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Akki AJ, Patil SA, Hungund S, Sahana R, Patil MM, Kulkarni RV, Raghava Reddy K, Zameer F, Raghu AV. Advances in Parkinson's disease research - A computational network pharmacological approach. Int Immunopharmacol 2024; 139:112758. [PMID: 39067399 DOI: 10.1016/j.intimp.2024.112758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 07/22/2024] [Accepted: 07/22/2024] [Indexed: 07/30/2024]
Abstract
Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, is projected to see a significant rise in incidence over the next three decades. The precise treatment of PD remains a formidable challenge, prompting ongoing research into early diagnostic methodologies. Network pharmacology, a burgeoning field grounded in systems biology, examines the intricate networks of biological systems to identify critical signal nodes, facilitating the development of multi-target therapeutic molecules. This approach systematically maps the components of Parkinson's disease, thereby reducing its complexity. In this review, we explore the application of network pharmacology workflows in PD, discuss the techniques employed in this field, and evaluate the current advancements and status of network pharmacology in the context of Parkinson's disease. The comprehensive insights will pave newer paths to explore early disease biomarkers and to develop diagnosis with a holistic in silico, in vitro, in vivo and clinical studies.
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Affiliation(s)
- Ali Jawad Akki
- Faculty of Science and Technology, BLDE (Deemed-to-be University), Vijayapura 586 103, India
| | - Shruti A Patil
- Faculty of Science and Technology, BLDE (Deemed-to-be University), Vijayapura 586 103, India
| | - Sphoorty Hungund
- Faculty of Science and Technology, BLDE (Deemed-to-be University), Vijayapura 586 103, India
| | - R Sahana
- Department of Computer Science and Engineering, RV Institute of Technology and Management, 560 076 Bengaluru, India
| | - Malini M Patil
- Department of Computer Science and Engineering, RV Institute of Technology and Management, 560 076 Bengaluru, India.
| | - Raghavendra V Kulkarni
- Faculty of Science and Technology, BLDE (Deemed-to-be University), Vijayapura 586 103, India
| | - K Raghava Reddy
- School of Chemical and Biomolecular Engineering, The University of Sydney, Sydney, NSW 12 2006, Australia
| | - Farhan Zameer
- Department of Dravyaguna (Ayurveda Pharmacology), Alva's Ayurveda Medical College, and PathoGutOmics Laboratory, ATMA Research Centre, Dakshina Kannada 574 227, India.
| | - Anjanapura V Raghu
- Department of Basic Sciences, Faculty of Engineering and Technology, CMR University, 562149 Bangalore, India.
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2
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Lopez DM, Castro CE, Sotomayor M. In-Silico Analyses of Molecular Force Sensors for Mechanical Characterization of Biological Systems. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.17.603923. [PMID: 39091752 PMCID: PMC11291006 DOI: 10.1101/2024.07.17.603923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Mechanical forces play key roles in biological processes such as cell migration and sensory perception. In recent years molecular force sensors have been developed as tools for in situ force measurements. Here we use all-atom steered molecular dynamics simulations to predict and study the relationship between design parameters and mechanical properties for three types of molecular force sensors commonly used in cellular biological research: two peptide-and one DNA-based. The peptide-based sensors consist of a pair of fluorescent proteins, which can undergo Förster resonance energy transfer (FRET), linked by spider silk (GPGGA) n or synthetic (GGSGGS) n disordered regions. The DNA-based sensor consists of two fluorophore-labeled strands of DNA that can be unzipped or sheared upon force application with a FRET signal as readout of dissociation. We simulated nine sensors, three of each kind. After equilibration, flexible peptide linkers of three different lengths were stretched by applying forces to their N-and C-terminal Cα atoms in opposite directions. Similarly, we equilibrated a DNA-based sensor and pulled on the phosphate atom of the terminal guanine of one strand and a selected phosphate atom on the other strand in the opposite direction. These simulations were performed at constant velocity (0.01 nm/ns - 10 nm/ns) and constant force (10 pN - 500 pN) for all versions of the sensors. Our results show how the force response of these sensors depends on their length, sequence, configuration and loading rate. Mechanistic insights gained from simulations analyses indicate that interpretation of experimental results should consider the influence of transient formation of secondary structure in peptide-based sensors and of overstretching in DNA-based sensors. These predictions can guide optimal fluorophore choice and facilitate the rational design of new sensors for use in protein, DNA, hybrid systems, and molecular devices. STATEMENT OF SIGNIFICANCE Biomolecular structures involved in various biological processes, including muscle function and sensory perception, generate, convey, and respond to mechanical forces. In-vivo accurate measurement of these forces is challenging but needed to understand biological function. Here we present a comprehensive computational analysis of three different types of molecular force sensors used to report pico-Newton level forces in biomolecular systems. Our atom-level simulation predictions provide mechanistic insight that can facilitate experimental data interpretation, selection of sensor design parameters, and the development of new force sensors tailored to specific applications and environments.
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3
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Mikaelian G, Megariotis G, Theodorou DN. Interactions of a Novel Anthracycline with Oligonucleotide DNA and Cyclodextrins in an Aqueous Environment. J Phys Chem B 2024; 128:6291-6307. [PMID: 38899795 PMCID: PMC11228990 DOI: 10.1021/acs.jpcb.4c02213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/07/2024] [Accepted: 06/11/2024] [Indexed: 06/21/2024]
Abstract
Berubicin, a chemotherapy medication belonging to the class of anthracyclines, is simulated in double-stranded DNA sequences and cyclodextrins in an aqueous environment via full-atom molecular dynamics simulations on the time scale of microseconds. The drug is studied in both the neutral and protonated states so as to better comprehend the role of its charge in the formed complexes. The noncovalent berubicin-DNA and berubicin-cyclodextrin complexes are investigated in detail, paying special attention to their thermodynamic description by employing the double decoupling method, the solvent balance method, the weighted solvent accessible surface model, and the linear interaction energy method. A novel approach for extracting the desolvation thermodynamics of the binding process is also presented. Both the binding and desolvation Gibbs energies are decomposed into entropic and enthalpic contributions so as to elucidate the nature of complexation and its driving forces. Selected structural and geometrical properties of all the complexes, which are all stable, are analyzed. Both cyclodextrins under consideration are widely utilized for drug delivery purposes, and a comparative investigation between their bound states with berubicin is carried out.
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Affiliation(s)
- Georgios Mikaelian
- School
of Chemical Engineering, National Technical
University of Athens (NTUA), 9 Heroon Polytechniou Street, Zografou Campus, 15780 Athens, GR ,Greece
| | - Grigorios Megariotis
- School
of Chemical Engineering, National Technical
University of Athens (NTUA), 9 Heroon Polytechniou Street, Zografou Campus, 15780 Athens, GR ,Greece
- School
of Engineering, Department of Mineral Resources Engineering, University of Western Macedonia, 50100 Kozani, Greece
| | - Doros N. Theodorou
- School
of Chemical Engineering, National Technical
University of Athens (NTUA), 9 Heroon Polytechniou Street, Zografou Campus, 15780 Athens, GR ,Greece
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4
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Yu T, Sudhakar N, Okafor CD. Illuminating ligand-induced dynamics in nuclear receptors through MD simulations. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2024; 1867:195025. [PMID: 38614450 DOI: 10.1016/j.bbagrm.2024.195025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 03/27/2024] [Accepted: 04/06/2024] [Indexed: 04/15/2024]
Abstract
Nuclear receptors (NRs) regulate gene expression in critical physiological processes, with their functionality finely tuned by ligand-induced conformational changes. While NRs may sometimes undergo significant conformational motions in response to ligand-binding, these effects are more commonly subtle and challenging to study by traditional structural or biophysical methods. Molecular dynamics (MD) simulations are a powerful tool to bridge the gap between static protein-ligand structures and dynamical changes that govern NR function. Here, we summarize a handful of recent studies that apply MD simulations to study NRs. We present diverse methodologies for analyzing simulation data with a detailed examination of the information each method can yield. By delving into the strengths, limitations and unique contributions of these tools, this review provides guidance for extracting meaningful data from MD simulations to advance the goal of understanding the intricate mechanisms by which ligands orchestrate a range of functional outcomes in NRs.
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Affiliation(s)
- Tracy Yu
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Nishanti Sudhakar
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - C Denise Okafor
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA; Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA.
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5
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Mondal R, Vaissier Welborn V. Dynamics accelerate the kinetics of ion diffusion through channels: Continuous-time random walk models beyond the mean field approximation. J Chem Phys 2024; 160:144109. [PMID: 38597306 DOI: 10.1063/5.0188469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 03/14/2024] [Indexed: 04/11/2024] Open
Abstract
Ion channels are proteins that play a significant role in physiological processes, including neuronal excitability and signal transduction. However, the precise mechanisms by which these proteins facilitate ion diffusion through cell membranes are not well understood. This is because experimental techniques to characterize ion channel activity operate on a time scale too large to understand the role of the various protein conformations on diffusion. Meanwhile, computational approaches operate on a time scale too short to rationalize the observed behavior at the microscopic scale. In this paper, we present a continuous-time random walk model that aims to bridge the scales between the atomistic models of ion channels and the experimental measurement of their conductance. We show how diffusion slows down in complex systems by using 3D lattices that map out the pore geometry of two channels: Nav1.7 and gramicidin. We also introduce spatial and dynamic site disorder to account for system heterogeneity beyond the mean field approximation. Computed diffusion coefficients show that an increase in spatial disorder slows down diffusion kinetics, while dynamic disorder has the opposite effect. Our results imply that microscopic or phenomenological models based on the potential of mean force data overlook the functional importance of protein dynamics on ion diffusion through channels.
