Targeting RNA:protein interactions with an integrative approach leads to the identification of potent YBX1 inhibitors.

RNA-protein interactions (RPIs) are promising targets for developing new molecules of therapeutic interest. Nevertheless, challenges arise from the lack of methods and feedback between computational and experimental techniques during the drug discovery process. Here, we tackle these challenges by developing a drug screening approach that integrates chemical, structural and cellular data from both advanced computational techniques and a method to score RPIs in cells for the development of small RPI inhibitors; and we demonstrate its robustness by targeting Y-box binding protein 1 (YB-1), a messenger RNA-binding protein involved in cancer progression and resistance to chemotherapy. This approach led to the identification of 22 hits validated by molecular dynamics (MD) simulations and nuclear magnetic resonance (NMR) spectroscopy of which 11 were found to significantly interfere with the binding of messenger RNA (mRNA) to YB-1 in cells. One of our leads is an FDA-approved poly(ADP-ribose) polymerase 1 (PARP-1) inhibitor. This work shows the potential of our integrative approach and paves the way for the rational development of RPI inhibitors.

Structure-based virtual screening workflow to identify antivirals targeting HIV-1 capsid.

We have identified novel HIV-1 capsid inhibitors targeting the PF74 binding site. Acting as the building block of the HIV-1 capsid core, the HIV-1 capsid protein plays an important role in the viral life cycle and is an attractive target for antiviral development. A structure-based virtual screening workflow for hit identification was employed, which includes docking 1.6 million commercially-available drug-like compounds from the ZINC database to the capsid dimer, followed by applying two absolute binding free energy (ABFE) filters on the 500 top-ranked molecules from docking. The first employs the Binding Energy Distribution Analysis Method (BEDAM) in implicit solvent. The top-ranked compounds are then refined using the Double Decoupling method in explicit solvent. Both docking and BEDAM refinement were carried out on the IBM World Community Grid as part of the FightAIDS@Home project. Using this virtual screening workflow, we identified 24 molecules with calculated binding free energies between - 6 and - 12 kcal/mol. We performed thermal shift assays on these molecules to examine their potential effects on the stability of HIV-1 capsid hexamer and found that two compounds, ZINC520357473 and ZINC4119064 increased the melting point of the latter by 14.8 °C and 33 °C, respectively. These results support the conclusion that the two ZINC compounds are primary hits targeting the capsid dimer interface. Our simulations also suggest that the two hit molecules may bind at the capsid dimer interface by occupying a new sub-pocket that has not been exploited by existing CA inhibitors. The possible causes for why other top-scored compounds suggested by ABFE filters failed to show measurable activity are discussed.

Shaking the ß-Bulges.

ß-bulges are irregularities inside the ß-sheets. They represent more than 3 percent of the protein residues, i.e., they are as frequent as 3.10 helices. In terms of evolution, ß-bulges are not more conserved than any other local protein conformations within homologous protein structures. In a first of its kind study, we have investigated the dynamical behaviour of ß-bulges using the largest known set of protein molecular dynamics simulations. We observed that more than 50 percent of the existing ß-bulges in protein crystal structures remained stable during dynamics while more than1/6th were not stable at all and disappeared entirely. Surprisingly, 1.1 percent of ß-bulges that appeared remained stable. ß-bulges have been categorized in different subtypes. The most common ß-bulges' types are the smallest insertion in ß-strands (namely AC and AG); they are found as stable as the whole ß-bulges dataset. Low occurring types (namely PC and AS), that have the largest insertions, are significantly more stable than expected. Thus, this pioneer study allowed to precisely quantify the stability of the ß-bulges, demonstrating their structural robustness, with few unexpected cases raising structural questions.

Identification of a small molecule splicing inhibitor targeting UHM domains.

