Page Comparison

1. Generation of substituent list

• Removed phenyls with ortho-substituents

• Filter: cyclic substituents with (1) zero rotatable bond (2) # rings =1 or acyclic substituents with # rotatable bonds <2

• Combined Roche, Coverage, Pfizer, Bayer: 361 substituents (Acyclic aliphatic: 183, 2. aliphatic rings: 100, 3. 6-membered aromatic rings:50, 4. 5-membered aromatic rings:28)

  • Roche set

    • Acyclic aliphatic: 61, 2. aliphatic rings: 21, 3. 6-membered aromatic rings:5, 4. 5-membered aromatic rings:11

  • Coverage set

    • Acyclic aliphatic: 76, 2. aliphatic rings: 2, 3. 6-membered aromatic rings:6, 4. 5-membered aromatic rings:2

  • Pfizer set

    • Acyclic aliphatic: 24, 2. aliphatic rings: 9, 3. 6-membered aromatic rings:6, 4. 5-membered aromatic rings:7

  • eMolecules set (okay not to include eMolecules set?)

    • aliphatic chain: 148, 2. aliphatic rings: 75, 3. 6-membered aromatic rings:90, 4. 5-membered aromatic rings:51

  • Bayer set

    • Acyclic aliphatic: 116, 2. aliphatic rings: 86, 3. 6-membered aromatic rings:42, 4. 5-membered aromatic rings:16

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• Using 361 substituents, generated 59086 molecules (align by mol weights )

3. Curation of molecule set

3.1. Remove similar molecules using MACCS keys fingerprints and Check coverage of torsion parameters

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• Picking a center molecule(one with the largest sum of similarity indices) or the simplest molecule→ constantly choose certain substituents?

  • When choosing Choosing center molecules → need to check coverage of substituent list

    Image Removed

  • When choosing simple molecules → need check coverage of substituent list

  Random picking?

  • • 38 substituents out of 361 not included.(26 scaffolds missing)

• Choosing simple molecules

  • 65 substituents out of 361 not included. (28 scaffolds missing)

• Random picking

  • ~26 substituents out of 361 not included. (27 scaffolds missing)

• maybe, if the molecule covers all scaffolds (3-4 PM)

(5) check coverage of torsion parameter (missing torsions)

→ Generate torsiondrive dataset to submit

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3.2. Internal H bond forming mols : Better SMIRKS needed. How to consider spatial arrangement of 1-n chain

(1) Test filtering w/ oversimplified SMIRKS

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(2) More specific SMIKRS patterns

• Filter  [n,N,o,O,F]([H])[!#1][!#1]~!@[!#1;r]([#7X2;r])

  • # molecules matched : 1430 (out of 59086)

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    Right hand side mols dont seem to form internal H bond

• Filter [n,N,o,O,F]([H])[!#1]~!@[!#1]~!@[!#1;r]([#7X2;r])

  • # molecules matched : 1060 ( <2 % of total)

    

  • How to exclude right mol?

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TODO (2021-04-01)

•  1. Remove ortho substituents from substituent list, add ones with meta/para substituents
•  2. Remove similar molecules using MACCS keys fingerprints
•  3. Check coverage of torsion parameters → generate a draft of molecule set (~3000 entries)
•  4. Addition of intra H bond filter : by using SMIKRS pattern matching
•  5. Check the coverage of problematic substituents, which showed large discrepancies in Pavan’s 1.3.0 benchmarks
•  6. Range of WBOs of each training data subset, a list of scans training a certain torsion parameter
•  7. addition of double bond rotating torsion scans

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damn installation

1. conda create --name constructure -c conda-forge -c openeye -c omnia pydantic openeye-toolkits cmiles ipykernel python=3.8

2. python setup.py develop (constructure)

3. python setup.py install (fragmenter)

4. conda install -c conda-forge pyyaml

* Additionally openforcefield has been installed