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Affiliation(s)
- Ronnie Mondal
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, USA
- Macromolecules Innovation Institute, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - Valerie Vaissier Welborn
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, USA
- Macromolecules Innovation Institute, Virginia Tech, Blacksburg, Virginia 24061, USA
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6
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Raza S, Sarkar D, Chan LJG, Mae J, Sutter M, Petzold CJ, Kerfeld CA, Ralston CY, Gupta S, Vermaas JV. Comparative Pore Structure and Dynamics for Bacterial Microcompartment Shell Protein Assemblies in Sheets or Shells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.12.584231. [PMID: 38559214 PMCID: PMC10980050 DOI: 10.1101/2024.03.12.584231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semi-permeable shell proteins, analogous to many membrane-bound organelles. The shell proteins assemble into multimeric tiles; hexamers, trimers, and pentamers, and these tiles self-assemble into larger assemblies with icosahedral symmetry. While icosahedral shells are the predominant form in vivo, the tiles can also form nanoscale cylinders or sheets. The individual multimeric tiles feature central pores that are key to regulating transport across the protein shell. Our primary interest is to quantify pore shape changes in response to alternative component morphologies at the nanoscale. We use molecular modeling tools to develop atomically detailed models for both planar sheets of tiles and curved structures representative of the complete shells found in vivo. Subsequently, these models were animated using classical molecular dynamics simulations. From the resulting trajectories, we analyzed overall structural stability, water accessibility to individual residues, water residence time, and pore geometry for the hexameric and trimeric protein tiles from the Haliangium ochraceum model BMC shell. These exhaustive analyses suggest no substantial variation in pore structure or solvent accessibility between the flat and curved shell geometries. We additionally compare our analysis to hydroxyl radical footprinting data to serve as a check against our simulation results, highlighting specific residues where water molecules are bound for a long time. Although with little variation in morphology or water interaction, we propose that the planar and capsular morphology can be used interchangeably when studying permeability through BMC pores.
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Affiliation(s)
- Saad Raza
- MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing MI 48824
| | - Daipayan Sarkar
- MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing MI 48824
| | - Leanne Jade G Chan
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720
- Current address: Calico Life Sciences LLC, South San Francisco, CA 94080
| | - Joshua Mae
- MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing MI 48824
| | - Markus Sutter
- MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing MI 48824
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720
| | - Christopher J Petzold
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720
| | - Cheryl A Kerfeld
- MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing MI 48824
- Department Of Biochemistry and Molecular Biology, Michigan State University, East Lansing MI 48824
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720
| | - Corie Y Ralston
- Molecular Foundry Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720
| | - Sayan Gupta
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720
| | - Josh V Vermaas
- MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing MI 48824
- Department Of Biochemistry and Molecular Biology, Michigan State University, East Lansing MI 48824
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7
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Byju S, Hassan A, Whitford PC. The energy landscape of the ribosome. Biopolymers 2024; 115:e23570. [PMID: 38051695 DOI: 10.1002/bip.23570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 10/17/2023] [Accepted: 11/08/2023] [Indexed: 12/07/2023]
Abstract
The ribosome is a prototypical assembly that can be used to establish general principles and techniques for the study of biological molecular machines. Motivated by the fact that the dynamics of every biomolecule is governed by an underlying energy landscape, there has been great interest to understand and quantify ribosome energetics. In the present review, we will focus on theoretical and computational strategies for probing the interactions that shape the energy landscape of the ribosome, with an emphasis on more recent studies of the elongation cycle. These efforts include the application of quantum mechanical methods for describing chemical kinetics, as well as classical descriptions to characterize slower (microsecond to millisecond) large-scale (10-100 Å) rearrangements, where motion is described in terms of diffusion across an energy landscape. Together, these studies provide broad insights into the factors that control a diverse range of dynamical processes in this assembly.
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Affiliation(s)
- Sandra Byju
- Center for Theoretical Biological Physics, Northeastern University, Boston, Massachusetts, USA
- Department of Physics, Northeastern University, Boston, Massachusetts, USA
| | - Asem Hassan
- Department of Chemistry, The University of Texas at Austin, Austin, Texas, United States
| | - Paul C Whitford
- Center for Theoretical Biological Physics, Northeastern University, Boston, Massachusetts, USA
- Department of Physics, Northeastern University, Boston, Massachusetts, USA
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8
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Antolínez S, Jones PE, Phillips JC, Hadden-Perilla JA. AMBERff at Scale: Multimillion-Atom Simulations with AMBER Force Fields in NAMD. J Chem Inf Model 2024; 64:543-554. [PMID: 38176097 PMCID: PMC10806814 DOI: 10.1021/acs.jcim.3c01648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/18/2023] [Accepted: 12/18/2023] [Indexed: 01/06/2024]
Abstract
All-atom molecular dynamics (MD) simulations are an essential structural biology technique with increasing application to multimillion-atom systems, including viruses and cellular machinery. Classical MD simulations rely on parameter sets, such as the AMBER family of force fields (AMBERff), to accurately describe molecular motion. Here, we present an implementation of AMBERff for use in NAMD that overcomes previous limitations to enable high-performance, massively parallel simulations encompassing up to two billion atoms. Single-point potential energy comparisons and case studies on model systems demonstrate that the implementation produces results that are as accurate as running AMBERff in its native engine.
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Affiliation(s)
- Santiago Antolínez
- Department
of Chemistry and Biochemistry, University
of Delaware, Newark, Delaware 19716, United States
| | - Peter Eugene Jones
- Department
of Chemistry and Biochemistry, University
of Delaware, Newark, Delaware 19716, United States
| | - James C. Phillips
- National
Center for Supercomputing Applications, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States
| | - Jodi A. Hadden-Perilla
- Department
of Chemistry and Biochemistry, University
of Delaware, Newark, Delaware 19716, United States
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9
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Junier I, Ghobadpour E, Espeli O, Everaers R. DNA supercoiling in bacteria: state of play and challenges from a viewpoint of physics based modeling. Front Microbiol 2023; 14:1192831. [PMID: 37965550 PMCID: PMC10642903 DOI: 10.3389/fmicb.2023.1192831] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 09/25/2023] [Indexed: 11/16/2023] Open
Abstract
DNA supercoiling is central to many fundamental processes of living organisms. Its average level along the chromosome and over time reflects the dynamic equilibrium of opposite activities of topoisomerases, which are required to relax mechanical stresses that are inevitably produced during DNA replication and gene transcription. Supercoiling affects all scales of the spatio-temporal organization of bacterial DNA, from the base pair to the large scale chromosome conformation. Highlighted in vitro and in vivo in the 1960s and 1970s, respectively, the first physical models were proposed concomitantly in order to predict the deformation properties of the double helix. About fifteen years later, polymer physics models demonstrated on larger scales the plectonemic nature and the tree-like organization of supercoiled DNA. Since then, many works have tried to establish a better understanding of the multiple structuring and physiological properties of bacterial DNA in thermodynamic equilibrium and far from equilibrium. The purpose of this essay is to address upcoming challenges by thoroughly exploring the relevance, predictive capacity, and limitations of current physical models, with a specific focus on structural properties beyond the scale of the double helix. We discuss more particularly the problem of DNA conformations, the interplay between DNA supercoiling with gene transcription and DNA replication, its role on nucleoid formation and, finally, the problem of scaling up models. Our primary objective is to foster increased collaboration between physicists and biologists. To achieve this, we have reduced the respective jargon to a minimum and we provide some explanatory background material for the two communities.
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Affiliation(s)
- Ivan Junier
- CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, Université Grenoble Alpes, Grenoble, France
| | - Elham Ghobadpour
- CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, Université Grenoble Alpes, Grenoble, France
- École Normale Supérieure (ENS) de Lyon, CNRS, Laboratoire de Physique and Centre Blaise Pascal de l'ENS de Lyon, Lyon, France
| | - Olivier Espeli
- Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, Université PSL, Paris, France
| | - Ralf Everaers
- École Normale Supérieure (ENS) de Lyon, CNRS, Laboratoire de Physique and Centre Blaise Pascal de l'ENS de Lyon, Lyon, France
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10
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Chowdhury P, Jha A, Bhandary D. Influence of Temperature-Guided SAM Growth on Wetting and Its Mass Transfer Models. J Phys Chem B 2023; 127:8208-8215. [PMID: 37703434 DOI: 10.1021/acs.jpcb.3c04173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
The formation and growth of self-assembled monolayers (SAMs) composed of amphiphiles have garnered significant attention due to their diverse technical applications. This article reports the findings of molecular dynamics simulations aimed at elucidating the intricate relationship between the wetting behavior of amphiphiles, specifically n-alkanols, and the growth of their SAMs on a mica surface under varying temperature conditions. The investigation quantifies the structural characteristics of the formed SAMs, including density profiles, in-plane radial distribution functions, order parameters, and end-to-end length distributions of n-alkanol molecules within the SAM. Thermodynamic properties, such as the second virial coefficient and excess entropy, are examined in relation to temperature and time. The growth of the SAM is assessed by analyzing characteristic time scales at different temperatures and in-plane diffusion of n-alkanol molecules and utilizing classical theories of mass transfer to quantify the growth rate as a function of temperature. These results are then correlated with changes in the contact angle and spreading coefficient of n-alkanol droplets on the mica surface over time, providing insights into the impact of SAM growth on the wetting behavior and the mass transfer model of such systems.
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Affiliation(s)
- Prateek Chowdhury
- Department of Chemical Engineering and Technology, Indian Institute of Technology (BHU) Varanasi, Varanasi, UP 221005, India
| | - Ayush Jha
- Department of Chemical Engineering and Technology, Indian Institute of Technology (BHU) Varanasi, Varanasi, UP 221005, India
| | - Debdip Bhandary
- Department of Chemical Engineering and Technology, Indian Institute of Technology (BHU) Varanasi, Varanasi, UP 221005, India
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Klein F, Soñora M, Helene Santos L, Nazareno Frigini E, Ballesteros-Casallas A, Rodrigo Machado M, Pantano S. The SIRAH force field: A suite for simulations of complex biological systems at the coarse-grained and multiscale levels. J Struct Biol 2023; 215:107985. [PMID: 37331570 DOI: 10.1016/j.jsb.2023.107985] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/18/2023] [Accepted: 06/13/2023] [Indexed: 06/20/2023]
Abstract
The different combinations of molecular dynamics simulations with coarse-grained representations have acquired considerable popularity among the scientific community. Especially in biocomputing, the significant speedup granted by simplified molecular models opened the possibility of increasing the diversity and complexity of macromolecular systems, providing realistic insights on large assemblies for more extended time windows. However, a holistic view of biological ensembles' structural and dynamic features requires a self-consistent force field, namely, a set of equations and parameters that describe the intra and intermolecular interactions among moieties of diverse chemical nature (i.e., nucleic and amino acids, lipids, solvent, ions, etc.). Nevertheless, examples of such force fields are scarce in the literature at the fully atomistic and coarse-grained levels. Moreover, the number of force fields capable of handling simultaneously different scales is restricted to a handful. Among those, the SIRAH force field, developed in our group, furnishes a set of topologies and tools that facilitate the setting up and running of molecular dynamics simulations at the coarse-grained and multiscale levels. SIRAH uses the same classical pairwise Hamiltonian function implemented in the most popular molecular dynamics software. In particular, it runs natively in AMBER and Gromacs engines, and porting it to other simulation packages is straightforward. This review describes the underlying philosophy behind the development of SIRAH over the years and across families of biological molecules, discussing current limitations and future implementations.
