Journal articles: 'Conformational clustering'

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Roither, Bernhard, Chris Oostenbrink, Georg Pfeiler, Heinz Koelbl, and Wolfgang Schreiner. "Pembrolizumab Induces an Unexpected Conformational Change in the CC′-loop of PD-1." Cancers 13, no. 1 (December 22, 2020): 5. http://dx.doi.org/10.3390/cancers13010005.

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To improve cancer immunotherapy, a clearer understanding of key targets such as the immune checkpoint receptor PD-1 is essential. The PD-1 inhibitors nivolumab and pembrolizumab were recently approved by the FDA. The CC′-loop of PD-1 has been identified as a hotspot for drug targeting. Here, we investigate the influence of nivolumab and pembrolizumab on the molecular motion of the CC′-loop of PD-1. We performed molecular dynamics simulations on the complete extracellular domain of PD-1, in complex with PD-L1, and the blocking antibodies nivolumab and pembrolizumab. Conformations of the CC′-loop were analyzed unsupervised with the Daura et al. clustering algorithm and multidimensional scaling. Surprisingly, two conformations found were seen to correspond to the ‘open’ and ‘closed’ conformation of CC′-loop in apo-PD-1, already known from literature. Unsupervised clustering also surprisingly reproduced the natural ligand, PD-L1, exclusively stabilizing the ‘closed’ conformation, as also known from literature. Nivolumab, like PD-L1, was found to shift the equilibrium towards the ‘closed’ conformation, in accordance with the conformational selection model. Pembrolizumab, on the other hand, induced a third conformation of the CC′-loop which has not been described to date: Relative to the conformation ‘open’ the, CC′-loop turned 180° to form a new conformation which we called ‘overturned’. We show that the combination of clustering and multidimensional scaling is a fast, easy, and powerful method in analyzing structural changes in proteins. Possible refined antibodies or new small molecular compounds could utilize the flexibility of the CC′-loop to improve immunotherapy.

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Conklin, D., S. Fortier, J. I. Glasgow, and F. H. Allen. "Conformational analysis from crystallographic data using conceptual clustering." Acta Crystallographica Section B Structural Science 52, no. 3 (June 1, 1996): 535–49. http://dx.doi.org/10.1107/s010876819501696x.

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The rapid growth of crystallographic databases has created a demand for novel and efficient techniques for the analysis of molecular conformations, in order to derive new concepts and rules and to generate useful classifications of the available data. This paper presents a conceptual clustering approach, termed IMEM (image memory), which discovers the conformational diversity present in a dataset of crystal structures. In contrast to numerical clustering methods, IMEM views a molecular structure as comprising qualitative relationships among its parts, i.e. the structure is viewed as a molecular scene. In addition, IMEM does not require the user to have any a priori knowledge of an expected number of conformational classes within a given dataset. The IMEM approach is applied to several datasets derived from the Cambridge Structural Database and, in all cases, chemically correct and sensible conformational classifications were discovered. This is confirmed by a rigorous comparison of IMEM results with published conformational data obtained by energy-minimization and numerical clustering methods. Conformational analysis tools have an important part to play in the conversion of raw molecular databases to knowledge bases.

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Collins, A., A. Parkin, G. Barr, W. Dong, C. J. Gilmore, and C. C. Wilson. "Configurational and conformational classification of pyranose sugars." Acta Crystallographica Section B Structural Science 64, no. 1 (January 17, 2008): 57–65. http://dx.doi.org/10.1107/s0108768107067341.

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Automated cluster analysis is used to examine the conformation and configuration of pyranose sugars. Previous findings on this issue are confirmed, importantly from an analysis that requires no prior knowledge of the significant factors determining the conformational classification. The findings on the conformations adopted in the crystalline solid state are found to be different to existing quantum chemical calculations performed for D-glucose in the gas phase, but consistent with empirically determined conformations in the solution state. The use of this clustering analysis in studying chirality in the determined structures is discussed, as is the ability of this type of method to examine higher dimensions within the metric multi-dimensional scaling formalism.

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Huang, Shupei, Haizhong An, Xiangyun Gao, Xiaoqing Hao, and Xuan Huang. "The Multiscale Conformation Evolution of the Financial Time Series." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/563145.

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Fluctuations of the nonlinear time series are driven by the traverses of multiscale conformations from one state to another. Aiming to characterize the evolution of multiscale conformations with changes in time and frequency domains, we present an algorithm that combines the wavelet transform and the complex network. Based on defining the multiscale conformation using a set of fluctuation states from different frequency components at each time point rather than the single observable value, we construct the conformational evolution complex network. To illustrate, using data of Shanghai’s composition index with daily frequency from 1991 to 2014 as an example, we find that a few major conformations are the main contributors of evolution progress, the whole conformational evolution network has a clustering effect, and there is a turning point when the size of the chain of multiscale conformations is 14. This work presents a refined perspective into underlying fluctuation features of financial markets.

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Joshi, Arpita, Nurit Haspel, and Eduardo González. "Characterizing Protein Conformational Spaces using Efficient Data Reduction and Algebraic Topology." Journal of Human, Earth, and Future 3 (May 31, 2022): 1–21. http://dx.doi.org/10.28991/hef-sp2022-01-01.

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Datasets representing the conformational landscapes of protein structures are high-dimensional and hence present computational challenges. Efficient and effective dimensionality reduction of these datasets is therefore paramount to our ability to analyze the conformational landscapes of proteins and extract important information regarding protein folding, conformational changes, and binding. Representing the structures with fewer attributes that capture the most variance in the data makes for a quicker and more precise analysis of these structures. In this study, we make use of dimensionality reduction methods for reducing the number of instances and for feature reduction. The reduced dataset that is obtained is then subjected to topological and quantitative analysis. In this step, we perform hierarchical clustering to obtain different sets of conformation clusters that may correspond to intermediate structures. The structures represented by these conformations are then analyzed by studying their high-dimensional topological properties to identify truly distinct conformations and holes in the conformational space that may represent high energy barriers. Our results show that the clusters closely follow known experimental results about intermediate structures as well as binding and folding events. Doi: 10.28991/HEF-SP2022-01-01 Full Text: PDF

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Pérez, J., K. Nolsøe, M. Kessler, L. García, E. Pérez, and J. L. Serrano. "Bayesian methods for the conformational classification of eight-membered rings." Acta Crystallographica Section B Structural Science 61, no. 5 (September 23, 2005): 585–94. http://dx.doi.org/10.1107/s0108768105023931.

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Two methods for the classification of eight-membered rings based on a Bayesian analysis are presented. The two methods share the same probabilistic model for the measurement of torsion angles, but while the first method uses the canonical forms of cyclooctane and, given an empirical sequence of eight torsion angles, yields the probability that the associated structure corresponds to each of the ten canonical conformations, the second method does not assume previous knowledge of existing conformations and yields a clustering classification of a data set, allowing new conformations to be detected. Both methods have been tested using the conformational classification of Csp 3 eight-membered rings described in the literature. The methods have also been employed to classify the solid-state conformation in Csp 3 eight-membered rings using data retrieved from an updated version of the Cambridge Structural Database (CSD).

