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Start Over Author "Salla I. Virtanen" Topic molecular dynamics simulation
4 results on '"Salla I. Virtanen"'

1. Inverse Conformational Selection in Lipid–Protein Binding

Author

Matti Javanainen, Salla I. Virtanen, Fernando Favela-Rosales, Chris Papadopoulos, Antonio Peón, Amélie Bacle, Anne M. Kiirikki, Patrick F.J. Fuchs, O. H. Samuli Ollila, Pavel Buslaev, Ángel Piñeiro, Rebeca García-Fandiño, Paula Milán Rodríguez, Tiago Mendes Ferreira, Markus S. Miettinen, Jesper J. Madsen, Josef Melcr, Ivan Gushchin, Thomas J. Piggot, Lipotoxicity and Channelopathies - ConicMeds (LitCh), Signalisation et Transports Ioniques Membranaires (STIM), Université de Poitiers-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS)-Université de Poitiers-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS), Nanoscience Center [Jyväskylä Univ] (NSC@JYU), University of Jyväskylä (JYU), Moscow Institute of Physics and Technology [Moscow] (MIPT), Centro de Investigación en Química Biolóxica e Materiais Moleculares (CIQUS ), Universidade de Santiago de Compostela [Spain] (USC ), Universidade do Porto = University of Porto, Tecnológico Nacional de México (TecNM), Martin-Luther-University Halle-Wittenberg, Laboratoire des biomolécules (LBM UMR 7203), Chimie Moléculaire de Paris Centre (FR 2769), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Institut de Chimie du CNRS (INC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut de Chimie du CNRS (INC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département de Chimie - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), UFR Sciences du Vivant [Sciences] - Université Paris Cité (UFR SDV UPCité), Université Paris Cité (UPCité), Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences (IOCB / CAS), Czech Academy of Sciences [Prague] (CAS), HiLIFE - Institute of Biotechnology [Helsinki] (BI), Helsinki Institute of Life Science (HiLIFE), Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of Chicago, University of South Florida [Tampa] (USF), Groningen Biomolecular Sciences and Biotechnology Institute (GBB), University of Groningen [Groningen], Max Planck Institute of Colloids and Interfaces, Max-Planck-Gesellschaft, 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), University of Southampton, Molecular Dynamics, Institute of Biotechnology, Biophysical chemistry, Gestionnaire, Hal Sorbonne Université, Université Paris Cité - UFR Sciences du Vivant [Sciences] (UPCité - UFR SDV), Université de Poitiers-Université de Tours-Centre National de la Recherche Scientifique (CNRS)-Université de Poitiers-Université de Tours-Centre National de la Recherche Scientifique (CNRS), Universidade do Porto, Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Département de Chimie - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Chimie Moléculaire de Paris Centre (FR 2769), Institut de Chimie du CNRS (INC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Paris - UFR Sciences du Vivant [Sciences] (UP - UFR SDV), Université de Paris (UP), University of Helsinki-University of Helsinki, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), and Université Paris sciences et lettres (PSL)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
DYNAMICS, ELECTRIC CHARGE, BILAYERS, PHOSPHATIDYLCHOLINE HEADGROUP, Membrane lipids, DEUTERIUM, Plasma protein binding, Molecular Dynamics Simulation, lipidit, 010402 general chemistry, 01 natural sciences, Biochemistry, biomolekyylit, Catalysis, 03 medical and health sciences, Molecular dynamics, kemialliset sidokset, Colloid and Surface Chemistry, Protein structure, PHOSPHOLIPID-BINDING, MAGNETIC-RESONANCE, [SDV.BBM] Life Sciences [q-bio]/Biochemistry, Molecular Biology, SEGMENTAL ORDER, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Conformational ensembles, Nuclear Magnetic Resonance, Biomolecular, 030304 developmental biology, chemistry.chemical_classification, 0303 health sciences, Chemistry, Biomolecule, MEMBRANE-LIPIDS, Proteins, Phosphatidylglycerols, General Chemistry, computer.file_format, Protein Data Bank, Lipids, 0104 chemical sciences, Biophysics, Phospholipid Binding, Phosphatidylcholines, MAS NMR, 1182 Biochemistry, cell and molecular biology, lipids (amino acids, peptides, and proteins), proteiinit, computer, Protein Binding
Abstract

