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146 results on '"Reinharz, Vladimir"'

1. AlphaFold2 can predict single-mutation effects

Author

McBride, John M., Polev, Konstantin, Abdirasulov, Amirbek, Reinharz, Vladimir, Grzybowski, Bartosz A., and Tlusty, Tsvi

Subjects
Quantitative Biology - Biomolecules, Physics - Biological Physics, Quantitative Biology - Populations and Evolution
Abstract

AlphaFold2 (AF) is a promising tool, but is it accurate enough to predict single mutation effects? Here, we report that the localized structural deformation between protein pairs differing by only 1-3 mutations -- as measured by the effective strain -- is correlated across \num{3901} experimental and AF-predicted structures. Furthermore, analysis of ${\sim} 11000$ proteins shows that the local structural change correlates with various phenotypic changes. These findings suggest that AF can predict the range and magnitude of single-mutation effects on average, and we propose a method to improve precision of AF predictions and to indicate when predictions are unreliable.

Published
2022

3. $\alpha\beta$ DCA method identifies unspecific binding but specific disruption of the group I intron by the StpA chaperone

Author

Reinharz, Vladimir and Tlusty, Tsvi

Subjects
Quantitative Biology - Biomolecules, Physics - Biological Physics, Quantitative Biology - Populations and Evolution
Abstract

Chaperone protein - the most disordered among all protein groups - help RNAs fold into their functional structure by destabilizing misfolded configurations or stabilizing the functional ones. But disentangling the mechanism underlying RNA chaperoning is challenging, mostly due to inherent disorder of the chaperones and the transient nature of their interactions with RNA. In particular, it is unclear how specific the interactions are and what role is played by amino acid charge and polarity patterns. Here, we address these questions in the RNA chaperone StpA. We adapted direct coupling analysis (DCA) into the $\alpha\beta$DCA method that can treat in tandem sequences written in two alphabets, nucleotides and amino acids. With $\alpha\beta$DCA, we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure. Moreover, the interactions are strongly associated with the charge pattern: negatively charged regions in the destabilizing StpA N-terminal affect a few specific positions in the RNA, located in stems and in the pseudoknot. In contrast, positive regions in the C-terminal contain strongly coupled amino acids that promote non-specific or weakly-specific binding to the RNA. The present study opens new avenues to examine the functions of disordered proteins and to design disruptive proteins based on their charge patterns.

Published
2019

5. Stochastic Sampling of Structural Contexts Improves the Scalability and Accuracy of RNA 3D Module Identification

Author

Sarrazin-Gendron, Roman, Yao, Hua-Ting, Reinharz, Vladimir, Oliver, Carlos G., Ponty, Yann, Waldispühl, Jérôme, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, and Schwartz, Russell, editor

Published
2020
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7. Using structural and evolutionary information to detect and correct pyrosequencing errors in non-coding RNAs

Author

Reinharz, Vladimir, Ponty, Yann, and Waldispühl, Jérôme

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Analysis of the sequence-structure relationship in RNA molecules are essential to evolutionary studies but also to concrete applications such as error-correction methodologies in sequencing technologies. The prohibitive sizes of the mutational and conformational landscapes combined with the volume of data to proceed require efficient algorithms to compute sequence-structure properties. More specifically, here we aim to calculate which mutations increase the most the likelihood of a sequence to a given structure and RNA family. In this paper, we introduce RNApyro, an efficient linear-time and space inside-outside algorithm that computes exact mutational probabilities under secondary structure and evolutionary constraints given as a multiple sequence alignment with a consensus structure. We develop a scoring scheme combining classical stacking base pair energies to novel isostericity scales, and apply our techniques to correct point-wise errors in 5s and 16s rRNA sequences. Our results suggest that RNApyro is a promising algorithm to complement existing tools in the NGS error-correction pipeline., Comment: Extended version of RECOMB'13

Published
2013

10. Modeling suggests that virion production cycles within individual cells is key to understanding acute hepatitis B virus infection kinetics

Author

Hailegiorgis, Atesmachew, primary, Ishida, Yuji, additional, Collier, Nicholson, additional, Imamura, Michio, additional, Shi, Zhenzhen, additional, Reinharz, Vladimir, additional, Tsuge, Masataka, additional, Barash, Danny, additional, Hiraga, Nobuhiko, additional, Yokomichi, Hiroshi, additional, Tateno, Chise, additional, Ozik, Jonathan, additional, Uprichard, Susan L., additional, Chayama, Kazuaki, additional, and Dahari, Harel, additional