Splicing factor mutations are frequent in myeloid neoplasms, blood cancers, and solid tumors. Cancer cells harboring these mutations present a particular vulnerability to drugs that target splicing factors such as SF3b155 or CAPERα. Still, the arsenal of chemical probes that target the spliceosome is very limited. U2AF homology motifs (UHMs) are common protein interaction domains among splicing factors. They present a hydrophobic pocket ideally suited to anchor small molecules with the aim to inhibit protein-protein interaction. Here, we combined a virtual screening of a small molecules database and an in vitro competition assay and identified a small molecule, we named UHMCP1 that prevents the SF3b155/U2AF65 interaction. NMR analyses and molecular dynamics simulations confirmed the binding of this molecule in the hydrophobic pocket of the U2AF65 UHM domain. We further provide evidence that UHMCP1 impacts RNA splicing and cell viability and is therefore an interesting novel compound targeting an UHM domain with potential anticancer properties.

The cooperative binding of TDP-43 to GU-rich RNA repeats antagonizes TDP-43 aggregation.

TDP-43 is a nuclear RNA-binding protein that forms neuronal cytoplasmic inclusions in two major neurodegenerative diseases, ALS and FTLD. While the self-assembly of TDP-43 by its structured N-terminal and intrinsically disordered C-terminal domains has been widely studied, the mechanism by which mRNA preserves TDP-43 solubility in the nucleus has not been addressed. Here, we demonstrate that tandem RNA recognition motifs of TDP-43 bind to long GU-repeats in a cooperative manner through intermolecular interactions. Moreover, using mutants whose cooperativity is impaired, we found that the cooperative binding of TDP-43 to mRNA may be critical to maintain the solubility of TDP-43 in the nucleus and the miscibility of TDP-43 in cytoplasmic stress granules. We anticipate that the knowledge of a higher order assembly of TDP-43 on mRNA may clarify its role in intron processing and provide a means of interfering with the cytoplasmic aggregation of TDP-43.

Lin28, a major translation reprogramming factor, gains access to YB-1-packaged mRNA through its cold-shock domain.

The RNA-binding protein Lin28 (Lin28a) is an important pluripotency factor that reprograms translation and promotes cancer progression. Although Lin28 blocks let-7 microRNA maturation, Lin28 also binds to a large set of cytoplasmic mRNAs directly. However, how Lin28 regulates the processing of many mRNAs to reprogram global translation remains unknown. We show here, using a structural and cellular approach, a mixing of Lin28 with YB-1 (YBX1) in the presence of mRNA owing to their cold-shock domain, a conserved ß-barrel structure that binds to ssRNA cooperatively. In contrast, the other RNA binding-proteins without cold-shock domains tested, HuR, G3BP-1, FUS and LARP-6, did not mix with YB-1. Given that YB-1 is the core component of dormant mRNPs, a model in which Lin28 gains access to mRNPs through its co-association with YB-1 to mRNA may provide a means for Lin28 to reprogram translation. We anticipate that the translational plasticity provided by mRNPs may contribute to Lin28 functions in development and adaptation of cancer cells to an adverse environment.

Discrete analyses of protein dynamics.

Protein structures are highly dynamic macromolecules. This dynamics is often analysed through experimental and/or computational methods only for an isolated or a limited number of proteins. Here, we explore large-scale protein dynamics simulation to observe dynamics of local protein conformations using different perspectives. We analysed molecular dynamics to investigate protein flexibility locally, using classical approaches such as RMSf, solvent accessibility, but also innovative approaches such as local entropy. First, we focussed on classical secondary structures and analysed specifically how ß-strand, ß-turns, and bends evolve during molecular simulations. We underlined interesting specific bias between ß-turns and bends, which are considered as the same category, while their dynamics show differences. Second, we used a structural alphabet that is able to approximate every part of the protein structures conformations, namely protein blocks (PBs) to analyse (i) how each initial local protein conformations evolve during dynamics and (ii) if some exchange can exist among these PBs. Interestingly, the results are largely complex than simple regular/rigid and coil/flexible exchange. AbbreviationsNeqnumber of equivalentPBProtein BlocksPDBProtein DataBankRMSfroot mean square fluctuationsCommunicated by Ramaswamy H. Sarma.

iPBAvizu: a PyMOL plugin for an efficient 3D protein structure superimposition approach.

