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2D Plot and 3D Visualization of Protein-Ligand and Protein-Protein Interactions

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Intermolecular interactions are weak bonds formed due to electron sharing between two or more atoms to hold a molecule together. In molecular modelling or computer-aided drug designing (CADD), intermolecular interaction studies are performed to analyze the stability/energy of docking molecules. This video tutorial demonstrates two-dimensional (2D) plot and three-dimensional (3D) molecular visualization of protein-ligand and protein-protein inter-molecular interactions using LigPlot+/LigPlus tool. LigPlot+ is a successor of original LigPlot program. The protein-ligand inter-molecular interactions are computed using LigPlot program and protein-protein or domain-domain inter-molecular interactions using DimPlot program. Moreover, the interactive 3D molecular visualization of the computed result can be viewed using RasMol or PyMOL. List of softwares used in this tutorial are LigPlot+, LigPlus, RasMol, PyMOL, and JDK.

Splitting PDB File into Chains and Ligands Without using Tools

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Protein Data Bank (PDB) file format is a representation of a three-dimensional (3D) structure of the protein and ligand data extracted by interpreting the experimental result of high-energy electromagnetic radiation (X-ray) or Nuclear Magnetic Resonance (NMR) through the computational method. The standard PDB file format was created by RCSB during the 1970s for parsing through software.The atomic coordinate entries of protein are represented by ATOM & TER fields, and ligand by HETATM field (given in the table below).Record TypeColumnsDescriptionATOM1 - 4"ATOM"7 - 11Atom serial number13 - 16Atom name17Alternate location indicator18 - 20Residue name22Chain identifier23 - 26Residue sequence number27Code for insertions of residues31 - 38X orthogonal Å coordinate39 - 46Y orthogonal Å coordinate47 - 54Z orthogonal Å coordinate55 - 60Occupancy61 - 66Temperature factor73 - 76Segment identifier77 - 78Element symbol79 - 80ChargeHETATM1 - 6"HETATM"7 - 80same as ATOM recor…

Prediction of 3D Structure (Folding) of a RNA Sequence

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Ribonucleic acid (RNA) is a linear single-stranded molecule that takes part in translation to protein. The intramolecular interactions (a.k.a. folding) of RNA base pairs (A=U and C≡G) form a secondary structure. Nussinov (or) Zuker algorithm is a dynamic programming approach used for the prediction of the secondary structure of the RNA. The dot-bracket structure with the minimum free energy is a stable secondary structure.Prediction of the three-dimensional (3D) structure of RNA using mFold and RNAComposer tools have demonstrated in this tutorial. The mFold tool predicts the dot-bracket notation format RNA folding result from the RNA sequence, while the RNAComposer tool predicts the 3D structure from the dot-bracket notation. The resources used in this tutorial are NCBI GenBank, mFold, and RNAComposer.Note: The length of RNA sequence input in mFold is limited to 4000 bases and sequence/dot-bracket notation input in RNAComposer is limited to 500 bases, due to the complexity of the algo…

Constructing Entropy Plot from Multiple Sequence Alignment

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The entropy in sequence analysis refers to the measure of the variation of characters (column) in multiple sequences. Entropy plot through multiple sequence alignment can be predicted using different types of entropy formulas, namely Shannon's Entropy, Schneider's Entropy, Shenkin's Entropy, Gerstein's Entropy, and Gap normalized Entropy.Prediction of entropy plot consists of two phases: (i) performing multiple sequence alignment and consensus, and (ii) calculation of entropy number for each column through consensus of multiple sequence alignment. The entropy plot is generated by plotting vertical lines in the order of the consensus sequence on the x-axis, and the entropy number on the y-axis. This simple video tutorial demonstrates how to predict entropy plot through multiple sequence alignment. The tools used in this tutorial are ClustalW, and Entropy Plotter.Note: We can choose any multiple sequence alignment tool, but the alignment output must be FASTA file format.

Compound Name to 3D Structure Prediction

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The three-dimensional (3D) structure of a compound can be retrieved using standard chemical nomenclature from the most popular databases, namely PubChem, ChEBI, ChEMBL, ChemSpider, CSD, ZINC, DrugBank, etc. If the 3D structure or chemical data is not available in the database, this simple tutorial helps you to predict the most optimal structure. The tools used in this tutorial are OPSIN, CACTUS, and Chimera.

Epidemiology and Gene Diversity of COVID-19 through NextStrain

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the strain of coronavirus that causes coronavirus disease 2019 (COVID-19). The epidemiology study of COVID-19 reveals the incidence, distribution, and control of disease in different groups of people over regions. This tutorial helps you to find the current gene diversity of SARS-CoV-2 through epidemiology study.

Finding Current Gene Diversity of SARS-CoV-2 through NCBI

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the strain of coronavirus that causes coronavirus disease 2019 (COVID-19). It causes gene mutation in itself and the host organism, through receptor binding domain (RBD) and human angiotensin-converting enzyme 2 (ACE2) complex. The mutation level increase when it transmitted to other organisms. Gene diversity of the SARS-CoV-2 can found by constructing a phylogenetic tree through multiple sequence alignment of genome sequences. This tutorial helps you to find the current gene diversity of SARS-CoV-2.