3D protein structure
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Studium proteinů a zvláště jejich 3D struktury či protein -proteinových interakcí hraje v dnešním biochemickém výzkumu nezanedbatelnou roli. Řada alternativních metod tohoto výzkumu (např. PIXL, FRET) využívá biotechnologické postupy pro zavedení nepřirozených aminokyselin či jejich strukturních analogů do proteinové sekvence během jejich rekombinantní přípravy. Předkládaná práce uvádí několik biotechnologických přístupů inkorporace foto -methioninu (pMet, L-2-amino-5,5-azi -hexanová kyselina) do sekvence dvou modelových savčích proteinů.
The study of proteins and especially their 3D structure or protein -protein interactions plays significant role in contemporary biochemical research. Many alternative methods of the research (e.g. PIXL, FRET) employing different biotechnology techniques to introduce the non -natural amino acids or their structural analogues within protein sequence during its recombinant expression. This study presents several biotechnology approaches to introduce photo -methionine (pMet, L-2-amino-5,5-azi -hexanoic acid) into the sequence of two model mammalian proteins.
- Klíčová slova
- světlem iniciované síťování, foto-methionin,
- MeSH
- aminoacyl-tRNA-synthetasy metabolismus MeSH
- aminokyseliny chemie metabolismus MeSH
- biotechnologie MeSH
- diazomethan MeSH
- konformace proteinů * MeSH
- mapování interakce mezi proteiny * MeSH
- methionin MeSH
- posttranslační úpravy proteinů * MeSH
- proteiny chemie MeSH
- proteosyntéza MeSH
- techniky in vitro MeSH
- zobrazování trojrozměrné MeSH
- Publikační typ
- práce podpořená grantem MeSH
The purpose of this quick guide is to help new modelers who have little or no background in comparative modeling yet are keen to produce high-resolution protein 3D structures for their study by following systematic good modeling practices, using affordable personal computers or online computational resources. Through the available experimental 3D-structure repositories, the modeler should be able to access and use the atomic coordinates for building homology models. We also aim to provide the modeler with a rationale behind making a simple list of atomic coordinates suitable for computational analysis abiding to principles of physics (e.g., molecular mechanics). Keeping that objective in mind, these quick tips cover the process of homology modeling and some postmodeling computations such as molecular docking and molecular dynamics (MD). A brief section was left for modeling nonprotein molecules, and a short case study of homology modeling is discussed.
- MeSH
- algoritmy MeSH
- aminokyseliny chemie MeSH
- biologické modely MeSH
- databáze proteinů MeSH
- internet MeSH
- ionty MeSH
- koncentrace vodíkových iontů MeSH
- ligandy MeSH
- počítačová simulace MeSH
- posttranslační úpravy proteinů MeSH
- proteiny chemie MeSH
- rozpouštědla MeSH
- sbalování proteinů MeSH
- simulace molekulární dynamiky MeSH
- simulace molekulového dockingu MeSH
- software MeSH
- strojové učení MeSH
- strukturní homologie proteinů MeSH
- voda MeSH
- výpočetní biologie metody MeSH
- zobrazování trojrozměrné metody MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D structure analysis has been utilised in order to discover indications of antigenic pressure. The latter has been mostly based on the 3D models of the clonotypic B cell receptor immunoglobulin (BcR IG) amino acid sequences. Therefore, their accuracy is directly dependent on the quality of the model construction algorithms and the specific methods used to compare the ensuing models. Thus far, reliable and robust methods that can group the IG 3D models based on their structural characteristics are missing. RESULTS: Here we propose a novel method for clustering a set of proteins based on their 3D structure focusing on 3D structures of BcR IG from a large series of patients with CLL. The method combines techniques from the areas of bioinformatics, 3D object recognition and machine learning. The clustering procedure is based on the extraction of 3D descriptors, encoding various properties of the local and global geometrical structure of the proteins. The descriptors are extracted from aligned pairs of proteins. A combination of individual 3D descriptors is also used as an additional method. The comparison of the automatically generated clusters to manual annotation by experts shows an increased accuracy when using the 3D descriptors compared to plain bioinformatics-based comparison. The accuracy is increased even more when using the combination of 3D descriptors. CONCLUSIONS: The experimental results verify that the use of 3D descriptors commonly used for 3D object recognition can be effectively applied to distinguishing structural differences of proteins. The proposed approach can be applied to provide hints for the existence of structural groups in a large set of unannotated BcR IG protein files in both CLL and, by logical extension, other contexts where it is relevant to characterize BcR IG structural similarity. The method does not present any limitations in application and can be extended to other types of proteins.
