1
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Biasini E, Faccioli P. Functional, pathogenic, and pharmacological roles of protein folding intermediates. Proteins 2023. [PMID: 36779817 DOI: 10.1002/prot.26479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 02/09/2023] [Indexed: 02/14/2023]
Abstract
Protein expression and function in eukaryotic cells are tightly harmonized processes modulated by the combination of different layers of regulation, including transcription, processing, stability, and translation of messenger RNA, as well as assembly, maturation, sorting, recycling, and degradation of polypeptides. Integrating all these pathways and the protein quality control machinery, deputed to avoid the production and accumulation of aberrantly folded proteins, determines protein homeostasis. Over the last decade, the combined development of accurate time-resolved experimental techniques and efficient computer simulations has opened the possibility of investigating biological mechanisms at atomic resolution with physics-based models. A meaningful example is the reconstruction of protein folding pathways at atomic resolution, which has enabled the characterization of the folding kinetics of biologically relevant globular proteins consisting of a few hundred amino acids. Combining these innovative computational technologies with rigorous experimental approaches reveals the existence of non-native metastable states transiently appearing along the folding process of such proteins. Here, we review the primary evidence indicating that these protein folding intermediates could play roles in disparate biological processes, from the posttranslational regulation of protein expression to disease-relevant protein misfolding mechanisms. Finally, we discuss how the information encoded into protein folding pathways could be exploited to design an entirely new generation of pharmacological agents capable of promoting the selective degradation of protein targets.
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Affiliation(s)
- Emiliano Biasini
- Department of Cellular Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Pietro Faccioli
- Department of Physics, University of Trento, Trento, Italy
- Trento Institute for Fundamental Physics and Applications, Italian Institute for Nuclear Physics, Trento, Italy
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2
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Hauke P, Mattiotti G, Faccioli P. Dominant Reaction Pathways by Quantum Computing. PHYSICAL REVIEW LETTERS 2021; 126:028104. [PMID: 33512219 DOI: 10.1103/physrevlett.126.028104] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 12/18/2020] [Indexed: 06/12/2023]
Abstract
Characterizing thermally activated transitions in high-dimensional rugged energy surfaces is a very challenging task for classical computers. Here, we develop a quantum annealing scheme to solve this problem. First, the task of finding the most probable transition paths in configuration space is reduced to a shortest-path problem defined on a suitable weighted graph. Next, this optimization problem is mapped into finding the ground state of a generalized Ising model. A finite-size scaling analysis suggests this task may be solvable efficiently by a quantum annealing machine. Our approach leverages on the quantized nature of qubits to describe transitions between different system's configurations. Since it does not involve any lattice space discretization, it paves the way towards future biophysical applications of quantum computing based on realistic all-atom models.
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Affiliation(s)
- Philipp Hauke
- INO-CNR BEC Center and Department of Physics, University of Trento, Via Sommarive 14, I-38123 Trento, Italy
| | - Giovanni Mattiotti
- Department of Physics, University of Trento, Via Sommarive 14, I-38123 Trento, Italy
| | - Pietro Faccioli
- Department of Physics, University of Trento, Via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Via Sommarive 14, I-38123 Trento, Italy
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3
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Terruzzi L, Spagnolli G, Boldrini A, Requena JR, Biasini E, Faccioli P. All-atom simulation of the HET-s prion replication. PLoS Comput Biol 2020; 16:e1007922. [PMID: 32946455 PMCID: PMC7526898 DOI: 10.1371/journal.pcbi.1007922] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 09/30/2020] [Accepted: 08/03/2020] [Indexed: 11/18/2022] Open
Abstract
Prions are self-replicative protein particles lacking nucleic acids. Originally discovered for causing infectious neurodegenerative disorders, they have also been found to play several physiological roles in a variety of species. Functional and pathogenic prions share a common mechanism of replication, characterized by the ability of an amyloid conformer to propagate by inducing the conversion of its physiological, soluble counterpart. Since time-resolved biophysical experiments are currently unable to provide full reconstruction of the physico-chemical mechanisms responsible for prion replication, one must rely on computer simulations. In this work, we show that a recently developed algorithm called Self-Consistent Path Sampling (SCPS) overcomes the computational limitations of plain MD and provides a viable tool to investigate prion replication processes using state-of-the-art all-atom force fields in explicit solvent. First, we validate the reliability of SCPS simulations by characterizing the folding of a class of small proteins and comparing against the results of plain MD simulations. Next, we use SCPS to investigate the replication of the prion forming domain of HET-s, a physiological fungal prion for which high-resolution structural data are available. Our atomistic reconstruction shows remarkable similarities with a previously reported mechanism of mammalian PrPSc propagation obtained using a simpler and more approximate path sampling algorithm. Together, these results suggest that the propagation of prions generated by evolutionary distant proteins may share common features. In particular, in both these cases, prions propagate their conformation through a very similar templating mechanism. Prions are proteins capable of replicating in absence of nucleic acids. By propagating the information encoded in their conformation, prions exemplify the phenomenon of protein-based inheritance. These peculiar agents are associated with neurodegenerative pathologies in mammals, but also involved in a wide variety of physiological processes occurring in various biological contexts along the evolutionary scale. In this work, we apply a recently developed computational method to study the propagation mechanism of the fungal prion HET-s, using a realistic all-atom model. We find that the replication of HET-s shares fundamental features with the templated conversion of the mammalian prion PrPSc.
