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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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2
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Miotto M, Milanetti E, Mincigrucci R, Masciovecchio C, Ruocco G. High-Throughput Interactome Determination via Sulfur Anomalous Scattering. J Phys Chem Lett 2024; 15:3478-3485. [PMID: 38513124 PMCID: PMC11000237 DOI: 10.1021/acs.jpclett.3c03632] [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: 12/29/2023] [Revised: 02/16/2024] [Accepted: 02/22/2024] [Indexed: 03/23/2024]
Abstract
We propose a novel approach for detecting the binding between proteins making use of the anomalous diffraction of natively present heavy elements, e.g., sulfurs, inside molecular three-dimensional structures. In particular, we analytically and numerically show that the diffraction patterns produced by the anomalous scattering of the sulfur atoms in a given direction depend additively on the relative distances between all couples of sulfur atoms. Thus, the differences in the patterns produced by bound proteins with respect to their nonbonded states can be exploited to rapidly assess protein complex formation. On the basis of our results, we suggest a possible experimental procedure for detecting protein-protein binding. Overall, the completely label-free and rapid method we propose may be readily extended to probe interactions on a large scale, thus paving the way for the development of a novel field of research based on a synchrotron light source.
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Affiliation(s)
- Mattia Miotto
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy
| | - Edoardo Milanetti
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy
- Department
of Physics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Riccardo Mincigrucci
- Elettra-Sincrotrone
Trieste S.C.p.A. di interesse nazionale, Strada Statale 14 - km 163.5 in AREA Science Park,
Basovizza, 34149 Trieste, Italy
| | - Claudio Masciovecchio
- Elettra-Sincrotrone
Trieste S.C.p.A. di interesse nazionale, Strada Statale 14 - km 163.5 in AREA Science Park,
Basovizza, 34149 Trieste, Italy
| | - Giancarlo Ruocco
- Center
for Life Nano & Neuro Science, Istituto
Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy
- Department
of Physics, Sapienza University, Piazzale Aldo Moro 5, 00185 Rome, Italy
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3
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Botnari M, Tchertanov L. Synergy of Mutation-Induced Effects in Human Vitamin K Epoxide Reductase: Perspectives and Challenges for Allo-Network Modulator Design. Int J Mol Sci 2024; 25:2043. [PMID: 38396721 PMCID: PMC10889538 DOI: 10.3390/ijms25042043] [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: 01/19/2024] [Revised: 02/03/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
The human Vitamin K Epoxide Reductase Complex (hVKORC1), a key enzyme transforming vitamin K into the form necessary for blood clotting, requires for its activation the reducing equivalents delivered by its redox partner through thiol-disulfide exchange reactions. The luminal loop (L-loop) is the principal mediator of hVKORC1 activation, and it is a region frequently harbouring numerous missense mutations. Four L-loop hVKORC1 mutants, suggested in vitro as either resistant (A41S, H68Y) or completely inactive (S52W, W59R), were studied in the oxidised state by numerical approaches (in silico). The DYNASOME and POCKETOME of each mutant were characterised and compared to the native protein, recently described as a modular protein composed of the structurally stable transmembrane domain (TMD) and the intrinsically disordered L-loop, exhibiting quasi-independent dynamics. The DYNASOME of mutants revealed that L-loop missense point mutations impact not only its folding and dynamics, but also those of the TMD, highlighting a strong mutation-specific interdependence between these domains. Another consequence of the mutation-induced effects manifests in the global changes (geometric, topological, and probabilistic) of the newly detected cryptic pockets and the alternation of the recognition properties of the L-loop with its redox protein. Based on our results, we postulate that (i) intra-protein allosteric regulation and (ii) the inherent allosteric regulation and cryptic pockets of each mutant depend on its DYNASOME; and (iii) the recognition of the redox protein by hVKORC1 (INTERACTOME) depend on their DYNASOME. This multifaceted description of proteins produces "omics" data sets, crucial for understanding the physiological processes of proteins and the pathologies caused by alteration of the protein properties at various "omics" levels. Additionally, such characterisation opens novel perspectives for the development of "allo-network drugs" essential for the treatment of blood disorders.
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Affiliation(s)
| | - Luba Tchertanov
- Centre Borelli, École Normale Supérieure (ENS) Paris-Saclay, Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, 4 Avenue des Sciences, F-91190 Gif-sur-Yvette, France;
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4
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Gardner AM, Gardner PR. Dioxygen and glucose force motion of the electron-transfer switch in the iron(III) flavohemoglobin-type nitric oxide dioxygenase. J Inorg Biochem 2023; 245:112257. [PMID: 37229820 DOI: 10.1016/j.jinorgbio.2023.112257] [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: 12/18/2022] [Revised: 04/28/2023] [Accepted: 05/11/2023] [Indexed: 05/27/2023]
Abstract
Kinetic and structural investigations of the flavohemoglobin-type NO dioxygenase have suggested critical roles for transient Fe(III)O2 complex formation and O2-forced movements affecting hydride transfer to the FAD cofactor and electron-transfer to the Fe(III)O2 complex. Stark-effect theory together with structural models and dipole and internal electrostatic field determinations provided a semi-quantitative spectroscopic method for investigating the proposed Fe(III)O2 complex and O2-forced movements. Deoxygenation of the enzyme causes Stark effects on the ferric heme Soret and charge-transfer bands revealing the Fe(III)O2 complex. Deoxygenation also elicits Stark effects on the FAD that expose forces and motions that create a more restricted NADH access to FAD for hydride transfer and switch electron-transfer off. Glucose also forces the enzyme toward an off state. Amino acid substitutions at the B10, E7, E11, G8, D5, and F7 positions influence the Stark effects of O2 on resting heme spin states and FAD consistent with the proposed roles of the side chains in the enzyme mechanism. Deoxygenation of ferric myoglobin and hemoglobin A also induces Stark effects on the hemes suggesting a common 'oxy-met' state. The ferric myoglobin and hemoglobin heme spectra are also glucose-responsive. A conserved glucose or glucose-6-phosphate binding site is found bridging the BC-corner and G-helix in flavohemoglobin and myoglobin suggesting novel allosteric effector roles for glucose or glucose-6-phosphate in the NO dioxygenase and O2 storage functions. The results support the proposed roles of a ferric O2 intermediate and protein motions in regulating electron-transfer during NO dioxygenase turnover.
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Affiliation(s)
- Anne M Gardner
- Research and Development Division, Miami Valley Biotech, Suite 2445, 1001 E. 2(nd) Street, Dayton, OH 45402, USA; Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, R033, 3333 Burnet Avenue, Cincinnati, OH 45229, USA.
| | - Paul R Gardner
- Research and Development Division, Miami Valley Biotech, Suite 2445, 1001 E. 2(nd) Street, Dayton, OH 45402, USA; Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, R033, 3333 Burnet Avenue, Cincinnati, OH 45229, USA; Chemistry and Biochemistry Department, University of Dayton, 300 College Park, Dayton, OH 45469, USA.
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5
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Artificial intelligence-based HDX (AI-HDX) prediction reveals fundamental characteristics to protein dynamics: Mechanisms on SARS-CoV-2 immune escape. iScience 2023; 26:106282. [PMID: 36910327 PMCID: PMC9968663 DOI: 10.1016/j.isci.2023.106282] [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: 10/20/2022] [Revised: 01/10/2023] [Accepted: 02/23/2023] [Indexed: 03/03/2023] Open
Abstract
Three-dimensional structure and dynamics are essential for protein function. Advancements in hydrogen-deuterium exchange (HDX) techniques enable probing protein dynamic information in physiologically relevant conditions. HDX-coupled mass spectrometry (HDX-MS) has been broadly applied in pharmaceutical industries. However, it is challenging to obtain dynamics information at the single amino acid resolution and time consuming to perform the experiments and process the data. Here, we demonstrate the first deep learning model, artificial intelligence-based HDX (AI-HDX), that predicts intrinsic protein dynamics based on the protein sequence. It uncovers the protein structural dynamics by combining deep learning, experimental HDX, sequence alignment, and protein structure prediction. AI-HDX can be broadly applied to drug discovery, protein engineering, and biomedical studies. As a demonstration, we elucidated receptor-binding domain structural dynamics as a potential mechanism of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody efficacy and immune escape. AI-HDX fundamentally differs from the current AI tools for protein analysis and may transform protein design for various applications.
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6
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Sykes J, Holland BR, Charleston MA. A review of visualisations of protein fold networks and their relationship with sequence and function. Biol Rev Camb Philos Soc 2023; 98:243-262. [PMID: 36210328 PMCID: PMC10092621 DOI: 10.1111/brv.12905] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 09/08/2022] [Accepted: 09/09/2022] [Indexed: 01/12/2023]
Abstract
Proteins form arguably the most significant link between genotype and phenotype. Understanding the relationship between protein sequence and structure, and applying this knowledge to predict function, is difficult. One way to investigate these relationships is by considering the space of protein folds and how one might move from fold to fold through similarity, or potential evolutionary relationships. The many individual characterisations of fold space presented in the literature can tell us a lot about how well the current Protein Data Bank represents protein fold space, how convergence and divergence may affect protein evolution, how proteins affect the whole of which they are part, and how proteins themselves function. A synthesis of these different approaches and viewpoints seems the most likely way to further our knowledge of protein structure evolution and thus, facilitate improved protein structure design and prediction.
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Affiliation(s)
- Janan Sykes
- School of Natural Sciences, University of Tasmania, Private Bag 37, Hobart, Tasmania, 7001, Australia
| | - Barbara R Holland
- School of Natural Sciences, University of Tasmania, Private Bag 37, Hobart, Tasmania, 7001, Australia
| | - Michael A Charleston
- School of Natural Sciences, University of Tasmania, Private Bag 37, Hobart, Tasmania, 7001, Australia
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7
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Ulbrich P, Waldner M, Furmanova K, Marques SM, Bednar D, Kozlikova B, Byska J. sMolBoxes: Dataflow Model for Molecular Dynamics Exploration. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2023; 29:581-590. [PMID: 36155456 DOI: 10.1109/tvcg.2022.3209411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
We present sMolBoxes, a dataflow representation for the exploration and analysis of long molecular dynamics (MD) simulations. When MD simulations reach millions of snapshots, a frame-by-frame observation is not feasible anymore. Thus, biochemists rely to a large extent only on quantitative analysis of geometric and physico-chemical properties. However, the usage of abstract methods to study inherently spatial data hinders the exploration and poses a considerable workload. sMolBoxes link quantitative analysis of a user-defined set of properties with interactive 3D visualizations. They enable visual explanations of molecular behaviors, which lead to an efficient discovery of biochemically significant parts of the MD simulation. sMolBoxes follow a node-based model for flexible definition, combination, and immediate evaluation of properties to be investigated. Progressive analytics enable fluid switching between multiple properties, which facilitates hypothesis generation. Each sMolBox provides quick insight to an observed property or function, available in more detail in the bigBox View. The case studies illustrate that even with relatively few sMolBoxes, it is possible to express complex analytical tasks, and their use in exploratory analysis is perceived as more efficient than traditional scripting-based methods.
