Systemic Evolutionary Chemical Space Exploration for Drug Discovery

Related tags

Deep Learningdeep-learningde-novo-drug-designchemical-space-explorationfragment-based-drug-discovery
Overview

SECSE

SECSE: Systemic Evolutionary Chemical Space Explorer

plot

Chemical space exploration is a major task of the hit-finding process during the pursuit of novel chemical entities. Compared with other screening technologies, computational de novo design has become a popular approach to overcome the limitation of current chemical libraries. Here, we reported a de novo design platform named systemic evolutionary chemical space explorer (SECSE). The platform was conceptually inspired by fragment-based drug design, that miniaturized a “lego-building” process within the pocket of a certain target. The key of virtual hits generation was then turned into a computational search problem. To enhance search and optimization, human intelligence and deep learning were integrated. SECSE has the potential in finding novel and diverse small molecules that are attractive starting points for further validation.

Tutorials and Usage

  1. Set Environment Variables
    export $SECSE=path/to/SECSE
    if you use AutoDock Vina for docking: (download here)
    export $VINA=path/to/AutoDockVINA
    if you use Gilde for docking (additional installation & license required):
    export $SCHRODINGER=path/to/SCHRODINGER

  2. Give execution permissions to the SECSE directory
    chmod -R +X path/to/SECSE

  3. Input fragments: a tab split .smi file without header. See demo here.

  4. Parameters in config file:
    [DEFAULT]

    • workdir, working directory, create if not exists, otherwise overwrite, type=str
    • fragments, file path to seed fragments, smi format, type=str
    • num_gen, number of generations, type=int
    • num_per_gen, number of molecules generated each generation, type=int
    • seed_per_gen, number of selected seed molecules per generation, default=1000, type=int
    • start_gen, number of staring generation, default=0, type=int
    • docking_program, name of docking program, AutoDock-Vina (input vina) or Glide (input glide) , default=vina, type=str

    [docking]

    • target, protein PDBQT if use AutoDock Vina; Grid file if choose Glide, type=str
    • RMSD, docking pose RMSD cutoff between children and parent, default=2, type=float
    • delta_score, decreased docking score cutoff between children and parent, default=-1.0, type=float
    • score_cutoff, default=-9, type=float

    Parameters when docking by AutoDock Vina:

    • x, Docking box x, type=float
    • y, Docking box y, type=float
    • z, Docking box z, type=float
    • box_size_x, Docking box size x, default=20, type=float
    • box_size_y, Docking box size y, default=20, type=float
    • box_size_z, Docking box size z, default=20, type=float

    [deep learning]

    • mode, mode of deep learning modeling, 0: not use, 1: modeling per generation, 2: modeling overall after all the generation, default=0, type=int
    • dl_per_gen, top N predicted molecules for docking, default=100, type=int
    • dl_score_cutoff, default=-9, type=float

    [properties]

    • MW, molecular weights cutoff, default=450, type=int
    • logP_lower, minimum of logP, default=0.5, type=float
    • logP_upper, maximum of logP, default=7, type=float
    • chiral_center, maximum of chiral center,default=3, type=int
    • heteroatom_ratio, maximum of heteroatom ratio, default=0.35, type=float
    • rotatable_bound_num, maximum of rotatable bound, default=5, type=int
    • rigid_body_num, default=2, type=int

    Config file of a demo case phgdh_demo_vina.ini

  5. Run SECSE
    python $SECSE/run_secse.py --config path/to/config

  6. Output files

    • merged_docked_best_timestamp_with_grow_path.csv: selected molecules and growing path
    • selected.sdf: 3D conformers of all selected molecules

Dependencies

GNU Parallel installation

numpy~=1.20.3, pandas~=1.3.3, pandarallel~=1.5.2, tqdm~=4.62.2, biopandas~=0.2.9, openbabel~=3.1.1, rdkit~=2021.03.5, chemprop~=1.3.1, torch~=1.9.0+cu111

Citation

Lu, C.; Liu, S.; Shi, W.; Yu, J.; Zhou, Z.; Zhang, X.; Lu, X.; Cai, F.; Xia, N.; Wang, Y. Systemic Evolutionary Chemical Space Exploration For Drug Discovery. ChemRxiv 2021. This content is a preprint and has not been peer-reviewed.

