Predicting biomolecular function from 3D dynamics : sequence-sensitive coarse-grained elastic network model coupled to machine learning

La dynamique structurelle des biomolécules est intimement liée à leur fonction, mais très coûteuse à étudier expériementalement. Pour cette raison, de nombreuses méthodologies computationnelles ont été développées afin de simuler la dynamique structurelle biomoléculaire. Toutefois, lorsque l'on s'intéresse à la modélisation des effects de milliers de mutations, les méthodes de simulations classiques comme la dynamique moléculaire, que ce soit à l'échelle atomique ou gros-grain, sont trop coûteuses pour la majorité des applications. D'autre part, les méthodes d'analyse de modes normaux de modèles de réseaux élastiques gros-grain (ENM pour "elastic network model") sont très rapides et procurent des solutions analytiques comprenant toutes les échelles de temps. Par contre, la majorité des ENMs considèrent seulement la géométrie du squelette biomoléculaire, ce qui en fait de mauvais choix pour étudier les effets de mutations qui ne changeraient pas cette géométrie. Le "Elastic Network Contact Model" (ENCoM) est le premier ENM sensible à la séquence de la biomolécule à l'étude, ce qui rend possible son utilisation pour l'exploration efficace d'espaces conformationnels complets de variants de séquence. La présente thèse introduit le pipeline computationel ENCoM-DynaSig-ML, qui réduit les espaces conformationnels prédits par ENCoM à des Signatures Dynamiques qui sont ensuite utilisées pour entraîner des modèles d'apprentissage machine simples. ENCoM-DynaSig-ML est capable de prédire la fonction de variants de séquence avec une précision significative, est complémentaire à toutes les méthodes existantes, et peut générer de nouvelles hypothèses à propos des éléments importants de dynamique structurelle pour une fonction moléculaire donnée. Nous présentons trois exemples d'étude de relations séquence-dynamique-fonction: la maturation des microARN, le potentiel d'activation de ligands du récepteur mu-opioïde et l'efficacité enzymatique de l'enzyme VIM-2 lactamase. Cette application novatrice de l'analyse des modes normaux est rapide, demandant seulement quelques secondes de temps de calcul par variant de séquence, et est généralisable à toute biomolécule pour laquelle des données expérimentale de mutagénèse sont disponibles.The dynamics of biomolecules are intimately tied to their functions but experimentally elusive, making their computational study attractive. When modelling the effects of thousands of mutations, time-stepping methods such as classical or enhanced sampling molecular dynamics are too costly for most applications. On the other hand, normal mode analysis of coarse-grained elastic network models (ENMs) provides fast analytical dynamics spanning all timescales. However, the vast majority of ENMs consider backbone geometry alone, making them a poor choice to study point mutations which do not affect the equilibrium structure. The Elastic Network Contact Model (ENCoM) is the first sequence-sensitive ENM, enabling its use for the efficient exploration of full conformational spaces from sequence variants. The present work introduces the ENCoM-DynaSig-ML computational pipeline, in which the ENCoM conformational spaces are reduced to Dynamical Signatures and coupled to simple machine learning algorithms. ENCoM-DynaSig-ML predicts the function of sequence variants with significant accuracy, is complementary to all existing methods, and can generate new hypotheses about which dynamical features are important for the studied biomolecule's function. Examples given are the maturation efficiency of microRNA variants, the activation potential of mu-opioid receptor ligands and the effect of point mutations on VIM-2 lactamase's enzymatic efficiency. This novel application of normal mode analysis is very fast, taking a few seconds CPU time per variant, and is generalizable to any biomolecule on which experimental mutagenesis data exist

The NRGTEN Python package: an extensible toolkit for coarse-grained normal mode analysis of proteins, nucleic acids, small molecules and their complexes

Summary: Coarse-grained normal mode analysis (NMA) is a fast computational technique to study the dynamics of biomolecules. Here we present the Najmanovich Research Group Toolkit for Elastic Networks (NRGTEN). NRGTEN is a Python toolkit that implements four different NMA models in addition to popular and novel metrics to benchmark and measure properties from these models. Furthermore, the toolkit is available as a public Python package and is easily extensible for the development or implementation of additional NMA models. The inclusion of the ENCoM model (Elastic Network Contact Model) developed in our group within NRGTEN is noteworthy, owing to its account for the specific chemical nature of atomic interactions. This makes possible some unique predictions of the effect of mutations, such as on stability (via changes in vibrational entropy differences), on the transition probability between different conformational states or on the flexibility profile of the whole macromolecule/complex (to study allostery and signalling). In addition, all NMA models can be used to generate conformational ensembles from a starting structure to aid in protein-protein, protein-ligand or other docking studies among applications. NRGTEN is freely available via a public Python package which can be easily installed on any modern machine and includes a detailed user guide hosted online. Availability and implementation: https://github.com/gregorpatof/nrgten_package/ Contact: [email protected]

Photophysical processes and photochemical reactions involved in poly (N-vinylcarbazole) and in copolymers with carbazole units.

