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Feature Selection Methods for Improving Protein Structure Prediction with Rosetta

Ben Blum, Michael I. Jordan, David Kim, Rhiju Das, Philip Bradley, David Baker
2007 Neural Information Processing Systems  
Rosetta is one of the leading algorithms for protein structure prediction today. It is a Monte Carlo energy minimization method requiring many random restarts to find structures with low energy.  ...  In this paper we present a resampling technique for structure prediction of small alpha/beta proteins using Rosetta.  ...  Structure prediction methods fall into two broad camps: comparative modeling, in which solved protein structures are known for one or more proteins with sequences similar to the target sequence ("homologs  ... 
dblp:conf/nips/BlumJKDBB07 fatcat:eknti2s3sbc3ndz6voqsowpus4

ProQ3: Improved model quality assessments using Rosetta energy terms [article]

Karolis Uziela, Björn Wallner, Arne Elofsson
2016 arXiv   pre-print
Here, we examine if these features can be exchanged with energy terms calculated from Rosetta and if a combination of these terms can improve the quality assessment.  ...  structure prediction.  ...  Acknowledgements We thank Nanjiang Shu for valuable discussions. Funding This work was supported by grants from the Swedish Research Council (VR-NT 2012-5046 to AE and 2012-5270 to BW).  ... 
arXiv:1602.05832v1 fatcat:jor7ezxv6bd37ibjoajxamtexy

ProQM-resample: improved model quality assessment for membrane proteins by limited conformational sampling

Björn Wallner
2014 Computer applications in the biosciences : CABIOS  
It can be used to guide and explain experiments, as well as for prediction of proteins whose structure, in particular for membrane proteins, for the most part is unknown ($0.5% membrane protein in the  ...  While all structural features such as atom-atom contacts, residue-residue contacts, surface areas and secondary structures, as well as the SVM prediction are calculated by Rosetta during scoring, there  ... 
doi:10.1093/bioinformatics/btu187 pmid:24713439 pmcid:PMC4103597 fatcat:5gsyoi6ho5c2bczs5ogbnjymee

DeepCDpred: Inter-residue distance and contact prediction for improved prediction of protein structure

Shuangxi Ji, Tuğçe Oruç, Liam Mead, Muhammad Fayyaz Rehman, Christopher Morton Thomas, Sam Butterworth, Peter James Winn, Yang Zhang
2019 PLoS ONE  
Addition of distance constraints improved de novo structure predictions for test sets of 158 protein structures, as compared to using the best contact prediction methods alone.  ...  Massively improved prediction of protein structures has been driven by improving the prediction of the amino acid residues that contact in their 3D structure.  ...  Acknowledgments We would like to thank to University of Birmingham for providing the access to BlueBEAR HPC service and covering open access publishing costs. Author Contributions  ... 
doi:10.1371/journal.pone.0205214 pmid:30620738 pmcid:PMC6324825 fatcat:bfcqi4s5y5fupcblhemztq4u4i

Predicting Protein Complex Structure from Surface-Induced Dissociation Mass Spectrometry Data

Justin T. Seffernick, Sophie R. Harvey, Vicki H. Wysocki, Steffen Lindert
2019 ACS Central Science  
However, SID has not yet been coupled with computational structure prediction methods that could use the sparse information from SID to improve the prediction of quaternary structures, i.e., how protein  ...  Recently, mass spectrometry (MS) has become a viable method for elucidation of protein structure.  ...  ■ ACKNOWLEDGMENTS We thank the members of the Lindert lab for many useful discussions.  ... 
doi:10.1021/acscentsci.8b00912 pmid:31482115 pmcid:PMC6716128 fatcat:r6jdkmse4fcrdkfu2drpl7aqnq

Feature Design for Protein Interface Hotspots Using KFC2 and Rosetta [chapter]

Franziska Seeger, Anna Little, Yang Chen, Tina Woolf, Haiyan Cheng, Julie C. Mitchell
2019 Association for Women in Mathematics Series  
During the course of the ICERM WiSDM workshop 2017, we combined the KFC2a protein-protein interaction hotspot prediction features with Rosetta scoring function terms and interface filter metrics.  ...  From these results, we identified subsets of KFC2a and Rosetta combined features that show improved performance over KFC2a features alone.  ...  In this work, we will add features from Rosetta to those of KFC2 and train an improved model for protein-protein hotspot prediction.  ... 
doi:10.1007/978-3-030-11566-1_8 fatcat:acc6nq7vbbaz7b4vrvbejbuqai

Feature Design for Protein Interface hotspots using KFC2 and Rosetta [article]

Franziska Seeger, Anna Little, Yang Chen, Tina Woolf, Haiyan Cheng, Julie C Mitchell
2019 bioRxiv   pre-print
During the course of the ICERM WiSDM workshop 2017, we combined the KFC2a protein-protein interaction hotspot prediction features with Rosetta scoring function terms and interface filter metrics.  ...  From these results, we identified subsets of KFC2a and Rosetta combined features that show improved performance over KFC2a features alone.  ...  In this work, we will add features from Rosetta to those of KFC2 and train an improved model for protein-protein hotspot prediction.  ... 
doi:10.1101/514372 fatcat:ufcl3tt6qzfw5g3tz5eejscglq