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Affiliation(s)
- Luca Terruzzi
- Sibylla Biotech SRL, Verona, Italy.,Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Povo, Trento, Italy
| | - Giovanni Spagnolli
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Povo, Trento, Italy.,Dulbecco Telethon Institute, University of Trento, Povo, Trento, Italy
| | - Alberto Boldrini
- Sibylla Biotech SRL, Verona, Italy.,Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Povo, Trento, Italy
| | - Jesús R Requena
- CIMUS Biomedical Research Institute & Department of Medical Sciences, University of Santiago de Compostela-IDIS, Spain
| | - Emiliano Biasini
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Povo, Trento, Italy.,Dulbecco Telethon Institute, University of Trento, Povo, Trento, Italy
| | - Pietro Faccioli
- Department of Physics, University of Trento, Povo, Trento, Italy.,INFN-TIFPA, University of Trento, Povo, Trento, Italy
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4
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Spagnolli G, Requena JR, Biasini E. Understanding prion structure and conversion. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 175:19-30. [PMID: 32958233 DOI: 10.1016/bs.pmbts.2020.07.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Since their original identification, prions have represented enigmatic agents that defy the classical concept of genetic inheritance. For almost four decades, the high-resolution structure of PrPSc, the infectious and misfolded counterpart of the cellular prion protein (PrPC), has remained elusive, mostly due to technical challenges posed by its high insolubility and aggregation propensity. As a result, such a lack of information has critically hampered the search for an effective therapy against prion diseases. Nevertheless, multiple attempts to get insights into the structure of PrPSc have provided important experimental constraints that, despite being at limited resolution, are paving the way for the application of computer-aided technologies to model the three-dimensional architecture of prions and their templated replication mechanism. Here, we review the most relevant studies carried out so far to elucidate the conformation of infectious PrPSc and offer an overview of the most advanced molecular models to explain prion structure and conversion.
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Affiliation(s)
- Giovanni Spagnolli
- Department of Cellular, Computational and Integrative Biology (CIBIO), Trento, TN, Italy; Dulbecco Telethon Institute, University of Trento, Trento, TN, Italy
| | - Jesús R Requena
- CIMUS Biomedical Research Institute & Department of Medical Sciences, University of Santiago de Compostela-IDIS, Santiago, Spain
| | - Emiliano Biasini
- Department of Cellular, Computational and Integrative Biology (CIBIO), Trento, TN, Italy; Dulbecco Telethon Institute, University of Trento, Trento, TN, Italy.
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5
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Vastola JJ, Holmes WR. Chemical Langevin equation: A path-integral view of Gillespie's derivation. Phys Rev E 2020; 101:032417. [PMID: 32289899 DOI: 10.1103/physreve.101.032417] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 02/25/2020] [Indexed: 12/16/2022]
Abstract
In 2000, Gillespie rehabilitated the chemical Langevin equation (CLE) by describing two conditions that must be satisfied for it to yield a valid approximation of the chemical master equation (CME). In this work, we construct an original path-integral description of the CME and show how applying Gillespie's two conditions to it directly leads to a path-integral equivalent to the CLE. We compare this approach to the path-integral equivalent of a large system size derivation and show that they are qualitatively different. In particular, both approaches involve converting many sums into many integrals, and the difference between the two methods is essentially the difference between using the Euler-Maclaurin formula and using Riemann sums. Our results shed light on how path integrals can be used to conceptualize coarse-graining biochemical systems and are readily generalizable.
