Evaluation of novel Akt1 inhibitors as anticancer agents using virtual co-crystallized pharmacophore generation

Al-Sha’er, Mahmoud A.; Mansi, Iman; Almazari, Inas; Hakooz, Nancy

doi:10.1016/j.jmgm.2015.10.004

Cited by 19 publications

(8 citation statements)

References 27 publications

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“…The fundamental use of pharmacophores models is the discovery of new chemical scaffolds demonstrating similar biological characteristics or scaffold hopping [56][57][58][59][60][61][62][63][64][65][83][84][85]. Therefore, Refined-Hypo (SB-1) pharmacophore (Figure 2) was used as a 3D query to search and screen the NCI list of compounds for new Aurora-A kinase inhibitors with novel chemotypes.…”

Section: In-silico Screening and Fret Based Enzyme Inhibition Assaymentioning

confidence: 99%

Structure-Based Discovery and Bioactivity Evaluation of Novel Aurora-A Kinase Inhibitors as Anticancer Agents via Docking-Based Comparative Intermolecular Contacts Analysis (dbCICA)

2020

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Aurora-A kinase plays a central role in mitosis, where aberrant activation contributes to cancer by promoting cell cycle progression, genomic instability, epithelial-mesenchymal transition, and cancer stemness. Aurora-A kinase inhibitors have shown encouraging results in clinical trials but have not gained Food and Drug Administration (FDA) approval. An innovative computational workflow named Docking-based Comparative Intermolecular Contacts Analysis (dbCICA) was applied—aiming to identify novel Aurora-A kinase inhibitors—using seventy-nine reported Aurora-A kinase inhibitors to specify the best possible docking settings needed to fit into the active-site binding pocket of Aurora-A kinase crystal structure, in a process that only potent ligands contact critical binding-site spots, distinct from those occupied by less-active ligands. Optimal dbCICA models were transformed into two corresponding pharmacophores. The optimal one, in capturing active hits and discarding inactive ones, validated by receiver operating characteristic analysis, was used as a virtual in-silico search query for screening new molecules from the National Cancer Institute database. A fluorescence resonance energy transfer (FRET)-based assay was used to assess the activity of captured molecules and five promising Aurora-A kinase inhibitors were identified. The activity was next validated using a cell culture anti-proliferative assay (MTT) and revealed a most potent lead 85(NCI 14040) molecule after 72 h of incubation, scoring IC50 values of 3.5–11.0 μM against PANC1 (pancreas), PC-3 (prostate), T-47D and MDA-MB-231 (breast)cancer cells, and showing favorable safety profiles (27.5 μM IC50 on fibroblasts). Our results provide new clues for further development of Aurora-A kinase inhibitors as anticancer molecules.

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Section: In-silico Screening and Fret Based Enzyme Inhibition Assaymentioning

confidence: 99%

Structure-Based Discovery and Bioactivity Evaluation of Novel Aurora-A Kinase Inhibitors as Anticancer Agents via Docking-Based Comparative Intermolecular Contacts Analysis (dbCICA)

2020

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“…Additionally, given that hydrogen atoms cannot be seen by X-ray, it is challenging to predict the ionization state of complexed ligands. [103][104][105][106][107] These issues prompted us to complement pharmacophore models extracted from crystallographic Fig. 5 ML-selected ligand-based pharmacophore models generated by supervised modelling (HYPOGEN), Hypo-LB5 (details are as in Table 1).…”

Section: Resultsmentioning

confidence: 99%

Discovery of new potent lysine specific histone demythelase-1 inhibitors (LSD-1) using structure based and ligand based molecular modelling and machine learning

2022

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“…The "Ligand Pro ler" tool was utilized to scrutinize the capability of the engendered pharmacophores to retrieve active main protease inhibitors from a library of 1281 FDA drugs, as illustrated in Table 3 (11,12). Lopinavir scored the highest t value for the sum of the two pharmacophores (6.84), in which it scored the highest on Hypo(6LU7_2_02) with a tting value of 3.66.…”

Section: Pharmacophore Mappingmentioning

confidence: 99%

“…In this work, a rational methodology based on CADD techniques was employed to repurpose the currently available FDAapproved drugs for the treatment of COVID-19, which has the advantage of saving time and rescuing infected people by giving them possible inhibitors of the main protease enzyme. Structure-based and ligand-based techniques were used in this research in this work by subjecting the FDA approved drug to different selection criteria aiming to reach drugs with high a nity to the enzyme (11,12).…”

Section: Introductionmentioning

confidence: 99%

Repurposing FDA-approved drugs against the “main protease” pivotal enzyme in COVID-19 virus using computer-aided drug design techniques

Al-Sha’er

Balas

2021

Preprint

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Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is considered an unprecedented global pandemic in the modern era, infecting millions of people with an approximately 2% death rate. It emerged in late 2019 and researchers worldwide race time to identify druggable targets where medicinal chemists can design potential inhibitors. Objective: Drug repurposing is one of the most convenient methods available now to find already approved drugs for human use with a potential tendency to cure COVID-19. Method: Within this work, the FDA-approved drug database containing 1281 drugs was employed to extract possible drugs that could have activity against the “main protease” enzyme in this virus. Various computer-aided drug design techniques, such as pharmacophore generation, ligand pharmacophore mapping, molecular docking and filtering techniques, were used to identify potential inhibitors. The cocrystallized ligand inside the main protease enzyme was utilized to generate two structure-based pharmacophores that were used as templates for deletion in the FDA database. To validate the selection of the active hits from pharmacophore mapping, molecular docking via “LibDock” was performed, while the highest scoring candidate was selected. Results: Interestingly, three antiviral drugs (lopinavir, saquinavir and remdesivir) were qualified to be potential main protease inhibitors. Conclusion: The researchers in this work recommend clinically investigating the possibility of these drugs as preliminary therapies until selective drugs for COVID-19 virus are approved.

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Evaluation of novel Akt1 inhibitors as anticancer agents using virtual co-crystallized pharmacophore generation

Cited by 19 publications

References 27 publications

Structure-Based Discovery and Bioactivity Evaluation of Novel Aurora-A Kinase Inhibitors as Anticancer Agents via Docking-Based Comparative Intermolecular Contacts Analysis (dbCICA)

Structure-Based Discovery and Bioactivity Evaluation of Novel Aurora-A Kinase Inhibitors as Anticancer Agents via Docking-Based Comparative Intermolecular Contacts Analysis (dbCICA)

Discovery of new potent lysine specific histone demythelase-1 inhibitors (LSD-1) using structure based and ligand based molecular modelling and machine learning

Repurposing FDA-approved drugs against the “main protease” pivotal enzyme in COVID-19 virus using computer-aided drug design techniques

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