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17 results for “homology modelling”
Homology modelling, molecular docking and molecular dynamics simulations of wild type and mutant human CYP2J2 with three polyunsaturated fatty acids
<p>This is the "parent" repository for the Data Note : "­Molecular dynamics simulations of the interaction of wild type and mutant human CYP2J2 with polyunsaturated fatty acids" by Abelak, Bishop-Bailey and Nobeli.</p> <p>It contains a document (<strong>Abelak_etal_Methods.pdf</strong>) describing the methods used to produce the data here and the data in all repositories supplementing it.</p> <p>It also contains a shell script (<strong>create_sim4_repeats.sh</strong>) that is typical of those used to set up the molecular dynamics simulations in the repositories supplementing this one.</p> <p>Finally, it contains the results of the homology modelling and docking simulations that formed the starting points for the molecular dynamics simulations in this study.</p> <p>Description of files in this dataset:</p> <p><strong>C2J2_min3_mod_noH.pdb</strong> : Homology model of the wild type CYP2J2 built from an alignment of templates with PDB ids: 1SUO, 2P85, 3EBS and 1Z10.</p> <p><strong>docking_wild_type_C2J2.zip</strong> : Nine docked poses of arachidonic acid docked to the homology model of the wild type CYP2J2.</p> <p>Details of how this data was produced is available in the Abelak_etal_Methods.docx document.</p>
Structure of the Nt domain of mouse NBCe1 by homology modeling
<p>For the generation of the Nt model for NBCe1, a pair-wise alignment of the Nt region (residues 82-381) of mouse NBCe1-B (NCBI accession NP_061230.2) and the homologous portion of human NDCBE Nt (NCBI accession AAY79176) was generated by SWISS-MODEL. The overall identity is 54.55% between the two sequences. The alignment was used for structural modeling with the crystal structure of human NDCBE Nt (PDB ID: 5JHO) as the template. Structural assessment shows that the simulated model of NBCe1 Nt had QMEAN value −3.25, Cβ value −3.11, solvation value −0.62, torsion value −2.54, and scored 1.86 by using a MolProbity approach.</p>
Fig. 1 in Echinoderm model systems, homology, and phylogenetic inference: comment and reply to Paul (2021)
Fig. 1. Tree comparison between two phylogenetic inference methods with bootstrap support at the nodes. A. Phylogenetic hypothesis from Paul (2021) inferred via maximum parsimony. B. Phylogenetic hypothesis inferred via maximum likelihood.
Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity
<p>Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small number of available atomic resolution structures. We assessed the use of homology modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Homology models of the D<sub>2</sub> dopamine (D<sub>2</sub>R) and serotonin 5-HT<sub>2A</sub> receptors (5-HT<sub>2A</sub>R) were generated based on crystal structures of 16 different GPCRs. Comparison of the homology models to D<sub>2</sub>R and 5-HT<sub>2A</sub>R crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. Assessment of virtual screening performance was based on molecular docking of ligands and decoys. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs displayed ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. The best models even displayed ligand enrichment better than that of the D<sub>2</sub>R and 5-HT<sub>2A</sub>R crystal structures. Methods to consider binding site plasticity were explored to further improve predictions. Molecular docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Molecular dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homology models. These results provide guidelines for successful application of structure-based ligand discovery using GPCR homology models.</p>
Supplemental Movie Files for "Agent-Based Modeling of a Nuclear Chromosome Ensemble Identifies Determinants of Homolog Pairing During Meiosis" by Chriss et al.
<p>This set of Supplemental Information contains two movies made from the simulations from the model developed in the manuscript "<strong>Agent-Based Modeling of a Nuclear Chromosome Ensemble Identifies Determinants of Homolog Pairing During Meiosis</strong>" by A. Chriss, G. V. Börner, and S. D. Ryan. </p> <p> </p> <p>Supplemental Movie S1: <strong>WT Chromosome Trajectories during Prophase I. </strong>The first file "movie_WT..." contains the file for the results of simulations for the wild-type chromosomes and the exact parameter values can be found in Table 1 of the manuscript. The movie shows one realization of the agent-based model. The simulation movie covers the homology search process from <em>t = 3h </em>to <em>t = 9h</em>. Matching colors correspond to homologous pairs. True chromosome lengths are incorporated and scale the relevant interaction radii. The radius represents the attractive and non-homologous repulsive region.</p> <p> </p> <p>Supplemental Movie S2: <strong>WT Chromosome Trajectories during Prophase I with active dumbbell model. </strong> The second file "movie<em>WT</em>_activedumbbell..." contains the file for the results of the simulations for the modeling of chromosomes as active dumbbells (from polymers) to allow for the study of the effects of elongation, orientation, and flexibility. The movie shows one realization of the agent-based active dumbbell model which is closer to modeling a chromosome as a polymer. The simulation movie covers the homology search process from <em>t = 3h </em>to <em>t = 9h</em>. Matching colors correspond to homologous pairs. True chromosome lengths are incorporated and scale the relevant interaction radii, but are allowed to change in time as the two beads expand and contract. The radius represents the attractive and non-homologous repulsive region.</p> <p> </p> <p>Supplemental Movie S3: <strong><em>spo11</em> hypomorph (30% WT DSB levels) Chromosome Trajectories during Prophase I (parameters from Fig 7B)</strong>. The third file "movie_spo11..." contains the file for the results of the simulations for the spo-11 hypomorph and the associated parameter values can be found in Table 1 of the manuscript. The movie depicts one realization of the agent-based model for the {\it spo11} hypomorphic mutant. The simulation movie covers the homology search process from <em>t = 3h</em> to <em>t = 9h</em> where mutant <em>spo11</em> is associated with a weaker attractive and repulsive force (e.g., reduction to 77% of WT values). True chromosome lengths are incorporated and scale the relevant interaction radii. Matching colors correspond to homologous pairs. The radii represent the homologous attractive and the non-homologous repulsive region. Note that the reduction in interaction strength delays homologous pairing consistent with experimental observations in [13]. </p> <p> </p> <p> </p> <p>The codes that generated these movies were written in Matlab and freely available via GitHub: <a href="https://github.com/sdryan/ChromosomeDynamicsProphase1">https://github.com/sdryan/ChromosomeDynamicsProphase1</a></p> <p> </p> <p>For questions please contact the corresponding authors: G. Valentin Börner <a href="mailto:g.boerner@csuohio.edu">g.boerner@csuohio.edu</a> (Biology) or Shawn D. Ryan <a href="mailto:s.d.ryan@csuohio.edu">s.d.ryan@csuohio.edu</a> (Math).</p>