International audience; Interest in lipid interactions with proteins and other biomolecules is emerging not only in fundamental biochemistry but also in the field of nanobiotechnology where lipids are commonly used, for example, in carriers of mRNA vaccines. The outward-facing components of cellular membranes and lipid nanoparticles, the lipid headgroups, regulate membrane interactions with approaching substances, such as proteins, drugs, RNA, or viruses. Because lipid headgroup conformational ensembles have not been experimentally determined in physiologically relevant conditions, an essential question about their interactions with other biomolecules remains unanswered: Do headgroups exchange between a few rigid structures, or fluctuate freely across a practically continuous spectrum of conformations? Here, we combine solid-state NMR experiments and molecular dynamics simulations from the NMRlipids Project to resolve the conformational ensembles of headgroups of four key lipid types in various biologically relevant conditions. We find that lipid headgroups sample a wide range of overlapping conformations in both neutral and charged cellular membranes, and that differences in the headgroup chemistry manifest only in probability distributions of conformations. Furthermore, the analysis of 894 protein-bound lipid structures from the Protein Data Bank suggests that lipids can bind to proteins in a wide range of conformations, which are not limited by the headgroup chemistry. We propose that lipids can select a suitable headgroup conformation from the wide range available to them to fit the various binding sites in proteins. The proposed inverse conformational selection model will extend also to lipid binding to targets other than proteins, such as drugs, RNA, and viruses.

Published
2021

2. The Convergence of the Hedgehog/Intein Fold in Different Protein Splicing Mechanisms

Author

George T. Lountos, Hideo Iwaï, Hannes M. Beyer, Kornelia M. Mikula, O. H. Samuli Ollila, Alexander Wlodawer, Salla I. Virtanen, A. Sesilja Aranko, Institute of Biotechnology, Biochemistry and Biotechnology, Biophysical chemistry, and University Management

Subjects
0301 basic medicine, STRUCTURAL BASIS, Proteases, PARTICLE MESH EWALD, RNA Splicing, Computational biology, Molecular Dynamics Simulation, DATA-COLLECTION, intein, Article, Catalysis, FULLY-AUTOMATIC CHARACTERIZATION, Inteins, Mycobacterium, Protein evolution, Inorganic Chemistry, lcsh:Chemistry, 03 medical and health sciences, Bacterial Proteins, DOMAIN, Protein splicing, CHYMOTRYPSIN, Catalytic Domain, Protein Splicing, Hedgehog Proteins, CRYSTAL-STRUCTURE, Physical and Theoretical Chemistry, protein evolution, Molecular Biology, Hedgehog, lcsh:QH301-705.5, Spectroscopy, 030102 biochemistry & molecular biology, REFINEMENT, Chemistry, Organic Chemistry, protein-splicing mechanism, protein engineering, protease, General Medicine, Protein engineering, EVOLUTION, Computer Science Applications, 030104 developmental biology, lcsh:Biology (General), lcsh:QD1-999, RNA splicing, 1182 Biochemistry, cell and molecular biology, Intein
Abstract

Protein splicing catalyzed by inteins utilizes many different combinations of amino-acid types at active sites. Inteins have been classified into three classes based on their characteristic sequences. We investigated the structural basis of the protein splicing mechanism of class 3 inteins by determining crystal structures of variants of a class 3 intein from Mycobacterium chimaera and molecular dynamics simulations, which suggested that the class 3 intein utilizes a different splicing mechanism from that of class 1 and 2 inteins. The class 3 intein uses a bond cleavage strategy reminiscent of proteases but share the same Hedgehog/INTein (HINT) fold of other intein classes. Engineering of class 3 inteins from a class 1 intein indicated that a class 3 intein would unlikely evolve directly from a class 1 or 2 intein. The HINT fold appears as structural and functional solution for trans-peptidyl and trans-esterification reactions commonly exploited by diverse mechanisms using different combinations of amino-acid types for the active-site residues.

