Ab initio and comparative 3D modeling of FAM222A-encoded protein and target-driven-based virtual screening for the identification of novel therapeutics against Alzheimer's disease
Copyright © 2023. Published by Elsevier Inc..
The complex nature of Alzheimer's disease (AD) makes it difficult to understand the exact molecular processes leading to neuron death. However, two molecular factors - the production of amyloid-beta plaques and tau tangles - are considered to be linked to AD. A genetic marker for brain atrophy, FAM222A, has been identified by the unique cross-phenotype meta-analysis of genetics imaging and the molecular features show an interaction between the protein aggregatin encoded by FAM222A and amyloid beta (Aβ)-peptide (1-42) via its N-terminal Aβ binding domain, thus increasing Aβ aggregation. Function of Aggregatin protein is unclear, and its 3D structure has not been investigated in experimental analysis, so far. Hence, in the present study, first time in literature, 3D models of FAM222A-encoded Aggregatin were systematically constructed by applying diverse homology modeling approaches and they were used as target structures at the virtual screening of FDA-approved drugs and drugs currently under research in clinical trials. Then, the identified hit molecules were chosen for further molecular dynamics (MD) simulations and post-MD analyses. Our integrated ligand-based and protein-driven-based virtual screening results show that Cefpiramide, Diniprofylline, Fostriecin, and Droperidol may target Aggregatin.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:125 |
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| Enthalten in: |
Journal of molecular graphics & modelling - 125(2023) vom: 01. Dez., Seite 108575 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Alabdulraheem, Zeyad Tareq Jasim [VerfasserIn] |
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| Links: |
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| Themen: |
Aggregatin |
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| Anmerkungen: |
Date Completed 25.09.2023 Date Revised 25.09.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jmgm.2023.108575 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM36052544X |
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| 245 | 1 | 0 | |a Ab initio and comparative 3D modeling of FAM222A-encoded protein and target-driven-based virtual screening for the identification of novel therapeutics against Alzheimer's disease |
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| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023. Published by Elsevier Inc. | ||
| 520 | |a The complex nature of Alzheimer's disease (AD) makes it difficult to understand the exact molecular processes leading to neuron death. However, two molecular factors - the production of amyloid-beta plaques and tau tangles - are considered to be linked to AD. A genetic marker for brain atrophy, FAM222A, has been identified by the unique cross-phenotype meta-analysis of genetics imaging and the molecular features show an interaction between the protein aggregatin encoded by FAM222A and amyloid beta (Aβ)-peptide (1-42) via its N-terminal Aβ binding domain, thus increasing Aβ aggregation. Function of Aggregatin protein is unclear, and its 3D structure has not been investigated in experimental analysis, so far. Hence, in the present study, first time in literature, 3D models of FAM222A-encoded Aggregatin were systematically constructed by applying diverse homology modeling approaches and they were used as target structures at the virtual screening of FDA-approved drugs and drugs currently under research in clinical trials. Then, the identified hit molecules were chosen for further molecular dynamics (MD) simulations and post-MD analyses. Our integrated ligand-based and protein-driven-based virtual screening results show that Cefpiramide, Diniprofylline, Fostriecin, and Droperidol may target Aggregatin | ||
| 650 | 4 | |a Meta-Analysis | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Aggregatin | |
| 650 | 4 | |a Alzheimer's disease | |
| 650 | 4 | |a Amyloid-beta | |
| 650 | 4 | |a FAM222A | |
| 650 | 4 | |a MD simulations | |
| 650 | 4 | |a Molecular docking | |
| 650 | 4 | |a Protein modeling | |
| 650 | 7 | |a Amyloid beta-Peptides |2 NLM | |
| 700 | 1 | |a Durdagi, Serdar |e verfasserin |4 aut | |
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