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Zhang L, Rao V, Cornell W. r-BRICS - A Revised BRICS Module That Breaks Ring Structures and Carbon Chains. ChemMedChem 2024; 19:e202300202. [PMID: 37574458 DOI: 10.1002/cmdc.202300202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 07/24/2023] [Accepted: 08/11/2023] [Indexed: 08/15/2023]
Abstract
Molecular fragmentation has been frequently used for machine learning, molecular modeling, and drug discovery studies. However, the current molecular fragmentation tools often lead to large fragments that are useful to limited tasks. Specifically, long aliphatic chains, certain connected ring structures, fused rings, as well as various nitrogen-containing molecular entities often remain intact when using BRICS. With no known methods to solve this issue, we find that the fragments taken from BRICS are inflexible for tasks such as fragment-based machine learning, coarse-graining, and ligand-protein interaction assessment. In this work, a revised BRICS (r-BRICS) module is developed to allow more flexible fragmentation on a wider variety of molecules. It is shown that r-BRICS generates smaller fragments than BRICS, allowing localized fragment assessments. Furthermore, r-BRICS generates a fragment database with significantly more unique small fragments than BRICS, which is potentially useful for fragment-based drug discovery.
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Affiliation(s)
- Leili Zhang
- IBM Thomas J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, NY, 10598, USA
| | - Vasumitra Rao
- IBM Thomas J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, NY, 10598, USA
| | - Wendy Cornell
- IBM Thomas J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, NY, 10598, USA
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2
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Buehler Y, Reymond JL. Expanding Bioactive Fragment Space with the Generated Database GDB-13s. J Chem Inf Model 2023; 63:6239-6248. [PMID: 37722101 PMCID: PMC10598793 DOI: 10.1021/acs.jcim.3c01096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Indexed: 09/20/2023]
Abstract
Identifying innovative fragments for drug design can help medicinal chemistry address new targets and overcome the limitations of the classical molecular series. By deconstructing molecules into ring fragments (RFs, consisting of ring atoms plus ring-adjacent atoms) and acyclic fragments (AFs, consisting of only acyclic atoms), we find that public databases of molecules (i.e., ZINC and PubChem) and natural products (i.e., COCONUT) contain mostly RFs and AFs of up to 13 atoms. We also find that many RFs and AFs are enriched in bioactive vs inactive compounds from ChEMBL. We then analyze the generated database GDB-13s, which enumerates 99 million possible molecules of up to 13 atoms, for RFs and AFs resembling ChEMBL bioactive RFs and AFs. This analysis reveals a large number of novel RFs and AFs that are structurally simple, have favorable synthetic accessibility scores, and represent opportunities for synthetic chemistry to contribute to drug innovation in the context of fragment-based drug discovery.
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Affiliation(s)
- Ye Buehler
- Department of Chemistry,
Biochemistry and Pharmaceutical Sciences, University of Bern, Freiestrasse 3, 3012 Bern, Switzerland
| | - Jean-Louis Reymond
- Department of Chemistry,
Biochemistry and Pharmaceutical Sciences, University of Bern, Freiestrasse 3, 3012 Bern, Switzerland
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Diao Y, Hu F, Shen Z, Li H. MacFrag: segmenting large-scale molecules to obtain diverse fragments with high qualities. Bioinformatics 2023; 39:6986129. [PMID: 36637187 PMCID: PMC9872447 DOI: 10.1093/bioinformatics/btad012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 01/03/2023] [Accepted: 01/11/2023] [Indexed: 01/14/2023] Open
Abstract
SUMMARY Construction of high-quality fragment libraries by segmenting organic compounds is an important part of the drug discovery paradigm. This article presents a new method, MacFrag, for efficient molecule fragmentation. MacFrag utilized a modified version of BRICS rules to break chemical bonds and introduced an efficient subgraphs extraction algorithm for rapid enumeration of the fragment space. The evaluation results with ChEMBL dataset exhibited that MacFrag was overall faster than BRICS implemented in RDKit and modified molBLOCKS. Meanwhile, the fragments acquired through MacFrag were more compliant with the 'Rule of Three'. AVAILABILITY AND IMPLEMENTATION https://github.com/yydiao1025/MacFrag. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Yanyan Diao
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Feng Hu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Zihao Shen
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Honglin Li
- To whom correspondence should be addressed.
