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Structural Biology and Drug Discovery of Difficult Targets: The Limits of Ligandability
Open accessAbstract
Over the past decade, researchers in the pharmaceutical industry and academia have made retrospective analyses of successful drug campaigns in order to establish "rules" to guide the selection of new target proteins. They have identified features that are considered undesirable and some that make targets "unligandable." This review focuses on the factors that make targets difficult: featureless binding sites, the lack of hydrogen-bond donors and acceptors, the presence of metal ions, the need for adaptive changes in conformation, and the lipophilicity of residues at the protein-ligand interface. Protein-protein interfaces of multiprotein assemblies share many of these undesirable features, although those that involve concerted binding and folding in their assembly have better defined pockets or grooves, and these can provide opportunities for identifying hits and for lead optimization. In some protein-protein interfaces conformational changes-often involving rearrangement of large side chains such as those of tyrosine, tryptophan, or arginine-are required to configure an appropriate binding site, and this may require tethering of the ligands until higher affinity is achieved. In many enzymes, larger conformational rearrangements are required to form the binding site, and these can make fragment-based approaches particularly difficult.
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“not all members of a protein family have drug-compatible or ligandable21 binding sites”
From Unexplored therapeutic opportunities in the human genome (2018) · cites this paper as [21]
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Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(00)00129-0 · Cited by 18,139
An inhibitor of Bcl-2 family proteins induces regression of solid tumours
Oltersdorf, T., Elmore, S. W., Shoemaker, A. R., Armstrong, R. C., Augeri, D. J., Belli, B., Bruncko, M., Deckwerth, T. L., Dinges, J., Hajduk, P. J., et al. (2005) · Nature · doi:10.1038/nature03579 · Cited by 3,407
Hopkins, A. L., & Groom, C. R. (2002) · Nature Reviews Drug Discovery · doi:10.1038/nrd892 · Cited by 3,305
Discovering High-Affinity Ligands for Proteins: SAR by NMR
Shuker, S. B., Hajduk, P. J., Meadows, R. P., & Fesik, S. W. (1996) · Science · doi:10.1126/science.274.5292.1531 · Cited by 2,045
Reaching for high-hanging fruit in drug discovery at protein–protein interfaces
Wells, J. A., & McClendon, C. L. (2007) · Nature · doi:10.1038/nature06526 · Cited by 2,002
Anatomy of hot spots in protein interfaces
Bogan, A. A., & Thorn, K. S. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.1843 · Cited by 1,988
A Hot Spot of Binding Energy in a Hormone-Receptor Interface
Clackson, T., & Wells, J. A. (1995) · Science · doi:10.1126/science.7529940 · Cited by 1,987
Structural Mechanism for STI-571 Inhibition of Abelson Tyrosine Kinase
Schindler, T. H., Bornmann, W. G., Pellicena, P., Miller, W. T., Clarkson, B., & Kuriyan, J. (2000) · Science · doi:10.1126/science.289.5486.1938 · Cited by 1,785
Fpocket: An open source platform for ligand pocket detection
Guilloux, V. L., Schmidtke, P., & Tufféry, P. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-168 · Cited by 1,724
X-ray and NMR structure of human Bcl-xL, an inhibitor of programmed cell death
Muchmore, S. W., Sattler, M., Liang, H., Meadows, R. P., Harlan, J. E., Yoon, H. S., Nettesheim, D. G., Chang, B. S., Thompson, C. B., Wong, S., et al. (1996) · Nature · doi:10.1038/381335a0 · Cited by 1,467
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Items 201–234 of 234
Villoutreix, B. O., Kuenemann, M. A., Lagorce, D., Spérandio, O., & Miteva, M. A. (2015) · CRC Press eBooks · doi:10.1201/b18799-21
Caracterización bioquímica y estructural de glicosiltransferasas bacterianas
Salinas, S. R. (2013) · Repositorio Digital Institucional de la Universidad de Buenos Aires (Universidad de Buenos Aires)
Johnson, D. K. (2016) · KU ScholarWorks (The University of Kansas)
Dean, S. F., Spies, M. A., Doorn, J. A., & Duffel, M. W. (2016) · doi:10.17077/etd.ppygeuv8
Tailoring Hit Identification and Qualification Methods for Targeting Protein–Protein Interactions
Walse, B., Turnbull, A. P., & Boyd, S. M. (2017) · Wiley eBooks · doi:10.1002/9781119099512.ch3
Modeling of BACE-1 Inhibitors as Anti-Alzheimer’s Agents
Paz, O. S., Froes, T. Q., Leite, F. H. A., & Castilho, M. S. (2017) · Neuromethods · doi:10.1007/978-1-4939-7404-7_7
Fuchs, J. A., Brunner, C., Schineis, P., Hiss, J. A., & Schneider, G. (2019) · Angewandte Chemie · doi:10.1002/ange.201902022
Microfluidic Technologies and Platforms for Protein Crystallography
