| Literature DB >> 31667555 |
Patricia Santofimia-Castaño1, Bruno Rizzuti2, Yi Xia3, Olga Abian4,5,6,7,8, Ling Peng9, Adrián Velázquez-Campoy4,5,6,7,10, José L Neira11,12, Juan Iovanna13.
Abstract
Intrinsically disordered proteins (IDPs) do not have a well-defined structure under physiological conditions, but they have key roles in cell signaling and regulation, and they are frequently related to the development of diseases, such as cancer and other malignancies. This has converted IDPs in attractive therapeutic targets; however, targeting IDPs is challenging because of their dynamic nature. In the last years, different experimental and computational approaches, as well as the combination of both, have been explored to identify molecules to target either the hot-spots or the allosteric sites of IDPs. In this review, we summarize recent developments in successful targeting of IDPs, all of which are involved in different cancer types. The strategies used to develop and design (or in one particular example, to repurpose) small molecules targeting IDPs are, in a global sense, similar to those used in well-folded proteins: (1) screening of chemically diverse or target-oriented compound libraries; or (2) study of the interfaces involved in recognition of their natural partners, and design of molecular candidates capable of binding to such binding interface. We describe the outcomes of using these approaches in targeting IDPs involved in cancer, in the view to providing insight, to target IDPs in general. In a broad sense, the designed small molecules seem to target the most hydrophobic regions of the IDPs, hampering macromolecule (DNA or protein)-IDP interactions; furthermore, in most of the molecule-IDP complexes described so far, the protein remains disordered.Entities:
Keywords: Cancer; Drug design; Intrinsically disordered protein; NUPR1; Pancreatic ductal adenocarcinoma; Protein function; Protein–protein interactions; Stress response
Mesh:
Substances:
Year: 2019 PMID: 31667555 PMCID: PMC7190594 DOI: 10.1007/s00018-019-03347-3
Source DB: PubMed Journal: Cell Mol Life Sci ISSN: 1420-682X Impact factor: 9.261
Fig. 1The two approaches used in screening IDPs. The red oval indicates the molecule that binds to the PP interface of the target IDP (in blue), and it is designed based on the structural features of the partner protein, which, in our example, is another IDP (in red), but it could be a well-folded protein (a). In the second approach (b), a library of different compounds (represented as shapes with different colors) is used to find out whether one of them is captured by the IDP (in our example the red oval again). In both examples, we have assumed that the IDP folds after binding to the molecule, but it could also remain disordered upon binding
Fig. 2Structure of the homodimer of Max (PDB entry: 5I4Z) [104] (a) and the heterodimer with c-Myc and DNA [17] (PDB number: 1NKP) (b). The arrow in a indicates the homodimer interface; and that in b indicates the protein-DNA interface. The figure was produced with PyMOL [105]
Fig. 3Structure of compounds used in targeting IDPs: a sAJM589 for the c-Myc system; b MSI-1436 for C-PTIB; c NSC635437 for the EW-FLI1 fusion protein; d the compound targeting p27-KID; e TFP (left side) and Fluphenazine hydrochloride (right side) identified for NUPR1; f the ZZW-115 compound obtained by ligand-based design
Fig. 4Structure of the complex between the AF9 and the peptide-derived AF4 polypeptide. Ensemble of structures of the bound peptide (left), and details of a single peptide structure in a rotated view of the protein (right).
The figure was produced with PyMOL [105] from the PDB entry 2LM0 [47]
Fig. 5Structure of the complex between the MDM2 and p53-derived peptide from TA region.
The figure was produced with PyMOL [105] from the PDB entry 1YCR [68]
Fig. 6Simulated structures of NUPR1 in the first encounter with the compound ZZW-115. Examples of conformations in the solution ensemble of NUPR1 (left), and details of the binding pocket for ZZW-115 (right).
The figure was produced with PyMOL [105] from simulation models previously obtained [97, 100]