B Spresso - Akiyama Laboratory

An Ultrafast Pre-screening Method Based on Compound Decomposition


Spresso (Speedy PRE-Screening method with Segmented cOmpounds) is a novel structure-based virtual screening method based on compound decomposition. Partial structures (fragments) are often common among several compounds; therefore, the number of fragment variations neededfor evaluation is smaller than that of compounds. Our method increased calculation speeds up to approximately 200-fold compared to conventional methods.

Introduction slide (pdf)


spresso_decomp_v1.0.3.tar.gz (version 1.0.3, Last update: Mar. 31 2017)

fragment_docking.py (version 1.0.2, Last update: July 8 2016)

calc_compound_score.py (version 1.0.2, Last update: July 8 2016)



Codes are written in C++ and python2.


  • boost (version >= 1.36)
  •  $ sudo apt-get install libboost-all-dev
  • openbabel (version >= 2.3.2)
  •  $ sudo apt-get install libopenbabel-dev


  • numpy (version >= 1.10.4)
  • openbabel (version >= 2.3.2)
  • # Assumed environment is Anaconda
    # numpy was already installed as a default.
     $ conda install --channel https://conda.anaconda.org/Clyde_Fare openbabel 



 $ tar -zxvf spresso_decomp_v1.0.tar.gz
 $ cd spresso_decomp_v1.0
 $ make -j
# If it is finished correctly, an executable file "spresso_decompose" is made.


1. Decomposition

 $ ./spresso_decomp -c config.in
 $ ./spresso_decomp -l ligandfile -f fragmentfile -o annotated_ligandfile

A sample of config.in is here.

2. Fragment Docking

 $ python fragment_docking.py -g glide_protein_grid.zip -i fragment.sdf -o output.sdf -m SP

3. Compounds Evaluation

 $ python calc_compound_score.py annotated_ligand.sdf docked_fragment.sdf scored_ligand.sdf

For each program, "--help" option will tell you further information.


yanagisawa [at] bi.c.titech.ac.jp (Keisuke Yanagisawa, Tokyo Institute of Technology)


Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama. Spresso: an ultrafast compound pre-screening method based on compound decomposition, Bioinformatics. (in press) [open access]