LPMM UMR CNRS-UBP 6505 Université Blaise Pascal Clermont-Ferrand (63) et StateUniversity of Moldova Kishinev (Moldavie).This paper is devoted to the analysis of the photochemical behaviour of copolymers with carbazole units exposed to long-wavelength radiation. These copolymers are constitued of two types of carbazolylethyl methracrylate units (CEM) with octyl methacrylate moieties (OMA). The exposure of copolymers and PVK to UV light results in dramatic modifications of the physical and photophysical properties of the polymer. These modifications can be correlated with modifications of the chemical structure of the matrix. The photoageing of copolymers and PVK has been analysed by fluorescence, ESR, UV-vis and infrared spectroscopies. The effects of crosslinking and chain scissions were determined by gel fraction measurements and size exclusion chromotography

Anodic TiO2 nanotube layers for wastewater and air treatments: Assessment of performance using sulfamethoxazole degradation and N2O reduction

The preparation of anodic TiO2 nanotube layers has been performed using electrochemical anodization of Ti foil for 4 h at different voltages (from 0 V to 80 V). In addition, a TiO2 thin layer has been also prepared using the sol-gel method. All the photocatalysts have been characterized by XRD, SEM, and DRS to investigate the crystalline phase composition, the surface morphology, and the optical properties, respectively. The performance of the photocatalyst has been assessed in versatile photocatalytic reactions including the reduction of N2O gas and the oxidation of aqueous sulfamethoxazole. Due to their high specific surface area and excellent charge carriers transport, anodic TiO2 nanotube layers have exhibited the highest N2O conversion rate (up to 10% after 22 h) and the highest degradation extent of sulfamethoxazole (about 65% after 4 h) under UVA light. The degradation mechanism of sulfamethoxazole has been investigated by analyzing its transformation products by LC-MS and the predominant role of hydroxyl radicals has been confirmed. Finally, the efficiency of the anodic TiO2 nanotube layer has been tested in real wastewater reaching up to 45% of sulfamethoxazole degradation after 4 h.Web of Science2724art. no. 895

The MAPS Adaptive Secondary Mirror: First Light, Laboratory Work, and Achievements

The MMT Adaptive Optics exoPlanet Characterization System (MAPS) is a comprehensive update to the first generation MMT adaptive optics system (MMTAO), designed to produce a facility class suite of instruments whose purpose is to image nearby exoplanets. The system's adaptive secondary mirror (ASM), although comprised in part of legacy components from the MMTAO ASM, represents a major leap forward in engineering, structure and function. The subject of this paper is the design, operation, achievements and technical issues of the MAPS adaptive secondary mirror. We discuss laboratory preparation for on-sky engineering runs, the results of those runs and the issues we discovered, what we learned about those issues in a follow-up period of laboratory work, and the steps we are taking to mitigate them.Comment: 22 pages, 22 images, 2 tables, submitted to SPIE Proceedings (Unconventional Imaging, Sensing and Adaptive Optics 2023 Conference

Etude des conséquences de l'evolution de la structure chimique sur la variation des propriétés physiques de polymères soumis à un vieillissement photochimique

L'objectif majeur de cette thèse était de passer dans la compréhension des phénomènes de photovieillissement, du niveau moléculaire au niveau macroscopique. Pour ce faire, trois polymères dont le vieillissement est gouverné par des réactions de réticulation et / ou de coupures de chaîne, ont été étudiés. Nous avons principalement développé l'utilisation de la microscopie à force atomique en effectuant des nanoindentations tant à la surface que dans l'épaisseur du matériau irradié et comparé les resultats à de nombreuses autres techniques. Cette mèthodologie nous a permis de progresser dans la connaissance des relations qui existent entre modification de la structure chimique et variation des propriétés physiques de polymères sous l'impact du photovieillissement.CLERMONT FD-BCIU Sci.et Tech. (630142101) / SudocSudocFranceF

Etude des conséquences de l'évolution de la structure chimique sur la variation des propriétés physiques de polymères soumis à un vieillissement photochimique

L'exposition des polymères aux contraintes de leur environnement d'usage provoque une modification de la structure chimique des macromolécules qui se traduit par une évolution irréversible de leurs propriétés fonctionnelles. L'objectif majeur de cette thèse était de passer, dans la compréhension des phénomènes de photovieillissement, du niveau moléculaire au niveau macroscopique. Pour ce faire, trois polymères dont le vieillissement est gouverné par des réactions de re ticulation et / ou de coupures de chaîne, ont été étudiés. Nous avons principalement développé l'utilisation de la microscopie à force atomique en effectuant des nanoindentations tant à la surface que dans l'épaisseur du matériau irradié et comparé les résultats à de nombreuses autres techniques. Cette méthodologie nous a permis de progresser dans la connaissance des relations qui existent entre modification de la structure chimique et variation des propriétés physiques de polymères sous l'impact du photovieillissementCLERMONT FD-BCIU Sci.et Tech. (630142101) / SudocSudocFranceF

Innovative depollution treatment using multi-valent iron species: from fundamental study to application in municipal wastewater

International audienceIn this work, a new combination of oxidation treatments for the degradation of bisphenol A (BPA) is investigated. This innovative wastewater (WW) treatment includes the use of ferrate (FeO42−) and its decomposition byproducts under dark and UVA irradiation. The oxidation by ferrate leads to a fast but incomplete degradation of BPA with a degradation extent of 45% after 60 min under adopted experimental conditions. However, the ferrate decomposition byproducts which are constituted by solid iron species can be used to further improve the pollutant degradation efficiency. Indeed, ferrate-mediated heterogeneous photo-Fenton process is employed for the first time to enhance the degradation of BPA. With respect to the application for wastewater treatment, UVA irradiation (which is part of solar light), non-toxic and natural origin compounds such as ascorbic acid (AA) and ethylenediamine-N,N′-disuccinic acid (EDDS), are used to design a sustainable process. Under optimized conditions, the degradation extent of BPA using this newly designed treatment reaches almost 100% with AA and 70% with EDDS. In order to assess the feasibility of this treatment, the ferrate-mediated photo-Fenton process is applied to treat municipal wastewater. The obtained results in WW are highly encouraging since a maximum BPA degradation extent of 63% and 60% is observed after 300 min by using AA and EDDS, respectively