1
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Nkepsu Mbitou RL, Goujon F, Dequidt A, Latour B, Devémy J, Martzel N, Hauret P, Malfreyt P. Autohesion Mechanisms at Interfaces Between Random Copolymer Melts: Mesoscopic Simulations with Realistic Coarse-Grained Models. Chemphyschem 2024; 25:e202400114. [PMID: 38669321 DOI: 10.1002/cphc.202400114] [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: 02/02/2024] [Revised: 04/07/2024] [Accepted: 04/21/2024] [Indexed: 04/28/2024]
Abstract
The increase in welding time during the interdiffusion of a pair of non reacting random copolymer melts favors the strength rate of healing at the interface. Furthermore, the diffusion kinetic during the interpenetration of copolymer chains across the interface is strongly dependent on molecular weight. In this paper we perform mesoscopic simulations with realistic coarse grain models to study the autohesion mechanism across the interface between slightly entangled styrene-butadiene random copolymer melts.
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Affiliation(s)
- R L Nkepsu Mbitou
- Université Clermont Auvergne, CNRS, Institut de Chimie de Clermont-Ferrand, Clermont-Ferrand, F, 63000, France
- Manufacture Française des Pneumatiques Michelin, 23, Place des Carmes, 63040, Clermont-Ferrand, France
| | - F Goujon
- Université Clermont Auvergne, CNRS, Institut de Chimie de Clermont-Ferrand, Clermont-Ferrand, F, 63000, France
| | - A Dequidt
- Université Clermont Auvergne, CNRS, Institut de Chimie de Clermont-Ferrand, Clermont-Ferrand, F, 63000, France
| | - B Latour
- Manufacture Française des Pneumatiques Michelin, 23, Place des Carmes, 63040, Clermont-Ferrand, France
| | - J Devémy
- Université Clermont Auvergne, CNRS, Institut de Chimie de Clermont-Ferrand, Clermont-Ferrand, F, 63000, France
| | - N Martzel
- Manufacture Française des Pneumatiques Michelin, 23, Place des Carmes, 63040, Clermont-Ferrand, France
| | - P Hauret
- Manufacture Française des Pneumatiques Michelin, 23, Place des Carmes, 63040, Clermont-Ferrand, France
| | - P Malfreyt
- Université Clermont Auvergne, CNRS, Institut de Chimie de Clermont-Ferrand, Clermont-Ferrand, F, 63000, France
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2
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Nemchinova M, Schuurman-Wolters GK, Whittaker JJ, Arkhipova V, Marrink SJ, Poolman B, Guskov A. Exploring the Ligand Binding and Conformational Dynamics of the Substrate-Binding Domain 1 of the ABC Transporter GlnPQ. J Phys Chem B 2024; 128:7822-7832. [PMID: 39090964 PMCID: PMC11331510 DOI: 10.1021/acs.jpcb.4c02662] [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: 04/23/2024] [Revised: 07/21/2024] [Accepted: 07/25/2024] [Indexed: 08/04/2024]
Abstract
The adenosine triphosphate (ATP)-binding cassette (ABC) importer GlnPQ from Lactococcus lactis has two sequential covalently linked substrate-binding domains (SBDs), which capture the substrates and deliver them to the translocon. The two SBDs differ in their ligand specificities, binding affinities and the distance to the transmembrane domain; interestingly, both SBDs can bind their ligands simultaneously without affecting each other. In this work, we studied the binding of ligands to both SBDs using X-ray crystallography and molecular dynamics simulations. We report three high-resolution structures of SBD1, namely, the wild-type SBD1 with bound asparagine or arginine, and E184D SBD1 with glutamine bound. Molecular dynamics (MD) simulations provide a detailed insight into the dynamics associated with open-closed transitions of the SBDs.
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Affiliation(s)
- Mariia Nemchinova
- Groningen
Institute for Biomolecular Sciences and Biotechnology, University of Groningen, 9747AG Groningen, The Netherlands
| | - Gea K. Schuurman-Wolters
- Groningen
Institute for Biomolecular Sciences and Biotechnology, University of Groningen, 9747AG Groningen, The Netherlands
| | - Jacob J. Whittaker
- Groningen
Institute for Biomolecular Sciences and Biotechnology, University of Groningen, 9747AG Groningen, The Netherlands
| | - Valentina Arkhipova
- Groningen
Institute for Biomolecular Sciences and Biotechnology, University of Groningen, 9747AG Groningen, The Netherlands
| | - Siewert J. Marrink
- Groningen
Institute for Biomolecular Sciences and Biotechnology, University of Groningen, 9747AG Groningen, The Netherlands
| | - Bert Poolman
- Groningen
Institute for Biomolecular Sciences and Biotechnology, University of Groningen, 9747AG Groningen, The Netherlands
| | - Albert Guskov
- Groningen
Institute for Biomolecular Sciences and Biotechnology, University of Groningen, 9747AG Groningen, The Netherlands
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3
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Thomasen FE, Skaalum T, Kumar A, Srinivasan S, Vanni S, Lindorff-Larsen K. Rescaling protein-protein interactions improves Martini 3 for flexible proteins in solution. Nat Commun 2024; 15:6645. [PMID: 39103332 DOI: 10.1038/s41467-024-50647-9] [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: 05/29/2023] [Accepted: 07/15/2024] [Indexed: 08/07/2024] Open
Abstract
Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is difficult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the 'symmetry' between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.
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Affiliation(s)
- F Emil Thomasen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark.
| | - Tórur Skaalum
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark
| | - Ashutosh Kumar
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Swiss National Center for Competence in Research (NCCR) Bio-inspired Materials, University of Fribourg, Chemin des Verdiers 4, CH-1700, Fribourg, Switzerland
| | | | - Stefano Vanni
- Department of Biology, University of Fribourg, Fribourg, Switzerland.
- Swiss National Center for Competence in Research (NCCR) Bio-inspired Materials, University of Fribourg, Chemin des Verdiers 4, CH-1700, Fribourg, Switzerland.
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark.
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4
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Sheng M, Ma L, Li Z, Peng X, Cen S, Feng M, Tian Y, Dai X, Shi X. A hybrid evaluation of the intestinal absorption performance of compounds from molecular structure. Chem Biol Drug Des 2024; 104:e14576. [PMID: 38969623 DOI: 10.1111/cbdd.14576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/30/2023] [Accepted: 06/26/2024] [Indexed: 07/07/2024]
Abstract
Intestinal absorption of compounds is significant in drug research and development. To evaluate this efficiently, a method combining mathematical modeling and molecular simulation was proposed, from the perspective of molecular structure. Based on the quantitative structure-property relationship study, the model between molecular structure and their apparent permeability coefficients was successfully constructed and verified, predicting intestinal absorption of drugs and interpreting decisive structural factors, such as AlogP98, Hydrogen bond donor and Ellipsoidal volume. The molecules with strong lipophilicity, less hydrogen bond donors and receptors, and small molecular volume are more easily absorbed. Then, the molecular dynamics simulation and molecular docking were utilized to study the mechanism of differences in intestinal absorption of drugs and investigate the role of molecular structure. Results indicated that molecules with strong lipophilicity and small volume interacted with the membrane at a lower energy and were easier to penetrate the membrane. Likewise, they had weaker interaction with P-glycoprotein and were easier to escape from it and harder to export from the body. More in, less out, is the main reason these molecules absorb well.
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Affiliation(s)
- Mengke Sheng
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Lina Ma
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Zhixun Li
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xinhui Peng
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Shuai Cen
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Minfang Feng
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Yuting Tian
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xingxing Dai
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xinyuan Shi
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
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5
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Borges-Araújo L, Pereira GP, Valério M, Souza PCT. Assessing the Martini 3 protein model: A review of its path and potential. BIOCHIMICA ET BIOPHYSICA ACTA. PROTEINS AND PROTEOMICS 2024; 1872:141014. [PMID: 38670324 DOI: 10.1016/j.bbapap.2024.141014] [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: 01/05/2024] [Revised: 03/13/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024]
Abstract
Coarse-grained (CG) protein models have become indispensable tools for studying many biological protein details, from conformational dynamics to the organization of protein macro-complexes, and even the interaction of proteins with other molecules. The Martini force field is one of the most widely used CG models for bio-molecular simulations, partly because of the enormous success of its protein model. With the recent release of a new and improved version of the Martini force field - Martini 3 - a new iteration of its protein model was also made available. The Martini 3 protein force field is an evolution of its Martini 2 counterpart, aimed at improving many of the shortcomings that had been previously identified. In this mini-review, we first provide a general overview of the model and then focus on the successful advances made in the short time since its release, many of which would not have been possible before. Furthermore, we discuss reported limitations, potential directions for model improvement and comment on what the likely future development and application avenues are.
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Affiliation(s)
- Luís Borges-Araújo
- Laboratoire de Biologie et Modélisation de la Cellule, CNRS, UMR 5239, Inserm, U1293, Université Claude Bernard Lyon 1, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon, France; Centre Blaise Pascal de Simulation et de Modélisation Numérique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon, France
| | - Gilberto P Pereira
- Laboratoire de Biologie et Modélisation de la Cellule, CNRS, UMR 5239, Inserm, U1293, Université Claude Bernard Lyon 1, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon, France; Centre Blaise Pascal de Simulation et de Modélisation Numérique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon, France
| | - Mariana Valério
- Laboratoire de Biologie et Modélisation de la Cellule, CNRS, UMR 5239, Inserm, U1293, Université Claude Bernard Lyon 1, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon, France; Centre Blaise Pascal de Simulation et de Modélisation Numérique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon, France
| | - Paulo C T Souza
- Laboratoire de Biologie et Modélisation de la Cellule, CNRS, UMR 5239, Inserm, U1293, Université Claude Bernard Lyon 1, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon, France; Centre Blaise Pascal de Simulation et de Modélisation Numérique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon, France.
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6
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Jeitler R, Glader C, König G, Kaplan J, Tetyczka C, Remmelgas J, Mußbacher M, Fröhlich E, Roblegg E. On the Structure, Stability, and Cell Uptake of Nanostructured Lipid Carriers for Drug Delivery. Mol Pharm 2024; 21:3674-3683. [PMID: 38838194 PMCID: PMC11220792 DOI: 10.1021/acs.molpharmaceut.4c00392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 06/07/2024]
Abstract
The efficacy of nanostructured lipid carriers (NLC) for drug delivery strongly depends on their stability and cell uptake. Both properties are governed by their compositions and internal structure. To test the effect of the lipid composition of NLC on cell uptake and stability, three kinds of liquid lipids with different degrees of unsaturation are employed. After ensuring homogeneous size distributions, the thermodynamic characteristics, stability, and mixing properties of NLC are characterized. Then the rates and predominant pathways of cell uptake are determined. Although the same surfactant is used in all cases, different uptake rates are observed. This finding contradicts the view that the surface properties of NLC are dominated by the surfactant. Instead, the uptake rates are explained by the structure of the nanocarrier. Depending on the mixing properties, some liquid lipids remain inside the nanocarrier, while other liquid lipids are present on the surface. Nanocarriers with liquid lipids on the surface are taken up more readily by the cells. This shows that the engineering of efficient lipid nanocarriers requires a delicate balance of interactions between all components of the nanocarrier on the molecular level.
