1
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Koda SI, Saito S. Flat-Bottom Elastic Network Model for Generating Improved Plausible Reaction Paths. J Chem Theory Comput 2024. [PMID: 39150850 DOI: 10.1021/acs.jctc.4c00792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/18/2024]
Abstract
Rapid generation of a plausible reaction path connecting a given reactant and product in advance is crucial for the efficient computation of precise reaction paths or transition states. We propose a computationally efficient potential energy based on the molecular structure to generate such paths. This potential energy has a flat bottom consisting of structures without atomic collisions while preserving nonreactive chemical bonds, bond angles, and partial planar structures. By combining this potential energy with the direct MaxFlux method, a recently developed reaction-path/transition-state search method, we can find the shortest plausible path passing within the bottom. Numerical results show that this combination yields lower energy paths compared to the paths obtained by the well-known image-dependent pair potential. We also theoretically investigate the differences between these two potential energies. The proposed potential energy and path generation routine are implemented in our Python version of the direct MaxFlux method, available on GitHub.
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Affiliation(s)
- Shin-Ichi Koda
- Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan
- School of Physical Sciences, The Graduate University for Advanced Studies, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Shinji Saito
- Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan
- School of Physical Sciences, The Graduate University for Advanced Studies, Myodaiji, Okazaki, Aichi 444-8585, Japan
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2
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Diepeveen W, Esteve-Yagüe C, Lellmann J, Öktem O, Schönlieb CB. Riemannian geometry for efficient analysis of protein dynamics data. Proc Natl Acad Sci U S A 2024; 121:e2318951121. [PMID: 39121160 PMCID: PMC11331106 DOI: 10.1073/pnas.2318951121] [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: 10/30/2023] [Accepted: 06/10/2024] [Indexed: 08/11/2024] Open
Abstract
An increasingly common viewpoint is that protein dynamics datasets reside in a nonlinear subspace of low conformational energy. Ideal data analysis tools should therefore account for such nonlinear geometry. The Riemannian geometry setting can be suitable for a variety of reasons. First, it comes with a rich mathematical structure to account for a wide range of geometries that can be modeled after an energy landscape. Second, many standard data analysis tools developed for data in Euclidean space can be generalized to Riemannian manifolds. In the context of protein dynamics, a conceptual challenge comes from the lack of guidelines for constructing a smooth Riemannian structure based on an energy landscape. In addition, computational feasibility in computing geodesics and related mappings poses a major challenge. This work considers these challenges. The first part of the paper develops a local approximation technique for computing geodesics and related mappings on Riemannian manifolds in a computationally feasible manner. The second part constructs a smooth manifold and a Riemannian structure that is based on an energy landscape for protein conformations. The resulting Riemannian geometry is tested on several data analysis tasks relevant for protein dynamics data. In particular, the geodesics with given start- and end-points approximately recover corresponding molecular dynamics trajectories for proteins that undergo relatively ordered transitions with medium-sized deformations. The Riemannian protein geometry also gives physically realistic summary statistics and retrieves the underlying dimension even for large-sized deformations within seconds on a laptop.
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Affiliation(s)
- Willem Diepeveen
- Faculty of Mathematics, University of Cambridge, CB3 0WACambridge, United Kingdom
| | - Carlos Esteve-Yagüe
- Faculty of Mathematics, University of Cambridge, CB3 0WACambridge, United Kingdom
| | - Jan Lellmann
- Institute of Mathematics and Image Computing, University of Lübeck, 23562Lübeck, Germany
| | - Ozan Öktem
- Department of Mathematics, Kungliga Tekniska högskolan (KTH), 114 28Stockholm, Sweden
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3
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Kolossváry I. A Fresh Look at the Normal Mode Analysis of Proteins: Introducing Allosteric Co-Vibrational Modes. JACS AU 2024; 4:1303-1309. [PMID: 38665643 PMCID: PMC11040550 DOI: 10.1021/jacsau.4c00109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 03/28/2024] [Accepted: 03/29/2024] [Indexed: 04/28/2024]
Abstract
We propose a new way of utilizing normal modes to study protein conformational transitions. Instead of considering individual modes independently, we show that a weighted mixture of low-frequency vibrational modes can reveal dynamic information about the conformational mechanism in more detail than any single mode can. The weights in the mixed mode, termed the allosteric covibrational mode, are determined using a simple model where the conformational transition is viewed as a perturbation of the coupled harmonic oscillator associated with either of the two conformations. We demonstrate our theory in a biologically relevant example of high pharmaceutical interest involving the V617F mutation of Janus 2 tyrosine kinase (JAK2).
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Affiliation(s)
- István Kolossváry
- Department of Biomedical
Engineering, Boston University, Boston, Massachusetts 02215, United States
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4
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Khan MW, Murali A. Normal mode analysis and comparative study of intrinsic dynamics of alcohol oxidase enzymes from GMC protein family. J Biomol Struct Dyn 2023:1-16. [PMID: 37676256 DOI: 10.1080/07391102.2023.2255275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/30/2023] [Indexed: 09/08/2023]
Abstract
Glucose-Methanol-Choline (GMC) family enzymes are very important in catalyzing the oxidation of a wide range of structurally diverse substrates. Enzymes that constitute the GMC family, share a common tertiary fold but < 25% sequence identity. Cofactor FAD, FAD binding signature motif, and similar structural scaffold of the active site are common features of oxidoreductase enzymes of the GMC family. Protein functionality mainly depends on protein three-dimensional structures and dynamics. In this study, we used the normal mode analysis method to search the intrinsic dynamics of GMC family enzymes. We have explored the dynamical behavior of enzymes with unique substrate catabolism and active site characteristics from different classes of the GMC family. Analysis of individual enzymes and comparative ensemble analysis of enzymes from different classes has shown conserved dynamic motion at FAD binding sites. The present study revealed that GMC enzymes share a strong dynamic similarity (Bhattacharyya coefficient >90% and root mean squared inner product >52%) despite low sequence identity across the GMC family enzymes. The study predicts that local deformation energy between atoms of the enzyme may be responsible for the catalysis of different substrates. This study may help that intrinsic dynamics can be used to make meaningful classifications of proteins or enzymes from different organisms.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mohammad Wahab Khan
- Department of Bioinformatics, School of Life Science, Pondicherry University, Puducherry, India
| | - Ayaluru Murali
- Department of Bioinformatics, School of Life Science, Pondicherry University, Puducherry, India
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5
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Hsieh YC, Delarue M, Orland H, Koehl P. Analyzing the Geometry and Dynamics of Viral Structures: A Review of Computational Approaches Based on Alpha Shape Theory, Normal Mode Analysis, and Poisson-Boltzmann Theories. Viruses 2023; 15:1366. [PMID: 37376665 DOI: 10.3390/v15061366] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 06/05/2023] [Accepted: 06/09/2023] [Indexed: 06/29/2023] Open
Abstract
The current SARS-CoV-2 pandemic highlights our fragility when we are exposed to emergent viruses either directly or through zoonotic diseases. Fortunately, our knowledge of the biology of those viruses is improving. In particular, we have more and more structural information on virions, i.e., the infective form of a virus that includes its genomic material and surrounding protective capsid, and on their gene products. It is important to have methods that enable the analyses of structural information on such large macromolecular systems. We review some of those methods in this paper. We focus on understanding the geometry of virions and viral structural proteins, their dynamics, and their energetics, with the ambition that this understanding can help design antiviral agents. We discuss those methods in light of the specificities of those structures, mainly that they are huge. We focus on three of our own methods based on the alpha shape theory for computing geometry, normal mode analyses to study dynamics, and modified Poisson-Boltzmann theories to study the organization of ions and co-solvent and solvent molecules around biomacromolecules. The corresponding software has computing times that are compatible with the use of regular desktop computers. We show examples of their applications on some outer shells and structural proteins of the West Nile Virus.
