Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology
Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural i...
| Main Authors: | , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
BioMed Central
2025
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| _version_ | 1824458990447230976 |
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| author | Ferla, MP Sánchez-García, R Skyner, RE Gahbauer, S Taylor, JC von Delft, F Marsden, BD Deane, CM |
| author_facet | Ferla, MP Sánchez-García, R Skyner, RE Gahbauer, S Taylor, JC von Delft, F Marsden, BD Deane, CM |
| author_sort | Ferla, MP |
| collection | OXFORD |
| description | Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein–ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode. Fragmenstein either takes the atomic coordinates of ligands from a experimental fragment screen and combines the atoms together to produce a novel merged virtual compound, or uses them to predict the bound complex for a provided molecule. The molecule is then energy minimised under strong constraints to obtain a structurally plausible conformer. The code is available at https://github.com/oxpig/Fragmenstein. Scientific contribution This work shows the importance of using the coordinates of known binders when predicting the conformation of derivative molecules through a retrospective analysis of the COVID Moonshot data. This method has had a prior real-world application in hit-to-lead screening, yielding a sub-micromolar merger from parent hits in a single round. It is therefore likely to further benefit future drug design campaigns and be integrated in future pipelines. Graphical Abstract: |
| first_indexed | 2025-02-19T04:34:40Z |
| format | Journal article |
| id | oxford-uuid:624a9b24-04a7-4a61-9cf6-ae23b688479e |
| institution | University of Oxford |
| language | English |
| last_indexed | 2025-02-19T04:34:40Z |
| publishDate | 2025 |
| publisher | BioMed Central |
| record_format | dspace |
| spelling | oxford-uuid:624a9b24-04a7-4a61-9cf6-ae23b688479e2025-01-23T20:03:45ZFragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodologyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:624a9b24-04a7-4a61-9cf6-ae23b688479eEnglishJisc Publications RouterBioMed Central2025Ferla, MPSánchez-García, RSkyner, REGahbauer, STaylor, JCvon Delft, FMarsden, BDDeane, CMCurrent strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein–ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode. Fragmenstein either takes the atomic coordinates of ligands from a experimental fragment screen and combines the atoms together to produce a novel merged virtual compound, or uses them to predict the bound complex for a provided molecule. The molecule is then energy minimised under strong constraints to obtain a structurally plausible conformer. The code is available at https://github.com/oxpig/Fragmenstein. Scientific contribution This work shows the importance of using the coordinates of known binders when predicting the conformation of derivative molecules through a retrospective analysis of the COVID Moonshot data. This method has had a prior real-world application in hit-to-lead screening, yielding a sub-micromolar merger from parent hits in a single round. It is therefore likely to further benefit future drug design campaigns and be integrated in future pipelines. Graphical Abstract: |
| spellingShingle | Ferla, MP Sánchez-García, R Skyner, RE Gahbauer, S Taylor, JC von Delft, F Marsden, BD Deane, CM Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology |
| title | Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology |
| title_full | Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology |
| title_fullStr | Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology |
| title_full_unstemmed | Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology |
| title_short | Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology |
| title_sort | fragmenstein predicting protein ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved binding based methodology |
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