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MUSCLE v/s T-COFFEE : An overview and different aspects

Dr. Muniba Faiza

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As I have discussed in my earlier articles about the multiple sequence alignment (MSA) tools (MUSCLE & T-COFFEE). Now in this article, we will discuss different aspects of these tools and which one is more preferred over the another. MUSCLE and T-COFFEE both are multiple sequence alignment tools and also helps to study the evolutionary relationships among the species.As I have already explained the algorithms involved in both the tools which are comparable. During the alignment using MUSCLE, it uses the UPGMA tree construction method which assumes that mutation occurs at the constant rate. This may be a fact which makes it different from other tools.

On the positive side, MUSCLE is a tool which is known for its speed and accuracy on each of the four benchmark test sets ( BAliBASE, SABmark, SMART and PREFAB). It is much faster than other MSA tools. MUSCLE also uses a progressive alignment which is iterated while it gets a better SP score (explained in “Basic concept of MSA” article).

T-COFFEE is an improvisation over MUSCLE in the sense that it combines both global and local alignments which provides better results and it also qualifies the four benchmark tests. Second thing which makes it better than other tools is that it uses an optimization method which provides the multiple alignment that best fits in the input library. T-COFFEE also uses progressive alignment strategy similar to MUSCLE, but unlike MUSCLE, T-COFFEE uses Neighbor Joining tree construction method during alignment which corrects the assumption of UPGMA method and assumes that mutation never occurs at a constant rate.

Let us take protein sequences of ‘Keratin’ protein of few species and align them using both the tools and construct the respective phylogeny trees. In this example, I have taken FASTA sequences of: Homo sapiens (GI: 7717238) , Paralichthys olivaceus (GI: 10716084), Pseudomonas viridiflava (GI: 934022154) and Pseudomonas aeruginosa (GI: 856785229). The results are as follows:

Fig.1
Fig 1. Tree constructed using MUSCLE.
Fig.2
Fig 2. Tree constructed using T-COFFEE.

As we have seen both the trees are slight different. The sequence of Paralichthys olivaceus is placed below to that of Homo sapiens, but it is placed above in tree constructed by T-COFFEE. Similarly, this is case with other two species. This is how MUSCLE & T-COFFEE are different from each other. T-COFFEE is more preferred over MUSCLE while aligning both closely or distantly related species but MUSCLE ia more suitable to align distantly related species since it uses global alignment only, but T-COFFEE uses both.

Note:

An exhaustive list of references for this article is available with the author and is available on personal request, for more details write to [email protected].

Dr. Muniba is a Bioinformatician based in New Delhi, India. She has completed her PhD in Bioinformatics from South China University of Technology, Guangzhou, China. She has cutting edge knowledge of bioinformatics tools, algorithms, and drug designing. When she is not reading she is found enjoying with the family. Know more about Muniba

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Bioinformatics Programming

Free_Energy_Landscape-MD: Python package to create Free Energy Landscape using PCA from GROMACS.

Dr. Muniba Faiza

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In molecular dynamics (MD) simulations, a free energy landscape (FEL) serves as a crucial tool for understanding the behavior of molecules and biomolecules over time. It is difficult to understand and plot a meaningful FEL and then extract the time frames at which the plot shows minima. In this article, we introduce a new Python package (Free_Energy_Landscape-MD) to generate an FEL based on principal component analysis (PCA) from MD simulation done by GROMACS [1].

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Bioinformatics News

VS_Analysis: A Python package to perform post-virtual screening analysis

Dr. Muniba Faiza

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VS_Analysis: A Python package to perform post-virtual screening analysis

Virtual screening (VS) is a crucial aspect of bioinformatics. As you may already know, there are various tools available for this purpose, including both paid and freely accessible options such as Autodock Vina. Conducting virtual screening with Autodock Vina requires less effort than analyzing its results. However, the analysis process can be challenging due to the large number of output files generated. To address this, we offer a comprehensive Python package designed to automate the analysis of virtual screening results.

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Bioinformatics Programming

vs_interaction_analysis.py: Python script to perform post-virtual screening analysis

Dr. Muniba Faiza

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vs_interaction_analysis.py: Python script to perform post-virtual screening analysis

Analyzing the results of virtual screening (VS) performed with Autodock Vina [1] can be challenging when done manually. In earlier instances, we supplied two scripts, namely vs_analysis.py [2,3] and vs_analysis_compounds.py [4]. This time, we have developed a new Python script to simplify the analysis of VS results.

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Software

How to install Interactive Genome Viewer (IGV) & tools on Ubuntu?

Dr. Muniba Faiza

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How to install Interactive Genome Viewer (IGV) & tools on Ubuntu?

Interactive Genome Viewer (IGV) is an interactive tool to visualize genomic data [1]. In this article, we are installing IGV and tools on Ubuntu desktop.

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MD Simulation

[Tutorial] Installing VIAMD on Ubuntu (Linux).

Dr. Muniba Faiza

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[Tutorial] Installing VIAMD on Ubuntu (Linux).

Visual Interactive Analysis of Molecular Dynamics (VIAMD) is a tool that allows the interactive analysis of molecular dynamics simulations [1]. In this article, we are installing it on Ubuntu (Linux).

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Docking

[Tutorial] Performing docking using DockingPie plugin in PyMOL.

