scholarly journals "From one seed a whole handful": homologous proteins as seeds in crystallisation

2014 ◽  
Vol 70 (a1) ◽  
pp. C1144-C1144
Author(s):  
Areej Abuhammad ◽  
Michael McDonough ◽  
Jürgen Brem ◽  
Christopher Schofield ◽  
Elspeth Garman
Keyword(s):  
Protein Crystallization ◽  
Protein Structures ◽  
Crystallization Time ◽  
Homologous Proteins ◽  
X Ray Crystallography ◽  
Alternative Approach ◽  
Crystallization Conditions ◽  
The Right

Protein structures have significantly impacted and aided drug discovery efforts. However, it is not enough to know the structure of a protein; it must be the right structure. Small alteration in sequence can lead to different conformations and oligomerization states, cause changes which lead to different active site architecture and also which modify function. Protein crystallization is an essential prerequisite for the determination of protein structures by X-ray crystallography. We have obtained encouraging initial results for a hitherto unexplored crystallization method with the enzyme arylamine N-acetyltransferase from M. tuberculosis (TBNAT). Despite prolonged and varied trials to crystallize TBNAT, an important anti-tubercular drug target, no crystals were obtained. In an alternative approach, cross-seeding of TBNAT protein with micro-crystalline seeds from a homologous NAT from M. marinum (74 % sequence identity (SID)) surprisingly resulted in a single 20 micron sized TBNAT crystal that diffracted to 2.1 Å and allowed for TBNAT structure determination (Abuhammad et al., 2013). To our knowledge, cross-seeding crystallisation using homologous proteins has only been previously successful in cases with more than 85% SID. In this study, we have explored the effect of low sequence homology on cross seeding using β-lactamases with SID as low as 30%. Despite the low SIDs, the results show cross seeding leads to an increase in hits obtained, the identification of new crystallization conditions, shortening of crystallization time and an improvement in the quality of the crystals obtained.

scholarly journals THE CONTACT ANGLE CONTROL OF THE SOLDER FOR IMPROVING THE SOLDERING QUALITY

2021 ◽  
pp. 161-166
Author(s):  
Чуйко М.М. ◽  
Завальський В.
Keyword(s):  
Contact Angle ◽  
Sessile Drop ◽  
Electrical Contact ◽  
Contact Angle Measurement ◽  
Angle Measurement ◽  
Soldering Process ◽  
Basic Parameters ◽  
The Right

High quality of the soldering process can be achieved with the right choice of the necessary soldering materials. Since wetting determines the further nature of the connection between the solder and the main soldering material, the contact angle  measurement  is the basis for quality control of soldering materials, provided that the basic requirements of the technological process. The determination of the contact angle value is carried out by the indirect method of the sessile drop, by measuring the basic parameters of the drop using infrared transducer. A smaller value of the contact angle corresponds to a better interaction of materials, and hence a better electrical contact

scholarly journals Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics

2018 ◽  
Vol 19 (11) ◽  
pp. 3401 ◽  
Author(s):  
Ashutosh Srivastava ◽  
Tetsuro Nagai ◽  
Arpita Srivastava ◽  
Osamu Miyashita ◽  
Florence Tama
Keyword(s):  
Protein Dynamics ◽  
Computational Methods ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
X Ray ◽  
X Ray Crystallography ◽  
Insight Into

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.

scholarly journals OPTIMALISASI PENENTUAN SUMBER PASOKAN KOPI ARABIKA GAYO MELALUI PENDEKATAN HIRARCHICAL CLUSTERING DATA MINING

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Arie Saputra
Keyword(s):  
Data Mining ◽  
Added Value ◽  
Purchase Price ◽  
Arabica Coffee ◽  
Sampling Process ◽  
Coffee Farmers ◽  
Clustering Data ◽  
The Right