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Dobrovolska, Olena, Øyvind Strømland, Ørjan Sele Handegård, Martin Jakubec, Morten L. Govasli, Åge Aleksander Skjevik, Nils Åge Frøystein, Knut Teigen, and Øyvind Halskau. "Investigating the Disordered and Membrane-Active Peptide A-Cage-C Using Conformational Ensembles." Molecules 26, no. 12 (June 12, 2021): 3607. http://dx.doi.org/10.3390/molecules26123607.

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The driving forces and conformational pathways leading to amphitropic protein-membrane binding and in some cases also to protein misfolding and aggregation is the subject of intensive research. In this study, a chimeric polypeptide, A-Cage-C, derived from α-Lactalbumin is investigated with the aim of elucidating conformational changes promoting interaction with bilayers. From previous studies, it is known that A-Cage-C causes membrane leakages associated with the sporadic formation of amorphous aggregates on solid-supported bilayers. Here we express and purify double-labelled A-Cage-C and prepare partially deuterated bicelles as a membrane mimicking system. We investigate A-Cage-C in the presence and absence of these bicelles at non-binding (pH 7.0) and binding (pH 4.5) conditions. Using in silico analyses, NMR, conformational clustering, and Molecular Dynamics, we provide tentative insights into the conformations of bound and unbound A-Cage-C. The conformation of each state is dynamic and samples a large amount of overlapping conformational space. We identify one of the clusters as likely representing the binding conformation and conclude tentatively that the unfolding around the central W23 segment and its reorientation may be necessary for full intercalation at binding conditions (pH 4.5). We also see evidence for an overall elongation of A-Cage-C in the presence of model bilayers.

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Modi, Vivek, and Roland L. Dunbrack. "Defining a new nomenclature for the structures of active and inactive kinases." Proceedings of the National Academy of Sciences 116, no. 14 (March 13, 2019): 6818–27. http://dx.doi.org/10.1073/pnas.1814279116.

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Targeting protein kinases is an important strategy for intervention in cancer. Inhibitors are directed at the active conformation or a variety of inactive conformations. While attempts have been made to classify these conformations, a structurally rigorous catalog of states has not been achieved. The kinase activation loop is crucial for catalysis and begins with the conserved DFGmotif. This motif is observed in two major classes of conformations, DFGin—a set of active and inactive conformations where the Phe residue is in contact with the C-helix of the N-terminal lobe—and DFGout—an inactive form where Phe occupies the ATP site exposing the C-helix pocket. We have developed a clustering of kinase conformations based on the location of the Phe side chain (DFGin, DFGout, and DFGinter or intermediate) and the backbone dihedral angles of the sequence X-D-F, where X is the residue before the DFGmotif, and the DFG-Phe side-chain rotamer, utilizing a density-based clustering algorithm. We have identified eight distinct conformations and labeled them based on the Ramachandran regions (A, alpha; B, beta; L, left) of the XDF motif and the Phe rotamer (minus, plus, trans). Our clustering divides the DFGin group into six clusters including BLAminus, which contains active structures, and two common inactive forms, BLBplus and ABAminus. DFGout structures are predominantly in the BBAminus conformation, which is essentially required for binding type II inhibitors. The inactive conformations have specific features that make them unable to bind ATP, magnesium, and/or substrates. Our structurally intuitive nomenclature will aid in understanding the conformational dynamics of kinases and structure-based development of kinase drugs.

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Humphries, M. J. "Monoclonal antibodies as probes of integrin priming and activation." Biochemical Society Transactions 32, no. 3 (June 1, 2004): 407–11. http://dx.doi.org/10.1042/bst0320407.

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Integrins are a family of heterodimeric, transmembrane receptors that mediate a range of cell–cell and cell–extracellular matrix interactions in an array of physiological and pathophysiological situations. Integrin-mediated cell adhesion is dynamically regulated in vivo to facilitate cell anchorage and movement, but prevents aberrant trafficking and aggregation. Following ligand engagement, integrin signalling imposes a spatial constraint on the assembly of signalling complexes and controls the transduction of mechanical force to the cytoskeleton. This transmembrane passage of signals via integrins is achieved both by clustering of receptors, which makes the ligand and effector engagement more favourable kinetically, and by induction of conformational changes, that theoretically creates ligand and effector binding sites de novo. Clustering and conformational changes can be triggered both from the inside of the cell (resulting in acquisition of ligand-competent conformers) and from the outside (ligand-induced signalling). In this paper, these processes will be described and distinguished by the terms priming and activation, respectively. Although both clustering and conformation are important for integrin function, the latter will be the main focus of this article; in particular, the importance of monoclonal antibodies for the study of integrin shape changes.

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Kessler, Mathieu, María C. Bueso, and José Pérez. "Model-based conformational clustering of ring molecules." Journal of Chemometrics 21, no. 1-2 (January 2007): 53–64. http://dx.doi.org/10.1002/cem.1035.

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Bianchi, Greta, Marco Mangiagalli, Alberto Barbiroli, Sonia Longhi, Rita Grandori, Carlo Santambrogio, and Stefania Brocca. "Distribution of Charged Residues Affects the Average Size and Shape of Intrinsically Disordered Proteins." Biomolecules 12, no. 4 (April 9, 2022): 561. http://dx.doi.org/10.3390/biom12040561.

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Intrinsically disordered proteins (IDPs) are ensembles of interconverting conformers whose conformational properties are governed by several physico-chemical factors, including their amino acid composition and the arrangement of oppositely charged residues within the primary structure. In this work, we investigate the effects of charge patterning on the average compactness and shape of three model IDPs with different proline content. We model IDP ensemble conformations as ellipsoids, whose size and shape are calculated by combining data from size-exclusion chromatography and native mass spectrometry. For each model IDP, we analyzed the wild-type protein and two synthetic variants with permuted positions of charged residues, where positive and negative amino acids are either evenly distributed or segregated. We found that charge clustering induces remodeling of the conformational ensemble, promoting compaction and/or increasing spherical shape. Our data illustrate that the average shape and volume of the ensembles depend on the charge distribution. The potential effect of other factors, such as chain length, number of proline residues, and secondary structure content, is also discussed. This methodological approach is a straightforward way to model IDP average conformation and decipher the salient sequence attributes influencing IDP structural properties.

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WEN, BIN, YUNYU SHI, and ZHIYONG ZHANG. "CLUSTERING MULTI-DOMAIN PROTEIN STRUCTURES IN THE ESSENTIAL DYNAMICS SUBSPACE." Journal of Theoretical and Computational Chemistry 12, no. 08 (December 2013): 1341008. http://dx.doi.org/10.1142/s0219633613410083.

