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      The APC waiver has been extended to also apply to manuscripts submitted until March 31, 2024.

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      Worldwide Protein Data Bank (wwPDB): A virtual treasure for research in biotechnology

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          Abstract

          The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RSCB PDB) provides a wide range of digital data regarding biology and biomedicine. This huge internet resource involves a wide range of important biological data, obtained from experiments around the globe by different scientists. The Worldwide Protein Data Bank (wwPDB) represents a brilliant collection of 3D structure data associated with important and vital biomolecules including nucleic acids (RNAs and DNAs) and proteins. Moreover, this database accumulates knowledge regarding function and evolution of biomacromolecules which supports different disciplines such as biotechnology. 3D structure, functional characteristics and phylogenetic properties of biomacromolecules give a deep understanding of the biomolecules’ characteristics. An important advantage of the wwPDB database is the data updating time, which is done every week. This updating process helps users to have the newest data and information for their projects. The data and information in wwPDB can be a great support to have an accurate imagination and illustrations of the biomacromolecules in biotechnology. As demonstrated by the SARS-CoV-2 pandemic, rapidly reliable and accessible biological data for microbiology, immunology, vaccinology, and drug development are critical to address many healthcare-related challenges that are facing humanity. The aim of this paper is to introduce the readers to wwPDB, and to highlight the importance of this database in biotechnology, with the expectation that the number of scientists interested in the utilization of Protein Data Bank’s resources will increase substantially in the coming years.

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          The Protein Data Bank.

          The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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            SWISS-MODEL: homology modelling of protein structures and complexes

            Abstract Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated workflows and servers simplify and streamline the homology modelling process, also allowing users without a specific computational expertise to generate reliable protein models and have easy access to modelling results, their visualization and interpretation. Here, we present an update to the SWISS-MODEL server, which pioneered the field of automated modelling 25 years ago and been continuously further developed. Recently, its functionality has been extended to the modelling of homo- and heteromeric complexes. Starting from the amino acid sequences of the interacting proteins, both the stoichiometry and the overall structure of the complex are inferred by homology modelling. Other major improvements include the implementation of a new modelling engine, ProMod3 and the introduction a new local model quality estimation method, QMEANDisCo. SWISS-MODEL is freely available at https://swissmodel.expasy.org.
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              The FAIR Guiding Principles for scientific data management and stewardship

              There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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                Author and article information

                Contributors
                Journal
                1886
                European Journal of Microbiology and Immunology
                Akadémiai Kiadó (Budapest )
                2062-509X
                2062-8633
                15 December 2021
                Affiliations
                [1 ] Department of Microbiology, College of Basic Sciences, Shahr-e-Qods Branch, Islamic Azad University , Tehran, 37541-374, Iran
                [2 ] Department of Oral Biology and Experimental Dental Research, Faculty of Dentistry, University of Szeged , 6720, Szeged, Hungary
                Author notes
                [* ]Corresponding author. Tel.: +36-62-342-532. E-mail: gajdacs.mario@ 123456stoma.szote.u-szeged.hu
                Author information
                https://orcid.org/0000-0003-1270-0365
                Article
                10.1556/1886.2021.00020
                1e86ca91-de82-4dbd-b999-99bbf382b4ff
                © 2021 The Author(s)

                Open Access. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated. (SID_1)

                History
                : 06 November 2021
                : 23 November 2021
                Page count
                Figures: 3, Equations: 0, References: 106, Pages: 10
                Funding
                Funded by: ÚNKP-21-5-540-SZTE New National Excellence Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund
                Custom metadata
                1

                Medicine,Immunology,Public health,Microbiology & Virology,Infectious disease & Microbiology
                PDB,DNA,drug design,COVID-19,nucleic acids,biotechnology,proteins,RNA,vaccines

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