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8
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Mondal A, Paul D, Dastidar SG, Saha T, Goswami AM. In silico analyses of Wnt1 nsSNPs reveal structurally destabilizing variants, altered interactions with Frizzled receptors and its deregulation in tumorigenesis. Sci Rep 2022; 12:14934. [PMID: 36056132 PMCID: PMC9440047 DOI: 10.1038/s41598-022-19299-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 08/26/2022] [Indexed: 11/26/2022] Open
Abstract
Wnt1 is the first mammalian Wnt gene, which is discovered as proto-oncogene and in human the gene is located on the chromosome 12q13. Mutations in Wnt1 are reported to be associated with various cancers and other human diseases. The structural and functional consequences of most of the non-synonymous SNPs (nsSNPs), present in the human Wnt1 gene, are not known. In the present work, extensive bioinformatics analyses are used to screen 292 nsSNPs of Wnt1 for predicting pathogenic and harmless polymorphisms. We have identified 10 highly deleterious nsSNPs among which 7 are located within the highly conserved areas. These 10 nsSNPs are also predicted to affect the post-translational modifications of Wnt1. Further, structure based stability analyses of these 10 highly deleterious nsSNPs revealed 8 variants as highly destabilizing. These 8 highly destabilizing variants were shown to have high BC score and high RMSIP score from normal mode analyses. Based on the deformation energies, obtained from the normal mode analyses, variants like G169A, G169S, G331R and G331S were found to be unstable. Molecular Dynamics (MD) simulations revealed structural stability and fluctuation of WT Wnt1 and its prioritized variants. RMSD remained fluctuating mostly between 4 and 5 Å and occasionally between 3.5 and 5.5 Å ranges. RMSF in the CTD region (residues 330-360) of the binding pocket were lower compared to that of WT. Studying the impacts of nsSNPs on the binding interface of Wnt1 and seven Frizzled receptors have predicted substitutions which can stabilize or destabilize the binding interface. We have found that Wnt1 and FZD8-CRD is the best docked complex in our study. MD simulation based analyses of wild type Wnt1-FZD8-CRD complex and the 8 prioritized variants revealed that RMSF was higher in the unstructured regions and RMSD remained fluctuating in the region of 5 Å ± 1 Å. We have also observed differential Wnt1 gene expression pattern in normal, tumor and metastatic conditions across different tissues. Wnt1 gene expression was significantly higher in metastatic tissues of lungs, colon and skin; and was significantly lower in metastatic tissues of breast, esophagus and kidney. We have also found that Wnt1 deregulation is associated with survival outcome in patients with gastric and breast cancer. Furthermore, these computationally screened highly deleterious nsSNPs of Wnt1 can be analyzed in population based genetic studies and may help understand the Wnt1 associated diseases.
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Affiliation(s)
- Amalesh Mondal
- Department of Physiology, Katwa College, Purba Bardhaman, Katwa, West Bengal, 713130, India
- Department of Molecular Biology and Biotechnology, University of Kalyani, Nadia, Kalyani, India
| | - Debarati Paul
- Division of Bioinformatics, Bose Institute, P-1/12 CIT Scheme VII M, Kolkata, 700054, India
| | - Shubhra Ghosh Dastidar
- Division of Bioinformatics, Bose Institute, P-1/12 CIT Scheme VII M, Kolkata, 700054, India
| | - Tanima Saha
- Department of Molecular Biology and Biotechnology, University of Kalyani, Nadia, Kalyani, India.
| | - Achintya Mohan Goswami
- Department of Physiology, Krishnagar Govt. College, Nadia, Krishnagar, West Bengal, 741101, India.
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9
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Bai F, Puk KM, Liu J, Zhou H, Tao P, Zhou W, Wang S. Sparse group selection and analysis of function-related residue for protein-state recognition. J Comput Chem 2022; 43:1342-1354. [PMID: 35656889 PMCID: PMC9248267 DOI: 10.1002/jcc.26937] [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: 11/05/2021] [Revised: 03/23/2022] [Accepted: 05/08/2022] [Indexed: 11/08/2022]
Abstract
Machine learning methods have helped to advance wide range of scientific and technological field in recent years, including computational chemistry. As the chemical systems could become complex with high dimension, feature selection could be critical but challenging to develop reliable machine learning based prediction models, especially for proteins as bio-macromolecules. In this study, we applied sparse group lasso (SGL) method as a general feature selection method to develop classification model for an allosteric protein in different functional states. This results into a much improved model with comparable accuracy (Acc) and only 28 selected features comparing to 289 selected features from a previous study. The Acc achieves 91.50% with 1936 selected feature, which is far higher than that of baseline methods. In addition, grouping protein amino acids into secondary structures provides additional interpretability of the selected features. The selected features are verified as associated with key allosteric residues through comparison with both experimental and computational works about the model protein, and demonstrate the effectiveness and necessity of applying rigorous feature selection and evaluation methods on complex chemical systems.
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Affiliation(s)
- Fangyun Bai
- Department of Management Science and Engineering, Tongji University. Fangyun Bai and Kin Ming Puk contributed equally to this work
| | | | - Jin Liu
- Department of Pharmaceutical Sciences, University of North Texas System College of Pharmacy, University of North Texas Health Science Center
| | - Hongyu Zhou
- Department of Chemistry, Center for Scientific Computation, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University
| | - Peng Tao
- Department of Chemistry, Center for Scientific Computation, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University
| | - Wenyong Zhou
- Department of Management Science and Engineering, Tongji University
| | - Shouyi Wang
- Corresponding author: Shouyi Wang, Department of Industrial, Manufacturing and Systems Engineering, University of Texas at Arlington.
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10
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In Search of a Dynamical Vocabulary: A Pipeline to Construct a Basis of Shared Traits in Large-Scale Motions of Proteins. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12147157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The paradigmatic sequence–structure–dynamics–function relation in proteins is currently well established in the scientific community; in particular, a large effort has been made to probe the first connection, indeed providing convincing evidence of its strength and rationalizing it in a quantitative and general framework. In contrast, however, the role of dynamics as a link between structure and function has eluded a similarly clear-cut verification and description. In this work, we propose a pipeline aimed at building a basis for the quantitative characterization of the large-scale dynamics of a set of proteins, starting from the sole knowledge of their native structures. The method hinges on a dynamics-based clusterization, which allows a straightforward comparison with structural and functional protein classifications. The resulting basis set, obtained through the application to a group of related proteins, is shown to reproduce the salient large-scale dynamical features of the dataset. Most interestingly, the basis set is shown to encode the fluctuation patterns of homologous proteins not belonging to the initial dataset, thus highlighting the general applicability of the pipeline used to build it.
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11
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Wieczór M, Genna V, Aranda J, Badia RM, Gelpí JL, Gapsys V, de Groot BL, Lindahl E, Municoy M, Hospital A, Orozco M. Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case. WILEY INTERDISCIPLINARY REVIEWS. COMPUTATIONAL MOLECULAR SCIENCE 2022; 13:e1622. [PMID: 35935573 PMCID: PMC9347456 DOI: 10.1002/wcms.1622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 04/25/2022] [Accepted: 04/28/2022] [Indexed: 06/15/2023]
Abstract
Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.
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Affiliation(s)
- Miłosz Wieczór
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
- Department of Physical ChemistryGdansk University of TechnologyGdańskPoland
| | - Vito Genna
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Juan Aranda
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | | | - Josep Lluís Gelpí
- Barcelona Supercomputing CenterBarcelonaSpain
- Department of Biochemistry and BiomedicineUniversity of BarcelonaBarcelonaSpain
| | - Vytautas Gapsys
- Max Planck Institute for Multidisciplinary SciencesComputational Biomolecular Dynamics GroupGoettingenGermany
| | - Bert L. de Groot
- Max Planck Institute for Multidisciplinary SciencesComputational Biomolecular Dynamics GroupGoettingenGermany
| | - Erik Lindahl
- Department of Applied PhysicsSwedish e‐Science Research Center, KTH Royal Institute of TechnologyStockholmSweden
- Department of Biochemistry and Biophysics, Science for Life LaboratoryStockholm UniversityStockholmSweden
| | | | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
- Department of Biochemistry and BiomedicineUniversity of BarcelonaBarcelonaSpain
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12
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Volkhardt A, Grubmüller H. Estimating ruggedness of free-energy landscapes of small globular proteins from principal component analysis of molecular dynamics trajectories. Phys Rev E 2022; 105:044404. [PMID: 35590540 DOI: 10.1103/physreve.105.044404] [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: 08/18/2021] [Accepted: 02/28/2022] [Indexed: 06/15/2023]
Abstract
The internal dynamics of biomolecules, and hence their function, is governed by the structure of their free-energy landscape. Early flash-photolysis experiments on myoglobin suggested that the free-energy landscapes of proteins are hierarchically structured, with a characteristic distribution of free-energy barriers which gives rise to anomalous diffusion. Analytical results have been derived for one-dimensional or high-dimensional hierarchical free-energy landscapes. Recent improvements in methods and computer performance enable generating sufficiently long molecular dynamics (MD) trajectories to extract dynamics information covering many orders of magnitude, such that the broad distributions of energy barriers of proteins become accessible to quantitative studies of intermediate dimensions. In this work, we present a nonequilibrium method to estimate barrier height distributions from microsecond-long MD simulations. It infers barrier height distributions from anomalous diffusion exponents derived from principal component analysis and by comparison to simple hierarchical lattice models. These models are d-dimensional lattices of states separated by free-energy barriers, the heights of which are distributed as p(ΔG)=1/γexp(-ΔG/γ). The parameter γ quantifies the "ruggedness" of the free-energy landscape in such models. We show that both parameters, i.e., ruggedness and effective dimensionality d, can be inferred from anomalous diffusion exponents. Assuming a similar dependency of anomalous diffusion exponents on γ and d for proteins, we estimate the ruggedness of the free-energy landscapes of 500 small, single-domain globular proteins between 15 and 20 kT per dimension with an estimated accuracy of 4.2 kT and dimensionality between 40 and 60 with an estimated accuracy of 10 dimensions. Remarkably, neither effective dimensionality nor the ruggedness correlates with protein size and both ruggedness and effective dimensionality are much smaller than the scatter of protein sizes. From this finding, we conclude that these two properties of the free-energy landscape of a protein are rather adapted to the particular function of each single protein and that, quite generally, are functionally relevant for globular proteins.
