Identification of key NOEs: Difference between revisions

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# CYANA
# CYANA
# Python3
# Python3
# PDBcor. In case if PDBcor is not yet installed, please go to this [https://github.com/dzmitryashkinadze/PDBCor link] and follow installation instructions. Later we will refer to the PDBcor installation path as ''PATH/To/PDBcor''
# PDBcor. In case if PDBcor is not yet installed, please go to this [https://github.com/dzmitryashkinadze/PDBCor link] and follow installation instructions. Later we will refer to the PDBcor installation path as '''PATH/To/PDBcor'''


==== Data preparation ====
==== Data preparation ====

Revision as of 11:06, 6 September 2021

In this tutorial we will provide you with guided examples for identification of key NOEs for a two-state eNOE calculation. Keep in mind that listed approach can be generalized to any other type of calculation.

In summary, our approach consists of following steps:

  1. We extract all long range NOEs
  2. For each long range NOE we run a two-state structure calculation missing this particular NOE
  3. We evaluate structure calculations in terms of target function and correlations (using PDBcor)

Software installation

This tutorial requires following software:

  1. CYANA
  2. Python3
  3. PDBcor. In case if PDBcor is not yet installed, please go to this link and follow installation instructions. Later we will refer to the PDBcor installation path as PATH/To/PDBcor

Data preparation

Please follow the following steps:

  1. Download the demo data.
  2. Unpack the demo data

Execution

We recommend to use parallel computation for the execution as it will significantly reduce the total running time.

Please follow the following steps carefully (exact Linux commands are given below; you may copy them to a terminal):

First, run the series of two-state structure calculations:

cyana RUN.cya

Then, activate the PDBcor environment:

source PATH/To/PDBcor/venv/bin/activate

Then, run the analysis of the two-state structures:

cyana ANALYSE.cya

Finally, collect results:

cyana STAT_COLLECT.cya