Published
2020

3. Heterogeneous dynamics in partially disordered proteins

Author

Salla I. Virtanen, O. H. Samuli Ollila, Hideo Iwaï, Kornelia M. Mikula, Anne M. Kiirikki, Biochemistry and Biotechnology, Institute of Biotechnology, Hideo Iwai / Principal Investigator, Doctoral Programme in Drug Research, and Biophysical chemistry

Subjects
TONB, PREDICTION, Globular protein, Protein Conformation, 116 Chemical sciences, Protein domain, General Physics and Astronomy, Nerve Tissue Proteins, Molecular Dynamics Simulation, 010402 general chemistry, 114 Physical sciences, 01 natural sciences, 03 medical and health sciences, Molecular dynamics, Protein structure, DOMAIN, Bacterial Proteins, Protein Domains, Animals, Amino Acid Sequence, Physical and Theoretical Chemistry, N-15 RELAXATION, Conformational ensembles, Nuclear Magnetic Resonance, Biomolecular, 030304 developmental biology, chemistry.chemical_classification, Homeodomain Proteins, 0303 health sciences, Helicobacter pylori, Nitrogen Isotopes, Cell Membrane, CONFORMATIONAL DYNAMICS, Membrane Proteins, Periplasmic space, Nuclear magnetic resonance spectroscopy, 0104 chemical sciences, MODEL, Intrinsically Disordered Proteins, chemistry, ESCHERICHIA-COLI, Chemical physics, NMR-SPECTROSCOPY, FORCE-FIELD, BACKBONE DYNAMICS, Intein, Chickens
Abstract

Importance of disordered protein regions is increasingly recognized in biology, but their characterization remains challenging due to the lack of suitable experimental and theoretical methods. NMR experiments can detect multiple timescale dynamics and structural details of disordered protein regions, but their detailed interpretation is often difficult. Here we combine protein backbone(15)N spin relaxation data with molecular dynamics (MD) simulations to detect not only heterogeneous dynamics of large partially disordered proteins but also their conformational ensembles. We observed that the rotational dynamics of folded regions in partially disordered proteins is dominated by similar rigid body rotation as in globular proteins, thereby being largely independent of flexible disordered linkers. Disordered regions, on the other hand, exhibit complex rotational motions with multiple timescales below similar to 30 ns which are difficult to detect from experimental data alone, but can be captured by MD simulations. Combining MD simulations and backbone(15)N spin relaxation data, measured applying segmental isotopic labeling with salt-inducible split intein, we resolved the conformational ensemble and dynamics of partially disordered periplasmic domain of TonB protein fromHelicobacter pyloricontaining 250 residues. To demonstrate the universality of our approach, it was applied also to the partially disordered region of chicken Engrailed 2. Our results pave the way in understanding how TonB transfers energy from inner membrane to the outer membrane receptors in Gram-negative bacteria, as well as the function of other proteins with disordered domains.

Published
2020

4. Comparison of virtual high-throughput screening methods for the identification of phosphodiesterase-5 inhibitors

Author

Olli T. Pentikäinen, Sanna Niinivehmas, Jukka V. Lehtonen, Pekka A. Postila, and Salla I. Virtanen

Subjects
Cyclic Nucleotide Phosphodiesterases, Type 5, Virtual screening, High-Throughput Screening Methods, Drug discovery, Chemistry, General Chemical Engineering, High-throughput screening, Medical screening, Static Electricity, Drug Evaluation, Preclinical, Nanotechnology, General Chemistry, Computational biology, Library and Information Sciences, Molecular Dynamics Simulation, Phosphodiesterase 5 Inhibitors, Ligands, Computer Science Applications, High-Throughput Screening Assays, Substrate Specificity, User-Computer Interface, Docking (molecular), Catalytic Domain
Abstract

Reliable and effective virtual high-throughput screening (vHTS) methods are desperately needed to minimize the expenses involved in drug discovery projects. Here, we present an improvement to the negative image-based (NIB) screening: the shape, the electrostatics, and the solvation state of the target protein’s ligand-binding site are included into the vHTS. Additionally, the initial vHTS results are postprocessed with molecular mechanics/generalized Born surface area (MMGBSA) calculations to estimate the favorability of ligand-protein interactions. The results show that docking produces very good early enrichment for phosphodiesterase-5 (PDE-5); however, in general, the NIB and the ligand-based screening performed better with or without the added electrostatics. Furthermore, the postprocessing of the NIB screening results using MMGBSA calculations improved the early enrichment for the PDE-5 considerably, thus, making hit discovery affordable.

Published
2011

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