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Affiliation(s)
- Andreas Volkhardt
- Max Planck Institute for Multidisciplinary Sciences, Theoretical and Computational Biophysics Department, Am Fassberg 11, 37077 Göttingen, Germany
| | - Helmut Grubmüller
- Max Planck Institute for Multidisciplinary Sciences, Theoretical and Computational Biophysics Department, Am Fassberg 11, 37077 Göttingen, Germany
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13
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Karaca E, Prévost C, Sacquin-Mora S. Modeling the Dynamics of Protein-Protein Interfaces, How and Why? Molecules 2022; 27:1841. [PMID: 35335203 PMCID: PMC8950966 DOI: 10.3390/molecules27061841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 03/06/2022] [Accepted: 03/08/2022] [Indexed: 12/07/2022] Open
Abstract
Protein-protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein-protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein-protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein-protein interface.
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Affiliation(s)
- Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir 35340, Turkey;
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir 35340, Turkey
| | - Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
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14
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Trozzi F, Wang X, Tao P. UMAP as a Dimensionality Reduction Tool for Molecular Dynamics Simulations of Biomacromolecules: A Comparison Study. J Phys Chem B 2021; 125:5022-5034. [PMID: 33973773 PMCID: PMC8356557 DOI: 10.1021/acs.jpcb.1c02081] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Proteins are the molecular machines of life. The multitude of possible conformations that proteins can adopt determines their free-energy landscapes. However, the inherently high dimensionality of a protein free-energy landscape poses a challenge to deciphering how proteins perform their functions. For this reason, dimensionality reduction is an active field of research for molecular biologists. The uniform manifold approximation and projection (UMAP) is a dimensionality reduction method based on a fuzzy topological analysis of data. In the present study, the performance of UMAP is compared with that of other popular dimensionality reduction methods such as t-distributed stochastic neighbor embedding (t-SNE), principal component analysis (PCA), and time-structure independent components analysis (tICA) in the context of analyzing molecular dynamics simulations of the circadian clock protein VIVID. A good dimensionality reduction method should accurately represent the data structure on the projected components. The comparison of the raw high-dimensional data with the projections obtained using different dimensionality reduction methods based on various metrics showed that UMAP has superior performance when compared with linear reduction methods (PCA and tICA) and has competitive performance and scalable computational cost.
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Affiliation(s)
- Francesco Trozzi
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, 75275, United States of America
| | - Xinlei Wang
- Department of Statistical Science, Southern Methodist University, Dallas, Texas, 75275, United States of America
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, 75275, United States of America
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15
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Di Rienzo L, Miotto M, Bò L, Ruocco G, Raimondo D, Milanetti E. Characterizing Hydropathy of Amino Acid Side Chain in a Protein Environment by Investigating the Structural Changes of Water Molecules Network. Front Mol Biosci 2021; 8:626837. [PMID: 33718433 PMCID: PMC7954116 DOI: 10.3389/fmolb.2021.626837] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 01/04/2021] [Indexed: 12/14/2022] Open
Abstract
Assessing the hydropathy properties of molecules, like proteins and chemical compounds, has a crucial role in many fields of computational biology, such as drug design, biomolecular interaction, and folding prediction. Over the past decades, many descriptors were devised to evaluate the hydrophobicity of side chains. In this field, recently we likewise have developed a computational method, based on molecular dynamics data, for the investigation of the hydrophilicity and hydrophobicity features of the 20 natural amino acids, analyzing the changes occurring in the hydrogen bond network of water molecules surrounding each given compound. The local environment of each residue is complex and depends on the chemical nature of the side chain and the location in the protein. Here, we characterize the solvation properties of each amino acid side chain in the protein environment by considering its spatial reorganization in the protein local structure, so that the computational evaluation of differences in terms of hydropathy profiles in different structural and dynamical conditions can be brought to bear. A set of atomistic molecular dynamics simulations have been used to characterize the dynamic hydrogen bond network at the interface between protein and solvent, from which we map out the local hydrophobicity and hydrophilicity of amino acid residues.
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Affiliation(s)
- Lorenzo Di Rienzo
- Center for Life Nanoscience, Istituto Italiano di Tecnologia, Rome, Italy
| | - Mattia Miotto
- Center for Life Nanoscience, Istituto Italiano di Tecnologia, Rome, Italy.,Department of Physics, Sapienza University, Rome, Italy
| | - Leonardo Bò
- Center for Life Nanoscience, Istituto Italiano di Tecnologia, Rome, Italy
| | - Giancarlo Ruocco
- Center for Life Nanoscience, Istituto Italiano di Tecnologia, Rome, Italy.,Department of Physics, Sapienza University, Rome, Italy
| | | | - Edoardo Milanetti
- Center for Life Nanoscience, Istituto Italiano di Tecnologia, Rome, Italy.,Department of Physics, Sapienza University, Rome, Italy
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16
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Yang L, Jiao X. Distinguishing Enzymes and Non-enzymes Based on Structural Information with an Alignment Free Approach. Curr Bioinform 2021. [DOI: 10.2174/1574893615666200324134037] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
Knowledge of protein functions is very crucial for the understanding of biological processes. Experimental methods for protein function prediction are powerless to treat the growing amount of protein sequence and structure data.
Objective:
To develop some computational techniques for the protein function prediction.
Method:
Based on the residue interaction network features and the motion mode information, an
SVM model was constructed and used as the predictor. The role of these features was analyzed
and some interesting results were obtained.
Results:
An alignment-free method for the classification of enzyme and non-enzyme is developed in this work. There is not any single feature that occupies a dominant position in the prediction process. The topological and the information-theoretic residue interaction network features have a better performance. The combination of the fast mode and the slow mode can get a better explanation for the classification result.
Conclusion:
The method proposed in this paper can act as a classifier for the enzymes and nonenzymes.
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Affiliation(s)
- Lifeng Yang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, 030600,China
| | - Xiong Jiao
- College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan, 030600,China
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17
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Giulini M, Menichetti R, Shell MS, Potestio R. An Information-Theory-Based Approach for Optimal Model Reduction of Biomolecules. J Chem Theory Comput 2020; 16:6795-6813. [PMID: 33108737 PMCID: PMC7659038 DOI: 10.1021/acs.jctc.0c00676] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Indexed: 02/06/2023]
Abstract
In theoretical modeling of a physical system, a crucial step consists of the identification of those degrees of freedom that enable a synthetic yet informative representation of it. While in some cases this selection can be carried out on the basis of intuition and experience, straightforward discrimination of the important features from the negligible ones is difficult for many complex systems, most notably heteropolymers and large biomolecules. We here present a thermodynamics-based theoretical framework to gauge the effectiveness of a given simplified representation by measuring its information content. We employ this method to identify those reduced descriptions of proteins, in terms of a subset of their atoms, that retain the largest amount of information from the original model; we show that these highly informative representations share common features that are intrinsically related to the biological properties of the proteins under examination, thereby establishing a bridge between protein structure, energetics, and function.
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Affiliation(s)
- Marco Giulini
- Physics
Department, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, I-38123 Trento, Italy
| | - Roberto Menichetti
- Physics
Department, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, I-38123 Trento, Italy
| | - M. Scott Shell
- Department
of Chemical Engineering, University of California
Santa Barbara, Santa
Barbara, California 93106, United States
| | - Raffaello Potestio
- Physics
Department, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, I-38123 Trento, Italy
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18
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Nagel D, Weber A, Stock G. MSMPathfinder: Identification of Pathways in Markov State Models. J Chem Theory Comput 2020; 16:7874-7882. [PMID: 33141565 DOI: 10.1021/acs.jctc.0c00774] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Markov state models represent a popular means to interpret biomolecular processes in terms of memoryless transitions between metastable conformational states. To gain insight into the underlying mechanism, it is instructive to determine all relevant pathways between initial and final states of the process. Currently available methods, such as Markov chain Monte Carlo and transition path theory, are convenient for identifying the most frequented pathways. They are less suited to account for the typically huge amount of pathways with low probability which, though, may dominate the cumulative flux of the reaction. On the basis of a systematic construction of all possible pathways, the here proposed method MSMPathfinder is able to characterize the multitude of unique pathways (say, up to 1010) in a complex system and to quantitatively calculate their correct weights and associated waiting times with predefined accuracy. Adopting the chiral transitions of a peptide helix and the folding of the villin headpiece as model problems, mechanisms and associated waiting times of these processes are discussed using a kinetic network representation. The analysis reveals that the waiting time distribution may yield only little insight into the diversity of pathways, because the measured folding times do typically not reflect the most probable path lengths but rather the cumulative effect of many different pathways.
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Affiliation(s)
- Daniel Nagel
- Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University, 79104 Freiburg, Germany
| | - Anna Weber
- Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University, 79104 Freiburg, Germany
| | - Gerhard Stock
- Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University, 79104 Freiburg, Germany
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19
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20
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Paul S, Ainavarapu SRK, Venkatramani R. Variance of Atomic Coordinates as a Dynamical Metric to Distinguish Proteins and Protein-Protein Interactions in Molecular Dynamics Simulations. J Phys Chem B 2020; 124:4247-4262. [PMID: 32281802 DOI: 10.1021/acs.jpcb.0c01191] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Protein dynamics is a manifestation of the complex trajectories of these biomolecules on a multidimensional rugged potential energy surface (PES) driven by thermal energy. At present, computational methods such as atomistic molecular dynamics (MD) simulations can describe thermal protein conformational changes in fully solvated environments over millisecond timescales. Despite these advances, a quantitative assessment of protein dynamics remains a complicated topic, intricately linked to issues such as sampling convergence and the identification of appropriate reaction coordinates/structural features to describe protein conformational states and motions. Here, we present the cumulative variance of atomic coordinate fluctuations (CVCF) along trajectories as an intuitive PES sensitive metric to assess both the extent of sampling and protein dynamics captured in MD simulations. We first examine the sampling problem in model one- (1D) and two-dimensional (2D) PES to demonstrate that the CVCF when traced as a function of the sampling variable (time in MD simulations) can identify local and global equilibria. Further, even far from global equilibrium, a situation representative of standard MD trajectories of proteins, the CVCF can distinguish different PES and therefore resolve the resultant protein dynamics. We demonstrate the utility of our CVCF analysis by applying it to distinguish the dynamics of structurally homologous proteins from the ubiquitin family (ubiquitin, SUMO1, SUMO2) and ubiquitin protein-protein interactions. Our CVCF analysis reveals that differential side-chain dynamics from the structured part of the protein (the conserved β-grasp fold) present distinct protein PES to distinguish ubiquitin from SUMO isoforms. Upon binding to two functionally distinct protein partners (UBCH5A and UEV), intrinsic ubiquitin dynamics changes to reflect the binding context even though the two proteins have similar binding modes, which lead to negligible (sub-angstrom scale) structural changes.