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Affiliation(s)
- Yin-Chen Hsieh
- Institute for Arctic and Marine Biology, Department of Biosciences, Fisheries, and Economics, UiT The Arctic University of Norway, 9037 Tromso, Norway
| | - Marc Delarue
- Institut Pasteur, Université Paris-Cité and CNRS, UMR 3528, Unité Architecture et Dynamique des Macromolécules Biologiques, 75015 Paris, France
| | - Henri Orland
- Institut de Physique Théorique, CEA, CNRS, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Patrice Koehl
- Department of Computer Science, University of California, Davis, CA 95616, USA
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6
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Lichtinger SM, Biggin PC. Tackling Hysteresis in Conformational Sampling: How to Be Forgetful with MEMENTO. J Chem Theory Comput 2023. [PMID: 37285481 DOI: 10.1021/acs.jctc.3c00140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The structure of proteins has long been recognized to hold the key to understanding and engineering their function, and rapid advances in structural biology and protein structure prediction are now supplying researchers with an ever-increasing wealth of structural information. Most of the time, however, structures can only be determined in free energy minima, one at a time. While conformational flexibility may thus be inferred from static end-state structures, their interconversion mechanisms─a central ambition of structural biology─are often beyond the scope of direct experimentation. Given the dynamical nature of the processes in question, many studies have attempted to explore conformational transitions using molecular dynamics (MD). However, ensuring proper convergence and reversibility in the predicted transitions is extremely challenging. In particular, a commonly used technique to map out a path from a starting to a target conformation called steered MD (SMD) can suffer from starting-state dependence (hysteresis) when combined with techniques such as umbrella sampling (US) to compute the free energy profile of a transition. Here, we study this problem in detail on conformational changes of increasing complexity. We also present a new, history-independent approach that we term "MEMENTO" (Morphing End states by Modelling Ensembles with iNdependent TOpologies) to generate paths that alleviate hysteresis in the construction of conformational free energy profiles. MEMENTO utilizes template-based structure modelling to restore physically reasonable protein conformations based on coordinate interpolation (morphing) as an ensemble of plausible intermediates, from which a smooth path is picked. We compare SMD and MEMENTO on well-characterized test cases (the toy peptide deca-alanine and the enzyme adenylate kinase) before discussing its use in more complicated systems (the kinase P38α and the bacterial leucine transporter LeuT). Our work shows that for all but the simplest systems SMD paths should not in general be used to seed umbrella sampling or related techniques, unless the paths are validated by consistent results from biased runs in opposite directions. MEMENTO, on the other hand, performs well as a flexible tool to generate intermediate structures for umbrella sampling. We also demonstrate that extended end-state sampling combined with MEMENTO can aid the discovery of collective variables on a case-by-case basis.
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Affiliation(s)
| | - Philip C Biggin
- Department of Biochemistry, University of Oxford, Oxford OX1 3QU, U.K
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7
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Vuillemot R, Mirzaei A, Harastani M, Hamitouche I, Fréchin L, Klaholz BP, Miyashita O, Tama F, Rouiller I, Jonic S. MDSPACE: Extracting Continuous Conformational Landscapes from Cryo-EM Single Particle Datasets Using 3D-to-2D Flexible Fitting based on Molecular Dynamics Simulation. J Mol Biol 2023; 435:167951. [PMID: 36638910 DOI: 10.1016/j.jmb.2023.167951] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 12/08/2022] [Accepted: 01/03/2023] [Indexed: 01/12/2023]
Abstract
This article presents an original approach for extracting atomic-resolution landscapes of continuous conformational variability of biomolecular complexes from cryo electron microscopy (cryo-EM) single particle images. This approach is based on a new 3D-to-2D flexible fitting method, which uses molecular dynamics (MD) simulation and is embedded in an iterative conformational-landscape refinement scheme. This new approach is referred to as MDSPACE, which stands for Molecular Dynamics simulation for Single Particle Analysis of Continuous Conformational hEterogeneity. The article describes the MDSPACE approach and shows its performance using synthetic and experimental datasets.
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Affiliation(s)
- Rémi Vuillemot
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France; Department of Biochemistry & Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Victoria, Australia
| | - Alex Mirzaei
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Mohamad Harastani
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Ilyes Hamitouche
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France
| | - Léo Fréchin
- Centre for Integrative Biology, Department of Integrated Structural Biology, IGBMC-UMR 7104 CNRS, U964 Inserm, Université de Strasbourg, Strasbourg, France
| | - Bruno P Klaholz
- Centre for Integrative Biology, Department of Integrated Structural Biology, IGBMC-UMR 7104 CNRS, U964 Inserm, Université de Strasbourg, Strasbourg, France
| | | | - Florence Tama
- RIKEN Center for Computational Science, Kobe, Japan; Institute of Transformative Biomolecules, Graduate School of Science, Nagoya University, Nagoya, Japan; Department of Physics, Graduate School of Science, Nagoya University, Nagoya, Japan
| | - Isabelle Rouiller
- Department of Biochemistry & Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Victoria, Australia
| | - Slavica Jonic
- IMPMC-UMR 7590 CNRS, Sorbonne Université, Muséum National d'Histoire Naturelle, Paris, France.
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8
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López-Blanco JR, Dehouck Y, Bastolla U, Chacón P. Local Normal Mode Analysis for Fast Loop Conformational Sampling. J Chem Inf Model 2022; 62:4561-4568. [PMID: 36099639 PMCID: PMC9516680 DOI: 10.1021/acs.jcim.2c00870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
![]()
We propose and validate
a novel method to efficiently
explore local
protein loop conformations based on a new formalism for constrained
normal mode analysis (NMA) in internal coordinates. The manifold of
possible loop configurations imposed by the position and orientation
of the fixed loop ends is reduced to an orthogonal set of motions
(or modes) encoding concerted rotations of all the backbone dihedral
angles. We validate the sampling power on a set of protein loops with
highly variable experimental structures and demonstrate that our approach
can efficiently explore the conformational space of closed loops.
We also show an acceptable resemblance of the ensembles around equilibrium
conformations generated by long molecular simulations and constrained
NMA on a set of exposed and diverse loops. In comparison with other
methods, the main advantage is the lack of restrictions on the number
of dihedrals that can be altered simultaneously. Furthermore, the
method is computationally efficient since it only requires the diagonalization
of a tiny matrix, and the modes of motions are energetically contextualized
by the elastic network model, which includes both the loop and the
neighboring residues.
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Affiliation(s)
- José Ramón López-Blanco
- Department of Biological Physical Chemistry, Rocasolano Institute of Physical Chemistry, CSIC, Serrano 119, 28006 Madrid, Spain
| | - Yves Dehouck
- Centro de Biología Molecular "Severo Ochoa," CSIC-UAM, Cantoblanco, 28049 Madrid, Spain
| | - Ugo Bastolla
- Centro de Biología Molecular "Severo Ochoa," CSIC-UAM, Cantoblanco, 28049 Madrid, Spain
| | - Pablo Chacón
- Department of Biological Physical Chemistry, Rocasolano Institute of Physical Chemistry, CSIC, Serrano 119, 28006 Madrid, Spain
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9
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Hamitouche I, Jonic S. DeepHEMNMA: ResNet-based hybrid analysis of continuous conformational heterogeneity in cryo-EM single particle images. Front Mol Biosci 2022; 9:965645. [PMID: 36158571 PMCID: PMC9493108 DOI: 10.3389/fmolb.2022.965645] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Single-particle cryo-electron microscopy (cryo-EM) is a technique for biomolecular structure reconstruction from vitrified samples containing many copies of a biomolecular complex (known as single particles) at random unknown 3D orientations and positions. Cryo-EM allows reconstructing multiple conformations of the complexes from images of the same sample, which usually requires many rounds of 2D and 3D classifications to disentangle and interpret the combined conformational, orientational, and translational heterogeneity. The elucidation of different conformations is the key to understand molecular mechanisms behind the biological functions of the complexes and the key to novel drug discovery. Continuous conformational heterogeneity, due to gradual conformational transitions giving raise to many intermediate conformational states of the complexes, is both an obstacle for high-resolution 3D reconstruction of the conformational states and an opportunity to obtain information about multiple coexisting conformational states at once. HEMNMA method, specifically developed for analyzing continuous conformational heterogeneity in cryo-EM, determines the conformation, orientation, and position of the complex in each single particle image by image analysis using normal modes (the motion directions simulated for a given atomic structure or EM map), which in turn allows determining the full conformational space of the complex but at the price of high computational cost. In this article, we present a new method, referred to as DeepHEMNMA, which speeds up HEMNMA by combining it with a residual neural network (ResNet) based deep learning approach. The performance of DeepHEMNMA is shown using synthetic and experimental single particle images.
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10
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Zhang Z, Chen M, Zhan L, Zheng F, Si W, Sha J, Chen Y. Length-dependent collective vibrational dynamics in alpha-helices. Chemphyschem 2022; 23:e202200082. [PMID: 35384211 DOI: 10.1002/cphc.202200082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 04/03/2022] [Indexed: 11/06/2022]
Abstract
Functions of protein molecules in nature are closely associated with their well-defined three-dimensional structures and dynamics in body fluid. So far, many efforts have been made to reveal the relation of protein structure, dynamics, and function, but the structural origin of protein dynamics, especially for secondary structures as building blocks of conformation transition, is still ambiguous. Here we theoretically uncover the collective vibrations of elastic poly-alanine α-helices and find vibration patterns that are distinctively different over residue numbers ranging from 20 to 80. Contrary to the decreasing vibration magnitude from ends to the middle region for short helices, the vibration magnitude for long helices takes the minimum at approximately 1/5 of helix length from ends but reaches a peak at the center. Further analysis indicates that major vibrational modes of helical structures strongly depend on their residue numbers, where the twist mode dominates in the vibrations of short helices while the bend mode dominates the long ones analogous to an elastic Euler beam. The helix-coil transition pathway is also affected by the alternation of the first-order mode in helices with different lengths. The dynamic properties of the helical polypeptides are promising to be harnessed for de novo design of protein-based materials and artificial biomolecules in clinical treatments.
