Protein quality assessment is a long-standing problem in bioinformatics. For more than a decade we have developed state-of-art predictors by carefully selecting and optimising inputs to a machine ...learning method. The correlation has increased from 0.60 in ProQ to 0.81 in ProQ2 and 0.85 in ProQ3 mainly by adding a large set of carefully tuned descriptions of a protein. Here, we show that a substantial improvement can be obtained using exactly the same inputs as in ProQ2 or ProQ3 but replacing the support vector machine by a deep neural network. This improves the Pearson correlation to 0.90 (0.85 using ProQ2 input features).
ProQ3D is freely available both as a webserver and a stand-alone program at http://proq3.bioinfo.se/.
arne@bioinfo.se.
Supplementary data are available at Bioinformatics online.
Abstract
Motivation
Residue contact prediction was revolutionized recently by the introduction of direct coupling analysis (DCA). Further improvements, in particular for small families, have been ...obtained by the combination of DCA and deep learning methods. However, existing deep learning contact prediction methods often rely on a number of external programs and are therefore computationally expensive.
Results
Here, we introduce a novel contact predictor, PconsC4, which performs on par with state of the art methods. PconsC4 is heavily optimized, does not use any external programs and therefore is significantly faster and easier to use than other methods.
Availability and implementation
PconsC4 is freely available under the GPL license from https://github.com/ElofssonLab/PconsC4. Installation is easy using the pip command and works on any system with Python 3.5 or later and a GCC compiler. It does not require a GPU nor special hardware.
Supplementary information
Supplementary data are available at Bioinformatics online.
Proteins are ubiquitous molecules whose function in biological processes is determined by their 3D structure. Experimental identification of a protein's structure can be time-consuming, prohibitively ...expensive and not always possible. Alternatively, protein folding can be modeled using computational methods, which however are not guaranteed to always produce optimal results. GraphQA is a graph-based method to estimate the quality of protein models, that possesses favorable properties such as representation learning, explicit modeling of both sequential and 3D structure, geometric invariance and computational efficiency.
GraphQA performs similarly to state-of-the-art methods despite using a relatively low number of input features. In addition, the graph network structure provides an improvement over the architecture used in ProQ4 operating on the same input features. Finally, the individual contributions of GraphQA components are carefully evaluated.
PyTorch implementation, datasets, experiments and link to an evaluation server are available through this GitHub repository: github.com/baldassarreFe/graphqa.
Supplementary data are available at Bioinformatics online.
Estimation of model accuracy in CASP13 Cheng, Jianlin; Choe, Myong‐Ho; Elofsson, Arne ...
Proteins,
December 2019, Letnik:
87, Številka:
12
Journal Article
Recenzirano
Odprti dostop
Methods to reliably estimate the accuracy of 3D models of proteins are both a fundamental part of most protein folding pipelines and important for reliable identification of the best models when ...multiple pipelines are used. Here, we describe the progress made from CASP12 to CASP13 in the field of estimation of model accuracy (EMA) as seen from the progress of the most successful methods in CASP13. We show small but clear progress, that is, several methods perform better than the best methods from CASP12 when tested on CASP13 EMA targets. Some progress is driven by applying deep learning and residue‐residue contacts to model accuracy prediction. We show that the best EMA methods select better models than the best servers in CASP13, but that there exists a great potential to improve this further. Also, according to the evaluation criteria based on local similarities, such as lDDT and CAD, it is now clear that single model accuracy methods perform relatively better than consensus‐based methods.
The microtubule associated protein tau promotes neuronal survival through binding and stabilization of MTs. Phosphorylation regulates tau-microtubule interactions and hyperphosphorylation contributes ...to the aberrant formation of insoluble tau aggregates in Alzheimer's disease (AD) and related tauopathies. However, other pathogenic post-translational tau modifications have not been well characterized. Here we demonstrate that tau acetylation inhibits tau function via impaired tau-microtubule interactions and promotes pathological tau aggregation. Mass spectrometry analysis identified specific lysine residues, including lysine 280 (K280) within the microtubule-binding motif as the major sites of tau acetylation. Immunohistochemical and biochemical studies of brains from tau transgenic mice and patients with AD and related tauopathies showed that acetylated tau pathology is specifically associated with insoluble, Thioflavin-positive tau aggregates. Thus, tau K280 acetylation in our studies was only detected in diseased tissue, suggesting it may have a role in pathological tau transformation. This study suggests that tau K280 acetylation is a potential target for drug discovery and biomarker development for AD and related tauopathies.