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Affiliation(s)
- Florencia Klein
- Laboratoire de Biochimie Théorique, UPR9080, CNRS, Paris, France
| | - Martín Soñora
- Institut Pasteur de Montevideo, Mataojo 2020, 11400, Montevideo, Uruguay
| | | | - Ezequiel Nazareno Frigini
- Instituto Multidisciplinario de Investigaciones Biológicas de San Luis (IMIBIO-SL), Universidad Nacional de San Luis - CONICET, San Luis, Argentina
| | - Andrés Ballesteros-Casallas
- Institut Pasteur de Montevideo, Mataojo 2020, 11400, Montevideo, Uruguay; Area Bioinformática, DETEMA, Facultad de Química, Universidad de la República, General Flores 2124, Montevideo, 11600, Uruguay
| | | | - Sergio Pantano
- Institut Pasteur de Montevideo, Mataojo 2020, 11400, Montevideo, Uruguay; Area Bioinformática, DETEMA, Facultad de Química, Universidad de la República, General Flores 2124, Montevideo, 11600, Uruguay.
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12
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Pavlin M, Herlah B, Valjavec K, Perdih A. Unveiling the interdomain dynamics of type II DNA topoisomerase through all-atom simulations: Implications for understanding its catalytic cycle. Comput Struct Biotechnol J 2023; 21:3746-3759. [PMID: 37602233 PMCID: PMC10436251 DOI: 10.1016/j.csbj.2023.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 07/01/2023] [Accepted: 07/19/2023] [Indexed: 08/22/2023] Open
Abstract
Type IIA DNA topoisomerases are complex molecular nanomachines that manage topological states of the DNA molecule in the cell and play a crucial role in cellular processes such as cell division and transcription. They are also established targets of cancer chemotherapy. Starting from the available crystal structure of a fully catalytic topoisomerase IIA homodimer from Saccharomyces cerevisiae, we constructed three states of this molecular motor primarily changing the configurations of the DNA segment bound in the DNA gate and performed μs-long all-atom molecular simulations. A comprehensive analysis revealed a sliding motion within the DNA gate and a teamwork between the N-gate and DNA gate that may be associated with the necessary molecular events that allow passage of the T-segment of DNA. The observed movement of the ATPase dimer relative to the DNA domain was reflected in different interaction patterns between the K-loops of the transducer domain and the B-A-B form of the bound DNA. Based on the obtained results, we mapped simulated configurations to the structures in the proposed catalytic cycle through which type IIA topoisomerases exert their function and discussed the possible transition events. The results extend our understanding of the mechanism of action of type IIA topoisomerases and provide an atomistic interpretation of some of the observed features of these molecular motors.
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Affiliation(s)
- Matic Pavlin
- Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
| | - Barbara Herlah
- Theory Department, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva 7, 1000 Ljubljana, Slovenia
| | - Katja Valjavec
- Theory Department, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
| | - Andrej Perdih
- Theory Department, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva 7, 1000 Ljubljana, Slovenia
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13
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Yu J. On the common pathways of deformation: RNA vs DNA under interrogation. Proc Natl Acad Sci U S A 2023; 120:e2306453120. [PMID: 37224189 PMCID: PMC10266000 DOI: 10.1073/pnas.2306453120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2023] Open
Affiliation(s)
- Jin Yu
- Department of Physics and Astronomy, University of California Irvine, Irvine, CA92697
- Department of Chemistry, University of California Irvine, Irvine, CA92697
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14
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Chowdhury P, Bhandary D. Evolution, Stability, and Applicability of Surfactant Aggregates in Targeted Delivery. J Phys Chem B 2023; 127:3001-3009. [PMID: 36971543 DOI: 10.1021/acs.jpcb.2c08625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
Self-assembly/self-aggregation of surfactant molecules in bulk and the vicinity of a surface has been a topic of interest for decades because of its utilization in numerous modern technical applications. In this article, the results of molecular dynamics simulations are reported to investigate the self-aggregation of sodium dodecyl sulfate (SDS) at an interface of mica and water. SDS molecules starting from lower to higher surface concentrations tend to create distinct aggregated structures in the vicinity of a mica surface. The structural properties, such as density profiles, radial distribution functions, and thermodynamic properties like excess entropy and second virial coefficient, are calculated to address the bits and pieces of the self-aggregation. The change in the free energy for aggregates of varied sizes approaching the surface from the bulk aqueous solution, along with the change in their shapes during the process in terms of change in the radius of gyration and its components, is reported respectively to model a generic pathway for a surfactant-based targeted delivery system.
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15
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Sinha S, Pindi C, Ahsan M, Arantes PR, Palermo G. Machines on Genes through the Computational Microscope. J Chem Theory Comput 2023; 19:1945-1964. [PMID: 36947696 PMCID: PMC10104023 DOI: 10.1021/acs.jctc.2c01313] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
Macromolecular machines acting on genes are at the core of life's fundamental processes, including DNA replication and repair, gene transcription and regulation, chromatin packaging, RNA splicing, and genome editing. Here, we report the increasing role of computational biophysics in characterizing the mechanisms of "machines on genes", focusing on innovative applications of computational methods and their integration with structural and biophysical experiments. We showcase how state-of-the-art computational methods, including classical and ab initio molecular dynamics to enhanced sampling techniques, and coarse-grained approaches are used for understanding and exploring gene machines for real-world applications. As this review unfolds, advanced computational methods describe the biophysical function that is unseen through experimental techniques, accomplishing the power of the "computational microscope", an expression coined by Klaus Schulten to highlight the extraordinary capability of computer simulations. Pushing the frontiers of computational biophysics toward a pragmatic representation of large multimegadalton biomolecular complexes is instrumental in bridging the gap between experimentally obtained macroscopic observables and the molecular principles playing at the microscopic level. This understanding will help harness molecular machines for medical, pharmaceutical, and biotechnological purposes.
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16
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Curti M, Maffeis V, Teixeira Alves Duarte LG, Shareef S, Hallado LX, Curutchet C, Romero E. Engineering excitonically coupled dimers in an artificial protein for light harvesting via computational modeling. Protein Sci 2023; 32:e4579. [PMID: 36715022 PMCID: PMC9951196 DOI: 10.1002/pro.4579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/23/2023] [Accepted: 01/25/2023] [Indexed: 01/31/2023]
Abstract
In photosynthesis, pigment-protein complexes achieve outstanding photoinduced charge separation efficiencies through a set of strategies in which excited states delocalization over multiple pigments ("excitons") and charge-transfer states play key roles. These concepts, and their implementation in bioinspired artificial systems, are attracting increasing attention due to the vast potential that could be tapped by realizing efficient photochemical reactions. In particular, de novo designed proteins provide a diverse structural toolbox that can be used to manipulate the geometric and electronic properties of bound chromophore molecules. However, achieving excitonic and charge-transfer states requires closely spaced chromophores, a non-trivial aspect since a strong binding with the protein matrix needs to be maintained. Here, we show how a general-purpose artificial protein can be optimized via molecular dynamics simulations to improve its binding capacity of a chlorophyll derivative, achieving complexes in which chromophores form two closely spaced and strongly interacting dimers. Based on spectroscopy results and computational modeling, we demonstrate each dimer is excitonically coupled, and propose they display signatures of charge-transfer state mixing. This work could open new avenues for the rational design of chromophore-protein complexes with advanced functionalities.
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Affiliation(s)
- Mariano Curti
- Institute of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science and Technology (BIST)TarragonaSpain
| | - Valentin Maffeis
- Institute of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science and Technology (BIST)TarragonaSpain
- Laboratoire de Chimie, UMR 5182, ENS Lyon, CNRSUniversité Lyon 1LyonFrance
| | | | - Saeed Shareef
- Institute of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science and Technology (BIST)TarragonaSpain
- Departament de Química Física i InorgànicaUniversitat Rovira i VirgiliTarragonaSpain
| | - Luisa Xiomara Hallado
- Institute of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science and Technology (BIST)TarragonaSpain
- Departament de Química Física i InorgànicaUniversitat Rovira i VirgiliTarragonaSpain
| | - Carles Curutchet
- Departament de Farmàcia i Tecnologia Farmacèutica i Fisicoquímica, Facultat de Farmàcia i Ciències de l'AlimentacióUniversitat de Barcelona (UB)BarcelonaSpain
- Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona (UB)BarcelonaSpain
| | - Elisabet Romero
- Institute of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science and Technology (BIST)TarragonaSpain
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17
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Duncan AL, Pezeshkian W. Mesoscale simulations: An indispensable approach to understand biomembranes. Biophys J 2023:S0006-3495(23)00123-6. [PMID: 36809878 DOI: 10.1016/j.bpj.2023.02.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/10/2022] [Accepted: 02/13/2023] [Indexed: 02/23/2023] Open
Abstract
Computer simulation techniques form a versatile tool, a computational microscope, for exploring biological processes. This tool has been particularly effective in exploring different features of biological membranes. In recent years, thanks to elegant multiscale simulation schemes, some fundamental limitations of investigations by distinct simulation techniques have been resolved. As a result, we are now capable of exploring processes spanning multiple scales beyond the capacity of any single technique. In this perspective, we argue that mesoscale simulations require more attention and must be further developed to fill evident gaps in a quest toward simulating and modeling living cell membranes.