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Affiliation(s)
- Zhenyu Zhang
- Southeast University, School of Mechanical Engineering, School of Mechanical Engineering, No. 2, Southeast University Road, 211189, Nanjing, CHINA
| | - Mu Chen
- Southeast University, School of Mechanical Engineering, CHINA
| | - Lijian Zhan
- Southeast University, School of Mechanical Engineering, CHINA
| | - Fei Zheng
- Southeast University, School of Mechanical Engineering, CHINA
| | - Wei Si
- Southeast University, School of Mechanical Engineering, CHINA
| | - Jingjie Sha
- Southeast University, School of Mechanical Engineering, CHINA
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11
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Mechanical couplings of protein backbone and side chains exhibit scale-free network properties and specific hotspots for function. Comput Struct Biotechnol J 2021; 19:5309-5320. [PMID: 34765086 PMCID: PMC8554173 DOI: 10.1016/j.csbj.2021.09.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 09/02/2021] [Accepted: 09/05/2021] [Indexed: 11/23/2022] Open
Abstract
Statistical learning from protein dynamics unravels rigidities in interaction network. Backbone and side-chain mechanical couplings exhibit scale-free network properties. Graphical depiction of network rigidities captures sequence co-evolution patterns. Functional sites at secondary structure peripheries are mechanical hotspots. Our rigidity scores are compelling metrics for residue biological significance.
A backbone-side-chain elastic network model (bsENM) is devised in this contribution to decipher the network of molecular interactions during protein dynamics. The chemical details in 5 μs all-atom molecular dynamics (MD) simulation are mapped onto the bsENM spring constants by self-consistent iterations. The elastic parameters obtained by this structure-mechanics statistical learning are then used to construct inter-residue rigidity graphs for the chemical components in protein amino acids. A key discovery is that the mechanical coupling strengths of both backbone and side chains exhibit heavy-tailed distributions and scale-free network properties. In both rat trypsin and PDZ3 proteins, the statistically prominent modes of rigidity graphs uncover the sequence-specific coupling patterns and mechanical hotspots. Based on the contributions to graphical modes, our residue rigidity scores in backbone and side chains are found to be very useful metrics for the biological significance. Most functional sites have high residue rigidity scores in side chains while the biologically important glycines are generally next to mechanical hotspots. Furthermore, prominent modes in the rigidity graphs involving side chains oftentimes coincide with the co-evolution patterns due to evolutionary restraints. The bsENM specifically devised to resolve the protein chemical character thus provides useful means for extracting functional information from all-atom MD.
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12
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Zhang Y, Krieger J, Mikulska-Ruminska K, Kaynak B, Sorzano COS, Carazo JM, Xing J, Bahar I. State-dependent sequential allostery exhibited by chaperonin TRiC/CCT revealed by network analysis of Cryo-EM maps. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 160:104-120. [PMID: 32866476 PMCID: PMC7914283 DOI: 10.1016/j.pbiomolbio.2020.08.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 06/25/2020] [Accepted: 08/16/2020] [Indexed: 12/17/2022]
Abstract
The eukaryotic chaperonin TRiC/CCT plays a major role in assisting the folding of many proteins through an ATP-driven allosteric cycle. Recent structures elucidated by cryo-electron microscopy provide a broad view of the conformations visited at various stages of the chaperonin cycle, including a sequential activation of its subunits in response to nucleotide binding. But we lack a thorough mechanistic understanding of the structure-based dynamics and communication properties that underlie the TRiC/CCT machinery. In this study, we present a computational methodology based on elastic network models adapted to cryo-EM density maps to gain a deeper understanding of the structure-encoded allosteric dynamics of this hexadecameric machine. We have analysed several structures of the chaperonin resolved in different states toward mapping its conformational landscape. Our study indicates that the overall architecture intrinsically favours cooperative movements that comply with the structural variabilities observed in experiments. Furthermore, the individual subunits CCT1-CCT8 exhibit state-dependent sequential events at different states of the allosteric cycle. For example, in the ATP-bound state, subunits CCT5 and CCT4 selectively initiate the lid closure motions favoured by the overall architecture; whereas in the apo form of the heteromer, the subunit CCT7 exhibits the highest predisposition to structural change. The changes then propagate through parallel fluxes of allosteric signals to neighbours on both rings. The predicted state-dependent mechanisms of sequential activation provide new insights into TRiC/CCT intra- and inter-ring signal transduction events.
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Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - James Krieger
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Karolina Mikulska-Ruminska
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | | | - José-María Carazo
- Centro Nacional de Biotecnología (CSIC), Darwin, 3, 28049, Madrid, Spain
| | - Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA.
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13
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Manalastas-Cantos K, Konarev PV, Hajizadeh NR, Kikhney AG, Petoukhov MV, Molodenskiy DS, Panjkovich A, Mertens HDT, Gruzinov A, Borges C, Jeffries CM, Svergun DI, Franke D. ATSAS 3.0: expanded functionality and new tools for small-angle scattering data analysis. J Appl Crystallogr 2021; 54:343-355. [PMID: 33833657 PMCID: PMC7941305 DOI: 10.1107/s1600576720013412] [Citation(s) in RCA: 434] [Impact Index Per Article: 144.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 10/06/2020] [Indexed: 11/11/2022] Open
Abstract
The ATSAS software suite encompasses a number of programs for the processing, visualization, analysis and modelling of small-angle scattering data, with a focus on the data measured from biological macromolecules. Here, new developments in the ATSAS 3.0 package are described. They include IMSIM, for simulating isotropic 2D scattering patterns; IMOP, to perform operations on 2D images and masks; DATRESAMPLE, a method for variance estimation of structural invariants through parametric resampling; DATFT, which computes the pair distance distribution function by a direct Fourier transform of the scattering data; PDDFFIT, to compute the scattering data from a pair distance distribution function, allowing comparison with the experimental data; a new module in DATMW for Bayesian consensus-based concentration-independent molecular weight estimation; DATMIF, an ab initio shape analysis method that optimizes the search model directly against the scattering data; DAMEMB, an application to set up the initial search volume for multiphase modelling of membrane proteins; ELLLIP, to perform quasi-atomistic modelling of liposomes with elliptical shapes; NMATOR, which models conformational changes in nucleic acid structures through normal mode analysis in torsion angle space; DAMMIX, which reconstructs the shape of an unknown intermediate in an evolving system; and LIPMIX and BILMIX, for modelling multilamellar and asymmetric lipid vesicles, respectively. In addition, technical updates were deployed to facilitate maintainability of the package, which include porting the PRIMUS graphical interface to Qt5, updating SASpy - a PyMOL plugin to run a subset of ATSAS tools - to be both Python 2 and 3 compatible, and adding utilities to facilitate mmCIF compatibility in future ATSAS releases. All these features are implemented in ATSAS 3.0, freely available for academic users at https://www.embl-hamburg.de/biosaxs/software.html.
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Affiliation(s)
- Karen Manalastas-Cantos
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Petr V. Konarev
- A.V. Shubnikov Institute of Crystallography, Federal Scientific Research Centre ‘Crystallography and Photonics’ of Russian Academy of Sciences, Leninsky prospekt 59, Moscow, 119333, Russian Federation
| | - Nelly R. Hajizadeh
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Alexey G. Kikhney
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Maxim V. Petoukhov
- A.V. Shubnikov Institute of Crystallography, Federal Scientific Research Centre ‘Crystallography and Photonics’ of Russian Academy of Sciences, Leninsky prospekt 59, Moscow, 119333, Russian Federation
| | - Dmitry S. Molodenskiy
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Alejandro Panjkovich
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Haydyn D. T. Mertens
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Andrey Gruzinov
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Clemente Borges
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Cy M. Jeffries
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Dmitri I. Svergun
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
| | - Daniel Franke
- European Molecular Biology Laboratory, Hamburg Site, Notkestrasse 85, Building 25 A, Hamburg, 22607, Germany
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14
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Bourassin N, Baaden M, Lojou E, Sacquin-Mora S. Implicit Modeling of the Impact of Adsorption on Solid Surfaces for Protein Mechanics and Activity with a Coarse-Grained Representation. J Phys Chem B 2020; 124:8516-8523. [PMID: 32924507 DOI: 10.1021/acs.jpcb.0c05347] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Surface immobilized enzymes play a key role in numerous biotechnological applications such as biosensors, biofuel cells, or biocatalytic synthesis. As a consequence, the impact of adsorption on the enzyme structure, dynamics, and function needs to be understood on the molecular level as it is critical for the improvement of these technologies. With this perspective in mind, we used a theoretical approach for investigating local protein flexibility on the residue scale that couples a simplified protein representation with an elastic network and Brownian dynamics simulations. The impact of protein adsorption on a solid surface is implicitly modeled via additional external constraints between the residues in contact with the surface. We first performed calculations on a redox enzyme, bilirubin oxidase (BOD) from M. verrucaria, to study the impact of adsorption on its mechanical properties. The resulting rigidity profiles show that, in agreement with the available experimental data, the mechanical variations observed in the adsorbed BOD will depend on its orientation and its anchor residues (i.e., residues that are in contact with the functionalized surface). Additional calculations on ribonuclease A and nitroreductase shed light on how seemingly stable adsorbed enzymes can nonetheless display an important decrease in their catalytic activity resulting from a perturbation of their mechanics and internal dynamics.
