The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Synthon-based ligand discovery in virtual libraries of over 11 billion compounds
Open accessAbstract
Structure-based virtual ligand screening is emerging as a key paradigm for early drug discovery owing to the availability of high-resolution target structures 1-4 and ultra-large libraries of virtual compounds 5,6. However, to keep pace with the rapid growth of virtual libraries, such as readily available for synthesis (REAL) combinatorial libraries 7, new approaches to compound screening are needed 8,9. Here we introduce a modular synthon-based approach-V-SYNTHES-to perform hierarchical structure-based screening of a REAL Space library of more than 11 billion compounds. V-SYNTHES first identifies the best scaffold-synthon combinations as seeds suitable for further growth, and then iteratively elaborates these seeds to select complete molecules with the best docking scores. This hierarchical combinatorial approach enables the rapid detection of the best-scoring compounds in the gigascale chemical space while performing docking of only a small fraction (<0.1%) of the library compounds. Chemical synthesis and experimental testing of novel cannabinoid antagonists predicted by V-SYNTHES demonstrated a 33% hit rate, including 14 submicromolar ligands, substantially improving over a standard virtual screening of the Enamine REAL diversity subset, which required approximately 100 times more computational resources. Synthesis of selected analogues of the best hits further improved potencies and affinities (best inhibitory constant (K i) = 0.9 nM) and CB 2/CB 1 selectivity (50-200-fold). V-SYNTHES was also tested on a kinase target, ROCK1, further supporting its use for lead discovery. The approach is easily scalable for the rapid growth of combinatorial libraries and potentially adaptable to any docking algorithm.
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“For example, a 100-fold acceleration of the process was observed by docking a fraction of the chemical library in synchrony with an AI/ML ligand-based prediction of the remaining docking scores.144”
From Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence (2023) · cites this paper as [144]
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Cites
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“The remaining compounds were filtered with PAINS score, drug-likeness properties, chemical diversity as well as ligand interaction diversity to sample different binding modes in the pocket.”
InfluentialStructure-Function of the G Protein–Coupled Receptor Superfamily
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Self-citationUltra-large library docking for discovering new chemotypes
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“Recently, ultra-large libraries of more than 100 million readily accessible (REAL) compounds have been developed and used in docking-based VLS, yielding high-quality hits for lead discovery 5,6 .”
MethodInfluentialSelf-citationComprehensive assay of kinase catalytic activity reveals features of kinase inhibitor selectivity
Anastassiadis, T., Deacon, S. W., Devarajan, K., Ma, H., & Peterson, J. R. (2011) · Nature Biotechnology · doi:10.1038/nbt.2017 · Cited by 919 · cited 1×
“The HotSpot radiometric assay (Reaction Biology Corporation) measures inhibition of ROCK1 catalytic activity towards a specific peptide substrate (KEAKEKRQEQIAKRRRLSSLRASTSKSGGSQK), which is monitored by P81 filter-binding methods 45 .”
MethodPRESTO-Tango as an open-source resource for interrogation of the druggable human GPCRome
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“The Tango arrestin recruitment assays were performed as previously described 23 .”
MethodInfluentialSelf-citationCannabinoids: potential anticancer agents
Guzmán, M. (2003) · Nature reviews. Cancer · doi:10.1038/nrc1188 · Cited by 721 · cited 1×
“The approach is applied here to cannabinoid receptors, which are class A G-protein-coupled receptors (GPCRs), and are key targets in drug discovery for inflammatory disorders, neurodegenerative diseases and cancer 17–19 .”
BackgroundCrystal Structure of the Human Cannabinoid Receptor CB1
Hua, T., Vemuri, K. V., Pu, M., Qu, L., Han, G. W., Wu, Y., Zhao, S., Shui, W., Li, S., Korde, A., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.004 · Cited by 702
Self-citationAn open-source drug discovery platform enables ultra-large virtual screens
Gorgulla, C., Boeszoermenyi, A., Wang, Z., Fischer, P. D., Coote, P. W., Das, K. M., Malets, Y. S., Radchenko, D. S., Moroz, Y. S., Scott, D. A., et al. (2020) · Nature · doi:10.1038/s41586-020-2117-z · Cited by 677 · cited 2×
“Two binding modes for the CB 2 receptor binding pocket were prepared: one guided by 20 known antagonists and another by 20 agonists, selected from ChEMBL high-affinity ligands for CB 2 (CHEMBL253, affinity p Kd > 8).”