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Affiliation(s)
- Anna L Duncan
- Department of Chemistry, Aarhus University, Aarhus C, Denmark.
| | - Weria Pezeshkian
- Niels Bohr International Academy, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
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18
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Stevens JA, Grünewald F, van Tilburg PAM, König M, Gilbert BR, Brier TA, Thornburg ZR, Luthey-Schulten Z, Marrink SJ. Molecular dynamics simulation of an entire cell. Front Chem 2023; 11:1106495. [PMID: 36742032 PMCID: PMC9889929 DOI: 10.3389/fchem.2023.1106495] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 01/09/2023] [Indexed: 01/19/2023] Open
Abstract
The ultimate microscope, directed at a cell, would reveal the dynamics of all the cell's components with atomic resolution. In contrast to their real-world counterparts, computational microscopes are currently on the brink of meeting this challenge. In this perspective, we show how an integrative approach can be employed to model an entire cell, the minimal cell, JCVI-syn3A, at full complexity. This step opens the way to interrogate the cell's spatio-temporal evolution with molecular dynamics simulations, an approach that can be extended to other cell types in the near future.
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Affiliation(s)
- Jan A. Stevens
- Molecular Dynamics Group, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands
| | - Fabian Grünewald
- Molecular Dynamics Group, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands
| | - P. A. Marco van Tilburg
- Molecular Dynamics Group, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands
| | - Melanie König
- Molecular Dynamics Group, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands
| | - Benjamin R. Gilbert
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Champaign, IL, United States
| | - Troy A. Brier
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Champaign, IL, United States
| | - Zane R. Thornburg
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Champaign, IL, United States
| | - Zaida Luthey-Schulten
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Champaign, IL, United States
| | - Siewert J. Marrink
- Molecular Dynamics Group, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands,*Correspondence: Siewert J. Marrink,
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19
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Iwasa JH, Lyons B, Johnson GT. The dawn of interoperating spatial models in cell biology. Curr Opin Biotechnol 2022; 78:102838. [PMID: 36402095 DOI: 10.1016/j.copbio.2022.102838] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 06/01/2022] [Accepted: 10/07/2022] [Indexed: 11/18/2022]
Abstract
Spatial simulations are becoming an increasingly ubiquitous component in the cycle of discovery, experimentation, and communication across the sciences. In cell biology, many researchers share a vision of developing multiscale models that recapitulate observable behaviors spanning from atoms to cells to tissues. For this dream to become a reality, however, simulation technologies must provide a means for integration and interoperability as they advance. Already, the field has developed numerous methods that span scales of length, time, and complexity to create an extensive body of effective simulation approaches, and although these approaches rarely interoperate, they collectively cover a large spectrum of knowledge that future models may handle in a more unified manner. Here, we discuss the importance of making the data, workflows, and outputs of spatial simulations shareable and interoperable; and how democratization could encourage diverse biologists to participate more easily in developing models to advance our understanding of biological systems.
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Affiliation(s)
| | - Blair Lyons
- Visualization & Data Integration, Allen Institute for Cell Science, USA
| | - Graham T Johnson
- Visualization & Data Integration, Allen Institute for Cell Science, USA.
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20
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Pantano S. Back and forth modeling through biological scales. Biochem Biophys Res Commun 2022; 633:39-41. [DOI: 10.1016/j.bbrc.2022.09.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 09/09/2022] [Indexed: 11/06/2022]
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21
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22
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Artsimovitch I, Ramírez-Sarmiento CA. Metamorphic proteins under a computational microscope: Lessons from a fold-switching RfaH protein. Comput Struct Biotechnol J 2022; 20:5824-5837. [PMID: 36382197 PMCID: PMC9630627 DOI: 10.1016/j.csbj.2022.10.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 10/18/2022] [Accepted: 10/18/2022] [Indexed: 11/28/2022] Open
Abstract
Metamorphic proteins constitute unexpected paradigms of the protein folding problem, as their sequences encode two alternative folds, which reversibly interconvert within biologically relevant timescales to trigger different cellular responses. Once considered a rare aberration, metamorphism may be common among proteins that must respond to rapidly changing environments, exemplified by NusG-like proteins, the only transcription factors present in every domain of life. RfaH, a specialized paralog of bacterial NusG, undergoes an all-α to all-β domain switch to activate expression of virulence and conjugation genes in many animal and plant pathogens and is the quintessential example of a metamorphic protein. The dramatic nature of RfaH structural transformation and the richness of its evolutionary history makes for an excellent model for studying how metamorphic proteins switch folds. Here, we summarize the structural and functional evidence that sparked the discovery of RfaH as a metamorphic protein, the experimental and computational approaches that enabled the description of the molecular mechanism and refolding pathways of its structural interconversion, and the ongoing efforts to find signatures and general properties to ultimately describe the protein metamorphome.
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Affiliation(s)
- Irina Artsimovitch
- Department of Microbiology and The Center for RNA Biology, The Ohio State University, Columbus, OH, USA
| | - César A. Ramírez-Sarmiento
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile
- ANID, Millennium Science Initiative Program, Millennium Institute for Integrative Biology (iBio), Santiago, Chile
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23
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Gomes PSFC, Gomes DEB, Bernardi RC. Protein structure prediction in the era of AI: Challenges and limitations when applying to in silico force spectroscopy. FRONTIERS IN BIOINFORMATICS 2022; 2:983306. [PMID: 36304287 PMCID: PMC9580946 DOI: 10.3389/fbinf.2022.983306] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 09/21/2022] [Indexed: 11/06/2022] Open
Abstract
Mechanoactive proteins are essential for a myriad of physiological and pathological processes. Guided by the advances in single-molecule force spectroscopy (SMFS), we have reached a molecular-level understanding of how mechanoactive proteins sense and respond to mechanical forces. However, even SMFS has its limitations, including the lack of detailed structural information during force-loading experiments. That is where molecular dynamics (MD) methods shine, bringing atomistic details with femtosecond time-resolution. However, MD heavily relies on the availability of high-resolution structural data, which is not available for most proteins. For instance, the Protein Data Bank currently has 192K structures deposited, against 231M protein sequences available on Uniprot. But many are betting that this gap might become much smaller soon. Over the past year, the AI-based AlphaFold created a buzz on the structural biology field by being able to predict near-native protein folds from their sequences. For some, AlphaFold is causing the merge of structural biology with bioinformatics. Here, using an in silico SMFS approach pioneered by our group, we investigate how reliable AlphaFold structure predictions are to investigate mechanical properties of Staphylococcus bacteria adhesins proteins. Our results show that AlphaFold produce extremally reliable protein folds, but in many cases is unable to predict high-resolution protein complexes accurately. Nonetheless, the results show that AlphaFold can revolutionize the investigation of these proteins, particularly by allowing high-throughput scanning of protein structures. Meanwhile, we show that the AlphaFold results need to be validated and should not be employed blindly, with the risk of obtaining an erroneous protein mechanism.
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24
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Veríssimo GC, Serafim MSM, Kronenberger T, Ferreira RS, Honorio KM, Maltarollo VG. Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern. Expert Opin Drug Discov 2022; 17:929-947. [PMID: 35983695 DOI: 10.1080/17460441.2022.2114451] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Modern drug discovery generally is accessed by useful information from previous large databases or uncovering novel data. The lack of biological and/or chemical data tends to slow the development of scientific research and innovation. Here, approaches that may help provide solutions to generate or obtain enough relevant data or improve/accelerate existing methods within the last five years were reviewed. AREAS COVERED One-shot learning (OSL) approaches, structural modeling, molecular docking, scoring function space (SFS), molecular dynamics (MD), and quantum mechanics (QM) may be used to amplify the amount of available data to drug design and discovery campaigns, presenting methods, their perspectives, and discussions to be employed in the near future. EXPERT OPINION Recent works have successfully used these techniques to solve a range of issues in the face of data scarcity, including complex problems such as the challenging scenario of drug design aimed at intrinsically disordered proteins and the evaluation of potential adverse effects in a clinical scenario. These examples show that it is possible to improve and kickstart research from scarce available data to design and discover new potential drugs.
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Affiliation(s)
- Gabriel C Veríssimo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Mateus Sá M Serafim
- Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Thales Kronenberger
- Department of Medical Oncology and Pneumology, Internal Medicine VIII, University Hospital of Tübingen, Tübingen, Germany.,School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Rafaela S Ferreira
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Kathia M Honorio
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo (USP), São Paulo, Brazil.,Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, Brazil
| | - Vinícius G Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
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25
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Barhaghi MS, Crawford B, Schwing G, Hardy DJ, Stone JE, Schwiebert L, Potoff J, Tajkhorshid E. py-MCMD: Python Software for Performing Hybrid Monte Carlo/Molecular Dynamics Simulations with GOMC and NAMD. J Chem Theory Comput 2022; 18:4983-4994. [PMID: 35621307 PMCID: PMC9760104 DOI: 10.1021/acs.jctc.1c00911] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
py-MCMD, an open-source Python software, provides a robust workflow layer that manages communication of relevant system information between the simulation engines NAMD and GOMC and generates coherent thermodynamic properties and trajectories for analysis. To validate the workflow and highlight its capabilities, hybrid Monte Carlo/molecular dynamics (MC/MD) simulations are performed for SPC/E water in the isobaric-isothermal (NPT) and grand canonical (GC) ensembles as well as with Gibbs ensemble Monte Carlo (GEMC). The hybrid MC/MD approach shows close agreement with reference MC simulations and has a computational efficiency that is 2 to 136 times greater than traditional Monte Carlo simulations. MC/MD simulations performed for water in a graphene slit pore illustrate significant gains in sampling efficiency when the coupled-decoupled configurational-bias MC (CD-CBMC) algorithm is used compared with simulations using a single unbiased random trial position. Simulations using CD-CBMC reach equilibrium with 25 times fewer cycles than simulations using a single unbiased random trial position, with a small increase in computational cost. In a more challenging application, hybrid grand canonical Monte Carlo/molecular dynamics (GCMC/MD) simulations are used to hydrate a buried binding pocket in bovine pancreatic trypsin inhibitor. Water occupancies produced by GCMC/MD simulations are in close agreement with crystallographically identified positions, and GCMC/MD simulations have a computational efficiency that is 5 times better than MD simulations. py-MCMD is available on GitHub at https://github.com/GOMC-WSU/py-MCMD.