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Affiliation(s)
- John J Vastola
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA and Quantitative Systems Biology Center, Vanderbilt University, Nashville, Tennessee 37235, USA
| | - William R Holmes
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA; Quantitative Systems Biology Center, Vanderbilt University, Nashville, Tennessee 37235, USA; and Department of Mathematics, Vanderbilt University, Nashville, Tennessee 37235, USA
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6
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Gershenson A, Gosavi S, Faccioli P, Wintrode PL. Successes and challenges in simulating the folding of large proteins. J Biol Chem 2020; 295:15-33. [PMID: 31712314 PMCID: PMC6952611 DOI: 10.1074/jbc.rev119.006794] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Computational simulations of protein folding can be used to interpret experimental folding results, to design new folding experiments, and to test the effects of mutations and small molecules on folding. However, whereas major experimental and computational progress has been made in understanding how small proteins fold, research on larger, multidomain proteins, which comprise the majority of proteins, is less advanced. Specifically, large proteins often fold via long-lived partially folded intermediates, whose structures, potentially toxic oligomerization, and interactions with cellular chaperones remain poorly understood. Molecular dynamics based folding simulations that rely on knowledge of the native structure can provide critical, detailed information on folding free energy landscapes, intermediates, and pathways. Further, increases in computational power and methodological advances have made folding simulations of large proteins practical and valuable. Here, using serpins that inhibit proteases as an example, we review native-centric methods for simulating the folding of large proteins. These synergistic approaches range from Gō and related structure-based models that can predict the effects of the native structure on folding to all-atom-based methods that include side-chain chemistry and can predict how disease-associated mutations may impact folding. The application of these computational approaches to serpins and other large proteins highlights the successes and limitations of current computational methods and underscores how computational results can be used to inform experiments. These powerful simulation approaches in combination with experiments can provide unique insights into how large proteins fold and misfold, expanding our ability to predict and manipulate protein folding.
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Affiliation(s)
- Anne Gershenson
- Department of Biochemistry and Molecular Biology, University of Massachusetts, Amherst, Massachusetts 01003; Molecular and Cellular Biology Graduate Program, University of Massachusetts, Amherst, Massachusetts 01003.
| | - Shachi Gosavi
- Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore-560065, India.
| | - Pietro Faccioli
- Dipartimento di Fisica, Universitá degli Studi di Trento, 38122 Povo (Trento), Italy; Trento Institute for Fundamental Physics and Applications, 38123 Povo (Trento), Italy.
| | - Patrick L Wintrode
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland 21201.
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7
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Wang F, Orioli S, Ianeselli A, Spagnolli G, A Beccara S, Gershenson A, Faccioli P, Wintrode PL. All-Atom Simulations Reveal How Single-Point Mutations Promote Serpin Misfolding. Biophys J 2019; 114:2083-2094. [PMID: 29742402 DOI: 10.1016/j.bpj.2018.03.027] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Revised: 03/09/2018] [Accepted: 03/13/2018] [Indexed: 10/17/2022] Open
Abstract
Protein misfolding is implicated in many diseases, including serpinopathies. For the canonical inhibitory serpin α1-antitrypsin, mutations can result in protein deficiencies leading to lung disease, and misfolded mutants can accumulate in hepatocytes, leading to liver disease. Using all-atom simulations based on the recently developed bias functional algorithm, we elucidate how wild-type α1-antitrypsin folds and how the disease-associated S (Glu264Val) and Z (Glu342Lys) mutations lead to misfolding. The deleterious Z mutation disrupts folding at an early stage, whereas the relatively benign S mutant shows late-stage minor misfolding. A number of suppressor mutations ameliorate the effects of the Z mutation, and simulations on these mutants help to elucidate the relative roles of steric clashes and electrostatic interactions in Z misfolding. These results demonstrate a striking correlation between atomistic events and disease severity and shine light on the mechanisms driving chains away from their correct folding routes.
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Affiliation(s)
- Fang Wang
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland
| | - Simone Orioli
- Dipartimento di Fisica, Università degli Studi di Trento, Povo (Trento), Italy; Trento Institute for Fundamental Physics and Applications, Povo (Trento), Italy
| | - Alan Ianeselli
- Dipartimento di Fisica, Università degli Studi di Trento, Povo (Trento), Italy; Trento Institute for Fundamental Physics and Applications, Povo (Trento), Italy
| | - Giovanni Spagnolli
- Dipartimento di Fisica, Università degli Studi di Trento, Povo (Trento), Italy; Trento Institute for Fundamental Physics and Applications, Povo (Trento), Italy
| | - Silvio A Beccara
- Dipartimento di Fisica, Università degli Studi di Trento, Povo (Trento), Italy; Trento Institute for Fundamental Physics and Applications, Povo (Trento), Italy
| | - Anne Gershenson
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, Massachusetts.
| | - Pietro Faccioli
- Dipartimento di Fisica, Università degli Studi di Trento, Povo (Trento), Italy; Trento Institute for Fundamental Physics and Applications, Povo (Trento), Italy.
| | - Patrick L Wintrode
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland.