Gayo coffee scattered in the mountains and being in two districts of the central highlands and Central Aceh district has become the center of world attention. Gayo Arabica coffee has a unique manifold and the added value created by the mountainous nature Gayo. This factor makes Gayo Arabica coffee has the added value that is not replaceable by other similar commodities. The success of the stakeholders Gayo coffee obtain certification which is organic, fairtrade, coffee practice and Geographic indication that can be a proof of the worldwide recognition of the quality and added value of this coffee. The average price of the last on the coffee harvest season in March 2012 ranged between Rp 100.000,- until Rp 110.000,- in each Kg grean bean on exporter level. Determination of clusters of farmers the right so that the quality and price of supplies could be predicted well by the cooperative as exporters are very important. These routes and ketelusuran origin coffee blend in one location with other location mebuat coffee quality decreases. Mapping the supply of unclear origin uniformity of the quality of the coffee making is difficult to determine. This effect on selling prices decreased overall coffee farmers to the detriment of farmers with good quality coffee. The good name of the cooperative from the viewpoint of importers deteriorate as evidenced by a decrease in the purchase price of the importer in the contract.The sampling process quality coffee supply also becomes difficult because unhomogenity supply region. Supply region is crucial to the quality of the coffee due influenced the position and height of the land. Thus, this research is expected to help formulate clusters of farmers so that the quality and price of coffee could be improved both in terms of farmers and exporters. The last hope of course the welfare of farmers and other stakeholders could be better.Keywords: Data Mining, Optimization, Gayo Arabica Coffee, Supply Chain

Accurate multistage prediction of protein crystallization propensity using deep-cascade forest with sequence-based features

2020 ◽  
Author(s):  
Yi-Heng Zhu ◽  
Jun Hu ◽  
Fang Ge ◽  
Fuyi Li ◽  
Jiangning Song ◽  
...  
Keyword(s):  
Crystallization Process ◽  
Solvent Accessibility ◽  
Protein Crystallization ◽  
Protein Structures ◽  
X Ray ◽  
X Ray Crystallography ◽  
Benchmark Datasets ◽  
Pass Through ◽  
Matthew’S Correlation Coefficient ◽  
Dcf Model

Abstract X-ray crystallography is the major approach for determining atomic-level protein structures. Because not all proteins can be easily crystallized, accurate prediction of protein crystallization propensity provides critical help in guiding experimental design and improving the success rate of X-ray crystallography experiments. This study has developed a new machine-learning-based pipeline that uses a newly developed deep-cascade forest (DCF) model with multiple types of sequence-based features to predict protein crystallization propensity. Based on the developed pipeline, two new protein crystallization propensity predictors, denoted as DCFCrystal and MDCFCrystal, have been implemented. DCFCrystal is a multistage predictor that can estimate the success propensities of the three individual steps (production of protein material, purification and production of crystals) in the protein crystallization process. MDCFCrystal is a single-stage predictor that aims to estimate the probability that a protein will pass through the entire crystallization process. Moreover, DCFCrystal is designed for general proteins, whereas MDCFCrystal is specially designed for membrane proteins, which are notoriously difficult to crystalize. DCFCrystal and MDCFCrystal were separately tested on two benchmark datasets consisting of 12 289 and 950 proteins, respectively, with known crystallization results from various experimental records. The experimental results demonstrated that DCFCrystal and MDCFCrystal increased the value of Matthew’s correlation coefficient by 199.7% and 77.8%, respectively, compared to the best of other state-of-the-art protein crystallization propensity predictors. Detailed analyses show that the major advantages of DCFCrystal and MDCFCrystal lie in the efficiency of the DCF model and the sensitivity of the sequence-based features used, especially the newly designed pseudo-predicted hybrid solvent accessibility (PsePHSA) feature, which improves crystallization recognition by incorporating sequence-order information with solvent accessibility of residues. Meanwhile, the new crystal-dataset constructions help to train the models with more comprehensive crystallization knowledge.