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Affiliation(s)
- Mohammad Soroush Barhaghi
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Brad Crawford
- Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, Michigan 48202, United States
| | - Gregory Schwing
- Department of Computer Science, Wayne State University, Detroit, Michigan 48202, United States
| | - David J Hardy
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - John E Stone
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Loren Schwiebert
- Department of Computer Science, Wayne State University, Detroit, Michigan 48202, United States
| | - Jeffrey Potoff
- Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, Michigan 48202, United States
| | - Emad Tajkhorshid
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
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26
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Zhu S. Computational characterization of homologous ligands binding to a deep hydrophobic pocket in
Shigella flexneri
pilot protein MxiM. Proteins 2022; 90:2116-2123. [DOI: 10.1002/prot.26402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 07/10/2022] [Accepted: 07/19/2022] [Indexed: 11/07/2022]
Affiliation(s)
- Shun Zhu
- Department of Cellular and Genetic Medicine, School of Basic Medical Sciences Fudan University Shanghai People's Republic of China
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27
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Ma Y, Hua T, Trinh TA, Wang R, Chew JW. Molecular dynamics simulation of the competitive adsorption behavior of effluent organic matters by heated aluminum oxide particles (HAOPs). Sep Purif Technol 2022. [DOI: 10.1016/j.seppur.2022.120961] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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28
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Sumikama T, Federici Canova F, Gao DZ, Penedo M, Miyazawa K, Foster AS, Fukuma T. Computed Three-Dimensional Atomic Force Microscopy Images of Biopolymers Using the Jarzynski Equality. J Phys Chem Lett 2022; 13:5365-5371. [PMID: 35678499 PMCID: PMC9208010 DOI: 10.1021/acs.jpclett.2c01093] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/18/2022] [Indexed: 06/15/2023]
Abstract
Three-dimensional atomic force microscopy (3D-AFM) has resolved three-dimensional distributions of solvent molecules at solid-liquid interfaces at the subnanometer scale. This method is now being extended to the imaging of biopolymer assemblies such as chromosomes or proteins in cells, with the expectation of being able to resolve their three-dimensional structures. Here, we have developed a computational method to simulate 3D-AFM images of biopolymers by using the Jarzynski equality. It is found that some parts of the fiber structure of biopolymers are indeed resolved in the 3D-AFM image. The dependency of 3D-AFM images on the vertical scanning velocity is investigated, and optimum scanning velocities are found. It is also clarified that forces in nonequilibrium processes are measured in 3D-AFM measurements when the dynamics of polymers are slower than the scanning of the probe.
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Affiliation(s)
- Takashi Sumikama
- PRESTO,
JST, Kawaguchi, Saitama 332-0012, Japan
- Nano
Life Science Institute (WPI-NanoLSI), Kanazawa
University, Kanazawa 920-1192, Japan
| | - Filippo Federici Canova
- Nanolayers
Research Computing Ltd., 1 Granville Court, Granville Road, London N12 0HL, United Kingdom
- Department
of Applied Physics, Aalto University, Aalto 00076, Finland
| | - David Z. Gao
- Nanolayers
Research Computing Ltd., 1 Granville Court, Granville Road, London N12 0HL, United Kingdom
- Department
of Physics, Norwegian University of Science
and Technology (NTNU), 7491 Trondheim, Norway
| | - Marcos Penedo
- Nano
Life Science Institute (WPI-NanoLSI), Kanazawa
University, Kanazawa 920-1192, Japan
- Laboratory
for Bio and Nanoinstrumentation, Institute for Bioengineering, École Polytechnique Fédérale
de Lausanne, Lausanne CH-1015, Switzerland
| | - Keisuke Miyazawa
- Nano
Life Science Institute (WPI-NanoLSI), Kanazawa
University, Kanazawa 920-1192, Japan
- Division
of Electrical Engineering and Computer Science, Kanazawa University, Kanazawa 920-1192, Japan
- Faculty of
Frontier Engineering, Kanazawa University, Kanazawa 920-1192, Japan
| | - Adam S. Foster
- Nano
Life Science Institute (WPI-NanoLSI), Kanazawa
University, Kanazawa 920-1192, Japan
- Department
of Applied Physics, Aalto University, Aalto 00076, Finland
| | - Takeshi Fukuma
- Nano
Life Science Institute (WPI-NanoLSI), Kanazawa
University, Kanazawa 920-1192, Japan
- Division
of Electrical Engineering and Computer Science, Kanazawa University, Kanazawa 920-1192, Japan
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29
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Schöller A, Kearns F, Woodcock HL, Boresch S. Optimizing the Calculation of Free Energy Differences in Nonequilibrium Work SQM/MM Switching Simulations. J Phys Chem B 2022; 126:2798-2811. [PMID: 35404610 PMCID: PMC9036525 DOI: 10.1021/acs.jpcb.2c00696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/24/2022] [Indexed: 11/27/2022]
Abstract
A key step during indirect alchemical free energy simulations using quantum mechanical/molecular mechanical (QM/MM) hybrid potential energy functions is the calculation of the free energy difference ΔAlow→high between the low level (e.g., pure MM) and the high level of theory (QM/MM). A reliable approach uses nonequilibrium work (NEW) switching simulations in combination with Jarzynski's equation; however, it is computationally expensive. In this study, we investigate whether it is more efficient to use more shorter switches or fewer but longer switches. We compare results obtained with various protocols to reference free energy differences calculated with Crooks' equation. The central finding is that fewer longer switches give better converged results. As few as 200 sufficiently long switches lead to ΔAlow→high values in good agreement with the reference results. This optimized protocol reduces the computational cost by a factor of 40 compared to earlier work. We also describe two tools/ways of analyzing the raw data to detect sources of poor convergence. Specifically, we find it helpful to analyze the raw data (work values from the NEW switching simulations) in a quasi-time series-like manner. Principal component analysis helps to detect cases where one or more conformational degrees of freedom are different at the low and high level of theory.
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Affiliation(s)
- Andreas Schöller
- Faculty
of Chemistry, Department of Computational Biological Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Vienna, Austria
- Vienna
Doctoral School in Chemistry (DoSChem), University of Vienna, Währingerstrasse 42, A-1090 Vienna, Austria
| | - Fiona Kearns
- Department
of Chemistry, University of South Florida, 4202 E. Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
| | - H. Lee Woodcock
- Department
of Chemistry, University of South Florida, 4202 E. Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
| | - Stefan Boresch
- Faculty
of Chemistry, Department of Computational Biological Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Vienna, Austria
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30
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31
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Li Z, Zhu X, Li J, Zhong J, Zhang J, Fan J. Molecular insights into the resistance of phospholipid heads to the membrane penetration of graphene nanosheets. NANOSCALE 2022; 14:5384-5391. [PMID: 35319035 DOI: 10.1039/d1nr07684a] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
The interaction between nanomaterials and phospholipid membranes underlies many emerging biological applications. To what extent hydrophilic phospholipid heads shield the bilayer from the integration of hydrophobic nanomaterials remains unclear, and this open question contains important insights for understanding biological membrane physics. Here, we present molecular dynamics (MD) simulations to clarify the resistance of phospholipid heads to the membrane penetration of graphene nanosheets. With 130 simulation trials, we observed that ∼22% graphene nanosheets penetrate the POPC bilayer. Sharp corners of the nanosheets should have a lower energy barrier than nanosheet edges, but interestingly, the membrane penetration mainly starts from the edge-approaching orientation. We thoroughly analyzed the pentration pathway and propulsion, indicating that the membrane penetration of graphene nanosheets is dominated by the joint effects of nanosheet edges and corners. Furthermore, the molecular origin of the resistance is clarified by evaluating the bilayers of different phospholipids, which successfully correlates the penetration resistance of phospholipid heads with the correlated motions of neighboring phospholipids for the first time. These results are expected to inspire future studies on the dynamic behavior of phospholipids, bio-nano interfaces, and design of biological nanomaterials.
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Affiliation(s)
- Zhen Li
- School of Materials Science and Engineering, China University of Petroleum (East China), Qingdao 266580, China.
| | - Xiaohong Zhu
- Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong, China.
| | - Jiawei Li
- School of Materials Science and Engineering, China University of Petroleum (East China), Qingdao 266580, China.
- Key Laboratory of Marine Environmental Corrosion and Bio-Fouling, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Jie Zhong
- Department of Earth and Environmental Science and Department of Chemistry, University of Pennsylvania, Philadelphia, PA, 19104-6316, USA
| | - Jun Zhang
- School of Materials Science and Engineering, China University of Petroleum (East China), Qingdao 266580, China.
| | - Jun Fan
- Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong, China.
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Ferenczy GG, Kellermayer M. Contribution of Hydrophobic Interactions to Protein Mechanical Stability. Comput Struct Biotechnol J 2022; 20:1946-1956. [PMID: 35521554 PMCID: PMC9062142 DOI: 10.1016/j.csbj.2022.04.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Revised: 04/07/2022] [Accepted: 04/17/2022] [Indexed: 11/26/2022] Open
Abstract
The role of hydrophobic and polar interactions in providing thermodynamic stability to folded proteins has been intensively studied, but the relative contribution of these interactions to the mechanical stability is less explored. We used steered molecular dynamics simulations with constant-velocity pulling to generate force-extension curves of selected protein domains and monitor hydrophobic surface unravelling upon extension. Hydrophobic contribution was found to vary between one fifth and one third of the total force while the rest of the contribution is attributed primarily to hydrogen bonds. Moreover, hydrophobic force peaks were shifted towards larger protein extensions with respect to the force peaks attributed to hydrogen bonds. The higher importance of hydrogen bonds compared to hydrophobic interactions in providing mechanical resistance is in contrast with the relative importance of the hydrophobic interactions in providing thermodynamic stability of proteins. The different contributions of these interactions to the mechanical stability are explained by the steeper free energy dependence of hydrogen bonds compared to hydrophobic interactions on the relative positions of interacting atoms. Comparative analyses for several protein domains revealed that the variation of hydrophobic forces is modest, while the contribution of hydrogen bonds to the force peaks becomes increasingly important for mechanically resistant protein domains.
