Academic literature on the topic 'Conformational clustering'
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Journal articles on the topic "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.
Full textDissertations / Theses on the topic "Conformational clustering"
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Westerlund, Annie M. "Computational Study of Calmodulin’s Ca2+-dependent Conformational Ensembles." Licentiate thesis, KTH, Biofysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-234888.
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Ca2+ and calmodulin play important roles in many physiologically crucial pathways. The conformational landscape of calmodulin is intriguing. Conformational changes allow for binding target-proteins, while binding Ca2+ yields population shifts within the landscape. Thus, target-proteins become Ca2+-sensitive upon calmodulin binding. Calmodulin regulates more than 300 target-proteins, and mutations are linked to lethal disorders. The mechanisms underlying Ca2+ and target-protein binding are complex and pose interesting questions. Such questions are typically addressed with experiments which fail to provide simultaneous molecular and dynamics insights. In this thesis, questions on binding mechanisms are probed with molecular dynamics simulations together with tailored unsupervised learning and data analysis. In Paper 1, a free energy landscape estimator based on Gaussian mixture models with cross-validation was developed and used to evaluate the efficiency of regular molecular dynamics compared to temperature-enhanced molecular dynamics. This comparison revealed interesting properties of the free energy landscapes, highlighting different behaviors of the Ca2+-bound and unbound calmodulin conformational ensembles. In Paper 2, spectral clustering was used to shed light on Ca2+ and target protein binding. With these tools, it was possible to characterize differences in target-protein binding depending on Ca2+-state as well as N-terminal or C-terminal lobe binding. This work invites data-driven analysis into the field of biomolecule molecular dynamics, provides further insight into calmodulin’s Ca2+ and targetprotein binding, and serves as a stepping-stone towards a complete understanding of calmodulin’s Ca2+-dependent conformational ensembles.QC 20180912
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González-Alemán, Roy. "Computational fragment-based design of chemically modified oligonucleotides for selective protein inhibition : BACE1 as a case study." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASL149.
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La conception de médicaments à base de fragments (FBDD) est devenue une approche de plus en plus populaire dans la conception de ligand, avec de nombreuses réussites dans le processus de découverte de médicaments. Malgré certains défis liés à l'accessibilité synthétique et aux stratégies de conception de ligand, le FBDD reste une méthode prometteuse pour aborder l'espace chimique, la complexité moléculaire, la probabilité de liaison et l'efficacité des ligands. Les thérapies à ARN se développent rapidement, subissant une résurgence en raison des nombreux avantages de ces molécules par rapport aux médicaments et anticorps traditionnels, y compris leur petite taille, leur facilité de synthèse, leur stabilité et leur manque d'immunogénicité. Cependant, comme beaucoup d'autres médicaments, les effets hors-cible (où les inhibiteurs conçus pour une molécule spécifique inhibent par inadvertance d'autres recepteurs) peuvent entraver leur utilisation. Dans cette étude, nous introduisons une stratégie emph{in silico} pour la conception par fragments d'une classe prometteuse de ligands : les oligonucléotides chimiquement modifiés qui présentent une sélectivité potentielle pour leurs cibles. Comme preuve de concept, nous avons utilisé l'enzyme BACE1, une cible thérapeutique bien établie pour la maladie d'Alzheimer. L'exploration de la bibliothèque de fragments a été effectuée au moyen de simulations approfondies d'arrimage de mono-nucléotides à l'aide de la méthode de recherche simultanée à copies multiples (MCSS), dont la puissance d'arrimage et de criblage a été rigoureusement évaluée à l'aide d'un benchmark complet de 121 nucléotides-pour la première fois. Un assembleur de nucléotides efficace a été développé pour lier les meilleurs résultats obtenus lors des phases d'amarrage. L'analyse différentielle des oligonucléotides les mieux notés nous a permis de trouver des modes de liaison spécifiques à BACE1 par rapport à BACE2. Au niveau méthodologique, nous proposons également une optimisation substantielle