scholarly journals Crystallographic analysis and phasing of iron-assimilating protein 1 (FEA1) from Chlamydomonas reinhardtii

2021 ◽  
Vol 77 (5) ◽  
pp. 134-139
Author(s):  
Linda Juniar ◽  
Vida Adlfar ◽  
Michael Hippler ◽  
Hideaki Tanaka ◽  
Genji Kurisu
Keyword(s):  
Chlamydomonas Reinhardtii ◽  
Signal Sequence ◽  
Signal To Noise Ratio ◽  
Heavy Atom ◽  
Protein Structures ◽  
Data Bank ◽  
Crystallographic Analysis ◽  
Initial Structure ◽  
X Rays ◽  
Iron Assimilation

As an essential component of protein cofactors, iron is important for all photosynthetic organisms. In Chlamydomonas reinhardtii, iron levels are strictly controlled by proteins such as iron-assimilating protein 1 (FEA1). This periplasmic protein is expressed under conditions of iron deficiency, but its mechanisms of function remain unknown. Because FEA1 has no amino-acid similarity to protein structures in the Protein Data Bank, its crystal structure cannot be solved by molecular replacement. Here, recombinant FEA1 protein lacking the N-terminal signal sequence was successfully purified and crystals of apo FEA1 were obtained by hanging-drop vapor diffusion. Neither selenomethionine substitution nor heavy-atom derivatization was successful; therefore, the phase problem of FEA1 crystals was solved by the native sulfur SAD method using long-wavelength X-rays (2.7 Å). Laser-cutting technology was used to increase the signal-to-noise ratio and derive an initial structure. This study will lead to further structural studies of FEA1 to understand its function and its links to the iron-assimilation pathway.

scholarly journals From Femtoseconds to Hours–Measuring Dynamics over 18 Orders of Magnitude with Coherent X-rays

2021 ◽  
Vol 11 (13) ◽  
pp. 6179
Author(s):  
Felix Lehmkühler ◽  
Wojciech Roseker ◽  
Gerhard Grübel
Keyword(s):  
Time Scales ◽  
Free Electron Laser ◽  
Photon Correlation Spectroscopy ◽  
Signal To Noise Ratio ◽  
Coherent Scattering ◽  
Correlation Spectroscopy ◽  
X Rays ◽  
Photon Correlation ◽  
X Ray ◽  
Scattering Technique

X-ray photon correlation spectroscopy (XPCS) enables the study of sample dynamics between micrometer and atomic length scales. As a coherent scattering technique, it benefits from the increased brilliance of the next-generation synchrotron radiation and Free-Electron Laser (FEL) sources. In this article, we will introduce the XPCS concepts and review the latest developments of XPCS with special attention on the extension of accessible time scales to sub-μs and the application of XPCS at FELs. Furthermore, we will discuss future opportunities of XPCS and the related technique X-ray speckle visibility spectroscopy (XSVS) at new X-ray sources. Due to its particular signal-to-noise ratio, the time scales accessible by XPCS scale with the square of the coherent flux, allowing to dramatically extend its applications. This will soon enable studies over more than 18 orders of magnitude in time by XPCS and XSVS.

scholarly journals A large area diamond-based beam tagging hodoscope for ion therapy monitoring

2018 ◽  
Vol 170 ◽  
pp. 09005 ◽  
Author(s):  
M.-L. Gallin-Martel ◽  
L. Abbassi ◽  
A. Bes ◽  
G. Bosson ◽  
J. Collot ◽  
...  
Keyword(s):  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Therapy Monitoring ◽  
Chemical Vapor ◽  
X Rays ◽  
Reaction Products ◽  
Large Area ◽  
Position Measurement ◽  
Set Up ◽  
Good Signal

The MoniDiam project is part of the French national collaboration CLaRyS (Contrôle en Ligne de l’hAdronthérapie par RaYonnements Secondaires) for on-line monitoring of hadron therapy. It relies on the imaging of nuclear reaction products that is related to the ion range. The goal here is to provide large area beam detectors with a high detection efficiency for carbon or proton beams giving time and position measurement at 100 MHz count rates (beam tagging hodoscope). High radiation hardness and intrinsic electronic properties make diamonds reliable and very fast detectors with a good signal to noise ratio. Commercial Chemical Vapor Deposited (CVD) poly-crystalline, heteroepitaxial and monocrystalline diamonds were studied. Their applicability as a particle detector was investigated using α and β radioactive sources, 95 MeV/u carbon ion beams at GANIL and 8.5 keV X-ray photon bunches from ESRF. This facility offers the unique capability of providing a focused (~1 μm) beam in bunches of 100 ps duration, with an almost uniform energy deposition in the irradiated detector volume, therefore mimicking the interaction of single ions. A signal rise time resolution ranging from 20 to 90 ps rms and an energy resolution of 7 to 9% were measured using diamonds with aluminum disk shaped surface metallization. This enabled us to conclude that polycrystalline CVD diamond detectors are good candidates for our beam tagging hodoscope development. Recently, double-side stripped metallized diamonds were tested using the XBIC (X Rays Beam Induced Current) set-up of the ID21 beamline at ESRF which permits us to evaluate the capability of diamond to be used as position sensitive detector. The final detector will consist in a mosaic arrangement of double-side stripped diamond sensors read out by a dedicated fast-integrated electronics of several hundreds of channels.