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A multi-domain protein is able to exist as equilibrium of different conformations in solution, which may be critical to its biological function. Besides experimental techniques, computational methods like molecular dynamics (MD) simulations are suitable to study inter-domain motions of the protein and sample different conformational states. A MD simulation usually generates a trajectory containing large amount of protein structures, and a post-processing cluster analysis would be necessary to group similar structures into clusters and identify these typical conformations of the multi-domain protein. In this paper, the widely used k-means clustering algorithm is implemented in the protein essential dynamics (ED) subspace defined by principal component analysis on the MD trajectory. Cluster analysis of the formin binding protein 21 (FBP21) tandem WW domains demonstrate that the k-means clustering results by measuring distances between structures in the ED subspace are superior to those by using other metrics like pairwise inter-domain residue distances.

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Dluhy, R. A., D. Moffatt, D. G. Cameron, R. Mendelsohn, and H. H. Mantsch. "Characterization of cooperative conformational transitions by Fourier transform infrared spectroscopy: application to phospholipid binary mixtures." Canadian Journal of Chemistry 63, no. 7 (July 1, 1985): 1925–32. http://dx.doi.org/10.1139/v85-319.

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Temperature-induced cooperative conformational transitions in biopolymers may be examined in aqueous solution by the use of Fourier transform infrared spectroscopy. The transition is described in terms of a two-state model with a fractional population parameter (which describes the degree of transition at various values intermediate between the two limiting cases) that can be generated by a least-squares technique. This procedure allows for calculation of a conformational index without assuming a linear dependence of the infrared parameter on the extent of transition. Calculations based on the Zimm–Bragg theory of cooperative conformational transitions allow thermodynamic quantities to be derived using the conformational index in conjunction with calorimetric measurements.The method is illustrated with data from the gel/liquid-crystalline phase transitions of binary phospholipid vesicles where the use of isotopic substitution allows the conformation of each component of the binary mixture to be independently monitored. The data suggest the coexistence of well-defined structural domains of phospholipid as well as the preferential clustering of one of the lipid components at the interface between the two phases.

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Mana, Giulia, Donatella Valdembri, Janet A. Askari, Zhenhai Li, Patrick Caswell, Cheng Zhu, Martin J. Humphries, Christoph Ballestrem, and Guido Serini. "The βI domain promotes active β1 integrin clustering into mature adhesion sites." Life Science Alliance 6, no. 2 (November 21, 2022): e202201388. http://dx.doi.org/10.26508/lsa.202201388.

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Modulation of integrin function is required in many physiological and pathological settings, such as angiogenesis and cancer. Integrin allosteric changes, clustering, and trafficking cooperate to regulate cell adhesion and motility on extracellular matrix proteins via mechanisms that are partly defined. By exploiting four monoclonal antibodies recognizing distinct conformational epitopes, we show that in endothelial cells (ECs), the extracellular βI domain, but not the hybrid or I-EGF2 domain of active β1 integrins, promotes their FAK-regulated clustering into tensin 1–containing fibrillar adhesions and impairs their endocytosis. In this regard, the βI domain–dependent clustering of active β1 integrins is necessary to favor fibronectin-elicited directional EC motility, which cannot be effectively promoted by β1 integrin conformational activation alone.

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Modi, Vivek, and Roland L. Dunbrack. "Kincore: a web resource for structural classification of protein kinases and their inhibitors." Nucleic Acids Research 50, no. D1 (October 13, 2021): D654—D664. http://dx.doi.org/10.1093/nar/gkab920.

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Abstract The active form of kinases is shared across different family members, as are several commonly observed inactive forms. We previously performed a clustering of the conformation of the activation loop of all protein kinase structures in the Protein Data Bank (PDB) into eight classes based on the dihedral angles that place the Phe side chain of the DFG motif at the N-terminus of the activation loop. Our clusters are strongly associated with the placement of the activation loop, the C-helix, and other structural elements of kinases. We present Kincore, a web resource providing access to our conformational assignments for kinase structures in the PDB. While other available databases provide conformational states or drug type but not both, KinCore includes the conformational state and the inhibitor type (Type 1, 1.5, 2, 3, allosteric) for each kinase chain. The user can query and browse the database using these attributes or determine the conformational labels of a kinase structure using the web server or a standalone program. The database and labeled structure files can be downloaded from the server. Kincore will help in understanding the conformational dynamics of these proteins and guide development of inhibitors targeting specific states. Kincore is available at http://dunbrack.fccc.edu/kincore.

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Kim, Irene S., Simon Jenni, Megan L. Stanifer, Eatai Roth, Sean P. J. Whelan, Antoine M. van Oijen, and Stephen C. Harrison. "Mechanism of membrane fusion induced by vesicular stomatitis virus G protein." Proceedings of the National Academy of Sciences 114, no. 1 (December 14, 2016): E28—E36. http://dx.doi.org/10.1073/pnas.1618883114.

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The glycoproteins (G proteins) of vesicular stomatitis virus (VSV) and related rhabdoviruses (e.g., rabies virus) mediate both cell attachment and membrane fusion. The reversibility of their fusogenic conformational transitions differentiates them from many other low-pH-induced viral fusion proteins. We report single-virion fusion experiments, using methods developed in previous publications to probe fusion of influenza and West Nile viruses. We show that a three-stage model fits VSV single-particle fusion kinetics: (i) reversible, pH-dependent, G-protein conformational change from the known prefusion conformation to an extended, monomeric intermediate; (ii) reversible trimerization and clustering of the G-protein fusion loops, leading to an extended intermediate that inserts the fusion loops into the target-cell membrane; and (iii) folding back of a cluster of extended trimers into their postfusion conformations, bringing together the viral and cellular membranes. From simulations of the kinetic data, we conclude that the critical number of G-protein trimers required to overcome membrane resistance is 3 to 5, within a contact zone between the virus and the target membrane of 30 to 50 trimers. This sequence of conformational events is similar to those shown to describe fusion by influenza virus hemagglutinin (a “class I” fusogen) and West Nile virus envelope protein (“class II”). Our study of VSV now extends this description to “class III” viral fusion proteins, showing that reversibility of the low-pH-induced transition and architectural differences in the fusion proteins themselves do not change the basic mechanism by which they catalyze membrane fusion.

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DAMJANOVICH, S., R. GÁSPÁR, Jr., and C. PIERI. "Dynamic receptor superstructures at the plasma membrane." Quarterly Reviews of Biophysics 30, no. 1 (February 1997): 67–106. http://dx.doi.org/10.1017/s0033583596003307.

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1. INTRODUCTION 681.1 Receptor patterns in the plasma membrane 681.2 Different types of receptor patterns 712. METHODS TO INVESTIGATE NON-RANDOM RECEPTOR CLUSTERING 732.1 Fluorescence resonance energy transfer 732.2 Flow cytometric energy transfer measurement 782.3 Fluorescence anisotropy and energy transfer 792.4 Photobleaching energy transfer on single cells 812.5 Two-dimensional mapping of receptor superstructures 822.6 Detecting single receptor molecules 852.7 Chemical identification of receptor clusters 862.8 Electron microscopy 872.9 Scanning force microscopy 883. CONFORMATIONAL STATES OF RECEPTORS 903.1 Multi-subunit receptor structures 903.2 Physical parameters influencing conformational states 913.3 Chemical interactions and receptor conformations 924. ON THE ORIGIN OF NATURALLY OCCURRING RECEPTOR CLUSTERS 934.1 Synthesis of receptors and their localization in the plasma membrane 934.2 Lipid domain structure of the plasma membrane 944.3 The validity of the Singer–Nicolson model 945. CONCLUSIONS 966. ACKNOWLEDGEMENTS 967. REFERENCES 97

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Zok, Tomasz, Maciej Antczak, Martin Riedel, David Nebel, Thomas Villmann, Piotr Lukasiak, Jacek Blazewicz, and Marta Szachniuk. "Building the library of RNA 3D nucleotide conformations using the clustering approach." International Journal of Applied Mathematics and Computer Science 25, no. 3 (September 1, 2015): 689–700. http://dx.doi.org/10.1515/amcs-2015-0050.

