1
|
Frutiger A, Tanno A, Hwu S, Tiefenauer RF, Vörös J, Nakatsuka N. Nonspecific Binding-Fundamental Concepts and Consequences for Biosensing Applications. Chem Rev 2021; 121:8095-8160. [PMID: 34105942 DOI: 10.1021/acs.chemrev.1c00044] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Nature achieves differentiation of specific and nonspecific binding in molecular interactions through precise control of biomolecules in space and time. Artificial systems such as biosensors that rely on distinguishing specific molecular binding events in a sea of nonspecific interactions have struggled to overcome this issue. Despite the numerous technological advancements in biosensor technologies, nonspecific binding has remained a critical bottleneck due to the lack of a fundamental understanding of the phenomenon. To date, the identity, cause, and influence of nonspecific binding remain topics of debate within the scientific community. In this review, we discuss the evolution of the concept of nonspecific binding over the past five decades based upon the thermodynamic, intermolecular, and structural perspectives to provide classification frameworks for biomolecular interactions. Further, we introduce various theoretical models that predict the expected behavior of biosensors in physiologically relevant environments to calculate the theoretical detection limit and to optimize sensor performance. We conclude by discussing existing practical approaches to tackle the nonspecific binding challenge in vitro for biosensing platforms and how we can both address and harness nonspecific interactions for in vivo systems.
Collapse
Affiliation(s)
- Andreas Frutiger
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, Zürich CH-8092, Switzerland
| | - Alexander Tanno
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, Zürich CH-8092, Switzerland
| | - Stephanie Hwu
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, Zürich CH-8092, Switzerland
| | - Raphael F Tiefenauer
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, Zürich CH-8092, Switzerland
| | - János Vörös
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, Zürich CH-8092, Switzerland
| | - Nako Nakatsuka
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, Zürich CH-8092, Switzerland
| |
Collapse
|
2
|
Beyerle ER, Guenza MG. Comparison between slow anisotropic LE4PD fluctuations and the principal component analysis modes of ubiquitin. J Chem Phys 2021; 154:124111. [PMID: 33810675 DOI: 10.1063/5.0041211] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The biological function and folding mechanisms of proteins are often guided by large-scale slow motions, which involve crossing high energy barriers. In a simulation trajectory, these slow fluctuations are commonly identified using a principal component analysis (PCA). Despite the popularity of this method, a complete analysis of its predictions based on the physics of protein motion has been so far limited. This study formally connects the PCA to a Langevin model of protein dynamics and analyzes the contributions of energy barriers and hydrodynamic interactions to the slow PCA modes of motion. To do so, we introduce an anisotropic extension of the Langevin equation for protein dynamics, called the LE4PD-XYZ, which formally connects to the PCA "essential dynamics." The LE4PD-XYZ is an accurate coarse-grained diffusive method to model protein motion, which describes anisotropic fluctuations in the alpha carbons of the protein. The LE4PD accounts for hydrodynamic effects and mode-dependent free-energy barriers. This study compares large-scale anisotropic fluctuations identified by the LE4PD-XYZ to the mode-dependent PCA predictions, starting from a microsecond-long alpha carbon molecular dynamics atomistic trajectory of the protein ubiquitin. We observe that the inclusion of free-energy barriers and hydrodynamic interactions has important effects on the identification and timescales of ubiquitin's slow modes.
Collapse
Affiliation(s)
- E R Beyerle
- Institute for Fundamental Science and Department of Chemistry and Biochemistry, University of Oregon, Eugene, Oregon 97403, USA
| | - M G Guenza
- Institute for Fundamental Science and Department of Chemistry and Biochemistry, University of Oregon, Eugene, Oregon 97403, USA
| |
Collapse
|
3
|
Krieger JM, Doruker P, Scott AL, Perahia D, Bahar I. Towards gaining sight of multiscale events: utilizing network models and normal modes in hybrid methods. Curr Opin Struct Biol 2020; 64:34-41. [PMID: 32622329 DOI: 10.1016/j.sbi.2020.05.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 05/13/2020] [Accepted: 05/20/2020] [Indexed: 11/28/2022]
Abstract
With the explosion of normal mode analyses (NMAs) based on elastic network models (ENMs) in the last decade, and the proven precision of MD simulations for visualizing interactions at atomic scale, many hybrid methods have been proposed in recent years. These aim at exploiting the best of both worlds: the atomic precision of MD that often fall short of exploring time and length scales of biological interest, and the capability of ENM-NMA to predict the cooperative and often functional rearrangements of large structures and assemblies, albeit at low resolution. We present an overview of recent progress in the field with examples of successful applications highlighting the utility of such hybrid methods and pointing to emerging future directions guided by advances in experimental characterization of biomolecular systems structure and dynamics.