de la mémoire de quatre algorithmes de clustering largement utilisés, qui permettent l'identification des caractéristiques structurelles essentielles pour la liaison ligand-récepteur, partie intégrante de toute campagne FBDDFragment-based drug design (FBDD) has become an increasingly popular approach in ligand design, boasting numerous success stories within the drug discovery process. Despite some challenges relating to synthetic accessibility and ligand-design strategies, FBDD remains a promising method for addressing chemical space, molecular complexity, binding probability, and ligand efficiency. RNA therapeutics are rapidly expanding, undergoing a resurgence due to the several advantages of these molecules over traditional drugs and antibodies, including their small size, ease of synthesis, stability, and lack of immunogenicity. However, like many other drugs, off-target effects (where inhibitors designed for a specific molecule inadvertently inhibit others unintended) can hinder their usage. In this study, we introduce an in silico strategy for the fragment-based designing of a promising class of ligands: chemically modified oligonucleotides that exhibit potential selectivity for their intended targets. As a proof of concept, we employed the BACE1 enzyme, a well-established therapeutic target for Alzheimer's disease. The fragments library exploration was conducted through extensive docking simulations of mono-nucleotides using the Multiple Copy Simultaneous Search method, whose docking and screening power were rigorously assessed through a comprehensive benchmark of 121 nucleotide-protein complexes for the first time. An efficient nucleotide assembler was developed to link the best hits obtained in docking stages. Differential analysis of the best-scored oligonucleotides allowed us to find specific binding modes to BACE1 over BACE2. At a methodological level, we also propose substantial memory optimization of four widely employed clustering algorithms, which allow the identification of essential structural features for ligand-receptor binding, an integral part of any FBDD campaign
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Stamatelou, Ismini Christina. "Clustering approaches for extracting structural determinants of enzyme active sites." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-426221.
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The study of enzyme binding sites is an essential but rather demanding process of increased complexity since the amino acids lining these areas are not rigid. At the same time, the minimization of side effects and the specificity of new ligands is a great challenge in the structure-based drug design approach. Using glycogen phosphorylase - a validated target for the development of new antidiabetic agents - as a case study, this project focuses on the examination of side-chain conformations of amino acids that play a key role in the catalytic site of the enzyme. Specifically, different rotamers of each amino acid were collected to build a dataset of different conformations of the catalytic site. The rotamers were filtered by their probability of occurrence and subsequently, all rotamers that create steric clashes were rejected. Then, these conformations were clustered based on their similarity. Three different clustering algorithms and multiple numbers of clusters were tested using the silhouette scores evaluation for the clustering process. In order to measure the similarity, the Euclidean metric was used which due to the correspondence of the coordinates between the conformations was very similar to the cRMSD metric. Two-level clustering was applied to the dataset for more in-depth observations. According to the clustering results, specific aminoacids with major geometrical variations in their rotamers play the most important role in the separation of the clusters. Additionally, all rotamers of an amino acid can be grouped based on their structure, something that was confirmed using “Chimera” software as a visualization tool. To this end, the ultimate aim of this study is to examine whether the clustering of conformations produces clusters with points geometrically similar to each other, in order to identify near neighbors, i.e. conformations that are quite similar in structure but do not play a determinant role in the function and those that are quite diverse and could be further exploited.
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Asses, Yasmine. "Conception par modélisation et criblage in silico d'inhibiteurs du récepteur c-Met." Phd thesis, Université Henri Poincaré - Nancy I, 2011. http://tel.archives-ouvertes.fr/tel-00653609.