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Abstract An increasing number of known RNA 3D structures contributes to the recognition of various RNA families and identification of their features. These tasks are based on an analysis of RNA conformations conducted at different levels of detail. On the other hand, the knowledge of native nucleotide conformations is crucial for structure prediction and understanding of RNA folding. However, this knowledge is stored in structural databases in a rather distributed form. Therefore, only automated methods for sampling the space of RNA structures can reveal plausible conformational representatives useful for further analysis. Here, we present a machine learning-based approach to inspect the dataset of RNA three-dimensional structures and to create a library of nucleotide conformers. A median neural gas algorithm is applied to cluster nucleotide structures upon their trigonometric description. The clustering procedure is two-stage: (i) backbone- and (ii) ribose-driven. We show the resulting library that contains RNA nucleotide representatives over the entire data, and we evaluate its quality by computing normal distribution measures and average RMSD between data points as well as the prototype within each cluster.

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Steuer, Jakob, Oleksandra Kukharenko, Kai Riedmiller, Jörg S. Hartig, and Christine Peter. "Guanidine-II aptamer conformations and ligand binding modes through the lens of molecular simulation." Nucleic Acids Research 49, no. 14 (July 7, 2021): 7954–65. http://dx.doi.org/10.1093/nar/gkab592.

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Abstract Regulation of gene expression via riboswitches is a widespread mechanism in bacteria. Here, we investigate ligand binding of a member of the guanidine sensing riboswitch family, the guanidine-II riboswitch (Gd-II). It consists of two stem–loops forming a dimer upon ligand binding. Using extensive molecular dynamics simulations we have identified conformational states corresponding to ligand-bound and unbound states in a monomeric stem–loop of Gd-II and studied the selectivity of this binding. To characterize these states and ligand-dependent conformational changes we applied a combination of dimensionality reduction, clustering, and feature selection methods. In absence of a ligand, the shape of the binding pocket alternates between the conformation observed in presence of guanidinium and a collapsed conformation, which is associated with a deformation of the dimerization interface. Furthermore, the structural features responsible for the ability to discriminate against closely related analogs of guanidine are resolved. Based on these insights, we propose a mechanism that couples ligand binding to aptamer dimerization in the Gd-II system, demonstrating the value of computational methods in the field of nucleic acids research.

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Polêto, Marcelo D., Bruno I. Grisci, Marcio Dorn, and Hugo Verli. "ConfID: an analytical method for conformational characterization of small molecules using molecular dynamics trajectories." Bioinformatics 36, no. 11 (February 27, 2020): 3576–77. http://dx.doi.org/10.1093/bioinformatics/btaa130.

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Abstract Motivation The conformational space of small molecules can be vast and difficult to assess. Molecular dynamics (MD) simulations of free ligands in solution have been applied to predict conformational populations, but their characterization is often based on clustering algorithms or manual efforts. Results Here, we introduce ConfID, an analytical tool for conformational characterization of small molecules using MD trajectories. The evolution of conformational sampling and population frequencies throughout trajectories is calculated to check for sampling convergence while allowing to map relevant conformational transitions. The tool is designed to track conformational transition events and calculate time-dependent properties for each conformational population detected. Availability and implementation Toolkit and documentation are freely available at http://sbcb.inf.ufrgs.br/confid Contact marcelo.poleto@ufv.br or bigrisci@inf.ufrgs.br Supplementary information Supplementary data are available at Bioinformatics online.

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Adasme-Carreño, Francisco, Camila Muñoz-Gutierrez, Julio Caballero, and Jans H. Alzate-Morales. "Performance of the MM/GBSA scoring using a binding site hydrogen bond network-based frame selection: the protein kinase case." Phys. Chem. Chem. Phys. 16, no. 27 (2014): 14047–58. http://dx.doi.org/10.1039/c4cp01378f.

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Kobayashi, Masamichi, and Takehito Kozasa. "Conformational Ordering Process on Physical Gelation of Syndiotactic Polystyrene/Solvent Systems Revealed by Time-Resolved Infrared Spectroscopy." Applied Spectroscopy 47, no. 9 (September 1993): 1417–24. http://dx.doi.org/10.1366/0003702934067450.

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Syndiotactic polystyrene (SPS) dissolved in various organic solvents forms stable gels. Infrared spectroscopic research shows that SPS molecules assume highly ordered TTGG conformation in gels, giving rise to many infrared bands characteristic of the regular TTGG sequences. The behavior of the conformational ordering is strongly dependent on the solvent and the temperature. The time evolution of the conformational order on gelation has been investigated for SPS/CHCl3 systems at various polymer concentrations and temperatures by time-resolved infrared spectroscopy. By the analysis of the rate of formation of the ordered conformation derived from the time-resolved intensity measurement of the conformation-sensitive band at 572 cm−1, the number of the chain segments that contribute to the formation of clusters having ordered TTGG conformation has been evaluated as a function of temperature. The results indicate that at a temperature around 10°C the conformation ordering proceeds through clustering of five chain segments. The number decreases with lowering temperature and becomes unity below a certain temperature, suggesting that the ordering proceeds via self-organization within one chain. Such a crossover between the two mechanisms is found for other solvents, although the crossover temperature depends on the solvent. It has been concluded that strong interactions between polymer and solvent molecules play important roles in controlling the gelation behavior of SPS/solvent systems.

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Hato, Takaaki, Nisar Pampori, and Sanford J. Shattil. "Complementary Roles for Receptor Clustering and Conformational Change in the Adhesive and Signaling Functions of Integrin αIIbβ3." Journal of Cell Biology 141, no. 7 (June 29, 1998): 1685–95. http://dx.doi.org/10.1083/jcb.141.7.1685.