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Affiliation(s)
- Ramona Jeitler
- Institute
of Pharmaceutical Sciences, Pharmaceutical Technology and Biopharmacy, University of Graz, 8010 Graz, Austria
- Research
Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
| | - Christina Glader
- Institute
of Pharmaceutical Sciences, Pharmaceutical Technology and Biopharmacy, University of Graz, 8010 Graz, Austria
- Research
Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
| | - Gerhard König
- Research
Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
- Centre
for Enzyme Innovation, School of Biological Sciences, University of Portsmouth, Portsmouth PO1 2DY, United
Kingdom
| | - Jay Kaplan
- Research
Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
- Pritzker
School of Molecular Engineering, University
of Chicago, Chicago, Illinois 60637, United States
| | - Carolin Tetyczka
- Research
Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
| | - Johan Remmelgas
- Research
Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
| | - Marion Mußbacher
- Institute
of Pharmaceutical Sciences, Pharmacology and Toxicology, University of Graz, 8010 Graz, Austria
| | - Eleonore Fröhlich
- Center
for
Medical Research, Medical University of Graz, 8010 Graz, Austria
| | - Eva Roblegg
- Institute
of Pharmaceutical Sciences, Pharmaceutical Technology and Biopharmacy, University of Graz, 8010 Graz, Austria
- Research
Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
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7
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Ivanov M, Lyubartsev AP. Development of a bottom-up coarse-grained model for interactions of lipids with TiO 2 nanoparticles. J Comput Chem 2024; 45:1364-1379. [PMID: 38380763 DOI: 10.1002/jcc.27310] [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: 11/14/2023] [Revised: 12/29/2023] [Accepted: 01/03/2024] [Indexed: 02/22/2024]
Abstract
Understanding interactions of inorganic nanoparticles with biomolecules is important in many biotechnology, nanomedicine, and toxicological research, however, the size of typical nanoparticles makes their direct modeling by atomistic simulations unfeasible. Here, we present a bottom-up coarse-graining approach for modeling titanium dioxide (TiO 2 ) nanomaterials in contact with phospholipids that uses the inverse Monte Carlo method to optimize the effective interactions from the structural data obtained in small-scale all-atom simulations of TiO 2 surfaces with lipids in aqueous solution. The resulting coarse-grained models are able to accurately reproduce the structural details of lipid adsorption on different titania surfaces without the use of an explicit solvent, enabling significant computational resource savings and favorable scaling. Our coarse-grained simulations show that small spherical TiO 2 nanoparticles ( r = 2 nm) can only be partially wrapped by a lipid bilayer with phosphoethanolamine headgroups, however, the lipid adsorption increases with the radius of the nanoparticle. The current approach can be used to study the effect of the size and shape of TiO 2 nanoparticles on their interactions with cell membrane lipids, which can be a determining factor in membrane wrapping as well as the recently discovered phenomenon of nanoquarantining, which involves the formation of layered nanomaterial-lipid structures.
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Affiliation(s)
- Mikhail Ivanov
- Department of Materials and Environmental Chemistry, Stockholm University, Stockholm, Sweden
| | - Alexander P Lyubartsev
- Department of Materials and Environmental Chemistry, Stockholm University, Stockholm, Sweden
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8
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Tang K, Cui X. A Review on Investigating the Interactions between Nanoparticles and the Pulmonary Surfactant Monolayer with Coarse-Grained Molecular Dynamics Method. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2024; 40:11829-11842. [PMID: 38809819 DOI: 10.1021/acs.langmuir.4c00909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
Pulmonary drug delivery has garnered significant attention due to its targeted local lung action, minimal toxic side effects, and high drug utilization. However, the physicochemical properties of inhaled nanoparticles (NPs) used as drug carriers can influence their interactions with the pulmonary surfactant (PS) monolayer, potentially altering the fate of the NPs and impairing the biophysical function of the PS monolayer. Thus, the objective of this review is to summarize how the physicochemical properties of NPs affect their interactions with the PS monolayer. Initially, the definition and properties of NPs, as well as the composition and characteristics of the PS monolayer, are introduced. Subsequently, the coarse-grained molecular dynamics (CGMD) simulation method for studying the interactions between NPs and the PS monolayer is presented. Finally, the implications of the hydrophobicity, size, shape, surface charge, surface modification, and aggregation of NPs on their interactions with the PS monolayer and on the composition of biomolecular corona are discussed. In conclusion, gaining a deeper understanding of the effects of the physicochemical properties of NPs on their interactions with the PS monolayer will contribute to the development of safer and more effective nanomedicines for pulmonary drug delivery.
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Affiliation(s)
- Kailiang Tang
- School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Xinguang Cui
- School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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9
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Ghosh D, Biswas A, Radhakrishna M. Advanced computational approaches to understand protein aggregation. BIOPHYSICS REVIEWS 2024; 5:021302. [PMID: 38681860 PMCID: PMC11045254 DOI: 10.1063/5.0180691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 03/18/2024] [Indexed: 05/01/2024]
Abstract
Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.
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Affiliation(s)
- Deepshikha Ghosh
- Department of Biological Sciences and Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
| | - Anushka Biswas
- Department of Chemical Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
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10
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Malajczuk CJ, Mancera RL. An atomistic characterization of high-density lipoproteins and the conserved "LN" region of apoA-I. Biophys J 2024; 123:1116-1128. [PMID: 38555508 PMCID: PMC11079945 DOI: 10.1016/j.bpj.2024.03.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/19/2024] [Accepted: 03/27/2024] [Indexed: 04/02/2024] Open
Abstract
The physicochemical characteristics of the various subpopulations of high-density lipoproteins (HDLs) and, in particular, their surface properties determine their ability to scavenge lipids and interact with specific receptors and peptides. Five representative spheroidal HDL subpopulation models were mapped from a previously reported equilibrated coarse-grained (CG) description to an atomistic representation for subsequent molecular dynamics simulation. For each HDL model a range of finer-level analyses was undertaken, including the component-wise characterization of HDL surfaces, the average size and composition of hydrophobic surface patches, dynamic protein secondary structure monitoring, and the proclivity for solvent exposure of the proposed β-amyloid (Aβ) binding region of apolipoprotein A-I (apoA-I), "LN." This study reveals that previously characterized ellipsoidal HDL3a and HDL2a models revert to a more spherical geometry in an atomistic representation due to the enhanced conformational flexibility afforded to the apoA-I protein secondary structure, allowing for enhanced surface lipid packing and lower overall surface hydrophobicity. Indeed, the proportional surface hydrophobicity and apoA-I exposure reduced with increasing HDL size, consistent with previous characterizations. Furthermore, solvent exposure of the "LN" region of apoA-I was exclusively limited to the smallest HDL3c model within the timescale of the simulations, and typically corresponded to a distinct loss in secondary structure across the "LN" region to form part of a significant contiguous hydrophobic patch on the HDL surface. Taken together, these findings provide preliminary evidence for a subpopulation-specific interaction between HDL3c particles and circulating hydrophobic species such as Aβ via the exposed "LN" region of apoA-I.
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Affiliation(s)
- Chris J Malajczuk
- Curtin Medical School, Curtin Health Innovation Research Institute and Curtin Institute for Data Science, Curtin University, Perth, WA, Australia
| | - Ricardo L Mancera
- Curtin Medical School, Curtin Health Innovation Research Institute and Curtin Institute for Data Science, Curtin University, Perth, WA, Australia.
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11
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Shivgan AT, Marzinek JK, Krah A, Matsudaira P, Verma CS, Bond PJ. Coarse-Grained Model of Glycosaminoglycans for Biomolecular Simulations. J Chem Theory Comput 2024; 20:3308-3321. [PMID: 38358378 DOI: 10.1021/acs.jctc.3c01088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2024]
Abstract
Proteoglycans contain glycosaminoglycans (GAGs) which are negatively charged linear polymers made of repeating disaccharide units of uronic acid and hexosamine units. They play vital roles in numerous physiological and pathological processes, particularly in governing cellular communication and attachment. Depending on their sulfonation state, acetylation, and glycosidic linkages, GAGs belong to different families. The high molecular weight, heterogeneity, and flexibility of GAGs hamper their characterization at atomic resolution, but this may be circumvented via coarse-grained (CG) approaches. In this work, we report a CG model for a library of common GAG types in their isolated or proteoglycan-linked states compatible with version 2.2 (v2.2) of the widely popular CG Martini force field. The model reproduces conformational and thermodynamic properties for a wide variety of GAGs, as well as matching structural and binding data for selected proteoglycan test systems. The parameters developed here may thus be employed to study a range of GAG-containing biomolecular systems, thereby benefiting from the efficiency and broad applicability of the Martini framework.
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Affiliation(s)
- Aishwary T Shivgan
- National University of Singapore, Department of Biological Sciences, 14 Science Drive 4, Singapore 117543, Singapore
- Bioinformatics Institute (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
| | - Jan K Marzinek
- Bioinformatics Institute (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
| | - Alexander Krah
- Bioinformatics Institute (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
| | - Paul Matsudaira
- National University of Singapore, Department of Biological Sciences, 14 Science Drive 4, Singapore 117543, Singapore
| | - Chandra S Verma
- National University of Singapore, Department of Biological Sciences, 14 Science Drive 4, Singapore 117543, Singapore
- Bioinformatics Institute (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
- School of Biological sciences, Nanyang Technological University, 50 Nanyang Drive, Singapore 637551, Singapore
| | - Peter J Bond
- National University of Singapore, Department of Biological Sciences, 14 Science Drive 4, Singapore 117543, Singapore
- Bioinformatics Institute (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
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12
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Wang Y, Hernandez R. Construction of Multiscale Dissipative Particle Dynamics (DPD) Models from Other Coarse-Grained Models. ACS OMEGA 2024; 9:17667-17680. [PMID: 38645334 PMCID: PMC11025104 DOI: 10.1021/acsomega.4c01868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 03/06/2024] [Accepted: 03/15/2024] [Indexed: 04/23/2024]
Abstract
We present a general scheme for converting coarse-grained models into Dissipative Particle Dynamics (DPD) models. We build the corresponding DPD models by analogy with the de novo DPD coarse-graining scheme suggested by Groot and Warren (J. Chem. Phys., 1997). Electrostatic interactions between charged DPD particles are represented though the addition of a long-range Slater Coulomb potential as suggested by González-Melchor et al. (J. Chem. Phys., 2006). The construction is illustrated by converting MARTINI models for various proteins into a DPD representation, but it not restricted to the usual potential form in the MARTINI model-viz., Lennard-Jones potentials. We further extended the DPD scheme away from the typical use of homogeneous particle sizes, therefore faithfully representing the variations in the particle sizes seen in the underlying MARTINI model. The accuracy of the resulting construction of our generalized DPD models with respect to several structural observables has been benchmarked favorably against all-atom and MARTINI models for a selected set of peptides and proteins, and variations in the scales of the coarse-graining of the water solvent.
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Affiliation(s)
- Yinhan Wang
- Department of Chemistry, The Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Rigoberto Hernandez
- Department of Chemistry, The Johns Hopkins University, Baltimore, Maryland 21218, United States
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13
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Weiand E, Koenig PH, Rodriguez-Ropero F, Roiter Y, Angioletti-Uberti S, Dini D, Ewen JP. Boundary Lubrication Performance of Polyelectrolyte-Surfactant Complexes on Biomimetic Surfaces. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2024; 40:7933-7946. [PMID: 38573738 PMCID: PMC11025133 DOI: 10.1021/acs.langmuir.3c03737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 03/20/2024] [Accepted: 03/20/2024] [Indexed: 04/05/2024]
Abstract
Aqueous mixtures of oppositely charged polyelectrolytes and surfactants are useful in many industrial applications, such as shampoos and hair conditioners. In this work, we investigate the friction between biomimetic hair surfaces in the presence of adsorbed complexes formed from cationic polyelectrolytes and anionic surfactants in an aqueous solution. We apply nonequilibrium molecular dynamics (NEMD) simulations using the coarse-grained MARTINI model. We first developed new MARTINI parameters for cationic guar gum (CGG), a functionalized, plant-derived polysaccharide. The complexation of CGG and the anionic surfactant sodium dodecyl sulfate (SDS) on virgin and chemically damaged biomimetic hair surfaces was studied using a sequential adsorption approach. We then carried out squeeze-out and sliding NEMD simulations to assess the boundary lubrication performance of the CGG-SDS complex compressed between two hair surfaces. At low pressure, we observe a synergistic friction behavior for the CGG-SDS complex, which gives lower shear stress than either pure CGG or SDS. Here, friction is dominated by viscous dissipation in an interfacial layer comprising SDS and water. At higher pressures, which are probably beyond those usually experienced during hair manipulation, SDS and water are squeezed out, and friction increases due to interdigitation. The outcomes of this work are expected to be beneficial to fine-tune and screen sustainable hair care formulations to provide low friction and therefore a smooth feel and reduced entanglement.