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Affiliation(s)
- Sanjoy Paul
- Department of Chemical Sciences, Tata Institute of Fundamental Research, Dr. Homi Bhabha Road, Colaba, Mumbai 400005, Maharashtra, India
| | - Sri Rama Koti Ainavarapu
- Department of Chemical Sciences, Tata Institute of Fundamental Research, Dr. Homi Bhabha Road, Colaba, Mumbai 400005, Maharashtra, India
| | - Ravindra Venkatramani
- Department of Chemical Sciences, Tata Institute of Fundamental Research, Dr. Homi Bhabha Road, Colaba, Mumbai 400005, Maharashtra, India
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21
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Aharoni R, Tobi D. Dynamical comparison between Drosha and Dicer reveals functional motion similarities and dissimilarities. PLoS One 2019; 14:e0226147. [PMID: 31821368 PMCID: PMC6903759 DOI: 10.1371/journal.pone.0226147] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 11/20/2019] [Indexed: 12/01/2022] Open
Abstract
Drosha and Dicer are RNase III family members of classes II and III, respectively, which play a major role in the maturation of micro-RNAs. The two proteins share similar domain arrangement and overall fold despite no apparent sequence homology. The overall structural and catalytic reaction similarity of both proteins, on the one hand, and differences in the substrate and its binding mechanisms, on the other, suggest that both proteins also share dynamic similarities and dissimilarities. Since dynamics is essential for protein function, a comparison at their dynamics level is fundamental for a complete understanding of the overall relations between these proteins. In this study, we present a dynamical comparison between human Drosha and Giardia Dicer. Gaussian Network Model and Anisotropic Network Model modes of motion of the proteins are calculated. Dynamical comparison is performed using global and local dynamic programming algorithms for aligning modes of motion. These algorithms were recently developed based on the commonly used Needleman-Wunsch and Smith-Waterman algorithms for global and local sequence alignment. The slowest mode of Drosha is different from that of Dicer due to its more bended posture and allow the motion of the double-stranded RNA-binding domain toward and away from its substrate. Among the five slowest modes dynamics similarity exists only for the second slow mode of motion of Drosha and Dicer. In addition, high local dynamics similarity is observed at the catalytic domains, in the vicinity of the catalytic residues. The results suggest that the proteins exert a similar catalytic mechanism using similar motions, especially at the catalytic sites.
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Affiliation(s)
- Rotem Aharoni
- Department of Molecular Biology, Ariel University, Ariel, Israel
| | - Dror Tobi
- Department of Molecular Biology, Ariel University, Ariel, Israel
- Department of Computer Sciences, Ariel University, Ariel, Israel
- * E-mail:
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22
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Galano-Frutos JJ, García-Cebollada H, Sancho J. Molecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when. Brief Bioinform 2019; 22:3-19. [PMID: 31813950 DOI: 10.1093/bib/bbz146] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 09/22/2019] [Accepted: 10/25/2019] [Indexed: 12/18/2022] Open
Abstract
The increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical-chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80-85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore's law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.
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Affiliation(s)
- Juan J Galano-Frutos
- Protein Folding and Molecular Design (ProtMol)' group at BIFI, University of Zaragoza
| | | | - Javier Sancho
- Protein Folding and Molecular Design (ProtMol)' group at BIFI, University of Zaragoza
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23
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Damry AM, Mayer MM, Broom A, Goto NK, Chica RA. Origin of conformational dynamics in a globular protein. Commun Biol 2019; 2:433. [PMID: 31799435 PMCID: PMC6879633 DOI: 10.1038/s42003-019-0681-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Accepted: 11/06/2019] [Indexed: 11/28/2022] Open
Abstract
Protein structures are dynamic, undergoing motions that can play a vital role in function. However, the link between primary sequence and conformational dynamics remains poorly understood. Here, we studied how conformational dynamics can arise in a globular protein by evaluating the impact of individual core-residue substitutions in DANCER-3, a streptococcal protein G domain β1 variant that we previously designed to undergo a specific mode of conformational exchange that has never been observed in the wild-type protein. Using a combination of solution NMR experiments and molecular dynamics simulations, we demonstrate that only two mutations are necessary to create this conformational exchange, and that these mutations work synergistically, with one destabilizing the native structure and the other allowing two new conformational states to be accessed on the energy landscape. Overall, our results show how dynamics can appear in a stable globular fold, a critical step in the molecular evolution of dynamics-linked functions.
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Affiliation(s)
- Adam M. Damry
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie-Curie, Ottawa, ON Canada K1N 6N5
| | - Marc M. Mayer
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie-Curie, Ottawa, ON Canada K1N 6N5
| | - Aron Broom
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie-Curie, Ottawa, ON Canada K1N 6N5
| | - Natalie K. Goto
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie-Curie, Ottawa, ON Canada K1N 6N5
| | - Roberto A. Chica
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie-Curie, Ottawa, ON Canada K1N 6N5
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24
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Hospital A, Battistini F, Soliva R, Gelpí JL, Orozco M. Surviving the deluge of biosimulation data. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2019. [DOI: 10.1002/wcms.1449] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Adam Hospital
- Institut de Recerca Biomèdica, IRB Barcelona, The Barcelona Institute of Science and Technology Joint IRB‐BSC Program in Computational Biology Barcelona Spain
| | - Federica Battistini
- Institut de Recerca Biomèdica, IRB Barcelona, The Barcelona Institute of Science and Technology Joint IRB‐BSC Program in Computational Biology Barcelona Spain
| | | | - Josep Lluis Gelpí
- Barcelona Supercomputing Center Join IRB‐BSC Program in Computational Biology Barcelona Spain
- Departament de Bioquímica i Biomedicina Universitat de Barcelona Barcelona Spain
| | - Modesto Orozco
- Institut de Recerca Biomèdica, IRB Barcelona, The Barcelona Institute of Science and Technology Joint IRB‐BSC Program in Computational Biology Barcelona Spain
- Departament de Bioquímica i Biomedicina Universitat de Barcelona Barcelona Spain
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25
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Narwani TJ, Craveur P, Shinada NK, Floch A, Santuz H, Vattekatte AM, Srinivasan N, Rebehmed J, Gelly JC, Etchebest C, de Brevern AG. Discrete analyses of protein dynamics. J Biomol Struct Dyn 2019; 38:2988-3002. [PMID: 31361191 DOI: 10.1080/07391102.2019.1650112] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Protein structures are highly dynamic macromolecules. This dynamics is often analysed through experimental and/or computational methods only for an isolated or a limited number of proteins. Here, we explore large-scale protein dynamics simulation to observe dynamics of local protein conformations using different perspectives. We analysed molecular dynamics to investigate protein flexibility locally, using classical approaches such as RMSf, solvent accessibility, but also innovative approaches such as local entropy. First, we focussed on classical secondary structures and analysed specifically how β-strand, β-turns, and bends evolve during molecular simulations. We underlined interesting specific bias between β-turns and bends, which are considered as the same category, while their dynamics show differences. Second, we used a structural alphabet that is able to approximate every part of the protein structures conformations, namely protein blocks (PBs) to analyse (i) how each initial local protein conformations evolve during dynamics and (ii) if some exchange can exist among these PBs. Interestingly, the results are largely complex than simple regular/rigid and coil/flexible exchange. AbbreviationsNeqnumber of equivalentPBProtein BlocksPDBProtein DataBankRMSfroot mean square fluctuationsCommunicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Tarun Jairaj Narwani
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Pierrick Craveur
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
| | - Nicolas K Shinada
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Discngine, SAS, Paris, France
| | - Aline Floch
- Laboratoire D'Excellence GR-Ex, Paris, France.,Etablissement Français du Sang Ile de France, Créteil, France.,IMRB - INSERM U955 Team 2 « Transfusion et Maladies du Globule Rouge », Paris Est- Créteil Univ, Créteil, France.,UPEC, Université Paris Est-Créteil, Créteil, France
| | - Hubert Santuz
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Akhila Melarkode Vattekatte
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Faculté Des Sciences et Technologies, Saint Denis Messag, La Réunion, France
| | | | - Joseph Rebehmed
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Department of Computer Science and Mathematics, Lebanese American University, Byblos, Lebanon
| | - Jean-Christophe Gelly
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Faculté Des Sciences et Technologies, Saint Denis Messag, La Réunion, France.,IBL, Paris, France
| | - Catherine Etchebest
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Faculté Des Sciences et Technologies, Saint Denis Messag, La Réunion, France
| | - Alexandre G de Brevern
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Faculté Des Sciences et Technologies, Saint Denis Messag, La Réunion, France.,IBL, Paris, France
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26
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Diggins P, Liu C, Deserno M, Potestio R. Optimal Coarse-Grained Site Selection in Elastic Network Models of Biomolecules. J Chem Theory Comput 2018; 15:648-664. [PMID: 30514085 PMCID: PMC6391041 DOI: 10.1021/acs.jctc.8b00654] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Elastic network models, simple structure-based representations of biomolecules where atoms interact via short-range harmonic potentials, provide great insight into a molecule's internal dynamics and mechanical properties at extremely low computational cost. Their efficiency and effectiveness have made them a pivotal instrument in the computer-aided study of proteins and, since a few years, also of nucleic acids. In general, the coarse-grained sites, i.e. those effective force centers onto which the all-atom structure is mapped, are constructed based on intuitive rules: a typical choice for proteins is to retain only the C α atoms of each amino acid. However, a mapping strategy relying only on the atom type and not the local properties of its embedding can be suboptimal compared to a more careful selection. Here, we present a strategy in which the subset of atoms, each of which is mapped onto a unique coarse-grained site of the model, is selected in a stochastic search aimed at optimizing a cost function. The latter is taken to be a simple measure of the consistency between the harmonic approximation of an elastic network model and the harmonic model obtained through exact integration of the discarded degrees of freedom. The method is applied to two representatives of structurally very different types of biomolecules: the protein adenylate kinase and the RNA molecule adenine riboswitch. Our analysis quantifies the substantial impact that an algorithm-driven selection of coarse-grained sites can have on a model's properties.