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Integrin αIIbβ3 mediates platelet aggregation and “outside-in” signaling. It is regulated by changes in receptor conformation and affinity and/or by lateral diffusion and receptor clustering. To document the relative contributions of conformation and clustering to αIIbβ3 function, αIIb was fused at its cytoplasmic tail to one or two FKBP12 repeats (FKBP). These modified αIIb subunits were expressed with β3 in CHO cells, and the heterodimers could be clustered into morphologically detectable oligomers upon addition of AP1510, a membrane-permeable, bivalent FKBP ligand. Integrin clustering by AP1510 caused binding of fibrinogen and a multivalent (but not monovalent) fibrinogen-mimetic antibody. However, ligand binding due to clustering was only 25–50% of that observed when αIIbβ3 affinity was increased by an activating antibody or an activating mutation. The effects of integrin clustering and affinity modulation were additive, and clustering promoted irreversible ligand binding. Clustering of αIIbβ3 also promoted cell adhesion to fibrinogen or von Willebrand factor, but not as effectively as affinity modulation. However, clustering was sufficient to trigger fibrinogen-independent tyrosine phosphorylation of pp72Syk and fibrinogen-dependent phosphorylation of pp125FAK, even in non-adherent cells. Thus, receptor clustering and affinity modulation play complementary roles in αIIbβ3 function. Affinity modulation is the predominant regulator of ligand binding and cell adhesion, but clustering increases these responses further and triggers protein tyrosine phosphorylation, even in the absence of affinity modulation. Both affinity modulation and clustering may be needed for optimal function of αIIbβ3 in platelets.

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Collins, Anna, Gordon Barr, Wei Dong, Christopher J. Gilmore, Derek S. Middlemiss, Andrew Parkin, and Chick C. Wilson. "The application of cluster analysis to identify conformational preferences in enones and enimines from crystal structural data." Acta Crystallographica Section B Structural Science 63, no. 3 (May 16, 2007): 469–76. http://dx.doi.org/10.1107/s0108768107006969.

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Cluster analysis can be an effective tool for analysing large quantities of data. Here it has been applied to the conformational analysis of enones and enimines in the crystalline solid state, using structural information mined from the Cambridge Structural Database. The forms that are common in the gaseous state and in solution are already known from spectroscopic studies. These forms are also found to be the most common conformations observed in the solid state; however, the clustering method highlights those structures that do not conform to the expected geometries. The study is supported by ab initio gas phase calculations on simple enone and enimine fragments.

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Kim, Minsoo, Christopher V. Carman, Wei Yang, Azucena Salas, and Timothy A. Springer. "The primacy of affinity over clustering in regulation of adhesiveness of the integrin αLβ2." Journal of Cell Biology 167, no. 6 (December 20, 2004): 1241–53. http://dx.doi.org/10.1083/jcb.200404160.

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Dynamic regulation of integrin adhesiveness is required for immune cell–cell interactions and leukocyte migration. Here, we investigate the relationship between cell adhesion and integrin microclustering as measured by fluorescence resonance energy transfer, and macroclustering as measured by high resolution fluorescence microscopy. Stimuli that activate adhesion through leukocyte function–associated molecule-1 (LFA-1) failed to alter clustering of LFA-1 in the absence of ligand. Binding of monomeric intercellular adhesion molecule-1 (ICAM-1) induced profound changes in the conformation of LFA-1 but did not alter clustering, whereas binding of ICAM-1 oligomers induced significant microclustering. Increased diffusivity in the membrane by cytoskeleton-disrupting agents was sufficient to drive adhesion in the absence of affinity modulation and was associated with a greater accumulation of LFA-1 to the zone of adhesion, but redistribution did not precede cell adhesion. Disruption of conformational communication within the extracellular domain of LFA-1 blocked adhesion stimulated by affinity-modulating agents, but not adhesion stimulated by cytoskeleton-disrupting agents. Thus, LFA-1 clustering does not precede ligand binding, and instead functions in adhesion strengthening after binding to multivalent ligands.

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Raithby, P. R., G. P. Shields, and F. H. Allen. "Conformational Analysis of Macrocyclic Ether Ligands. I. 1,4,7,10-Tetraoxacyclododecane and 1,4,7,10-Tetrathiacyclododecane." Acta Crystallographica Section B Structural Science 53, no. 2 (April 1, 1997): 241–51. http://dx.doi.org/10.1107/s0108768196013663.

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Crystallographic results retrieved from the Cambridge Structural Database (CSD) have been used to perform systematic conformational analyses of both free and metal-coordinated unsaturated 12-membered oxa and thia macrocycles. Conformational classifications established using symmetry-modified Jarvis–Patrick clustering are visualized in conformational space by principal component analysis (PCA) plots. These show that the relationship between cluster populations and relative molecular mechanics energies is modified by the coordination requirements of a metal ion. With oxa donors the [3333] conformer (oxygen in edge positions) predominates for metal-coordinated macrocycles, with the donor atoms in a square-planar arrangement, whilst the [48] conformer occurs bound in a cis-octahedral fashion to metal ions and the [66] conformer does not bind in an endo-dentate manner at all. The [3333] and [66] conformers are both common for free ligands, reflecting their similar molecular mechanics energies; the conformation is often determined by the hydrogen-bonding network. There are few thia examples: it is found that conformers with low molecular mechanics energies are unsuited to metal coordination and substantial reorganization is necessary for chelation. The differences in behaviour of oxa and thia macrocycles may be rationalized in terms of differing torsion-angle preferences for CXCC and XCCX units (X = O, S).

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Tedeschi, Giulia, Edoardo Salladini, Carlo Santambrogio, Rita Grandori, Sonia Longhi, and Stefania Brocca. "Conformational response to charge clustering in synthetic intrinsically disordered proteins." Biochimica et Biophysica Acta (BBA) - General Subjects 1862, no. 10 (October 2018): 2204–14. http://dx.doi.org/10.1016/j.bbagen.2018.07.011.

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Boutonnet, Nathalie S., Marianne J. Rooman, and Shoshana J. Wodak. "Automatic Analysis of Protein Conformational Changes by Multiple Linkage Clustering." Journal of Molecular Biology 253, no. 4 (November 1995): 633–47. http://dx.doi.org/10.1006/jmbi.1995.0578.

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Comrie, William A., Alexander Babich, and Janis K. Burkhardt. "F-actin flow drives affinity maturation and spatial organization of LFA-1 at the immunological synapse." Journal of Cell Biology 208, no. 4 (February 9, 2015): 475–91. http://dx.doi.org/10.1083/jcb.201406121.

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Integrin-dependent interactions between T cells and antigen-presenting cells are vital for proper T cell activation, effector function, and memory. Regulation of integrin function occurs via conformational change, which modulates ligand affinity, and receptor clustering, which modulates valency. Here, we show that conformational intermediates of leukocyte functional antigen 1 (LFA-1) form a concentric array at the immunological synapse. Using an inhibitor cocktail to arrest F-actin dynamics, we show that organization of this array depends on F-actin flow and ligand mobility. Furthermore, F-actin flow is critical for maintaining the high affinity conformation of LFA-1, for increasing valency by recruiting LFA-1 to the immunological synapse, and ultimately for promoting intracellular cell adhesion molecule 1 (ICAM-1) binding. Finally, we show that F-actin forces are opposed by immobilized ICAM-1, which triggers LFA-1 activation through a combination of induced fit and tension-based mechanisms. Our data provide direct support for a model in which the T cell actin network generates mechanical forces that regulate LFA-1 activity at the immunological synapse.

