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1.
Chembiochem ; 19(6): 591-595, 2018 03 16.
Article in English | MEDLINE | ID: mdl-29282826

ABSTRACT

14-3-3 Proteins play a central role in signalling pathways in cells: they interact as gatekeeper proteins with a huge number of binding partners. Their function as hub for intracellular communication can explain why these adapter proteins are associated with a wide range of diseases. How they control the various cellular mechanisms is still unclear, but it is assumed that the dimeric nature of the 14-3-3 proteins plays a key role in their activity. Here, we present, to the best of our knowledge, the first example of a small molecule binding to the 14-3-3ζ dimerisation interface. This compound was designed by rational in silico optimisation of a peptidic ligand identified from biochemical screening of a peptidic library, and the binding was characterised by UV/Vis spectroscopy, microscale thermophoresis, multiscale simulations, and X-ray crystallography.


Subject(s)
14-3-3 Proteins/antagonists & inhibitors , Drug Design , Peptides/pharmacology , Small Molecule Libraries/pharmacology , 14-3-3 Proteins/metabolism , Binding Sites/drug effects , Crystallography, X-Ray , Dimerization , Humans , Ligands , Models, Molecular , Molecular Structure , Peptides/chemical synthesis , Peptides/chemistry , Small Molecule Libraries/chemical synthesis , Small Molecule Libraries/chemistry
2.
J Chem Inf Model ; 58(2): 315-327, 2018 02 26.
Article in English | MEDLINE | ID: mdl-29266929

ABSTRACT

Many biologically important ligands of proteins are large, flexible, and in many cases charged molecules that bind to extended regions on the protein surface. It is infeasible or expensive to locate such ligands on proteins with standard methods such as docking or molecular dynamics (MD) simulation. The alternative approach proposed here is scanning of a spatial and angular grid around the protein with smaller fragments of the large ligand. Energy values for complete grids can be computed efficiently with a well-known fast Fourier transform-accelerated algorithm and a physically meaningful interaction model. We show that the approach can readily incorporate flexibility of the protein and ligand. The energy grids (EGs) resulting from the ligand fragment scans can be transformed into probability distributions and then directly compared to probability distributions estimated from MD simulations and experimental structural data. We test the approach on a diverse set of complexes between proteins and large, flexible ligands, including a complex of sonic hedgehog protein and heparin, three heparin sulfate substrates or nonsubstrates of an epimerase, a multibranched supramolecular ligand that stabilizes a protein-peptide complex, a flexible zwitterionic ligand that binds to a surface basin of a Kringle domain, and binding of ATP to a flexible site of an ion channel. In all cases, the EG approach gives results that are in good agreement with experimental data or MD simulations.


Subject(s)
Computational Biology/methods , Hedgehog Proteins/chemistry , Heparin/chemistry , Proteins/chemistry , 14-3-3 Proteins/chemistry , Adenosine Triphosphate/chemistry , Cations , Crystallography, X-Ray , Kringles , Ligands , Molecular Dynamics Simulation , Protein Conformation , Racemases and Epimerases/chemistry , Receptors, Purinergic P2X4/chemistry , Static Electricity
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