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Affiliation(s)
- Nicolas Bourassin
- CNRS, Laboratoire de Biochimie Théorique, UPR 9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France.,Institut de Biologie Physico-Chimique-Fondation Edmond de Rotschild, PSL Research University, 75006 Paris, France
| | - Marc Baaden
- CNRS, Laboratoire de Biochimie Théorique, UPR 9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France.,Institut de Biologie Physico-Chimique-Fondation Edmond de Rotschild, PSL Research University, 75006 Paris, France
| | - Elisabeth Lojou
- CNRS, Bioénergétique et Ingénierie des Protéines, UMR 7281, Aix Marseille Univ, 31, chemin Joseph Aiguier, CS 70071, 13402 Cedex 09 Marseille, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR 9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France.,Institut de Biologie Physico-Chimique-Fondation Edmond de Rotschild, PSL Research University, 75006 Paris, France
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15
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Orellana L, Gustavsson J, Bergh C, Yoluk O, Lindahl E. eBDIMS server: protein transition pathways with ensemble analysis in 2D-motion spaces. Bioinformatics 2020; 35:3505-3507. [PMID: 30838394 PMCID: PMC6748756 DOI: 10.1093/bioinformatics/btz104] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2018] [Revised: 12/30/2018] [Accepted: 02/15/2019] [Indexed: 11/15/2022] Open
Abstract
SUMMARY Understanding how proteins transition between different conformers, and how conformers relate to each other in terms of structure and function, is not trivial. Here, we present an online tool for transition pathway generation between two protein conformations using Elastic Network Driven Brownian Dynamics Importance Sampling, a coarse-grained simulation algorithm, which spontaneously predicts transition intermediates trapped experimentally. In addition to path-generation, the server provides an interactive 2D-motion landscape graphical representation of the transitions or any additional conformers to explore their structural relationships. AVAILABILITY AND IMPLEMENTATION eBDIMS is available online: http://ebdims.biophysics.se/ or as standalone software: https://github.com/laura-orellana/eBDIMS, https://github.com/cabergh/eBDIMS. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Laura Orellana
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Johan Gustavsson
- Department of Computational Science and Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Cathrine Bergh
- Department of Applied Physics, Swedish e-Science Research Center, KTH Royal Institute of Technology, Solna, Sweden
| | - Ozge Yoluk
- Department of Applied Physics, Swedish e-Science Research Center, KTH Royal Institute of Technology, Solna, Sweden
| | - Erik Lindahl
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Stockholm, Sweden.,Department of Applied Physics, Swedish e-Science Research Center, KTH Royal Institute of Technology, Solna, Sweden
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16
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Shape-preserving elastic solid models of macromolecules. PLoS Comput Biol 2020; 16:e1007855. [PMID: 32407309 PMCID: PMC7297265 DOI: 10.1371/journal.pcbi.1007855] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 06/09/2020] [Accepted: 04/07/2020] [Indexed: 02/07/2023] Open
Abstract
Mass-spring models have been a standard approach in molecular modeling for the last few decades, such as elastic network models (ENMs) that are widely used for normal mode analysis. In this work, we present a vastly different elastic solid model (ESM) of macromolecules that shares the same simplicity and efficiency as ENMs in producing the equilibrium dynamics and moreover, offers some significant new features that may greatly benefit the research community. ESM is different from ENM in that it treats macromolecules as elastic solids. Our particular version of ESM presented in this work, named αESM, captures the shape of a given biomolecule most economically using alpha shape, a well-established technique from the computational geometry community. Consequently, it can produce most economical coarse-grained models while faithfully preserving the shape and thus makes normal mode computations and visualization of extremely large complexes more manageable. Secondly, as a solid model, ESM’s close link to finite element analysis renders it ideally suited for studying mechanical responses of macromolecules under external force. Lastly, we show that ESM can be applied also to structures without atomic coordinates such as those from cryo-electron microscopy. The complete MATLAB code of αESM is provided. Mass-spring models have been a standard approach in classical molecular modeling where atoms are modeled as spheres with a mass and their interactions modeled as springs. The models have been extremely successful. Thinking ahead, however, as molecular systems of our interest grow more quickly in size or dimension than what our computation resources can keep up with, some adjustments in methodology are timely. This work presents a vastly different elastic solid model (ESM) of macromolecules that shares the same simplicity and efficiency as mass-spring models in producing the equilibrium dynamics and moreover, offers some unique features that make it suitable for much larger systems. ESM is different from ENMs in that it treats macromolecules as elastic solids. Our particular version of ESM model presented in this work, named αESM, captures the shape of a given biomolecule most economically using alpha shape, a well-established technique from the computational geometry community. Consequently, it can produce most economical coarse-grained models while faithfully preserving the shape. ESM can be applied also to structures without atomic coordinates such as those from cryo-electron microscopy.
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17
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Zhang S, Li H, Krieger JM, Bahar I. Shared Signature Dynamics Tempered by Local Fluctuations Enables Fold Adaptability and Specificity. Mol Biol Evol 2020; 36:2053-2068. [PMID: 31028708 PMCID: PMC6736388 DOI: 10.1093/molbev/msz102] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Recent studies have drawn attention to the evolution of protein dynamics, in addition to sequence and structure, based on the premise structure-encodes-dynamics-encodes-function. Of interest is to understand how functional differentiation is accomplished while maintaining the fold, or how intrinsic dynamics plays out in the evolution of structural variations and functional specificity. We performed a systematic computational analysis of 26,899 proteins belonging to 116 CATH superfamilies. Characterizing cooperative mechanisms and convergent/divergent features that underlie the shared/differentiated dynamics of family members required a methodology that lends itself to efficient analyses of large ensembles of proteins. We therefore introduced, SignDy, an integrated pipeline for evaluating the signature dynamics of families based on elastic network models. Our analysis confirmed that family members share conserved, highly cooperative (global) modes of motion. Importantly, our analysis discloses a subset of motions that sharply distinguishes subfamilies, which lie in a low-to-intermediate frequency regime of the mode spectrum. This regime has maximal impact on functional differentiation of families into subfamilies, while being evolutionarily conserved among subfamily members. Notably, the high-frequency end of the spectrum also reveals evolutionary conserved features across and within subfamilies; but in sharp contrast to global motions, high-frequency modes are minimally collective. Modulation of robust/conserved global dynamics by low-to-intermediate frequency fluctuations thus emerges as a versatile mechanism ensuring the adaptability of selected folds and the specificity of their subfamilies. SignDy further allows for dynamics-based categorization as a new layer of information relevant to distinctive mechanisms of action of subfamilies, beyond sequence or structural classifications.
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Affiliation(s)
- She Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Hongchun Li
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - James M Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA
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18
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Bauer JA, Pavlović J, Bauerová-Hlinková V. Normal Mode Analysis as a Routine Part of a Structural Investigation. Molecules 2019; 24:E3293. [PMID: 31510014 PMCID: PMC6767145 DOI: 10.3390/molecules24183293] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 08/30/2019] [Accepted: 08/30/2019] [Indexed: 12/13/2022] Open
Abstract
Normal mode analysis (NMA) is a technique that can be used to describe the flexible states accessible to a protein about an equilibrium position. These states have been shown repeatedly to have functional significance. NMA is probably the least computationally expensive method for studying the dynamics of macromolecules, and advances in computer technology and algorithms for calculating normal modes over the last 20 years have made it nearly trivial for all but the largest systems. Despite this, it is still uncommon for NMA to be used as a component of the analysis of a structural study. In this review, we will describe NMA, outline its advantages and limitations, explain what can and cannot be learned from it, and address some criticisms and concerns that have been voiced about it. We will then review the most commonly used techniques for reducing the computational cost of this method and identify the web services making use of these methods. We will illustrate several of their possible uses with recent examples from the literature. We conclude by recommending that NMA become one of the standard tools employed in any structural study.
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Affiliation(s)
- Jacob A Bauer
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava, Slovakia.
| | - Jelena Pavlović
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava, Slovakia
| | - Vladena Bauerová-Hlinková
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava, Slovakia
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19
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Zhang PF, Su JG. Identification of key sites controlling protein functional motions by using elastic network model combined with internal coordinates. J Chem Phys 2019; 151:045101. [PMID: 31370540 DOI: 10.1063/1.5098542] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
The elastic network model (ENM) is an effective method to extract the intrinsic dynamical properties encoded in protein tertiary structures. We have proposed a new ENM-based analysis method to reveal the motion modes directly responsible for a specific protein function, in which an internal coordinate related to the specific function was introduced to construct the internal/Cartesian hybrid coordinate space. In the present work, the function-related internal coordinates combined with a linear perturbation method were applied to identify the key sites controlling specific protein functional motions. The change in the fluctuations of the internal coordinate in response to residue perturbation was calculated in the hybrid coordinate space by using the linear response theory. The residues with the large fluctuation changes were identified to be the key sites that allosterically control the specific protein function. Two proteins, i.e., human DNA polymerase β and the chaperonin from Methanococcus maripaludis, were investigated as case studies, in which several collective and local internal coordinates were applied to identify the functionally key residues of these two studied proteins. The calculation results are consistent with the experimental observations. It is found that different collective internal coordinates lead to similar results, where the predicted functionally key sites are located at similar positions in the protein structure. While for the local internal coordinates, the predicted key sites tend to be situated at the region near to the coordinate-involving residues. Our studies provide a starting point for further exploring other function-related internal coordinates for other interesting proteins.
