Apport de la modélisation et des simulations de dynamique moléculaire à la description de STAT5 comme cible pour moduler la signalisation oncogénique

STAT5 is a protein involved in normal cell signalling that is crucial for transformation, survival and resistance to tyrosine kinase inhibitors of tumour cells. The constitutive phosphorylation activates STAT5 and is related to oncogenic proteins like the hybrid protein BCR/ABL1 (chronic myeloid leukaemia) or mutated KIT receptor (mastocytosis). The pharmacologic inhibition of STAT5 is thus a major therapeutic concern in several malignant pathologies. We performed the first modelling and molecular dynamics simulations of the main cellular species of STAT5: the cytoplasmic phosphorylated or unphosphorylated monomer, and the phosphorylated dimer bound to DNA. We characterized the dynamical properties and the intramolecular allosteric network of the monomers. The generated results show structural and dynamic variations linked to the primary sequence changes between the two STAT5 isoforms and/or to the phosphate group. Two pockets were characterized at the surface of STAT5. Their location at close proximity of allosteric communication pathways suggests new putative inhibition sites to modulate STAT5 functions. We also described the hydrogen bonds network between the monomers of the dimeric species and the recognition of the DNA. We identified key residues at the interfaces, allowing us to better understand the effects of clinically relevant STAT5 mutations observed in malignancies.STAT5 est une protéine de la signalisation cellulaire normale, qui peut jouer un rôle important dans la transformation, la survie et à la résistance aux inhibiteurs de tyrosine kinase des cellules tumorales. Son activation constitutive par phosphorylation est liée à la présence de protéines oncogéniques comme la protéine de fusion BCR/ABL1 (leucémie myéloïde chronique) ou de formes mutées de KIT (mastocytoses), par exemple. L’inhibition pharmacologique de STAT5 constitue donc un enjeu thérapeutique majeur pour plusieurs pathologies malignes. Nous avons réalisé la première modélisation et les simulations de dynamique moléculaire des principales formes de STAT5 : la forme monomérique cytoplasmique phosphorylée ou non, et la forme dimérique phosphorylée et liée à l’ADN. Nous avons caractérisé les propriétés dynamiques et le réseau allostérique intramoléculaire des monomères de STAT5. Les résultats générés montrent des variations structurales et dynamiques liées à la différence de séquence primaire des isoformes de STAT5 et/ou à la présence du groupement phosphate. Deux poches à la surface des protéines ont également été caractérisées. Leur localisation à proximité de voies de communication allostériques suggère que ces poches pourraient constituer des sites de modulation des fonctions de STAT5. Nous avons également caractérisé les liaisons hydrogènes entre les monomères constituant les dimères de STAT5 et leur reconnaissance de l’ADN. En outre, nous avons identifié des résidus clés aux interfaces entre les entités moléculaires, nous permettant de mieux comprendre les effets de mutations de STAT5 observées en clinique dans certaines pathologies malignes

SHREC2020 track:Multi-domain protein shape retrieval challenge

Proteins are natural modular objects usually composed of several domains, each domain bearing a specific function that is mediated through its surface, which is accessible to vicinal molecules. This draws attention to an understudied characteristic of protein structures: surface, that is mostly unexploited by protein structure comparison methods. In the present work, we evaluated the performance of six shape comparison methods, among which three are based on machine learning, to distinguish between 588 multi-domain proteins and to recreate the evolutionary relationships at the proteinand species levels of the SCOPe database. The six groups that participated in the challenge submitted a total of 15 sets of results. We observed that the performance of all the methods significantly decreases at the species level, suggesting that shape-only protein comparison is challenging for closely related proteins. Even if the dataset is limited in size (only 588 proteins are considered whereas more than 160,000 protein structures are experimentally solved), we think that this work provides useful insights into the current shape comparison methods performance, and highlights possible limitations to large-scale applications due to the computational cost