License

SECSE is released under Apache License, Version 2.0.

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Comments
  • Problem running demo

    Problem running demo

    Hi!

    When I try to run the demo with the command below. python $SECSE/run_secse.py --config demo/phgdh_demo_vina.ini

    It generates pandas.errors.EmptyDataError: No columns to parse from file, what should I do to solve it? Thank you!

    Here is the output

    **************************************************************************************** 
      ____    _____    ____   ____    _____ 
     / ___|  | ____|  / ___| / ___|  | ____|
     \___ \  |  _|   | |     \___ \  |  _|  
      ___) | | |___  | |___   ___) | | |___ 
     |____/  |_____|  \____| |____/  |_____|
/home/bruce/Downloads/Softwares/Anaconda/envs/secse/lib/python3.7/site-packages/pandas/core/generic.py:2882: UserWarning: The spaces in these column names will not be changed. In pandas versions < 0.14, spaces were converted to underscores.
 method=method,
Table 'G-001' already exists.

******************************************************************
Input fragment file: /home/bruce/Work/CADD/SECSE/code/demo/demo_1020.smi
Target grid file: /home/bruce/Work/CADD/SECSE/code/demo/PHGDH_6RJ3_for_vina.pdbqt
Workdir: /home/bruce/Work/CADD/SECSE/code/res/


************************************************** 
Generation  0 ...
Step 1: Docking with Autodock Vina ...
/home/bruce/Work/CADD/SECSE/code/secse/evaluate/ligprep_vina_parallel.sh /home/bruce/Work/CADD/SECSE/code/res/generation_0 /home/bruce/Work/CADD/SECSE/code/demo/demo_1020.smi /home/bruce/Work/CADD/SECSE/code/demo/PHGDH_6RJ3_for_vina.pdbqt 20.9 -10.4 3.0 20.0 20.0 25.0 10
find /home/bruce/Work/CADD/SECSE/code/res/generation_0/sdf_files -name "*sdf" | xargs -n 100 cat > /home/bruce/Work/CADD/SECSE/code/res/generation_0/docking_outputs_with_score.sdf
Docking time cost: 0.12 min.
Step 2: Ranking docked molecules...
9 cmpds after evaluate
The evaluate score cutoff is: -9.0
9 final seeds.

************************************************** 
Generation  1 ...
Step 1: Mutation
No rule class:  B-001
No rule class:  G-003
No rule class:  G-004
No rule class:  G-005
No rule class:  G-006
No rule class:  G-007
No rule class:  M-001
No rule class:  M-002
No rule class:  M-003
No rule class:  M-004
No rule class:  M-005
No rule class:  M-006
No rule class:  M-007
No rule class:  M-008
No rule class:  M-009
No rule class:  M-010
No rule class: G-002
Step 2: Filtering all mutated mols
sh /home/bruce/Work/CADD/SECSE/code/secse/growing/filter_parallel.sh /home/bruce/Work/CADD/SECSE/code/res/generation_1 1 demo/phgdh_demo_vina.ini 10
Filter runtime: 0.00 min.
Traceback (most recent call last):
 File "/home/bruce/Work/CADD/SECSE/code/secse/run_secse.py", line 80, in <module>
   main()
 File "/home/bruce/Work/CADD/SECSE/code/secse/run_secse.py", line 65, in main
   workflow.grow()
 File "/home/bruce/Work/CADD/SECSE/code/secse/grow_processes.py", line 208, in grow
   self._filter_df = pd.read_csv(os.path.join(self.workdir_now, "filter.csv"), header=None)
 File "/home/bruce/Downloads/Softwares/Anaconda/envs/secse/lib/python3.7/site-packages/pandas/util/_decorators.py", line 311, in wrapper
   return func(*args, **kwargs)
 File "/home/bruce/Downloads/Softwares/Anaconda/envs/secse/lib/python3.7/site-packages/pandas/io/parsers/readers.py", line 586, in read_csv
   return _read(filepath_or_buffer, kwds)
 File "/home/bruce/Downloads/Softwares/Anaconda/envs/secse/lib/python3.7/site-packages/pandas/io/parsers/readers.py", line 482, in _read
   parser = TextFileReader(filepath_or_buffer, **kwds)
 File "/home/bruce/Downloads/Softwares/Anaconda/envs/secse/lib/python3.7/site-packages/pandas/io/parsers/readers.py", line 811, in __init__
   self._engine = self._make_engine(self.engine)
 File "/home/bruce/Downloads/Softwares/Anaconda/envs/secse/lib/python3.7/site-packages/pandas/io/parsers/readers.py", line 1040, in _make_engine
   return mapping[engine](self.f, **self.options)  # type: ignore[call-arg]
 File "/home/bruce/Downloads/Softwares/Anaconda/envs/secse/lib/python3.7/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 69, in __init__
   self._reader = parsers.TextReader(self.handles.handle, **kwds)
 File "pandas/_libs/parsers.pyx", line 549, in pandas._libs.parsers.TextReader.__cinit__
pandas.errors.EmptyDataError: No columns to parse from file
    opened by BW15061999 17
  • Question about running the demo code