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Affiliation(s)
- Peng Fei Zhang
- Key Laboratory for Microstructural Material Physics of Hebei Province, College of Science, Yanshan University, Qinhuangdao 066004, China
| | - Ji Guo Su
- Key Laboratory for Microstructural Material Physics of Hebei Province, College of Science, Yanshan University, Qinhuangdao 066004, China
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20
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Sacquin-Mora S. Coarse-grain simulations on NMR conformational ensembles highlight functional residues in proteins. J R Soc Interface 2019; 16:20190075. [PMID: 31288649 DOI: 10.1098/rsif.2019.0075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Dynamics are a key feature of protein function, and this is especially true of gating residues, which occupy cavity or tunnel lining positions in the protein structure, and will reversibly switch between open and closed conformations in order to control the diffusion of small molecules within a protein's internal matrix. Earlier work on globins and hydrogenases have shown that these gating residues can be detected using a multiscale scheme combining all-atom classic molecular dynamics simulations and coarse-grain calculations of the resulting conformational ensemble mechanical properties. Here, we show that the structural variations observed in the conformational ensembles produced by NMR spectroscopy experiments are sufficient to induce noticeable mechanical changes in a protein, which in turn can be used to identify residues important for function and forming a mechanical nucleus in the protein core. This new approach, which combines experimental data and rapid coarse-grain calculations and no longer needs to resort to time-consuming all-atom simulations, was successfully applied to five different protein families.
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Affiliation(s)
- Sophie Sacquin-Mora
- Laboratoire de Biochimie Théorique, CNRS UPR9080, Institut de Biologie Physico-Chimique , 13 rue Pierre et Marie Curie, 75005 Paris , France
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21
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Multiscale modeling of proteins interaction with functionalized nanoparticles. Curr Opin Colloid Interface Sci 2019. [DOI: 10.1016/j.cocis.2018.12.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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22
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Mikulska-Ruminska K, Shrivastava I, Krieger J, Zhang S, Li H, Bayır H, Wenzel SE, VanDemark AP, Kagan VE, Bahar I. Characterization of Differential Dynamics, Specificity, and Allostery of Lipoxygenase Family Members. J Chem Inf Model 2019; 59:2496-2508. [PMID: 30762363 PMCID: PMC6541894 DOI: 10.1021/acs.jcim.9b00006] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Accurate modeling of structural dynamics of proteins and their differentiation across different species can help us understand generic mechanisms of function shared by family members and the molecular basis of the specificity of individual members. We focused here on the family of lipoxygenases, enzymes that catalyze lipid oxidation, the mammalian and bacterial structures of which have been elucidated. We present a systematic method of approach for characterizing the sequence, structure, dynamics, and allosteric signaling properties of these enzymes using a combination of structure-based models and methods and bioinformatics tools applied to a data set of 88 structures. The analysis elucidates the signature dynamics of the lipoxygenase family and its differentiation among members, as well as key sites that enable its adaptation to specific substrate binding and allosteric activity.
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Affiliation(s)
- Karolina Mikulska-Ruminska
- Institute of Physics, Department of Biophysics and Medical Physics , Nicolaus Copernicus University , 87-100 Torun , Poland
| | | | | | | | | | | | | | | | - Valerian E Kagan
- Laboratory of Navigational Redox Lipidomics , I M Sechenov Moscow State Medical University , Moskva 119146 , Russia
| | - Ivet Bahar
- Mol & Cell Cancer Biology , UPMC Hillman Cancer Center , Pittsburgh , Pennsylvania 15232 , United States
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23
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Frezza E, Lavery R. Internal Coordinate Normal Mode Analysis: A Strategy To Predict Protein Conformational Transitions. J Phys Chem B 2019; 123:1294-1301. [DOI: 10.1021/acs.jpcb.8b11913] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Elisa Frezza
- MMSB, UMR 5086 CNRS/Univ. Lyon I, Institut de Biologie et Chimie des Protéines, 7 passage du Vercors, Lyon 69367, France
| | - Richard Lavery
- MMSB, UMR 5086 CNRS/Univ. Lyon I, Institut de Biologie et Chimie des Protéines, 7 passage du Vercors, Lyon 69367, France
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24
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Zhu Q, Yuan Y, Ma J, Dong H. A Data‐Driven Accelerated Sampling Method for Searching Functional States of Proteins. ADVANCED THEORY AND SIMULATIONS 2019. [DOI: 10.1002/adts.201800171] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Qiang Zhu
- Key Laboratory of Mesoscopic Chemistry of Ministry of EducationInstitute of Theoretical and Computational Chemistry School of Chemistry and Chemical EngineeringNanjing University Nanjing 210023 P. R. China
- Kuang Yaming Honors SchoolNanjing University Nanjing 210023 P. R. China
| | - Yigao Yuan
- Kuang Yaming Honors SchoolNanjing University Nanjing 210023 P. R. China
| | - Jing Ma
- Key Laboratory of Mesoscopic Chemistry of Ministry of EducationInstitute of Theoretical and Computational Chemistry School of Chemistry and Chemical EngineeringNanjing University Nanjing 210023 P. R. China
| | - Hao Dong
- Kuang Yaming Honors SchoolNanjing University Nanjing 210023 P. R. China
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25
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Sorzano COS, Jiménez A, Mota J, Vilas JL, Maluenda D, Martínez M, Ramírez-Aportela E, Majtner T, Segura J, Sánchez-García R, Rancel Y, del Caño L, Conesa P, Melero R, Jonic S, Vargas J, Cazals F, Freyberg Z, Krieger J, Bahar I, Marabini R, Carazo JM. Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy. Acta Crystallogr F Struct Biol Commun 2019; 75:19-32. [PMID: 30605122 PMCID: PMC6317454 DOI: 10.1107/s2053230x18015108] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 10/26/2018] [Indexed: 11/10/2022] Open
Abstract
Single-particle analysis by electron microscopy is a well established technique for analyzing the three-dimensional structures of biological macromolecules. Besides its ability to produce high-resolution structures, it also provides insights into the dynamic behavior of the structures by elucidating their conformational variability. Here, the different image-processing methods currently available to study continuous conformational changes are reviewed.
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Affiliation(s)
| | - A. Jiménez
- National Center of Biotechnology (CSIC), Spain
| | - J. Mota
- National Center of Biotechnology (CSIC), Spain
| | - J. L. Vilas
- National Center of Biotechnology (CSIC), Spain
| | - D. Maluenda
- National Center of Biotechnology (CSIC), Spain
| | - M. Martínez
- National Center of Biotechnology (CSIC), Spain
| | | | - T. Majtner
- National Center of Biotechnology (CSIC), Spain
| | - J. Segura
- National Center of Biotechnology (CSIC), Spain
| | | | - Y. Rancel
- National Center of Biotechnology (CSIC), Spain
| | - L. del Caño
- National Center of Biotechnology (CSIC), Spain
| | - P. Conesa
- National Center of Biotechnology (CSIC), Spain
| | - R. Melero
- National Center of Biotechnology (CSIC), Spain
| | - S. Jonic
- Sorbonne Université, UMR CNRS 7590, Muséum National d’Histoire Naturelle, IRD, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Paris, France
| | | | - F. Cazals
- Inria Sophia Antipolis – Méditerranée, France
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26
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Echave J. Beyond Stability Constraints: A Biophysical Model of Enzyme Evolution with Selection on Stability and Activity. Mol Biol Evol 2018; 36:613-620. [DOI: 10.1093/molbev/msy244] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Affiliation(s)
- Julian Echave
- Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín (UNSAM), Buenos Aires, Argentina
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27
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Togashi Y, Flechsig H. Coarse-Grained Protein Dynamics Studies Using Elastic Network Models. Int J Mol Sci 2018; 19:ijms19123899. [PMID: 30563146 PMCID: PMC6320916 DOI: 10.3390/ijms19123899] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 11/28/2018] [Accepted: 12/03/2018] [Indexed: 01/03/2023] Open
Abstract
Elastic networks have been used as simple models of proteins to study their slow structural dynamics. They consist of point-like particles connected by linear Hookean springs and hence are convenient for linear normal mode analysis around a given reference structure. Furthermore, dynamic simulations using these models can provide new insights. As the computational cost associated with these models is considerably lower compared to that of all-atom models, they are also convenient for comparative studies between multiple protein structures. In this review, we introduce examples of coarse-grained molecular dynamics studies using elastic network models and their derivatives, focusing on the nonlinear phenomena, and discuss their applicability to large-scale macromolecular assemblies.