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Affiliation(s)
- Erik Weiand
- Department
of Mechanical Engineering, Imperial College
London, South Kensington Campus, London SW7 2AZ, U.K.
- Institute
of Molecular Science and Engineering, Imperial
College London, South
Kensington Campus, London SW7 2AZ, U.K.
- Thomas
Young Centre for the Theory and Simulation of Materials, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K.
| | - Peter H. Koenig
- Corporate
Functions Analytical and Data & Modeling Sciences, Mason Business
Center, The Procter and Gamble Company, Mason, Ohio 45040, United States
| | - Francisco Rodriguez-Ropero
- Corporate
Functions Analytical and Data & Modeling Sciences, Mason Business
Center, The Procter and Gamble Company, Mason, Ohio 45040, United States
| | - Yuri Roiter
- Corporate
Functions Analytical and Data & Modeling Sciences, Mason Business
Center, The Procter and Gamble Company, Mason, Ohio 45040, United States
| | - Stefano Angioletti-Uberti
- Institute
of Molecular Science and Engineering, Imperial
College London, South
Kensington Campus, London SW7 2AZ, U.K.
- Thomas
Young Centre for the Theory and Simulation of Materials, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K.
- Department
of Materials, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K.
| | - Daniele Dini
- Department
of Mechanical Engineering, Imperial College
London, South Kensington Campus, London SW7 2AZ, U.K.
- Institute
of Molecular Science and Engineering, Imperial
College London, South
Kensington Campus, London SW7 2AZ, U.K.
- Thomas
Young Centre for the Theory and Simulation of Materials, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K.
| | - James P. Ewen
- Department
of Mechanical Engineering, Imperial College
London, South Kensington Campus, London SW7 2AZ, U.K.
- Institute
of Molecular Science and Engineering, Imperial
College London, South
Kensington Campus, London SW7 2AZ, U.K.
- Thomas
Young Centre for the Theory and Simulation of Materials, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K.
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14
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Grassmann G, Miotto M, Desantis F, Di Rienzo L, Tartaglia GG, Pastore A, Ruocco G, Monti M, Milanetti E. Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments. Chem Rev 2024; 124:3932-3977. [PMID: 38535831 PMCID: PMC11009965 DOI: 10.1021/acs.chemrev.3c00550] [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: 07/31/2023] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 04/11/2024]
Abstract
Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.
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Affiliation(s)
- Greta Grassmann
- Department
of Biochemical Sciences “Alessandro Rossi Fanelli”, Sapienza University of Rome, Rome 00185, Italy
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Rome 00161, Italy
| | - Mattia Miotto
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Rome 00161, Italy
| | - Fausta Desantis
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Rome 00161, Italy
- The
Open University Affiliated Research Centre at Istituto Italiano di
Tecnologia, Genoa 16163, Italy
| | - Lorenzo Di Rienzo
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Rome 00161, Italy
| | - Gian Gaetano Tartaglia
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Rome 00161, Italy
- Department
of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Genoa 16163, Italy
- Center
for Human Technologies, Genoa 16152, Italy
| | - Annalisa Pastore
- Experiment
Division, European Synchrotron Radiation
Facility, Grenoble 38043, France
| | - Giancarlo Ruocco
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Rome 00161, Italy
- Department
of Physics, Sapienza University, Rome 00185, Italy
| | - Michele Monti
- RNA
System Biology Lab, Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Genoa 16163, Italy
| | - Edoardo Milanetti
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Rome 00161, Italy
- Department
of Physics, Sapienza University, Rome 00185, Italy
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15
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Ozturk TN, König M, Carpenter TS, Pedersen KB, Wassenaar TA, Ingólfsson HI, Marrink SJ. Building complex membranes with Martini 3. Methods Enzymol 2024; 701:237-285. [PMID: 39025573 DOI: 10.1016/bs.mie.2024.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
The Martini model is a popular force field for coarse-grained simulations. Membranes have always been at the center of its development, with the latest version, Martini 3, showing great promise in capturing more and more realistic behavior. In this chapter we provide a step-by-step tutorial on how to construct starting configurations, run initial simulations and perform dedicated analysis for membrane-based systems of increasing complexity, including leaflet asymmetry, curvature gradients and embedding of membrane proteins.
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Affiliation(s)
- Tugba Nur Ozturk
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States
| | - Melanie König
- Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands
| | - Timothy S Carpenter
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States
| | | | - Tsjerk A Wassenaar
- Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands; Institute for Life Science and Technology, Hanze University of Applied Sciences, Groningen, The Netherlands
| | - Helgi I Ingólfsson
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States.
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands.
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16
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Xu Q, Wang Y, Zheng Y, Zhu Y, Li Z, Liu Y, Ding M. Polymersomes in Drug Delivery─From Experiment to Computational Modeling. Biomacromolecules 2024; 25:2114-2135. [PMID: 38011222 DOI: 10.1021/acs.biomac.3c00903] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Polymersomes, composed of amphiphilic block copolymers, are self-assembled vesicles that have gained attention as potential drug delivery systems due to their good biocompatibility, stability, and versatility. Various experimental techniques have been employed to characterize the self-assembly behaviors and properties of polymersomes. However, they have limitations in revealing molecular details and underlying mechanisms. Computational modeling techniques have emerged as powerful tools to complement experimental studies and enabled researchers to examine drug delivery mechanisms at molecular resolution. This review aims to provide a comprehensive overview of the state of the art in the field of polymersome-based drug delivery systems, with an emphasis on insights gained from both experimental and computational studies. Specifically, we focus on polymersome morphologies, self-assembly kinetics, fusion and fission, behaviors in flow, as well as drug encapsulation and release mechanisms. Furthermore, we also identify existing challenges and limitations in this rapidly evolving field and suggest possible directions for future research.
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Affiliation(s)
- Qianru Xu
- College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, P. R. China
| | - Yiwei Wang
- College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, P. R. China
| | - Yi Zheng
- College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, P. R. China
| | - Yuling Zhu
- College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, P. R. China
| | - Zifen Li
- College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, P. R. China
| | - Yang Liu
- College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, P. R. China
| | - Mingming Ding
- College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, P. R. China
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17
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Jin J, Reichman DR. Hierarchical Framework for Predicting Entropies in Bottom-Up Coarse-Grained Models. J Phys Chem B 2024; 128:3182-3199. [PMID: 38507575 DOI: 10.1021/acs.jpcb.3c07624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
The thermodynamic entropy of coarse-grained (CG) models stands as one of the most important properties for quantifying the missing information during the CG process and for establishing transferable (or extendible) CG interactions. However, performing additional CG simulations on top of model construction often leads to significant additional computational overhead. In this work, we propose a simple hierarchical framework for predicting the thermodynamic entropies of various molecular CG systems. Our approach employs a decomposition of the CG interactions, enabling the estimation of the CG partition function and thermodynamic properties a priori. Starting from the ideal gas description, we leverage classical perturbation theory to systematically incorporate simple yet essential interactions, ranging from the hard sphere model to the generalized van der Waals model. Additionally, we propose an alternative approach based on multiparticle correlation functions, allowing for systematic improvements through higher-order correlations. Numerical applications to molecular liquids validate the high fidelity of our approach, and our computational protocols demonstrate that a reduced model with simple energetics can reasonably estimate the thermodynamic entropy of CG models without performing any CG simulations. Overall, our findings present a systematic framework for estimating not only the entropy but also other thermodynamic properties of CG models, relying solely on information from the reference system.
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Affiliation(s)
- Jaehyeok Jin
- Department of Chemistry, Columbia University, 3000 Broadway, New York, New York 10027, United States
| | - David R Reichman
- Department of Chemistry, Columbia University, 3000 Broadway, New York, New York 10027, United States
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18
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Cioffi MD, Husby ML, Gerstman BS, Stahelin RV, Chapagain PP. Role of phosphatidic acid lipids on plasma membrane association of the Ebola virus matrix protein VP40. Biochim Biophys Acta Mol Cell Biol Lipids 2024; 1869:159464. [PMID: 38360201 DOI: 10.1016/j.bbalip.2024.159464] [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: 08/21/2023] [Revised: 01/14/2024] [Accepted: 01/31/2024] [Indexed: 02/17/2024]
Abstract
The Ebola virus matrix protein VP40 is responsible for the formation of the viral matrix by localizing at the inner leaflet of the human plasma membrane (PM). Various lipid types, including PI(4,5)P2 (i.e. PIP2) and phosphatidylserine (PS), play active roles in this process. Specifically, the negatively charged headgroups of both PIP2 and PS interact with the basic residues of VP40 and stabilize it at the membrane surface, allowing for eventual egress. Phosphatidic acid (PA), resulting from the enzyme phospholipase D (PLD), is also known to play an active role in viral development. In this work, we performed a biophysical and computational analysis to investigate the effects of the presence of PA on the membrane localization and association of VP40. We used coarse-grained molecular dynamics simulations to quantify VP40 hexamer interactions with the inner leaflet of the PM. Analysis of the local distribution of lipids shows enhanced lipid clustering when PA is abundant in the membrane. We observed that PA lipids have a similar role to that of PS lipids in VP40 association due to the geometry and charge. Complementary experiments performed in cell culture demonstrate competition between VP40 and a canonical PA-binding protein for the PM. Also, inhibition of PA synthesis reduced the detectable budding of virus-like particles. These computational and experimental results provide new insights into the early stages of Ebola virus budding and the role that PA lipids have on the VP40-PM association.
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Affiliation(s)
- Michael D Cioffi
- Department of Physics, Florida International University, Miami, FL 33199, USA
| | - Monica L Husby
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907, USA
| | - Bernard S Gerstman
- Department of Physics, Florida International University, Miami, FL 33199, USA; Biomolecular Sciences Institute, Florida International University, Miami, FL 33199, USA
| | - Robert V Stahelin
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907, USA; The Purdue Institute for Inflammation, Immunology and Infectious Disease, Purdue University, West Lafayette, IN 47907, USA.
| | - Prem P Chapagain
- Department of Physics, Florida International University, Miami, FL 33199, USA; Biomolecular Sciences Institute, Florida International University, Miami, FL 33199, USA.
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19
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Vo ATN, Murphy MA, Phan PK, Prabhu RK, Stone TW. Effect of Force Field Resolution on Membrane Mechanical Response and Mechanoporation Damage under Deformation Simulations. Mol Biotechnol 2024; 66:865-875. [PMID: 37016179 DOI: 10.1007/s12033-023-00726-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 03/19/2023] [Indexed: 04/06/2023]
Abstract
Damage induced by transient disruption and mechanoporation in an intact cell membrane is a vital nanoscale biomechanical mechanism that critically affects cell viability. To complement experimental studies of mechanical membrane damage and disruption, molecular dynamics (MD) simulations have been performed at different force field resolutions, each of which follows different parameterization strategies and thus may influence the properties and dynamics of membrane systems. Therefore, the current study performed tensile deformation MD simulations of bilayer membranes using all-atom (AA), united-atom (UA), and coarse-grained Martini (CG-M) models to investigate how the damage biomechanics differs across atomistic and coarse-grained (CG) simulations. The mechanical response and mechanoporation damage were qualitatively similar but quantitatively different in the three models, including some progressive changes based on the coarse-graining level. The membranes yielded and reached ultimate strength at similar strains; however, the coarser systems exhibited lower average yield stresses and failure strains. The average failure strain in the UA model was approximately 7% lower than the AA, and the CG-M was 20% lower than UA and 27% lower than AA. The CG systems also nucleated a higher number of pores and larger pores, which resulted in higher damage during the deformation process. Overall, the study provides insight on the impact of force field-a critical factor in modeling biomolecular systems and their interactions-in inspecting membrane mechanosensitive responses and serves as a reference for justifying the appropriate force field for future studies of more complex membranes and more diverse biomolecular assemblies.
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Affiliation(s)
- Anh T N Vo
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, 200 Research Blvd, Starkville, MS, 39759, USA.
- Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, Starkville, MS, 39762, USA.
| | - Michael A Murphy
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, 200 Research Blvd, Starkville, MS, 39759, USA
| | - Phong K Phan
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, 200 Research Blvd, Starkville, MS, 39759, USA
- Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, Starkville, MS, 39762, USA
| | - Raj K Prabhu
- NASA Johnson Space Center, 2101 NASA Parkway, Houston, TX, 77058, USA
| | - Tonya W Stone
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, 200 Research Blvd, Starkville, MS, 39759, USA
- Department of Mechanical Engineering, Mississippi State University, Mississippi State, Starkville, MS, 39762, USA
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20
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Yang S, Song C. Switching Go̅ -Martini for Investigating Protein Conformational Transitions and Associated Protein-Lipid Interactions. J Chem Theory Comput 2024; 20:2618-2629. [PMID: 38447049 DOI: 10.1021/acs.jctc.3c01222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Proteins are dynamic biomolecules that can transform between different conformational states when exerting physiological functions, which is difficult to simulate using all-atom methods. Coarse-grained (CG) Go̅-like models are widely used to investigate large-scale conformational transitions, which usually adopt implicit solvent models and therefore cannot explicitly capture the interaction between proteins and surrounding molecules, such as water and lipid molecules. Here, we present a new method, named Switching Go̅-Martini, to simulate large-scale protein conformational transitions between different states, based on the switching Go̅ method and the CG Martini 3 force field. The method is straightforward and efficient, as demonstrated by the benchmarking applications for multiple protein systems, including glutamine binding protein (GlnBP), adenylate kinase (AdK), and β2-adrenergic receptor (β2AR). Moreover, by employing the Switching Go̅-Martini method, we can not only unveil the conformational transition from the E2Pi-PL state to E1 state of the type 4 P-type ATPase (P4-ATPase) flippase ATP8A1-CDC50 but also provide insights into the intricate details of lipid transport.
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Affiliation(s)
- Song Yang
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Chen Song
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
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21
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Chaimovich M, Chaimovich A. Relative Resolution: An Analysis with the Kullback-Leibler Entropy. J Chem Theory Comput 2024; 20:2074-2087. [PMID: 38416535 DOI: 10.1021/acs.jctc.3c01052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
A novel type of a multiscale approach, called Relative Resolution (RelRes), can correctly retrieve the behavior of various nonpolar liquids while speeding up molecular simulations by almost an order of magnitude. In this approach in a single system, molecules switch their resolution in terms of their relative separation, with near neighbors interacting via fine-grained potentials, yet far neighbors interacting via coarse-grained potentials; notably, these two potentials are analytically parametrized by a multipole approximation. Our current work focuses on analyzing RelRes by relating it with the Kullback-Leibler (KL) entropy, which is a useful metric for multiscale errors. In particular, we thoroughly examine the exact and approximate versions of this informatic measure for several alkane systems. By analyzing its dependency on the system size, we devise a formula for predicting the exact KL entropy of an "infinite" system via the computation of the approximate KL entropy of an "infinitesimal" system. Demonstrating that the KL entropy can holistically capture many multiscale errors, we settle bounds for the KL entropy that ensure a sufficient representation of the structural and thermal behavior by the RelRes algorithm. This, in turn, allows the scientific community to readily determine the ideal switching distance for an arbitrary RelRes system.
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Affiliation(s)
- Mark Chaimovich
- Russian School of Mathematics, North Bethesda, Maryland 20852, United States
| | - Aviel Chaimovich
- Department of Chemical and Biological Engineering, Drexel University, Philadelphia, Pennsylvania 19104, United States
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22
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Mondal S, Cui Q. Sequence Sensitivity in Membrane Remodeling by Polyampholyte Condensates. J Phys Chem B 2024; 128:2087-2099. [PMID: 38407041 DOI: 10.1021/acs.jpcb.3c08149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Intrinsically disordered peptides (IDPs) have been found to undergo liquid-liquid phase separation (LLPS) and produce complex coacervates that play numerous regulatory roles in the cell. Recent experimental studies have discovered that LLPS at or near the membrane surface helps in the biomolecular organization during signaling events and can significantly alter the membrane morphology. However, the molecular mechanism and microscopic details of such processes still remain unclear. Here we study the effect of polyampholyte and polyelectrolyte condensation on two different anionic membranes, as they represent a majority of naturally occurring IDPs. The polyampholytes are fifty-residue polymers, made of glutamate(E) and lysine(K) with different charge patterns. The polyelectrolytes are separate chains of E25 and K25. We first calibrate the MARTINI v3.0 force field and then perform long-time-scale coarse-grained molecular dynamics simulations. We find that condensates formed by all the polyampholytes get adsorbed on the membrane. However, the strong polyampholytes (i.e., blocky sequences) can remodel the membranes more prominently than the weaker ones (i.e., scrambled sequences). Condensates formed by the blocky sequences induce a significant negative curvature (∼0.1 nm-1) and local demixing of lipids, whereas those by the scrambled sequences tend to wet the membrane to a greater extent without generating significant curvature or demixing. We perform several microscopic analyses to characterize the nature of the interaction between membranes and these condensates. Our analyses of interaction energetics reveal that membrane remodeling and/or wetting are favored by enhanced interactions between polyampholytes with lipids and the counterions.
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Affiliation(s)
- Sayantan Mondal
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Qiang Cui
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States
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23
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Pornputtapitak W, Thiangjit Y, Tantirungrotechai Y. Effect of Functional Groups in Lipid Molecules on the Stability of Nanostructured Lipid Carriers: Experimental and Computational Investigations. ACS OMEGA 2024; 9:11012-11024. [PMID: 38463339 PMCID: PMC10918666 DOI: 10.1021/acsomega.4c00685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 02/05/2024] [Indexed: 03/12/2024]
Abstract
Lipid nanoparticles have been used as drug carriers for decades. Many lipid types have been screened for both solid lipid nanoparticles and nanostructured lipid carriers (NLCs). Specifically, for NLCs that are composed of lipids in the solid form mixed with lipids in the liquid form, compatibility of lipid combination and phase behavior play a significant role in the NLC quality. In this study, stearic acid (STA) and cetyl palmitate (CTP) were used as solid lipids, and oleic acid (OLA), isopropyl palmitate (IPP), and caprylic/capric triglycerides were used as liquid lipids. NLCs were prepared at solid:liquid ratios of 50:50, 70:30, and 90:10, respectively. The characteristics and stability of the prepared NLCs were investigated. Laboratory results showed that the solid lipid had a greater influence on the particle size than the liquid lipid. Meanwhile, cetyl palmitate, an ester compound, provides higher NLC stability compared to stearic acid, a carboxylic acid compound. A MARTINI-based coarse-grained molecular dynamics simulation was used to simulate the lipid droplet in water. The distribution of lipid molecules in the droplet was characterized by the polar group density distribution. Different spatial arrangements of the lipid headgroup and lipid molecules, when CTP or STA was used as solid lipids, might contribute to the different stabilities of prepared NLCs. The understanding of mixed lipid systems via simulations will be a significant tool for screening the type of lipids for drug carriers and other pharmaceutical applications.
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Affiliation(s)
- Warangkana Pornputtapitak
- Department
of Chemical Engineering, Faculty of Engineering, Mahidol University, Nakhon
Pathom 73170, Thailand
| | - Yenruedee Thiangjit
- Thammasat
University Research Unit in Innovation of Molecular Hybrid for Biomedical
Application and Division of Chemistry, Faculty of Science and Technology, Thammasat University, Pathum Thani 12120, Thailand
| | - Yuthana Tantirungrotechai
- Thammasat
University Research Unit in Innovation of Molecular Hybrid for Biomedical
Application and Division of Chemistry, Faculty of Science and Technology, Thammasat University, Pathum Thani 12120, Thailand
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24
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Hooten M, Banerjee A, Dutt M. Multiscale, Multiresolution Coarse-Grained Model via a Hybrid Approach: Solvation, Structure, and Self-Assembly of Aromatic Tripeptides. J Chem Theory Comput 2024; 20:1689-1703. [PMID: 37931005 DOI: 10.1021/acs.jctc.3c00458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
Short aromatic peptides have been observed to assemble into diverse nanostructures, including fibers, tubes, and vesicles, using computational techniques. However, the computational studies have employed top-down coarse-grained (CG) models, which are unable to capture the assembly along with the conformation, packing, and organization of the peptides within the aggregates in a manner that is consistent with the all atom (AA) representation of the molecules. In this study, a hybrid structure- and force-based approach is adapted to develop a bottom-up CG force field of triphenylalanine using reference data from AA trajectories. This approach follows a flexible methodology to approximate the chemical complexity of the underlying AA representation with the chosen CG representation. Two CG models are developed with distinct representations of the aromatic side chains. The first uses a simple single-bead representation, while the second uses a three-bead representation to more accurately represent the planarity of the ring. The one-bead model yields nanorods, while the three-bead model results in nanospheres. The role of different chemical groups in the assembly of nanostructures is identified, along with the importance of steric effects on the packing of the peptides within assemblies.
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Affiliation(s)
- Mason Hooten
- Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States
| | - Akash Banerjee
- Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States
| | - Meenakshi Dutt
- Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States
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25
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Kharche S, Yadav M, Hande V, Prakash S, Sengupta D. Improved Protein Dynamics and Hydration in the Martini3 Coarse-Grain Model. J Chem Inf Model 2024; 64:837-850. [PMID: 38291973 DOI: 10.1021/acs.jcim.3c00802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
The Martini coarse-grain force-field has emerged as an important framework to probe cellular processes at experimentally relevant time- and length-scales. However, the recently developed version, the Martini3 force-field with the implemented Go̅ model (Martini3Go̅), as well as previous variants of the Martini model have not been benchmarked and rigorously tested for globular proteins. In this study, we consider three globular proteins, ubiquitin, lysozyme, and cofilin, and compare protein dynamics and hydration with observables from experiments and all-atom simulations. We show that the Martini3Go̅ model is able to accurately model the structural and dynamic features of small globular proteins. Overall, the structural integrity of the proteins is maintained, as validated by contact maps, radii of gyration (Rg), and SAXS profiles. The chemical shifts predicted from the ensemble sampled in the simulations are consistent with the experimental data. Further, a good match is observed in the protein-water interaction energetics, and the hydration levels of the residues are similar to atomistic simulations. However, the protein-water interaction dynamics is not accurately represented and appears to depend on the protein structural complexity, residue specificity, and water dynamics. Our work is a step toward testing and assessing the Martini3Go̅ model and provides insights into future efforts to refine Martini models with improved solvation effects and better correspondence to the underlying all-atom systems.
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Affiliation(s)
- Shalmali Kharche
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Manjul Yadav
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Vrushali Hande
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Shikha Prakash
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Durba Sengupta
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
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26
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Schnee P, Pleiss J, Jeltsch A. Approaching the catalytic mechanism of protein lysine methyltransferases by biochemical and simulation techniques. Crit Rev Biochem Mol Biol 2024; 59:20-68. [PMID: 38449437 DOI: 10.1080/10409238.2024.2318547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/10/2024] [Indexed: 03/08/2024]
Abstract
Protein lysine methyltransferases (PKMTs) transfer up to three methyl groups to the side chains of lysine residues in proteins and fulfill important regulatory functions by controlling protein stability, localization and protein/protein interactions. The methylation reactions are highly regulated, and aberrant methylation of proteins is associated with several types of diseases including neurologic disorders, cardiovascular diseases, and various types of cancer. This review describes novel insights into the catalytic machinery of various PKMTs achieved by the combined application of biochemical experiments and simulation approaches during the last years, focusing on clinically relevant and well-studied enzymes of this group like DOT1L, SMYD1-3, SET7/9, G9a/GLP, SETD2, SUV420H2, NSD1/2, different MLLs and EZH2. Biochemical experiments have unraveled many mechanistic features of PKMTs concerning their substrate and product specificity, processivity and the effects of somatic mutations observed in PKMTs in cancer cells. Structural data additionally provided information about the substrate recognition, enzyme-substrate complex formation, and allowed for simulations of the substrate peptide interaction and mechanism of PKMTs with atomistic resolution by molecular dynamics and hybrid quantum mechanics/molecular mechanics methods. These simulation technologies uncovered important mechanistic details of the PKMT reaction mechanism including the processes responsible for the deprotonation of the target lysine residue, essential conformational changes of the PKMT upon substrate binding, but also rationalized regulatory principles like PKMT autoinhibition. Further developments are discussed that could bring us closer to a mechanistic understanding of catalysis of this important class of enzymes in the near future. The results described here illustrate the power of the investigation of enzyme mechanisms by the combined application of biochemical experiments and simulation technologies.