Dr. Muniba Faiza

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[Tutorial] Performing docking using DockingPie plugin in PyMOL.

DockingPie [1] is a PyMOL plugin to perform computational docking within PyMOL [2]. In this article, we will perform simple docking using DockingPie1.2.

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Docking

How to install the DockingPie plugin on PyMOL?

Dr. Muniba Faiza

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How to install DockingPie plugin on PyMOL?

DockingPie [1] is a plugin of PyMOL [2] made to fulfill the purpose of docking within the PyMOL interface. This plugin will allow you to dock using four different algorithms, namely, Vina, RxDock, SMINA, and ADFR. It will also allow you to perform flexible docking. Though the installation procedure is the same for all OSs, in this article, we are installing this plugin on Ubuntu (Linux).

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Software

Video Tutorial: Calculating binding pocket volume using PyVol plugin.

Dr. Muniba Faiza

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Calculate Binding Pocket Volume in Pymol (using PyVol plugin).

This is a video tutorial for calculating binding pocket volume using the PyVol plugin [1] in Pymol [2].

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Software

How to generate topology from SMILES for MD Simulation?

Dr. Muniba Faiza

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How to generate topology from SMILES for MD Simulation?

If you need to generate the topology of molecules using their SMILES, a simple Python script is available.

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Software

[Tutorial] Installing jdock on Ubuntu (Linux).

Dr. Muniba Faiza

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[Tutorial] Installing jdock on Ubuntu (Linux).

jdock is an extended version of idock [1]. It has the same features as the idock along with some bug fixes. However, the binary name and the GitHub repository names are changed. We are installing jdock on Ubuntu (Linux).

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Software

How to upgrade cmake on Ubuntu (Linux)?

Dr. Muniba Faiza

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How to upgrade cmake on Ubuntu/Linux?

In bioinformatics, cmake is used to install multiple software including GROMACS, jdock, and so on. Here is a short tutorial on how to upgrade cmake on Ubuntu and get rid of the previous version. (more…)

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Software

How to install GMXPBSA on Ubuntu (Linux)?

Dr. Muniba Faiza

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How to install GMXPBSA on Ubuntu (Linux)?

GMXPBSA is a tool to calculate binding free energy [1]. It is compatible with Gromacs version 4.5 and later. In this article, we will install GMXPBSA version 2.1.2 on Ubuntu (Linux).

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Docking

[Tutorial] Installing Pyrx on Windows.

Dr. Muniba Faiza

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[Tutorial] Installing Pyrx on Windows.

Pyrx [1] is another virtual screening software that also offers to perform docking using Autodock Vina. In this article, we will install Pyrx on Windows. (more…)

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MD Simulation

How to solve ‘Could NOT find CUDA: Found unsuitable version “10.1”‘ error during GROMACS installation?

Dr. Muniba Faiza

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How to solve ‘Could NOT find CUDA: Found unsuitable version “10.1”‘ error during GROMACS installation?

Compiling GROMACS [1] with GPU can be trivial. Previously, we have provided a few articles on the same. In this article, we will solve an error frequently occurring during GROMACS installation.

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Software

Installing Autodock4 on MacOS.

Dr. Muniba Faiza

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Installing Autodock4 on MacOS

Previously, we installed the Autodock suite [1] on Ubuntu. Visit this article for details. Now, let’s install it on MacOS.

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Docking

How to install Autodock4 on Ubuntu?

Dr. Muniba Faiza

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How to install Autodock4 on Ubuntu?

Autodock suite is used for docking small molecules [1]. Recently, Autodock-GPU [2] is developed to accelerate the docking process. Its installation is described in this article. In this tutorial, we will install Autodock 4.2.6 on Ubuntu.

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Software

DS Visualizer: Uses & Applications

Dr. Muniba Faiza

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DS Visualizer: Uses & Applications

Discovery Studio (DS) Visualizer (from BIOVIA) is a visualization tool for viewing, sharing, and analyzing proteins [1]. Here are some uses and applications of DS Visualizer.

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Software

Protein structure & folding information exploited from remote homologs.

Dr. Muniba Faiza

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protein structure & folding prediction using remote homologs

Remote homologs are similar protein structures that share similar functions, but there is no easily detectable sequence similarity in them. A new study has revealed that the protein folding information can be exploited from remote homologous structures. A new tool is developed to recognize such proteins and predict their structure and folding pathway. (more…)

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RNA-seq analysis

Pathonoia- A new tool to detect pathogens in RNA-seq data.

Dr. Muniba Faiza

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Pathonoia- A new tool to detect pathogens in RNA-seq data.

Detecting viruses and bacteria in RNA-seq data with less false positive rate is a difficult task. A new tool is introduced to detect pathogens in RNA-seq data with high precision and recall known as Pathonoia [1].

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Software

AlphaFill- New algorithm to fill ligands in AlphaFold models.

Dr. Muniba Faiza

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AlphaFill- New algorithm to fill ligands in AlphaFold models.

AlphaFold is a popular artificial intelligence based protein prediction tool [1]. Though it predicts good protein structures, it lacks the capability to predict the small molecules present in the structure such as ligands. For this purpose, AlphaFill is introduced by Hekkelman et al.,[2]. (more…)

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