Surface-based protein domains retrieval methods from a SHREC2021 challenge

publication dans une revue suite à la communication hal-03467479 (SHREC 2021: surface-based protein domains retrieval)International audienceProteins are essential to nearly all cellular mechanism and the effectors of the cells activities. As such, they often interact through their surface with other proteins or other cellular ligands such as ions or organic molecules. The evolution generates plenty of different proteins, with unique abilities, but also proteins with related functions hence similar 3D surface properties (shape, physico-chemical properties, …). The protein surfaces are therefore of primary importance for their activity. In the present work, we assess the ability of different methods to detect such similarities based on the geometry of the protein surfaces (described as 3D meshes), using either their shape only, or their shape and the electrostatic potential (a biologically relevant property of proteins surface). Five different groups participated in this contest using the shape-only dataset, and one group extended its pre-existing method to handle the electrostatic potential. Our comparative study reveals both the ability of the methods to detect related proteins and their difficulties to distinguish between highly related proteins. Our study allows also to analyze the putative influence of electrostatic information in addition to the one of protein shapes alone. Finally, the discussion permits to expose the results with respect to ones obtained in the previous contests for the extended method. The source codes of each presented method have been made available online

SHREC 2018 - Protein Shape Retrieval

Proteins are macromolecules central to biological processes that display a dynamic and complex surface. They display multiple conformations differing by local (residue side-chain) or global (loop or domain) structural changes which can impact drastically their global and local shape. Since the structure of proteins is linked to their function and the disruption of their interactions can lead to a disease state, it is of major importance to characterize their shape. In the present work, we report the performance in enrichment of six shape-retrieval methods (3D-FusionNet, GSGW, HAPT, DEM, SIWKS and WKS) on a 2 267 protein structures dataset generated for this protein shape retrieval track of SHREC’18

Contribution of molecular modeling and dynamics simulations to describe STAT5 as a target to modulate oncogenic signaling

STAT5 est une protéine de la signalisation cellulaire normale, qui peut jouer un rôle important dans la transformation, la survie et à la résistance aux inhibiteurs de tyrosine kinase des cellules tumorales. Son activation constitutive par phosphorylation est liée à la présence de protéines oncogéniques comme la protéine de fusion BCR/ABL1 (leucémie myéloïde chronique) ou de formes mutées de KIT (mastocytoses), par exemple. L’inhibition pharmacologique de STAT5 constitue donc un enjeu thérapeutique majeur pour plusieurs pathologies malignes. Nous avons réalisé la première modélisation et les simulations de dynamique moléculaire des principales formes de STAT5 : la forme monomérique cytoplasmique phosphorylée ou non, et la forme dimérique phosphorylée et liée à l’ADN. Nous avons caractérisé les propriétés dynamiques et le réseau allostérique intramoléculaire des monomères de STAT5. Les résultats générés montrent des variations structurales et dynamiques liées à la différence de séquence primaire des isoformes de STAT5 et/ou à la présence du groupement phosphate. Deux poches à la surface des protéines ont également été caractérisées. Leur localisation à proximité de voies de communication allostériques suggère que ces poches pourraient constituer des sites de modulation des fonctions de STAT5. Nous avons également caractérisé les liaisons hydrogènes entre les monomères constituant les dimères de STAT5 et leur reconnaissance de l’ADN. En outre, nous avons identifié des résidus clés aux interfaces entre les entités moléculaires, nous permettant de mieux comprendre les effets de mutations de STAT5 observées en clinique dans certaines pathologies malignes.STAT5 is a protein involved in normal cell signalling that is crucial for transformation, survival and resistance to tyrosine kinase inhibitors of tumour cells. The constitutive phosphorylation activates STAT5 and is related to oncogenic proteins like the hybrid protein BCR/ABL1 (chronic myeloid leukaemia) or mutated KIT receptor (mastocytosis). The pharmacologic inhibition of STAT5 is thus a major therapeutic concern in several malignant pathologies. We performed the first modelling and molecular dynamics simulations of the main cellular species of STAT5: the cytoplasmic phosphorylated or unphosphorylated monomer, and the phosphorylated dimer bound to DNA. We characterized the dynamical properties and the intramolecular allosteric network of the monomers. The generated results show structural and dynamic variations linked to the primary sequence changes between the two STAT5 isoforms and/or to the phosphate group. Two pockets were characterized at the surface of STAT5. Their location at close proximity of allosteric communication pathways suggests new putative inhibition sites to modulate STAT5 functions. We also described the hydrogen bonds network between the monomers of the dimeric species and the recognition of the DNA. We identified key residues at the interfaces, allowing us to better understand the effects of clinically relevant STAT5 mutations observed in malignancies