In this paper, we present a novel algorithm for measuring protein similarity based on their 3-D structure (protein tertiary structure). The algorithm used a suffix tree for discovering common parts of main chains of all proteins appearing in the current research collaboratory for structural bioinformatics protein data bank (PDB). By identifying these common parts, we build a vector model and use some classical information retrieval (IR) algorithms based on the vector model to measure the similarity between proteins--all to all protein similarity. For the calculation of protein similarity, we use term frequency × inverse document frequency ( tf × idf ) term weighing schema and cosine similarity measure. The goal of this paper is to introduce new protein similarity metric based on suffix trees and IR methods. Whole current PDB database was used to demonstrate very good time complexity of the algorithm as well as high precision. We have chosen the structural classification of proteins (SCOP) database for verification of the precision of our algorithm because it is maintained primarily by humans. The next success of this paper would be the ability to determine SCOP categories of proteins not included in the latest version of the SCOP database (v. 1.75) with nearly 100% precision.
- MeSH
- algoritmy MeSH
- data mining metody MeSH
- databáze proteinů MeSH
- lidé MeSH
- proteiny chemie MeSH
- reprodukovatelnost výsledků MeSH
- strukturní homologie proteinů MeSH
- terciární struktura proteinů MeSH
- umělá inteligence MeSH
- výpočetní biologie metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Invadopodia and podosomes have been intensively studied because of their involvement in the degradation of extracellular matrix. As both structures have been studied mostly on thin matrices, their commonly reported shapes and characteristics may differ from those in vivo. To assess the morphology of invadopodia in a complex 3D environment, we observed invadopodial formation in cells grown on a dense matrix based on cell-free dermis. We have found that invadopodia differ in morphology when cells grown on the dermis-based matrix and thin substrates are compared. The cells grown on the dermis-based matrix display invadopodia which are formed by a thick protruding base rich in F-actin, phospho-paxillin, phospho-cortactin and phosphotyrosine signal, from which numerous thin filaments protrude into the matrix. The protruding filaments are composed of an F-actin core and are free of phospho-paxillin and phospho-cortactin but capped by phosphotyrosine signal. Furthermore, we found that a matrix-degrading activity is localized to the base of invadopodia and not along the matrix-penetrating protrusions. Our description of invadopodial structures on a dermis-based matrix should greatly aid the development of new criteria for the identification of invadopodia in vivo, and opens up the possibility of studying the invadopodia-related signaling in a more physiological environment.
- MeSH
- aktiny metabolismus MeSH
- buněčné kultury MeSH
- buněčné výběžky metabolismus ultrastruktura MeSH
- cytoskelet metabolismus MeSH
- elektronová mikroskopie MeSH
- experimentální sarkom metabolismus ultrastruktura MeSH
- extracelulární matrix metabolismus fyziologie ultrastruktura MeSH
- fluorescenční protilátková technika MeSH
- kortaktin metabolismus MeSH
- krysa rodu rattus MeSH
- lidé MeSH
- nádorové buněčné linie MeSH
- prasata MeSH
- signální transdukce MeSH
- zobrazování trojrozměrné MeSH
- zvířata MeSH
- Check Tag
- krysa rodu rattus MeSH
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Summary: Amino acid residues showing above background levels of conservation are often indicative of functionally significant regions within a protein. Understanding how the sequence conservation profile relates in space requires projection onto a protein structure, a potentially time-consuming process. 3DPatch is a web application that streamlines this task by automatically generating multiple sequence alignments (where appropriate) and finding structural homologs, presenting the user with a choice of structures matching their query, annotated with residue conservation scores in a matter of seconds. Availability and implementation: 3DPatch is written in JavaScript and is freely available at http://www.skylign.org/3DPatch/. Mozilla Firefox, Google Chrome, and Safari web browsers are supported. Source code is available under MIT license at https://github.com/davidjakubec/3DPatch. Supplementary information: Supplementary data are available at Bioinformatics online.