Collapse
Affiliation(s)
- James M Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Ana Ligia Scott
- Laboratory of Bioinformatics and Computational Biology, Federal University of ABC, Santo André, SP, Brazil
| | - David Perahia
- Laboratoire de Biologie et de Pharmacologie Appliquée, Ecole Normale Superieure Paris-Saclay, UMR 8113, CNRS, 4 Avenue des Sciences, 91190 Gif-sur-Yvette, France
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA.
| |
Collapse
|
4
|
Jalalypour F, Sensoy O, Atilgan C. Perturb-Scan-Pull: A Novel Method Facilitating Conformational Transitions in Proteins. J Chem Theory Comput 2020; 16:3825-3841. [PMID: 32324386 DOI: 10.1021/acs.jctc.9b01222] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Conformational transitions in proteins facilitate precise physiological functions. Therefore, it is crucial to understand the mechanisms underlying these processes to modulate protein function. Yet, studying structural and dynamical properties of proteins is notoriously challenging due to the complexity of the underlying potential energy surfaces (PES). We have previously developed the perturbation-response scanning (PRS) method to identify key residues that participate in the communication network responsible for specific conformational transitions. PRS is based on a residue-by-residue scan of the protein to determine the subset of residues/forces which provide the closest conformational change leading to a target conformational state, inasmuch as linear response theory applies to these motions. Here, we develop a novel method to further evaluate if conformational transitions may be triggered on the PES. We aim to study functionally relevant conformational transitions in proteins by using results obtained from PRS and feeding them as inputs to steered molecular dynamics simulations. The success and the transferability of the method are evaluated on three protein systems having different complexities of motion on the PES: calmodulin, adenylate kinase, and bacterial ferric binding protein. We find that the method captures the target conformation, while providing key residues and the optimum paths with relatively low free energy profiles.
Collapse
Affiliation(s)
- Farzaneh Jalalypour
- Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Istanbul, Turkey
| | - Ozge Sensoy
- School of Engineering and Natural Sciences, Istanbul Medipol University, 34810, Istanbul, Turkey
| | - Canan Atilgan
- Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Istanbul, Turkey.,Sabanci University Nanotechnology Research and Application Center, SUNUM, 34956, Istanbul, Turkey
| |
Collapse
|
5
|
Khade PM, Kumar A, Jernigan RL. Characterizing and Predicting Protein Hinges for Mechanistic Insight. J Mol Biol 2019; 432:508-522. [PMID: 31786268 DOI: 10.1016/j.jmb.2019.11.018] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 11/01/2019] [Accepted: 11/15/2019] [Indexed: 12/21/2022]
Abstract
The functioning of proteins requires highly specific dynamics, which depend critically on the details of how amino acids are packed. Hinge motions are the most common type of large motion, typified by the opening and closing of enzymes around their substrates. The packing and geometries of residues are characterized here by graph theory. This characterization is sufficient to enable reliable hinge predictions from a single static structure, and notably, this can be from either the open or the closed form of a structure. This new method to identify hinges within protein structures is called PACKMAN. The predicted hinges are validated by using permutation tests on B-factors. Hinge prediction results are compared against lists of manually curated hinge residues, and the results suggest that PACKMAN is robust enough to reproduce the known conformational changes and is able to predict hinge regions equally well from either the open or the closed forms of a protein. A group of 167 protein pairs with open and closed structures has been investigated Examples are shown for several additional proteins, including Zika virus nonstructured (NS) proteins where there are 6 hinge regions in the NS5 protein, 5 hinge regions in the NS2B bound in the NS3 protease complex and 5 hinges in the NS3- helicase protein. Results obtained from this method can be important for generating conformational ensembles of protein targets for drug design. PACKMAN is freely accessible at (https://PACKMAN.bb.iastate.edu/).