scholarly journals Macromolecular Structure Databases: Past Progress and Future Challenges

1998 ◽  
Vol 54 (6) ◽  
pp. 1085-1094 ◽  
Author(s):  
Helge Weissig ◽  
Ilya N. Shindyalov ◽  
Philip E. Bourne
Keyword(s):  
Management Practices ◽  
Temporal Trends ◽  
Protein Structures ◽  
Data Bank ◽  
Macromolecular Structure ◽  
Paper Briefly ◽  
Future Challenges ◽  
Structure Databases ◽  
Full Discussion ◽  
Self Consistency

Databases containing macromolecular structure data provide a crystallographer with important tools for use in solving, refining and understanding the functional significance of their protein structures. Given this importance, this paper briefly summarizes past progress by outlining the features of the significant number of relevant databases developed to date. One recent database, PDB+, containing all current and obsolete structures deposited with the Protein Data Bank (PDB) is discussed in more detail. PDB+ has been used to analyze the self-consistency of the current (1 January 1998) corpus of over 7000 structures. A summary of those findings is presented (a full discussion will appear elsewhere) in the form of global and temporal trends within the data. These trends indicate that challenges exist if crystallographers are to provide the community with complete and consistent structural results in the future. It is argued that better information management practices are required to meet these challenges.

scholarly journals Enriched Conformational Sampling of DNA and Proteins with a Hybrid Hamiltonian Derived from the Protein Data Bank

2018 ◽  
Vol 19 (11) ◽  
pp. 3405 ◽  
Author(s):  
Emanuel Peter ◽  
Jiří Černý
Keyword(s):  
Partition Function ◽  
Protein Data Bank ◽  
Protein Structures ◽  
Data Bank ◽  
Weighting Factor ◽  
Potential Of Mean Force ◽  
Conformational Space ◽  
Dynamics Simulation ◽  
Conformational Sampling ◽  
Speed Increase

In this article, we present a method for the enhanced molecular dynamics simulation of protein and DNA systems called potential of mean force (PMF)-enriched sampling. The method uses partitions derived from the potentials of mean force, which we determined from DNA and protein structures in the Protein Data Bank (PDB). We define a partition function from a set of PDB-derived PMFs, which efficiently compensates for the error introduced by the assumption of a homogeneous partition function from the PDB datasets. The bias based on the PDB-derived partitions is added in the form of a hybrid Hamiltonian using a renormalization method, which adds the PMF-enriched gradient to the system depending on a linear weighting factor and the underlying force field. We validated the method using simulations of dialanine, the folding of TrpCage, and the conformational sampling of the Dickerson–Drew DNA dodecamer. Our results show the potential for the PMF-enriched simulation technique to enrich the conformational space of biomolecules along their order parameters, while we also observe a considerable speed increase in the sampling by factors ranging from 13.1 to 82. The novel method can effectively be combined with enhanced sampling or coarse-graining methods to enrich conformational sampling with a partition derived from the PDB.

scholarly journals Expanding our knowledge of the protein universe: Modelling of protein structures

2014 ◽  
Vol 70 (a1) ◽  
pp. C491-C491
Author(s):  
Jürgen Haas ◽  
Alessandro Barbato ◽  
Tobias Schmidt ◽  
Steven Roth ◽  
Andrew Waterhouse ◽  
...  
Keyword(s):  
Computational Modeling ◽  
Structure Prediction ◽  
Structural Information ◽  
Protein Structures ◽  
Model Organism ◽  
Data Bank ◽  
Continuous Model ◽  
Structure Modeling ◽  
Structure Comparison ◽  
Modeling And Prediction

