PPT-Alignment & Secondary Structure

You have learned about Data amp databases Tools Amino Acids Protein Structure Today we will discuss Aligning sequences After this You know how to perform structural alignments. Why do we want to know protein structure?. Classification. Functional Prediction. What is protein structure?. Primary - chains of amino acids. Secondary - interaction between groups of amino acids. Tertiary - the organization in three dimensions of all the atoms in a polypeptide. E – Recall the different structures of proteins and the test for proteins..  . C. . – Describe how a peptide bond is formed. . Describe the different structure of proteins.  . A – . Explain how the structures of a polypeptide build up and how changes to this may affect function. Yann. . Ponty. (VARNA), CNRS/. Ecole. . Polytechnique. , France. Jim Procter . (. JalView. ), University of Dundee, UK. Goals. To help your . survive. . the . RNA data jungle. .. To conceptually and . Independent scientist. robert@drive5.com. www.drive5.com. Multiple . alingnment. and database search. Multiple alignment in 16S world. Curated. 16S multiple alignments:. RDP. SILVA. Greengenes. MSA methods for 16s:. loops (coil). Bovine . carboxypeptidase. A. Figure 6-28. Tertiary . structures . may contain . common patterns, or motifs, of secondary structures (= . supersecondary. structures) . βαβ. β. -hairpins. By: Z. S. . Rezaei. Structural comparison. Structural alignment. spectrum. of structural alignment methods. The properties of output. Types of comparison. Algorithmic complexity. Representation of structures. loops (coil). Bovine . carboxypeptidase. A. Figure 6-28. Tertiary . structures . may contain . common patterns, or motifs, of secondary structures (= . supersecondary. structures) . βαβ. β. -hairpins. by . Sadhana S. definition. Protein structure prediction/protein . modelling. is the prediction of the three-dimensional structure of protein from its amino acid sequence. i.e., the prediction of its folding & its. . Miguel . Andrade. Faculty of Biology, . Johannes Gutenberg University . Institute of Molecular Biology. Mainz, Germany. a. ndrade@uni-mainz.de. Secondary structure prediction. Amino acid sequence -> Secondary structure. BMI/CS 776 . www.biostat.wisc.edu/bmi776/. Spring . 2018. Anthony Gitter. gitter@biostat.wisc.edu. These slides, excluding third-party material, are licensed . under . CC BY-NC 4.0. by Mark . Craven, Colin Dewey, and Anthony Gitter. 02 - 710 Computational Genomics Seyoung Kim Outline • RNA folding • Dynamic programming for RNA secondary structure prediction • Covariance model for RNA structure prediction RNA Basics • RN Proteins are biopolymers, made of the 20 L- . α. -amino acids linked by peptide bonds.. Polypeptide backbone is a repeating sequence of. . N-C-C-N-C-C…. The side chain or R group is not a part of the backbone or the peptide bond.. Some of the slides are adapted from Dr. Dong Xu’s lecture notes. Why secondary structure prediction?. Accurate secondary structure prediction can be an important information for the tertiary structure prediction. , . Brent O. . Cezairliyan. , Robert A. Grant, Jesse C. . Cochrane, . and Robert T. . Sauer - . Department . of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139 . Presented by . Gayathri Priya Ravichandran.