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Peptide structure prediction by global optimization of a potential energy function

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PEPSGO

Use your custom global optimization algorithm to predict the three-dimensional structure of a peptide from its amino acid sequence. Using multivariate quantile function the continuous search space formed by Rosetta fragments and Dunbrack rotamer library. The search space is unit hypercube.

Results using Adaptive Differential Evolution. Native (green) vs predicted (cyan).

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Requirements

To compile from source, you will need:

Installation

git clone https://github.com/poluyan/PEPSGO
cd PEPSGO/
  • Modify the CMakeLists.txt. Set the path to the Rosetta build with the kernel and gcc versions which were used in Rosetta build:
set( ROSETTAMAINPATH "/work/rosetta_src_2020.50.61505_bundle/main" )
set( ROSETTALINUXVER "5.9" )
set( ROSETTACPPCOMP "gcc" )
set( ROSETTACPPVER "10.2" )
set( MVEQFDIR "${CMAKE_SOURCE_DIR}" )
  • Then compile PEPSGO from source with cmake . and make commands. This will generate library file libpepsgo.so and demos presented in bin directory.
  • The file run_testX.sh in each test process the following input directory and get the proper input for the program.

Input files

  • sequence.fasta Peptide sequence in FASTA format.
  • fragments.Nmers Fragment file formatted in Rosetta-style (like the output from fragment picker). Fragments can be any length.
  • native.data File with a path to the native structure.
  • prediction.horiz Secondary structure prediction in PSIPRED HFORMAT.

Only peptide sequence in FASTA format is requred for most examples presented in demo.

Usage

The demos/testX contains examples of using PEPSGO.

License

The PEPSGO is distributed under Apache License 2.0 and it is open-source software. Feel free to make a copy and modify the source code, but keep the copyright notice and license intact. The PEPSGO is Rosetta-based, please read Rosetta Licensing Information before using.

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