Searching for potential mTOR inhibitors: Ligand-based drug design, docking and molecular dynamics studies of rapamycin binding site

Kist, Roger; Timmers, Luís Fernando Saraiva Macedo; Caceres, Rafael Andrade

doi:10.1016/j.jmgm.2017.12.015

Cited by 15 publications

(6 citation statements)

References 69 publications

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“…Instead, it relies on knowledge of known molecules binding to the target macromolecule of interest. Using these known molecules, a pharmacophore model that defines the minimum necessary structural characteristics a molecule must possess in order to bind to the target can be derived [48,49]. Then, this model can be further used to design new molecular entities that interact with the target.…”

Section: Ligand-based Drug Designmentioning

confidence: 99%

A Review on Applications of Computational Methods in Drug Screening and Design

2020

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Drug development is one of the most significant processes in the pharmaceutical industry. Various computational methods have dramatically reduced the time and cost of drug discovery. In this review, we firstly discussed roles of multiscale biomolecular simulations in identifying drug binding sites on the target macromolecule and elucidating drug action mechanisms. Then, virtual screening methods (e.g., molecular docking, pharmacophore modeling, and QSAR) as well as structure-and ligand-based classical/de novo drug design were introduced and discussed. Last, we explored the development of machine learning methods and their applications in aforementioned computational methods to speed up the drug discovery process. Also, several application examples of combining various methods was discussed. A combination of different methods to jointly solve the tough problem at different scales and dimensions will be an inevitable trend in drug screening and design.Molecules 2020, 25, 1375 2 of 17 Biomolecular Simulations in Drug Screening and DesignThe Nobel Prize in Chemistry 2013 was awarded jointly to Martin Karplus, Michael Levitt, and Arieh Warshel for their pioneering contributions in the development of multiscale models for complex biochemical systems, recognizing the important role that theory and computational methods play as a direct and necessary complement to experiments [12]. Further, applications of biomolecular simulations in identifying drug binding sites and elucidating the molecular mechanisms of diseases have been subject to rapid developments [13][14][15].Depending on the biological problems to be studied, multiscale models will be used in biomolecular simulations. The combination of quantum mechanics (QM) and molecular mechanics (MM) (QM/MM) can be used to study the electronic properties [16], simulate chemical reactions (e.g., the enzyme catalysis mechanism [17]), and calculate spectra [18] in a single simulation, which can be used to elucidate the action mechanism of certain drugs. Another widely used biomolecular method is molecular dynamics (MD) simulation [19][20][21][22][23][24], which applies empirical molecular mechanics (MM) force fields and is based on classical Newtonian mechanics. According to different accuracy requirements, all-atom (AA), united-atom (UA), and coarse-grained (CG) MD simulations as well as explicit/implicit solvent models, which allow simulations of temporal and spatial scales, can be used to facilitate the drug discovery [25,26]. Generally, MD simulations have been used for the identification of potential drug binding sites on target proteins, the calculation of binding free energy between target proteins and drug molecules, the action mechanism of drug molecules, etc. [27,28]. However, it is worth mentioning that MD simulations are also limited to time and length scales. Currently, AAMD simulations can explore time-dependent phenomena of large systems such as viral capsids in atomic detail as long as microseconds or even milliseconds [21,29,30]. Therefore, different types of ...

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Section: Ligand-based Drug Designmentioning

confidence: 99%

A Review on Applications of Computational Methods in Drug Screening and Design

2020

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“…The affinity of the molecules against their target proteins were generated with computational techniques. Molecular docking is a method of binding orientation prediction of molecules with protein targets ( 10 ). Therefore, molecular docking is regarded as a vital technique in drug design.…”

Section: Introductionmentioning

confidence: 99%

Identification of MMP9 as a novel key gene in mantle cell lymphoma based on bioinformatic analysis and design of cyclic peptides as MMP9 inhibitors based on molecular docking

