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Rosetta protein

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https://www.readbyqxmd.com/read/29775664/auto-induction-for-high-level-production-of-biologically-active-reteplase-in-escherichia-coli
#1
Mehrnoosh Fathi-Roudsari, Nader Maghsoudi, Amirhossein Maghsoudi, Sepideh Niazi, Morvarid Soleiman
Reteplase is a third generation tissue plasminogen activator (tPA) with a modified structure and prolonged half-life in comparison to native tPA. As a non-glycosylated protein, reteplase is expressed in Escherichia coli. Due to presence of several disulfide bonds, high level production of reteplase is complicated and needs extra steps for conversion to biologically active form. Auto-induction represents a method for high-yield growth of bacterial cells and higher expression of recombinant proteins. Here we have tried to optimize the auto-induction procedure for soluble and active expression of reteplase in E...
May 15, 2018: Protein Expression and Purification
https://www.readbyqxmd.com/read/29728674/qm-mm-free-energy-simulations-of-an-efficient-gluten-hydrolase-kuma030-implicate-for-a-reactant-state-based-protein-design-strategy-for-general-acid-base-catalysis
#2
Xia Wang, Ruirui Li, Wenchao Cui, Qiang Li, Jianzhuang Yao
It is a grand attraction for contemporary biochemists to computationally design enzymes for novel chemical transformation or improved catalytic efficiency. Rosetta by Baker et al. is no doubt the leading software in the protein design society. Generally, optimization of the transition state (TS) is part of the Rosetta's protocol to enhance the catalytic efficiency of target enzymes, since TS stabilization is the determining factor for catalytic efficiency based on the TS theory (TST). However, it is confusing that optimization of the reactant state (RS) also results in significant improvement of catalytic efficiency in some cases, such as design of gluten hydrolase (Kuma030)...
May 4, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29722803/self-consistency-test-reveals-systematic-bias-in-programs-for-prediction-change-of-stability-upon-mutation
#3
Dinara R Usmanova, Natalya S Bogatyreva, Joan Ariño Bernad, Aleksandra A Eremina, Anastasiya A Gorshkova, German M Kanevskiy, Lyubov R Lonishin, Alexander V Meister, Alisa G Yakupova, Fyodor A Kondrashov, Dmitry N Ivankov
Motivation: Computational prediction of the effect of mutations on protein stability is used by researchers in many fields. The utility of the prediction methods is affected by their accuracy and bias. Bias, a systematic shift of the predicted change of stability, has been noted as an issue for several methods, but has not been investigated systematically. Presence of the bias may lead to misleading results especially when exploring the effects of combination of different mutations. Results: Here we use a protocol to measure the bias as a function of the number of introduced mutations...
May 2, 2018: Bioinformatics
https://www.readbyqxmd.com/read/29718115/efficient-flexible-backbone-protein-protein-docking-for-challenging-targets
#4
Nicholas A Marze, Shourya S Roy Burman, William Sheffler, Jeffrey J Gray
Motivation: Binding-induced conformational changes challenge current computational docking algorithms by exponentially increasing the conformational space to be explored. To restrict this search to relevant space, some computational docking algorithms exploit the inherent flexibility of the protein monomers to simulate conformational selection from pre-generated ensembles. As the ensemble size expands with increased flexibility, these methods struggle with efficiency and high false positive rates...
April 30, 2018: Bioinformatics
https://www.readbyqxmd.com/read/29717995/the-putative-siderophore-interacting-protein-from-vibrio-anguillarum-protein-production-analysis-crystallization-and-x-ray-crystallographic-studies
#5
Yu Han, Kun Zang, Changshui Liu, Yingjie Li, Qingjun Ma
Siderophore-interacting proteins (SIPs) play an important role in iron acquisition in many bacteria. SIPs release iron from the internalized ferric siderophore complex by reducing ferric iron to ferrous iron, but how the iron is reduced is not well understood. Here, a sip gene was identified in the genome of Vibrio anguillarum 775. To further understand the catalytic mechanism of the protein, the SIP was overexpressed in Escherichia coli Rosetta (DE3) cells, purified and crystallized for X-ray diffraction analysis...
May 1, 2018: Acta Crystallographica. Section F, Structural Biology Communications
https://www.readbyqxmd.com/read/29712830/tertiary-structure-of-apolipoprotein-a-i-in-nascent-high-density-lipoproteins
#6
Mohsen Pourmousa, Hyun D Song, Yi He, Jay W Heinecke, Jere P Segrest, Richard W Pastor
Understanding the function of high-density lipoprotein (HDL) requires detailed knowledge of the structure of its primary protein, apolipoprotein A-I (APOA1). However, APOA1 flexibility and HDL heterogeneity have confounded decades of efforts to determine high-resolution structures and consistent models. Here, molecular dynamics simulations totaling 30 μs on two nascent HDLs, each with 2 APOA1 and either 160 phospholipids and 24 cholesterols or 200 phospholipids and 20 cholesterols, show that residues 1-21 of the N-terminal domains of APOA1 interact via strong salt bridges...