Combining `dry' co-crystallization andin situdiffraction to facilitate ligand screening by X-ray crystallography

2015 ◽  
Vol 71 (8) ◽  
pp. 1777-1787 ◽  
Author(s):  
Muriel Gelin ◽  
Vanessa Delfosse ◽  
Frédéric Allemand ◽  
François Hoh ◽  
Yoann Sallaz-Damaz ◽  
...  
Keyword(s):  
Protein Crystallization ◽  
X Ray Diffraction ◽  
X Ray ◽  
X Ray Crystallography ◽  
Ligand Screening ◽  
Alternative Approach ◽  
Manual Handling ◽  
Stock Solutions ◽  
Established Technique

X-ray crystallography is an established technique for ligand screening in fragment-based drug-design projects, but the required manual handling steps – soaking crystals with ligand and the subsequent harvesting – are tedious and limit the throughput of the process. Here, an alternative approach is reported: crystallization plates are pre-coated with potential binders prior to protein crystallization and X-ray diffraction is performed directly `in situ' (or in-plate). Its performance is demonstrated on distinct and relevant therapeutic targets currently being studied for ligand screening by X-ray crystallography using either a bending-magnet beamline or a rotating-anode generator. The possibility of using DMSO stock solutions of the ligands to be coated opens up a route to screening most chemical libraries.

Magnetic Particles used in a New Approach for Designed Protein Crystallization

CrystEngComm ◽  
2021 ◽  
Author(s):  
Raquel dos Santos ◽  
Maria João Romão ◽  
Ana C A Roque ◽  
Ana Luisa Moreira Carvalho
Keyword(s):  
Structure Determination ◽  
Magnetic Particles ◽  
Protein Crystallization ◽  
Protein Structures ◽  
3D Structure ◽  
New Approach ◽  
X Ray ◽  
X Ray Crystallography ◽  
3D Structure Determination

After more than one hundred and thirty thousand protein structures determined by X-ray crystallography, the challenge of protein crystallization for 3D structure determination remains. In the quest for additives for...

scholarly journals Determination of the mixing extent of sugar from C4 plants in juice using the isotopic signature of carbon (δ13C) in sugar

2021 ◽  
Vol 63 (3) ◽  
pp. 60-64
Author(s):  
Lan Anh Ha ◽  
◽  
Duc Khue Pham ◽  
Dinh Kien Mai ◽  
Thi Tuoi Nguyen ◽  
...  
Keyword(s):  
Apple Juice ◽  
Isotopic Signature ◽  
C4 Plants ◽  
Carbon Stable Isotope ◽  
Pee Dee ◽  
Isotope Ratio Mass Spectrometer ◽  
The Right ◽  
End Members

The objective of this study was to apply a method for estimating the mixing extent of C4 sugar in juice (apple) based on the fingerprinting of carbon stable isotope (δ13C). The values of δ13C in sugar separated from fresh apples, pure apple juices as well as sugar produced from C4 plants (plants conduct C4 cycle photo-synthesis, in this case, it was sugar canes) were analysed on an isotope ratio mass spectrometer equipped with an elemental analyzer (EA IRMS). The results showed that the δ13C in sugar separated from fresh apples was in the range of -27.00 to -24.00‰ with an average of -25.47‰ (n=6) vs. VPDB standard (Vienna Pee Dee Belemnite). Meanwhile, the δ13C in sugar cane products ranged from -13.00 to -11.00‰, with an average of -12,47‰ vs. VPDB. Based on the isotope signature of carbon (δ13C) and the two end-members mixing model, the extent of mixing C4 sugar in apple juice available on the market could be estimated precisely. It was found one out of 9 apple juice samples available in the Hanoi markets to have a high content of C4 sugar mixed in the product, it was up to 96% instead of 5% as proclaimed on the label. The developed method seems to be of high accuracy so it was advisable to wider its application in the evaluation of the quality of juices available at the markets in Vietnam to ensure the right of the consumers.

scholarly journals Principles and characteristics of biological assemblies in experimentally determined protein structures

2019 ◽  
Author(s):  
Qifang Xu ◽  
Roland L. Dunbrack
Keyword(s):  
Physical Properties ◽  
Computational Methods ◽  
Structural Information ◽  
Protein Structures ◽  
Sequence Conservation ◽  
Homologous Proteins ◽  
X Ray ◽  
Biologically Relevant ◽  
X Ray Crystallography

