Molecular Docking Simulations with ArgusLab

Bitencourt-Ferreira, Gabriela; Azevedo, Walter Filgueira de

doi:10.1007/978-1-4939-9752-7_13

Cited by 27 publications

(13 citation statements)

References 61 publications

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“…The present study used various photochemical methods to analyze and derive the 3D structures of 22 compounds from A. paniculate, 4 from T. laurifolia, 9 from T. crispa L, 11 from S. suberosa and 15 from C. verum and examined the effects of these compounds on blood glucose levels and the inhibition of AG using AutoDock, AutoDock Vina and ArgusLab [32,33,34,35,36]. Chemical binding was visualized by Discovery Studio [37].…”

Section: Introductionmentioning

confidence: 99%

Computational study and in vitro alpha-glucosidase inhibitory effects of medicinal plants from a Thai folk remedy

Eawsakul

Panichayupakaranant

Ongtanasup

et al. 2021

Heliyon

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The number of patients with type 2 diabetes mellitus (T2DM) has increased worldwide. Although an instant cure was achieved with the standard treatment acabose, unsatisfactory symptoms associated with cardiovascular disease after acabose administration have been reported. Therefore, it is important to explore new treatments. A Thai folk recipe has long been used for T2DM treatment, and it effectively decreases blood glucose. However, the mechanism of this recipe has never been proven. Therefore, the potential anti-T2DM effect of this recipe, which is used in Thai hospitals, was determined to involve alpha-glucosidase (AG) inhibition with a half maximal inhibitory concentration (IC 50 ). In vitro experiments showed that crude Cinnamomum verum extract (IC 50 ¼ 0.35 AE 0.12 mg/mL) offered excellent inhibitory activity, followed by extracts from Tinospora crispa (IC 50 ¼ 0.69 AE 0.39 mg/ mL), Stephania suberosa (IC 50 ¼ 1.50 AE 0.17 mg/mL), Andrographis paniculate (IC 50 ¼ 1.78 AE 0.35 mg/mL), and Thunbergia laurifolia (IC 50 ¼ 4.66 AE 0.27 mg/mL). However, the potencies of these extracts were lower than that of acabose (IC 50 ¼ 0.55 AE 0.11 mg/mL). Therefore, this study investigated and developed a formulation of this recipe using computational docking. Among 61 compounds, 7 effectively inhibited AG, including chlorogenic acid (IC 50 ¼ 819.07 pM) through 5 hydrogen bonds (HBs) and 2 hydrophobic interactions (HIs); β-sitosterol (IC 50 ¼ 4.46 nM, 6 HIs); ergosterol peroxide (IC 50 ¼ 4.18 nM, 6 HIs); borapetoside D (IC 50 ¼ 508.63 pM, 7 HBs and 2 HIs); borapetoside A (IC 50 ¼ 1.09 nM, 2 HBs and 2 His), stephasubimine (IC 50 ¼ 285.37 pM, 6 HIs); and stephasubine (IC 50 ¼ 1.09 nM, 3 HBs and 4 HIs). These compounds bind with high affinity to different binding pockets, leading to additive effects. Moreover, the pharmacokinetics of six of these seven compounds (except ergosterol peroxide) showed poor absorption in the gastrointestinal tract, which would allow for competitive binding to AG in the small intestine. These results indicate that the development of these 6 compounds into oral antidiabetic agents is promising.

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Section: Introductionmentioning

confidence: 99%

Computational study and in vitro alpha-glucosidase inhibitory effects of medicinal plants from a Thai folk remedy

Eawsakul

Panichayupakaranant

Ongtanasup

et al. 2021

Heliyon

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“…Based on our prediction and known protein–ligand structural complexes, we performed the molecular docking of predicted inhibitors to 3CLpro. Four inhibitors, Z56899184, Z57728899, Z57013003 and Z1245218850, were docked to 3CLpro using ArgusLab [ 20 ]. For each compound, the best pose with the lowest binding affinity from the ArgusLab docking results was selected.…”