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Affiliation(s)
- Philipp Schnee
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany
| | - Jürgen Pleiss
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany
| | - Albert Jeltsch
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany
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27
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Del Razo MJ, Crommelin D, Bolhuis PG. Data-driven dynamical coarse-graining for condensed matter systems. J Chem Phys 2024; 160:024108. [PMID: 38193550 DOI: 10.1063/5.0177553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 12/05/2023] [Indexed: 01/10/2024] Open
Abstract
Simulations of condensed matter systems often focus on the dynamics of a few distinguished components but require integrating the full system. A prime example is a molecular dynamics simulation of a (macro)molecule in a solution, where the molecule(s) and the solvent dynamics need to be integrated, rendering the simulations computationally costly and often unfeasible for physically/biologically relevant time scales. Standard coarse graining approaches can reproduce equilibrium distributions and structural features but do not properly include the dynamics. In this work, we develop a general data-driven coarse-graining methodology inspired by the Mori-Zwanzig formalism, which shows that macroscopic systems with a large number of degrees of freedom can be described by a few relevant variables and additional noise and memory terms. Our coarse-graining method consists of numerical integrators for the distinguished components, where the noise and interaction terms with other system components are substituted by a random variable sampled from a data-driven model. The model is parameterized using data from multiple short-time full-system simulations, and then, it is used to run long-time simulations. Applying our methodology to three systems-a distinguished particle under a harmonic and a bistable potential and a dimer with two metastable configurations-the resulting coarse-grained models are capable of reproducing not only the equilibrium distributions but also the dynamic behavior due to temporal correlations and memory effects. Remarkably, our method even reproduces the transition dynamics between metastable states, which is challenging to capture correctly. Our approach is not constrained to specific dynamics and can be extended to systems beyond Langevin dynamics, and, in principle, even to non-equilibrium dynamics.
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Affiliation(s)
- Mauricio J Del Razo
- Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany
- Van't Hoff Institute for Molecular Sciences, University of Amsterdam, PO Box 94157, 1090GD Amsterdam, The Netherlands
- Korteweg-de Vries Institute for Mathematics, University of Amsterdam, PO Box 94248, 1090GD Amsterdam, The Netherlands
- Dutch Institute for Emergent Phenomena, University of Amsterdam, Amsterdam, The Netherlands
| | - Daan Crommelin
- Korteweg-de Vries Institute for Mathematics, University of Amsterdam, PO Box 94248, 1090GD Amsterdam, The Netherlands
- Centrum Wiskunde & Informatica, 1098 XG Amsterdam, The Netherlands
| | - Peter G Bolhuis
- Van't Hoff Institute for Molecular Sciences, University of Amsterdam, PO Box 94157, 1090GD Amsterdam, The Netherlands
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28
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Patel KN, Chavda D, Manna M. Molecular Docking of Intrinsically Disordered Proteins: Challenges and Strategies. Methods Mol Biol 2024; 2780:165-201. [PMID: 38987470 DOI: 10.1007/978-1-0716-3985-6_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024]
Abstract
Intrinsically disordered proteins (IDPs) are a novel class of proteins that have established a significant importance and attention within a very short period of time. These proteins are essentially characterized by their inherent structural disorder, encoded mainly by their amino acid sequences. The profound abundance of IDPs and intrinsically disordered regions (IDRs) in the biological world delineates their deep-rooted functionality. IDPs and IDRs convey such extensive functionality through their unique dynamic nature, which enables them to carry out huge number of multifaceted biomolecular interactions and make them "interaction hub" of the cellular systems. Additionally, with such widespread functions, their misfunctioning is also intimately associated with multiple diseases. Thus, understanding the dynamic heterogeneity of various IDPs along with their interactions with respective binding partners is an important field with immense potentials in biomolecular research. In this context, molecular docking-based computational approaches have proven to be remarkable in case of ordered proteins. Molecular docking methods essentially model the biomolecular interactions in both structural and energetic terms and use this information to characterize the putative interactions between the two participant molecules. However, direct applications of the conventional docking methods to study IDPs are largely limited by their structural heterogeneity and demands for unique IDP-centric strategies. Thus, in this chapter, we have presented an overview of current methodologies for successful docking operations involving IDPs and IDRs. These specialized methods majorly include the ensemble-based and fragment-based approaches with their own benefits and limitations. More recently, artificial intelligence and machine learning-assisted approaches are also used to significantly reduce the complexity and computational burden associated with various docking applications. Thus, this chapter aims to provide a comprehensive summary of major challenges and recent advancements of molecular docking approaches in the IDP field for their better utilization and greater applicability.Asp (D).
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Affiliation(s)
- Keyur N Patel
- Applied Phycology and Biotechnology Division, CSIR Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Dhruvil Chavda
- Applied Phycology and Biotechnology Division, CSIR Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Moutusi Manna
- Applied Phycology and Biotechnology Division, CSIR Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India.
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29
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Cieślak D, Kabelka I, Bartuzi D. Molecular Dynamics Simulations in Protein-Protein Docking. Methods Mol Biol 2024; 2780:91-106. [PMID: 38987465 DOI: 10.1007/978-1-0716-3985-6_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024]
Abstract
Concerted interactions between all the cell components form the basis of biological processes. Protein-protein interactions (PPIs) constitute a tremendous part of this interaction network. Deeper insight into PPIs can help us better understand numerous diseases and lead to the development of new diagnostic and therapeutic strategies. PPI interfaces, until recently, were considered undruggable. However, it is now believed that the interfaces contain "hot spots," which could be targeted by small molecules. Such a strategy would require high-quality structural data of PPIs, which are difficult to obtain experimentally. Therefore, in silico modeling can complement or be an alternative to in vitro approaches. There are several computational methods for analyzing the structural data of the binding partners and modeling of the protein-protein dimer/oligomer structure. The major problem with in silico structure prediction of protein assemblies is obtaining sufficient sampling of protein dynamics. One of the methods that can take protein flexibility and the effects of the environment into account is Molecular Dynamics (MD). While sampling of the whole protein-protein association process with plain MD would be computationally expensive, there are several strategies to harness the method to PPI studies while maintaining reasonable use of resources. This chapter reviews known applications of MD in the PPI investigation workflows.
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Affiliation(s)
- Dominika Cieślak
- Laboratory of Plant Protein Phosphorylation, Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
| | - Ivo Kabelka
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Damian Bartuzi
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modelling Lab, Medical University of Lublin, Lublin, Poland.
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30
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Loose T, Sahrmann PG, Qu TS, Voth GA. Coarse-Graining with Equivariant Neural Networks: A Path Toward Accurate and Data-Efficient Models. J Phys Chem B 2023; 127:10564-10572. [PMID: 38033234 PMCID: PMC10726966 DOI: 10.1021/acs.jpcb.3c05928] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/30/2023] [Accepted: 11/09/2023] [Indexed: 12/02/2023]
Abstract
Machine learning has recently entered into the mainstream of coarse-grained (CG) molecular modeling and simulation. While a variety of methods for incorporating deep learning into these models exist, many of them involve training neural networks to act directly as the CG force field. This has several benefits of which the most significant is accuracy. Neural networks can inherently incorporate multibody effects during the calculation of CG forces, and a well-trained neural network force field outperforms pairwise basis sets generated from essentially any methodology. However, this comes at a significant cost. First, these models are typically slower than pairwise force fields, even when accounting for specialized hardware, which accelerates the training and integration of such networks. The second and the focus of this paper is the need for a considerable amount of data to train such force fields. It is common to use 10s of microseconds of molecular dynamics data to train a single CG model, which approaches the point of eliminating the CG model's usefulness in the first place. As we investigate in this work, this "data-hunger" trap from neural networks for predicting molecular energies and forces can be remediated in part by incorporating equivariant convolutional operations. We demonstrate that, for CG water, networks that incorporate equivariant convolutional operations can produce functional models using data sets as small as a single frame of reference data, while networks without these operations cannot.
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Affiliation(s)
| | | | - Thomas S. Qu
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, James Franck Institute,
and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, United States
| | - Gregory A. Voth
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, James Franck Institute,
and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, United States
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31
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Venkatraman K, Lee CT, Garcia GC, Mahapatra A, Milshteyn D, Perkins G, Kim K, Pasolli HA, Phan S, Lippincott‐Schwartz J, Ellisman MH, Rangamani P, Budin I. Cristae formation is a mechanical buckling event controlled by the inner mitochondrial membrane lipidome. EMBO J 2023; 42:e114054. [PMID: 37933600 PMCID: PMC10711667 DOI: 10.15252/embj.2023114054] [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: 03/19/2023] [Revised: 10/16/2023] [Accepted: 10/18/2023] [Indexed: 11/08/2023] Open
Abstract
Cristae are high-curvature structures in the inner mitochondrial membrane (IMM) that are crucial for ATP production. While cristae-shaping proteins have been defined, analogous lipid-based mechanisms have yet to be elucidated. Here, we combine experimental lipidome dissection with multi-scale modeling to investigate how lipid interactions dictate IMM morphology and ATP generation. When modulating phospholipid (PL) saturation in engineered yeast strains, we observed a surprisingly abrupt breakpoint in IMM topology driven by a continuous loss of ATP synthase organization at cristae ridges. We found that cardiolipin (CL) specifically buffers the inner mitochondrial membrane against curvature loss, an effect that is independent of ATP synthase dimerization. To explain this interaction, we developed a continuum model for cristae tubule formation that integrates both lipid and protein-mediated curvatures. This model highlighted a snapthrough instability, which drives IMM collapse upon small changes in membrane properties. We also showed that cardiolipin is essential in low-oxygen conditions that promote PL saturation. These results demonstrate that the mechanical function of cardiolipin is dependent on the surrounding lipid and protein components of the IMM.
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Affiliation(s)
- Kailash Venkatraman
- Department of Chemistry and BiochemistryUniversity of California San DiegoLa JollaCAUSA
| | - Christopher T Lee
- Department of Mechanical and Aerospace EngineeringUniversity of California San DiegoLa JollaCAUSA
| | - Guadalupe C Garcia
- Computational Neurobiology LaboratorySalk Institute for Biological StudiesLa JollaCAUSA
| | - Arijit Mahapatra
- Department of Mechanical and Aerospace EngineeringUniversity of California San DiegoLa JollaCAUSA
- Present address:
Applied Physical SciencesUniversity of North Carolina Chapel HillChapel HillNCUSA
| | - Daniel Milshteyn
- Department of Chemistry and BiochemistryUniversity of California San DiegoLa JollaCAUSA
| | - Guy Perkins
- National Center for Microscopy and Imaging Research, Center for Research in Biological SystemsUniversity of California San DiegoLa JollaCAUSA
| | - Keun‐Young Kim
- National Center for Microscopy and Imaging Research, Center for Research in Biological SystemsUniversity of California San DiegoLa JollaCAUSA
| | - H Amalia Pasolli
- Howard Hughes Medical InstituteAshburnVAUSA
- Present address:
Electron Microscopy Resource CenterThe Rockefeller UniversityNew YorkNYUSA
| | - Sebastien Phan
- National Center for Microscopy and Imaging Research, Center for Research in Biological SystemsUniversity of California San DiegoLa JollaCAUSA
| | | | - Mark H Ellisman
- National Center for Microscopy and Imaging Research, Center for Research in Biological SystemsUniversity of California San DiegoLa JollaCAUSA
| | - Padmini Rangamani
- Department of Mechanical and Aerospace EngineeringUniversity of California San DiegoLa JollaCAUSA
| | - Itay Budin
- Department of Chemistry and BiochemistryUniversity of California San DiegoLa JollaCAUSA
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32
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Ballabio F, Paissoni C, Bollati M, de Rosa M, Capelli R, Camilloni C. Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations. J Chem Theory Comput 2023; 19:8401-8413. [PMID: 37923304 PMCID: PMC10687869 DOI: 10.1021/acs.jctc.3c00864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/11/2023] [Accepted: 10/24/2023] [Indexed: 11/07/2023]
Abstract
Small-angle X-ray and neutron scattering (SAXS/SANS) provide valuable insights into the structure and dynamics of biomolecules in solution, complementing a wide range of structural techniques, including molecular dynamics simulations. As contrast-based methods, they are sensitive not only to structural properties but also to solvent-solute interactions. Their use in molecular dynamics simulations requires a forward model that should be as fast and accurate as possible. In this work, we demonstrate the feasibility of calculating SAXS and SANS intensities using a coarse-grained representation consisting of one bead per amino acid and three beads per nucleic acid, with form factors that can be corrected on the fly to account for solvation effects at no additional computational cost. By coupling this forward model with molecular dynamics simulations restrained with SAS data, it is possible to determine conformational ensembles or refine the structure and dynamics of proteins and nucleic acids in agreement with the experimental results. To assess the robustness of this approach, we applied it to gelsolin, for which we acquired SAXS data on its closed state, and to a UP1-microRNA complex, for which we used previously collected measurements. Our hybrid-resolution small-angle scattering (hySAS) implementation, being distributed in PLUMED, can be used with atomistic and coarse-grained simulations using diverse restraining strategies.