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Affiliation(s)
- Yuichi Togashi
- Research Center for the Mathematics on Chromatin Live Dynamics (RcMcD), Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8526, Japan.
- RIKEN Center for Biosystems Dynamics Research (BDR), 6-2-3 Furuedai, Suita, Osaka 565-0874, Japan.
- Cybermedia Center, Osaka University, 5-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan.
| | - Holger Flechsig
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa 920-1192, Japan.
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28
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Advances in coarse-grained modeling of macromolecular complexes. Curr Opin Struct Biol 2018; 52:119-126. [PMID: 30508766 DOI: 10.1016/j.sbi.2018.11.005] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 11/05/2018] [Accepted: 11/17/2018] [Indexed: 01/12/2023]
Abstract
Recent progress in coarse-grained (CG) molecular modeling and simulation has facilitated an influx of computational studies on biological macromolecules and their complexes. Given the large separation of length-scales and time-scales that dictate macromolecular biophysics, CG modeling and simulation are well-suited to bridge the microscopic and mesoscopic or macroscopic details observed from all-atom molecular simulations and experiments, respectively. In this review, we first summarize recent innovations in the development of CG models, which broadly include structure-based, knowledge-based, and dynamics-based approaches. We then discuss recent applications of different classes of CG models to explore various macromolecular complexes. Finally, we conclude with an outlook for the future in this ever-growing field of biomolecular modeling.
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29
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Modeling of Protein Structural Flexibility and Large-Scale Dynamics: Coarse-Grained Simulations and Elastic Network Models. Int J Mol Sci 2018; 19:ijms19113496. [PMID: 30404229 PMCID: PMC6274762 DOI: 10.3390/ijms19113496] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 10/29/2018] [Accepted: 10/31/2018] [Indexed: 12/13/2022] Open
Abstract
Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this minireview, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions, and highly simplified structure-based elastic network models of protein flexibility. In contrast to classical all-atom molecular dynamics, the modeling strategies discussed here allow the quite accurate modeling of much larger systems and longer-time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.
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30
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Coarse-grained dynamics of supramolecules: Conformational changes in outer shells of Dengue viruses. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2018; 143:20-37. [PMID: 30273615 DOI: 10.1016/j.pbiomolbio.2018.09.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 09/22/2018] [Accepted: 09/24/2018] [Indexed: 01/12/2023]
Abstract
While structural data on viruses are more and more common, information on their dynamics is much harder to obtain as those viruses form very large molecular complexes. In this paper, we propose a new method for computing the coarse-grained normal modes of such supra-molecules, NormalGo. A new formalism is developed to represent the Hessian of a quadratic potential using tensor products. This formalism is applied to the Tirion elastic potential, as well as to a Gō like potential. When combined with a fast method for computing a select set of eigenpairs of the Hessian, this new formalism enables the computation of thousands of normal modes of a full viral shell with more than one hundred thousand atoms in less than 2 h on a standard desktop computer. We then compare the two coarse-grained potentials. We show that, despite significant differences in their formulations, the Tirion and the Gō like potentials capture very similar dynamics characteristics of the molecule under study. However, we find that the Gō like potential should be preferred as it leads to less local deformations in the structure of the molecule during normal mode dynamics. Finally, we use NormalGo to characterize the structural transitions that occur when FAB fragments bind to the icosahedral outer shell of serotype 3 of the Dengue virus. We have identified residues at the surface of the outer shell that are important for the transition between the FAB-free and FAB-bound conformations, and therefore potentially useful for the design of antibodies to Dengue viruses.
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31
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Mechanical variations in proteins with large-scale motions highlight the formation of structural locks. J Struct Biol 2018; 203:195-204. [DOI: 10.1016/j.jsb.2018.05.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Revised: 05/18/2018] [Accepted: 05/22/2018] [Indexed: 12/18/2022]
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Hodges M, Barahona M, Yaliraki SN. Allostery and cooperativity in multimeric proteins: bond-to-bond propensities in ATCase. Sci Rep 2018; 8:11079. [PMID: 30038211 PMCID: PMC6056424 DOI: 10.1038/s41598-018-27992-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 06/13/2018] [Indexed: 11/08/2022] Open
Abstract
Aspartate carbamoyltransferase (ATCase) is a large dodecameric enzyme with six active sites that exhibits allostery: its catalytic rate is modulated by the binding of various substrates at distal points from the active sites. A recently developed method, bond-to-bond propensity analysis, has proven capable of predicting allosteric sites in a wide range of proteins using an energy-weighted atomistic graph obtained from the protein structure and given knowledge only of the location of the active site. Bond-to-bond propensity establishes if energy fluctuations at given bonds have significant effects on any other bond in the protein, by considering their propagation through the protein graph. In this work, we use bond-to-bond propensity analysis to study different aspects of ATCase activity using three different protein structures and sources of fluctuations. First, we predict key residues and bonds involved in the transition between inactive (T) and active (R) states of ATCase by analysing allosteric substrate binding as a source of energy perturbations in the protein graph. Our computational results also indicate that the effect of multiple allosteric binding is non linear: a switching effect is observed after a particular number and arrangement of substrates is bound suggesting a form of long range communication between the distantly arranged allosteric sites. Second, cooperativity is explored by considering a bisubstrate analogue as the source of energy fluctuations at the active site, also leading to the identification of highly significant residues to the T ↔ R transition that enhance cooperativity across active sites. Finally, the inactive (T) structure is shown to exhibit a strong, non linear communication between the allosteric sites and the interface between catalytic subunits, rather than the active site. Bond-to-bond propensity thus offers an alternative route to explain allosteric and cooperative effects in terms of detailed atomistic changes to individual bonds within the protein, rather than through phenomenological, global thermodynamic arguments.
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Affiliation(s)
- Maxwell Hodges
- Department of Chemistry, Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom
- Institute of Chemical Biology, Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom
| | - Mauricio Barahona
- Department of Mathematics, Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom
- Institute of Chemical Biology, Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom
| | - Sophia N Yaliraki
- Department of Chemistry, Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom.
- Institute of Chemical Biology, Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom.
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33
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Abdizadeh H, Atilgan AR, Atilgan C, Dedeoglu B. Computational approaches for deciphering the equilibrium and kinetic properties of iron transport proteins. Metallomics 2018; 9:1513-1533. [PMID: 28967944 DOI: 10.1039/c7mt00216e] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
With the advances in three-dimensional structure determination techniques, high quality structures of the iron transport proteins transferrin and the bacterial ferric binding protein (FbpA) have been deposited in the past decade. These are proteins of relatively large size, and developments in hardware and software have only recently made it possible to study their dynamics using standard computational resources. We review computational techniques towards understanding the equilibrium and kinetic properties of iron transport proteins under different environmental conditions. At the level of detail that requires quantum chemical treatments, the octahedral geometry around iron has been scrutinized and it has been established that the iron coordinating tyrosines are in an unusual deprotonated state. At the atomistic level, both the N-lobe and the full bilobal structure of transferrin have been studied under varying conditions of pH, ionic strength and binding of other metal ions by molecular dynamics (MD) simulations. These studies have allowed questions to be answered, among others, on the function of second shell residues in iron release, the role of synergistic anions in preparing the active site for iron binding, and the differences between the kinetics of the N- and the C-lobe. MD simulations on FbpA have led to the detailed observation of the binding kinetics of phosphate to the apo form, and to the conformational preferences of the holo form under conditions mimicking the environmental niches provided by the periplasmic space. To study the dynamics of these proteins with their receptors, one must resort to coarse-grained methodologies, since these systems are prohibitively large for atomistic simulations. A study of the complex of human transferrin (hTf) with its pathogenic receptor by such methods has revealed a potential mechanistic explanation for the defense mechanism that arises in evolutionary warfare. Meanwhile, the motions in the transferrin receptor bound hTf have been shown to disfavor apo hTf dissociation, explaining why the two proteins remain in complex during the recycling process from the endosome to the cell surface. Open problems and possible technological applications related to metal ion binding-release in iron transport proteins that may be handled by hybrid use of quantum mechanical, MD and coarse-grained approaches are discussed.
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Affiliation(s)
- H Abdizadeh
- Faculty of Engineering and Natural Sciences, Sabancı University, Orhanlı 34956, Tuzla, Istanbul, Turkey.