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Affiliation(s)
- Patrick Diggins
- Department of Physics , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
| | - Changjiang Liu
- Department of Physics , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States.,Department of Biophysics , University of Michigan , Ann Arbor , Michigan 48109 , United States
| | - Markus Deserno
- Department of Physics , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
| | - Raffaello Potestio
- Physics Department , University of Trento , via Sommarive, 14 I-38123 Trento , Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications , I-38123 Trento , Italy
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27
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Abstract
A methodology to cluster proteins based on their dynamics’ similarity is presented. For each pair of proteins from a dataset, the structures are superimposed, and the Anisotropic Network Model modes of motions are calculated. The twelve slowest modes from each protein are matched using a local mode alignment algorithm based on the local sequence alignment algorithm of Smith–Waterman. The dynamical similarity distance matrix is calculated based on the top scoring matches of each pair and the proteins are clustered using a hierarchical clustering algorithm. The utility of this method is exemplified on a dataset of protein chains from the globin family and a dataset of tetrameric hemoglobins. The results demonstrate the effect of the quaternary structure of globin members on their intrinsic dynamics and show good ability to distinguish between different states of hemoglobin, revealing the dynamical relations between them.
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Affiliation(s)
- Dror Tobi
- Department of Molecular Biology, Ariel University, Ariel, Israel
- Department of Computer Sciences, Ariel University, Ariel, Israel
- * E-mail:
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28
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Aharoni R, Tobi D. Dynamical comparison between myoglobin and hemoglobin. Proteins 2018; 86:1176-1183. [PMID: 30183107 DOI: 10.1002/prot.25598] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 08/22/2018] [Accepted: 08/31/2018] [Indexed: 01/29/2023]
Abstract
Myoglobin and hemoglobin are globular hemeproteins, when the former is a monomer and the latter a heterotetramer. Despite the structural similarity of myoglobin to α and β subunits of hemoglobin, there is a functional difference between the two proteins, owing to the quaternary structure of hemoglobin. The effect of the quaternary structure of hemoglobin on the intrinsic dynamics of its subunits is explored by dynamical comparison of the two proteins. Anisotropic Network Model modes of motion were calculated for hemoglobin and myoglobin. Dynamical comparison between the proteins was performed using global and local Anisotropic Network Model mode alignment algorithms based on the algorithms of Smith-Waterman and Needleman-Wunsch for sequence comparison. The results indicate that the quaternary structure of hemoglobin substantially alters the intrinsic dynamics of its subunits, an effect that may contribute to the functional difference between the two proteins. Local dynamics similarity between the proteins is still observed at the major exit route of the ligand.
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Affiliation(s)
- Rotem Aharoni
- Department of Molecular Biology, Ariel University, Ariel, Israel
| | - Dror Tobi
- Department of Molecular Biology, Ariel University, Ariel, Israel.,Department of Computer Sciences, Ariel University, Ariel, Israel
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29
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Shao L, Gao H, Liu Z, Feng J, Tang L, Lin H. Identification of Antioxidant Proteins With Deep Learning From Sequence Information. Front Pharmacol 2018; 9:1036. [PMID: 30294271 PMCID: PMC6158654 DOI: 10.3389/fphar.2018.01036] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2018] [Accepted: 08/27/2018] [Indexed: 01/26/2023] Open
Abstract
Antioxidant proteins have been found closely linked to disease control for its ability to eliminate excess free radicals. Because of its medicinal value, the study of identifying antioxidant proteins is on the upsurge. Many machine-learning classifiers have performed poorly owing to the nonlinear and unbalanced nature of biological data. Recently, deep learning techniques showed advantages over many state-of-the-art machine learning methods in various fields. In this study, a deep learning based classifier was proposed to identify antioxidant proteins based on mixed g-gap dipeptide composition feature vector. The classifier employed deep autoencoder to extract nonlinear representation from raw input. The t-Distributed Stochastic Neighbor Embedding (t-SNE) was used for dimensionality reduction. Support vector machine was finally performed for classification. The classifier achieved F 1 score of 0.8842 and MCC of 0.7409 in 10-fold cross validation. Experimental results show that our proposed method outperformed the traditional machine learning methods and could be a promising tool for antioxidant protein identification. For the convenience of others' scientific research, we have developed a user-friendly web server called IDAod for antioxidant protein identification, which can be accessed freely at http://bigroup.uestc.edu.cn/IDAod/.
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Affiliation(s)
- Lifen Shao
- Center for Informational Biology, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Hui Gao
- Center for Informational Biology, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhen Liu
- Center for Informational Biology, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Juan Feng
- Key Laboratory for Neuro-Information of Ministry of Education, Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Lixia Tang
- Key Laboratory for Neuro-Information of Ministry of Education, Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hao Lin
- Key Laboratory for Neuro-Information of Ministry of Education, Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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30
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Miao H, Klein T, Kouřil D, Mindek P, Schatz K, Gröller ME, Kozlíková B, Isenberg T, Viola I. Multiscale Molecular Visualization. J Mol Biol 2018; 431:1049-1070. [PMID: 30227136 DOI: 10.1016/j.jmb.2018.09.004] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 08/28/2018] [Accepted: 09/05/2018] [Indexed: 02/07/2023]
Abstract
We provide a high-level survey of multiscale molecular visualization techniques, with a focus on application-domain questions, challenges, and tasks. We provide a general introduction to molecular visualization basics and describe a number of domain-specific tasks that drive this work. These tasks, in turn, serve as the general structure of the following survey. First, we discuss methods that support the visual analysis of molecular dynamics simulations. We discuss, in particular, visual abstraction and temporal aggregation. In the second part, we survey multiscale approaches that support the design, analysis, and manipulation of DNA nanostructures and related concepts for abstraction, scale transition, scale-dependent modeling, and navigation of the resulting abstraction spaces. In the third part of the survey, we showcase approaches that support interactive exploration within large structural biology assemblies up to the size of bacterial cells. We describe fundamental rendering techniques as well as approaches for element instantiation, visibility management, visual guidance, camera control, and support of depth perception. We close the survey with a brief listing of important tools that implement many of the discussed approaches and a conclusion that provides some research challenges in the field.
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31
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Choi H, Yoon T, Na S. Length-Dependent Manifestation of Vibration Modes Regulates a Specific Intermediate Morphology of Aβ17-42 in Different Environments. Chemphyschem 2018; 19:1643-1654. [PMID: 29575445 DOI: 10.1002/cphc.201800010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Indexed: 12/25/2022]
Abstract
Various cytotoxic mechanisms for neurodegenerative disease are induced by specific conformations of Aβ intermediates. The efforts to understand the diverse intermediate forms of amyloid oligomers have been focused on understanding the aggregation mechanism of specific morphologies for Aβ intermediates. However, these are still not easy tasks to be accomplished because the diverse conformations of Aβ intermediates can be altered during the aggregation process, even though the same Aβ monomers are present. Thus, efforts to reveal the conformational change mechanism could be a fundamental process to understand the formation of diverse Aβ intermediate conformations. Here, we evaluate the conformational characteristics of Aβ17-42 fibrillar oligomers in different environments according to the length. We observed that Aβ fibrillar oligomers optimize their inherent hydrogen bonds and configurational entropy to stabilize their structure according to the simulation time and their length increase. In addition, we revealed the role of the expressed vibration mode shape in the fibrillar oligomers' elongation and deformation processes. Our results suggest that limitations in amyloid oligomer growth and transformations of their morphologies can be regulated and controlled by modifying the vibration features.
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Affiliation(s)
- Hyunsung Choi
- Department of Mechanical Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Taeyoung Yoon
- Department of Mechanical Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Sungsoo Na
- Department of Mechanical Engineering, Korea University, Seoul, 02841, Republic of Korea
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32
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Cieplak-Rotowska MK, Tarnowski K, Rubin M, Fabian MR, Sonenberg N, Dadlez M, Niedzwiecka A. Structural Dynamics of the GW182 Silencing Domain Including its RNA Recognition motif (RRM) Revealed by Hydrogen-Deuterium Exchange Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2018; 29:158-173. [PMID: 29080206 PMCID: PMC5785596 DOI: 10.1007/s13361-017-1830-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Revised: 09/08/2017] [Accepted: 10/01/2017] [Indexed: 06/07/2023]
Abstract
The human GW182 protein plays an essential role in micro(mi)RNA-dependent gene silencing. miRNA silencing is mediated, in part, by a GW182 C-terminal region called the silencing domain, which interacts with the poly(A) binding protein and the CCR4-NOT deadenylase complex to repress protein synthesis. Structural studies of this GW182 fragment are challenging due to its predicted intrinsically disordered character, except for its RRM domain. However, detailed insights into the properties of proteins containing disordered regions can be provided by hydrogen-deuterium exchange mass spectrometry (HDX/MS). In this work, we applied HDX/MS to define the structural state of the GW182 silencing domain. HDX/MS analysis revealed that this domain is clearly divided into a natively unstructured part, including the CCR4-NOT interacting motif 1, and a distinct RRM domain. The GW182 RRM has a very dynamic structure, since water molecules can penetrate the whole domain in 2 h. The finding of this high structural dynamics sheds new light on the RRM structure. Though this domain is one of the most frequently occurring canonical protein domains in eukaryotes, these results are - to our knowledge - the first HDX/MS characteristics of an RRM. The HDX/MS studies show also that the α2 helix of the RRM can display EX1 behavior after a freezing-thawing cycle. This means that the RRM structure is sensitive to environmental conditions and can change its conformation, which suggests that the state of the RRM containing proteins should be checked by HDX/MS in regard of the conformational uniformity. Graphical Abstract.
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Affiliation(s)
- Maja K Cieplak-Rotowska
- Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, 02-089, Warsaw, Poland
| | - Krzysztof Tarnowski
- Laboratory of Mass Spectrometry, Institute of Biochemistry and Biophysics, Polish Academy of Sciences, PL-02106, Warsaw, Poland
| | - Marcin Rubin
- Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, 02-089, Warsaw, Poland
| | - Marc R Fabian
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec, Canada
- Department of Oncology, McGill University, Montréal, Québec, Canada
| | - Nahum Sonenberg
- Department of Biochemistry, McGill University, Montréal, Québec, Canada
- Goodman Cancer Center, McGill University, Montréal, Québec, Canada
| | - Michal Dadlez
- Laboratory of Mass Spectrometry, Institute of Biochemistry and Biophysics, Polish Academy of Sciences, PL-02106, Warsaw, Poland
| | - Anna Niedzwiecka
- Laboratory of Biological Physics, Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668, Warsaw, Poland.