Saccharomyces cerevisiae IRC7 homology model
<p><strong>IRC7 homology model for S. cerevisiae.</strong></p> <p>IRC7 was modelled using the structures for <em>Escherichia coli</em> Cystathionine beta-lyase (PDB accession: 1CL2) and <em>Trichomonas vaginalis </em>Methionine Gamma-Lyase (PDB accession: 1E5F) as comparative references. The A and B chains of 1CL2 were superposed to 1E5F. The sequences for IRC7, 1CL2 and 1E5F were aligned with clustalx. Ten models were generated with UCSF Modeller v9.15 and evaluated with PROCHECK. The best model is uploaded here and is also available at the Protein Model DataBase (accession: PM0081794).</p>
Homology model based on 1JXX
<p>Homology model based on 1JXX</p> <p>starting sequence: SVCCPSLVARTNYNVCRLPGTEAALCATFTGCIIIPGATCGGDYAN</p> <p>Swiss Model online 24-11-2019</p>
Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity
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Structure of transmembrane domain of mouse NBCe1 by homology modeling
<p>The structure model of the transmembrane domain of mouse NBCe1 was generated by SWISS-MODEL with the cryo-EM structure of human NBCe1 (PDB ID: 6CAA) as the template. Residues 445–1007 of mouse NBCe1-B was aligned with the homologous region of human NBCe1 by using SWISS-MODEL. The sequence identity between the two sequences is 96.09%. Structural assessment shows that the simulated model of mouse NBCe1 had QMEAN value −6.86, Cβ −3.57, solvation value −1.80, torsion value −5.49, and scored 1.49 by MolProbity approach.</p>
Data from: Serial homology and correlated characters in morphological phylogenetics: modeling the evolution of dental crests in placentals
Accurate modeling of the complexity of morphological evolution is crucial for morphological phylogenetics and for performing tests on a wide variety of evolutionary scenarios. In this context, morphological integration and the problem of correlated categorical characters represent a major challenge. In particular, the magnitude and implications of correlations among serially homologous structures such as teeth have been much debated but were never tested statistically within a broad phylogenetic context. Here, we present a large-scale empirical study analyzing the serial variation of cingular crests on successive molars (M1, M2 and M3) of 274 placental species in a phylogenetic context. Both likelihood analyses and analysis of phylogenetic co-distributions demonstrated highly correlated evolution in the entire sample and thus the non-independence of these serial features at a macroevolutionary scale. Likelihood analyses show that their serial variation should be better scored within a single composite character model with constrained paths for transitions enabling simultaneous changes on all three molars, which suggests a strong developmental or genetic integration. These results are congruent with current molecular and developmental knowledge related to dental morphological variation and call into question the frequent use of separate characters scored on serially homologous structures of the dentition in phylogenetic analyses. Overall, they provide long-overdue and clear empirical evidence that in-depth studies of patterns of integration constitute an essential step towards more realistic character construction and modeling. This approach is critical for more accurate morphological phylogenetics and, more generally, for testing macroevolutionary scenarios on groups of correlated characters.
Live imaging and biophysical modeling support a button-based mechanism of somatic homolog pairing in Drosophila
<p></p><p>3D eukaryotic genome organization provides the structural basis for gene regulation. In Drosophila melanogaster, genome folding is characterized by somatic homolog pairing, where homologous chromosomes are intimately paired from end to end; however, how homologs identify one another and pair has remained mysterious. Recently, this process has been proposed to be driven by specifically interacting 'buttons' encoded along chromosomes. Here, we turned this hypothesis into a quantitative biophysical model to demonstrate that a button-based mechanism can lead to chromosome-wide pairing. We tested our model using live-imaging measurements of chromosomal loci tagged with the MS2 and PP7 nascent RNA labeling systems. We show solid agreement between model predictions and experiments in the pairing dynamics of individual homologous loci. Our results strongly support a button-based mechanism of somatic homolog pairing in Drosophila and provide a theoretical framework for revealing the molecular identity and regulation of buttons.</p><p></p>
Campylobacter Jejuni Challenge Model Development: Assessment of Homologous Protection
ClinicalTrials.gov study NCT01048112. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: A logical model of homology for comparative biology
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Live imaging and biophysical modeling support a button-based mechanism of somatic homolog pairing in Drosophila
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Data from: Serial homology and correlated characters in morphological phylogenetics: modeling the evolution of dental crests in placentals
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Homology Model for the IRAK-M death domain
<p>Dataset for the contruction and validation of a homology model for the IRAK-M death domain.</p>
HiPHD: Hierarchical Classification for Protein Remote Homology Detection using Graph Neural Networks and Language Models
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