April 30, 2018: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/29702641/rosettaantibodydesign-rabd-a-general-framework-for-computational-antibody-design
#7
Jared Adolf-Bryfogle, Oleks Kalyuzhniy, Michael Kubitz, Brian D Weitzner, Xiaozhen Hu, Yumiko Adachi, William R Schief, Roland L Dunbrack
A structural-bioinformatics-based computational methodology and framework have been developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) samples the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for the design of antibodies in a broad range of applications. The program samples antibody sequences and structures by grafting structures from a widely accepted set of the canonical clusters of CDRs (North et al., J...
April 27, 2018: PLoS Computational Biology
https://www.readbyqxmd.com/read/29679026/computational-protein-design-with-deep-learning-neural-networks
#8
Jingxue Wang, Huali Cao, John Z H Zhang, Yifei Qi
Computational protein design has a wide variety of applications. Despite its remarkable success, designing a protein for a given structure and function is still a challenging task. On the other hand, the number of solved protein structures is rapidly increasing while the number of unique protein folds has reached a steady number, suggesting more structural information is being accumulated on each fold. Deep learning neural network is a powerful method to learn such big data set and has shown superior performance in many machine learning fields...
April 20, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29659276/protocols-for-requirement-driven-protein-design-in-the-rosetta-modeling-program
#9
Sharon Guffy, Frank Teets, Minnie Langlois, Brian Kuhlman
We have developed a set of protocols in the molecular modeling program Rosetta for performing requirement-driven protein design. First, the user specifies a set of structural features that they wish to be present in the designed protein. These requirements can be general, e.g. create a protein with five helices, or they can be very specific and require the correct placement of a set of amino acids to bind a ligand. Next, a large set of protein models are generated that satisfy the design requirements. The models are built using a method we recently introduced into Rosetta, called SEWING, that rapidly assembles novel protein backbones by combining pieces of naturally occurring proteins...
April 16, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/29652499/rapid-sampling-of-hydrogen-bond-networks-for-computational-protein-design
#10
Jack B Maguire, Scott E Boyken, David Baker, Brian Kuhlman
Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions...
April 20, 2018: Journal of Chemical Theory and Computation
https://www.readbyqxmd.com/read/29614397/heterologous-expression-and-antimicrobial-activity-of-osgasr3-from-rice-oryza-sativa-l
#11
Krissana Boonpa, Supaluk Tantong, Kamonwan Weerawanich, Pawinee Panpetch, Onanong Pringsulaka, Yodying Yingchutrakul, Sittiruk Roytrakul, Supaart Sirikantaramas
According to an in silico analysis, OsGASR3 (LOC_Os03g55290) from rice (Oryza sativa L.) was predicted to be involved in plant defense mechanisms. A semi-quantitative reverse transcription polymerase chain reaction assay revealed that OsGASR3 is highly expressed in the inflorescences of Thai jasmine rice (O. sativa L. subsp. indica 'KDML 105'). To characterize the biological activity of OsGASR3, we produced an OsGASR3-glutathione S-transferase fusion protein in Escherichia coli Rosetta-gami (DE3) cells for a final purified recombinant OsGASR3 yield of 0...
March 27, 2018: Journal of Plant Physiology
https://www.readbyqxmd.com/read/29605934/modeling-the-structure-of-helical-assemblies-with-experimental-constraints-in-rosetta
#12
Ingemar André
Determining high-resolution structures of proteins with helical symmetry can be challenging due to limitations in experimental data. In such instances, structure-based protein simulations driven by experimental data can provide a valuable approach for building models of helical assemblies. This chapter describes how the Rosetta macromolecular package can be used to model homomeric protein assemblies with helical symmetry in a range of modeling scenarios including energy refinement, symmetrical docking, comparative modeling, and de novo structure prediction...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29595057/accurately-predicting-disordered-regions-of-proteins-using-rosetta-residuedisorder-application
#13
Stephanie S Kim, Justin T Seffernick, Steffen Lindert
Although many proteins necessitate well-folded structures to properly instigate their biological functions, a large fraction of functioning proteins contain regions-known as intrinsically disordered protein regions-where stable structures are not likely to form. Notable functional roles of intrinsically disordered proteins are in transcriptional regulation, translation, and cellular signal transduction. Moreover, intrinsically disordered protein regions are highly abundant in many proteins associated with various human diseases, therefore these segments have become attractive drug targets for potential therapeutics...
March 29, 2018: Journal of Physical Chemistry. B
https://www.readbyqxmd.com/read/29532025/ube2v2-is-a-rosetta-stone-bridging-redox-and-ubiquitin-codes-coordinating-dna-damage-responses
#14
Yi Zhao, Marcus J C Long, Yiran Wang, Sheng Zhang, Yimon Aye
Posttranslational modifications (PTMs) are the lingua franca of cellular communication. Most PTMs are enzyme-orchestrated. However, the reemergence of electrophilic drugs has ushered mining of unconventional/non-enzyme-catalyzed electrophile-signaling pathways. Despite the latest impetus toward harnessing kinetically and functionally privileged cysteines for electrophilic drug design, identifying these sensors remains challenging. Herein, we designed "G-REX"-a technique that allows controlled release of reactive electrophiles in vivo...