MethodInfluentialSelf-citationCryo-EM in drug discovery: achievements, limitations and prospects
Renaud, J., Chari, A., Ciferri, C., Liu, W.-T., Rémigy, H., Stark, H., & Wiesmann, C. (2018) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2018.77 · Cited by 473 · cited 1×
“The affinities ( K i ) of the new compounds for rat CB 1 receptors and human CB 2 receptors were obtained using membrane preparations from rat brain or HEK293 cells, respectively, and [ 3 H]CP-55,940 as the radioligand, as previously described 42,43 .”
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Scientific discovery in the age of artificial intelligence.
Wang, H., Fu, T., Du, Y., Gao, W., Huang, K., Liu, Z., Chandak, P., Liu, S., Van Katwyk, P., Deac, A., et al. (2023) · Nature · doi:10.1038/s41586-023-06221-2 · Cited by 1,823
Computational approaches streamlining drug discovery
Sadybekov, A., & Katritch, V. (2023) · Nature · doi:10.1038/s41586-023-05905-z · Cited by 1,424
“The recently developed virtual synthon hierarchical enumeration screening (V-SYNTHES) 26 technology applies fragment-based design to on-demand chemical spaces, thus avoiding the challenges of custom synthesis (Fig.”
BackgroundMethodInfluentialSelf-citationSelf-Driving Laboratories for Chemistry and Materials Science
Tom, G., Schmid, S. P., Baird, S. G., Cao, Y., Darvish, K., Hao, H., Lo, S., Pablo-García, S., Rajaonson, E. M., Skreta, M., et al. (2024) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00055 · Cited by 707
The Art and Science of Molecular Docking
Paggi, J. M., Pandit, A., & Dror, R. O. (2024) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-030222-120000 · Cited by 546
The neural basis of psychedelic action
Kwan, A. C., Olson, D. E., Preller, K. H., & Roth, B. L. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01177-4 · Cited by 330
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Metadata
- Authors
- Sadybekov, A. A., Sadybekov, A. V., Liu, Y., Iliopoulos-Tsoutsouvas, C., Huang, X.-P., Pickett, J., Houser, B., Patel, N., Tran, N. K., Tong, F., Zvonok, N., Jain, M. K., Savych, O., Radchenko, D. S., Nikas, S. P., Petasis, N. A., Moroz, Y. S., Roth, B. L., Makriyannis, A., & Katritch, V.
- Affiliations
- University of Southern California (US)
- University of North Carolina at Chapel Hill (US)
- Northeastern University (US)
- Enamine (Ukraine) (UA)
- Taras Shevchenko National University of Kyiv (UA)
- Corresponding author
- Roth, Bryan L.
- Makriyannis, Alexandros
- Katritch, Vsevolod
- ORCID
- Venue
- Nature
- Published
- 2021-12-15
- Volume
- 601
- Issue
- 7893
- Pages
- 452-459
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC9763054
- OpenAlex
- W4200233821
- Cited by
- 417
- References
- 43
- Citations by year
- 2026: 65 · 2025: 96 · 2024: 119 · 2023: 88 · 2022: 46 · 2021: 2
- FWCI
- 33.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- UNC Libraries
- Funders
- National Institute of Mental Health (R01MH112205)
- National Institute on Drug Abuse (R01DA041435, R01DA045020, R37DA045657)
- National Institute of General Medical Sciences (GM118289, T32GM118289)
- National Institute of Diabetes and Digestive and Kidney Diseases (U24DK116195)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
- Physical Sciences › Chemistry › Organic Chemistry › Synthesis and Characterization of Heterocyclic Compounds
- Keywords
- structure-based virtual screening, cannabinoid receptor antagonists, cannabinoid receptor ligands, lead compound identification
- MeSH terms
- Algorithms, Ligands, Combinatorial Chemistry Techniques, Libraries, Digital, rho-Associated Kinases, Drug Discovery, Molecular Docking Simulation
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