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https://www.readbyqxmd.com/read/28933304/survey-of-predictors-of-propensity-for-protein-production-and-crystallization-with-application-to-predict-resolution-of-crystal-structures
#1
Jianzhao Gao, Zhonghua Wu, Gang Hu, Kui Wang, Jiangning Song, Andrzej Joachimiak, Lukasz Kurgan
Selection of proper targets for the X-ray crystallography will benefit biological research community immensely. Several computational models were proposed to predict propensity of successful protein production and diffraction quality crystallization from protein sequences. We reviewed a comprehensive collection of 22 such predictors that were developed in the last decade. We found that almost all of these models are easily accessible as webservers and/or standalone software and we demonstrated that some of them are widely used by the research community...
September 20, 2017: Current Protein & Peptide Science
https://www.readbyqxmd.com/read/28651335/critical-evaluation-of-bioinformatics-tools-for-the-prediction-of-protein-crystallization-propensity
#2
Huilin Wang, Liubin Feng, Geoffrey I Webb, Lukasz Kurgan, Jiangning Song, Donghai Lin
No abstract text is available yet for this article.
June 22, 2017: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/28589442/comprehensive-review-of-methods-for-prediction-of-intrinsic-disorder-and-its-molecular-functions
#3
REVIEW
Fanchi Meng, Vladimir N Uversky, Lukasz Kurgan
Computational prediction of intrinsic disorder in protein sequences dates back to late 1970 and has flourished in the last two decades. We provide a brief historical overview, and we review over 30 recent predictors of disorder. We are the first to also cover predictors of molecular functions of disorder, including 13 methods that focus on disordered linkers and disordered protein-protein, protein-RNA, and protein-DNA binding regions. We overview their predictive models, usability, and predictive performance...
September 2017: Cellular and Molecular Life Sciences: CMLS
https://www.readbyqxmd.com/read/28369666/computational-prediction-of-intrinsic-disorder-in-proteins
#4
Fanchi Meng, Vladimir Uversky, Lukasz Kurgan
Computational prediction of intrinsically disordered proteins (IDPs) is a mature research field. These methods predict disordered residues and regions in an input protein chain. More than 60 predictors of IDPs have been developed. This unit defines computational prediction of intrinsic disorder, summarizes major types of predictors of disorder, and provides details about three accurate and recently released methods. We demonstrate the use of these methods to predict intrinsic disorder for several illustrative proteins, provide insights into how predictions should be interpreted, and quantify and discuss predictive performance...
April 3, 2017: Current Protocols in Protein Science
https://www.readbyqxmd.com/read/28334258/review-and-comparative-assessment-of-sequence-based-predictors-of-protein-binding-residues
#5
Jian Zhang, Lukasz Kurgan
Understanding of molecular mechanisms that govern protein-protein interactions and accurate modeling of protein-protein docking rely on accurate identification and prediction of protein-binding partners and protein-binding residues. We review over 40 methods that predict protein-protein interactions from protein sequences including methods that predict interacting protein pairs, protein-binding residues for a pair of interacting sequences and protein-binding residues in a single protein chain. We focus on the latter methods that provide residue-level annotations and that can be broadly applied to all protein sequences...
March 1, 2017: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/28334201/critical-evaluation-of-bioinformatics-tools-for-the-prediction-of-protein-crystallization-propensity
#6
Huilin Wang, Liubin Feng, Geoffrey I Webb, Lukasz Kurgan, Jiangning Song, Donghai Lin
X-ray crystallography is the main tool for structural determination of proteins. Yet, the underlying crystallization process is costly, has a high attrition rate and involves a series of trial-and-error attempts to obtain diffraction-quality crystals. The Structural Genomics Consortium aims to systematically solve representative structures of major protein-fold classes using primarily high-throughput X-ray crystallography. The attrition rate of these efforts can be improved by selection of proteins that are potentially easier to be crystallized...
February 27, 2017: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/28132027/drnapred-fast-sequence-based-method-that-accurately-predicts-and-discriminates-dna-and-rna-binding-residues
#7
Jing Yan, Lukasz Kurgan
Protein-DNA and protein-RNA interactions are part of many diverse and essential cellular functions and yet most of them remain to be discovered and characterized. Recent research shows that sequence-based predictors of DNA-binding residues accurately find these residues but also cross-predict many RNA-binding residues as DNA-binding, and vice versa. Most of these methods are also relatively slow, prohibiting applications on the whole-genome scale. We describe a novel sequence-based method, DRNApred, which accurately and in high-throughput predicts and discriminates between DNA- and RNA-binding residues...
June 2, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/27801519/computational-prediction-of-protein-secondary-structure-from-sequence
#8
Fanchi Meng, Lukasz Kurgan
Secondary structure of proteins refers to local and repetitive conformations, such as α-helices and β-strands, which occur in protein structures. Computational prediction of secondary structure from protein sequences has a long history with three generations of predictive methods. This unit summarizes several recent third-generation predictors. We discuss their inputs and outputs, availability, and predictive performance and explain how to perform and interpret their predictions. We cover methods for the prediction of the 3-class secondary structure states (helix, strand, and coil) as well as the 8-class secondary structure states...