    Question about running the demo code

    Hi authors,

    I have tried to run your demo code in README.md, but got some errors.

    Command

    python /home/xxx/workspace/off-SECSE/secse/run_secse.py --config ./config.ini

    Output

     **************************************************************************************** 
       ____    _____    ____   ____    _____ 
      / ___|  | ____|  / ___| / ___|  | ____|
      \___ \  |  _|   | |     \___ \  |  _|  
       ___) | | |___  | |___   ___) | | |___ 
      |____/  |_____|  \____| |____/  |_____|

******************************************************************
Input fragment file: /home/xxx/workspace/off-SECSE/fy-run/demo001/ligand.smi
Target grid file: /home/xxx/workspace/off-SECSE/fy-run/demo001/receptor.pdbqt
Workdir: /home/xxx/workspace/off-SECSE/fy-run/demo001/

Step 1: Docking with Autodock Vina ...
/home/xxx/workspace/off-SECSE/secse/evaluate/ligprep_vina_parallel.sh /home/xxx/workspace/off-SECSE/fy-run/demo001/generation_0 /home/xxx/workspace/off-SECSE/fy-run/demo001/ligand.smi /home/t-yafan/workspace/off-SECSE/fy-run/demo001/receptor.pdbqt 20.9 -10.4 3.0 20.0 20.0 25.0 10
find /home/xxx/workspace/off-SECSE/fy-run/demo001/generation_0/sdf_files -name "*sdf" | xargs -n 100 cat > /home/xxx/workspace/off-SECSE/fy-run/demo001/generation_0/docking_outputs_with_score.sdf
Docking time cost: 0.11 min.
Step 2: Ranking docked molecules...
9 cmpds after evaluate
The evaluate score cutoff is: -9.0
9 final seeds.

 ************************************************** 
Generation  1 ...
Step 1: Mutation
Traceback (most recent call last):
  File "/home/xxx/workspace/off-SECSE/secse/run_secse.py", line 70, in <module>
    main()
  File "/home/xxx/workspace/off-SECSE/secse/run_secse.py", line 55, in main
    workflow.grow()
  File "/home/xxx/workspace/off-SECSE/secse/grow_processes.py", line 159, in grow
    header = mutation_df(self.winner_df, self.workdir, self.cpu_num, self.gen)
  File "/home/xxx/workspace/off-SECSE/secse/growing/mutation/mutation.py", line 166, in mutation_df
    mutation = Mutation(5000, workdir)
  File "/home/xxx/workspace/off-SECSE/secse/growing/mutation/mutation.py", line 29, in __init__
    self.load_common_rules()
  File "/home/xxx/workspace/off-SECSE/secse/growing/mutation/mutation.py", line 50, in load_common_rules
    c.execute(sql)
sqlite3.OperationalError: no such table: B-001

    It seems that the file secse/growing/mutation/rules_demo.db is missing in the repo. How can I fix it?

    Thanks!

    opened by fyabc 5
  • All dockings do not work because there's no gridding process.

    All dockings do not work because there's no gridding process.

    Hi, I was trying out the repo when I realised that neither the autodock nor glide is able to run because there was no gridding process, resulting in no grid files. >.<

    opened by yipy0005 3
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