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Affiliation(s)
- Federico Ballabio
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
| | - Cristina Paissoni
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
| | - Michela Bollati
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
- Istituto
di Biofisica, Consiglio Nazionale delle
Ricerche (IBF-CNR), via
Alfonso Corti 12, 20133 Milano, Italy
| | - Matteo de Rosa
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
- Istituto
di Biofisica, Consiglio Nazionale delle
Ricerche (IBF-CNR), via
Alfonso Corti 12, 20133 Milano, Italy
| | - Riccardo Capelli
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
| | - Carlo Camilloni
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
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33
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Jones MS, Shmilovich K, Ferguson AL. DiAMoNDBack: Diffusion-Denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces. J Chem Theory Comput 2023; 19:7908-7923. [PMID: 37906711 DOI: 10.1021/acs.jctc.3c00840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Coarse-grained molecular models of proteins permit access to length and time scales unattainable by all-atom models and the simulation of processes that occur on long time scales, such as aggregation and folding. The reduced resolution realizes computational accelerations, but an atomistic representation can be vital for a complete understanding of mechanistic details. Backmapping is the process of restoring all-atom resolution to coarse-grained molecular models. In this work, we report DiAMoNDBack (Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping) as an autoregressive denoising diffusion probability model to restore all-atom details to coarse-grained protein representations retaining only Cα coordinates. The autoregressive generation process proceeds from the protein N-terminus to C-terminus in a residue-by-residue fashion conditioned on the Cα trace and previously backmapped backbone and side-chain atoms within the local neighborhood. The local and autoregressive nature of our model makes it transferable between proteins. The stochastic nature of the denoising diffusion process means that the model generates a realistic ensemble of backbone and side-chain all-atom configurations consistent with the coarse-grained Cα trace. We train DiAMoNDBack over 65k+ structures from the Protein Data Bank (PDB) and validate it in applications to a hold-out PDB test set, intrinsically disordered protein structures from the Protein Ensemble Database (PED), molecular dynamics simulations of fast-folding mini-proteins from DE Shaw Research, and coarse-grained simulation data. We achieve state-of-the-art reconstruction performance in terms of correct bond formation, avoidance of side-chain clashes, and the diversity of the generated side-chain configurational states. We make the DiAMoNDBack model publicly available as a free and open-source Python package.
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Affiliation(s)
- Michael S Jones
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
| | - Kirill Shmilovich
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
| | - Andrew L Ferguson
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
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34
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Navarro C, Majewski M, De Fabritiis G. Top-Down Machine Learning of Coarse-Grained Protein Force Fields. J Chem Theory Comput 2023; 19:7518-7526. [PMID: 37874270 PMCID: PMC10777392 DOI: 10.1021/acs.jctc.3c00638] [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: 06/13/2023] [Indexed: 10/25/2023]
Abstract
Developing accurate and efficient coarse-grained representations of proteins is crucial for understanding their folding, function, and interactions over extended time scales. Our methodology involves simulating proteins with molecular dynamics and utilizing the resulting trajectories to train a neural network potential through differentiable trajectory reweighting. Remarkably, this method requires only the native conformation of proteins, eliminating the need for labeled data derived from extensive simulations or memory-intensive end-to-end differentiable simulations. Once trained, the model can be employed to run parallel molecular dynamics simulations and sample folding events for proteins both within and beyond the training distribution, showcasing its extrapolation capabilities. By applying Markov state models, native-like conformations of the simulated proteins can be predicted from the coarse-grained simulations. Owing to its theoretical transferability and ability to use solely experimental static structures as training data, we anticipate that this approach will prove advantageous for developing new protein force fields and further advancing the study of protein dynamics, folding, and interactions.
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Affiliation(s)
- Carles Navarro
- Acellera
Labs, Doctor Trueta 183, 08005 Barcelona, Spain
| | | | - Gianni De Fabritiis
- Computational
Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003 Barcelona, Spain
- Acellera
Ltd., Devonshire House
582, Middlesex HA7 1JS, United Kingdom
- Institució
Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010 Barcelona, Spain
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35
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Gu Y, Li Y, Ma B, Ren K, Cao C, Gu N. Probing Conformational Transition of TRPV5 Induced by Mechanical Force Using Coarse-Grained Molecular Dynamics. J Chem Inf Model 2023; 63:6768-6777. [PMID: 37871325 DOI: 10.1021/acs.jcim.3c00614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Transient receptor potential vanilloid 5 (TRPV5) is a calcium-selective TRP channel that plays a crucial role in calcium homeostasis regulation. However, there are still many issues that need to be addressed, such as the specific conformational transition of TRPV5 and the specific functions of each structure in cation gating. Here, we build a model of the calcium ion transport protein from Xenopus oocytes in the presence of the lipid membrane and water molecules. Due to the activation process of ion channels are global and collective, coarse-grained molecular dynamics (CG-MD) simulations of the potential of mean force along the conformational transition pathway are performed. The CG-MD simulations show that the S6 helix plays a vital role in the TRPV5 conformational transition. Most importantly, these simulated trajectories indicate that the activation of ion channels happens before the extension and rotation of S6 helices, revealing that TRPV5 has a unique gating mechanism different from TRPV6. The present work demonstrates how the mechanical force acting on the S6 helix opens the TRPV5 channel gates. These results deepen our understanding of the TRPV5 gating mechanism.
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Affiliation(s)
- Yinwei Gu
- State Key Laboratory of Bioelectronics, Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
| | - Yan Li
- State Key Laboratory of Bioelectronics, Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
| | - Baocai Ma
- State Key Laboratory of Bioelectronics, Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
| | - Ke Ren
- Department of Orthopaedics, Zhongda Hospital, Southeast University, Nanjing 210009, China
| | - Chen Cao
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
| | - Ning Gu
- State Key Laboratory of Bioelectronics, Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
- Medical School, Nanjing University, Nanjing 210093, China
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36
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Tu CK, Mou W, Shen ZL. Computer simulation of the structural properties of fatty-acid modified PAMAM dendrimers at pH 5 and 7. J Mol Graph Model 2023; 124:108570. [PMID: 37487373 DOI: 10.1016/j.jmgm.2023.108570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 07/19/2023] [Accepted: 07/19/2023] [Indexed: 07/26/2023]
Abstract
In this work, we performed coarse-grained molecular dynamics (CGMD) simulations of G3, G4, and G5 polyamidoamine (PAMAM) dendrimers grafting with fatty acid (FTA) chains. The FTA chains of varying length and grafting densities (50% and 100% of surface terminals) correspond to pH 7 and 5, respectively. Our findings suggested that the structural properties of dendrimers were determined by dendrimer generation, polymerization degrees, and pH. With one exception, the size of the FTA grafting dendrimer shrank after fatty acid attachment. Because of the protonation of the dendrimer's interior amines at low pH, the FTA chains are distributed at the dendrimer's surface group. At pH 7, the FTA chains that have aggregated in the interior of the dendrimer cause chain crowding. Our research provided references on drug encapsulation and the lower toxicity of these hydrophobically modified nanoparticles.
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Affiliation(s)
- Chen-Kun Tu
- Kangda College, Nanjing Medical University, Lianyungang, China.
| | - Wei Mou
- Kangda College, Nanjing Medical University, Lianyungang, China
| | - Zhuang-Lin Shen
- Shenzhen Key Laboratory of Environmental Chemistry and Ecological Remediation, College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, China.
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Saini R, Debnath A. Thylakoid Composition Facilitates Chlorophyll a Dimerization through Stronger Interlipid Interactions. J Phys Chem B 2023; 127:9082-9094. [PMID: 37819861 DOI: 10.1021/acs.jpcb.3c04942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
Plant thylakoid membrane serves as a crucial matrix for the aggregation of chlororophyll a (CLA) pigments, essential for light harvesting. To understand the role of lipid compositions in the stability of CLA aggregates, dimerization of chlorophyll a molecules (CLA) is studied in the presence of the thylakoid and the bilayers comprising either the least or the highest unsaturated lipids by using coarse-grained molecular dynamics simulations. The thylakoid membrane enhances the stability of the CLA dimer compared with other membranes due to very strong lipid-lipid interactions. The thylakoid exhibits a distinct distribution of lipids around the CLA dimer. Less unsaturated lipids reside in close proximity to the dimer, promoting increased order and efficient packing. Conversely, higher unsaturated lipids are depleted from the dimer, imparting flexibility to the membrane. The combination of tight packing near the dimer and membrane flexibility away from the dimer enhances the stability of the dimer in the thylakoid membrane. Our results suggest that lipid mixing, rather than lipid unsaturation, plays a critical role in facilitating CLA dimerization by modulating the membrane microenvironment through stronger lipid-lipid interactions. These insights will be useful in understanding how lipid compositions affect efficient light absorption and energy transfer during photosynthesis in the future.
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Affiliation(s)
- Renu Saini
- Department of Chemistry, Indian Institute of Technology, Jodhpur, Rajasthan 342030, India
| | - Ananya Debnath
- Department of Chemistry, Indian Institute of Technology, Jodhpur, Rajasthan 342030, India
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38
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Bernardi A, Bennett WFD, He S, Jones D, Kirshner D, Bennion BJ, Carpenter TS. Advances in Computational Approaches for Estimating Passive Permeability in Drug Discovery. MEMBRANES 2023; 13:851. [PMID: 37999336 PMCID: PMC10673305 DOI: 10.3390/membranes13110851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 10/19/2023] [Accepted: 10/21/2023] [Indexed: 11/25/2023]
Abstract
Passive permeation of cellular membranes is a key feature of many therapeutics. The relevance of passive permeability spans all biological systems as they all employ biomembranes for compartmentalization. A variety of computational techniques are currently utilized and under active development to facilitate the characterization of passive permeability. These methods include lipophilicity relations, molecular dynamics simulations, and machine learning, which vary in accuracy, complexity, and computational cost. This review briefly introduces the underlying theories, such as the prominent inhomogeneous solubility diffusion model, and covers a number of recent applications. Various machine-learning applications, which have demonstrated good potential for high-volume, data-driven permeability predictions, are also discussed. Due to the confluence of novel computational methods and next-generation exascale computers, we anticipate an exciting future for computationally driven permeability predictions.
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Affiliation(s)
| | | | | | | | | | | | - Timothy S. Carpenter
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA; (A.B.); (W.F.D.B.); (S.H.); (D.J.); (D.K.); (B.J.B.)