Published
2023
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12. Automatic Exploration of the Natural Variability of RNA Non-Canonical Geometric Patterns with a Parameterized Sampling Technique

Author

Théo Boury and Yann Ponty and Vladimir Reinharz, Boury, Théo, Ponty, Yann, Reinharz, Vladimir, Théo Boury and Yann Ponty and Vladimir Reinharz, Boury, Théo, Ponty, Yann, and Reinharz, Vladimir

Abstract

Motivation. Recurrent substructures in RNA, known as 3D motifs, consist of networks of base pair interactions and are critical to understanding the relationship between structure and function. Their structure is naturally expressed as a graph which has led to many graph-based algorithms to automatically catalog identical motifs found in 3D structures. Yet, due to the complexity of the problem, state-of-the-art methods are often optimized to find exact matches, limiting the search to a subset of potential solutions, or do not allow explicit control over the desired variability. Results. We developed FuzzTree, a method able to efficiently sample approximate instances of an RNA motif, abstracted as a subgraph within a target RNA structure. It is the first method that allows explicit control over (1) the admissible geometric variability in the interactions; (2) the number of missing edges; and (3) the introduction of discontinuities in the backbone given close distances in the 3D structure. Our tool relies on a multidimensional Boltzmann sampling, having complexity parameterized by the treewidth of the requested motif. We applied our method to the well-known internal loop Kink-Turn motif, which can be divided into 12 subgroups. Given only the graph representing the main Kink-Turn subgroup, FuzzTree retrieved over 3/4 of all kink-turns. We also highlighted two occurrences of new sampled patterns. Our tool is available as free software and can be customized for different parameters and types of graphs.

Published
2023
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13. Advances in parameter estimation for mathematical models of hepatitis C viral kinetics.

Author

Reinharz, Vladimir, Churkin, Alexander, Dahari, Harel, and Barash, Danny

Subjects
*VIRAL hepatitis, *PARAMETER estimation, *MATHEMATICAL models, *MULTISCALE modeling, *HEPATITIS C virus
Abstract

Mathematical models, some of which incorporate both intracellular and extracellular hepatitis C viral dynamics, have been advanced in recent years to study HCV-host kinetics and antivirals mode of action and efficacy. The standard hepatitis C virus (HCV) dynamic model keeps track of uninfected hepatocytes, infected hepatocytes, and free virus in blood. In multiscale models, a fourth equation accounts for the intracellular viral RNA (vRNA) kinetics in an infected cell. A multiscale model with vRNA kinetics consideration is substantially more difficult to solve, with the governing differential equations that are stiff. In previous contributions, we developed and implemented stable and efficient numerical methods for both the solution of the model equations and parameter estimation. In this contribution, we perform sensitivity analysis on model parameters to gain insight on important properties of these models and to ensure our numerical methods can be safely used for HCV viral dynamic simulations. [ABSTRACT FROM AUTHOR]

Published
2023
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14. A Linear Inside-Outside Algorithm for Correcting Sequencing Errors in Structured RNAs

Author

Reinharz, Vladimir, Ponty, Yann, Waldispühl, Jérôme, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Deng, Minghua, editor, Jiang, Rui, editor, Sun, Fengzhu, editor, and Zhang, Xuegong, editor

Published
2013
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19. AlphaFold2 can predict single-mutation effects on structure and phenotype

Author

McBride, John M., Polev, Konstantin, Abdirasulov, Amirbek, Reinharz, Vladimir, Grzybowski, Bartosz A., and Tlusty, Tsvi

Subjects
Quantitative Biology - Biomolecules, Biological Physics (physics.bio-ph), FOS: Biological sciences, Populations and Evolution (q-bio.PE), FOS: Physical sciences, Biomolecules (q-bio.BM), Physics - Biological Physics, Quantitative Biology - Populations and Evolution
Abstract

AlphaFold2 (AF) is a promising tool, but is it accurate enough to predict single mutation effects? Here, we report that a measure for localized structural deformation between protein pairs differing by only 1-3 mutations is correlated across 3,901 experimental and AF-predicted structures. Furthermore, analysis of $\sim$11,000 proteins shows that the local structural change correlates with various phenotypic changes. These findings suggest that AF can predict the range and magnitude of single-mutation effects on average, and we propose a method to improve precision of AF predictions and to indicate when predictions are unreliable.