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Towards systematic exploration of chemical space: building the fragment library module in molecular property diagnostic suite. Mol Divers 2022:10.1007/s11030-022-10506-5. [PMID: 35925528 PMCID: PMC9362107 DOI: 10.1007/s11030-022-10506-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 07/23/2022] [Indexed: 11/04/2022]
Abstract
A fragment-based drug discovery (FBDD) approach has traditionally been of utmost significance in drug design studies. It allows the exploration of large chemical space to find novel scaffolds and chemotypes which can be improved into selective inhibitors with good affinity. In the current work, several public domain chemical libraries (ChEMBL, DrugCentral, PDB ligands, COCONUT, and SAVI) comprising bioactive and virtual molecules were retrieved to develop a fragment library. A systematic fragmentation method that breaks a given molecule into rings, linkers, and substituents was used to cleave the molecules and the fragments were analyzed. Further, only the ring framework was taken into the consideration to develop a fragment library that consists of a total number of 107,614 unique fragments. This set represents a rich diverse structure framework that covers a wide variety of yet-to-be-explored fragments for a wide range of small molecule-based applications. This fragment library is an integral part of the molecular property diagnostic suite (MPDS) suite that can be used with other modeling and informatics methods for FBDD approaches. The fragment library module of MPDS can be accessed at http://mpds.neist.res.in:8085.
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Fialková V, Zhao J, Papadopoulos K, Engkvist O, Bjerrum EJ, Kogej T, Patronov A. LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design. J Chem Inf Model 2021; 62:2046-2063. [PMID: 34460269 DOI: 10.1021/acs.jcim.1c00469] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Because of the strong relationship between the desired molecular activity and its structural core, the screening of focused, core-sharing chemical libraries is a key step in lead optimization. Despite the plethora of current research focused on in silico methods for molecule generation, to our knowledge, no tool capable of designing such libraries has been proposed. In this work, we present a novel tool for de novo drug design called LibINVENT. It is capable of rapidly proposing chemical libraries of compounds sharing the same core while maximizing a range of desirable properties. To further help the process of designing focused libraries, the user can list specific chemical reactions that can be used for the library creation. LibINVENT is therefore a flexible tool for generating virtual chemical libraries for lead optimization in a broad range of scenarios. Additionally, the shared core ensures that the compounds in the library are similar, possess desirable properties, and can also be synthesized under the same or similar conditions. The LibINVENT code is freely available in our public repository at https://github.com/MolecularAI/Lib-INVENT. The code necessary for data preprocessing is further available at: https://github.com/MolecularAI/Lib-INVENT-dataset.
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Affiliation(s)
- Vendy Fialková
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Jiaxi Zhao
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden.,Department of Pharmaceutical Biosciences, Uppsala University, Uppsala 75237, Sweden
| | - Kostas Papadopoulos
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Ola Engkvist
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden.,Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg 41756, Sweden
| | | | - Thierry Kogej
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Atanas Patronov
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden
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Heikamp K, Zuccotto F, Kiczun M, Ray P, Gilbert IH. Exhaustive sampling of the fragment space associated to a molecule leading to the generation of conserved fragments. Chem Biol Drug Des 2018; 91:655-667. [PMID: 29063731 PMCID: PMC5836963 DOI: 10.1111/cbdd.13129] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Revised: 10/09/2017] [Accepted: 10/14/2017] [Indexed: 11/28/2022]
Abstract
The first step in hit optimization is the identification of the pharmacophore, which is normally achieved by deconstruction of the hit molecule to generate "deletion analogues." In silico fragmentation approaches often focus on the generation of small fragments that do not describe properly the fragment space associated to the deletion analogues. We present significant modifications to the molecular fragmentation programme molBLOCKS, which allows the exhaustive sampling of the fragment space associated with a molecule to generate all possible molecular fragments. This generates larger fragments, by combining the smallest fragments. Additionally, it has been modified to deal with the problem of changing pharmacophoric properties through fragmentation, by highlighting bond cuts. The modified molBLOCKS programme was used on a set of drug compounds, where it generated more unique fragments than standard fragmentation approaches by increasing the number of fragments derived per compound. This fragment set was found to be more diverse than those generated by standard fragmentation programmes and was relevant to drug discovery as it contains the key fragments representing the pharmacophoric elements associated with ligand recognition. The use of dummy atoms to highlight bond cuts further increases the information content of fragments by visualizing their previous bonding pattern.
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Affiliation(s)
- Kathrin Heikamp
- Drug Discovery UnitDivision of Biological Chemistry and Drug DiscoverySchool of Life SciencesUniversity of DundeeDundeeScotland, UK
| | - Fabio Zuccotto
- Drug Discovery UnitDivision of Biological Chemistry and Drug DiscoverySchool of Life SciencesUniversity of DundeeDundeeScotland, UK
| | - Michael Kiczun
- Drug Discovery UnitDivision of Biological Chemistry and Drug DiscoverySchool of Life SciencesUniversity of DundeeDundeeScotland, UK
| | - Peter Ray
- Drug Discovery UnitDivision of Biological Chemistry and Drug DiscoverySchool of Life SciencesUniversity of DundeeDundeeScotland, UK
| | - Ian H. Gilbert
- Drug Discovery UnitDivision of Biological Chemistry and Drug DiscoverySchool of Life SciencesUniversity of DundeeDundeeScotland, UK
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