Methods to reliably estimate the quality of 3D models of proteins are essential drivers for the wide adoption and serious acceptance of protein structure predictions by life scientists. In this ...article, the most successful groups in CASP12 describe their latest methods for estimates of model accuracy (EMA). We show that pure single model accuracy estimation methods have shown clear progress since CASP11; the 3 top methods (MESHI, ProQ3, SVMQA) all perform better than the top method of CASP11 (ProQ2). Although the pure single model accuracy estimation methods outperform quasi‐single (ModFOLD6 variations) and consensus methods (Pcons, ModFOLDclust2, Pcomb‐domain, and Wallner) in model selection, they are still not as good as those methods in absolute model quality estimation and predictions of local quality. Finally, we show that when using contact‐based model quality measures (CAD, lDDT) the single model quality methods perform relatively better.
Accurate contact predictions can be used for predicting the structure of proteins. Until recently these methods were limited to very big protein families, decreasing their utility. However, recent ...progress by combining direct coupling analysis with machine learning methods has made it possible to predict accurate contact maps for smaller families. To what extent these predictions can be used to produce accurate models of the families is not known.
We present the PconsFold2 pipeline that uses contact predictions from PconsC3, the CONFOLD folding algorithm and model quality estimations to predict the structure of a protein. We show that the model quality estimation significantly increases the number of models that reliably can be identified. Finally, we apply PconsFold2 to 6379 Pfam families of unknown structure and find that PconsFold2 can, with an estimated 90% specificity, predict the structure of up to 558 Pfam families of unknown structure. Out of these, 415 have not been reported before.
Datasets as well as models of all the 558 Pfam families are available at http://c3.pcons.net/ . All programs used here are freely available.
arne@bioinfo.se.
Although job stress models suggest that changing the work social environment to increase job resources improves psychological health, many intervention studies have weak designs and overlook ...influences of family caregiving demands. We tested the effects of an organizational intervention designed to increase supervisor social support for work and nonwork roles, and job control in a results-oriented work environment on the stress and psychological distress of health care employees who care for the elderly, while simultaneously considering their own family caregiving responsibilities. Using a group-randomized organizational field trial with an intent-to-treat design, 420 caregivers in 15 intervention extended-care nursing facilities were compared with 511 caregivers in 15 control facilities at 4 measurement times: preintervention and 6, 12, and 18 months. There were no main intervention effects showing improvements in stress and psychological distress when comparing intervention with control sites. Moderation analyses indicate that the intervention was more effective in reducing stress and psychological distress for caregivers who were also caring for other family members off the job (those with elders and those "sandwiched" with both child and elder caregiving responsibilities) compared with employees without caregiving demands. These findings extend previous studies by showing that the effect of organizational interventions designed to increase job resources to improve psychological health varies according to differences in nonwork caregiving demands. This research suggests that caregivers, especially those with "double-duty" elder caregiving at home and work and "triple-duty" responsibilities, including child care, may benefit from interventions designed to increase work-nonwork social support and job control.
A few years ago it was shown that by using a maximum entropy approach to describe couplings between columns in a multiple sequence alignment it is possible to significantly increase the accuracy of ...residue contact predictions. For very large protein families with more than 1000 effective sequences the accuracy is sufficient to produce accurate models of proteins as well as complexes. Today, for about half of all Pfam domain families no structure is known, but unfortunately most of these families have at most a few hundred members, i.e. are too small for such contact prediction methods.
To extend accurate contact predictions to the thousands of smaller protein families we present PconsC3, a fast and improved method for protein contact predictions that can be used for families with even 100 effective sequence members. PconsC3 outperforms direct coupling analysis (DCA) methods significantly independent on family size, secondary structure content, contact range, or the number of selected contacts.
PconsC3 is available as a web server and downloadable version at http://c3.pcons.net . The downloadable version is free for all to use and licensed under the GNU General Public License, version 2. At this site contact predictions for most Pfam families are also available. We do estimate that more than 4000 contact maps for Pfam families of unknown structure have more than 50% of the top-ranked contacts predicted correctly.
arne@bioinfo.se.
Supplementary data are available at Bioinformatics online.
PDF