Computational modeling and prediction of three-dimensional macromolecular structures and complexes from their sequence has been a long standing goal in structural biology. Over the last two decades, a paradigm shift has occurred: starting from a large "knowledge gap" between the huge number of protein sequences compared to a small number of experimentally known structures, today, some form of structural information – either experimental or computational – is available for the majority of amino acids encoded by common model organism genomes. Methods for structure modeling and prediction have made substantial progress of the last decades, and template based homology modeling techniques have matured to a point where they are now routinely used to complement experimental techniques. However, computational modeling and prediction techniques often fall short in accuracy compared to high-resolution experimental structures, and it is often difficult to convey the expected accuracy and structural variability of a specific model. Retrospectively assessing the quality of blind structure prediction in comparison to experimental reference structures allows benchmarking the state-of-the-art in structure prediction and identifying areas which need further development. The Critical Assessment of Structure Prediction (CASP) experiment has for the last 20 years assessed the progress in the field of protein structure modeling based on predictions for ca. 100 blind prediction targets per experiment which are carefully evaluated by human experts. The "Continuous Model EvaluatiOn" (CAMEO) project aims to provide a fully automated blind assessment for prediction servers based on weekly pre-released sequences of the Protein Data Bank PDB. CAMEO has been made possible by the development of novel scoring methods such as lDDT, which are robust against domain movements to allow for automated continuous structure comparison without human intervention.

FINDNCS: a program to detect non-crystallographic symmetries in protein crystals from heavy-atom sites

1999 ◽  
Vol 32 (2) ◽  
pp. 365-368 ◽  
Author(s):  
Guoguang Lu
Keyword(s):  
Protein Data Bank ◽  
Root Mean Square ◽  
Heavy Atom ◽  
Data Bank ◽  
Protein Crystals ◽  
Translation Vector ◽  
Mean Square ◽  
Acta Cryst ◽  
Crystallographic Symmetry ◽  
Averaging Techniques

In order to facilitate applications of averaging techniques in the MIR/MAD procedure, a program,FINDNCS, which automatically identifies non-crystallographic symmetry (NCS) from heavy-atom sites, has been developed. The program outputs the NCS operations (a rotation matrix and a translation vector), the corresponding root-mean-square (r.m.s.) deviations of heavy-atom sites, polar angles and screw translations, and writes coordinates of matching sites in Protein Data Bank (PDB) format. The program has an interface with the graphics programO[Joneset al. (1991).Acta Cryst.A47, 110–119] so that the NCS operations can be displayed automatically. In the test examples, all the correct NCS operations were identified and were above the noise solutions.

scholarly journals Conformational variability in proteins bound to single-stranded DNA: a new benchmark for new docking perspectives

2021 ◽  
Author(s):  
Dominique MIAS-LUCQUIN ◽  
Isaure Chauvot de Beauchêne
Keyword(s):  
Protein Data Bank ◽  
Conformational Changes ◽  
Molecular Interactions ◽  
Protein Structures ◽  
Data Bank ◽  
Computational Docking ◽  
Ssdna Binding ◽  
Conformational Variability ◽  
High Flexibility ◽  
Docking Benchmark

We explored the Protein Data-Bank (PDB) to collect protein-ssDNA structures and create a multi-conformational docking benchmark including both bound and unbound protein structures. Due to ssDNA high flexibility when not bound, no ssDNA unbound structure is included. For the 143 groups identified as bound-unbound structures of the same protein , we studied the conformational changes in the protein induced by the ssDNA binding. Moreover, based on several bound or unbound protein structures in some groups, we also assessed the intrinsic conformational variability in either bound or unbound conditions, and compared it to the supposedly binding-induced modifications. This benchmark is, to our knowledge, the first attempt made to peruse available structures of protein – ssDNA interactions to such an extent, aiming to improve computational docking tools dedicated to this kind of molecular interactions.

scholarly journals Structure-Guided Computational Approaches to Unravel Druggable Proteomic Landscape of Mycobacterium leprae

2021 ◽  
Vol 8 ◽  
Author(s):  
Sundeep Chaitanya Vedithi ◽  
Sony Malhotra ◽  
Marta Acebrón-García-de-Eulate ◽  
Modestas Matusevicius ◽  
Pedro Henrique Monteiro Torres ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Schwann Cells ◽  
Protein Structures ◽  
Mycobacterium Leprae ◽  
Data Bank ◽  
Nerve Damage ◽  
Structural Proteomics ◽  
Bacterial Survival ◽  
Functional Sites