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Zimmermann MT. Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research. Compr Physiol 2022; 12:3141-3166. [PMID: 35578963 DOI: 10.1002/cphy.c190047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.
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Affiliation(s)
- Michael T Zimmermann
- Bioinformatics Research and Development Laboratory, Genomic Sciences and Precision Medicine Center, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.,Clinical and Translational Sciences Institute, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.,Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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34
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Neel BL, Nisler CR, Walujkar S, Araya-Secchi R, Sotomayor M. Elastic versus brittle mechanical responses predicted for dimeric cadherin complexes. Biophys J 2022; 121:1013-1028. [PMID: 35151631 PMCID: PMC8943749 DOI: 10.1016/j.bpj.2022.02.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 01/02/2022] [Accepted: 02/07/2022] [Indexed: 12/15/2022] Open
Abstract
Cadherins are a superfamily of adhesion proteins involved in a variety of biological processes that include the formation of intercellular contacts, the maintenance of tissue integrity, and the development of neuronal circuits. These transmembrane proteins are characterized by ectodomains composed of a variable number of extracellular cadherin (EC) repeats that are similar but not identical in sequence and fold. E-cadherin, along with desmoglein and desmocollin proteins, are three classical-type cadherins that have slightly curved ectodomains and engage in homophilic and heterophilic interactions through an exchange of conserved tryptophan residues in their N-terminal EC1 repeat. In contrast, clustered protocadherins are straighter than classical cadherins and interact through an antiparallel homophilic binding interface that involves overlapped EC1 to EC4 repeats. Here we present molecular dynamics simulations that model the adhesive domains of these cadherins using available crystal structures, with systems encompassing up to 2.8 million atoms. Simulations of complete classical cadherin ectodomain dimers predict a two-phased elastic response to force in which these complexes first softly unbend and then stiffen to unbind without unfolding. Simulated α, β, and γ clustered protocadherin homodimers lack a two-phased elastic response, are brittle and stiffer than classical cadherins and exhibit complex unbinding pathways that in some cases involve transient intermediates. We propose that these distinct mechanical responses are important for function, with classical cadherin ectodomains acting as molecular shock absorbers and with stiffer clustered protocadherin ectodomains facilitating overlap that favors binding specificity over mechanical resilience. Overall, our simulations provide insights into the molecular mechanics of single cadherin dimers relevant in the formation of cellular junctions essential for tissue function.
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Affiliation(s)
- Brandon L Neel
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio; The Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio
| | - Collin R Nisler
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio; Biophysics Graduate Program, The Ohio State University, Columbus, Ohio
| | - Sanket Walujkar
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio; Chemical Physics Graduate Program, The Ohio State University, Columbus, Ohio
| | - Raul Araya-Secchi
- Facultad de Ingeniería y Tecnología, Universidad San Sebastián, Santiago, Chile
| | - Marcos Sotomayor
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio; The Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio; Biophysics Graduate Program, The Ohio State University, Columbus, Ohio; Chemical Physics Graduate Program, The Ohio State University, Columbus, Ohio.
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Neel BL, Nisler CR, Walujkar S, Araya-Secchi R, Sotomayor M. Collective mechanical responses of cadherin-based adhesive junctions as predicted by simulations. Biophys J 2022; 121:991-1012. [PMID: 35150618 PMCID: PMC8943820 DOI: 10.1016/j.bpj.2022.02.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 01/02/2022] [Accepted: 02/07/2022] [Indexed: 12/13/2022] Open
Abstract
Cadherin-based adherens junctions and desmosomes help stabilize cell-cell contacts with additional function in mechano-signaling, while clustered protocadherin junctions are responsible for directing neuronal circuits assembly. Structural models for adherens junctions formed by epithelial cadherin (CDH1) proteins indicate that their long, curved ectodomains arrange to form a periodic, two-dimensional lattice stabilized by tip-to-tip trans interactions (across junction) and lateral cis contacts. Less is known about the exact architecture of desmosomes, but desmoglein (DSG) and desmocollin (DSC) cadherin proteins are also thought to form ordered junctions. In contrast, clustered protocadherin (PCDH)-based cell-cell contacts in neuronal tissues are thought to be responsible for self-recognition and avoidance, and structural models for clustered PCDH junctions show a linear arrangement in which their long and straight ectodomains form antiparallel overlapped trans complexes. Here, we report all-atom molecular dynamics simulations testing the mechanics of minimalistic adhesive junctions formed by CDH1, DSG2 coupled to DSC1, and PCDHγB4, with systems encompassing up to 3.7 million atoms. Simulations generally predict a favored shearing pathway for the adherens junction model and a two-phased elastic response to tensile forces for the adhesive adherens junction and the desmosome models. Complexes within these junctions first unbend at low tensile force and then become stiff to unbind without unfolding. However, cis interactions in both the CDH1 and DSG2-DSC1 systems dictate varied mechanical responses of individual dimers within the junctions. Conversely, the clustered protocadherin PCDHγB4 junction lacks a distinct two-phased elastic response. Instead, applied tensile force strains trans interactions directly, as there is little unbending of monomers within the junction. Transient intermediates, influenced by new cis interactions, are observed after the main rupture event. We suggest that these collective, complex mechanical responses mediated by cis contacts facilitate distinct functions in robust cell-cell adhesion for classical cadherins and in self-avoidance signaling for clustered PCDHs.
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Affiliation(s)
- Brandon L Neel
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio; The Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio
| | - Collin R Nisler
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio; Biophysics Graduate Program, The Ohio State University, Columbus, Ohio
| | - Sanket Walujkar
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio; Chemical Physics Graduate Program, The Ohio State University, Columbus, Ohio
| | - Raul Araya-Secchi
- Facultad de Ingenieria y Tecnologia, Universidad San Sebastian, Santiago, Chile
| | - Marcos Sotomayor
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio; The Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio; Biophysics Graduate Program, The Ohio State University, Columbus, Ohio; Chemical Physics Graduate Program, The Ohio State University, Columbus, Ohio.
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36
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Karaca E, Prévost C, Sacquin-Mora S. Modeling the Dynamics of Protein–Protein Interfaces, How and Why? Molecules 2022; 27:molecules27061841. [PMID: 35335203 PMCID: PMC8950966 DOI: 10.3390/molecules27061841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 03/06/2022] [Accepted: 03/08/2022] [Indexed: 12/07/2022] Open
Abstract
Protein–protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein–protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein–protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein–protein interface.
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Affiliation(s)
- Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir 35340, Turkey;
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir 35340, Turkey
| | - Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
- Correspondence:
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37
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Bourassin N, Barbault F, Baaden M, Sacquin-Mora S. Between Two Walls: Modeling the Adsorption Behavior of β-Glucosidase A on Bare and SAM-Functionalized Gold Surfaces. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2022; 38:1313-1323. [PMID: 35050631 DOI: 10.1021/acs.langmuir.1c01774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The efficient immobilization of enzymes on surfaces remains a complex but central issue in the biomaterials field, which requires us to understand this process at the atomic level. Using a multiscale approach combining all-atom molecular dynamics and coarse-grain Brownian dynamics simulations, we investigated the adsorption behavior of β-glucosidase A (βGA) on bare and self-assembled monolayer (SAM)-functionalized gold surfaces. We monitored the enzyme position and orientation during the molecular dynamics (MD) trajectories and measured the contacts it forms with both surfaces. While the adsorption process has little impact on the protein conformation, it can nonetheless perturb its mechanical properties and catalytic activity. Our results show that compared to the SAM-functionalized surface, the adsorption of βGA on bare gold is more stable, but less specific, and more likely to disrupt the enzyme's function. This observation emphasizes the fact that the structural organization of proteins at the solid interface is a key point when designing devices based on enzyme immobilization, as one must find an acceptable stability-activity trade-off.
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Affiliation(s)
- Nicolas Bourassin
- Laboratoire de Biochimie Théorique, UPR 9080, Université de Paris, CNRS, 13 rue Pierre et Marie Curie, 75005 Paris, France
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, 75005 Paris, France
| | | | - Marc Baaden
- Laboratoire de Biochimie Théorique, UPR 9080, Université de Paris, CNRS, 13 rue Pierre et Marie Curie, 75005 Paris, France
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, 75005 Paris, France
| | - Sophie Sacquin-Mora
- Laboratoire de Biochimie Théorique, UPR 9080, Université de Paris, CNRS, 13 rue Pierre et Marie Curie, 75005 Paris, France
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, 75005 Paris, France
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38
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Tavakol M, Vaughan TJ. Energy dissipation of osteopontin at a HAp mineral interface: Implications for bone biomechanics. Biophys J 2022; 121:228-236. [PMID: 34932955 PMCID: PMC8790188 DOI: 10.1016/j.bpj.2021.12.023] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 11/04/2021] [Accepted: 12/16/2021] [Indexed: 01/21/2023] Open
Abstract
Osteopontin (OPN) is a one of the most abundant non-collagenous proteins in the bone's organic matrix. OPN is responsible for mediating bonding at mineral interfaces in the extrafibrillar space and recent evidence shows that it is a major contributor to bone's fracture resistance. While several experimental studies have identified an important role for calcium ions in mediating energy dissipation in OPN protein networks, the underlying molecular mechanisms remain largely unknown. In the current study, the role of calcium ions on energy dissipation at OPN interface with hydroxyapatite (HAp) as the main bone mineral was investigated. For the first time, the three-dimensional structure of OPN proteins were predicted, and it was found that calcium ions greatly influenced the final protein configuration and energy dissipation performance. Under small deformation, the compact cOPN structure, resulting from calcium ions presence, facilitated greater energy dissipation through sacrificial bond breaking and mechanisms mediated by the surface-bound calcium. At larger deformation, the compact structure also enabled cOPN to dissipate higher energy. Moreover, it was found that phosphorylation of OPN played an important role in energy dissipation. While previous studies have shown that OPN dissipated energy by forming aggregate networks, this study also showed that network formation is not necessary and that individual OPN proteins can dissipate large amounts of energy at HAp interfaces.
