Discovery of potential HER2 inhibitors from <i>Mangifera indica</i> for the treatment of HER2-Positive breast cancer: an integrated computational approach

Balogun, Toheeb Adewale; Iqbal, Muhammad Nasir; Saibu, Oluwatosin A.; Akintubosun, Michael Olawale; Lateef, Olubodun Michael; Nneka, Uche Catherine; Abdullateef, Olayemi Taye; Omoboyowa, Damilola Alex

doi:10.1080/07391102.2021.1975570

Cited by 31 publications

(3 citation statements)

References 57 publications

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“…The structural and energy information between the protein–ligand complexes was considered for energetic computation and further stability studies. The 2D interaction profile of protein–ligand complexes was generated using the Ligand Interaction Diagram (LID) in Maestro ( Friesner et al, 2004 ; Balogun et al, 2021b ). The reproducibility and reliability of the docking procedure were validated by superimposing and re-docking the co-crystalized ligand structures into the target active site, which generated an RMSD value of 0.76 A (normal range: 0–2 A).…”

Section: Methodsmentioning

confidence: 99%

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

et al. 2022

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SARS-CoV-2 triggered a worldwide medical crisis, affecting the world’s social, emotional, physical, and economic equilibrium. However, treatment choices and targets for finding a solution to COVID-19’s threat are becoming limited. A viable approach to combating the threat of COVID-19 is by unraveling newer pharmacological and therapeutic targets pertinent in the viral survival and adaptive mechanisms within the host biological milieu which in turn provides the opportunity to discover promising inhibitors against COVID-19. Therefore, using high-throughput virtual screening, manually curated compounds library from some medicinal plants were screened against four main drivers of SARS-CoV-2 (spike glycoprotein, PLpro, 3CLpro, and RdRp). In addition, molecular docking, Prime MM/GBSA (molecular mechanics/generalized Born surface area) analysis, molecular dynamics (MD) simulation, and drug-likeness screening were performed to identify potential phytodrugs candidates for COVID-19 treatment. In support of these approaches, we used a series of computational modeling approaches to develop therapeutic agents against COVID-19. Out of the screened compounds against the selected SARS-CoV-2 therapeutic targets, only compounds with no violations of Lipinski’s rule of five and high binding affinity were considered as potential anti-COVID-19 drugs. However, lonchocarpol A, diplacol, and broussonol E (lead compounds) were recorded as the best compounds that satisfied this requirement, and they demonstrated their highest binding affinity against 3CLpro. Therefore, the 3CLpro target and the three lead compounds were selected for further analysis. Through protein–ligand mapping and interaction profiling, the three lead compounds formed essential interactions such as hydrogen bonds and hydrophobic interactions with amino acid residues at the binding pocket of 3CLpro. The key amino acid residues at the 3CLpro active site participating in the hydrophobic and polar inter/intra molecular interaction were TYR54, PRO52, CYS44, MET49, MET165, CYS145, HIS41, THR26, THR25, GLN189, and THR190. The compounds demonstrated stable protein–ligand complexes in the active site of the target (3CLpro) over a 100 ns simulation period with stable protein–ligand trajectories. Drug-likeness screening shows that the compounds are druggable molecules, and the toxicity descriptors established that the compounds demonstrated a good biosafety profile. Furthermore, the compounds were chemically reactive with promising molecular electron potential properties. Collectively, we propose that the discovered lead compounds may open the way for establishing phytodrugs to manage COVID-19 pandemics and new chemical libraries to prevent COVID-19 entry into the host based on the findings of this computational investigation.

