Browse
Submit Data
Databases
API
Help

Dataset Information

16 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

FILTREST3D: discrimination of structural models using restraints from experimental data.

ABSTRACT: Automatic methods for macromolecular structure prediction (fold recognition, de novo folding and docking programs) produce large sets of alternative models. These large model sets often include many native-like structures, which are often scored as false positives. Such native-like models can be more easily identified based on data from experimental analyses used as structural restraints (e.g. identification of nearby residues by cross-linking, chemical modification, site-directed mutagenesis, deuterium exchange coupled with mass spectrometry, etc.). We present a simple server for scoring and ranking of models according to their agreement with user-defined restraints.FILTREST3D is freely available for users as a web server and standalone software at: http://filtrest3d.genesilico.pl/iamb@genesilico.plSupplementary data are available at Bioinformatics online.

SUBMITTER: Gajda MJ

PROVIDER: S-EPMC2982159 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

FILTREST3D: discrimination of structural models using restraints from experimental data.

Gajda Michal J MJ Tuszynska Irina I Kaczor Marta M Bakulina Anastasia Yu AY Bujnicki Janusz M JM

Bioinformatics (Oxford, England) 20101017 23

<h4>Summary</h4>Automatic methods for macromolecular structure prediction (fold recognition, de novo folding and docking programs) produce large sets of alternative models. These large model sets often include many native-like structures, which are often scored as false positives. Such native-like models can be more easily identified based on data from experimental analyses used as structural restraints (e.g. identification of nearby residues by cross-linking, chemical modification, site-directe ...[more]

PMID: 20956242

Similar Datasets

Structural prediction of protein models using distance restraints derived from cross-linking mass spectrometry data.

Project description:This protocol describes a workflow for creating structural models of proteins or protein complexes using distance restraints derived from cross-linking mass spectrometry experiments. The distance restraints are used (i) to adjust preliminary models that are calculated on the basis of a homologous template and primary sequence, and (ii) to select the model that is in best agreement with the experimental data. In the case of protein complexes, the cross-linking data are further used to dock the subunits to one another to generate models of the interacting proteins. Predicting models in such a manner has the potential to indicate multiple conformations and dynamic changes that occur in solution. This modeling protocol is compatible with many cross-linking workflows and uses open-source programs or programs that are free for academic users and do not require expertise in computational modeling. This protocol is an excellent additional application with which to use cross-linking results for building structural models of proteins. The established protocol is expected to take 6-12 d to complete, depending on the size of the proteins and the complexity of the cross-linking data.

| S-EPMC5999019 | biostudies-literature

Discrimination between thermodynamic models of cis-regulation using transcription factor occupancy data.

Project description:Many studies have identified binding preferences for transcription factors (TFs), but few have yielded predictive models of how combinations of transcription factor binding sites generate specific levels of gene expression. Synthetic promoters have emerged as powerful tools for generating quantitative data to parameterize models of combinatorial cis-regulation. We sought to improve the accuracy of such models by quantifying the occupancy of TFs on synthetic promoters in vivo and incorporating these data into statistical thermodynamic models of cis-regulation. Using chromatin immunoprecipitation-seq, we measured the occupancy of Gcn4 and Cbf1 in synthetic promoter libraries composed of binding sites for Gcn4, Cbf1, Met31/Met32 and Nrg1. We measured the occupancy of these two TFs and the expression levels of all promoters in two growth conditions. Models parameterized using only expression data predicted expression but failed to identify several interactions between TFs. In contrast, models parameterized with occupancy and expression data predicted expression data, and also revealed Gcn4 self-cooperativity and a negative interaction between Gcn4 and Nrg1. Occupancy data also allowed us to distinguish between competing regulatory mechanisms for the factor Gcn4. Our framework for combining occupancy and expression data produces predictive models that better reflect the mechanisms underlying combinatorial cis-regulation of gene expression.

| S-EPMC3936720 | biostudies-literature

Protein loop closure using orientational restraints from NMR data.