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8
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Wodak SJ, Paci E, Dokholyan NV, Berezovsky IN, Horovitz A, Li J, Hilser VJ, Bahar I, Karanicolas J, Stock G, Hamm P, Stote RH, Eberhardt J, Chebaro Y, Dejaegere A, Cecchini M, Changeux JP, Bolhuis PG, Vreede J, Faccioli P, Orioli S, Ravasio R, Yan L, Brito C, Wyart M, Gkeka P, Rivalta I, Palermo G, McCammon JA, Panecka-Hofman J, Wade RC, Di Pizio A, Niv MY, Nussinov R, Tsai CJ, Jang H, Padhorny D, Kozakov D, McLeish T. Allostery in Its Many Disguises: From Theory to Applications. Structure 2019; 27:566-578. [PMID: 30744993 PMCID: PMC6688844 DOI: 10.1016/j.str.2019.01.003] [Citation(s) in RCA: 234] [Impact Index Per Article: 46.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 11/29/2018] [Accepted: 01/02/2019] [Indexed: 12/19/2022]
Abstract
Allosteric regulation plays an important role in many biological processes, such as signal transduction, transcriptional regulation, and metabolism. Allostery is rooted in the fundamental physical properties of macromolecular systems, but its underlying mechanisms are still poorly understood. A collection of contributions to a recent interdisciplinary CECAM (Center Européen de Calcul Atomique et Moléculaire) workshop is used here to provide an overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems. The main conceptual frameworks instrumental in driving the field are discussed. We illustrate the role of these frameworks in illuminating molecular mechanisms and explaining cellular processes, and describe some of their promising practical applications in engineering molecular sensors and informing drug design efforts.
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Affiliation(s)
| | | | - Nikolay V Dokholyan
- Department of Biochemistry & Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Departments of Pharmacology and Biochemistry & Molecular Biology, Penn State Medical Center, Hershey, PA, USA
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A(∗)STAR), and Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Amnon Horovitz
- Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Jing Li
- Departments of Biology and T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, USA
| | - Vincent J Hilser
- Departments of Biology and T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, USA
| | - Ivet Bahar
- School of Medicine, University of Pittsburgh, Pittsburgh, USA
| | | | - Gerhard Stock
- Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University, Freiburg, Germany
| | - Peter Hamm
- Department of Chemistry, University of Zurich, Zurich, Switzerland
| | - Roland H Stote
- Department of Integrative Structural Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France
| | - Jerome Eberhardt
- Department of Integrative Structural Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France
| | - Yassmine Chebaro
- Department of Integrative Structural Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France
| | - Annick Dejaegere
- Department of Integrative Structural Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France
| | - Marco Cecchini
- Institut de Chimie de Strasbourg, UMR7177 CNRS & Université de Strasbourg, Strasbourg, France
| | | | - Peter G Bolhuis
- van 't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam, Netherlands
| | - Jocelyne Vreede
- van 't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam, Netherlands
| | - Pietro Faccioli
- Physics Department, Università di Trento and INFN-TIFPA, Trento, Italy
| | - Simone Orioli
- Physics Department, Università di Trento and INFN-TIFPA, Trento, Italy
| | - Riccardo Ravasio
- Institute of Physics, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Le Yan
- Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106, USA
| | - Carolina Brito
- Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS 91501-970, Brazil
| | - Matthieu Wyart
- Institute of Physics, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Paraskevi Gkeka
- Structure Design and Informatics, Sanofi R&D, Chilly-Mazarin, France
| | - Ivan Rivalta
- École Normale Supérieure de Lyon, Université de Lyon, CNRS, Université Claude Bernard Lyon 1, Lyon, France
| | - Giulia Palermo
- Department of Chemistry and Biochemistry, University of California, San Diego, USA; Department of Bioengineering, University of California Riverside, CA 92507, USA
| | - J Andrew McCammon
- Department of Chemistry and Biochemistry, University of California, San Diego, USA
| | - Joanna Panecka-Hofman
- Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland
| | - Rebecca C Wade
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS) and Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany; Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany
| | - Antonella Di Pizio
- Leibniz-Institute for Food Systems Biology, Technical University of Munich, Munich, Germany
| | - Masha Y Niv