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34
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Koehl P. Large Eigenvalue Problems in Coarse-Grained Dynamic Analyses of Supramolecular Systems. J Chem Theory Comput 2018; 14:3903-3919. [DOI: 10.1021/acs.jctc.8b00338] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Patrice Koehl
- Department of Computer Sciences and Genome Center, University of California, Davis, California 95616, United States
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35
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Dutta S, Eckmann JP, Libchaber A, Tlusty T. Green function of correlated genes in a minimal mechanical model of protein evolution. Proc Natl Acad Sci U S A 2018; 115:E4559-E4568. [PMID: 29712824 PMCID: PMC5960285 DOI: 10.1073/pnas.1716215115] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The function of proteins arises from cooperative interactions and rearrangements of their amino acids, which exhibit large-scale dynamical modes. Long-range correlations have also been revealed in protein sequences, and this has motivated the search for physical links between the observed genetic and dynamic cooperativity. We outline here a simplified theory of protein, which relates sequence correlations to physical interactions and to the emergence of mechanical function. Our protein is modeled as a strongly coupled amino acid network with interactions and motions that are captured by the mechanical propagator, the Green function. The propagator describes how the gene determines the connectivity of the amino acids and thereby, the transmission of forces. Mutations introduce localized perturbations to the propagator that scatter the force field. The emergence of function is manifested by a topological transition when a band of such perturbations divides the protein into subdomains. We find that epistasis-the interaction among mutations in the gene-is related to the nonlinearity of the Green function, which can be interpreted as a sum over multiple scattering paths. We apply this mechanical framework to simulations of protein evolution and observe long-range epistasis, which facilitates collective functional modes.
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Affiliation(s)
- Sandipan Dutta
- Center for Soft and Living Matter, Institute for Basic Science, Ulsan 44919, Korea
| | - Jean-Pierre Eckmann
- Département de Physique Théorique and Section de Mathématiques, Université de Genève, CH-1211 Geneva 4, Switzerland
| | - Albert Libchaber
- Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 10021;
| | - Tsvi Tlusty
- Center for Soft and Living Matter, Institute for Basic Science, Ulsan 44919, Korea;
- Department of Physics, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
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36
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Devaurs D, Papanastasiou M, Antunes DA, Abella JR, Moll M, Ricklin D, Lambris JD, Kavraki LE. Native State of Complement Protein C3d Analysed via Hydrogen Exchange and Conformational Sampling. INTERNATIONAL JOURNAL OF COMPUTATIONAL BIOLOGY AND DRUG DESIGN 2018; 11:90-113. [PMID: 30700993 PMCID: PMC6349257 DOI: 10.1504/ijcbdd.2018.090834] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Hydrogen/deuterium exchange detected by mass spectrometry (HDXMS) provides valuable information on protein structure and dynamics. Although HDX-MS data is often interpreted using crystal structures, it was suggested that conformational ensembles produced by molecular dynamics simulations yield more accurate interpretations. In this paper, we analyse the complement protein C3d by performing an HDX-MS experiment, and evaluate several interpretation methodologies using an existing prediction model to derive HDX-MS data from protein structure. To interpret and refine C3d's HDX-MS data, we look for a conformation (or conformational ensemble) of C3d that allows computationally replicating this data. We confirm that crystal structures are not a good choice and suggest that conformational ensembles produced by molecular dynamics simulations might not always be satisfactory either. Finally, we show that coarse-grained conformational sampling of C3d produces a conformation from which its HDX-MS data can be replicated and refined.
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Affiliation(s)
- Didier Devaurs
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Malvina Papanastasiou
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
| | - Dinler A Antunes
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Jayvee R Abella
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Mark Moll
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Daniel Ricklin
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
| | - John D Lambris
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lydia E Kavraki
- Department of Computer Science, Rice University, Houston, TX, USA
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37
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Allosteric Modulation of Intact γ-Secretase Structural Dynamics. Biophys J 2018; 113:2634-2649. [PMID: 29262358 DOI: 10.1016/j.bpj.2017.10.012] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 09/26/2017] [Accepted: 10/10/2017] [Indexed: 12/20/2022] Open
Abstract
As a protease complex involved in the cleavage of amyloid precursor proteins that lead to the formation of amyloid β fibrils implicated in Alzheimer's disease, γ-secretase is an important target for developing therapeutics against Alzheimer's disease. γ-secretase is composed of four subunits: nicastrin (NCT) in the extracellular (EC) domain, presenilin-1 (PS1), anterior pharynx defective 1, and presenilin enhancer 2 in the transmembrane (TM) domain. NCT and PS1 play important roles in binding amyloid β precursor proteins and modulating PS1 catalytic activity. Yet, the molecular mechanisms of coupling between substrate/modulator binding and catalytic activity remain to be elucidated. Recent determination of intact human γ-secretase cryo-electron microscopy structure has opened the way for a detailed investigation of the structural dynamics of this complex. Our analysis, based on a membrane-coupled anisotropic network model, reveals two types of NCT motions, bending and twisting, with respect to PS1. These underlie the fluctuations between the "open" and "closed" states of the lid-like NCT with respect to a hydrophilic loop 1 (HL1) on PS1, thus allowing or blocking access of the substrate peptide (EC portion) to HL1 and to the neighboring helix TM2. In addition to this alternating access mechanism, fluctuations in the volume of the PS1 central cavity facilitate the exposure of the catalytic site for substrate cleavage. Druggability simulations show that γ-secretase presents several hot spots for either orthosteric or allosteric inhibition of catalytic activity, consistent with experimental data. In particular, a hinge region at the interface between the EC and TM domains, near the interlobe groove of NCT, emerges as an allo-targeting site that would impact the coupling between HL1/TM2 and the catalytic pocket, opening, to our knowledge, new avenues for structure-based design of novel allosteric modulators of γ-secretase protease activity.
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38
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Dorantes-Gilardi R, Bourgeat L, Pacini L, Vuillon L, Lesieur C. In proteins, the structural responses of a position to mutation rely on the Goldilocks principle: not too many links, not too few. Phys Chem Chem Phys 2018; 20:25399-25410. [DOI: 10.1039/c8cp04530e] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
A disease has distinct genetic and molecular hallmarks such as sequence variants that are likely to produce the alternative protein structures accountable for individual responses to drugs and disease development.
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Affiliation(s)
| | | | - Lorenza Pacini
- Institut Rhônalpin des systèmes complexes
- IXXI-ENS-Lyon
- Lyon
- France
- AMPERE
| | - Laurent Vuillon
- LAMA
- Univ. Savoie Mont Blanc
- CNRS, LAMA
- 73376 Le Bourget du Lac
- France
| | - Claire Lesieur
- Institut Rhônalpin des systèmes complexes
- IXXI-ENS-Lyon
- Lyon
- France
- AMPERE
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39
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Computational Methods for Efficient Sampling of Protein Landscapes and Disclosing Allosteric Regions. COMPUTATIONAL MOLECULAR MODELLING IN STRUCTURAL BIOLOGY 2018; 113:33-63. [DOI: 10.1016/bs.apcsb.2018.06.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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40
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Bope CD, Tong D, Li X, Lu L. Fluctuation matching approach for elastic network model and structure-based model of biomacromolecules. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2017; 128:100-112. [DOI: 10.1016/j.pbiomolbio.2016.12.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Revised: 11/25/2016] [Accepted: 12/19/2016] [Indexed: 10/24/2022]
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41
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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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42
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Lv D, Gong W, Zhang Y, Liu Y, Li C. A coarse-grained method to predict the open-to-closed behavior of glutamine binding protein. Chem Phys 2017. [DOI: 10.1016/j.chemphys.2017.05.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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43
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Abstract
X-ray scattering is uniquely suited to the study of disordered systems and thus has the potential to provide insight into dynamic processes where diffraction methods fail. In particular, while X-ray crystallography has been a staple of structural biology for more than half a century and will continue to remain so, a major limitation of this technique has been the lack of dynamic information. Solution X-ray scattering has become an invaluable tool in structural and mechanistic studies of biological macromolecules where large conformational changes are involved. Such systems include allosteric enzymes that play key roles in directing metabolic fluxes of biochemical pathways, as well as large, assembly-line type enzymes that synthesize secondary metabolites with pharmaceutical applications. Furthermore, crystallography has the potential to provide information on protein dynamics via the diffuse scattering patterns that are overlaid with Bragg diffraction. Historically, these patterns have been very difficult to interpret, but recent advances in X-ray detection have led to a renewed interest in diffuse scattering analysis as a way to probe correlated motions. Here, we will review X-ray scattering theory and highlight recent advances in scattering-based investigations of protein solutions and crystals, with a particular focus on complex enzymes.
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Affiliation(s)
- Steve P Meisburger
- Department of Chemistry, Princeton University , Princeton, New Jersey 08544, United States
| | - William C Thomas
- Department of Chemistry, Princeton University , Princeton, New Jersey 08544, United States
| | - Maxwell B Watkins
- Department of Chemistry, Princeton University , Princeton, New Jersey 08544, United States
| | - Nozomi Ando
- Department of Chemistry, Princeton University , Princeton, New Jersey 08544, United States
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44
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Koehl P. Minimum action principle and shape dynamics. J R Soc Interface 2017; 14:rsif.2017.0031. [PMID: 28515327 DOI: 10.1098/rsif.2017.0031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 04/24/2017] [Indexed: 01/02/2023] Open
Abstract
In this paper, we propose a new method for computing a distance between two shapes embedded in three-dimensional space. Instead of comparing directly the geometric properties of the two shapes, we measure the cost of deforming one of the two shapes into the other. The deformation is computed as the geodesic between the two shapes in the space of shapes. The geodesic is found as a minimizer of the Onsager-Machlup action, based on an elastic energy for shapes that we define. Its length is set to be the integral of the action along that path; it defines an intrinsic quasi-metric on the space of shapes. We illustrate applications of our method to geometric morphometrics using three datasets representing bones and teeth of primates. Experiments on these datasets show that the variational quasi-metric we have introduced performs remarkably well both in shape recognition and in identifying evolutionary patterns, with success rates similar to, and in some cases better than, those obtained by expert observers.