Project description:Protein loops often play important roles in biological functions. Modeling loops accurately is crucial to determining the functional specificity of a protein. Despite the recent progress in loop prediction approaches, which led to a number of algorithms over the past decade, few rigorous algorithmic approaches exist to model protein loops using global orientational restraints, such as those obtained from residual dipolar coupling (RDC) data in solution nuclear magnetic resonance (NMR) spectroscopy. In this article, we present a novel, sparse data, RDC-based algorithm, which exploits the mathematical interplay between RDC-derived sphero-conics and protein kinematics, and formulates the loop structure determination problem as a system of low-degree polynomial equations that can be solved exactly, in closed-form. The polynomial roots, which encode the candidate conformations, are searched systematically, using provable pruning strategies that triage the vast majority of conformations, to enumerate or prune all possible loop conformations consistent with the data; therefore, completeness is ensured. Results on experimental RDC datasets for four proteins, including human ubiquitin, FF2, DinI, and GB3, demonstrate that our algorithm can compute loops with higher accuracy, a three- to six-fold improvement in backbone RMSD, versus those obtained by traditional structure determination protocols on the same data. Excellent results were also obtained on synthetic RDC datasets for protein loops of length 4, 8, and 12 used in previous studies. These results suggest that our algorithm can be successfully applied to determine protein loop conformations, and hence, will be useful in high-resolution protein backbone structure determination, including loops, from sparse NMR data. Proteins 2012. © 2011 Wiley Periodicals, Inc.

| S-EPMC3305838 | biostudies-literature

Proton channel models filling the gap between experimental data and the structural rationale.

Project description:Voltage-gated proton channels are integral membrane proteins with the capacity to permeate elementary particles in a voltage- and pH-dependent manner. These proteins have been found in several species and are involved in various physiological processes. Although their primary topology is known, lack of details regarding their structures in the open conformation has limited analyses toward a deeper understanding of the molecular determinants of their function and regulation. Consequently, the function–structure relationships have been inferred based on homology models. In the present work, we review the existing proton channel models, their assumptions, predictions, and the experimental facts that support them. Modeling proton channels is not a trivial task due to the lack of a close homolog template. Hence, there are important differences between published models. This work attempts to critically review existing proton channel models toward the aim of contributing to a better understanding of the structural features of these proteins.

| S-EPMC4203746 | biostudies-literature

MESMER: minimal ensemble solutions to multiple experimental restraints.

Project description:MotivationMacromolecular structures and interactions are intrinsically heterogeneous, temporally adopting a range of configurations that can confound the analysis of data from bulk experiments. To obtain quantitative insights into heterogeneous systems, an ensemble-based approach can be employed, in which predicted data computed from a collection of models is compared to the observed experimental results. By simultaneously fitting orthogonal structural data (e.g. small-angle X-ray scattering, nuclear magnetic resonance residual dipolar couplings, dipolar electron-electron resonance spectra), the range and population of accessible macromolecule structures can be probed.ResultsWe have developed MESMER, software that enables the user to identify ensembles that can recapitulate experimental data by refining thousands of component collections selected from an input pool of potential structures. The MESMER suite includes a powerful graphical user interface (GUI) to streamline usage of the command-line tools, calculate data from structure libraries and perform analyses of conformational and structural heterogeneity. To allow for incorporation of other data types, modular Python plugins enable users to compute and fit data from nearly any type of quantitative experimental data.ResultsConformational heterogeneity in three macromolecular systems was analyzed with MESMER, demonstrating the utility of the streamlined, user-friendly software.Availability and implementationhttps://code.google.com/p/mesmer/

| S-EPMC4542774 | biostudies-literature

Using surface envelopes for discrimination of molecular models.

Project description:Shape information about macromolecules is increasingly available but is difficult to use in modeling efforts. We demonstrate that shape information alone can often distinguish structural models of biological macromolecules. By using a data structure called a surface envelope (SE) to represent the shape of the molecule, we propose a method that generates a fitness score for the shape of a particular molecular model. This score correlates well with root mean squared deviation (RMSD) of the model to the known test structures and can be used to filter models in decoy sets. The scoring method requires both alignment of the model to the SE in three-dimensional space and assessment of the degree to which atoms in the model fill the SE. Alignment combines a hybrid algorithm using principal components and a previously published iterated closest point algorithm. We test our method against models generated from random atom perturbation from crystal structures, published decoy sets used in structure prediction, and models created from the trajectories of atoms in molecular modeling runs. We also test our alignment algorithm against experimental electron microscopic data from rice dwarf virus. The alignment performance is reliable, and we show a high correlation between model RMSD and score function. This correlation is stronger for molecular models with greater oblong character (as measured by the ratio of largest to smallest principal component).

| S-EPMC2286533 | biostudies-literature

Experimental and Computational Models for Side Chain Discrimination in Peptide-Protein Interactions.