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L'enjeu des travaux effectués au cours de cette thèse est l'extraction in silico de molécules potentiellement intéressantes dans le processus d'inhibition du récepteur tyrosine kinase c-Met. La faculté de cette protéine à interagir dans les phénomènes d'embryogenèse et de réparation tissulaires rendent son inhibition cruciale dans les traitements contre les développements tumoraux où c-Met se trouve impliquée. Dans ce but, la stratégie que nous avons employée implique l'utilisation de plusieurs méthodes in silico de conception rationnelle de médicaments. Nous avons utilisé comme support les multiples structures cristallographiques publiées sur la ProteinData Base (PDB). Un travail de modélisation par homologie fut tout d'abord nécessaire pour combler les lacunes des structures cristallographiques collectées. Afin d'échantillonner au mieux l'espace conformationnel du récepteur kinase c-Met et de caractériser sa flexibilité, une longue campagne de simulation de Dynamique Moléculaire (DM) fut menée concernant les formes apo et holo des structures cristallographiques disponibles. Pour compléter ces simulations, une partie du travail consista à utiliser également la méthode des modes normaux de vibration (NM). De ces 2 approches (DM et NM), nous avons extrait un ensemble de 10 conformères considérés comme les plus représentatifs de l'espace conformationnel simulé pour la kinase c-Met et avons proposé un mode de fonctionnement de ce récepteur. Utilisant les conformations extraites de l'échantillonnage conformationnel, nous avons ensuite mené une importante campagne de criblage virtuel sur plusieurs chimiothèques constituant au total environ 70.000 composés. L'analyse des résultats de l'arrimage moléculaire nous a conduits à la sélection de plusieurs molécules intéressantes possédant théoriquement une bonne affinité pour la kinase c-Met. Ces molécules ont été soumises aux tests expérimentaux effectués par l'équipe de biologistes associée à nos travaux.
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Le, Faucheur Xavier Jean Maurice. "Statistical methods for feature extraction in shape analysis and bioinformatics." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33911.
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The presented research explores two different problems of statistical data analysis.
In the first part of this thesis, a method for 3D shape representation, compression and smoothing is presented. First, a technique for encoding non-spherical surfaces using second generation wavelet decomposition is described. Second, a novel model is proposed for wavelet-based surface enhancement. This part of the work aims to develop an efficient algorithm for removing irrelevant and noise-like variations from 3D shapes. Surfaces are encoded using second generation wavelets, and the proposed methodology consists of separating noise-like wavelet coefficients from those contributing to the relevant part of the signal. The empirical-based Bayesian models developed in this thesis threshold wavelet coefficients in an adaptive and robust manner. Once thresholding is performed, irrelevant coefficients are removed and the inverse wavelet transform is applied to the clean set of wavelet coefficients. Experimental results show the efficiency of the proposed technique for surface smoothing and compression.
The second part of this thesis proposes using a non-parametric clustering method for studying RNA (RiboNucleic Acid) conformations. The local conformation of RNA molecules is an important factor in determining their catalytic and binding properties. RNA conformations can be characterized by a finite set of parameters that define the local arrangement of the molecule in space. Their analysis is particularly difficult due to the large number of degrees of freedom, such as torsion angles and inter-atomic distances among interacting residues. In order to understand and analyze the structural variability of RNA molecules, this work proposes a methodology for detecting repetitive conformational sub-structures along RNA strands. Clusters of similar structures in the conformational space are obtained using a nearest-neighbor search method based on the statistical mechanical Potts model. The proposed technique is a mostly automatic clustering algorithm and may be applied to problems where there is no prior knowledge on the structure of the data space, in contrast to many other clustering techniques. First, results are reported for both single residue conformations- where the parameter set of the data space includes four to seven torsional angles-, and base pair geometries. For both types of data sets, a very good match is observed between the results of the proposed clustering method and other known classifications, with only few exceptions. Second, new results are reported for base stacking geometries. In this case, the proposed classification is validated with respect to specific geometrical constraints, while the content and geometry of the new clusters are fully analyzed.
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YU, Chun-Ping, and 游竣評. "Kinetics and thermodynamics of protein-folding simulations by clustering conformational ensemble." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/18919973484035044063.
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博士國立中央大學
物理研究所
97
The kinetics of the folding of the Trp-cage and protein G were studied in all-atomic molecular dynamics simulations using the AMBER 2003 force-field in implicit solvent. Replica exchange method (REM) was used to enhance sampling of folding conformational space. Folding simulations of twenty-four replicas of Trp-cage and protein G were run from extended state and native state, respectively, ranging from 276 K to 508 K. The conformational ensemble of molecular simulations was clustering by OPTICS. The results showed that the folding conformational spaces for both proteins are hierarchical. The average conformation representing centroid clustering structure for Trp-cage has a backbone root mean square deviation of 1.2 A relative to experimental structure, and 1.4 A for protein G. After regression tree analyze for mapping cluster ordering generated by OPTICS, the folding conformational space can demarcate four hierarchical regimes: unfolded state, formation of secondary structure, formation of tertiary structure, and native state. Three characterized factors for Trp-cage, Pro12-Ψ angle, Leu2-Ψ angle, and total energy, dominated folding space; and four factors for protein G: Lys4-Ψ, Thr18-Ψ, Glu42-Ψ, and Asp22-Ψ.
