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2022 ◽  
Vol 33 (1) ◽  
pp. 50
Author(s):  
Eduardo Sánchez-Lara

<p><span>La Mioglobina fue la primer proteína visualizada en tres dimensiones (3D) a través de la cristalografía de rayos-X, sentando las bases para una nueva era de comprensión biológica. A partir de este hecho, se comenzaron a determinar estructuralmente una serie de macromoléculas de considerable interés biológico. Sin embargo, este impresionante avance en las ciencias de la vida, contrastaba radicalmente con la ausencia de un repositorio global para archivar y compartir los datos cristalográficos colectados de los experimentos de difracción. Con el propósito de llenar este vacío, en 1971 se estableció el Protein Data Bank (PDB) en el Brookhaven National Laboratory, como el único almacén central de estructuras 3D de macromoléculas biológicas. Establecido con apenas siete estructuras, el PDB ha evolucionado a un gigantesco repositorio de acceso abierto, almacenando datos estructurales de más de 170,000 biomoléculas, principalmente de proteínas y ácidos nucleicos. Además de ser un banco de datos biológicos, el PDB sirve como un portal educativo a través del PDB-101, ofreciendo un conjunto de recursos extraordinarios para admirar el mundo biológico. En esta revisión, festejamos los 50 años de oro del PDB con una mirada a su historia y un recorrido por algunas herramientas educativas que el archivo pone a disposición de estudiantes, investigadores, profesores y público no especializado. Ilustramos el valor de estos recursos con la estructura 3D de la maquinaria biológica recientemente depositada en el archivo, del ubicuo y nuevo coronavirus causante del síndrome respiratorio agudo severo (SARS-CoV-2) o COVID-19.</span></p>


2022 ◽  
Author(s):  
Christoph Beuthner ◽  
Florian Keusch ◽  
Henning Silber ◽  
Bernd Weiß ◽  
Jette Schröder

As our modern world has become increasingly digitalized, various types of data from different data domains are available that can enrich survey data. To link survey data to other sources, consent from the survey respondents is required. This article compares consent to data linkage requests for seven data domains: administrative data, smartphone usage data, bank data, biomarkers, Facebook data, health insurance data, and sensor data. We experimentally explore three factors of interest to survey designers seeking to maximize consent rates: consent question order, consent question wording, and incentives. The results of the study using a German online sample (n = 3,374) show that survey respondents have a relatively high probability of consent to share smartphone usage data, Facebook data, and biomarkers, while they are least likely to share their bank data in a survey. Of the three experimental factors, only the consent question order affected consent rates significantly. Additionally, the study investigated the interactions between the three experimental manipulations and the seven data domains, of which only the interaction between the data domains and the consent question order showed a consistent significant effect.


2022 ◽  
Author(s):  
Mariusz Jaskolski ◽  
Alexander Wlodawer ◽  
Zbigniew Dauter ◽  
Wladek Minor ◽  
Bernhard Rupp
Keyword(s):  

Author(s):  
MANOJ GADEWAR ◽  
BHARAT LAL

Objective: The aim of present investigation is docking of various existing antiviral, anti-tubercular and anti-malarial drugs on 6LU7 receptor of SARS-CoV-2 in the treatment of COVID-19. Methods: In this study, the structure of coronavirus binding protein and ligands for various drugs were collected from the protein data bank and pub chem. Molecular docking was carried out using Schrodinger 9.0 software. In molecular docking study, 19 different drugs of various categories like antiviral, anti-malarial and anti-tubercular were investigated for analyzing binding to 6LU7 receptors of COVID-19. Results: The docking result showed a high affinity of zanamivir, montelukast, ramdesvir, ritonavir, cobicistat and favipravir to the 6LU7 receptor of novel coronavirus. Thus the combination of these drugs may be useful in preventing further infection and can be used as a potential target for further in vitro and in vivo studies of SARS-CoV-2. Conclusion: Treatment of COVID-19 has been challenge due to the non-availability of effective drug therapy. In this study, we reported drugs for targeting 6LU7 Mpro/3Clpro protein, which showed prominent effects as potential inhibitors of COVID-19 Mpro.


2022 ◽  
Vol 8 ◽  
Author(s):  
Sucharita Dey ◽  
Jaime Prilusky ◽  
Emmanuel D. Levy

The identification of physiologically relevant quaternary structures (QSs) in crystal lattices is challenging. To predict the physiological relevance of a particular QS, QSalign searches for homologous structures in which subunits interact in the same geometry. This approach proved accurate but was limited to structures already present in the Protein Data Bank (PDB). Here, we introduce a webserver (www.QSalign.org) allowing users to submit homo-oligomeric structures of their choice to the QSalign pipeline. Given a user-uploaded structure, the sequence is extracted and used to search homologs based on sequence similarity and PFAM domain architecture. If structural conservation is detected between a homolog and the user-uploaded QS, physiological relevance is inferred. The web server also generates alternative QSs with PISA and processes them the same way as the query submitted to widen the predictions. The result page also shows representative QSs in the protein family of the query, which is informative if no QS conservation was detected or if the protein appears monomeric. These representative QSs can also serve as a starting point for homology modeling.


