Molecular Modelling of NONO and SFPQ Dimerization Process and RNA Recognition Mechanism

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Abstract

NONO and SFPQ are involved in multiple nuclear processes (e.g., pre-mRNA splicing, DNA repair, and transcriptional regulation). These proteins, along with NEAT1, enable paraspeckle formation, thus promoting multiple myeloma cell survival. In this paper, we investigate NONO and SFPQ dimer stability, highlighting the hetero- and homodimer structural differences, and model their interactions with RNA, simulating their binding to a polyG probe mimicking NEAT1guanine-rich regions. We demonstrated in silico that NONO::SFPQ heterodimerization is a more favorable process than homodimer formation. We also show that NONO and SFPQ RRM2 subunits are primarily required for protein–protein interactions with the other DBHS protomer. Simulation of RNA binding to NONO and SFPQ, beside validating RRM1 RNP signature importance, highlighted the role of β2 and β4 strand residues for RNA specific recognition. Moreover, we demonstrated the role of the NOPS region and other protomer’s RRM2 β2/β3 loop in strengthening the interaction with RNA. Our results, having deepened RNA and DBHS dimer interactions, could contribute to the design of small molecules to modulate the activity of these proteins. RNA-mimetics, able to selectively bind to NONO and/or SFPQ RNA-recognition site, could impair paraspeckle formation, thus representing a first step towards the discovery of drugs for multiple myeloma treatment.

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The RNA recognition motif, a plastic RNA-binding platform to regulate post-transcriptional gene expression.

Christophe Maris, Cyril Dominguez, Frédéric Allain (2005)

The RNA recognition motif (RRM), also known as RNA-binding domain (RBD) or ribonucleoprotein domain (RNP) is one of the most abundant protein domains in eukaryotes. Based on the comparison of more than 40 structures including 15 complexes (RRM-RNA or RRM-protein), we reviewed the structure-function relationships of this domain. We identified and classified the different structural elements of the RRM that are important for binding a multitude of RNA sequences and proteins. Common structural aspects were extracted that allowed us to define a structural leitmotif of the RRM-nucleic acid interface with its variations. Outside of the two conserved RNP motifs that lie in the center of the RRM beta-sheet, the two external beta-strands, the loops, the C- and N-termini, or even a second RRM domain allow high RNA-binding affinity and specific recognition. Protein-RRM interactions that have been found in several structures reinforce the notion of an extreme structural versatility of this domain supporting the numerous biological functions of the RRM-containing proteins.

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Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pKa Values.

Chresten Søndergaard, Mats H M Olsson, Michal Rostkowski … (2011)

The new empirical rules for protein pKa predictions implemented in the PROPKA3.0 software package (Olsson et al. J. Chem. Theory Comput.2010, 7, 525-537) have been extended to the prediction of pKa shifts of active site residues and ionizable ligand groups in protein-ligand complexes. We present new algorithms that allow pKa shifts due to inductive (i.e., covalently coupled) intraligand interactions, as well as noncovalently coupled interligand interactions in multiligand complexes, to be included in the prediction. The number of different ligand chemical groups that are automatically recognized has been increased to 18, and the general implementation has been changed so that new functional groups can be added easily by the user, aided by a new and more general protonation scheme. Except for a few cases, the new algorithms in PROPKA3.1 are found to yield results similar to or better than those obtained with PROPKA2.0 (Bas et al. Proteins: Struct., Funct., Bioinf.2008, 73, 765-783). Finally, we present a novel algorithm that identifies noncovalently coupled ionizable groups, where pKa prediction may be especially difficult. This is a general improvement to PROPKA and is applied to proteins with and without ligands.