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39
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Nguyen D, Wu J, Corrigan P, Li Y. Computational investigation on lipid bilayer disruption induced by amphiphilic Janus nanoparticles: combined effect of Janus balance and charged lipid concentration. NANOSCALE 2023; 15:16112-16130. [PMID: 37753922 DOI: 10.1039/d3nr00403a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
Janus nanoparticles (NPs) with charged/hydrophobic compartments have garnered attention for their potential antimicrobial activity. These NPs have been shown to disrupt lipid bilayers in experimental studies, yet the underlying mechanisms of this disruption at the particle-membrane interface remain unclear. To address this knowledge gap, the present study conducts a computational investigation to systematically examine the disruption of lipid bilayers induced by amphiphilic Janus NPs. The focus of this study is on the combined effects of the hydrophobicity of the Janus NP, referred to as the Janus balance, defined as the ratio of hydrophilic to hydrophobic surface coverage, and the concentration of charged phospholipids on the interactions between Janus NPs and lipid bilayers. Computational simulations were conducted using a coarse-grained molecular dynamics (MD) approach. The results of these MD simulations reveal that while the area change of the bilayer increases monotonically with the Janus balance, the effect of charged lipid concentration in the membrane is not easy to be predicted. Specifically, it was found that the concentration of negatively charged lipids is directly proportional to the intensity of membrane disruption. Conversely, positively charged lipids have a negligible effect on membrane defects. This study provides molecular insights into the significant role of Janus balance in the disruption of lipid bilayers by Janus NPs and supports the selectivity of Janus NPs for negatively charged lipid membranes. Furthermore, the anisotropic properties of Janus NPs were found to play a crucial role in their ability to disrupt the membrane via the combination of hydrophobic and electrostatic interactions. This finding is validated by testing the current Janus NP design on a bacterial membrane-mimicking model. This computational study may serve as a foundation for further studies aimed at optimizing the properties of Janus NPs for specific antimicrobial applications.
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Affiliation(s)
- Danh Nguyen
- Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
| | - James Wu
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Patrick Corrigan
- Department of Chemistry, University of Connecticut, Storrs, CT 06269, USA
| | - Ying Li
- Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
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40
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Ivanov M, Posysoev M, Lyubartsev AP. Coarse-Grained Modeling Using Neural Networks Trained on Structural Data. J Chem Theory Comput 2023; 19:6704-6717. [PMID: 37712507 PMCID: PMC10569054 DOI: 10.1021/acs.jctc.3c00516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Indexed: 09/16/2023]
Abstract
We propose a method of bottom-up coarse-graining, in which interactions within a coarse-grained model are determined by an artificial neural network trained on structural data obtained from multiple atomistic simulations. The method uses ideas of the inverse Monte Carlo approach, relating changes in the neural network weights with changes in average structural properties, such as radial distribution functions. As a proof of concept, we demonstrate the method on a system interacting by a Lennard-Jones potential modeled by a simple linear network and a single-site coarse-grained model of methanol-water solutions. In the latter case, we implement a nonlinear neural network with intermediate layers trained by atomistic simulations carried out at different methanol concentrations. We show that such a network acts as a transferable potential at the coarse-grained resolution for a wide range of methanol concentrations, including those not included in the training set.
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Affiliation(s)
- Mikhail Ivanov
- Department of Materials and
Environmental Chemistry, Stockholm University, SE-106 91 Stockholm, Sweden
| | - Maksim Posysoev
- Department of Materials and
Environmental Chemistry, Stockholm University, SE-106 91 Stockholm, Sweden
| | - Alexander P. Lyubartsev
- Department of Materials and
Environmental Chemistry, Stockholm University, SE-106 91 Stockholm, Sweden
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41
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Lavagna E, Salassi S, Bochicchio D, Rossi G. Dumbbells, chains, and ribbons: anisotropic self-assembly of isotropic nanoparticles. NANOSCALE 2023; 15:15153-15160. [PMID: 37671876 PMCID: PMC10540935 DOI: 10.1039/d3nr02384b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 08/16/2023] [Indexed: 09/07/2023]
Abstract
Functionalizing the surface of metal nanoparticles can assure their stability in solution or mediate their self-assembly into aggregates with controlled shapes. Here we present a computational study of the colloidal aggregation of gold nanoparticles (Au NPs) isotropically functionalized by a mixture of charged and hydrophobic ligands. We show that, by varying the relative proportion of the two ligands, the NPs form anisotropic aggregates with markedly different topologies: dumbbells, chains, or ribbons. In all cases, two kinds of connections keep the aggregates together: hydrophobic bonds and ion bridges. We show that the anisotropy of the aggregates derives from the NP shell reshaping due to the formation of the hydrophobic links, while ion bridges are accountable for the "secondary structure" of the aggregates. Our findings provide a general physical principle that can also be exploited in different self-assembled systems: anisotropic/directional aggregation can be achieved starting from isotropic objects with a soft, deformable surface.
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Affiliation(s)
- Enrico Lavagna
- Physics Department, University of Genoa, Via Dodecaneso 33, 16146 Genoa, Italy.
| | - Sebastian Salassi
- Physics Department, University of Genoa, Via Dodecaneso 33, 16146 Genoa, Italy.
| | - Davide Bochicchio
- Physics Department, University of Genoa, Via Dodecaneso 33, 16146 Genoa, Italy.
| | - Giulia Rossi
- Physics Department, University of Genoa, Via Dodecaneso 33, 16146 Genoa, Italy.
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42
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Aceves-Luna H, Glossman-Mitnik D, Flores-Holguín N. Permeability of antioxidants through a lipid bilayer model with coarse-grained simulations. J Biomol Struct Dyn 2023:1-19. [PMID: 37768552 DOI: 10.1080/07391102.2023.2262044] [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: 06/30/2023] [Accepted: 09/13/2023] [Indexed: 09/29/2023]
Abstract
Oxidative stress caused by pollution and lifestyle changes causes an excess of free radicals that react chemically with cell constituents leading to irreversible damage. There are molecules known as antioxidants that reduce the levels of free radicals. Some pigments of fruits and vegetables known as anthocyanins have antioxidant properties. Their interaction with the cell membrane becomes a crucial step in studying these substances. In this research, molecular dynamics simulations, particularly, coarse-grained molecular dynamics (CGMD) were used. This technique aims to replace functional groups with corresponding beads that represent their level of polarity and affinities to other chemical groups. Also, umbrella sampling was carried out to obtain free energy profiles that describe well the orientation and location of antioxidants in a membrane considering Trolox, Cyanidin, Gallic Acid, and Resveratrol molecules to study the structural effects they cause on it. It was concluded in this study that an antioxidant when crossing the membrane does not cause either damage to the structural properties or the loss of packing and stratification of phospholipids. it was also observed that the most reactive part of the molecules could easily approach area A prone to lipid oxidation, which can describe the antioxidant capacity of these molecules.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Hugo Aceves-Luna
- Laboratorio Virtual NANOCOSMOS, Departamento de Medio Ambiente y Energía, Centro de Investigación en Materiales Avanzados, Chihuahua, Chih, Mexico
| | - Daniel Glossman-Mitnik
- Laboratorio Virtual NANOCOSMOS, Departamento de Medio Ambiente y Energía, Centro de Investigación en Materiales Avanzados, Chihuahua, Chih, Mexico
| | - Norma Flores-Holguín
- Laboratorio Virtual NANOCOSMOS, Departamento de Medio Ambiente y Energía, Centro de Investigación en Materiales Avanzados, Chihuahua, Chih, Mexico
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43
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Majewski M, Pérez A, Thölke P, Doerr S, Charron NE, Giorgino T, Husic BE, Clementi C, Noé F, De Fabritiis G. Machine learning coarse-grained potentials of protein thermodynamics. Nat Commun 2023; 14:5739. [PMID: 37714883 PMCID: PMC10504246 DOI: 10.1038/s41467-023-41343-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/29/2023] [Indexed: 09/17/2023] Open
Abstract
A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach this problem by constructing coarse-grained molecular potentials based on artificial neural networks and grounded in statistical mechanics. For training, we build a unique dataset of unbiased all-atom molecular dynamics simulations of approximately 9 ms for twelve different proteins with multiple secondary structure arrangements. The coarse-grained models are capable of accelerating the dynamics by more than three orders of magnitude while preserving the thermodynamics of the systems. Coarse-grained simulations identify relevant structural states in the ensemble with comparable energetics to the all-atom systems. Furthermore, we show that a single coarse-grained potential can integrate all twelve proteins and can capture experimental structural features of mutated proteins. These results indicate that machine learning coarse-grained potentials could provide a feasible approach to simulate and understand protein dynamics.
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Affiliation(s)
- Maciej Majewski
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003, Barcelona, Spain
- Acellera Labs, Doctor Trueta 183, 08005, Barcelona, Spain
| | - Adrià Pérez
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003, Barcelona, Spain
- Acellera Labs, Doctor Trueta 183, 08005, Barcelona, Spain
| | - Philipp Thölke
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003, Barcelona, Spain
| | - Stefan Doerr
- Acellera Labs, Doctor Trueta 183, 08005, Barcelona, Spain
| | - Nicholas E Charron
- Department of Physics, Rice University, Houston, TX, 77005, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, 77005, USA
- Department of Physics, FU Berlin, Arnimallee 12, 14195, Berlin, Germany
| | - Toni Giorgino
- Biophysics Institute, National Research Council (CNR-IBF), 20133, Milan, Italy
| | - Brooke E Husic
- Department of Mathematics and Computer Science, FU Berlin, Arnimallee 12, 14195, Berlin, Germany
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, 08540, USA
- Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, 08540, USA
- Center for the Physics of Biological Function, Princeton University, Princeton, NJ, 08540, USA
| | - Cecilia Clementi
- Department of Physics, Rice University, Houston, TX, 77005, USA.
- Center for Theoretical Biological Physics, Rice University, Houston, TX, 77005, USA.
- Department of Physics, FU Berlin, Arnimallee 12, 14195, Berlin, Germany.
- Department of Chemistry, Rice University, Houston, TX, 77005, USA.
| | - Frank Noé
- Department of Physics, FU Berlin, Arnimallee 12, 14195, Berlin, Germany.
- Department of Mathematics and Computer Science, FU Berlin, Arnimallee 12, 14195, Berlin, Germany.
- Department of Chemistry, Rice University, Houston, TX, 77005, USA.
- Microsoft Research AI4Science, Karl-Liebknecht Str. 32, 10178, Berlin, Germany.
| | - Gianni De Fabritiis
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003, Barcelona, Spain.
- Acellera Labs, Doctor Trueta 183, 08005, Barcelona, Spain.
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010, Barcelona, Spain.
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44
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Livraghi M, Pahi S, Nowakowski P, Smith DM, Wick CR, Smith AS. Block Chemistry for Accurate Modeling of Epoxy Resins. J Phys Chem B 2023; 127:7648-7662. [PMID: 37616478 PMCID: PMC10493980 DOI: 10.1021/acs.jpcb.3c04724] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 07/26/2023] [Indexed: 08/26/2023]
Abstract
Accurate molecular modeling of the physical and chemical behavior of highly cross-linked epoxy resins at the atomistic scale is important for the design of new property-optimized materials. However, a systematic approach to parametrizing and characterizing these systems in molecular dynamics is missing. We therefore present a unified scheme to derive atomic charges for amine-based epoxy resins, in agreement with the AMBER force field, based on defining reactive fragments─blocks─building the network. The approach is applicable to all stages of curing from pure liquid to gelation to fully cured glass. We utilize this approach to study DGEBA/DDS epoxy systems, incorporating dynamic topology changes into atomistic molecular dynamics simulations of the curing reaction with 127,000 atoms. We study size effects in our simulations and predict the gel point utilizing a rigorous percolation theory to recover accurately the experimental data. Furthermore, we observe excellent agreement between the estimated and the experimentally determined glass transition temperatures as a function of curing rate. Finally, we demonstrate the quality of our model by the prediction of the elastic modulus based on uniaxial tensile tests. The presented scheme paves the way for a broadly consistent approach for modeling and characterizing all amine-based epoxy resins.