Decoys Selection in Benchmarking Datasets: Overview and Perspectives

Virtual Screening (VS) is designed to prospectively help identifying potential hits, i.e., compounds capable of interacting with a given target and potentially modulate its activity, out of large compound collections. Among the variety of methodologies, it is crucial to select the protocol that is the most adapted to the query/target system under study and that yields the most reliable output. To this aim, the performance of VS methods is commonly evaluated and compared by computing their ability to retrieve active compounds in benchmarking datasets. The benchmarking datasets contain a subset of known active compounds together with a subset of decoys, i.e., assumed non-active molecules. The composition of both the active and the decoy compounds subsets is critical to limit the biases in the evaluation of the VS methods. In this review, we focus on the selection of decoy compounds that has considerably changed over the years, from randomly selected compounds to highly customized or experimentally validated negative compounds. We first outline the evolution of decoys selection in benchmarking databases as well as current benchmarking databases that tend to minimize the introduction of biases, and secondly, we propose recommendations for the selection and the design of benchmarking datasets

How Intrinsic Molecular Dynamics Control Intramolecular Communication in Signal Transducers and Activators of Transcription Factor STAT5

<div><p>Signal Transducer and Activator of Transcription STAT5 is a key mediator of cell proliferation, differentiation and survival. While STAT5 activity is tightly regulated in normal cells, its constitutive activation directly contributes to oncogenesis and is associated with a broad range of hematological and solid tumor cancers. Therefore the development of compounds able to modulate pathogenic activation of this protein is a very challenging endeavor. A crucial step of drug design is the understanding of the protein conformational features and the definition of putative binding site(s) for such modulators. Currently, there is no structural data available for human STAT5 and our study is the first footprint towards the description of structure and dynamics of this protein. We investigated structural and dynamical features of the two STAT5 isoforms, STAT5a and STAT5b, taken into account their phosphorylation status. The study was based on the exploration of molecular dynamics simulations by different analytical methods. Despite the overall folding similarity of STAT5 proteins, the MD conformations display specific structural and dynamical features for each protein, indicating first, sequence-encoded structural properties and second, phosphorylation-induced effects which contribute to local and long-distance structural rearrangements interpreted as allosteric event. Further examination of the dynamical coupling between distant sites provides evidence for alternative profiles of the communication pathways inside and between the STAT5 domains. These results add a new insight to the understanding of the crucial role of intrinsic molecular dynamics in mediating intramolecular signaling in STAT5. Two pockets, localized in close proximity to the phosphotyrosine-binding site and adjacent to the channel for communication pathways across STAT5, may constitute valid targets to develop inhibitors able to modulate the function-related communication properties of this signaling protein.</p></div

Comparative evaluation of shape retrieval methods on macromolecular surfaces: an application of computer vision methods in structural bioinformatics

International audienceMotivation The investigation of the structure of biological systems at the molecular level gives insights about their functions and dynamics. Shape and surface of biomolecules are fundamental to molecular recognition events. Characterizing their geometry can lead to more adequate predictions of their interactions. In the present work, we assess the performance of reference shape retrieval methods from the computer vision community on protein shapes. Results Shape retrieval methods are efficient in identifying orthologous proteins and tracking large conformational changes. This work illustrates the interest for the protein surface shape as a higher-level representation of the protein structure that (i) abstracts the underlying protein sequence, structure or fold, (ii) allows the use of shape retrieval methods to screen large databases of protein structures to identify surficial homologs and possible interacting partners and (iii) opens an extension of the protein structure–function paradigm toward a protein structure-surface(s)-function paradigm. Availabilityand implementation All data are available online at http://datasetmachat.drugdesign.fr. Supplementary information Supplementary data are available at Bioinformatics online

Independent Dynamic Fragments identified in STAT5 proteins.

<p>Top: 3D structural mapping of the <i>Independent Dynamic Fragments</i> (<i>IDSs</i>) in STAT5a referred to as S_i, where i = 1, 2 …N, is presented on the average conformation as they were found by LFA <b>(A)</b> and by PFD <b>(B)</b> algorithms. Bottom: <b>(C)</b> Graph representation of <i>IDSs</i> found by PFD and LFA in each studied STAT5. Each color specifies an <i>IDS</i> obtained from a <i>seed</i> (LFA) or a <i>predictor</i> (PFD); the <i>IDSs</i> localized on the same structural fragment in various STAT5s may be colored differently according to a number of the first predicted residue in a given <i>IDS</i>.</p