ala mutant complex. A notable conformational change in Arg398Ala mutant occurred near the mutation site as compared to the equilibrated C-Raf/RKIP native state conformation and an essential hydrogen bonding interaction was lost. The thirteen binding sites assimilated from the overall analysis were mapped onto the complex as surface and divided into active and allosteric binding sites, depending on their location at the interface. The acquired information on the predicted 3D structural complex and the detected sites aid as promising targets in designing novel inhibitors to block the C-Raf/RKIP interaction.

SUBMITTER: Parate S

PROVIDER: S-EPMC8194344 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Alzheimer's Disease (AD) is the prevailing type of neurodegenerative illness, characterised by the accumulation of amyloid beta plaques. The symptoms associated with AD are memory loss, emotional variability, and a decline in cognitive functioning. To date, the pharmaceuticals currently accessible in the marketplace are limited to symptom management. According to several research, antidepressants have demonstrated potential efficacy in the management of AD. In this particular investigation, a total of 24 anti-depressant medications were selected as ligands, while the Microtubule Affinity Receptor Kinase 4 (MARK4) protein was chosen as the focal point of our study. The selection of MARK4 was based on its known involvement in the advancement of AD and other types of malignancies, rendering it a highly prospective target for therapeutic interventions. The initial step involved doing ADMET analysis, which was subsequently followed by molecular docking of 24 drugs. This was succeeded by molecular dynamics simulation and molecular mechanics generalised Born surface area (MMGBSA) calculations. Upon conducting molecular docking experiments, it has been determined that the binding affinities observed fall within the range of -5.5 kcal/mol to -9.0 kcal/mol. In this study, we selected six anti-depressant compounds (CID ID - 4184, 2771, 4205, 5533, 4543, and 2160) based on their binding affinities, which were determined to be -9.0, -8.7, -8.4, -8.3, -8.2, and -8.2, respectively. Molecular dynamics simulations were conducted for all six drugs, with donepezil serving as the control drug. Various analyses were performed, including basic analysis and post-trajectory analysis such as free energy landscape (FEL), polarizable continuum model (PCM), and MMGBSA calculations. Based on the findings from molecular dynamics simulations and the MMGBSA analysis, it can be inferred that citalopram and mirtazapine exhibit considerable potential as anti-depressant agents. Consequently, these compounds warrant further investigation through in vitro and in vivo investigations in the context of treating AD.

Project description:Diabetes is a chronic fast-growing metabolic disorder that is characterized by high blood glucose levels. Tagetes minuta L. has been used as a traditional remedy for various illnesses for many years, and, furthermore, its oil is used in the perfume and flavor industries. T. minuta contains various metabolites, such as flavonoids, thiophenes, terpenes, sterols, and phenolics, with varied bioactivities. Flavonoids can inhibit carbohydrate-digesting enzymes, such as alpha-amylase, which is a convenient dietary strategy for controlling hyperglycemia. In the current investigation, the isolated flavonoids quercetagetin-6-O-(6-O-caffeoyl-β-D-glucopyranoside), quercetagetin-7-O-β-D-glucopyranoside, quercetagetin-6-O-β-D-glucopyranoside, minutaside A, patuletin-7-O-β-D-glucopyranoside, quercetagetin-7-methoxy-6-O-β-D-glucopyranoside, tagenols A and B, quercetagetin-3,7-dimethoxy-6-O-β-D-glucopyranoside, patuletin, quercetin-3,6-dimethyl ether, and quercetin-3-methyl ether from T. minuta were assessed for their alpha-amylase inhibition (AAI) efficacy using an in vitro assay, as well as molecular docking, dynamics simulation, and ADMET analyses. Our findings show that quercetagetin-6-O-(6-O-caffeoyl-β-D-glucopyranoside) (1), quercetagetin-7-O-β-D-glucopyranoside (2), quercetagetin-6-O-β-D-glucopyranoside (3), minutaside A (4), patuletin-7-O-β-D-glucopyranoside (5), and quercetagetin-7-methoxy-6-O-β-D-glucopyranoside (6) had a notable AAI capacity (IC50s ranged from 7.8 to 10.1 μM) compared to acarbose (IC50 7.1 μM). Furthermore, these compounds with the highest binding affinity among the tested flavonoids revealed high docking scores for AA (ranging from -12.171 to 13.882 kcal/mol) compared to that of acarbose (-14.668 kcal/mol). In MDS, these compounds were observed to show maximum stability and the greatest binding free energy, suggesting that they may contend with native ligands. In addition, the ADMET analysis showed that these active compounds had a broad span of drug-like, pharmacokinetic, and physicochemical features and did not possess any considerable undesired effects. The current results suggest the potential of these metabolites as AAI candidates. However, further in vivo and mechanistic studies are warranted to specify the efficacy of these metabolites.

Project description:BackgroundYinchen Wuling powder is often used to treat clinical hyperlipidemia, although its mechanism of action remains unclear. In this study, we aimed to investigate the active ingredients found in Yinchen Wuling powder and find its mechanism of action when treating hyperlipidemia, using a combination of network pharmacology, molecular docking, and molecular dynamics simulation approaches.MethodsThe TCMSP database was used to obtain the principle active ingredients found in Yinchen Wuling powder and the NCBI and DisGeNet databases were used to obtain the main target genes involved in hyperlipidemia, and the intersectional targets were obtained by EXCEL. We also used Cytoscape 3.7.2 software to construct a "Traditional Chinese Medicine-Active Ingredient-Target" network and use STRING platform to conduct "protein-protein interactional" (PPI) analyses on the intersection targets. Bioconductor software and RX 64 4.0.0 software were then used to perform GO functional enrichment analysis and KEGG pathway enrichment analysis on the targets. Molecular docking of core protein-ligand interactions was modeled using AutoDock Vina software. A simulation of molecular dynamics was conducted for the optimal core protein-ligand obtained by molecular docking using Amber18 software.ResultsA total of 63 active ingredients were found in Yinchen Wuling powder, corresponding to 175 targets, 508 hyperlipidemia targets, and 55 intersection targets in total. Cytoscape 3.7.2 showed that the key active ingredients were quercetin, isorhamnetin, taxifolin, demethoxycapillarisin, and artepillin A. The PPI network showed that the key proteins involved were AKT1, IL6, VEGFA, and PTGS2. GO enrichment analysis found that genes were enriched primarily in response to oxygen levels and nutrient levels of the vesicular lumen and were associated with membrane rafts. These were mainly enriched in AGE-RAGE (advanced glycation end products-receptor for advanced glycation end products) signaling pathway in diabetic complications, fluid shear stress, and atherosclerosis, as well as other pathways. The molecular docking results indicated key binding activity between PTGS2-quercetin, PTGS2-isorhamnetin, and PTGS2-taxifolin. Results from molecular dynamics simulations showed that PTGS2-quercetin, PTGS2-isorhamnetin, and PTGS2-taxifolin bound more stably, and their binding free energies were PTGS2-quercetin -29.5 kcal/mol, PTGS2-isorhamnetin -32 kcal/mol, and PTGS2-taxifolin -32.9 kcal/mol.ConclusionThis study is based on network pharmacology and reveals the potential molecular mechanisms involved in the treatment of hyperlipidemia by Yinchen Wuling powder.

Dataset Information

Exploring the Binding Interaction of Raf Kinase Inhibitory Protein With the N-Terminal of C-Raf Through Molecular Docking and Molecular Dynamics Simulation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets