How Does a Drug Molecule Find Its Target Binding Site?
Open accessAbstract
Although the thermodynamic principles that control the binding of drug molecules to their protein targets are well understood, detailed experimental characterization of the process by which such binding occurs has proven challenging. We conducted relatively long, unguided molecular dynamics simulations in which a ligand (the cancer drug dasatinib or the kinase inhibitor PP1) was initially placed at a random location within a box that also contained a protein (Src kinase) to which that ligand was known to bind. In several of these simulations, the ligand correctly identified its target binding site, forming a complex virtually identical to the crystallographically determined bound structure. The simulated trajectories provide a continuous, atomic-level view of the entire binding process, revealing persistent and noteworthy intermediate conformations and shedding light on the role of water molecules. The technique we employed, which does not assume any prior knowledge of the binding site's location, may prove particularly useful in the development of allosteric inhibitors that target previously undiscovered binding sites.
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Direct simulation can achieve timescales sufficient to observe ligand binding events.
“While direct simulation can achieve timescales sufficient to observe ligand binding events [54]”
From Markov state models of biomolecular conformational dynamics (2014) · cites this paper as [54]
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Funnels, pathways, and the energy landscape of protein folding: A synthesis
Bryngelson, J. D., Onuchic, J. N., Socci, N. D., & Wolynes, P. G. (1995) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.340210302 · Cited by 2,648 · see citing works
Crystal structure of the Src family tyrosine kinase Hck
Sicheri, F., Moarefi, I., & Kuriyan, J. (1997) · Nature · doi:10.1038/385602a0 · Cited by 1,181 · see citing works
Modification of the Generalized Born Model Suitable for Macromolecules
Onufriev, A. V., Bashford, D., & Case, D. A. (2000) · The Journal of Physical Chemistry B · doi:10.1021/jp994072s · Cited by 1,093 · see citing works
Protein kinases: evolution of dynamic regulatory proteins
Taylor, S. S., & Kornev, A. P. (2010) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2010.09.006 · Cited by 940 · see citing works
Motifs for molecular recognition exploiting hydrophobic enclosure in protein–ligand binding
Young, T. K., Abel, R., Kim, B., Berne, B. J., & Friesner, R. A. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610202104 · Cited by 697 · see citing works
Ladbury, J. E. (1996) · Chemistry & Biology · doi:10.1016/s1074-5521(96)90164-7 · Cited by 521 · see citing works
Blind docking of drug‐sized compounds to proteins with up to a thousand residues
Hetényi, C., & van der Spoel, D. (2006) · FEBS Letters · doi:10.1016/j.febslet.2006.01.074 · Cited by 325 · see citing works
A conserved protonation-dependent switch controls drug binding in the Abl kinase
Shan, Y., Seeliger, M. A., Eastwood, M. P., Frank, F., Xu, H., Jensen, M. Ø., Dror, R. O., Kuriyan, J., & Shaw, D. E. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811223106 · Cited by 264 · see citing works
Self-citationEnergy Landscape Theory, Funnels, Specificity, and Optimal Criterion of Biomolecular Binding
Wang, J., & Verkhivker, G. M. (2003) · Physical Review Letters · doi:10.1103/physrevlett.90.188101 · Cited by 158 · see citing works
Hybrid Compound Design To Overcome the Gatekeeper T338M Mutation in cSrc
Getlik, M., Grütter, C., Simard, J. R., Klüter, S., Rabiller, M., Rode, H. B., Robubi, A., & Rauh, D. (2009) · Journal of Medicinal Chemistry · doi:10.1021/jm9002928 · Cited by 142 · see citing works
Blind docking of pharmaceutically relevant compounds using RosettaLigand
Davis, I., Raha, K., Head, M. S., & Baker, D. A. (2009) · Protein Science · doi:10.1002/pro.192 · Cited by 85 · see citing works
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Chodera, J. D., & Noé, F. (2014) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2014.04.002 · Cited by 776 · see citing works
The future of molecular dynamics simulations in drug discovery
Borhani, D. W., & Shaw, D. E. (2012) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-011-9517-y · Cited by 313 · see citing works
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Miller, E. B., Murphy, R. B., Sindhikara, D., Borrelli, K. W., Grisewood, M. J., Ranalli, F., Dixon, S. L., Jerome, S., Boyles, N. A., Day, T., et al. (2021) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c00136 · Cited by 210 · see citing works
Huggins, D. J., Biggin, P. C., Dämgen, M. A., Essex, J. W., Harris, S. A., Henchman, R. H., Khalid, S., Kuzmanic, A., Laughton, C. A., Michel, J., et al. (2019) · WIREs Computational Molecular Science · doi:10.1002/wcms.1393 · Cited by 169 · see citing works
Exploring the role of receptor flexibility in structure-based drug discovery
Feixas, F., Lindert, S., Sinko, W., & McCammon, J. A. (2014) · Biophysical Chemistry · doi:10.1016/j.bpc.2013.10.007 · Cited by 156 · see citing works
Recent computational advances in the identification of allosteric sites in proteins
Lu, S., Huang, W., & Zhang, J. (2014) · Drug Discovery Today · doi:10.1016/j.drudis.2014.07.012 · Cited by 102 · see citing works
Verkhivker, G. M., Agajanian, S., Hu, G., & Tao, P. (2020) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2020.00136 · Cited by 76 · see citing works
Howard, R. J., Trudell, J. R., & Harris, R. A. (2014) · Pharmacological Reviews · doi:10.1124/pr.113.007468 · Cited by 56 · see citing works
Challenges of docking in large, flexible and promiscuous binding sites
Kotev, M., Soliva, R., & Orozco, M. (2016) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2016.08.010 · Cited by 25 · see citing works
Mingione, V. R., Foda, Z. H., Paung, Y., Philipose, H., Rangwala, A. M., Shan, Y., & Seeliger, M. A. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2022.167628 · Cited by 13 · see citing works
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- Authors
- Shan, Y., Kim, E. T., Eastwood, M. P., Dror, R. O., Seeliger, M. A., & Shaw, D. E.
- Affiliations
- D. E. Shaw Research (US)
- Stony Brook University (US)
- Corresponding author
- Shaw, David E.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-05-13
- Volume
- 133
- Issue
- 24
- Pages
- 9181-9183
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- PMC
- PMC3221467
- OpenAlex
- W1989814214
- Cited by
- 614
- References
- 11
- Citations by year
- 2026: 18 · 2025: 23 · 2024: 24 · 2023: 35 · 2022: 46 · 2021: 49 · 2020: 52 · 2019: 40 · 2018: 46 · 2017: 49 · 2016: 46 · 2015: 46 · 2014: 45 · 2013: 40 · 2012: 40
- FWCI
- 41.89
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of the American Chemical Society (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of General Medical Sciences (R00GM080097)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Keywords
- Src kinase, dasatinib, protein phosphatase 1, kinase inhibitors, binding intermediates, allosteric inhibitors, protein-ligand binding
- MeSH terms
- Dasatinib, Binding Sites, Protein Binding, Protein Conformation, Pyrazoles, Pyrimidines, Thiazoles, src-Family Kinases, Molecular Dynamics Simulation
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