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Folkertsma, Simon, Paula I. van Noort, Arnold de Heer, Peter Carati, Ralph Brandt, Arie Visser, Gerrit Vriend, and Jacob de Vlieg. "The Use of in Vitro Peptide Binding Profiles and in Silico Ligand-Receptor Interaction Profiles to Describe Ligand-Induced Conformations of the Retinoid X Receptor α Ligand-Binding Domain." Molecular Endocrinology 21, no. 1 (January 1, 2007): 30–48. http://dx.doi.org/10.1210/me.2006-0072.

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Abstract It is hypothesized that different ligand-induced conformational changes can explain the different interactions of nuclear receptors with regulatory proteins, resulting in specific biological activities. Understanding the mechanism of how ligands regulate cofactor interaction facilitates drug design. To investigate these ligand-induced conformational changes at the surface of proteins, we performed a time-resolved fluorescence resonance energy transfer assay with 52 different cofactor peptides measuring the ligand-induced cofactor recruitment to the retinoid X receptor-α (RXRα) in the presence of 11 compounds. Simultaneously we analyzed the binding modes of these compounds by molecular docking. An automated method converted the complex three-dimensional data of ligand-protein interactions into two-dimensional fingerprints, the so-called ligand-receptor interaction profiles. For a subset of compounds the conformational changes at the surface, as measured by peptide recruitment, correlate well with the calculated binding modes, suggesting that clustering of ligand-receptor interaction profiles is a very useful tool to discriminate compounds that may induce different conformations and possibly different effects in a cellular environment. In addition, we successfully combined ligand-receptor interaction profiles and peptide recruitment data to reveal structural elements that are possibly involved in the ligand-induced conformations. Interestingly, we could predict a possible binding mode of LG100754, a homodimer antagonist that showed no effect on peptide recruitment. Finally, the extensive analysis of the peptide recruitment profiles provided novel insight in the potential cellular effect of the compound; for the first time, we showed that in addition to the induction of coactivator peptide binding, all well-known RXRα agonists also induce binding of corepressor peptides to RXRα.

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Nikoloudis, Dimitris, Jim E. Pitts, and José W. Saldanha. "A complete, multi-level conformational clustering of antibody complementarity-determining regions." PeerJ 2 (July 1, 2014): e456. http://dx.doi.org/10.7717/peerj.456.

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Marinova, Veselina, Laurence Dodd, Song-Jun Lee, Geoffrey P. F. Wood, Ivan Marziano, and Matteo Salvalaglio. "Identifying Conformational Isomers of Organic Molecules in Solution via Unsupervised Clustering." Journal of Chemical Information and Modeling 61, no. 5 (April 29, 2021): 2263–73. http://dx.doi.org/10.1021/acs.jcim.0c01387.

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Sittel, Florian, and Gerhard Stock. "Robust Density-Based Clustering To Identify Metastable Conformational States of Proteins." Journal of Chemical Theory and Computation 12, no. 5 (April 21, 2016): 2426–35. http://dx.doi.org/10.1021/acs.jctc.5b01233.

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Klyshko, Eugene, and Sarah Rauscher. "Defining Conformational States of Proteins using Dimensionality Reduction and Clustering Algorithms." Biophysical Journal 116, no. 3 (February 2019): 290a. http://dx.doi.org/10.1016/j.bpj.2018.11.1564.

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Solihah, Binti, Aina Musdholifah, and Azhari Azhari. "A Novel Epitope Dataset: Performance of the MCL-Based Algorithms to Generate Dataset for Graph Learning Model." Engineering Innovations 4 (February 15, 2023): 37–46. http://dx.doi.org/10.4028/p-8a27xd.

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Naturally, the epitope dataset can be presented as a graph. Dataset preparation in the previous methods is part of model development. There are many graph-based classification and regression methods. Still, it is difficult to identify their performance on the conformational epitope prediction model because datasets in a suitable format are unavailable. This research aims to build a dataset in a suitable format to evaluate kernel graph and graph convolution network. This dataset, which results from graph clustering on graph antigens, can be used to identify the performance of many graph neural network-based algorithms for conformational epitope prediction. The Ag-Ab complexes that meet the criteria for forming a conformational epitope prediction dataset from previous studies were downloaded from the Protein Data Bank. Raw datasets in the form of specific exposed antigen chain residues are labeled as epitope or non-epitope based on their proximity to the paratope. The engineering features in the raw dataset are derived from the structure of the antigen-antibody complex and the propensity score. Aggregating atomic-level interactions into residual levels create an initial graph of the antigen chain. The MCL, MLR-MCL, and PS-MCL are graph clustering algorithms to obtain labeled sub-clusters from the initial graph. A balance factor parameter is set to several values to identify the optimal dataset formation based on minimal fragmentation. The output of the MCL algorithm is used as a baseline. As a result of the fragmentation analysis that occurs, the MLR-MCL algorithm gives the best model performance at a balance factor equal to 2. PS-MCL gives the best performance at a value of 0.9. Based on the minimum fragmentation, the MLR-MCL algorithm provides the best model performance compared to MCL and PS-MCL. The dataset in a format according to benchmarking dataset can be used to identify the characteristics of antigen subgraphs formed from the graph clustering process and to explore the performance of graph-based learning conformational epitope prediction models such as graph convolution networks.

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Tu, Sidong, Chandan K. Choudhury, Michaela Giltner, Igor Luzinov, and Olga Kuksenok. "Mesoscale Modeling of Agglomeration of Molecular Bottlebrushes: Focus on Conformations and Clustering Criteria." Polymers 14, no. 12 (June 9, 2022): 2339. http://dx.doi.org/10.3390/polym14122339.

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Using dissipative particle dynamics, we characterize dynamics of aggregation of molecular bottlebrushes in solvents of various qualities by tracking the number of clusters, the size of the largest cluster, and an average aggregation number. We focus on a low volume fraction of bottlebrushes in a range of solvents and probe three different cutoff criteria to identify bottlebrushes belonging to the same cluster. We demonstrate that the cutoff criteria which depend on both the coordination number and the length of the side chain allows one to correlate the agglomeration status with the structural characteristics of bottlebrushes in solvents of various qualities. We characterize conformational changes of the bottlebrush within the agglomerates with respect to those of an isolated bottlebrush in the same solvents. The characterization of bottlebrush conformations within the agglomerates is an important step in understanding the relationship between the bottlebrush architecture and material properties. An analysis of three distinct cutoff criteria to identify bottlebrushes belonging to the same cluster introduces a framework to identify both short-lived transient and long-lived agglomerates; the same approach could be further extended to characterize agglomerates of various macromolecules with complex architectures beyond the specific bottlebrush architecture considered herein.

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Jiang, Hangjin, and Xiaodan Fan. "The Two-Step Clustering Approach for Metastable States Learning." International Journal of Molecular Sciences 22, no. 12 (June 19, 2021): 6576. http://dx.doi.org/10.3390/ijms22126576.

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Understanding the energy landscape and the conformational dynamics is crucial for studying many biological or chemical processes, such as protein–protein interaction and RNA folding. Molecular Dynamics (MD) simulations have been a major source of dynamic structure. Although many methods were proposed for learning metastable states from MD data, some key problems are still in need of further investigation. Here, we give a brief review on recent progresses in this field, with an emphasis on some popular methods belonging to a two-step clustering framework, and hope to draw more researchers to contribute to this area.