Published
2022

20. Modelling Agile Backlogs as Composable Artefacts to support Developers and Product Owners

Author

Mosser, Sébastien, Pulgar, Corinne, Reinharz, Vladimir, Mosser, Sébastien, Pulgar, Corinne, and Reinharz, Vladimir

Abstract

The DevOps paradigm combines (agile) software development and IT operations to deliver high-quality software, thanks to a feedback loop where “ops” feed “devs” and vice versa. In this context, a central challenge is to reduce as much as possible the duration of the feedback loop, allowing stakeholders to reduce their time-to-market and release process duration. This paper describes how to model a product backlog (usually expressed as informal user stories in plain text in an agile context) as a queryable graph-based model. This graph is automatically extracted from existing artifacts thanks to natural language processing techniques. Then, developers and product owners can support their iteration planning process by leveraging the model, enacting a short-range impact analysis feedback loop of their planning decisions. The approach considers the iterative and incremental nature of agile methods through the definition of composition operators to incrementally build the models. We have validated this approach on five industrial scenarios, on top of a reference open-source dataset of 22 product backlogs, representing 1, 671 user stories.

Published
2022

22. Multiphasic hepatitis B virus kinetic patterns in humanized chimeric mice can be explained via stochastic agent-based modeling of intracellular virion production cycles

Author

Hailegiorgis, Atesmachew, primary, Ishida, Yuji, additional, Collier, Nicholson, additional, Imamura, Michio, additional, Shi, Zhenzhen, additional, Reinharz, Vladimir, additional, Tsuge, Masataka, additional, Barash, Danny, additional, Hiraga, Nobuhiko, additional, Yokomichi, Hiroshi, additional, Tateno, Chise, additional, Ozik, Jonathan, additional, Uprichard, Susan L., additional, Chayama, Kazuaki, additional, and Dahari, Harel, additional

Published
2022
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24. A Graph-Based Similarity Approach to Classify Recurrent Complex Motifs from Their Context in RNA Structures

Author

Gianfrotta, Coline, Reinharz, Vladimir, Barth, Dominique, Denise, Alain, Données et algorithmes pour une ville intelligente et durable - DAVID (DAVID), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université du Québec à Montréal = University of Québec in Montréal (UQAM), Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
RNA 3D folding, RNA motif, [SDV]Life Sciences [q-bio], [INFO]Computer Science [cs], Applied computing → Molecular structural biology, Graph similarity, clustering
Abstract

This article proposes to use an RNA graph similarity metric, based on the MCES resolution problem, to compare the occurrences of specific complex motifs in RNA graphs, according to their context represented as subgraph. We rely on a new modeling by graphs of these contexts, at two different levels of granularity, and obtain a classification of these graphs, which is consistent with the RNA 3D structure. RNA many non-translational functions, as a ribozyme, riboswitch, or ribosome, require complex structures. Those are composed of a rigid skeleton, a set of canonical interactions called the secondary structure. Decades of experimental and theoretical work have produced precise thermodynamic parameters and efficient algorithms to predict, from sequence, the secondary structure of RNA molecules. On top of the skeleton, the nucleotides form an intricate network of interactions that are not captured by present thermodynamic models. This network has been shown to be composed of modular motifs, that are linked to function, and have been leveraged for better prediction and design. A peculiar subclass of complex structural motifs are those connecting RNA regions far away in the secondary structure. They are crucial to predict since they determine the global shape of the molecule, therefore important for the function. In this paper, we show by using our graph approach that the context is important for the formation of conserved complex structural motifs. We furthermore show that a natural classification of structural variants of the motifs emerges from their context. We explore the cases of three known motif families and we exhibit their experimentally emerging classification., LIPIcs, Vol. 190, 19th International Symposium on Experimental Algorithms (SEA 2021), pages 19:1-19:18

Published
2021

26. A Graph-Based Similarity Approach to Classify Recurrent Complex Motifs from Their Context in RNA Structures

Author

Coline Gianfrotta and Vladimir Reinharz and Dominique Barth and Alain Denise, Gianfrotta, Coline, Reinharz, Vladimir, Barth, Dominique, Denise, Alain, Coline Gianfrotta and Vladimir Reinharz and Dominique Barth and Alain Denise, Gianfrotta, Coline, Reinharz, Vladimir, Barth, Dominique, and Denise, Alain