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Affiliation(s)
- Mahdi Tavakol
- Biomedical Engineering and Biomechanics Research Centre (BioMEC), School of Engineering, College of Science and Engineering, National University of Ireland Galway, Galway, Ireland
| | - Ted J. Vaughan
- Biomedical Engineering and Biomechanics Research Centre (BioMEC), School of Engineering, College of Science and Engineering, National University of Ireland Galway, Galway, Ireland,Corresponding author
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39
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Sharing data, sharing methods, sharing science. MethodsX 2022; 9:101607. [PMID: 35024349 PMCID: PMC8728097 DOI: 10.1016/j.mex.2021.101607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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40
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Tolmachev D, Lukasheva N, Ramazanov R, Nazarychev V, Borzdun N, Volgin I, Andreeva M, Glova A, Melnikova S, Dobrovskiy A, Silber SA, Larin S, de Souza RM, Ribeiro MCC, Lyulin S, Karttunen M. Computer Simulations of Deep Eutectic Solvents: Challenges, Solutions, and Perspectives. Int J Mol Sci 2022; 23:645. [PMID: 35054840 PMCID: PMC8775846 DOI: 10.3390/ijms23020645] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 01/02/2022] [Accepted: 01/04/2022] [Indexed: 12/13/2022] Open
Abstract
Deep eutectic solvents (DESs) are one of the most rapidly evolving types of solvents, appearing in a broad range of applications, such as nanotechnology, electrochemistry, biomass transformation, pharmaceuticals, membrane technology, biocomposite development, modern 3D-printing, and many others. The range of their applicability continues to expand, which demands the development of new DESs with improved properties. To do so requires an understanding of the fundamental relationship between the structure and properties of DESs. Computer simulation and machine learning techniques provide a fruitful approach as they can predict and reveal physical mechanisms and readily be linked to experiments. This review is devoted to the computational research of DESs and describes technical features of DES simulations and the corresponding perspectives on various DES applications. The aim is to demonstrate the current frontiers of computational research of DESs and discuss future perspectives.
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Affiliation(s)
- Dmitry Tolmachev
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Natalia Lukasheva
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Ruslan Ramazanov
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Victor Nazarychev
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Natalia Borzdun
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Igor Volgin
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Maria Andreeva
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Artyom Glova
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Sofia Melnikova
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Alexey Dobrovskiy
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Steven A. Silber
- Department of Physics and Astronomy, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada;
- The Centre of Advanced Materials and Biomaterials Research, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
| | - Sergey Larin
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Rafael Maglia de Souza
- Departamento de Química Fundamental, Instituto de Química, Universidade de São Paulo, Avenida Professor Lineu Prestes 748, São Paulo 05508-070, Brazil; (R.M.d.S.); (M.C.C.R.)
| | - Mauro Carlos Costa Ribeiro
- Departamento de Química Fundamental, Instituto de Química, Universidade de São Paulo, Avenida Professor Lineu Prestes 748, São Paulo 05508-070, Brazil; (R.M.d.S.); (M.C.C.R.)
| | - Sergey Lyulin
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
| | - Mikko Karttunen
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia; (N.L.); (R.R.); (V.N.); (N.B.); (I.V.); (M.A.); (A.G.); (S.M.); (A.D.); (S.L.); (S.L.)
- Department of Physics and Astronomy, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada;
- The Centre of Advanced Materials and Biomaterials Research, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- Department of Chemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
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A stepwise docking molecular dynamics approach for simulating antibody recognition with substantial conformational changes. Comput Struct Biotechnol J 2022; 20:710-720. [PMID: 35198128 PMCID: PMC8816672 DOI: 10.1016/j.csbj.2022.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 12/24/2021] [Accepted: 01/13/2022] [Indexed: 11/23/2022] Open
Abstract
Conformational changes or rearrangements are common events during inter-biomolecular recognition. Tracking these changes are essential for exploring the allosteric mechanism and it is usually achieved by molecular dynamics simulation in silico. We previously identified a broad-neutralizing antibody against H5 influenza virus, 13D4, and solved the crystal structures of the free 13D4 Fab and its complex with hemagglutinin (HA). Structural comparison of the unbound and bound 13D4 Fabs showed that the heavy chain complementarity-determining region 3 (HCDR3) undergoes a substantial conformational rearrangement when it recognizes the receptor-binding site (RBS). Here, we used molecular dynamics (MD) to simulate the conformational changes that occur during antibody recognition. We showed that neither conventional MD nor steered MD could recapitulate the loop fitting of the RBS structure contour. Consequently, to simulate these challenging conformational changes, we engaged a stepwise docking MD method that allowed for the gradual docking of the ligand to receptor. This new method recapitulates the bound shape of the HCDR3 and provides the best approximation of the shape rendered by the co-crystal structure, with an RMSD of 0.926 Å. This strategy affords a flexible MD approach for simulating complicated conformational changes that occur during molecular recognition, and helps to provide an understanding of the involved allosteric mechanism.
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42
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Kapakayala AB, Nair NN. Boosting the conformational sampling by combining replica exchange with solute tempering and well-sliced metadynamics. J Comput Chem 2021; 42:2233-2240. [PMID: 34585768 DOI: 10.1002/jcc.26752] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 08/30/2021] [Accepted: 09/12/2021] [Indexed: 01/22/2023]
Abstract
Methods that combine collective variable (CV) based enhanced sampling and global tempering approaches are used in speeding-up the conformational sampling and free energy calculation of large and soft systems with a plethora of energy minima. In this paper, a new method of this kind is proposed in which the well-sliced metadynamics approach (WSMTD) is united with replica exchange with solute tempering (REST2) method. WSMTD employs a divide-and-conquer strategy wherein high-dimensional slices of a free energy surface are independently sampled and combined. The method enables one to accomplish a controlled exploration of the CV-space with a restraining bias as in umbrella sampling, and enhance-sampling of one or more orthogonal CVs using a metadynamics like bias. The new hybrid method proposed here enables boosting the sampling of more slow degrees of freedom in WSMTD simulations, without the need to specify associated CVs, through a replica exchange scheme within the framework of REST2. The high-dimensional slices of the probability distributions of CVs computed from the united WSMTD and REST2 simulations are subsequently combined using the weighted histogram analysis method to obtain the free energy surface. We show that the new method proposed here is accurate, improves the conformational sampling, and achieves quick convergence in free energy estimates. We demonstrate this by computing the conformational free energy landscapes of solvated alanine tripeptide and Trp-cage mini protein in explicit water.
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Affiliation(s)
- Anji Babu Kapakayala
- Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur, India.,School of Pharmacy and Biomedical Sciences, Curtin University, Perth, Australia
| | - Nisanth N Nair
- Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur, India
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43
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Nin-Hill A, Mueller NPF, Molteni C, Rovira C, Alfonso-Prieto M. Photopharmacology of Ion Channels through the Light of the Computational Microscope. Int J Mol Sci 2021; 22:12072. [PMID: 34769504 PMCID: PMC8584574 DOI: 10.3390/ijms222112072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 10/31/2021] [Accepted: 11/02/2021] [Indexed: 12/13/2022] Open
Abstract
The optical control and investigation of neuronal activity can be achieved and carried out with photoswitchable ligands. Such compounds are designed in a modular fashion, combining a known ligand of the target protein and a photochromic group, as well as an additional electrophilic group for tethered ligands. Such a design strategy can be optimized by including structural data. In addition to experimental structures, computational methods (such as homology modeling, molecular docking, molecular dynamics and enhanced sampling techniques) can provide structural insights to guide photoswitch design and to understand the observed light-regulated effects. This review discusses the application of such structure-based computational methods to photoswitchable ligands targeting voltage- and ligand-gated ion channels. Structural mapping may help identify residues near the ligand binding pocket amenable for mutagenesis and covalent attachment. Modeling of the target protein in a complex with the photoswitchable ligand can shed light on the different activities of the two photoswitch isomers and the effect of site-directed mutations on photoswitch binding, as well as ion channel subtype selectivity. The examples presented here show how the integration of computational modeling with experimental data can greatly facilitate photoswitchable ligand design and optimization. Recent advances in structural biology, both experimental and computational, are expected to further strengthen this rational photopharmacology approach.
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Affiliation(s)
- Alba Nin-Hill
- Departament de Química Inorgànica i Orgànica (Secció de Química Orgànica) and Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, 08028 Barcelona, Spain; (A.N.-H.); (C.R.)
| | - Nicolas Pierre Friedrich Mueller
- Institute for Advanced Simulations IAS-5 and Institute of Neuroscience and Medicine INM-9, Computational Biomedicine, Forschungszentrum Jülich, 52425 Jülich, Germany;
- Faculty of Mathematics and Natural Sciences, Heinrich-Heine-University Düsseldorf, Universitätsstr. 1, 40225 Düsseldorf, Germany
| | - Carla Molteni
- Physics Department, King’s College London, London WC2R 2LS, UK;
| | - Carme Rovira
- Departament de Química Inorgànica i Orgànica (Secció de Química Orgànica) and Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, 08028 Barcelona, Spain; (A.N.-H.); (C.R.)