BACKGROUND: Protein 3D structure is the support of its function. Comparison of 3D protein structures provides insight on their evolution and their functional specificities and can be done efficiently via protein structure superimposition analysis. Multiple approaches have been developed to perform such task and are often based on structural superimposition deduced from sequence alignment, which does not take into account structural features. Our methodology is based on the use of a Structural Alphabet (SA), i.e. a library of 3D local protein prototypes able to approximate protein backbone. The interest of a SA is to translate into 1D sequences into the 3D structures. RESULTS: We used Protein blocks (PB), a widely used SA consisting of 16 prototypes, each representing a conformation of the pentapeptide skeleton defined in terms of dihedral angles. Proteins are described using PB from which we have previously developed a sequence alignment procedure based on dynamic programming with a dedicated PB Substitution Matrix. We improved the procedure with a specific two-step search: (i) very similar regions are selected using very high weights and aligned, and (ii) the alignment is completed (if possible) with less stringent parameters. Our approach, iPBA, has shown to perform better than other available tools in benchmark tests. To facilitate the usage of iPBA, we designed and implemented iPBAvizu, a plugin for PyMOL that allows users to run iPBA in an easy way and analyse protein superimpositions. CONCLUSIONS: iPBAvizu is an implementation of iPBA within the well-known and widely used PyMOL software. iPBAvizu enables to generate iPBA alignments, create and interactively explore structural superimposition, and assess the quality of the protein alignments.

In silico prediction of protein flexibility with local structure approach.

Flexibility is an intrinsic essential feature of protein structures, directly linked to their functions. To this day, most of the prediction methods use the crystallographic data (namely B-factors) as the only indicator of protein's inner flexibility and predicts them as rigid or flexible. PredyFlexy stands differently from other approaches as it relies on the definition of protein flexibility (i) not only taken from crystallographic data, but also (ii) from Root Mean Square Fluctuation (RMSFs) observed in Molecular Dynamics simulations. It also uses a specific representation of protein structures, named Long Structural Prototypes (LSPs). From Position-Specific Scoring Matrix, the 120 LSPs are predicted with a good accuracy and directly used to predict (i) the protein flexibility in three categories (flexible, intermediate and rigid), (ii) the normalized B-factors, (iii) the normalized RMSFs, and (iv) a confidence index. Prediction accuracy among these three classes is equivalent to the best two class prediction methods, while the normalized B-factors and normalized RMSFs have a good correlation with experimental and in silico values. Thus, PredyFlexy is a unique approach, which is of major utility for the scientific community. It support parallelization features and can be run on a local cluster using multiple cores.

Bisubstrate Inhibitors of Nicotinamide N-Methyltransferase (NNMT) with Enhanced Activity.

Nicotinamide N-methyltransferase (NNMT) catalyzes the methylation of nicotinamide to form N-methylnicotinamide. Overexpression of NNMT is associated with a variety of diseases, including a number of cancers and metabolic disorders, suggesting a role for NNMT as a potential therapeutic target. By structural modification of a lead NNMT inhibitor previously developed in our group, we prepared a diverse library of inhibitors to probe the different regions of the enzyme's active site. This investigation revealed that incorporation of a naphthalene moiety, intended to bind the hydrophobic nicotinamide binding pocket via π-π stacking interactions, significantly increases the activity of bisubstrate-like NNMT inhibitors (half-maximal inhibitory concentration 1.41 µM). These findings are further supported by isothermal titration calorimetry binding assays as well as modeling studies. The most active NNMT inhibitor identified in the present study demonstrated a dose-dependent inhibitory effect on the cell proliferation of the HSC-2 human oral cancer cell line.

Investigation of the impact of PTMs on the protein backbone conformation.

