BioGem Blog

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 c...

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...

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 (Open Parser for Systematic IUPAC Nomenclature), CACTUS , and Chimera .