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Section: Methodsmentioning

confidence: 99%

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

et al. 2022

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“…Molecular docking is a computational approach that predicts the interaction between receptor-ligand complexes through binding orientation of the ligands in the active site of the protein and ranking score of the interactions (Balogun et al, 2021). To predict potent inhibitors of PDE-5 for the management of erectile dysfunction, small molecules from Aframomum melegueta were screened against the binding site of PDE-5 with the binding a nity estimated using three glide ltering procedures.…”

Section: Post-docking Analysis and Binding Free Energy Estimationmentioning

confidence: 99%

Deciphering Phosphodiesterase-5 Inhibitors from Aframemum melegueta: Computational Models against Erectile dysfunction

Omoboyowa

2023

Preprint

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Insufficient and inability to maintain erection in male for satisfactory sexual performance remains global challenge among couples. The identification of phosphodiesterase-5 (PDE-5) antagonist in the pathogenesis of erectile dysfunction has improved the search for therapeutic agents for the management of this sexual dysfunction. Here in, bioactive compounds from Aframomum melegueta were virtually screened against PDE-5 using Schrodinger suite 2017-1 as computational tool. The lead compound was further validated in comparison with Viagra by performing 100 ns molecular dynamics (MD) simulation using Desmond. Among 109 bioactive compounds screened, nine (9) molecules were predicted as potent inhibitors of PDE-5 with binding affinities comparable to the co-crystalized ligand (sildenafil). 1,7-bis(3,4-dihyroxy-5-methoxyphenyl)heptane-3,5-diyldiacetate was observed to have the best docking score (-11.522 kcal/mol) among the hit compounds which is very close to the co-crystalized ligand (-11.872 kcal/mol). Validation using pharmacophore hypothesis and QSAR modeling further confirmed the prediction of the hit compounds with fitness score ranging from 0.754 to 2.605 and predicted pIC50 of 3.835 to 7.976 µM. All the hit compounds obeyed Lipinski’s rule of five and within the reference range of the pharmacokinetics parameters. The MD simulation result predicted the stability of 1,7-bis(3,4-dihydroxy-5-methoxyphenyl)heptane-3,5-diyldiacetate-PDE-5 complex comparable to the sildenafil-PDE-5 complex. The outcome of this study predicted nine molecules from A. melegueta as potent PDE-5 antagonists which required isolation and experimental validation for the management of erectile dysfunction.

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“…Based on in silico study by Balogun et al, 2021 Anticancer potential of isolated phytocompounds from Macaranga denticulate against breast cancer was studied by Zaheed and his colleagues (2016) where compound 3-acetylaleuritolic acid, β-sitosterol, macarangin, oleanic acid, scopoletin and stigmasterol were docked with estrogen receptor alpha with docking score of -4.482, -5.795, -6.647, -2.406, -6.569, and -5.822 respectively. Out of the six compounds, macarangin was shown to be the best compound for selective inhibitors of the estrogen receptor.…”

Section: Toxicity Evaluation Of Plant Compoundsmentioning

confidence: 99%

Dimocarpus longan phytocompounds possess anticancer activity by specifically targeting breast cancer biomarkers via computational biology tools

Elengoe

Suhaibun

2022

ijhs

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Worldwide, breast cancer (BC) is the most common cancer among women. Natural plant compounds with anticancer potential can block BC biomarkers, but they must be chosen carefully to avoid adverse side effects. In this research, the interaction between the BC biomarkers and plant compounds from Dimocarpus Longan was studied using a molecular docking approach. Twenty plant constituents from longan and two target proteins considered involved in BC (1ERR: Estrogen receptor and 3D90: Progesterone receptor) were obtained from the PubChem database and RCSB Protein Data Bank (PDB) respectively. They were docked using the SwissDock server. Then, the drug-likeness of the plant compounds that demonstrated interaction was evaluated. The results show that 1ERR and 3D90 had the lowest binding affinity with the L-epicatechin at the value of -9.5 and -8.3 kcal/mol respectively. These proteins had the most stable interaction with their plant compounds. The toxicity prediction analysis revealed that L-epicatechin is not safe to use as a drug due to AMES toxicity. All of the ten compounds had low binding scores, indicating that they had good interactions. Therefore, α-terpineol was chosen to use as a safe drug. The findings of this study should aid pharmaceutical researchers in identifying longan-based medications.

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Discovery of potential HER2 inhibitors from Mangifera indica for the treatment of HER2-Positive breast cancer: an integrated computational approach

Cited by 31 publications

References 57 publications

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

Deciphering Phosphodiesterase-5 Inhibitors from Aframemum melegueta: Computational Models against Erectile dysfunction

Dimocarpus longan phytocompounds possess anticancer activity by specifically targeting breast cancer biomarkers via computational biology tools

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