Post-translational modifications (PTMs) are known to play a critical role in the regulation of protein functions. Their impact on protein structures and their link to disorder regions have already been spotted in the past decade. Nonetheless, the high diversity of PTM types and the multiple schemes of protein modifications (multiple PTMs, of different types, at different time, etc.) make difficult the direct confrontation of PTM annotations and protein structure data. Therefore, we analyzed the impact of the residue modifications on the protein structures at the local level. Thanks to a dedicated structure database, namely PTM-SD, a large screen of PTMs have been done and analyzed at local protein conformation levels using the structural alphabet protein blocks (PBs). We investigated the relation between PTMs and the backbone conformation of modified residues, of their local environment, and at the level of the complete protein structure. The two main PTM types (N-glycosylation and phosphorylation) have been studied in non-redundant datasets, and then four different proteins were focused, covering three types of PTMs: N-glycosylation in renin endopeptidase and liver carboxylesterase, phosphorylation in cyclin-dependent kinase 2 (CDK2), and methylation in actin. We observed that PTMs could either stabilize or destabilize the backbone structure, at a local and global scale, and that these effects depend on the PTM types.

Novel Intersubunit Interaction Critical for HIV-1 Core Assembly Defines a Potentially Targetable Inhibitor Binding Pocket.

HIV-1 capsid protein (CA) plays critical roles in both early and late stages of the viral replication cycle. Mutagenesis and structural experiments have revealed that capsid core stability significantly affects uncoating and initiation of reverse transcription in host cells. This has led to efforts in developing antivirals targeting CA and its assembly, although none of the currently identified compounds are used in the clinic for treatment of HIV infection. A specific interaction that is primarily present in pentameric interfaces in the HIV-1 capsid core was identified and is reported to be important for CA assembly. This is shown by multidisciplinary characterization of CA site-directed mutants using biochemical analysis of virus-like particle formation, transmission electron microscopy of in vitro assembly, crystallographic studies, and molecular dynamic simulations. The data are consistent with a model where a hydrogen bond between CA residues E28 and K30' from neighboring N-terminal domains (CANTDs) is important for CA pentamer interactions during core assembly. This pentamer-preferred interaction forms part of an N-terminal domain interface (NDI) pocket that is amenable to antiviral targeting.IMPORTANCE Precise assembly and disassembly of the HIV-1 capsid core are key to the success of viral replication. The forces that govern capsid core formation and dissociation involve intricate interactions between pentamers and hexamers formed by HIV-1 CA. We identified one particular interaction between E28 of one CA and K30' of the adjacent CA that appears more frequently in pentamers than in hexamers and that is important for capsid assembly. Targeting the corresponding site could lead to the development of antivirals which disrupt this interaction and affect capsid assembly.

PBxplore: a tool to analyze local protein structure and deformability with Protein Blocks.

This paper describes the development and application of a suite of tools, called PBxplore, to analyze the dynamics and deformability of protein structures using Protein Blocks (PBs). Proteins are highly dynamic macromolecules, and a classical way to analyze their inherent flexibility is to perform molecular dynamics simulations. The advantage of using small structural prototypes such as PBs is to give a good approximation of the local structure of the protein backbone. More importantly, by reducing the conformational complexity of protein structures, PBs allow analysis of local protein deformability which cannot be done with other methods and had been used efficiently in different applications. PBxplore is able to process large amounts of data such as those produced by molecular dynamics simulations. It produces frequencies, entropy and information logo outputs as text and graphics. PBxplore is available at https://github.com/pierrepo/PBxplore and is released under the open-source MIT license.

Protein flexibility in the light of structural alphabets.

Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.

PTM-SD: a database of structurally resolved and annotated posttranslational modifications in proteins.