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33
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Yefremova Y, Danquah BD, Opuni KF, El-Kased R, Koy C, Glocker MO. Mass spectrometric characterization of protein structures and protein complexes in condensed and gas phase. EUROPEAN JOURNAL OF MASS SPECTROMETRY (CHICHESTER, ENGLAND) 2017; 23:445-459. [PMID: 29183193 DOI: 10.1177/1469066717722256] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Proteins are essential for almost all physiological processes of life. They serve a myriad of functions which are as varied as their unique amino acid sequences and their corresponding three-dimensional structures. To fulfill their tasks, most proteins depend on stable physical associations, in the form of protein complexes that evolved between themselves and other proteins. In solution (condensed phase), proteins and/or protein complexes are in constant energy exchange with the surrounding solvent. Albeit methods to describe in-solution thermodynamic properties of proteins and of protein complexes are well established and broadly applied, they do not provide a broad enough access to life-science experimentalists to study all their proteins' properties at leisure. This leaves great desire to add novel methods to the analytical biochemist's toolbox. The development of electrospray ionization created the opportunity to characterize protein higher order structures and protein complexes rather elegantly by simultaneously lessening the need of sophisticated sample preparation steps. Electrospray mass spectrometry enabled us to translate proteins and protein complexes very efficiently into the gas phase under mild conditions, retaining both, intact protein complexes, and gross protein structures upon phase transition. Moreover, in the environment of the mass spectrometer (gas phase, in vacuo), analyte molecules are free of interactions with surrounding solvent molecules and, therefore, the energy of inter- and intramolecular forces can be studied independently from interference of the solvating environment. Provided that gas phase methods can give information which is relevant for understanding in-solution processes, gas phase protein structure studies and/or investigations on the characterization of protein complexes has rapidly gained more and more attention from the bioanalytical scientific community. Recent reports have shown that electrospray mass spectrometry provides direct access to six prime protein complex properties: stabilities, compositions, binding surfaces (epitopes), disassembly processes, stoichiometries, and thermodynamic parameters.
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Affiliation(s)
- Yelena Yefremova
- 1 Proteome Center Rostock, University of Rostock, Rostock, Germany
| | - Bright D Danquah
- 1 Proteome Center Rostock, University of Rostock, Rostock, Germany
| | | | - Reham El-Kased
- 3 Microbiology and Immunology, Faculty of Pharmacy, The British University in Egypt, Cairo, Egypt
| | - Cornelia Koy
- 1 Proteome Center Rostock, University of Rostock, Rostock, Germany
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34
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Putz I, Brock O. Elastic network model of learned maintained contacts to predict protein motion. PLoS One 2017; 12:e0183889. [PMID: 28854238 PMCID: PMC5576689 DOI: 10.1371/journal.pone.0183889] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2016] [Accepted: 08/14/2017] [Indexed: 12/21/2022] Open
Abstract
We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein's contact topology. Existing elastic network models assume that the contact topology remains unchanged throughout the motion and are thus most appropriate to simulate highly collective function-related movements. lmcENM uses machine learning to differentiate breaking from maintained contacts. We show that lmcENM accurately captures functional transitions unexplained by the classical ENM and three reference ENM variants, while preserving the simplicity of classical ENM. We demonstrate the effectiveness of our approach on a large set of proteins covering different motion types. Our results suggest that accurately predicting a "deformation-invariant" contact topology offers a promising route to increase the general applicability of ENMs. We also find that to correctly predict this contact topology a combination of several features seems to be relevant which may vary slightly depending on the protein. Additionally, we present case studies of two biologically interesting systems, Ferric Citrate membrane transporter FecA and Arachidonate 15-Lipoxygenase.
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Affiliation(s)
- Ines Putz
- Robotics and Biology Laboratory, Department of Computer Science and Electrical Engineering, Technische Universität Berlin, Berlin, Berlin, Germany
| | - Oliver Brock
- Robotics and Biology Laboratory, Department of Computer Science and Electrical Engineering, Technische Universität Berlin, Berlin, Berlin, Germany
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35
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Morgan NK, Wallace A, Bedford MR, Choct M. Efficiency of xylanases from families 10 and 11 in production of xylo -oligosaccharides from wheat arabinoxylans. Carbohydr Polym 2017; 167:290-296. [DOI: 10.1016/j.carbpol.2017.03.063] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 02/23/2017] [Accepted: 03/18/2017] [Indexed: 10/19/2022]
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36
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Tobi D. Dynamical differences of hemoglobin and the ionotropic glutamate receptor in different states revealed by a new dynamics alignment method. Proteins 2017; 85:1507-1517. [PMID: 28459140 DOI: 10.1002/prot.25311] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 04/02/2017] [Accepted: 04/24/2017] [Indexed: 12/26/2022]
Abstract
A new algorithm for comparison of protein dynamics is presented. Compared protein structures are superposed and their modes of motions are calculated using the anisotropic network model. The obtained modes are aligned using the dynamic programming algorithm of Needleman and Wunsch, commonly used for sequence alignment. Dynamical comparison of hemoglobin in the T and R2 states reveals that the dynamics of the allosteric effector 2,3-bisphosphoglycerate binding site is different in the two states. These differences can contribute to the selectivity of the effector to the T state. Similar comparison of the ionotropic glutamate receptor in the kainate+(R,R)-2b and ZK bound states reveals that the kainate+(R,R)-2b bound states slow modes describe upward motions of ligand binding domain and the transmembrane domain regions. Such motions may lead to the opening of the receptor. The upper lobes of the LBDs of the ZK bound state have a smaller interface with the amino terminal domains above them and have a better ability to move together. The present study exemplifies the use of dynamics comparison as a tool to study protein function. Proteins 2017; 85:1507-1517. © 2014 Wiley Periodicals, Inc.
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Affiliation(s)
- Dror Tobi
- Department of Computer Sciences, Ariel University, Ariel, 40700, Israel.,Department of Molecular Biology, Ariel University, Ariel, 40700, Israel
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37
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Kocincová L, Jarešová M, Byška J, Parulek J, Hauser H, Kozlíková B. Comparative visualization of protein secondary structures. BMC Bioinformatics 2017; 18:23. [PMID: 28251875 PMCID: PMC5333176 DOI: 10.1186/s12859-016-1449-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Background Protein function is determined by many factors, namely by its constitution, spatial arrangement, and dynamic behavior. Studying these factors helps the biochemists and biologists to better understand the protein behavior and to design proteins with modified properties. One of the most common approaches to these studies is to compare the protein structure with other molecules and to reveal similarities and differences in their polypeptide chains. Results We support the comparison process by proposing a new visualization technique that bridges the gap between traditionally used 1D and 3D representations. By introducing the information about mutual positions of protein chains into the 1D sequential representation the users are able to observe the spatial differences between the proteins without any occlusion commonly present in 3D view. Our representation is designed to serve namely for comparison of multiple proteins or a set of time steps of molecular dynamics simulation. Conclusions The novel representation is demonstrated on two usage scenarios. The first scenario aims to compare a set of proteins from the family of cytochromes P450 where the position of the secondary structures has a significant impact on the substrate channeling. The second scenario focuses on the protein flexibility when by comparing a set of time steps our representation helps to reveal the most dynamically changing parts of the protein chain.
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Affiliation(s)
| | | | - Jan Byška
- Masaryk University, Brno, Czech Republic. .,University of Bergen, Bergen, Norway.
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38
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Kamenik AS, Kahler U, Fuchs JE, Liedl KR. Localization of Millisecond Dynamics: Dihedral Entropy from Accelerated MD. J Chem Theory Comput 2016; 12:3449-55. [PMID: 27322931 PMCID: PMC4980685 DOI: 10.1021/acs.jctc.6b00231] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Indexed: 11/28/2022]
Abstract
Here, we demonstrate a method to capture local dynamics on a time scale 3 orders of magnitude beyond state-of-the-art simulation approaches. We apply accelerated molecular dynamics simulations for conformational sampling and extract reweighted backbone dihedral distributions. Local dynamics are characterized by torsional probabilities, resulting in residue-wise dihedral entropies. Our approach is successfully validated for three different protein systems of increasing size: alanine dipeptide, bovine pancreatic trypsin inhibitor (BPTI), and the major birch pollen allergen Bet v 1a. We demonstrate excellent agreement of flexibility profiles with both large-scale computer simulations and NMR experiments. Thus, our method provides efficient access to local protein dynamics on extended time scales of high biological relevance.
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Affiliation(s)
- Anna S. Kamenik
- Institute of General, Inorganic
and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, Austria
| | - Ursula Kahler
- Institute of General, Inorganic
and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, Austria
| | - Julian E. Fuchs
- Institute of General, Inorganic
and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, Austria
| | - Klaus R. Liedl
- Institute of General, Inorganic
and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, Austria
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39
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Buchenberg S, Schaudinnus N, Stock G. Hierarchical Biomolecular Dynamics: Picosecond Hydrogen Bonding Regulates Microsecond Conformational Transitions. J Chem Theory Comput 2016; 11:1330-6. [PMID: 26579778 DOI: 10.1021/ct501156t] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Biomolecules exhibit structural dynamics on a number of time scales, including picosecond (ps) motions of a few atoms, nanosecond (ns) local conformational transitions, and microsecond (μs) global conformational rearrangements. Despite this substantial separation of time scales, fast and slow degrees of freedom appear to be coupled in a nonlinear manner; for example, there is theoretical and experimental evidence that fast structural fluctuations are required for slow functional motion to happen. To elucidate a microscopic mechanism of this multiscale behavior, Aib peptide is adopted as a simple model system. Combining extensive molecular dynamics simulations with principal component analysis techniques, a hierarchy of (at least) three tiers of the molecule's free energy landscape is discovered. They correspond to chiral left- to right-handed transitions of the entire peptide that happen on a μs time scale, conformational transitions of individual residues that take about 1 ns, and the opening and closing of structure-stabilizing hydrogen bonds that occur within tens of ps and are triggered by sub-ps structural fluctuations. Providing a simple mechanism of hierarchical dynamics, fast hydrogen bond dynamics is found to be a prerequisite for the ns local conformational transitions, which in turn are a prerequisite for the slow global conformational rearrangement of the peptide. As a consequence of the hierarchical coupling, the various processes exhibit a similar temperature behavior which may be interpreted as a dynamic transition.
