Dataset Information

Identification of new small molecules as dual FoxM1 and Hsp70 inhibitors using computational methods.

ABSTRACT:

Background and purpose

FoxM1 and Hsp70 proteins are highly expressed in many cancers. Thus, their inhibition serves as Bonafede targets in cancer treatment.

Experimental approach

FDI-6, an inhibitor of FoxM1, was selected as a template, and based on its structure, a new library from the ZINC database was obtained. Virtual screening was then performed using the created pharmacophore model. The second virtual screening phase was conducted with molecular docking to get the best inhibitor for both FoxM1 and Hsp70 active sites. In silico, ADMET properties were also calculated. Finally, molecular dynamics simulation was performed on the best ligand, ZINC1152745, for both Hsp70 and FoxM1 proteins during 100 ns.

Findings / results

The results of this study indicated that ZINC1152745 was stable in the active site of both proteins, Hsp70 and FoxM1. The final scaffold identified by the presented computational approach could offer a hit compound for designing promising anticancer agents targeting both FoxM1 and Hsp70.

Conclusion and implications

Molecular dynamics simulations were performed on ZINC1152745 targeting FoxM1 and Hsp70 active sites. The results of several hydrogen bonds, the radius of gyration, RMSF, RMSD, and free energy during the simulations showed good stability of ZINC1152745 with FoxM1 and Hsp70.

SUBMITTER: Alimardan Z

PROVIDER: S-EPMC9872178 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of new small molecules as dual FoxM1 and Hsp70 inhibitors using computational methods.

Alimardan Zahra Z Abbasi Maryam M Khodarahmi Ghadamali G Kashfi Khosrow K Hasanzadeh Farshid F Mahmud Aghaei A

Research in pharmaceutical sciences 20221029 6

<h4>Background and purpose</h4>FoxM1 and Hsp70 proteins are highly expressed in many cancers. Thus, their inhibition serves as Bonafede targets in cancer treatment.<h4>Experimental approach</h4>FDI-6, an inhibitor of FoxM1, was selected as a template, and based on its structure, a new library from the ZINC database was obtained. Virtual screening was then performed using the created pharmacophore model. The second virtual screening phase was conducted with molecular docking to get the best inhib ...[more]

PMID: 36704430

Similar Datasets

Project description:BackgroundWith the emergence of new influenza virus strains that are resistant to current inhibitors such as oseltamivir (anti-neuraminidase (NA)) and amantadine (anti-M2 proton channel), influenza A viruses continue to be a serious threat to the public health worldwide. With this in view, there is a persistent need for the development of broader and more effective vaccines and therapeutics. Identification of broadly neutralizing antibodies (bNAbs) that recognize relatively invariant structures ‎on influenza haemagglutinin (HA) stem has invigorated efforts to develop universal influenza vaccines.AimThe current computational study is designed to identify potential flavonoid inhibitors that bind to the contact epitopes of HA stem that are targeted by broadly neutralizing antibodies (bNAb).MethodIn this study, we utilized the three-dimensional crystallographic structure of different HA subtypes (H1, H2, H5, H3, and H7) in complex with bNAb to screen for potential broadly reactive influenza inhibitors. We performed Quantitative Structure-Activity and Relationship (QSAR) for 100 natural compounds known for their antiviral activity and performed molecular docking using AutoDock 4.2 suite. Furthermore, we conducted virtual screening of 1413 bioassay hit compounds by using virtual lab bench CLC Drug Discovery.ResultsThe results showed 18 lead flavonoids with strong binding abilities to bNAb epitopes of various HA subtypes. These 18 broadly reactive compounds exhibited significant interactions with an average of seven Hbonds, docking energy of -22.43 kcal·mol-1, and minimum interaction ‎ energy of -4.65 kcal·mol-1, with functional contact residues. Procyanidin depicted strong interactions with group 1 HAs, whereas both sorbitol and procyanidin exhibited significant interactions with group 2 HAs.ConclusionUsing in silico docking analysis, we identified 18 bioactive flavonoids with potential strong binding cababilities to influenza HA-stems of various subtypes, which are the target for bNAb. The virtual screened bioassay hit compounds depicted a high number of Hbonds but low interaction and docking values compared to antiviral flavonoids. Using structure-based design and nanotechnology-based approaches, identified molecules could be modified to generate next generation anti-influenza drugs.

Dataset Information

Identification of new small molecules as dual FoxM1 and Hsp70 inhibitors using computational methods.

Background and purpose

Experimental approach

Findings / results

Conclusion and implications

Publications

Identification of new small molecules as dual FoxM1 and Hsp70 inhibitors using computational methods.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets