BIOINFORMATICS REVIEW- NOVEMBER 2019

NOVEMBER 2019 VOL 5 ISSUE 11

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Sequence search against a set of local sequences (local database) using phmmer

Vina output analysis using Discovery Studio visualizer

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Contents

November 2019

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Topics Editorial....

03 Docking Vina output analysis using Discovery Studio visualizer 06

04 Sequence Analysis Sequence search against a set of local sequences (local database) using phmmer 08

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FOUNDER TARIQ ABDULLAH EDITORIAL EXECUTIVE EDITOR TARIQ ABDULLAH FOUNDING EDITOR MUNIBA FAIZA SECTION EDITORS FOZAIL AHMAD ALTAF ABDUL KALAM MANISH KUMAR MISHRA SANJAY KUMAR PRAKASH JHA NABAJIT DAS REPRINTS AND PERMISSIONS You must have permission before reproducing any material from Bioinformatics Review. Send E-mail requests to info@bioinformaticsreview.com. Please include contact detail in your message.

BACK ISSUE Bioinformatics Review back issues can be downloaded in digital format from bioinformaticsreview.com at $5 per issue. Back issue in print format cost $2 for India delivery and $11 for international delivery, subject to availability. Pre-payment is required CONTACT PHONE +91. 991 1942-428 / 852 7572-667 MAIL Editorial: 101 FF Main Road Zakir Nagar, Okhla New Delhi IN 110025 STAFF ADDRESS To contact any of the Bioinformatics Review staff member, simply format the address as firstname@bioinformaticsreview.com PUBLICATION INFORMATION Volume 1, Number 1, Bioinformatics Reviewâ„¢ is published monthly for one year (12 issues) by Social and Educational Welfare Association (SEWA)trust (Registered under Trust Act 1882). Copyright 2015 Sewa Trust. All rights reserved. Bioinformatics Review is a trademark of Idea Quotient Labs and used under license by SEWA trust. Published in India

Should predatory journals be eliminated completely from the research community?

Muniba Faiza

EDITORIAL

Founding Editor

The fast-emergence of predatory journals is a new problem in the scientific research area. These journals send attractive advertising emails to the authors to seek money and in turn, they don't provide any proper service including a peer review for their article. As a result, they publish research studies irrelevantly for the sole purpose of draining the money down from the authors. This is affecting the research quality in the scientific field.

As we all are aware of Beall's list [1] created by Jeffery Beall, an academic librarian at the University of Colorado in Denver, it lists all the predatory journals and publishers as mentioned in one of our previous articles. It represents a valuable tool for researchers to be aware of predatory journals. This list is growing continuously over time. Although Beall's list has a few shortcomings for which it has been criticized for some reasons by some researchers and publishers. These reasons include the weak methodology used by Beall's list to classify a predatory journal and some journals pointed out that Beall added newly started journals without contacting and discussing their publishing policies.

Now, various scientists are objecting to the predatory journals [2] and some of them have urged publishing companies to establish their standards so that they could easily differentiate predatory journals from real scientific ones [3]. Besides, these journals are causing great harm to the scientific community. There are some predatory journals that even display a fake impact factor on their website just to attract the authors, which as compared to the real

Letters and responses: info@bioinformaticsreview.com

scientific journals is higher. This is just increasing the number of publications in scientific literature without any significant contributions.

Some of the major problems and harms caused by these journals include the lack of significant information, less and irrelevant data, damaged reputation, lack of knowledge and quality control. Young researchers need to think about the harmful effects of publishing in predatory journals. What is the use of such research which can not benefit the scientific community? They must be aware of their external reputation damage as well.

EDITORIAL

Journal Citation Report (JCR) provides a list of journals with an official impact factor. But most of the new researchers are not aware of this. The question arises here is that either the predatory journals should be completely eliminated? or the scientific journals and publishers should strengthen the open-access concept and contribute significantly toward the scientific community. Further, there is a strict demand for a new system to identify predatory journals and the articles published in it.

References Butler, D. (2013). Investigating journals: The dark side of publishing. Nature News, 495(7442), 433.

Richtig, G., Berger, M., Lange�Asschenfeldt, B., Aberer, W., & Richtig, E. (2018). Problems and challenges of predatory journals. Journal of the European Academy of Dermatology and Venereology, 32(9), 1441-1449.

Strielkowski, W. (2017). Predatory journals: Beall's List is missed. Nature, 544(7651), 416.

Write to us at info@bioinformaticreview.com.

DOCKING

Vina output analysis using Discovery Studio visualizer

Image Credit: Stock photos

“In previous articles ("Tutorial: Vina Output Analysis Using PyMol" and "Video Tutorial: Autodock Vina Result Analysis with PyMol"), the analysis of Autodock Vina [2] result using the Pymol viewer [3] was explained.” he discovery studio (DS) visualizer [1] offers several features for analyzing docking results. In previous articles ("Tutorial: Vina Output Analysis Using PyMol" and "Video Tutorial: Autodock Vina Result Analysis with PyMol"), the analysis of Autodock Vina [2] result using the Pymol viewer [3] was explained. In this article, the Autodock Vina result is being analyzed in the DS visualizer [1].

T

To visualize Autodock Vina results in DS visualizer, you need the same files as used for the Pymol viewer: protein in .pdb format (here, 2bxa.pdb) and vina output file (here, SO.pdbqt).

1. Open DS visualizer.

2. Open “2bxa.pdb” and “SO.pdbqt” files.

3. In the “pdbqt” tab, you will see a dropdown in a new left panel

showing different poses of the ligand named as model_0, model_1, and so on.

Click on one of these poses and the ligand will switch its position on the screen. Select one of these poses, say, “model_4”, --> rightclick on the blank space --> click “Copy”.

4. Go to the receptor tab, here, “pdb” --> rightclick on the blank space --> click “Paste”. After

that, you will see the ligand somewhere within the protein.

But it is not showing any interactions yet.

5. To see the interactions between the protein and the ligand, look at the panel in the left corner for “Display receptor-ligand interactions.” Just below this,

click on “Ligand interactions”. After that,

you will be able to see the interactions.

6. To see the bond length, click “Show Distances” under the same section of “Display receptor-ligand interactions.”

7. For labeling the interacting residues, double-click the amino acid residue, it will become highlighted.

Right-click on it, a menu will appear, then click “Label” --> “Add”.

A small window will appear where you can select what you want to label, for example, one letter or three-letter amino acid residues, atoms, etc. You can also select the font and size. After setting everything, click “Ok”.

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You can see the receptor in different surfaces such as hydrophobic, charge, ionizability, and so on. They can be selected under the section in the left corner titled “Display receptor surfaces.”.

This is article covers the basic steps for Vina output analysis. You can always look for further operations including changing the color of the receptor protein and the ligand and save them in different formats. You can do this for different poses generated by Vina.

References 1. DSV3. (2010). Discovery Studio Visualizer v3.0.

Accelrys software inc.

2. Trott, O., & Olson, A. J. (2010). Software news and update AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334 3. Schrödinger, LLC. (2015). The PyMOL Molecular Graphics System, Version{\textasciitilde}1.8. Schrödinger, LLC.

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SEQUENCE ANALYSIS

Sequence search against a set of local sequences (local database) using phmmer Image Credit: Stock Photos

“In this article, a sequence search against a set of local sequences is explained using PHMMER stand-alone tool including the output in FASTA format.�

P

HMMER is a sequence analysis tool used for protein sequences (http://hmmer.org; version 3.1 b2). It is available online as a web server and as well as a part of the HMMER stand-alone package (http://hmmer.org; version 3.1 b2).

HMMER offers various useful features such as multiple sequence alignment including the file format conversion.

In this article, a sequence search against a set of local sequences is explained using PHMMER stand-

alone tool including the output in FASTA format. To do this, we will first obtain the primary output in Stockholm (.sto) format and then convert it into the FASTA format.

1. Make a local database The local database consists of protein sequences in FASTA format.

Let's say, our local dataset file is 'sequences.fasta'.

2. Search for protein sequences according to the input in the local database

Make a query sequence file, we will name it as 'query.fasta'. This file consists of FASTA sequences to be searched within the local database.

Open a terminal and type the following command: $ /path/to/phmmer -A phmmer.sto query.fasta sequences.fasta

where -A is used to define a filename to save the multiple alignments of all significant hits in Stockholm format.

You can also adjust the inclusion thresholds of different e-values by Bioinformatics Review | 8

using different arguments. For example, --incE, default value is 0.01 which means that ~1 false positive in every 100 searches with different query sequences.

--incT, instead of using e-value, use a bit score of >=<value>.

There are several other arguments that you can find in the user guide of HMMER. Now, we have output in Stockholm format. If you want it in FASTA format, then proceed to the next step.

3. Output in FASTA format For this, we will be using the 'eslreformat' binary of HMMER $ /path/to/esl-reformat fasta phmmer.sto > phmmerout.fasta

here, you can convert it into other formats such as a2m, just replace 'fasta' with 'a2m' in the command line.

This output file will consist of FASTA sequences of significant hits.

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