Posttranslational modifications (PTMs) define covalent and chemical modifications of protein residues. They play important roles in modulating various biological functions. Current PTM databases contain important sequence annotations but do not provide informative 3D structural resource about these modifications. Posttranslational modification structural database (PTM-SD) provides access to structurally solved modified residues, which are experimentally annotated as PTMs. It combines different PTM information and annotation gathered from other databases, e.g. Protein DataBank for the protein structures and dbPTM and PTMCuration for fine sequence annotation. PTM-SD gives an accurate detection of PTMs in structural data. PTM-SD can be browsed by PDB id, UniProt accession number, organism and classic PTM annotation. Advanced queries can also be performed, i.e. detailed PTM annotations, amino acid type, secondary structure, SCOP class classification, PDB chain length and number of PTMs by chain. Statistics and analyses can be computed on a selected dataset of PTMs. Each PTM entry is detailed in a dedicated page with information on the protein sequence, local conformation with secondary structure and Protein Blocks. PTM-SD gives valuable information on observed PTMs in protein 3D structure, which is of great interest for studying sequence-structure- function relationships at the light of PTMs, and could provide insights for comparative modeling and PTM predictions protocols. Database URL: PTM-SD can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/PTM-SD/.

ß-Bulges: extensive structural analyses of ß-sheets irregularities.

ß-Sheets are quite frequent in protein structures and are stabilized by regular main-chain hydrogen bond patterns. Irregularities in ß-sheets, named ß-bulges, are distorted regions between two consecutive hydrogen bonds. They disrupt the classical alternation of side chain direction and can alter the directionality of ß-strands. They are implicated in protein-protein interactions and are introduced to avoid ß-strand aggregation. Five different types of ß-bulges are defined. Previous studies on ß-bulges were performed on a limited number of protein structures or one specific family. These studies evoked a potential conservation during evolution. In this work, we analyze the ß-bulge distribution and conservation in terms of local backbone conformations and amino acid composition. Our dataset consists of 66 times more ß-bulges than the last systematic study (Chan et al. Protein Science 1993, 2:1574-1590). Novel amino acid preferences are underlined and local structure conformations are highlighted by the use of a structural alphabet. We observed that ß-bulges are preferably localized at the N- and C-termini of ß-strands, but contrary to the earlier studies, no significant conservation of ß-bulges was observed among structural homologues. Displacement of ß-bulges along the sequence was also investigated by Molecular Dynamics simulations.

Cis-trans isomerization of omega dihedrals in proteins.

Peptide bonds in protein structures are mainly found in trans conformation with a torsion angle ω close to 180°. Only a very low proportion is observed in cis conformation with ω angle around 0°. Cis-trans isomerization leads to local conformation changes which play an important role in many biological processes. In this paper, we reviewed the recent discoveries and research achievements in this field. First, we presented some interesting cases of biological processes in which cis-trans isomerization is directly implicated. It is involved in protein folding and various aspect of protein function like dimerization interfaces, autoinhibition control, channel gating, membrane binding. Then we reviewed conservation studies of cis peptide bonds which emphasized evolution constraints in term of sequence and local conformation. Finally we made an overview of the numerous molecular dynamics studies and prediction methodologies already developed to take into account this structural feature in the research area of protein modeling. Many cis peptide bonds have not been recognized as such due to the limited resolution of the data and to the refinement protocol used. Cis-trans proline isomerization reactions represents a vast and promising research area that still needs to be further explored for a better understanding of isomerization mechanism and improvement of cis peptide bond predictions.

PredyFlexy: flexibility and local structure prediction from sequence.

Protein structures are necessary for understanding protein function at a molecular level. Dynamics and flexibility of protein structures are also key elements of protein function. So, we have proposed to look at protein flexibility using novel methods: (i) using a structural alphabet and (ii) combining classical X-ray B-factor data and molecular dynamics simulations. First, we established a library composed of structural prototypes (LSPs) to describe protein structure by a limited set of recurring local structures. We developed a prediction method that proposes structural candidates in terms of LSPs and predict protein flexibility along a given sequence. Second, we examine flexibility according to two different descriptors: X-ray B-factors considered as good indicators of flexibility and the root mean square fluctuations, based on molecular dynamics simulations. We then define three flexibility classes and propose a method based on the LSP prediction method for predicting flexibility along the sequence. This method does not resort to sophisticate learning of flexibility but predicts flexibility from average flexibility of predicted local structures. The method is implemented in PredyFlexy web server. Results are similar to those obtained with the most recent, cutting-edge methods based on direct learning of flexibility data conducted with sophisticated algorithms. PredyFlexy can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/predyflexy/.