Presentation is loading. Please wait.

Presentation is loading. Please wait.

Python + PyMOL Arbitrary Python code possible within python scripts PyMOL functionality available by importing PyMOL's modules cmd, cgo, stored etc. Call.

Published byNicholas Roy Rodgers Modified over 9 years ago

Similar presentations

Presentation on theme: "Python + PyMOL Arbitrary Python code possible within python scripts PyMOL functionality available by importing PyMOL's modules cmd, cgo, stored etc. Call."— Presentation transcript:

1 Python + PyMOL Arbitrary Python code possible within python scripts PyMOL functionality available by importing PyMOL's modules cmd, cgo, stored etc. Call pymol interpreter, which acts on PyMOL specific code and propagates the rest to Similar concept in MODELLER (modeling), Chimera, Yasara, VMD (visualization) - they all have Python bindings

2 Example: Scripted alignment

3 PyMOL: Center of Mass Calculation Command line execution without graphic interface With graphic interface:

4 Conservation coloring using Consurf-HSSP Base: Extracted sequences from SwissProt with high similarity to a certain PDB Entry (HSSP) Sequence Alignment Goal: Reflect residue variability in each column on the structural template Consurf-HSSP: database derivative using Maximum-Likelihood calculation to express residue entropy (round to 1-9)

5 Consurf-HSSP: Flatfile Data collection POS: The position of the AA in the SEQRES derived sequence. SEQ: The SEQRES derived sequence in one letter code. SCORE: The normalized conservation scores. 3LATOM: The ATOM derived sequence in three letter code, including the AA's positions as they appear in the PDB file and the chain identifier. COLOR: The color scale representing the conservation scores (9 - conserved, 1 - variable). MSA DATA: The number of aligned sequences having an amino acid (non-gapped) from the overall number of sequences at each position. RESIDUE VARIETY: The residues variety at each position of the multiple sequence alignment.

6 ConSurf-HSSP Parser – Part I

7 ConSurf-HSSP Parser – Part II

8 ConSurf-HSSP Parser – Part III

9 Conservation: Result in PyMOL

10 Movie Making Different Representations Arbitrary actions using cmd.mdo Nice effect: Close-up flights over particularly interesting regions Movie control bar

11 Movie Making: Example Part I

12 Movie Making: Example Part II

13 Movie Making: Example Part III

14 Movie Making: Example Part IV

Download ppt "Python + PyMOL Arbitrary Python code possible within python scripts PyMOL functionality available by importing PyMOL's modules cmd, cgo, stored etc. Call."

Similar presentations

Molecular Graphics Perspective of Protein Structure and Function.

Molecular Graphics Perspective of Protein Structure and Function.
Measuring the degree of similarity: PAM and blosum Matrix

Measuring the degree of similarity: PAM and blosum Matrix
Bioinformatics Finding signals and motifs in DNA and proteins Expectation Maximization Algorithm MEME The Gibbs sampler Lecture 10.

Bioinformatics Finding signals and motifs in DNA and proteins Expectation Maximization Algorithm MEME The Gibbs sampler Lecture 10.
Tertiary protein structure viewing and prediction July 1, 2009 Learning objectives- Learn how to manipulate protein structures with Deep View software.

Tertiary protein structure viewing and prediction July 1, 2009 Learning objectives- Learn how to manipulate protein structures with Deep View software.
Chapter 9 Structure Prediction. Motivation Given a protein, can you predict molecular structure Want to avoid repeated x-ray crystallography, but want.

Chapter 9 Structure Prediction. Motivation Given a protein, can you predict molecular structure Want to avoid repeated x-ray crystallography, but want.
. Class 5: Multiple Sequence Alignment. Multiple sequence alignment VTISCTGSSSNIGAG-NHVKWYQQLPG VTISCTGTSSNIGS--ITVNWYQQLPG LRLSCSSSGFIFSS--YAMYWVRQAPG.

. Class 5: Multiple Sequence Alignment. Multiple sequence alignment VTISCTGSSSNIGAG-NHVKWYQQLPG VTISCTGTSSNIGS--ITVNWYQQLPG LRLSCSSSGFIFSS--YAMYWVRQAPG.
Expect value Expect value (E-value) Expected number of hits, of equivalent or better score, found by random chance in a database of the size.

Expect value Expect value (E-value) Expected number of hits, of equivalent or better score, found by random chance in a database of the size.
Progressive MSA Do pair-wise alignment Develop an evolutionary tree Most closely related sequences are then aligned, then more distant are added. Genetic.

Progressive MSA Do pair-wise alignment Develop an evolutionary tree Most closely related sequences are then aligned, then more distant are added. Genetic.
Alignment methods and database searching April 14, 2005 Quiz#1 today Learning objectives- Finish Dotter Program analysis. Understand how to use the program.

Alignment methods and database searching April 14, 2005 Quiz#1 today Learning objectives- Finish Dotter Program analysis. Understand how to use the program.
Tutorial 5 Motif discovery.

Tutorial 5 Motif discovery.
Computational Biology, Part 10 Protein Structure Prediction and Display Robert F. Murphy Copyright  1996, 1999, 2001. All rights reserved.

Computational Biology, Part 10 Protein Structure Prediction and Display Robert F. Murphy Copyright  1996, 1999, All rights reserved.
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=

I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
The Protein Data Bank (PDB)

The Protein Data Bank (PDB)
Alignment methods June 26, 2007 Learning objectives- Understand how Global alignment program works. Understand how Local alignment program works.

Alignment methods June 26, 2007 Learning objectives- Understand how Global alignment program works. Understand how Local alignment program works.
Algorithm Animation for Bioinformatics Algorithms.

Algorithm Animation for Bioinformatics Algorithms.
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=

I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
Introduction to Bioinformatics - Tutorial no. 8 Predicting protein structure PSI-BLAST.

Introduction to Bioinformatics - Tutorial no. 8 Predicting protein structure PSI-BLAST.
Alignment IV BLOSUM Matrices. 2 BLOSUM matrices Blocks Substitution Matrix. Scores for each position are obtained frequencies of substitutions in blocks.

Alignment IV BLOSUM Matrices. 2 BLOSUM matrices Blocks Substitution Matrix. Scores for each position are obtained frequencies of substitutions in blocks.
Detecting the Domain Structure of Proteins from Sequence Information Niranjan Nagarajan and Golan Yona Department of Computer Science Cornell University.

Detecting the Domain Structure of Proteins from Sequence Information Niranjan Nagarajan and Golan Yona Department of Computer Science Cornell University.
Alignment methods II April 24, 2007 Learning objectives- 1) Understand how Global alignment program works using the longest common subsequence method.

Alignment methods II April 24, 2007 Learning objectives- 1) Understand how Global alignment program works using the longest common subsequence method.

Similar presentations

Ads by Google