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Huang, Zhaohong, Xinyue Cui, Yuhao Xia, Kailong Zhao, and Guijun Zhang. "Pathfinder: Protein folding pathway prediction based on conformational sampling." PLOS Computational Biology 19, no. 9 (September 11, 2023): e1011438. http://dx.doi.org/10.1371/journal.pcbi.1011438.

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The study of protein folding mechanism is a challenge in molecular biology, which is of great significance for revealing the movement rules of biological macromolecules, understanding the pathogenic mechanism of folding diseases, and designing protein engineering materials. Based on the hypothesis that the conformational sampling trajectory contain the information of folding pathway, we propose a protein folding pathway prediction algorithm named Pathfinder. Firstly, Pathfinder performs large-scale sampling of the conformational space and clusters the decoys obtained in the sampling. The heterogeneous conformations obtained by clustering are named seed states. Then, a resampling algorithm that is not constrained by the local energy basin is designed to obtain the transition probabilities of seed states. Finally, protein folding pathways are inferred from the maximum transition probabilities of seed states. The proposed Pathfinder is tested on our developed test set (34 proteins). For 11 widely studied proteins, we correctly predicted their folding pathways and specifically analyzed 5 of them. For 13 proteins, we predicted their folding pathways to be further verified by biological experiments. For 6 proteins, we analyzed the reasons for the low prediction accuracy. For the other 4 proteins without biological experiment results, potential folding pathways were predicted to provide new insights into protein folding mechanism. The results reveal that structural analogs may have different folding pathways to express different biological functions, homologous proteins may contain common folding pathways, and α-helices may be more prone to early protein folding than β-strands.

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Das, Swagata, Supriya Das, Anupam Roy, Uttam Pal, and Nakul C. Maiti. "Orientation of tyrosine side chain in neurotoxic Aβ differs in two different secondary structures of the peptide." Royal Society Open Science 3, no. 10 (October 2016): 160112. http://dx.doi.org/10.1098/rsos.160112.

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Amyloid β (Aβ) peptide is present as a major component in amyloid plaque that is one of the hallmarks of Alzheimer's disease. The peptide contains a single tyrosine residue and Aβ has a major implication in the pathology of the disease progression. Current investigation revealed that the tyrosine side chain attained two different critical stereo orientations in two dissimilar conformational states of the peptide. The extended α-helical structure of the peptide observed in an apolar solvent or methanol/water mixture became disordered in aqueous medium and the radius of gyration decreased. In aqueous medium, the torsional angle around C α –C β of tyrosine group became −60°. However, in its α-helical conformation in an apolar system, the measured angle was 180° and this rotameric state may be reasoned behind stronger tyrosine fluorescence compared with the disordered state of the peptide. Molecular dynamics simulation analyses and spectroscopic studies have helped us to understand the major structural changes in the secondary structure of the peptide in the two conformational states. A conformational clustering indicated that the compact state is more stable with tyrosine residue attaining the torsion angle value of −60°, whereas the native state (in HFIP/water mixture) is prevalent at a torsion angle value of −180°. High solvent accessibility has possibly stabilized the particular rotameric state (−60°) of the tyrosine residue and could be the reason behind decrease in fluorescence of the sole tyrosine residue in an aqueous buffer solution (pH 7.4) compared with its fluorescence in the α-helical structure in the micellar environment.

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Kolloff, Christopher, Adam Mazur, Jan K. Marzinek, Peter J. Bond, Simon Olsson, and Sebastian Hiller. "Motional clustering in supra-τc conformational exchange influences NOE cross-relaxation rate." Journal of Magnetic Resonance 338 (May 2022): 107196. http://dx.doi.org/10.1016/j.jmr.2022.107196.

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41

Allen, F. H., and S. Fortier. "Stereochemical and conformational classification of the hexopyranose sugars using numerical clustering methods." Acta Crystallographica Section B Structural Science 49, no. 6 (December 1, 1993): 1021–31. http://dx.doi.org/10.1107/s0108768193008353.

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Bouchoux, Guy, Sylvie Jezequel, and Florence Penaud-Berruyer. "Conformational effect on gas-phase protonation and NH4+ clustering of 1,2-diols." Organic Mass Spectrometry 28, no. 4 (April 1993): 421–27. http://dx.doi.org/10.1002/oms.1210280426.

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Asses, Yasmine, Vishwesh Venkatraman, Vincent Leroux, David W. Ritchie, and Bernard Maigret. "Exploring c-Met kinase flexibility by sampling and clustering its conformational space." Proteins: Structure, Function, and Bioinformatics 80, no. 4 (January 24, 2012): 1227–38. http://dx.doi.org/10.1002/prot.24021.

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Zuffo, Michela, Aurélie Gandolfini, Brahim Heddi, and Anton Granzhan. "Harnessing intrinsic fluorescence for typing of secondary structures of DNA." Nucleic Acids Research 48, no. 11 (April 20, 2020): e61-e61. http://dx.doi.org/10.1093/nar/gkaa257.

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Abstract High-throughput investigation of structural diversity of nucleic acids is hampered by the lack of suitable label-free methods, combining fast and cheap experimental workflow with high information content. Here, we explore the use of intrinsic fluorescence emitted by nucleic acids for this scope. After a preliminary assessment of suitability of this phenomenon for tracking conformational changes of DNA, we examined steady-state emission spectra of an 89-membered set of oligonucleotides with reported conformation (G-quadruplexes (G4s), i-motifs, single- and double-strands) by means of multivariate analysis. Principal component analysis of emission spectra resulted in successful clustering of oligonucleotides into three corresponding conformational groups, without discrimination between single- and double-stranded structures. Linear discriminant analysis was exploited for the assessment of novel sequences, allowing the evaluation of their G4-forming propensity. Our method does not require any labeling agent or dye, avoiding the related bias, and can be utilized to screen novel sequences of interest in a high-throughput and cost-effective manner. In addition, we observed that left-handed (Z-) G4 structures were systematically more fluorescent than most other G4 structures, almost reaching the quantum yield of 5′-d[(G3T)3G3]-3′ (G3T, the most fluorescent G4 structure reported to date).

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Allen, F. H., and R. Taylor. "Automated conformational analysis from crystallographic data. 5. Recognition of special positions in conformational space in symmetry-modified clustering algorithms." Acta Crystallographica Section B Structural Science 47, no. 3 (June 1, 1991): 404–12. http://dx.doi.org/10.1107/s0108768190014094.

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Bonilla, Steve L., Sarah K. Denny, John H. Shin, Aurora Alvarez-Buylla, William J. Greenleaf, and Daniel Herschlag. "High-throughput dissection of the thermodynamic and conformational properties of a ubiquitous class of RNA tertiary contact motifs." Proceedings of the National Academy of Sciences 118, no. 33 (August 9, 2021): e2109085118. http://dx.doi.org/10.1073/pnas.2109085118.