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Affiliation(s)
- Sebastian Buchenberg
- Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University , Freiburg, 79104 Germany
| | - Norbert Schaudinnus
- Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University , Freiburg, 79104 Germany
| | - Gerhard Stock
- Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University , Freiburg, 79104 Germany.,Freiburg Institute for Advanced Studies (FRIAS), Albert Ludwigs University , Freiburg, 79104 Germany
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40
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Hati S, Bhattacharyya S. Incorporating modeling and simulations in undergraduate biophysical chemistry course to promote understanding of structure-dynamics-function relationships in proteins. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2016; 44:140-159. [PMID: 26801683 DOI: 10.1002/bmb.20942] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 11/15/2015] [Indexed: 06/05/2023]
Abstract
A project-based biophysical chemistry laboratory course, which is offered to the biochemistry and molecular biology majors in their senior year, is described. In this course, the classroom study of the structure-function of biomolecules is integrated with the discovery-guided laboratory study of these molecules using computer modeling and simulations. In particular, modern computational tools are employed to elucidate the relationship between structure, dynamics, and function in proteins. Computer-based laboratory protocols that we introduced in three modules allow students to visualize the secondary, super-secondary, and tertiary structures of proteins, analyze non-covalent interactions in protein-ligand complexes, develop three-dimensional structural models (homology model) for new protein sequences and evaluate their structural qualities, and study proteins' intrinsic dynamics to understand their functions. In the fourth module, students are assigned to an authentic research problem, where they apply their laboratory skills (acquired in modules 1-3) to answer conceptual biophysical questions. Through this process, students gain in-depth understanding of protein dynamics-the missing link between structure and function. Additionally, the requirement of term papers sharpens students' writing and communication skills. Finally, these projects result in new findings that are communicated in peer-reviewed journals.
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Affiliation(s)
- Sanchita Hati
- Department of Chemistry, University Wisconsin, Eau Claire, Wisconsin
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41
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Yefremova Y, Al-Majdoub M, Opuni KF, Koy C, Yan Y, Gross M, Glocker MO. A Dynamic Model of pH-Induced Protein G'e Higher Order Structure Changes derived from Mass Spectrometric Analyses. Anal Chem 2016; 88:890-7. [PMID: 26606592 PMCID: PMC5201196 DOI: 10.1021/acs.analchem.5b03536] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
To obtain insight into pH change-driven molecular dynamics, we studied the higher order structure changes of protein G'e at the molecular and amino acid residue levels in solution by using nanoESI- and IM-mass spectrometry, CD spectroscopy, and protein chemical modification reactions (protein footprinting). We found a dramatic change of the overall tertiary structure of protein G'e when the pH was changed from neutral to acidic, whereas its secondary structure features remained nearly invariable. Limited proteolysis and surface-topology mapping of protein G'e by fast photochemical oxidation of proteins (FPOP) under neutral and acidic conditions reveal areas where higher order conformational changes occur on the amino-acid residue level. Under neutral solution conditions, lower oxidation occurs for residues of the first linker region, whereas greater oxidative modifications occur for amino-acid residues of the IgG-binding domains I and II. We propose a dynamic model of pH-induced structural changes in which protein G'e at neutral pH adopts an overall tight conformation with all four domains packed in a firm assembly, whereas at acidic pH, the three IgG-binding domains form an elongated alignment, and the N-terminal, His-tag-carrying domain unfolds. At the same time the individual IgG-binding domains themselves seem to adopt a more compacted fold. As the secondary structure features are nearly unchanged at either pH, interchange between both conformations is highly reversible, explaining the high reconditioning power of protein G'e-based affinity chromatography columns.
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Affiliation(s)
- Yelena Yefremova
- Proteome Center Rostock, University Medicine Rostock, Rostock, Germany
| | | | | | - Cornelia Koy
- Proteome Center Rostock, University Medicine Rostock, Rostock, Germany
| | - Yuetian Yan
- Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130 USA
| | - Michael Gross
- Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130 USA
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42
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Byska J, Le Muzic M, Gröller ME, Viola I, Kozlíková B. AnimoAminoMiner: Exploration of Protein Tunnels and their Properties in Molecular Dynamics. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2016; 22:747-756. [PMID: 26529726 DOI: 10.1109/tvcg.2015.2467434] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
In this paper we propose a novel method for the interactive exploration of protein tunnels. The basic principle of our approach is that we entirely abstract from the 3D/4D space the simulated phenomenon is embedded in. A complex 3D structure and its curvature information is represented only by a straightened tunnel centerline and its width profile. This representation focuses on a key aspect of the studied geometry and frees up graphical estate to key chemical and physical properties represented by surrounding amino acids. The method shows the detailed tunnel profile and its temporal aggregation. The profile is interactively linked with a visual overview of all amino acids which are lining the tunnel over time. In this overview, each amino acid is represented by a set of colored lines depicting the spatial and temporal impact of the amino acid on the corresponding tunnel. This representation clearly shows the importance of amino acids with respect to selected criteria. It helps the biochemists to select the candidate amino acids for mutation which changes the protein function in a desired way. The AnimoAminoMiner was designed in close cooperation with domain experts. Its usefulness is documented by their feedback and a case study, which are included.
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43
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Panneerselvam S, Durai P, Yesudhas D, Achek A, Kwon HK, Choi S. Cysteine redox state plays a key role in the inter-domain movements of HMGB1: a molecular dynamics simulation study. RSC Adv 2016. [DOI: 10.1039/c6ra16343b] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
We have modelled and simulated different states of HMGB1, suggesting that the fully reduced HMGB1 maintains the inter-domain movements during the activity.
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Affiliation(s)
| | | | - Dhanusha Yesudhas
- Department of Molecular Science and Technology
- Ajou University
- Suwon 443-749
- Korea
| | - Asma Achek
- Department of Molecular Science and Technology
- Ajou University
- Suwon 443-749
- Korea
| | - Hyuk-Kwon Kwon
- Department of Molecular Science and Technology
- Ajou University
- Suwon 443-749
- Korea
| | - Sangdun Choi
- Department of Molecular Science and Technology
- Ajou University
- Suwon 443-749
- Korea
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44
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Hospital A, Andrio P, Cugnasco C, Codo L, Becerra Y, Dans PD, Battistini F, Torres J, Goñi R, Orozco M, Gelpí JL. BIGNASim: a NoSQL database structure and analysis portal for nucleic acids simulation data. Nucleic Acids Res 2015; 44:D272-8. [PMID: 26612862 PMCID: PMC4702913 DOI: 10.1093/nar/gkv1301] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Accepted: 11/02/2015] [Indexed: 12/25/2022] Open
Abstract
Molecular dynamics simulation (MD) is, just behind genomics, the bioinformatics tool that generates the largest amounts of data, and that is using the largest amount of CPU time in supercomputing centres. MD trajectories are obtained after months of calculations, analysed in situ, and in practice forgotten. Several projects to generate stable trajectory databases have been developed for proteins, but no equivalence exists in the nucleic acids world. We present here a novel database system to store MD trajectories and analyses of nucleic acids. The initial data set available consists mainly of the benchmark of the new molecular dynamics force-field, parmBSC1. It contains 156 simulations, with over 120 μs of total simulation time. A deposition protocol is available to accept the submission of new trajectory data. The database is based on the combination of two NoSQL engines, Cassandra for storing trajectories and MongoDB to store analysis results and simulation metadata. The analyses available include backbone geometries, helical analysis, NMR observables and a variety of mechanical analyses. Individual trajectories and combined meta-trajectories can be downloaded from the portal. The system is accessible through http://mmb.irbbarcelona.org/BIGNASim/. Supplementary Material is also available on-line at http://mmb.irbbarcelona.org/BIGNASim/SuppMaterial/.
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Affiliation(s)
- Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Joint BSC-IRB Research Program in Computational Biology, Baldiri Reixac 10-12, 08028 Barcelona, Spain
| | - Pau Andrio
- Joint BSC-IRB Research Program in Computational Biology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain
| | - Cesare Cugnasco
- Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain Dept. Computer Architecture, Technical University of Catalonia (UPC-BarcelonaTech), 08034 Barcelona, Spain
| | - Laia Codo
- Joint BSC-IRB Research Program in Computational Biology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain
| | - Yolanda Becerra
- Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain Dept. Computer Architecture, Technical University of Catalonia (UPC-BarcelonaTech), 08034 Barcelona, Spain
| | - Pablo D Dans
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Joint BSC-IRB Research Program in Computational Biology, Baldiri Reixac 10-12, 08028 Barcelona, Spain
| | - Federica Battistini
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Joint BSC-IRB Research Program in Computational Biology, Baldiri Reixac 10-12, 08028 Barcelona, Spain
| | - Jordi Torres
- Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain Dept. Computer Architecture, Technical University of Catalonia (UPC-BarcelonaTech), 08034 Barcelona, Spain
| | - Ramón Goñi
- Joint BSC-IRB Research Program in Computational Biology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Joint BSC-IRB Research Program in Computational Biology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain Department of Biochemistry and Molecular Biology, University of Barcelona, 08028 Barcelona, Spain
| | - Josep Ll Gelpí
- Joint BSC-IRB Research Program in Computational Biology, Baldiri Reixac 10-12, 08028 Barcelona, Spain Barcelona Supercomputing Center, Jordi Girona 29, 08034 Barcelona, Spain Department of Biochemistry and Molecular Biology, University of Barcelona, 08028 Barcelona, Spain
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45
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Carvalho HF, Roque ACA, Iranzo O, Branco RJF. Comparison of the Internal Dynamics of Metalloproteases Provides New Insights on Their Function and Evolution. PLoS One 2015; 10:e0138118. [PMID: 26397984 PMCID: PMC4580569 DOI: 10.1371/journal.pone.0138118] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Accepted: 08/25/2015] [Indexed: 11/20/2022] Open
Abstract
Metalloproteases have evolved in a vast number of biological systems, being one of the most diverse types of proteases and presenting a wide range of folds and catalytic metal ions. Given the increasing understanding of protein internal dynamics and its role in enzyme function, we are interested in assessing how the structural heterogeneity of metalloproteases translates into their dynamics. Therefore, the dynamical profile of the clan MA type protein thermolysin, derived from an Elastic Network Model of protein structure, was evaluated against those obtained from a set of experimental structures and molecular dynamics simulation trajectories. A close correspondence was obtained between modes derived from the coarse-grained model and the subspace of functionally-relevant motions observed experimentally, the later being shown to be encoded in the internal dynamics of the protein. This prompted the use of dynamics-based comparison methods that employ such coarse-grained models in a representative set of clan members, allowing for its quantitative description in terms of structural and dynamical variability. Although members show structural similarity, they nonetheless present distinct dynamical profiles, with no apparent correlation between structural and dynamical relatedness. However, previously unnoticed dynamical similarity was found between the relevant members Carboxypeptidase Pfu, Leishmanolysin, and Botulinum Neurotoxin Type A, despite sharing no structural similarity. Inspection of the respective alignments shows that dynamical similarity has a functional basis, namely the need for maintaining proper intermolecular interactions with the respective substrates. These results suggest that distinct selective pressure mechanisms act on metalloproteases at structural and dynamical levels through the course of their evolution. This work shows how new insights on metalloprotease function and evolution can be assessed with comparison schemes that incorporate information on protein dynamics. The integration of these newly developed tools, if applied to other protein families, can lead to more accurate and descriptive protein classification systems.