- Institució Catalana de Recerca i Estudis Avançats (ICREA), 08020 Barcelona, Spain
| | - Mercedes Alfonso-Prieto
- Institute for Advanced Simulations IAS-5 and Institute of Neuroscience and Medicine INM-9, Computational Biomedicine, Forschungszentrum Jülich, 52425 Jülich, Germany;
- Cécile and Oskar Vogt Institute for Brain Research, University Hospital Düsseldorf, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
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44
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Bauer J, Žoldák G. Interpretation of Single-Molecule Force Experiments on Proteins Using Normal Mode Analysis. NANOMATERIALS 2021; 11:nano11112795. [PMID: 34835560 PMCID: PMC8624234 DOI: 10.3390/nano11112795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 10/20/2021] [Accepted: 10/20/2021] [Indexed: 11/25/2022]
Abstract
Single-molecule force spectroscopy experiments allow protein folding and unfolding to be explored using mechanical force. Probably the most informative technique for interpreting the results of these experiments at the structural level makes use of steered molecular dynamics (MD) simulations, which can explicitly model the protein under load. Unfortunately, this technique is computationally expensive for many of the most interesting biological molecules. Here, we find that normal mode analysis (NMA), a significantly cheaper technique from a computational perspective, allows at least some of the insights provided by MD simulation to be gathered. We apply this technique to three non-homologous proteins that were previously studied by force spectroscopy: T4 lysozyme (T4L), Hsp70 and the glucocorticoid receptor domain (GCR). The NMA results for T4L and Hsp70 are compared with steered MD simulations conducted previously, and we find that we can recover the main results. For the GCR, which did not undergo MD simulation, our approach identifies substructures that correlate with experimentally identified unfolding intermediates. Overall, we find that NMA can make a valuable addition to the analysis toolkit for the structural analysis of single-molecule force experiments on proteins.
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Affiliation(s)
- Jacob Bauer
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava, Slovakia
- Correspondence: (J.B.); (G.Ž.); Tel.: +421-55-234-2242 (G.Ž.)
| | - Gabriel Žoldák
- Center for Interdisciplinary Biosciences, P. J. Šafárik University, Technology and Innovation Park, Trieda SNP 1, 041 54 Košice, Slovakia
- Correspondence: (J.B.); (G.Ž.); Tel.: +421-55-234-2242 (G.Ž.)
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45
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Plant Sterol Clustering Correlates with Membrane Microdomains as Revealed by Optical and Computational Microscopy. MEMBRANES 2021; 11:membranes11100747. [PMID: 34677513 PMCID: PMC8539253 DOI: 10.3390/membranes11100747] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/22/2021] [Accepted: 09/27/2021] [Indexed: 11/26/2022]
Abstract
Local inhomogeneities in lipid composition play a crucial role in the regulation of signal transduction and membrane traffic. This is particularly the case for plant plasma membrane, which is enriched in specific lipids, such as free and conjugated forms of phytosterols and typical phytosphingolipids. Nevertheless, most evidence for microdomains in cells remains indirect, and the nature of membrane inhomogeneities has been difficult to characterize. We used a new push–pull pyrene probe and fluorescence lifetime imaging microscopy (FLIM) combined with all-atom multiscale molecular dynamics simulations to provide a detailed view on the interaction between phospholipids and phytosterol and the effect of modulating cellular phytosterols on membrane-associated microdomains and phase separation formation. Our understanding of the organization principles of biomembranes is limited mainly by the challenge to measure distributions and interactions of lipids and proteins within the complex environment of living cells. Comparing phospholipids/phytosterol compositions typical of liquid-disordered (Ld) and liquid-ordered (Lo) domains, we furthermore show that phytosterols play crucial roles in membrane homeostasis. The simulation work highlights how state-of-the-art modeling alleviates some of the prior concerns and how unrefuted discoveries can be made through a computational microscope. Altogether, our results support the role of phytosterols in the lateral structuring of the PM of plant cells and suggest that they are key compounds for the formation of plant PM microdomains and the lipid-ordered phase.
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46
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Casalino L, Dommer AC, Gaieb Z, Barros EP, Sztain T, Ahn SH, Trifan A, Brace A, Bogetti AT, Clyde A, Ma H, Lee H, Turilli M, Khalid S, Chong LT, Simmerling C, Hardy DJ, Maia JD, Phillips JC, Kurth T, Stern AC, Huang L, McCalpin JD, Tatineni M, Gibbs T, Stone JE, Jha S, Ramanathan A, Amaro RE. AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. THE INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2021; 35:432-451. [PMID: 38603008 PMCID: PMC8064023 DOI: 10.1177/10943420211006452] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike's full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.
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Affiliation(s)
- Lorenzo Casalino
- University of California San Diego, La Jolla, CA, USA
- Authors with symbol indicate equal contribution
| | - Abigail C Dommer
- University of California San Diego, La Jolla, CA, USA
- Authors with symbol indicate equal contribution
| | - Zied Gaieb
- University of California San Diego, La Jolla, CA, USA
- Authors with symbol indicate equal contribution
| | | | - Terra Sztain
- University of California San Diego, La Jolla, CA, USA
| | - Surl-Hee Ahn
- University of California San Diego, La Jolla, CA, USA
| | - Anda Trifan
- Argonne National Lab, Lemont, IL, USA
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | - Austin Clyde
- Argonne National Lab, Lemont, IL, USA
- University of Chicago, Chicago, IL, USA
| | - Heng Ma
- Argonne National Lab, Lemont, IL, USA
| | | | | | | | | | | | - David J Hardy
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Julio Dc Maia
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | | | - Lei Huang
- Texas Advanced Computing Center, Austin, TX, USA
| | | | | | - Tom Gibbs
- NVIDIA Corporation, Santa Clara, CA, USA
| | - John E Stone
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Shantenu Jha
- Rutgers University, Piscataway, NJ, USA
- Brookhaven National Lab, Upton, NY, USA
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47
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Zozoulenko I, Franco-Gonzalez JF, Gueskine V, Mehandzhiyski A, Modarresi M, Rolland N, Tybrandt K. Electronic, Optical, Morphological, Transport, and Electrochemical Properties of PEDOT: A Theoretical Perspective. Macromolecules 2021. [DOI: 10.1021/acs.macromol.1c00444] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Igor Zozoulenko
- Laboratory of Organic Electronics, ITN, Linköping University, 60174 Norrköping, Sweden
| | | | - Viktor Gueskine
- Laboratory of Organic Electronics, ITN, Linköping University, 60174 Norrköping, Sweden
| | | | - Mohsen Modarresi
- Department of Physics, Ferdowsi University of Mashhad, Mashhad, PO Box 91775-1436, Iran
| | - Nicolas Rolland
- Laboratory of Organic Electronics, ITN, Linköping University, 60174 Norrköping, Sweden
| | - Klas Tybrandt
- Laboratory of Organic Electronics, ITN, Linköping University, 60174 Norrköping, Sweden
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48
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Giulini M, Rigoli M, Mattiotti G, Menichetti R, Tarenzi T, Fiorentini R, Potestio R. From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules. Front Mol Biosci 2021; 8:676976. [PMID: 34164432 PMCID: PMC8215203 DOI: 10.3389/fmolb.2021.676976] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 05/06/2021] [Indexed: 12/18/2022] Open
Abstract
The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.
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Affiliation(s)
- Marco Giulini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Marta Rigoli
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Giovanni Mattiotti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Roberto Menichetti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Thomas Tarenzi
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaele Fiorentini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaello Potestio
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
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49
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Doerr S, Majewski M, Pérez A, Krämer A, Clementi C, Noe F, Giorgino T, De Fabritiis G. TorchMD: A Deep Learning Framework for Molecular Simulations. J Chem Theory Comput 2021; 17:2355-2363. [PMID: 33729795 PMCID: PMC8486166 DOI: 10.1021/acs.jctc.0c01343] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Indexed: 11/28/2022]
Abstract
Molecular dynamics simulations provide a mechanistic description of molecules by relying on empirical potentials. The quality and transferability of such potentials can be improved leveraging data-driven models derived with machine learning approaches. Here, we present TorchMD, a framework for molecular simulations with mixed classical and machine learning potentials. All force computations including bond, angle, dihedral, Lennard-Jones, and Coulomb interactions are expressed as PyTorch arrays and operations. Moreover, TorchMD enables learning and simulating neural network potentials. We validate it using standard Amber all-atom simulations, learning an ab initio potential, performing an end-to-end training, and finally learning and simulating a coarse-grained model for protein folding. We believe that TorchMD provides a useful tool set to support molecular simulations of machine learning potentials. Code and data are freely available at github.com/torchmd.
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Affiliation(s)
| | - Maciej Majewski
- Computational
Science Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Adrià Pérez
- Computational
Science Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Andreas Krämer
- Department
of Mathematics and Computer Science, Freie
Universität, 14195 Berlin, Germany
| | - Cecilia Clementi
- Department
of Physics, Freie Universität, 14195 Berlin, Germany
- Department
of Chemistry, Rice University, Houston, 77005 Texas, United States
| | - Frank Noe
- Department
of Mathematics and Computer Science, Freie
Universität, 14195 Berlin, Germany
- Department
of Physics, Freie Universität, 14195 Berlin, Germany
- Department
of Chemistry, Rice University, Houston, 77005 Texas, United States
| | - Toni Giorgino
- Biophysics
Institute, National Research Council (CNR-IBF), 20133 Milano, Italy
- Department
of Biosciences, Università degli
Studi di Milano, 20133 Milano, Italy
| | - Gianni De Fabritiis
- Acellera, 08005 Barcelona, Spain
- Computational
Science Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain
- Institució
Catalana de Recerca i Estudis Avançats, 08010 Barcelona, Spain
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50
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Jana AK, May ER. Atomistic dynamics of a viral infection process: Release of membrane lytic peptides from a non-enveloped virus. SCIENCE ADVANCES 2021; 7:7/16/eabe1761. [PMID: 33853772 PMCID: PMC8046363 DOI: 10.1126/sciadv.abe1761] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 02/23/2021] [Indexed: 05/13/2023]
Abstract
Molecular simulations have played an instrumental role in uncovering the structural dynamics and physical properties of virus capsids. In this work, we move beyond equilibrium physicochemical characterization of a virus system to study a stage of the infection process that is required for viral proliferation. Despite many biochemical and functional studies, the molecular mechanism of host cell entry by non-enveloped viruses remains largely unresolved. Flock House virus (FHV) is a model system for non-enveloped viruses and is the subject of the current study. FHV infects through the acid-dependent endocytic pathway, where low pH triggers externalization of membrane-disrupting (γ) peptides from the capsid interior. Using all-atom equilibrium and enhanced sampling simulations, the mechanism and energetics of γ peptide liberation and the effect of pH on this process are investigated. Our computations agree with experimental findings and reveal nanoscopic details regarding the pH control mechanism, which are not readily accessible in experiments.
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Affiliation(s)
- Asis K Jana
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269, USA
| | - Eric R May
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269, USA.
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