- Institute of Biochemistry, Food Science and Nutrition, Robert H Smith Faculty of Agriculture Food and Environment, The Hebrew University, Jerusalem, Israel
| | - Ruth Nussinov
- Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, USA; Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Chung-Jung Tsai
- Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, USA
| | - Hyunbum Jang
- Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, USA
| | - Dzmitry Padhorny
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, USA
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, USA
| | - Tom McLeish
- Department of Physics, University of York, York, UK
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9
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Cuendet MA, Margul DT, Schneider E, Vogt-Maranto L, Tuckerman ME. Endpoint-restricted adiabatic free energy dynamics approach for the exploration of biomolecular conformational equilibria. J Chem Phys 2018; 149:072316. [DOI: 10.1063/1.5027479] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Affiliation(s)
- Michel A. Cuendet
- Molecular Modeling Group, Swiss Institute of Bioinformatics, UNIL Sorge, 1015 Lausanne, Switzerland
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York 10065, USA
| | - Daniel T. Margul
- Department of Chemistry, New York University, New York, New York 10003, USA
| | - Elia Schneider
- Department of Chemistry, New York University, New York, New York 10003, USA
| | | | - Mark E. Tuckerman
- Department of Chemistry, New York University, New York, New York 10003, USA
- Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, 3663 Zhongshan Road North, Shanghai 200062, China
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10
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Ianeselli A, Orioli S, Spagnolli G, Faccioli P, Cupellini L, Jurinovich S, Mennucci B. Atomic Detail of Protein Folding Revealed by an Ab Initio Reappraisal of Circular Dichroism. J Am Chem Soc 2018; 140:3674-3682. [DOI: 10.1021/jacs.7b12399] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Alan Ianeselli
- Centre for Integrative Biology, Trento University, Via Sommarive 9, 38128 Povo, Trento, Italy
| | - Simone Orioli
- Physics Department, Trento University, Via Sommarive 14, 38128 Povo, Trento, Italy
- INFN-TIFPA, Via Sommarive 14, 38128 Povo, Trento, Italy
| | - Giovanni Spagnolli
- Centre for Integrative Biology, Trento University, Via Sommarive 9, 38128 Povo, Trento, Italy
| | - Pietro Faccioli
- Physics Department, Trento University, Via Sommarive 14, 38128 Povo, Trento, Italy
- INFN-TIFPA, Via Sommarive 14, 38128 Povo, Trento, Italy
| | - Lorenzo Cupellini
- Dipartimento di Chimica e Chimica Industriale, University of Pisa, via G. Moruzzi 13, 56124, Pisa, Italy
| | - Sandro Jurinovich
- Dipartimento di Chimica e Chimica Industriale, University of Pisa, via G. Moruzzi 13, 56124, Pisa, Italy
| | - Benedetta Mennucci
- Dipartimento di Chimica e Chimica Industriale, University of Pisa, via G. Moruzzi 13, 56124, Pisa, Italy
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11
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Orioli S, Ianeselli A, Spagnolli G, Faccioli P. All-atom calculation of protein free-energy profiles. J Chem Phys 2017; 147:152724. [PMID: 29055321 DOI: 10.1063/1.5006039] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The Bias Functional (BF) approach is a variational method which enables one to efficiently generate ensembles of reactive trajectories for complex biomolecular transitions, using ordinary computer clusters. For example, this scheme was applied to simulate in atomistic detail the folding of proteins consisting of several hundreds of amino acids and with experimental folding time of several minutes. A drawback of the BF approach is that it produces trajectories which do not satisfy microscopic reversibility. Consequently, this method cannot be used to directly compute equilibrium observables, such as free energy landscapes or equilibrium constants. In this work, we develop a statistical analysis which permits us to compute the potential of mean-force (PMF) along an arbitrary collective coordinate, by exploiting the information contained in the reactive trajectories calculated with the BF approach. We assess the accuracy and computational efficiency of this scheme by comparing its results with the PMF obtained for a small protein by means of plain molecular dynamics.
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Affiliation(s)
- S Orioli
- Dipartimento di Fisica, Università degli Studi di Trento, Via Sommarive 14, Povo (Trento) I-38123, Italy
| | - A Ianeselli
- Dipartimento di Fisica, Università degli Studi di Trento, Via Sommarive 14, Povo (Trento) I-38123, Italy
| | - G Spagnolli
- Dipartimento di Fisica, Università degli Studi di Trento, Via Sommarive 14, Povo (Trento) I-38123, Italy
| | - P Faccioli
- Dipartimento di Fisica, Università degli Studi di Trento, Via Sommarive 14, Povo (Trento) I-38123, Italy
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