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Affiliation(s)
- Patrice Koehl
- Department of Computer Science and Genome Center, University of California, Davis, CA 95616, USA
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45
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Devaurs D, Antunes DA, Papanastasiou M, Moll M, Ricklin D, Lambris JD, Kavraki LE. Coarse-Grained Conformational Sampling of Protein Structure Improves the Fit to Experimental Hydrogen-Exchange Data. Front Mol Biosci 2017; 4:13. [PMID: 28344973 PMCID: PMC5344923 DOI: 10.3389/fmolb.2017.00013] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Accepted: 02/24/2017] [Indexed: 11/13/2022] Open
Abstract
Monitoring hydrogen/deuterium exchange (HDX) undergone by a protein in solution produces experimental data that translates into valuable information about the protein's structure. Data produced by HDX experiments is often interpreted using a crystal structure of the protein, when available. However, it has been shown that the correspondence between experimental HDX data and crystal structures is often not satisfactory. This creates difficulties when trying to perform a structural analysis of the HDX data. In this paper, we evaluate several strategies to obtain a conformation providing a good fit to the experimental HDX data, which is a premise of an accurate structural analysis. We show that performing molecular dynamics simulations can be inadequate to obtain such conformations, and we propose a novel methodology involving a coarse-grained conformational sampling approach instead. By extensively exploring the intrinsic flexibility of a protein with this approach, we produce a conformational ensemble from which we extract a single conformation providing a good fit to the experimental HDX data. We successfully demonstrate the applicability of our method to four small and medium-sized proteins.
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Affiliation(s)
- Didier Devaurs
- Department of Computer Science, Rice UniversityHouston, TX, USA
| | | | - Malvina Papanastasiou
- Department of Pathology and Laboratory Medicine, University of PennsylvaniaPhiladelphia, PA, USA
- Broad Institute of MIT & HarvardCambridge, MA, USA
| | - Mark Moll
- Department of Computer Science, Rice UniversityHouston, TX, USA
| | - Daniel Ricklin
- Department of Pathology and Laboratory Medicine, University of PennsylvaniaPhiladelphia, PA, USA
- Department of Pharmaceutical Sciences, University of BaselBasel, Switzerland
| | - John D. Lambris
- Department of Pathology and Laboratory Medicine, University of PennsylvaniaPhiladelphia, PA, USA
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46
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Koehl P. Minimum action transition paths connecting minima on an energy surface. J Chem Phys 2017; 145:184111. [PMID: 27846680 DOI: 10.1063/1.4966974] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Dynamics is essential to the biological functions of many bio-molecules, yet our knowledge of dynamics remains fragmented. Experimental techniques for studying bio-molecules either provide high resolution information on static conformations of the molecule or provide low-resolution, ensemble information that does not shed light on single molecule dynamics. In parallel, bio-molecular dynamics occur at time scale that are not yet attainable through detailed simulation methods. These limitations are especially noticeable when studying transition paths. To address this issue, we report in this paper two methods that derive meaningful trajectories for proteins between two of their conformations. The first method, MinActionPath, uses approximations of the potential energy surface for the molecule to derive an analytical solution of the equations of motion related to the concept of minimum action path. The second method, RelaxPath, follows the same principle of minimum action path but implements a more sophisticated potential, including a mixed elastic potential and a collision term to alleviate steric clashes. Using this new potential, the equations of motion cannot be solved analytically. We have introduced a relaxation method for solving those equations. We describe both the theories behind the two methods and their implementations, focusing on the specific techniques we have used that make those implementations amenable to study large molecular systems. We have illustrated the performance of RelaxPath on simple 2D systems. We have also compared MinActionPath and RelaxPath to other methods for generating transition paths on a well suited test set of large proteins, for which the end points of the trajectories as well as an intermediate conformation between those end points are known. We have shown that RelaxPath outperforms those other methods, including MinActionPath, in its ability to generate trajectories that get close to the known intermediates. We have also shown that the structures along the RelaxPath trajectories remain protein-like. Open source versions of the two programs MinActionPath and RelaxPath are available by request.
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Affiliation(s)
- Patrice Koehl
- Department of Computer Science and Genome Center, University of California, Davis, California 95616, USA
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47
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Koehl P, Poitevin F, Navaza R, Delarue M. The Renormalization Group and Its Applications to Generating Coarse-Grained Models of Large Biological Molecular Systems. J Chem Theory Comput 2017; 13:1424-1438. [PMID: 28170254 DOI: 10.1021/acs.jctc.6b01136] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.
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Affiliation(s)
- Patrice Koehl
- Department of Computer Sciences and Genome Center, University of California, Davis , Davis, California 95616, United States
| | - Frédéric Poitevin
- Department of Structural Biology, Stanford University , Stanford, California 94305, United States.,Stanford PULSE Institute, SLAC National Accelerator Laboratory, Standford University , Menlo Park, California 94025, United States
| | - Rafael Navaza
- Platform of Crystallogenesis and Crystallography, CiTech, Institut Pasteur , 75015 Paris, France
| | - Marc Delarue
- Unité de Dynamique Structurale des Macromolécules, UMR 3528 du CNRS, Institut Pasteur , 75015 Paris, France
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48
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Ozgur B, Ozdemir ES, Gursoy A, Keskin O. Relation between Protein Intrinsic Normal Mode Weights and Pre-Existing Conformer Populations. J Phys Chem B 2017; 121:3686-3700. [DOI: 10.1021/acs.jpcb.6b10401] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Beytullah Ozgur
- Center for Computational Biology and Bioinformatics, ‡Chemical and Biological
Engineering, and §Computer Engineering,
College of Engineering, Koc University, 34450 Istanbul, Turkey
| | - E. Sila Ozdemir
- Center for Computational Biology and Bioinformatics, ‡Chemical and Biological
Engineering, and §Computer Engineering,
College of Engineering, Koc University, 34450 Istanbul, Turkey
| | - Attila Gursoy
- Center for Computational Biology and Bioinformatics, ‡Chemical and Biological
Engineering, and §Computer Engineering,
College of Engineering, Koc University, 34450 Istanbul, Turkey
| | - Ozlem Keskin
- Center for Computational Biology and Bioinformatics, ‡Chemical and Biological
Engineering, and §Computer Engineering,
College of Engineering, Koc University, 34450 Istanbul, Turkey
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49
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Hsieh YC, Poitevin F, Delarue M, Koehl P. Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids. Front Mol Biosci 2016; 3:85. [PMID: 28083537 PMCID: PMC5187361 DOI: 10.3389/fmolb.2016.00085] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 12/12/2016] [Indexed: 11/13/2022] Open
Abstract
Key steps in the life cycle of a virus, such as the fusion event as the virus infects a host cell and its maturation process, relate to an intricate interplay between the structure and the dynamics of its constituent proteins, especially those that define its capsid, much akin to an envelope that protects its genomic material. We present a comprehensive, comparative analysis of such interplay for the capsids of two viruses from the flaviviridae family, Dengue (DENV) and Zika (ZIKV). We use for that purpose our own software suite, DD-NMA, which is based on normal mode analysis. We describe the elements of DD-NMA that are relevant to the analysis of large systems, such as virus capsids. In particular, we introduce our implementation of simplified elastic networks and justify their parametrization. Using DD-NMA, we illustrate the importance of packing interactions within the virus capsids on the dynamics of the E proteins of DENV and ZIKV. We identify differences between the computed atomic fluctuations of the E proteins in DENV and ZIKV and relate those differences to changes observed in their high resolution structures. We conclude with a discussion on additional analyses that are needed to fully characterize the dynamics of the two viruses.
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Affiliation(s)
- Yin-Chen Hsieh
- Department of Computer Science and Genome Center, University of California, Davis Davis, CA, USA
| | - Frédéric Poitevin
- Department of Structural Biology, Stanford UniversityStanford, CA, USA; SLAC National Accelerator Laboratory, Stanford PULSE InstituteMenlo Park, CA, USA
| | - Marc Delarue
- Unit of Structural Dynamics of Macromolecules, UMR 3528 du Centre National de la Recherche Scientifique, Institut Pasteur Paris, France
| | - Patrice Koehl
- Department of Computer Science and Genome Center, University of California, Davis Davis, CA, USA
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50
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Multiscale design of coarse-grained elastic network-based potentials for the μ opioid receptor. J Mol Model 2016; 22:227. [DOI: 10.1007/s00894-016-3092-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Accepted: 08/08/2016] [Indexed: 01/10/2023]
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