Journal Article FZJ-2023-01001

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Predictions of the Poses and Affinity of a Ligand over the Entire Surface of a NEET Protein: The Case of Human MitoNEET

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2023
American Chemical Society Washington, DC

Journal of chemical information and modeling 63(2), 643 - 654 () [10.1021/acs.jcim.2c01280]

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Abstract: Human NEET proteins contain two [2Fe–2S] iron–sulfur clusters, bound to three Cys residues and one His residue. They exist in two redox states. Recently, these proteins have revealed themselves as attractive drug targets for mitochondrial dysfunction-related diseases, such as type 2 diabetes, Wolfram syndrome 2, and cancers. Unfortunately, the lack of information and mechanistic understanding of ligands binding to the whole functional, cytoplasmatic domain has limited rational drug design approaches. Here, we use an enhanced sampling technique, volume-based metadynamics, recently developed by a team involving some of us, to predict the poses and affinity of the 2-benzamido-4-(1,2,3,4-tetrahydronaphthalen-2-yl)-thiophene-3-carboxylate ligand to the entire surface of the cytoplasmatic domain of the human NEET protein mitoNEET (mNT) in an aqueous solution. The calculations, based on the recently published X-ray structure of the complex, are consistent with the measured affinity. The calculated free energy landscape revealed that the ligand can bind in multiple sites and with poses other than the one found in the X-ray. This difference is likely to be caused by crystal packing effects that allow the ligand to interact with multiple adjacent NEET protein copies. Such extra contacts are of course absent in the solution; therefore, the X-ray pose is only transient in our calculations, where the binding free energy correlates with the number of contacts. We further evaluated how the reduction and protonation of the Fe-bound histidine, as well as temperature, can affect ligand binding. Both such modifications introduce the possibility for the ligand to bind in an area of the protein other than the one observed in the X-ray, with no or little impact on affinity. Overall, our study can provide insights on the molecular recognition mechanisms of ligand binding to mNT in different oxidative conditions, possibly helping rational drug design of NEET ligands.

Classification:

Contributing Institute(s):
  1. Computational Biomedicine (IAS-5)
  2. Computational Biomedicine (INM-9)
  3. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 5241 - Molecular Information Processing in Cellular Systems (POF4-524) (POF4-524)
  2. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2023
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Medline ; Embargoed OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; Essential Science Indicators ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Dokumenttypen > Aufsätze > Zeitschriftenaufsätze
Institutssammlungen > IAS > IAS-5
Institutssammlungen > INM > INM-9
Workflowsammlungen > Öffentliche Einträge
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Institutssammlungen > JSC
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Open Access

 Datensatz erzeugt am 2023-01-26, letzte Änderung am 2024-06-25


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