2022 ◽  
Author(s):  
Adam Zemla ◽  
Jonathan E. Allen ◽  
Dan Kirshner ◽  
Felice C. Lightstone

We present a structure-based method for finding and evaluating structural similarities in protein regions relevant to ligand binding. PDBspheres comprises an exhaustive library of protein structure regions (spheres) adjacent to complexed ligands derived from the Protein Data Bank (PDB), along with methods to find and evaluate structural matches between a protein of interest and spheres in the library. Currently, PDBspheres library contains more than 2 million spheres, organized to facilitate searches by sequence and/or structure similarity of protein-ligand binding sites or interfaces between interacting molecules. PDBspheres uses the LGA structure alignment algorithm as the main engine for detecting structure similarities between the protein of interest and library spheres. An all-atom structure similarity metric ensures that sidechain placement is taken into account in the PDBspheres primary assessment of confidence in structural matches. In this paper, we (1) describe the PDBspheres method, (2) demonstrate how PDBspheres can be used to detect and characterize binding sites in protein structures, (3) compare PDBspheres use for binding site prediction with seven other binding site prediction methods using a curated dataset of 2,528 ligand-bound and ligand-free crystal structures, and (4) use PDBspheres to cluster pockets and assess structural similarities among protein binding sites of the 4,876 structures in the refined set of PDBbind 2019 dataset. The PDBspheres library is made publicly available for download at https://proteinmodel.org/AS2TS/PDBspheres


2022 ◽  
Vol 9 (2) ◽  
pp. 195-202
Author(s):  
Maulana Arief ◽  
Amalia Nurul Muthmainnah

ABSTRACT The government built Satu Data Indonesia (SDI) as part of implementing the principle of open government. Through SDI, all data from the government from in Indonesia including data from government agencies can be easily accessed by visiting the data.go.id website. This situation should be a good ecosystem to develop data journalism in Indonesia, because the government provides abundant data. This study aims to see the implementation of SDI from the perspective of data journalists. Data journalist is a profession that is directly related to SDI, they are tasked with managing data to be presented to the public in a simple and easy-to-understand manner for the general public. By interviewing data journalists from Katadata and Lokadata (two online media who declare themselves as data journalism), this qualitative research is expected to provide constructive input on the implementation of One Data Indonesia. In general, the existence of SDI is appreciated by data journalists. But data journalists from Katadata and Lokadata do not use SDI as part of their news-seeking activities. They see SDI has  basic problems, the lack of data availability, data relevance problems, problems with easy data access, no data updates (updates) to data reliability. In addition, problems with data updating and data reliability, on the other hand, not all regions in Indonesia are connected to SDI. As a result, data journalists do not use Satu Data Indonesia as an instrument to make news. They prefer to dig up data through data mining on the internet and collect data gradually in their data bank for processing at a later date.   Keywords: One Data Indonesia, Open Government, Online Media, Data Journalism


2022 ◽  
Vol 2161 (1) ◽  
pp. 012016
Author(s):  
Salim Ahmed Ali ◽  
B G Prasad

Abstract Semantic segmentation is an important technology commonly used in medical imaging, autonomous driving vehicles, and backgrounds for virtual meetings. Scale Aware approaches have become the standard when it comes to the semantic segmentation domain of Machine Learning. Multiple image scales are passed through the network allowing the result to use the regular CNN layers such as max-pooling as well as convolution layers. Also, a cascading hierarchy of attention has been shown to improve the accuracy of models for such segmentation tasks. The combination of both these approaches has been shown to greatly improve the accuracy of such models. A side effect of using the cascading approach is that the model turns out to use less memory in comparison to previous approaches. Auto-labelling engines are also helpful in generalizing the model further. The cityscapes dataset used here is a useful data bank as it consists of a myriad of situations where the model can be trained and tested on. This paper presents the tested results of such a segmentation model and incremental modifications to the model pipeline to understand and improve upon the existing architecture.


Structure ◽  
2022 ◽  
Author(s):  
Chenghua Shao ◽  
John D. Westbrook ◽  
Changpeng Lu ◽  
Charmi Bhikadiya ◽  
Ezra Peisach ◽  
...  

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