Abstract

This article proposes to use an RNA graph similarity metric, based on the MCES resolution problem, to compare the occurrences of specific complex motifs in RNA graphs, according to their context represented as subgraph. We rely on a new modeling by graphs of these contexts, at two different levels of granularity, and obtain a classification of these graphs, which is consistent with the RNA 3D structure. RNA many non-translational functions, as a ribozyme, riboswitch, or ribosome, require complex structures. Those are composed of a rigid skeleton, a set of canonical interactions called the secondary structure. Decades of experimental and theoretical work have produced precise thermodynamic parameters and efficient algorithms to predict, from sequence, the secondary structure of RNA molecules. On top of the skeleton, the nucleotides form an intricate network of interactions that are not captured by present thermodynamic models. This network has been shown to be composed of modular motifs, that are linked to function, and have been leveraged for better prediction and design. A peculiar subclass of complex structural motifs are those connecting RNA regions far away in the secondary structure. They are crucial to predict since they determine the global shape of the molecule, therefore important for the function. In this paper, we show by using our graph approach that the context is important for the formation of conserved complex structural motifs. We furthermore show that a natural classification of structural variants of the motifs emerges from their context. We explore the cases of three known motif families and we exhibit their experimentally emerging classification.

Published
2021
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28. Repliement de l'ARN

Author

Ponty, Yann, Reinharz, Vladimir, Algorithms and Models for Integrative BIOlogy (AMIBIO), Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Département d'informatique [Montréal], Université du Québec à Montréal = University of Québec in Montréal (UQAM), Annie Chateau, Mikaël Salson, and Ponty, Yann

Subjects
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience

Published
2020

38. Mining for recurrent long-range interactions in RNA structures reveals embedded hierarchies in network families

Author

Reinharz, Vladimir, Soulé, Antoine, Westhof, Eric, Waldispühl, Jérôme, Denise, Alain, McGill Centre for Bioinformatics ( MCB ), McGill University, Ben-Gourion University of the Negev, Laboratoire d'informatique de l'École polytechnique [Palaiseau] ( LIX ), Centre National de la Recherche Scientifique ( CNRS ) -École polytechnique ( X ), Architecture et réactivité de l'ARN ( ARN ), Université Louis Pasteur - Strasbourg I-Centre National de la Recherche Scientifique ( CNRS ), Institut de Biologie Intégrative de la Cellule ( I2BC ), Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Sud - Paris 11 ( UP11 ), Bioinformatique (LRI) ( BioInfo - LRI ), Laboratoire de Recherche en Informatique ( LRI ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ), McGill Centre for Bioinformatics (MCB), McGill University = Université McGill [Montréal, Canada], Ben-Gurion University of the Negev (BGU), Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Architecture et réactivité de l'ARN (ARN), Université Louis Pasteur - Strasbourg I-Centre National de la Recherche Scientifique (CNRS), Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Bioinformatique (LRI) (BioInfo - LRI), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), and CentraleSupélec-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [ SDV.BBM.BS ] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biomolecules [q-bio.BM]
Abstract

International audience; The wealth of the combinatorics of nucleotide base pairs enables RNA molecules to assemble into sophisticated interaction networks, which are used to create complex 3D substructures. These interaction networks are essential to shape the 3D architecture of the molecule, and also to provide the key elements to carry molecular functions such as protein or lig-and binding. They are made of organised sets of long-range tertiary interactions which connect distinct secondary structure elements in 3D structures. Here, we present a de novo data-driven approach to extract automatically from large data sets of full RNA 3D structures the recurrent interaction networks (RINs). Our methodology enables us for the first time to detect the interaction networks connecting distinct components of the RNA structure, highlighting their diversity and conservation through non-related functional RNAs. We use a graphical model to perform pairwise comparisons of all RNA structures available and to extract RINs and modules. Our analysis yields a complete catalog of RNA 3D structures available in the Protein Data Bank and reveals the intricate hierarchical organization of the RNA interaction networks and modules. We assembled our results in an online database (http://carnaval.lri.fr) which will be regularly updated. Within the site, a tool allows users with a novel RNA structure to detect automatically whether the novel structure contains previously observed RINs.

Published
2018

46. Additional file 1 of Reconstruction of ancestral RNA sequences under multiple structural constraints

Author

Tremblay-Savard, Olivier, Reinharz, Vladimir, and Waldispühl, Jérôme

Abstract

The file contains the algorithms of CalculateScores-1struct and CalculateScores- 2structs. It is followed by the running times of Fitch, Sankoff, CalculateScores-1struct and CalculateScores- 2structs on the simulated data sets. It also contains the list of bacterial strains used in the biological analysis. We also present additional results on the Glm and FinP-traJ clans reconstructions. (425 KB PDF)

Published
2016
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