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Affiliation(s)
- Mattia Livraghi
- Friedrich-Alexander-Universität
Erlangen-Nürnberg (FAU), Institute for Theoretical Physics,
PULS Group, Interdisciplinary Center for Nanostructured Films (IZNF), Cauerstrasse 3, Erlangen 91058, Germany
| | - Sampanna Pahi
- Friedrich-Alexander-Universität
Erlangen-Nürnberg (FAU), Institute for Theoretical Physics,
PULS Group, Interdisciplinary Center for Nanostructured Films (IZNF), Cauerstrasse 3, Erlangen 91058, Germany
| | - Piotr Nowakowski
- Group
for Computational Life Sciences, Division of Physical Chemistry, Ruđer Bošković Institute, Bijenička cesta 54, Zagreb 10000, Croatia
| | - David M. Smith
- Group
for Computational Life Sciences, Division of Physical Chemistry, Ruđer Bošković Institute, Bijenička cesta 54, Zagreb 10000, Croatia
| | - Christian R. Wick
- Friedrich-Alexander-Universität
Erlangen-Nürnberg (FAU), Institute for Theoretical Physics,
PULS Group, Interdisciplinary Center for Nanostructured Films (IZNF), Cauerstrasse 3, Erlangen 91058, Germany
| | - Ana-Sunčana Smith
- Friedrich-Alexander-Universität
Erlangen-Nürnberg (FAU), Institute for Theoretical Physics,
PULS Group, Interdisciplinary Center for Nanostructured Films (IZNF), Cauerstrasse 3, Erlangen 91058, Germany
- Group
for Computational Life Sciences, Division of Physical Chemistry, Ruđer Bošković Institute, Bijenička cesta 54, Zagreb 10000, Croatia
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45
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Venkatraman K, Lee CT, Garcia GC, Mahapatra A, Milshteyn D, Perkins G, Kim KY, Pasolli HA, Phan S, Lippincott-Schwartz J, Ellisman MH, Rangamani P, Budin I. Cristae formation is a mechanical buckling event controlled by the inner membrane lipidome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.13.532310. [PMID: 36993370 PMCID: PMC10054968 DOI: 10.1101/2023.03.13.532310] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Cristae are high curvature structures in the inner mitochondrial membrane (IMM) that are crucial for ATP production. While cristae-shaping proteins have been defined, analogous mechanisms for lipids have yet to be elucidated. Here we combine experimental lipidome dissection with multi-scale modeling to investigate how lipid interactions dictate IMM morphology and ATP generation. When modulating phospholipid (PL) saturation in engineered yeast strains, we observed a surprisingly abrupt breakpoint in IMM topology driven by a continuous loss of ATP synthase organization at cristae ridges. We found that cardiolipin (CL) specifically buffers the IMM against curvature loss, an effect that is independent of ATP synthase dimerization. To explain this interaction, we developed a continuum model for cristae tubule formation that integrates both lipid and protein-mediated curvatures. The model highlighted a snapthrough instability, which drives IMM collapse upon small changes in membrane properties. We also showed that CL is essential in low oxygen conditions that promote PL saturation. These results demonstrate that the mechanical function of CL is dependent on the surrounding lipid and protein components of the IMM.
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Affiliation(s)
- Kailash Venkatraman
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093
| | - Christopher T Lee
- Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA 92093
| | - Guadalupe C Garcia
- Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla CA 92097
| | - Arijit Mahapatra
- Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA 92093
| | - Daniel Milshteyn
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093
| | - Guy Perkins
- National Center for Microscopy and Imaging Research, Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093
| | - Keun-Young Kim
- National Center for Microscopy and Imaging Research, Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093
| | - H Amalia Pasolli
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn VA 20147
| | - Sebastien Phan
- National Center for Microscopy and Imaging Research, Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093
| | | | - Mark H Ellisman
- National Center for Microscopy and Imaging Research, Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093
| | - Padmini Rangamani
- Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA 92093
| | - Itay Budin
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093
- Lead contact
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46
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Shao H, Zhou J, Lin X, Zhou Y, Xue Y, Hong W, Lin X, Jia X, Fan Y. Bio-inspired peptide-conjugated liposomes for enhanced planktonic bacteria killing and biofilm eradication. Biomaterials 2023; 300:122183. [PMID: 37302278 DOI: 10.1016/j.biomaterials.2023.122183] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 05/15/2023] [Accepted: 05/29/2023] [Indexed: 06/13/2023]
Abstract
Developing new antimicrobial agents has become an urgent task to address the increasing prevalence of multidrug-resistant pathogens and the emergence of biofilms. Cationic antimicrobial peptides (AMPs) have been regarded as promising candidates due to their unique non-specific membrane rupture mechanism. However, a series of problems with the peptides hindered their practical application due to their high toxicity and low bioactivity and stability. Here, inspired by broadening the application of cell-penetrating peptides (CPPs), we selected five different sequences of cationic peptides which are considered as both CPPs and AMPs, and developed a biomimetic strategy to construct cationic peptide-conjugated liposomes with the virus-like structure for both enhancements of antibacterial efficacy and biosafety. The correlation between available peptide density/peptide variety and antimicrobial capabilities was evaluated from quantitative perspectives. Computational simulation and experimental investigations assisted to identify the optimal peptide-conjugated liposomes and revealed that the designed system provides high charge density for enhanced anionic bacterial membrane binding capability without compromised cytotoxicity, being capable of enhanced antibacterial efficacy of bacteria/biofilm of clinically important pathogens. The bio-inspired design has shown enhanced therapeutic efficiency of peptides and may promote the development of next-generation antimicrobials.
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Affiliation(s)
- Hui Shao
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China
| | - Jin Zhou
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China.
| | - Xiaoqian Lin
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China
| | - Yue Zhou
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China
| | - Yumeng Xue
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China
| | - Weili Hong
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China
| | - Xubo Lin
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China
| | - Xiaoling Jia
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China.
| | - Yubo Fan
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, And with the School of Engineering Medicine, Beihang University, Beijing, 100083, China.
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47
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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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Dandekar BR, Majumdar BB, Mondal J. Nonmonotonic Modulation of the Protein-Ligand Recognition Event by Inert Crowders. J Phys Chem B 2023; 127:7449-7461. [PMID: 37590118 DOI: 10.1021/acs.jpcb.3c03946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
The ubiquitous event of a protein recognizing small molecules or ligands at its native binding site is crucial for initiating major biological processes. However, how a crowded environment, as is typically represented by a cellular interior, would modulate the protein-ligand search process is largely debated. Excluded volume-based theory suggests that the presence of an inert crowder would reinforce a steady stabilization and enhancement of the protein-ligand recognition process. Here, we counter this long-held perspective via the molecular dynamics simulation and Markov state model of the protein-ligand recognition event in the presence of inert crowders. Specifically, we demonstrate that, depending on concentration, even purely inert crowders can exert a nonmonotonic effect via either stabilizing or destabilizing the protein-ligand binding event. Analysis of the kinetic network of binding pathways reveals that the crowders would either modulate precedent non-native on-pathway intermediates or would devise additional ones in a multistate recognition event across a wide range of concentrations. As an important insight, crowders gradually shift the relative transitional preference of these intermediates toward a native-bound state, with ligand residence time at the binding pocket dictating the trend of nonmonotonic concentration dependence by simple inert crowders.
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Weiand E, Rodriguez-Ropero F, Roiter Y, Koenig PH, Angioletti-Uberti S, Dini D, Ewen JP. Effects of surfactant adsorption on the wettability and friction of biomimetic surfaces. Phys Chem Chem Phys 2023; 25:21916-21934. [PMID: 37581271 DOI: 10.1039/d3cp02546b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
The properties of solid-liquid interfaces can be markedly altered by surfactant adsorption. Here, we use molecular dynamics (MD) simulations to study the adsorption of ionic surfactants at the interface between water and heterogeneous solid surfaces with randomly arranged hydrophilic and hydrophobic regions, which mimic the surface properties of human hair. We use the coarse-grained MARTINI model to describe both the hair surfaces and surfactant solutions. We consider negatively-charged virgin and bleached hair surface models with different grafting densities of neutral octadecyl and anionic sulfonate groups. The adsorption of cationic cetrimonium bromide (CTAB) and anionic sodium dodecyl sulfate (SDS) surfactants from water are studied above the critical micelle concentration. The simulated adsorption isotherms suggest that cationic surfactants adsorb to the surfaces via a two-stage process, initially forming monolayers and then bilayers at high concentrations, which is consistent with previous experiments. Anionic surfactants weakly adsorb via hydrophobic interactions, forming only monolayers on both virgin and medium bleached hair surfaces. We also conduct non-equilibrium molecular dynamics simulations, which show that applying cationic surfactant solutions to bleached hair successfully restores the low friction seen with virgin hair. Friction is controlled by the combined surface coverage of the grafted lipids and the adsorbed CTAB molecules. Treated surfaces containing monolayers and bilayers both show similar friction, since the latter are easily removed by compression and shear. Further wetting MD simulations show that bleached hair treated with CTAB increases the hydrophobicity to similar levels seen for virgin hair. Treated surfaces containing CTAB monolayers with the tailgroups pointing predominantly away from the surface are more hydrophobic than bilayers due to the electrostatic interactions between water molecules and the exposed cationic headgroups.
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Affiliation(s)
- Erik Weiand
- Department of Mechanical Engineering, Imperial College London, South Kensington Campus, SW7 2AZ London, UK.
- Institute of Molecular Science and Engineering, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
- Thomas Young Centre for the Theory and Simulation of Materials, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
| | - Francisco Rodriguez-Ropero
- Corporate Functions Analytical and Data & Modeling Sciences, Mason Business Center, The Procter and Gamble Company, Mason, 45040 Ohio, USA
| | - Yuri Roiter
- Corporate Functions Analytical and Data & Modeling Sciences, Mason Business Center, The Procter and Gamble Company, Mason, 45040 Ohio, USA
| | - Peter H Koenig
- Corporate Functions Analytical and Data & Modeling Sciences, Mason Business Center, The Procter and Gamble Company, Mason, 45040 Ohio, USA
| | - Stefano Angioletti-Uberti
- Institute of Molecular Science and Engineering, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
- Thomas Young Centre for the Theory and Simulation of Materials, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
- Department of Materials, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
| | - Daniele Dini
- Department of Mechanical Engineering, Imperial College London, South Kensington Campus, SW7 2AZ London, UK.
- Institute of Molecular Science and Engineering, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
- Thomas Young Centre for the Theory and Simulation of Materials, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
| | - James P Ewen
- Department of Mechanical Engineering, Imperial College London, South Kensington Campus, SW7 2AZ London, UK.
- Institute of Molecular Science and Engineering, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
- Thomas Young Centre for the Theory and Simulation of Materials, Imperial College London, South Kensington Campus, SW7 2AZ London, UK
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Das T, Mukhopadhyay C. Comparison and Possible Binding Orientations of SARS-CoV-2 Spike N-Terminal Domain for Gangliosides GM3 and GM1. J Phys Chem B 2023; 127:6940-6948. [PMID: 37523476 DOI: 10.1021/acs.jpcb.3c02286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/02/2023]
Abstract
SARS-CoV-2 spike glycoprotein is anchored by gangliosides. The sialic acid in the ganglioside headgroup is responsible for virus attachment and entry into host cells. We used coarse-grained (CG) molecular dynamics simulations to expand on our previous study of GM1 interaction with two different orientations of the SARS-CoV-2 S1 subunit N-terminal domain (NTD) and to confirm the role of sialic acid receptors in driving the viral receptor; GM3 was used as another ganglioside on the membrane. Because of the smaller headgroup, sialic acid is crucial in GM3 interactions, whereas GM1 interacts with NTD via both the sialic acid and external galactose. In line with our previous findings for NTD orientations in GM1 binding, we identified two orientations, "compact" and "distributed", comprising sugar receptor-interacting residues in GM3-embedded lipid bilayers. Gangliosides in closer proximity to the compact NTD orientation might cause relatively greater restrictions to penetrate the bilayer. However, the attachment of a distributed NTD orientation with more negative interaction energies appears to facilitate GM1/GM3 to move quickly across the membrane. Our findings likely shed some light on the orientations that the NTD receptor acquires during the early phases of interaction with GM1 and GM3 in a membrane environment.
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Affiliation(s)
- Tanushree Das
- Department of Chemistry, University of Calcutta, 92, A.P.C. Road, Kolkata 700009, India
| | - Chaitali Mukhopadhyay
- Department of Chemistry, University of Calcutta, 92, A.P.C. Road, Kolkata 700009, India
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