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Despite RNA’s diverse secondary and tertiary structures and its complex conformational changes, nature utilizes a limited set of structural “motifs”—helices, junctions, and tertiary contact modules—to build diverse functional RNAs. Thus, in-depth descriptions of a relatively small universe of RNA motifs may lead to predictive models of RNA tertiary conformational landscapes. Motifs may have different properties depending on sequence and secondary structure, giving rise to subclasses that expand the universe of RNA building blocks. Yet we know very little about motif subclasses, given the challenges in mapping conformational properties in high throughput. Previously, we used “RNA on a massively parallel array” (RNA-MaP), a quantitative, high-throughput technique, to study thousands of helices and two-way junctions. Here, we adapt RNA-MaP to study the thermodynamic and conformational properties of tetraloop/tetraloop receptor (TL/TLR) tertiary contact motifs, analyzing 1,493 TLR sequences from different classes. Clustering analyses revealed variability in TL specificity, stability, and conformational behavior. Nevertheless, natural GAAA/11ntR TL/TLRs, while varying in tertiary stability by ∼2.5 kcal/mol, exhibited conserved TL specificity and conformational properties. Thus, RNAs may tune stability without altering the overall structure of these TL/TLRs. Furthermore, their stability correlated with natural frequency, suggesting thermodynamics as the dominant selection pressure. In contrast, other TL/TLRs displayed heterogenous conformational behavior and appear to not be under strong thermodynamic selection. Our results build toward a generalizable model of RNA-folding thermodynamics based on the properties of isolated motifs, and our characterized TL/TLR library can be used to engineer RNAs with predictable thermodynamic and conformational behavior.

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van der Wal, Dianne, Sandra Verhoef, Roger Schutgens, Marjolein Peters, Yaping Wu, and Jan Willem Akkerman. "Role of glycoprotein Ibα mobility in platelet function." Thrombosis and Haemostasis 103, no. 05 (2010): 1033–43. http://dx.doi.org/10.1160/th09-11-0751.

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SummaryIncubation at 0°C is known to expose β-N-acetyl-D-glucosamine residues on glycoprotein (GP) Ibα inducing receptor clustering and αMβ2-mediated platelet destruction by macrophages. Here we show that incubation at 0/37°C (4 hours at 0°C, followed by 1 hour at 37°C to mimic cold-storage and post-transfusion conditions) triggers a conformational change in the N-terminal flank (NTF, amino acids, aa 1–35) but not in aa 36–282 of GPIbα as detected by antibody binding. Addition of the sugar N-acetyl-D-glucosamine (GN) inhibits responses induced by 0/37°C. Incubation at 0°C shifts GPIbα from the membrane skeleton to the cytoskeleton. Different GPIbα conformations have little effect on VWF/ristocetin-induced aggregation, but arrest of NTF change by GN interferes with agglutination and spreading on a VWF-coated surface under flow. Strikingly, incubation at 0/37°C initiates thromboxane A2 formation through a von Willebrand factor (VWF)-independent and GPIbα-dependent mechanism, as confirmed in VWF- and GPIbαﺹdeficient platelets. We conclude that the NTF change induced by 0/37°C incubation reflects clustering of GPIbα supports VWF/ristocetin-induced agglutination and spreading and is sufficient to initiate platelet activation in the absence of VWF.

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Mir, Sonia, Sajda Ashraf, Maria Saeed, Atta-ur Rahman, and Zaheer Ul-Haq. "Protonation states at different pH, conformational changes and impact of glycosylation in synapsin Ia." Physical Chemistry Chemical Physics 23, no. 31 (2021): 16718–29. http://dx.doi.org/10.1039/d1cp00531f.

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Synapsin I (SynI) is the most abundant brain phosphoprotein present at presynaptic terminals that regulates neurotransmitter release, clustering of synaptic vesicles (SVs) at active zones, and stimulates synaptogenesis and neurite outgrowth.

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Barszczewski, Marcin, John J. Chua, Alexander Stein, Ulrike Winter, Rainer Heintzmann, Felipe E. Zilly, Dirk Fasshauer, Thorsten Lang, and Reinhard Jahn. "A Novel Site of Action for α-SNAP in the SNARE Conformational Cycle Controlling Membrane Fusion." Molecular Biology of the Cell 19, no. 3 (March 2008): 776–84. http://dx.doi.org/10.1091/mbc.e07-05-0498.

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Regulated exocytosis in neurons and neuroendocrine cells requires the formation of a stable soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex consisting of synaptobrevin-2/vesicle-associated membrane protein 2, synaptosome-associated protein of 25 kDa (SNAP-25), and syntaxin 1. This complex is subsequently disassembled by the concerted action of α-SNAP and the ATPases associated with different cellular activities-ATPase N-ethylmaleimide-sensitive factor (NSF). We report that NSF inhibition causes accumulation of α-SNAP in clusters on plasma membranes. Clustering is mediated by the binding of α-SNAP to uncomplexed syntaxin, because cleavage of syntaxin with botulinum neurotoxin C1 or competition by using antibodies against syntaxin SNARE motif abolishes clustering. Binding of α-SNAP potently inhibits Ca2+-dependent exocytosis of secretory granules and SNARE-mediated liposome fusion. Membrane clustering and inhibition of both exocytosis and liposome fusion are counteracted by NSF but not when an α-SNAP mutant defective in NSF activation is used. We conclude that α-SNAP inhibits exocytosis by binding to the syntaxin SNARE motif and in turn prevents SNARE assembly, revealing an unexpected site of action for α-SNAP in the SNARE cycle that drives exocytotic membrane fusion.

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Yu, Tao, Xing Wu, Kiran B. Gupta, and Dennis F. Kucik. "Affinity, lateral mobility, and clustering contribute independently to β2-integrin-mediated adhesion." American Journal of Physiology-Cell Physiology 299, no. 2 (August 2010): C399—C410. http://dx.doi.org/10.1152/ajpcell.00039.2009.

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Affinity changes and avidity modulation both contribute to activation of β2-integrin-mediated adhesion, an essential, early step in inflammation. Avidity modulation, defined as an increase in adhesiveness independent of integrin conformational changes, might be due to integrin clustering, motion, or both. Increased integrin diffusion upon leukocyte activation has been demonstrated, but whether it is proadhesive in itself, or just constitutes a mechanism for integrin clustering, remains unclear. To understand the proadhesive effects of integrin affinity changes, clustering, and motion, an experimental system was devised to separate them. Clustering and integrin motion together were induced by cytochalasin D (CD) without inducing high-affinity; integrin motion could then be frozen by fixation; and high affinity was induced independently by Mn2+. Adhesion was equivalent for fixed and unfixed cells except following pretreatment with CD or Mn2+, which increased adhesion for both. However, fixed cells were less adhesive than unfixed cells after CD, even though integrin clustering was similar. A simple explanation is that CD induces both clustering and integrin motion, fixation then stops motion on fixed cells, but integrins continue to diffuse on unfixed cells, increasing the kinetics of integrin/ICAM-1 interactions to enhance adhesion. Affinity changes are then independent of, and additive to, avidity effects.

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Journal articles on the topic 'Conformational clustering'

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