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Huang, Fei. "Optimizing hydropathy scale to improve IDP prediction and characterizing IDPs' functions." Thesis, 2014. http://hdl.handle.net/1805/5191.
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Indiana University-Purdue University Indianapolis (IUPUI)Intrinsically disordered proteins (IDPs) are flexible proteins without defined 3D structures. Studies show that IDPs are abundant in nature and actively involved in numerous biological processes. Two crucial subjects in the study of IDPs lie in analyzing IDPs’ functions and identifying them. We thus carried out three projects to better understand IDPs. In the 1st project, we propose a method that separates IDPs into different function groups. We used the approach of CH-CDF plot, which is based the combined use of two predictors and subclassifies proteins into 4 groups: structured, mixed, disordered, and rare. Studies show different structural biases for each group. The mixed class has more order-promoting residues and more ordered regions than the disordered class. In addition, the disordered class is highly active in mitosis-related processes among others. Meanwhile, the mixed class is highly associated with signaling pathways, where having both ordered and disordered regions could possibly be important. The 2nd project is about identifying if an unknown protein is entirely disordered. One of the earliest predictors for this purpose, the charge-hydropathy plot (C-H plot), exploited the charge and hydropathy features of the protein. Not only is this algorithm simple yet powerful, its input parameters, charge and hydropathy, are informative and readily interpretable. We found that using different hydropathy scales significantly affects the prediction accuracy. Therefore, we sought to identify a new hydropathy scale that optimizes the prediction. This new scale achieves an accuracy of 91%, a significant improvement over the original 79%. In our 3rd project, we developed a per-residue C-H IDP predictor, in which three hydropathy scales are optimized individually. This is to account for the amino acid composition differences in three regions of a protein sequence (N, C terminus and internal). We then combined them into a single per-residue predictor that achieves an accuracy of 74% for per-residue predictions for proteins containing long IDP regions.
Book chapters on the topic "Conformational clustering"
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Bottegoni, Giovanni, Walter Rocchia, and Andrea Cavalli. "Application of Conformational Clustering in Protein–Ligand Docking." In Methods in Molecular Biology, 169–86. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-61779-465-0_12.
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Albert, Silvana, and Gabriela Czibula. "ProteinA: An Approach for Analyzing and Visualizing Protein Conformational Transitions Using Fuzzy and Hard Clustering Techniques." In Knowledge Science, Engineering and Management, 249–61. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29551-6_22.
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Rappuoli, R. "Introduction." In Guidebook to Protein Toxins and Their Use in Cell Biology, 25–27. Oxford University PressOxford, 1997. http://dx.doi.org/10.1093/oso/9780198599555.003.0008.
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Abstract The ability to sense extracellular signals is essential for all living organisms. In animals, the presence of specialized tissues with different functions, that need to coordinate and regulate their activities, makes signal transduction even more essential. Signals are most often delivered to surface receptors by hormones, growth factors, cell to cell contacts, etc. Once triggered by the ligand, the receptor is activated and the signal is transduced across the cell membrane by receptor clustering and/or conformational changes, that results in biochemical changes on the cytosolic side of the membrane. These occur mainly by two mechanisms:tyrosine kinase receptor phosphorylation of specific sites of its carboxyterminal cytoplasmic domain, that recruits SH2-transducers to start a cascade of phosphorylation of intracellular targets;modification of a receptor-coupled G protein that transduces the signal to enzymes, releasing second messengers such as cyclic-AMP (cAMP), inositoltriphosphate (ITP), diacyglycerol (DG), to a cytoplasmic kinase etc.
Conference papers on the topic "Conformational clustering"
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Parise, L. V., B. Steiner, L. Nannizzi, and D. A. Phillips. "PEPTIDES FROM FIBRINOGENAND FIBRONECTIN CHANGE THE CONFORMATIONOF PURIFIED PLATELET GLYCOPROTEIN IIb-IIIa." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1643697.