AbstractMore than half of all structures in the PDB are assemblies of two or more proteins, including both homooligomers and heterooligomers. Structural information on these assemblies comes from X-ray crystallography, NMR, and cryo-EM spectroscopy. The correct assembly in an X-ray structure is often ambiguous, and computational methods have been developed to identify the most likely biologically relevant assembly based on physical properties of assemblies and sequence conservation in interfaces. Taking advantage of the large number of structures now available, some of the most recent methods have relied on similarity of interfaces and assemblies across structures of homologous proteins.

scholarly journals BCrystal: an interpretable sequence-based protein crystallization predictor

2019 ◽  
Vol 36 (5) ◽  
pp. 1429-1438 ◽  
Author(s):  
Abdurrahman Elbasir ◽  
Raghvendra Mall ◽  
Khalid Kunji ◽  
Reda Rawi ◽  
Zeyaul Islam ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Solvent Accessibility ◽  
Protein Crystallization ◽  
Protein Structures ◽  
Attrition Rate ◽  
Supplementary Information ◽  
Gradient Boosting ◽  
Relative Solvent Accessibility ◽  
X Ray Crystallography ◽  
Matthew’S Correlation Coefficient

Abstract Motivation X-ray crystallography has facilitated the majority of protein structures determined to date. Sequence-based predictors that can accurately estimate protein crystallization propensities would be highly beneficial to overcome the high expenditure, large attrition rate, and to reduce the trial-and-error settings required for crystallization. Results In this study, we present a novel model, BCrystal, which uses an optimized gradient boosting machine (XGBoost) on sequence, structural and physio-chemical features extracted from the proteins of interest. BCrystal also provides explanations, highlighting the most important features for the predicted crystallization propensity of an individual protein using the SHAP algorithm. On three independent test sets, BCrystal outperforms state-of-the-art sequence-based methods by more than 12.5% in accuracy, 18% in recall and 0.253 in Matthew’s correlation coefficient, with an average accuracy of 93.7%, recall of 96.63% and Matthew’s correlation coefficient of 0.868. For relative solvent accessibility of exposed residues, we observed higher values to associate positively with protein crystallizability and the number of disordered regions, fraction of coils and tripeptide stretches that contain multiple histidines associate negatively with crystallizability. The higher accuracy of BCrystal enables it to accurately screen for sequence variants with enhanced crystallizability. Availability and implementation Our BCrystal webserver is at https://machinelearning-protein.qcri.org/ and source code is available at https://github.com/raghvendra5688/BCrystal. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Structure Determination of Inactive-State GPCRs with a Universal Nanobody

2021 ◽  
Author(s):  
Michael J. Robertson ◽  
Feng He ◽  
Justin G. Meyerowitz ◽  
Alpay B. Seven ◽  
Ouliana Panova ◽  
...  
Keyword(s):  
Somatostatin Receptor ◽  
Protein Structures ◽  
Single Chain ◽  
Intracellular Loop ◽  
Single Chain Antibody ◽  
Inactive State ◽  
X Ray Crystallography ◽  
High Resolution Map ◽  
Μ Opioid Receptor

Cryogenic electron microscopy (cryo-EM) has widened the field of structure-based drug discovery by allowing for routine determination of membrane protein structures previously intractable. However, despite representing one of the largest classes of therapeutic targets, most inactive-state G protein-coupled receptors (GPCRs) have remained inaccessible for cryo-EM because their small size and membrane-embedded nature impedes projection alignment for high-resolution map reconstructions. Here we demonstrate that a camelid single-chain antibody (nanobody) recognizing a grafted intracellular loop can be used to obtain cryo-EM structures of different inactive-state GPCRs at resolutions comparable or better than those obtained by X-ray crystallography. Using this approach, we obtained the structure of human neurotensin 1 receptor (NTSR1) bound to antagonist SR48692, of μ-opioid receptor (MOR) bound to the clinical antagonist alvimopan, as well as the structure of the previously uncharacterized somatostatin receptor 2 (SSTR2) in the apo state; each of these structures yields novel insights into ligand binding and specificity. We expect this rapid, straightforward approach to facilitate the broad structural exploration of GPCR inactive states without the need for extensive engineering and crystallization.

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