Project description:A bis(18-crown-6) Tröger's base receptor and 4-substituted hepta-1,7-diyl bisammonium salt ligands have been used as a model system to study the interactions between non-polar side chains of peptides and an aromatic cavity of a protein. NMR titrations and NOESY/ROESY NMR spectroscopy were used to analyze the discrimination of the ligands by the receptor based on the substituent of the ligand, both quantitatively (free binding energies) and qualitatively (conformations). The analysis showed that an all-anti conformation of the heptane chain was preferred for most of the ligands, both free and when bound to the receptor, and that for all of the receptor-ligand complexes, the substituent was located inside or partly inside of the aromatic cavity of the receptor. We estimated the free binding energy of a methyl- and a phenyl group to an aromatic cavity, via CH-π, and combined aromatic CH-π and π-π interactions to be -1.7 and -3.3 kJ mol-1 , respectively. The experimental results were used to assess the accuracy of different computational methods, including molecular mechanics (MM) and density functional theory (DFT) methods, showing that MM was superior.

| S-EPMC8362025 | biostudies-literature

Simulating longitudinal data from marginal structural models using the additive hazard model.

Project description:Observational longitudinal data on treatments and covariates are increasingly used to investigate treatment effects, but are often subject to time-dependent confounding. Marginal structural models (MSMs), estimated using inverse probability of treatment weighting or the g-formula, are popular for handling this problem. With increasing development of advanced causal inference methods, it is important to be able to assess their performance in different scenarios to guide their application. Simulation studies are a key tool for this, but their use to evaluate causal inference methods has been limited. This paper focuses on the use of simulations for evaluations involving MSMs in studies with a time-to-event outcome. In a simulation, it is important to be able to generate the data in such a way that the correct forms of any models to be fitted to those data are known. However, this is not straightforward in the longitudinal setting because it is natural for data to be generated in a sequential conditional manner, whereas MSMs involve fitting marginal rather than conditional hazard models. We provide general results that enable the form of the correctly specified MSM to be derived based on a conditional data generating procedure, and show how the results can be applied when the conditional hazard model is an Aalen additive hazard or Cox model. Using conditional additive hazard models is advantageous because they imply additive MSMs that can be fitted using standard software. We describe and illustrate a simulation algorithm. Our results will help researchers to effectively evaluate causal inference methods via simulation.

| S-EPMC7612178 | biostudies-literature

Structural investigation of MscL gating using experimental data and coarse grained MD simulations.

Project description:The mechanosensitive channel of large conductance (MscL) has become a model system in which to understand mechanosensation, a process involved in osmoregulation and many other physiological functions. While a high resolution closed state structure is available, details of the open structure and the gating mechanism remain unknown. In this study we combine coarse grained simulations with restraints from EPR and FRET experiments to study the structural changes involved in gating with much greater level of conformational sampling than has previously been possible. We generated a set of plausible open pore structures that agree well with existing open pore structures and gating models. Most interestingly, we found that membrane thinning induces a kink in the upper part of TM1 that causes an outward motion of the periplasmic loop away from the pore centre. This previously unobserved structural change might present a new mechanism of tension sensing and might be related to a functional role in osmoregulation.

| S-EPMC3447979 | biostudies-literature

Experimental discrimination of ion stopping models near the Bragg peak in highly ionized matter.

Project description:The energy deposition of ions in dense plasmas is a key process in inertial confinement fusion that determines the ?-particle heating expected to trigger a burn wave in the hydrogen pellet and resulting in high thermonuclear gain. However, measurements of ion stopping in plasmas are scarce and mostly restricted to high ion velocities where theory agrees with the data. Here, we report experimental data at low projectile velocities near the Bragg peak, where the stopping force reaches its maximum. This parameter range features the largest theoretical uncertainties and conclusive data are missing until today. The precision of our measurements, combined with a reliable knowledge of the plasma parameters, allows to disprove several standard models for the stopping power for beam velocities typically encountered in inertial fusion. On the other hand, our data support theories that include a detailed treatment of strong ion-electron collisions.

| S-EPMC5461488 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data