- MeSH
- databáze proteinů MeSH
- internetový prohlížeč MeSH
- konformace proteinů * MeSH
- lidé MeSH
- sekvenční seřazení * MeSH
- software * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Cholesteryl ester transfer protein (CETP), an enzyme which catalyses the transfer of cholesteryl ester from HDL to VLDL, is a promising target for discovery of novel antihyperlipidemic agents due to its pivotal role in HDL metabolism and reverse cholesterol transport. Quantitative structure activity relationship study of a series of CETP inhibitors was carried out using genetic function approximation to study various structural requirements for CETP inhibition. Various lipophilic, electronic, geometric and spatial descriptors were correlated with CETP inhibitory activity. Developed models were found predictive as indicated by their good r2pred values and satisfactory internal and external cross-validation results. Study reveals that lipophilicity (ClogP), with parabolic relationship, contributed significantly to the activity along with some electronic, geometric and quantum mechanical descriptors. The present study can be applied to future lead optimization of CETP inhibitors.
The myelin sheath is an essential, multilayered membrane structure that insulates axons, enabling the rapid transmission of nerve impulses. The tetraspan myelin proteolipid protein (PLP) is the most abundant protein of compact myelin in the central nervous system (CNS). The integral membrane protein PLP adheres myelin membranes together and enhances the compaction of myelin, having a fundamental role in myelin stability and axonal support. PLP is linked to severe CNS neuropathies, including inherited Pelizaeus-Merzbacher disease and spastic paraplegia type 2, as well as multiple sclerosis. Nevertheless, the structure, lipid interaction properties, and membrane organization mechanisms of PLP have remained unidentified. We expressed, purified, and structurally characterized human PLP and its shorter isoform DM20. Synchrotron radiation circular dichroism spectroscopy and small-angle X-ray and neutron scattering revealed a dimeric, α-helical conformation for both PLP and DM20 in detergent complexes, and pinpoint structural variations between the isoforms and their influence on protein function. In phosphatidylcholine membranes, reconstituted PLP and DM20 spontaneously induced formation of multilamellar myelin-like membrane assemblies. Cholesterol and sphingomyelin enhanced the membrane organization but were not crucial for membrane stacking. Electron cryomicroscopy, atomic force microscopy, and X-ray diffraction experiments for membrane-embedded PLP/DM20 illustrated effective membrane stacking and ordered organization of membrane assemblies with a repeat distance in line with CNS myelin. Our results shed light on the 3D structure of myelin PLP and DM20, their structure-function differences, as well as fundamental protein-lipid interplay in CNS compact myelin.
- MeSH
- axony metabolismus MeSH
- centrální nervový systém metabolismus MeSH
- lidé MeSH
- lipidové dvojvrstvy * metabolismus MeSH
- myelinová pochva metabolismus MeSH
- myelinový proteolipidový protein * metabolismus MeSH
- protein - isoformy metabolismus MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Protein function is determined by many factors, namely by its constitution, spatial arrangement, and dynamic behavior. Studying these factors helps the biochemists and biologists to better understand the protein behavior and to design proteins with modified properties. One of the most common approaches to these studies is to compare the protein structure with other molecules and to reveal similarities and differences in their polypeptide chains. RESULTS: We support the comparison process by proposing a new visualization technique that bridges the gap between traditionally used 1D and 3D representations. By introducing the information about mutual positions of protein chains into the 1D sequential representation the users are able to observe the spatial differences between the proteins without any occlusion commonly present in 3D view. Our representation is designed to serve namely for comparison of multiple proteins or a set of time steps of molecular dynamics simulation. CONCLUSIONS: The novel representation is demonstrated on two usage scenarios. The first scenario aims to compare a set of proteins from the family of cytochromes P450 where the position of the secondary structures has a significant impact on the substrate channeling. The second scenario focuses on the protein flexibility when by comparing a set of time steps our representation helps to reveal the most dynamically changing parts of the protein chain.