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Specific amino acid sequences in fibrinogen and fibronectin appear to mediate the binding of these ligands to the glycoprotein (GP) IIb-IIIacomplex in platelets. Thesesequences include LGGAKQAGDV from the y chain of fibrinogen, and RGD(S) from the a chain of fibrinogenand the cell-binding domain of fibronectin. Several recent reports suggest thatfibrinogen and/or peptides with these sequences cause clustering of GPIIb-IIIa on the platelet surface and Na+/H+ exchange in epinephrine-stimulated platelets. Thus, it is possible that occupancy of specific sites on GP Ilb-IIIa affects its conformation, initiating such events. In this study,we determined whether LGGAKQAGDV, RGDS, and related peptides affect the conformation of purified platelet GP IIb-IIIa. Conformational changes in GP IIb-IIIa were evaluated bychanges in proteolytic susceptibility and hydrodynamic properties. Thepurified GP IIb-IIIa complex was fund to be resistant to proteolysis bythrombin. However, pretreatment of GP IIb-IIIa with various peptidesincreased the susceptibility ofGP libα to thrombin-induced proteolysis,as quantitated onpolyacryfamide gels.The order of potency of these peptides was RGDS<LGGAKQAGDV < KGDS < RGES. This order of potency agrees with that for the abilityof these peptides to inhibit 125I-fibrinogen binding to platelets. The effect of the peptides on proteolysis was time-, temperature-, and concentration-dependent; RGDS Induced a half-maximal effect at ˜60μM. Evaluation of the hydrodynamic properties of GP IIb-IIIa showed that LGGAKQAGDV orRGDS, but not RGES, decreased thesedimentation coefficient of GP IIb-IIIa from 8.5S to 7.7 S or7.4, S,respectively. This changewas accompanied by an increase in theStoke’s radius from 73 A to 84 A. These results suggestthat LGGAKQAGDV andRGDS alterthe conformationof the purified GPIIb-IIIa heterodimer complex by causing it to unfold.This change in conformation may be related to changesin the distribution and function of GP IIb-IIIaon the platelet surface that occurwith occupancy ofligand binding sites.
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Haack, Fiete, Susanna Röblitz, Olga Scharkoi, Burkhard Schmidt, Marcus Weber, Theodore E. Simos, George Psihoyios, and Ch Tsitouras. "Adaptive Spectral Clustering for Conformation Analysis." In ICNAAM 2010: International Conference of Numerical Analysis and Applied Mathematics 2010. AIP, 2010. http://dx.doi.org/10.1063/1.3498116.
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Guo, Ziyi, and Brian Y. Chen. "Variational Bayesian clustering on protein cavity conformations for detecting influential amino acids." In BCB '14: ACM-BCB '14. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2649387.2660837.
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Estrada, Trlce, Roger Armen, and Michela Taufer. "Automatic selection of near-native protein-ligand conformations using a hierarchical clustering and volunteer computing." In the First ACM International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1854776.1854807.
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Jukić, Marko, and Urban Bren. "Identification of small molecule binding sites using CmDock." In 2nd International Conference on Chemo and Bioinformatics. Institute for Information Technologies, University of Kragujevac, 2023. http://dx.doi.org/10.46793/iccbi23.670j.
Full textAbstract:
Identification of binding sites for small molecules is critical in light of modern in silico and experimental methods for structure elucidation such as AlfaFold and CryoEM, respectively. The total number of entries in the PDB database is 208,702 through July 2023, and there are a large number of structural data without similar experimental entries and mechanistic or small molecule data. Herein, we report a simple, rapid, and efficient protocol for the identification of drug-like binding sites of small molecules using extended sampling with the self-developed molecular docking software CmDock. The protocol consists of preparing a docking receptor using the RbtProteinMapper method, which uses a full protein surface as a reference. Then, a series of drug-like interaction sampling probes are docked in an extended sampling of 1000 or more runs. The binding conformations calculated by the probes are analyzed using PacMAP reduction and DBSCAN density clustering to identify binding sites. The protocol is capable of identifying known binding sites of small molecules in a very short time frame. In addition, we demonstrate the application of the method to a known DNA Gyrase as well as to a STAT3 NTD domain system.