Section: Resultsmentioning

confidence: 99%

Prediction of Potential Commercially Available Inhibitors against SARS-CoV-2 by Multi-Task Deep Learning Model

Jiang

Yin

2022

Biomolecules

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The outbreak of COVID-19 caused millions of deaths worldwide, and the number of total infections is still rising. It is necessary to identify some potentially effective drugs that can be used to prevent the development of severe symptoms, or even death for those infected. Fortunately, many efforts have been made and several effective drugs have been identified. The rapidly increasing amount of data is of great help for training an effective and specific deep learning model. In this study, we propose a multi-task deep learning model for the purpose of screening commercially available and effective inhibitors against SARS-CoV-2. First, we pretrained a model on several heterogenous protein–ligand interaction datasets. The model achieved competitive results on some benchmark datasets. Next, a coronavirus-specific dataset was collected and used to fine-tune the model. Then, the fine-tuned model was used to select commercially available drugs against SARS-CoV-2 protein targets. Overall, twenty compounds were listed as potential inhibitors. We further explored the model interpretability and exhibited the predicted important binding sites. Based on this prediction, molecular docking was also performed to visualize the binding modes of the selected inhibitors.

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“…While FunFOLD was used to predict the ligand-binding site residues, using ligand-containing structures (from the PDB database) as templates and the default settings for homology-based modeling [ 55 , 56 ], FunFOLDQA was used to assess the 3D-model accuracy [ 57 ]. The top-ranked model of the Eh HAPp49 active site (saved as a PDB file) was used as the receptor for molecular docking simulations with ArgusLab (Planaria Software LLC; Seattle, WA) [ 58 ]. Ligands (pNPP, phytic acid, and PPi) were simulated based on 3D structures (SDF files), retrieved from PDB ( , accessed on 5 October 2020) and converted to Mol files with OpenBabel 3.0 [ 59 ].…”

Section: Methodsmentioning

confidence: 99%

Structure–Function Relationship Study of a Secretory Amoebic Phosphatase: A Computational-Experimental Approach

Terán-Ramírez

Mares-Alejandre

Estrada-González

et al. 2021

IJMS

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Phosphatases are hydrolytic enzymes that cleave the phosphoester bond of numerous substrates containing phosphorylated residues. The typical classification divides them into acid or alkaline depending on the pH at which they have optimal activity. The histidine phosphatase (HP) superfamily is a large group of functionally diverse enzymes characterized by having an active-site His residue that becomes phosphorylated during catalysis. HP enzymes are relevant biomolecules due to their current and potential application in medicine and biotechnology. Entamoeba histolytica, the causative agent of human amoebiasis, contains a gene (EHI_146950) that encodes a putative secretory acid phosphatase (EhHAPp49), exhibiting sequence similarity to histidine acid phosphatase (HAP)/phytase enzymes, i.e., branch-2 of HP superfamily. To assess whether it has the potential as a biocatalyst in removing phosphate groups from natural substrates, we studied the EhHAPp49 structural and functional features using a computational-experimental approach. Although the combined outcome of computational analyses confirmed its structural similarity with HP branch-2 proteins, the experimental results showed that the recombinant enzyme (rEhHAPp49) has negligible HAP/phytase activity. Nonetheless, results from supplementary activity evaluations revealed that rEhHAPp49 exhibits Mg2+-dependent alkaline pyrophosphatase activity. To our knowledge, this study represents the first computational-experimental characterization of EhHAPp49, which offers further insights into the structure–function relationship and the basis for future research.

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Molecular Docking Simulations with ArgusLab

Cited by 27 publications

References 61 publications

Computational study and in vitro alpha-glucosidase inhibitory effects of medicinal plants from a Thai folk remedy

Computational study and in vitro alpha-glucosidase inhibitory effects of medicinal plants from a Thai folk remedy

Prediction of Potential Commercially Available Inhibitors against SARS-CoV-2 by Multi-Task Deep Learning Model

Structure–Function Relationship Study of a Secretory Amoebic Phosphatase: A Computational-Experimental Approach

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