Leprosy, caused by Mycobacterium leprae (M. leprae), is treated with a multidrug regimen comprising Dapsone, Rifampicin, and Clofazimine. These drugs exhibit bacteriostatic, bactericidal and anti-inflammatory properties, respectively, and control the dissemination of infection in the host. However, the current treatment is not cost-effective, does not favor patient compliance due to its long duration (12 months) and does not protect against the incumbent nerve damage, which is a severe leprosy complication. The chronic infectious peripheral neuropathy associated with the disease is primarily due to the bacterial components infiltrating the Schwann cells that protect neuronal axons, thereby inducing a demyelinating phenotype. There is a need to discover novel/repurposed drugs that can act as short duration and effective alternatives to the existing treatment regimens, preventing nerve damage and consequent disability associated with the disease. Mycobacterium leprae is an obligate pathogen resulting in experimental intractability to cultivate the bacillus in vitro and limiting drug discovery efforts to repositioning screens in mouse footpad models. The dearth of knowledge related to structural proteomics of M. leprae, coupled with emerging antimicrobial resistance to all the three drugs in the multidrug therapy, poses a need for concerted novel drug discovery efforts. A comprehensive understanding of the proteomic landscape of M. leprae is indispensable to unravel druggable targets that are essential for bacterial survival and predilection of human neuronal Schwann cells. Of the 1,614 protein-coding genes in the genome of M. leprae, only 17 protein structures are available in the Protein Data Bank. In this review, we discussed efforts made to model the proteome of M. leprae using a suite of software for protein modeling that has been developed in the Blundell laboratory. Precise template selection by employing sequence-structure homology recognition software, multi-template modeling of the monomeric models and accurate quality assessment are the hallmarks of the modeling process. Tools that map interfaces and enable building of homo-oligomers are discussed in the context of interface stability. Other software is described to determine the druggable proteome by using information related to the chokepoint analysis of the metabolic pathways, gene essentiality, homology to human proteins, functional sites, druggable pockets and fragment hotspot maps.

A Novel Approach to Detect Abnormal Chest X-rays of COVID-19 Patients Using Image Processing and Deep Learning

2021 ◽  
pp. 23-41
Author(s):  
Subhagata Chattopadhyay
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Hessian Matrix ◽  
Region Of Interest ◽  
Computational Time ◽  
X Rays ◽  
Feed Forward Neural Network ◽  
Novel Approach ◽  
Input Dataset

The study proposes a novel approach to automate classifying Chest X-ray (CXR) images of COVID-19 positive patients. All acquired images have been pre-processed with Simple Median Filter (SMF) and Gaussian Filter (GF) with kernel size (5, 5). The better filter is then identified by comparing Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) of denoised images. Canny's edge detection has been applied to find the Region of Interest (ROI) on denoised images. Eigenvalues [-2, 2] of the Hessian matrix (5 × 5) of the ROIs are then extracted, which constitutes the 'input' dataset to the Feed Forward Neural Network (FFNN) classifier, developed in this study. Eighty percent of the data is used for training the said network after 10-fold cross-validation and the performance of the network is tested with the remaining 20% of the data. Finally, validation has been made on another set of 'raw' normal and abnormal CXRs. Precision, Recall, Accuracy, and Computational time complexity (Big(O)) of the classifier are then estimated to examine its performance.

MRPC (Missing Regions in Polypeptide Chains): a knowledgebase

2019 ◽  
Vol 52 (6) ◽  
pp. 1422-1426
Author(s):  
Rajendran Santhosh ◽  
Namrata Bankoti ◽  
Adgonda Malgonnavar Padmashri ◽  
Daliah Michael ◽  
Jeyaraman Jeyakanthan ◽  
...  
Keyword(s):  
Protein Structures ◽  
Three Dimensional ◽  
Protein Molecule ◽  
Data Bank ◽  
Protein Crystal ◽  
Dimensional Structure ◽  
Protein Structure Analysis ◽  
Three Dimensional Structure ◽  
X Ray Crystallography ◽  
Polypeptide Chains

Missing regions in protein crystal structures are those regions that cannot be resolved, mainly owing to poor electron density (if the three-dimensional structure was solved using X-ray crystallography). These missing regions are known to have high B factors and could represent loops with a possibility of being part of an active site of the protein molecule. Thus, they are likely to provide valuable information and play a crucial role in the design of inhibitors and drugs and in protein structure analysis. In view of this, an online database, Missing Regions in Polypeptide Chains (MRPC), has been developed which provides information about the missing regions in protein structures available in the Protein Data Bank. In addition, the new database has an option for users to obtain the above data for non-homologous protein structures (25 and 90%). A user-friendly graphical interface with various options has been incorporated, with a provision to view the three-dimensional structure of the protein along with the missing regions using JSmol. The MRPC database is updated regularly (currently once every three months) and can be accessed freely at the URL http://cluster.physics.iisc.ac.in/mrpc.

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