Collapse
Affiliation(s)
- Pranav M Khade
- Bioinformatics and Computational Biology Program, Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, 50011, USA
| | - Ambuj Kumar
- Bioinformatics and Computational Biology Program, Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, 50011, USA
| | - Robert L Jernigan
- Bioinformatics and Computational Biology Program, Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, 50011, USA.
| |
Collapse
|
6
|
Orellana L. Large-Scale Conformational Changes and Protein Function: Breaking the in silico Barrier. Front Mol Biosci 2019; 6:117. [PMID: 31750315 PMCID: PMC6848229 DOI: 10.3389/fmolb.2019.00117] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2019] [Accepted: 10/14/2019] [Indexed: 12/16/2022] Open
Abstract
Large-scale conformational changes are essential to link protein structures with their function at the cell and organism scale, but have been elusive both experimentally and computationally. Over the past few years developments in cryo-electron microscopy and crystallography techniques have started to reveal multiple snapshots of increasingly large and flexible systems, deemed impossible only short time ago. As structural information accumulates, theoretical methods become central to understand how different conformers interconvert to mediate biological function. Here we briefly survey current in silico methods to tackle large conformational changes, reviewing recent examples of cross-validation of experiments and computational predictions, which show how the integration of different scale simulations with biological information is already starting to break the barriers between the in silico, in vitro, and in vivo worlds, shedding new light onto complex biological problems inaccessible so far.
Collapse
Affiliation(s)
- Laura Orellana
- Institutionen för Biokemi och Biofysik, Stockholms Universitet, Stockholm, Sweden.,Science for Life Laboratory, Solna, Sweden
| |
Collapse
|
7
|
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.
Collapse
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
| |
Collapse
|
8
|
Sankar K, Mishra SK, Jernigan RL. Comparisons of Protein Dynamics from Experimental Structure Ensembles, Molecular Dynamics Ensembles, and Coarse-Grained Elastic Network Models. J Phys Chem B 2018; 122:5409-5417. [DOI: 10.1021/acs.jpcb.7b11668] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Kannan Sankar
- Bioinformatics and Computational Biology Interdepartmental Graduate Program, Iowa State University, Ames, Iowa 50011-1178, United States
- Roy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, Iowa 50011-1178, United States
| | - Sambit K. Mishra
- Bioinformatics and Computational Biology Interdepartmental Graduate Program, Iowa State University, Ames, Iowa 50011-1178, United States
- Roy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, Iowa 50011-1178, United States
| | - Robert L. Jernigan
- Bioinformatics and Computational Biology Interdepartmental Graduate Program, Iowa State University, Ames, Iowa 50011-1178, United States
- Roy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, Iowa 50011-1178, United States
| |
Collapse
|
9
|
Directional Force Originating from ATP Hydrolysis Drives the GroEL Conformational Change. Biophys J 2017; 112:1561-1570. [PMID: 28445748 DOI: 10.1016/j.bpj.2017.03.004] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 12/16/2016] [Accepted: 03/01/2017] [Indexed: 11/23/2022] Open
Abstract
Protein functional mechanisms usually require conformational changes, and often there are known structures for the different conformational states. However, usually neither the origin of the driving force nor the underlying pathways for these conformational transitions is known. Exothermic chemical reactions may be an important source of forces that drive conformational changes. Here we investigate this type of force originating from ATP hydrolysis in the chaperonin GroEL, by applying forces originating from the chemical reaction. Specifically, we apply directed forces to drive the GroEL conformational changes and learn that there is a highly specific direction for applied forces to drive the closed form to the open form. For this purpose, we utilize coarse-grained elastic network models. Principal component analysis on 38 GroEL experimental structures yields the most important motions, and these are used in structural interpolation for the construction of a coarse-grained free energy landscape. In addition, we investigate a more random application of forces with a Monte Carlo method and demonstrate pathways for the closed-open conformational transition in both directions by computing trajectories that are shown upon the free energy landscape. Initial root mean square deviation (RMSD) between the open and closed forms of the subunit is 14.7 Å and final forms from our simulations reach an average RMSD of 3.6 Å from the target forms, closely matching the level of resolution of the coarse-grained model.
Collapse
|
10
|
Ferguson AL. BayesWHAM: A Bayesian approach for free energy estimation, reweighting, and uncertainty quantification in the weighted histogram analysis method. J Comput Chem 2017; 38:1583-1605. [PMID: 28475830 DOI: 10.1002/jcc.24800] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Revised: 11/27/2016] [Accepted: 03/19/2017] [Indexed: 01/18/2023]
Abstract
The weighted histogram analysis method (WHAM) is a powerful approach to estimate molecular free energy surfaces (FES) from biased simulation data. Bayesian reformulations of WHAM are valuable in proving statistically optimal use of the data and providing a transparent means to incorporate regularizing priors and estimate statistical uncertainties. In this work, we develop a fully Bayesian treatment of WHAM to generate statistically optimal FES estimates in any number of biasing dimensions under arbitrary choices of the Bayes prior. Rigorous uncertainty estimates are generated by Metropolis-Hastings sampling from the Bayes posterior. We also report a means to project the FES and its uncertainties into arbitrary auxiliary order parameters beyond those in which biased sampling was conducted. We demonstrate the approaches in applications of alanine dipeptide and the unthreading of a synthetic mimic of the astexin-3 lasso peptide. Open-source MATLAB and Python implementations of our codes are available for free public download. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Andrew L Ferguson
- Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, 61801.,Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, 61801
| |
Collapse
|
11
|
Manibog K, Sankar K, Kim SA, Zhang Y, Jernigan RL, Sivasankar S. Molecular determinants of cadherin ideal bond formation: Conformation-dependent unbinding on a multidimensional landscape. Proc Natl Acad Sci U S A 2016; 113:E5711-20. [PMID: 27621473 PMCID: PMC5047164 DOI: 10.1073/pnas.1604012113] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Classical cadherin cell-cell adhesion proteins are essential for the formation and maintenance of tissue structures; their primary function is to physically couple neighboring cells and withstand mechanical force. Cadherins from opposing cells bind in two distinct trans conformations: strand-swap dimers and X-dimers. As cadherins convert between these conformations, they form ideal bonds (i.e., adhesive interactions that are insensitive to force). However, the biophysical mechanism for ideal bond formation is unknown. Here, we integrate single-molecule force measurements with coarse-grained and atomistic simulations to resolve the mechanistic basis for cadherin ideal bond formation. Using simulations, we predict the energy landscape for cadherin adhesion, the transition pathways for interconversion between X-dimers and strand-swap dimers, and the cadherin structures that form ideal bonds. Based on these predictions, we engineer cadherin mutants that promote or inhibit ideal bond formation and measure their force-dependent kinetics using single-molecule force-clamp measurements with an atomic force microscope. Our data establish that cadherins adopt an intermediate conformation as they shuttle between X-dimers and strand-swap dimers; pulling on this conformation induces a torsional motion perpendicular to the pulling direction that unbinds the proteins and forms force-independent ideal bonds. Torsional motion is blocked when cadherins associate laterally in a cis orientation, suggesting that ideal bonds may play a role in mechanically regulating cadherin clustering on cell surfaces.
Collapse
Affiliation(s)
- Kristine Manibog
- Department of Physics and Astronomy, Iowa State University, Ames, IA 50011; Ames Laboratory, US Department of Energy, Ames, IA 50011
| | - Kannan Sankar
- Bioinformatics and Computational Biology Interdepartmental Program, Iowa State University, Ames, IA 50011; Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011
| | - Sun-Ae Kim
- Department of Physics and Astronomy, Iowa State University, Ames, IA 50011; Ames Laboratory, US Department of Energy, Ames, IA 50011
| | - Yunxiang Zhang
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305
| | - Robert L Jernigan
- Department of Physics and Astronomy, Iowa State University, Ames, IA 50011; Bioinformatics and Computational Biology Interdepartmental Program, Iowa State University, Ames, IA 50011; Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011; L. H. Baker Center for Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011
| | - Sanjeevi Sivasankar
- Department of Physics and Astronomy, Iowa State University, Ames, IA 50011; Ames Laboratory, US Department of Energy, Ames, IA 50011;
| |
Collapse
|
12
|
Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations. Nat Commun 2016; 7:12575. [PMID: 27578633 PMCID: PMC5013691 DOI: 10.1038/ncomms12575] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 07/13/2016] [Indexed: 12/28/2022] Open
Abstract
Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general. Protein conformational changes are key to a wide range of cellular functions but remain difficult to access experimentally. Here the authors describe eBDIMS, a novel approach to predict intermediates observed in structural transition pathways from experimental ensembles.
Collapse
|
13
|
Kmiecik S, Gront D, Kolinski M, Wieteska L, Dawid AE, Kolinski A. Coarse-Grained Protein Models and Their Applications. Chem Rev 2016; 116:7898-936. [DOI: 10.1021/acs.chemrev.6b00163] [Citation(s) in RCA: 555] [Impact Index Per Article: 69.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Sebastian Kmiecik
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Dominik Gront
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Michal Kolinski
- Bioinformatics
Laboratory, Mossakowski Medical Research Center of the Polish Academy of Sciences, Pawinskiego 5, 02-106 Warsaw, Poland
| | - Lukasz Wieteska
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
- Department
of Medical Biochemistry, Medical University of Lodz, Mazowiecka 6/8, 92-215 Lodz, Poland
| | | | - Andrzej Kolinski
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| |
Collapse
|