Genetic algorithm feature-based resampling for protein structure prediction

Trent Higgs, Bela Stantic, Md Tamjidul Hoque, Abdul Sattar
2010 IEEE Congress on Evolutionary Computation  
numerous months even years to produce a predicted structure for a target protein.  ...  Computational protein structure prediction (PSP) methods have been introduced to speed up the PSP process due to manual methods, like nuclear magnetic resonance (NMR) and x-ray crystallography (XC) taking  ...  A basic example of feature-based resampling can be seen as having a predicted protein structure with one domain wrong, but by intermixing this protein with another protein, which has the other correct  ... 
doi:10.1109/cec.2010.5586149 dblp:conf/cec/HiggsSHS10 fatcat:6yiazgsknjhwnbqik257o6rvbm

Feature space resampling for protein conformational search

Ben Blum, Michael I. Jordan, David Baker
2010 Proteins: Structure, Function, and Bioinformatics  
We show that native features can be predicted at much higher than background rates, and that using the predicted feature distributions improves structure prediction in a benchmark of 28 proteins.  ...  We begin with a large number of conformations generated in independent Monte Carlo structure prediction trajectories from Rosetta.  ...  We also wish to acknowledge support to MIJ from the Miller Institute for Basic Research in Science.  ... 
doi:10.1002/prot.22677 pmid:20131376 pmcid:PMC2854516 fatcat:mv2aougztjhpvjyfb2fvigpdea

De novo protein structure determination using sparse NMR data

P M Bowers, C E Strauss, D Baker
2000 Journal of Biomolecular NMR  
We describe a method for generating moderate to high-resolution protein structures using limited NMR data combined with the ab initio protein structure prediction method Rosetta.  ...  The method requires only the sparse constraints available during initial stages of NMR structure determination, and thus holds promise for increasing the speed with which protein solution structures can  ...  structures.  ... 
pmid:11200525 fatcat:fob24e35rve5didjdl6ck3eiri

DeepCDpred: Inter-residue Distance and Contact Prediction for Improved Prediction of Protein Structure [article]

Shuangxi Ji, Tuğçe Oruç, Liam Mead, Muhammad Fayyaz Rehman, Christopher Morton Thomas, Sam Butterworth, Peter Winn
2018 bioRxiv   pre-print
Addition of distance constraints improved de novo structure predictions for test sets of 158 protein structures, as compared to using the best contact prediction methods alone.  ...  Massively improved prediction of protein structures has been driven by improving the prediction of the amino acid residues that contact in their 3D structure.  ...  For all other prediction methods, models were 353 selected either with the lowest Rosetta energy or the best TM-score. The calculations 354 were performed for the test set of 108 proteins.  ... 
doi:10.1101/425785 fatcat:hetr4rbtnnbndloht7ioipy7d4

Integration of Machine Learning Improves the Prediction Accuracy of Molecular Modelling for M. jannaschii Tyrosyl-tRNA Synthetase Substrate Specificity [article]

Bingya Duan, Yingfei Sun
2020 bioRxiv   pre-print
Design of enzyme binding pocket to accommodate substrates with different chemical structure is a great challenge.  ...  ratio for recognition of specific substrate.  ...  For example, improved score function of molecular docking software 19 , improved protein design performance 20 and accurate prediction of thermostability for protein mutants 21 have been achieved  ... 
doi:10.1101/2020.06.26.174524 fatcat:3mrufzviovfahllkc67out2vcm

ProQ2: estimation of model accuracy implemented in Rosetta

Karolis Uziela, Björn Wallner
2016 Bioinformatics  
Motivation: Model quality assessment programs are used to predict the quality of modeled protein structures.  ...  Single-model methods on the other hand do not have these inherent shortcomings and can be used both to sample new structures and to improve existing consensus methods.  ...  For example, one such feature is predicted secondary structure agreement with the actual secondary structure in the model, and there is also a similar feature for predicted surface accessibility.  ... 
doi:10.1093/bioinformatics/btv767 pmid:26733453 pmcid:PMC4848402 fatcat:cagedpzfwbb5bkp34ycppx3wwi

Robust Classification of Protein Variation Using Structural Modeling and Large-Scale Data Integration [article]

Evan H. Baugh, Riley Simmons-Edler, Christian L. Mueller, Rebecca F. Alford, Natalia Volfovsky, Alex E. Lash, Richard Bonneau
2015 bioRxiv   pre-print
To train VIPUR, we collected 9,477 protein variants with known effects on protein function from multiple organisms and curated structural models for each variant from crystal structures and homology models  ...  Existing methods for interpreting protein variation focus on annotating mutation pathogenicity rather than detailed interpretation of variant deleteriousness and frequently use only sequence-based or structure-based  ...  ACKNOWLEDGEMENTS We would like to thank the Simons Foundation, specifically the Simons Foundation Autism Research Initiative and the Simons Center for Data Analysis, and NYU-ITS, specifically Muataz Al-Barwani  ... 
doi:10.1101/029041 fatcat:e2lvnhljtrdh5lcaknwqxlrlya

Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools

Lei Jia, Ramya Yarlagadda, Charles C. Reed, Yang Zhang
2015 PLoS ONE  
Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models  ...  Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed.  ...  Acknowledgments We would like to thank Yax Sun, Robert Hormann, Richard Einstein, and Thomas Reed for their insightful suggestions. Author Contributions Conceived and designed the experiments: LJ.  ... 
doi:10.1371/journal.pone.0138022 pmid:26361227 pmcid:PMC4567301 fatcat:kzxx2ofluff7hppnutw3b422ay
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