November 1, 2016: Current Protocols in Protein Science
https://www.readbyqxmd.com/read/27787828/prediction-of-disordered-rna-dna-and-protein-binding-regions-using-disordpbind
#9
Zhenling Peng, Chen Wang, Vladimir N Uversky, Lukasz Kurgan
Intrinsically disordered proteins and regions (IDPs and IDRs) are involved in a wide range of cellular functions and they often facilitate interactions with RNAs, DNAs, and proteins. Although many computational methods can predict IDPs and IDRs in protein sequences, only a few methods predict their functions and these functions primarily concern protein binding. We describe how to use the first computational method DisoRDPbind for high-throughput prediction of multiple functions of disordered regions. Our method predicts the RNA-, DNA-, and protein-binding residues located in IDRs in the input protein sequences...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27663889/what-are-the-structural-features-that-drive-partitioning-of-proteins-in-aqueous-two-phase-systems
#10
Zhonghua Wu, Gang Hu, Kui Wang, Boris Yu Zaslavsky, Lukasz Kurgan, Vladimir N Uversky
Protein partitioning in aqueous two-phase systems (ATPSs) represents a convenient, inexpensive, and easy to scale-up protein separation technique. Since partition behavior of a protein dramatically depends on an ATPS composition, it would be highly beneficial to have reliable means for (even qualitative) prediction of partitioning of a target protein under different conditions. Our aim was to understand which structural features of proteins contribute to partitioning of a query protein in a given ATPS. We undertook a systematic empirical analysis of relations between 57 numerical structural descriptors derived from the corresponding amino acid sequences and crystal structures of 10 well-characterized proteins and the partition behavior of these proteins in 29 different ATPSs...
January 2017: Biochimica et Biophysica Acta
https://www.readbyqxmd.com/read/27377881/autophagy-related-intrinsically-disordered-proteins-in-intra-nuclear-compartments
#11
Insung Na, Fanchi Meng, Lukasz Kurgan, Vladimir N Uversky
Recent analyses indicated that autophagy can be regulated via some nuclear transcriptional networks and many important players in the autophagy and other forms of programmed cell death are known to be intrinsically disordered. To this end, we analyzed similarities and differences in the intrinsic disorder distribution of nuclear and non-nuclear proteins related to autophagy. We also looked at the peculiarities of the distribution of the intrinsically disordered autophagy-related proteins in various intra-nuclear organelles, such as the nucleolus, chromatin, Cajal bodies, nuclear speckles, promyelocytic leukemia (PML) nuclear bodies, nuclear lamina, nuclear pores, and perinucleolar compartment...
August 16, 2016: Molecular BioSystems
https://www.readbyqxmd.com/read/27307636/dflpred-high-throughput-prediction-of-disordered-flexible-linker-regions-in-protein-sequences
#12
Fanchi Meng, Lukasz Kurgan
MOTIVATION: Disordered flexible linkers (DFLs) are disordered regions that serve as flexible linkers/spacers in multi-domain proteins or between structured constituents in domains. They are different from flexible linkers/residues because they are disordered and longer. Availability of experimentally annotated DFLs provides an opportunity to build high-throughput computational predictors of these regions from protein sequences. To date, there are no computational methods that directly predict DFLs and they can be found only indirectly by filtering predicted flexible residues with predictions of disorder...
June 15, 2016: Bioinformatics
https://www.readbyqxmd.com/read/27044036/psionplus-accurate-sequence-based-predictor-of-ion-channels-and-their-types
#13
Jianzhao Gao, Wei Cui, Yajun Sheng, Jishou Ruan, Lukasz Kurgan
Ion channels are a class of membrane proteins that attracts a significant amount of basic research, also being potential drug targets. High-throughput identification of these channels is hampered by the low levels of availability of their structures and an observation that use of sequence similarity offers limited predictive quality. Consequently, several machine learning predictors of ion channels from protein sequences that do not rely on high sequence similarity were developed. However, only one of these methods offers a wide scope by predicting ion channels, their types and four major subtypes of the voltage-gated channels...
2016: PloS One
https://www.readbyqxmd.com/read/27037624/disordered-nucleiome-abundance-of-intrinsic-disorder-in-the-dna-and-rna-binding-proteins-in-1121-species-from-eukaryota-bacteria-and-archaea
#14
Chen Wang, Vladimir N Uversky, Lukasz Kurgan
Intrinsically disordered proteins (IDPs) are abundant in various proteomes, where they play numerous important roles and complement biological activities of ordered proteins. Among functions assigned to IDPs are interactions with nucleic acids. However, often, such assignments are made based on the guilty-by-association principle. The validity of the extension of these correlations to all nucleic acid binding proteins has never been analyzed on a large scale across all domains of life. To fill this gap, we perform a comprehensive computational analysis of the abundance of intrinsic disorder and intrinsically disordered domains in nucleiomes (∼548 000 nucleic acid binding proteins) of 1121 species from Archaea, Bacteria and Eukaryota...