February 28, 2018: ACS Central Science
https://www.readbyqxmd.com/read/29498112/phosphorylation-control-of-the-ubiquitin-ligase-cbl-is-conserved-in-choanoflagellates
#15
Jeanine F Amacher, Helen T Hobbs, Aaron C Cantor, Lochan Shah, Marco-Jose Rivero, Sarah A Mulchand, John Kuriyan
Cbl proteins are E3 ubiquitin ligases specialized for the regulation of tyrosine kinases by ubiquitylation. Human Cbl proteins are activated by tyrosine phosphorylation, thus setting up a feedback loop whereby the activation of tyrosine kinases triggers their own degradation. Cbl proteins are targeted to their substrates by a phosphotyrosine-binding SH2 domain. Choanoflagellates, unicellular eukaryotes that are closely related to metazoans, also contain Cbl. The tyrosine kinase complement of choanoflagellates is distinct from that of metazoans, and it is unclear if choanoflagellate Cbl is regulated similarly to metazoan Cbl...
May 2018: Protein Science: a Publication of the Protein Society
https://www.readbyqxmd.com/read/29483295/a-novel-rhodopsin-phosphodiesterase-from-salpingoeca-rosetta-shows-light-enhanced-substrate-affinity
#16
Yuehui Tian, Shiqiang Gao, Shang Yang, Georg Nagel
It is since many years textbook knowledge that the concentration of the second messenger cGMP is regulated in animal rod and cone cells by type II rhodopsins via a G-protein signaling cascade. Microbial rhodopsins with enzymatic activity for regulation of cGMP concentration were only recently discovered: in 2014 light-activated guanylyl-cyclase opsins in fungi and in 2017 a novel rhodopsin phosphodiesterase (RhoPDE) in the protist Salpingoeca rosetta ( Sr RhoPDE). The light regulation of Sr RhoPDE, however, seemed very weak or absent...
March 26, 2018: Biochemical Journal
https://www.readbyqxmd.com/read/29475175/guiding-exploration-in-conformational-feature-space-with-lipschitz-underestimation-for-ab-initio-protein-structure-prediction
#17
Xiaohu Hao, Guijun Zhang, Xiaogen Zhou
Computing conformations which are essential to associate structural and functional information with gene sequences, is challenging due to the high dimensionality and rugged energy surface of the protein conformational space. Consequently, the dimension of the protein conformational space should be reduced to a proper level, and an effective exploring algorithm should be proposed. In this paper, a plug-in method for guiding exploration in conformational feature space with Lipschitz underestimation (LUE) for ab-initio protein structure prediction is proposed...
April 2018: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/29474517/cost-function-network-based-design-of-protein-protein-interactions-predicting-changes-in-binding-affinity
#18
Clément Viricel, Simon de Givry, Thomas Schiex, Sophie Barbe
Motivation: Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of proteins for a wide range of applications. Free energy is defined by enthalpic and entropic contributions. Following the recent progresses of Artificial Intelligence-based algorithms for guaranteed NP-hard energy optimization and partition function computation, it becomes possible to quickly compute minimum energy conformations and to reliably estimate the entropic contribution of side-chains in the change of free energy of large protein interfaces...
February 20, 2018: Bioinformatics
https://www.readbyqxmd.com/read/29466712/dihydrolipoamide-dehydrogenase-from-leishmania-donovani-new-insights-through-biochemical-characterization
#19
Adarsh Kumar Chiranjivi, Vikash Kumar Dubey
Dihydrolipoamide dehydrogenase (DLDH) regulates many crucial metabolic pathways as a multi-enzyme complex. Leishmania donovani dihydrolipoamide dehydrogenase (LdDLDH) has two variants present on two different chromosomes with very less sequence similarities. In the current study, we cloned both the variants in pET28a (+) vector and expressed in Rosetta-gami (DE3) E. coli strain. Expressed proteins were finally purified from pellets using Ni-NTA affinity chromatography. Purified enzymes were biochemically characterized and different kinetic parameters were studied...
June 2018: International Journal of Biological Macromolecules
https://www.readbyqxmd.com/read/29454111/combining-rosetta-with-molecular-dynamics-md-a-benchmark-of-the-md-based-ensemble-protein-design
#20
Jan Ludwiczak, Adam Jarmula, Stanislaw Dunin-Horkawicz
Computational protein design is a set of procedures for computing amino acid sequences that will fold into a specified structure. Rosetta Design, a commonly used software for protein design, allows for the effective identification of sequences compatible with a given backbone structure, while molecular dynamics (MD) simulations can thoroughly sample near-native conformations. We benchmarked a procedure in which Rosetta design is started on MD-derived structural ensembles and showed that such a combined approach generates 20-30% more diverse sequences than currently available methods with only a slight increase in computation time...
February 14, 2018: Journal of Structural Biology
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