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Affiliation(s)
- Henrique F. Carvalho
- UCIBIO-REQUIMTE, Department of Chemistry, Faculty of Science and Technology, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Av. da República, 2780–157 Oeiras, Portugal
| | - Ana C. A. Roque
- UCIBIO-REQUIMTE, Department of Chemistry, Faculty of Science and Technology, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal
| | - Olga Iranzo
- Aix Marseille Université, Centrale Marseille, CNRS, iSm2 UMR 7313, 13397, Marseille, France
| | - Ricardo J. F. Branco
- UCIBIO-REQUIMTE, Department of Chemistry, Faculty of Science and Technology, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal
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46
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Dorner ME, McMunn RD, Bartholow TG, Calhoon BE, Conlon MR, Dulli JM, Fehling SC, Fisher CR, Hodgson SW, Keenan SW, Kruger AN, Mabin JW, Mazula DL, Monte CA, Olthafer A, Sexton AE, Soderholm BR, Strom AM, Hati S. Comparison of intrinsic dynamics of cytochrome p450 proteins using normal mode analysis. Protein Sci 2015; 24:1495-507. [PMID: 26130403 DOI: 10.1002/pro.2737] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Revised: 04/18/2015] [Accepted: 06/14/2015] [Indexed: 12/24/2022]
Abstract
Cytochrome P450 enzymes are hemeproteins that catalyze the monooxygenation of a wide-range of structurally diverse substrates of endogenous and exogenous origin. These heme monooxygenases receive electrons from NADH/NADPH via electron transfer proteins. The cytochrome P450 enzymes, which constitute a diverse superfamily of more than 8,700 proteins, share a common tertiary fold but < 25% sequence identity. Based on their electron transfer protein partner, cytochrome P450 proteins are classified into six broad classes. Traditional methods of pro are based on the canonical paradigm that attributes proteins' function to their three-dimensional structure, which is determined by their primary structure that is the amino acid sequence. It is increasingly recognized that protein dynamics play an important role in molecular recognition and catalytic activity. As the mobility of a protein is an intrinsic property that is encrypted in its primary structure, we examined if different classes of cytochrome P450 enzymes display any unique patterns of intrinsic mobility. Normal mode analysis was performed to characterize the intrinsic dynamics of five classes of cytochrome P450 proteins. The present study revealed that cytochrome P450 enzymes share a strong dynamic similarity (root mean squared inner product > 55% and Bhattacharyya coefficient > 80%), despite the low sequence identity (< 25%) and sequence similarity (< 50%) across the cytochrome P450 superfamily. Noticeable differences in Cα atom fluctuations of structural elements responsible for substrate binding were noticed. These differences in residue fluctuations might be crucial for substrate selectivity in these enzymes.
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Affiliation(s)
- Mariah E Dorner
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Ryan D McMunn
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Thomas G Bartholow
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Brecken E Calhoon
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Michelle R Conlon
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Jessica M Dulli
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Samuel C Fehling
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Cody R Fisher
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Shane W Hodgson
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Shawn W Keenan
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Alyssa N Kruger
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Justin W Mabin
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Daniel L Mazula
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Christopher A Monte
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Augustus Olthafer
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Ashley E Sexton
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Beatrice R Soderholm
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Alexander M Strom
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
| | - Sanchita Hati
- Department of Chemistry, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin, 54702
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47
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Laulumaa S, Nieminen T, Lehtimäki M, Aggarwal S, Simons M, Koza MM, Vattulainen I, Kursula P, Natali F. Dynamics of the Peripheral Membrane Protein P2 from Human Myelin Measured by Neutron Scattering--A Comparison between Wild-Type Protein and a Hinge Mutant. PLoS One 2015; 10:e0128954. [PMID: 26068118 PMCID: PMC4466134 DOI: 10.1371/journal.pone.0128954] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2015] [Accepted: 05/01/2015] [Indexed: 12/01/2022] Open
Abstract
Myelin protein P2 is a fatty acid-binding structural component of the myelin sheath in the peripheral nervous system, and its function is related to its membrane binding capacity. Here, the link between P2 protein dynamics and structure and function was studied using elastic incoherent neutron scattering (EINS). The P38G mutation, at the hinge between the β barrel and the α-helical lid, increased the lipid stacking capacity of human P2 in vitro, and the mutated protein was also functional in cultured cells. The P38G mutation did not change the overall structure of the protein. For a deeper insight into P2 structure-function relationships, information on protein dynamics in the 10 ps to 1 ns time scale was obtained using EINS. Values of mean square displacements mainly from protein H atoms were extracted for wild-type P2 and the P38G mutant and compared. Our results show that at physiological temperatures, the P38G mutant is more dynamic than the wild-type P2 protein, especially on a slow 1-ns time scale. Molecular dynamics simulations confirmed the enhanced dynamics of the mutant variant, especially within the portal region in the presence of bound fatty acid. The increased softness of the hinge mutant of human myelin P2 protein is likely related to an enhanced flexibility of the portal region of this fatty acid-binding protein, as well as to its interactions with the lipid bilayer surface requiring conformational adaptations.
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Affiliation(s)
- Saara Laulumaa
- Biochemistry and Molecular Medicine & Biocenter Oulu, University of Oulu, Oulu, Finland
- German Electron Synchrotron (DESY), Hamburg, Germany
- European Spallation Source (ESS), Lund, Sweden
| | - Tuomo Nieminen
- Department of Physics, Tampere University of Technology, Tampere, Finland
| | - Mari Lehtimäki
- Biochemistry and Molecular Medicine & Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Shweta Aggarwal
- Max Planck Institute for Experimental Medicine, Göttingen, Germany
| | - Mikael Simons
- Max Planck Institute for Experimental Medicine, Göttingen, Germany
| | | | - Ilpo Vattulainen
- Department of Physics, Tampere University of Technology, Tampere, Finland
| | - Petri Kursula
- Biochemistry and Molecular Medicine & Biocenter Oulu, University of Oulu, Oulu, Finland
- German Electron Synchrotron (DESY), Hamburg, Germany
- Department of Biomedicine, University of Bergen, Bergen, Norway
- * E-mail: (PK); (FN)
| | - Francesca Natali
- Institut Laue-Langevin (ILL), Grenoble, France
- CNR-IOM, OGG, Grenoble, France
- * E-mail: (PK); (FN)
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48
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Fuchs JE, Waldner BJ, Huber RG, von Grafenstein S, Kramer C, Liedl KR. Independent Metrics for Protein Backbone and Side-Chain Flexibility: Time Scales and Effects of Ligand Binding. J Chem Theory Comput 2015; 11:851-60. [DOI: 10.1021/ct500633u] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Julian E. Fuchs
- Institute
of General, Inorganic and Theoretical Chemistry, and Center for Molecular
Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain
80-82, A-6020 Innsbruck, Tyrol, Austria
- Centre
for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Birgit J. Waldner
- Institute
of General, Inorganic and Theoretical Chemistry, and Center for Molecular
Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain
80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Roland G. Huber
- Institute
of General, Inorganic and Theoretical Chemistry, and Center for Molecular
Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain
80-82, A-6020 Innsbruck, Tyrol, Austria
- Bioinformatics
Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, Matrix #07-01, 138671 Singapore
| | - Susanne von Grafenstein
- Institute
of General, Inorganic and Theoretical Chemistry, and Center for Molecular
Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain
80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Christian Kramer
- Institute
of General, Inorganic and Theoretical Chemistry, and Center for Molecular
Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain
80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Klaus R. Liedl
- Institute
of General, Inorganic and Theoretical Chemistry, and Center for Molecular
Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain
80-82, A-6020 Innsbruck, Tyrol, Austria
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49
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Balasubramaniam D, Komives EA. The phylogenetics of dynamics in DNA clamp proteins. Structure 2014; 22:511-2. [PMID: 24717558 DOI: 10.1016/j.str.2014.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Using HXMS to measure protein dynamics, Fang and colleagues (in this issue of Structure) probe the dynamics of processivity clamp proteins from all kingdoms of life. The proteins have similar structures but divergent sequences. Their results show conserved dynamics correlating with primary functions and divergent dynamics for divergent functions.
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Affiliation(s)
- Deepa Balasubramaniam
- Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0378, USA
| | - Elizabeth A Komives
- Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0378, USA.
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50
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Cilia E, Pancsa R, Tompa P, Lenaerts T, Vranken WF. From protein sequence to dynamics and disorder with DynaMine. Nat Commun 2014; 4:2741. [PMID: 24225580 DOI: 10.1038/ncomms3741] [Citation(s) in RCA: 109] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2013] [Accepted: 10/10/2013] [Indexed: 11/09/2022] Open
Abstract
Protein function and dynamics are closely related; however, accurate dynamics information is difficult to obtain. Here based on a carefully assembled data set derived from experimental data for proteins in solution, we quantify backbone dynamics properties on the amino-acid level and develop DynaMine--a fast, high-quality predictor of protein backbone dynamics. DynaMine uses only protein sequence information as input and shows great potential in distinguishing regions of different structural organization, such as folded domains, disordered linkers, molten globules and pre-structured binding motifs of different sizes. It also identifies disordered regions within proteins with an accuracy comparable to the most sophisticated existing predictors, without depending on prior disorder knowledge or three-dimensional structural information. DynaMine provides molecular biologists with an important new method that grasps the dynamical characteristics of any protein of interest, as we show here for human p53 and E1A from human adenovirus 5.
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Affiliation(s)
- Elisa Cilia
- 1] MLG, Département d'Informatique, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, 1050 Brussels, Belgium [2] Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, La Plaine Campus, Triomflaan, BC building, 6th floor, CP 263, 1050 Brussels, Belgium
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