May 2016: Proteomics
https://www.readbyqxmd.com/read/26712748/compartmentalization-and-functionality-of-nuclear-disorder-intrinsic-disorder-and-protein-protein-interactions-in-intra-nuclear-compartments
#15
Fanchi Meng, Insung Na, Lukasz Kurgan, Vladimir N Uversky
The cell nucleus contains a number of membrane-less organelles or intra-nuclear compartments. These compartments are dynamic structures representing liquid-droplet phases which are only slightly denser than the bulk intra-nuclear fluid. They possess different functions, have diverse morphologies, and are typically composed of RNA (or, in some cases, DNA) and proteins. We analyzed 3005 mouse proteins localized in specific intra-nuclear organelles, such as nucleolus, chromatin, Cajal bodies, nuclear speckles, promyelocytic leukemia (PML) nuclear bodies, nuclear lamina, nuclear pores, and perinuclear compartment and compared them with ~29,863 non-nuclear proteins from mouse proteome...
December 25, 2015: International Journal of Molecular Sciences
https://www.readbyqxmd.com/read/26651072/molecular-recognition-features-morfs-in-three-domains-of-life
#16
Jing Yan, A Keith Dunker, Vladimir N Uversky, Lukasz Kurgan
Intrinsically disordered proteins and protein regions offer numerous advantages in the context of protein-protein interactions when compared to the structured proteins and domains. These advantages include ability to interact with multiple partners, to fold into different conformations when bound to different partners, and to undergo disorder-to-order transitions concomitant with their functional activity. Molecular recognition features (MoRFs) are widespread elements located in disordered regions that undergo disorder-to-order transition upon binding to their protein partners...
March 2016: Molecular BioSystems
https://www.readbyqxmd.com/read/26504143/pdid-database-of-molecular-level-putative-protein-drug-interactions-in-the-structural-human-proteome
#17
Chen Wang, Gang Hu, Kui Wang, Michal Brylinski, Lei Xie, Lukasz Kurgan
MOTIVATION: Many drugs interact with numerous proteins besides their intended therapeutic targets and a substantial portion of these interactions is yet to be elucidated. Protein-Drug Interaction Database (PDID) addresses incompleteness of these data by providing access to putative protein-drug interactions that cover the entire structural human proteome. RESULTS: PDID covers 9652 structures from 3746 proteins and houses 16 800 putative interactions generated from close to 1...
February 15, 2016: Bioinformatics
https://www.readbyqxmd.com/read/26484121/genome-wide-analysis-of-thapsigargin-induced-micrornas-and-their-targets-in-nih3t3-cells
#18
Jody Groenendyk, Xiao Fan, Zhenling Peng, Yaroslav Ilnytskyy, Lukasz Kurgan, Marek Michalak
Disruption of the endoplasmic reticulum (ER) homeostasis is the cause of ER stress. We performed microRNA (miRNA) analysis (deep sequencing) to search for coping responses (including signaling pathways) induced by disrupted ER Ca(2 +) homeostasis. Our focus was on a specific branch of UPR namely the bi-functional protein kinase/endoribonuclease inositol-requiring element 1α (IRE1α). Activated IRE1α undergoes autophosphorylation and oligomerization, leading to the activation of the endoribonuclease domain and splicing of the mRNA encoding XBP1 specific transcription factor...
December 2014: Genomics Data
https://www.readbyqxmd.com/read/26297830/in-various-protein-complexes-disordered-protomers-have-large-per-residue-surface-areas-and-area-of-protein-dna-and-rna-binding-interfaces
#19
Zhonghua Wu, Gang Hu, Jianyi Yang, Zhenling Peng, Vladimir N Uversky, Lukasz Kurgan
We provide first large scale analysis of the peculiarities of surface areas of 5658 dissimilar (below 50% sequence similarity) proteins with known 3D-structures that bind to proteins, DNA or RNAs. We show here that area of the protein surface is highly correlated with the protein length. The size of the interface surface is only modestly correlated with the protein size, except for RNA-binding proteins where larger proteins are characterized by larger interfaces. Disordered proteins with disordered interfaces are characterized by significantly larger per-residue areas of their surfaces and interfaces when compared to the structured proteins...
September 14, 2015: FEBS Letters
https://www.readbyqxmd.com/read/26201486/untapped-potential-of-disordered-proteins-in-current-druggable-human-proteome
#20
REVIEW
Gang Hu, Zhonghua Wu, Kui Wang, Vladimir N Uversky, Lukasz Kurgan
Current efforts in design and characterization of drugs often rely on the structure of their protein targets. However, a large fraction of proteins lack unique 3-D structures and exist as highly dynamic structural ensembles. These intrinsically disordered proteins are involved in pathogenesis of various human diseases and are highly abundant in eukaryotes. Based on a comprehensive analysis of the current druggable human proteome covering 12 drug classes and 18 major classes of drug targets we show a significant bias toward high structural coverage and low abundance of intrinsic disorder...
2016: Current Drug Targets
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