Yan

Wei

et al. 2018

Oncol Rep

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Mantle cell lymphoma (MCL) is an aggressive disease. MCL is associated with poor patient prognosis and limited survival. To identify key genes and explore targeting cyclic peptide inhibitors for the treatment of MCL, we downloaded two gene expression profiles (GSE32018 and GSE9327) from the Gene Expression Omnibus (GEO) database. We screened 84 differentially expressed genes (DEGs). Pathway analysis showed that DEMs were mainly enriched in the ‘Pathway in cancer’, ‘PI3K-Akt signaling pathway’, ‘Cytokine-cytokine receptor interaction’, ‘Rap1 signaling pathway’, ‘NF-κB signaling pathway’ and ‘Leukocyte trans-endothelial migration’. We subsequently constructed a protein-protein interaction (PPI) network of DEGs. In addition, matrix metalloproteinase 9 (MMP9) with a high degree in the PPI network was identified as a hub gene in MCL. Meanwhile in the Molecular Complex Detection (MCODE) analysis, MMP9 was located in the important cluster. Thus, MMP9 can be used as a therapeutic target for MCL and we designed cyclic peptides as MMP9 inhibitors. MMP9 protein structure was gathered from the Protein Data Bank (PDB), with a PDB ID: 1L6J. MMP9 and cyclic peptides were docked using Molecular Operating Environment (MOE) software after structural optimization. It was revealed that cyclic peptide 2 bound deeply in the binding pocket of MMP9 and had interaction with the active-site Zn2+ ion in the catalytic domain. Cyclic peptides 1, 2, 4–6 also displayed potential interaction with active residues of MMP9; thus, these cyclic peptides can serve as potential drug candidates to block MMP9 activity and future studies are warranted to confirm their efficacy.

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“…Molecular docking is a quick and effective method of predicting the binding affinity between TCM ingredients and their targets based on the spatial structure of ligands and receptors (Gan et al, 2019). Molecular docking analysis was conducted by using AutoDock Vina software, which may serve as the AutoDock successor docking analysis, due to its effect on apparently improving performance and accuracy in comparison with those of Lamarckian Genetic Algorithm (Kist et al, 2018). Based on results of network pharmacology, it was known that flavonoids can possibly suppress liver fibrosis by inhibiting the IL-17 signaling pathway, which includes NF-κB, AP-1, IL-6, IL-1β, TNFα, IFN-γ, CCL2, COX2, MMP1, MMP3, and MMP9.…”

Section: Discussionmentioning

confidence: 99%

Integrating Network Pharmacology and Experimental Validation to Investigate the Effects and Mechanism of Astragalus Flavonoids Against Hepatic Fibrosis

Lin

et al. 2021

Front. Pharmacol.

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Hepatic fibrosis (HF) represents the excessive wound healing where an excess amount of connective tissues is formed within the liver, finally resulting in cirrhosis or even hepatocellular carcinoma (HCC). Therefore, it is significant to discover the efficient agents and components to treat HF, thus restraining the further progression of hepatopathy. Astragalus membranaceus (Fisch.) Bunge [also called Astragali Radix (AR)] is a famous herb in traditional Chinese medicine (TCM), which possesses a variety of biological activities and exerts good therapeutic effects in the treatment of HF. Flavonoids account for the major active ingredients related to the AR pharmacological effects. Total AR flavonoids have been proved to exert inhibitory effects on hepatic fibrosis. This study aimed to further undertake network pharmacology analysis coupled with experimental validation and molecular docking to investigate the effects and mechanism of multiple flavonoid components from AR against liver fibrosis. The results of the network pharmacology analysis showed that the flavonoids from AR exerted their pharmacological effects against liver fibrosis by modulating multiple targets and pathways. The experimental validation data showed that the flavonoids from AR were able to suppress transforming growth factor beta 1 (TGF-β1)-mediated activation of hepatic stellate cells (HSCs) and reduce extracellular matrix deposition in HSC-T6 cells via regulating the nuclear factor kappa B (NF-κB) signal transduction pathway. The results of the molecular docking study further showed that the flavonoids had a strong binding affinity for IκB kinase (IKKβ) after docking into the crystal structure. The above results indicated that, flavonoids possibly exerted the anti-inflammatory effect on treating HF by mediating inflammatory signaling pathways. The potential mechanism of these flavonoids against liver fibrosis may be related to suppression of the NF-κB pathway through effective inhibition of IKKβ. This study not only provides a scientific basis for clarifying the effects and mechanism of AR flavonoids against liver fibrosis but also suggests a novel promising therapeutic strategy for the treatment of liver fibrosis.

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Searching for potential mTOR inhibitors: Ligand-based drug design, docking and molecular dynamics studies of rapamycin binding site

Cited by 15 publications

References 69 publications

A Review on Applications of Computational Methods in Drug Screening and Design

A Review on Applications of Computational Methods in Drug Screening and Design

Identification of MMP9 as a novel key gene in mantle cell lymphoma based on bioinformatic analysis and design of cyclic peptides as MMP9 inhibitors based on molecular docking

Integrating Network Pharmacology and Experimental Validation to Investigate the Effects and Mechanism of Astragalus Flavonoids Against Hepatic Fibrosis

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