Maeki, M., & Tokeshi, M. (2019) · Bioanalysis · doi:10.1007/978-981-13-6229-3_2
Heinke, F., Hempel, L., & Labudde, D. (2019) · Communications in computer and information science · doi:10.1007/978-3-030-19093-4_18
Synthesis of peptidomimetic scaffolds
Wilson, A. J. (2013) · doi:10.4155/ebo.13.176
Targeted Protein Degradation: Current Status and Future Prospects
Mukherjee, S., Giri, S., Bera, S., Mukherjee, S., Dey, S., & Roy, N. S. (2021) · Research Journal of Pharmacy and Technology · doi:10.52711/0974-360x.2021.00880
Characterization of Multiple Surface Loops in Escherichia coli Biotin Protein Ligase Functions
Adikaram, P. R. (2012) · University Libraries (University of Maryland)
Computational Methods for Prediction of Protein-Protein Interactions
Rai, S., & Bhatnagar, S. (2016) · Advances in bioinformatics and biomedical engineering book series · doi:10.4018/978-1-5225-0427-6.ch010
Yuan, X., Jiang, H., Fu, D., Robida, A. M., Rajanayake, K. K., Yuan, H., Wen, B., Sun, D., Watch, B. T., Chinnaswamy, K., et al. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4138554
The Potential Use of Peptides in the Fight against Chagas Disease and LeishmaniasisPreprint
Qvit, N., Zerihun, M., Kumar, M., & Berhe, H. (2023) · Preprints.org · doi:10.20944/preprints202309.0207.v1
Microfluidic Technologies and Platforms for Protein Crystallography
Maeki, M., & Tokeshi, M. (2024) · Bioanalysis · doi:10.1007/978-981-97-6540-9_2
Multiobjective optimization of biological and physical properties in drug discovery
Gleeson, M. P., & Montanari, D. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-29808-0.00014-5
Loharch, S., Medina‐Trillo, C., Sedgwick, D. M., Barrio, P., Fustero, S., & Gallego, J. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.4c15031
Sun, L., Zhang, Y., Chen, G., Ji, Y., Ma, Q., Qiao, X., Wu, S., Zhou, L., Bu, J., Zhu, X., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26558123
Drug discovery guided by maximum drug likenessPreprint
Zhu, H.-Y., Xu, L., & Shi, W. F. (2025) · Research Square · doi:10.21203/rs.3.rs-8452302/v1
Zhu, H., Du, S., Yang, Q., Xu, L., & Shi, W. (2026) · Pharmaceuticals · doi:10.3390/ph19050744
NAALADL1 modulates cellular resistance to Tumor Treating Fields in colorectal cancer
Su, Z., Liu, M., Krohn, M., Ostermann, J., Schwarz, S., Hahn, O., Frank, M., Gemoll, T., Schafmayer, C., & Linnebacher, M. (2026) · npj Precision Oncology · doi:10.1038/s41698-026-01492-0
Zhu, H., Du, S., Yang, Q., Xu, L., & Shi, W. (2026) · Drug Design Development and Therapy · doi:10.2147/dddt.s595430
Tyagi, M., Poongavanam, V., Zich, S., Lindhagen, M., Asproudis, I., Putra, O. D., Yang, J., Ashworth, Z. J. R., Guadagni, A., Hagemeyer, L. J., et al. (2026) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.6c00830
Shen, A., Yuan, M., Huang, Q., Feng, B., Du, J., Ma, Y., & Wang, M. (2026) · Information Fusion · doi:10.1016/j.inffus.2026.104709
Liu, T., Wang, S., Wang, D., Wang, S., & Pang, S. (2026) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-026-00875-y
Future trends in structural biology
Anwar, S., Khan, S., Khan, S. A., Dinislam, K., Parvez, S., & Shamsi, A. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-44988-8.00017-4
Temporally Validated Models for Target “Tclin-likeness”
Quazi, M. A., Sirimulla, S., Bologa, C., Pushechnikov, A. O., Farley, B., Savchuk, N., & Oprea, T. I. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c03088
BindingDB Entry 50012354: Mining Natural Products for Macrocycles to Drug Difficult Targets.
BindingDB (2022) · UC San Diego · doi:10.7270/q23200kv
BindingDB (2014) · UC San Diego · doi:10.7270/q2nk3gh1
BindingDB Entry 50002721: Modulators of 14-3-3 Protein-Protein Interactions.
BindingDB (2020) · UC San Diego · doi:10.7270/q2rb7781
Metadata
- Authors
- Surade, S., & Blundell, T. L.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Blundell, Tom L.
- Venue
- Chemistry & Biology
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 19
- Issue
- 1
- Pages
- 42-50
- ISSN
- 1074-5521 (ISSN-L)
- OpenAlex
- W2084501039
- Cited by
- 230
- References
- 97
- Citations by year
- 2026: 10 · 2025: 15 · 2024: 15 · 2023: 10 · 2022: 12 · 2021: 18 · 2020: 10 · 2019: 9 · 2018: 16 · 2017: 20 · 2016: 31 · 2015: 19 · 2014: 11 · 2013: 22 · 2012: 12
- FWCI
- 2.28
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Chemistry & Biology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Bill and Melinda Gates Foundation
- University of Pittsburgh
- Wellcome Trust
- European Commission
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- ligandability, target selection, protein binding sites, hydrogen bond donors and acceptors, protein conformational change, protein-protein interfaces, fragment-based drug discovery, lead optimization
- MeSH terms
- Binding Sites, Ligands, Proteins, Catalytic Domain, BRCA2 Protein, Protein Interaction Mapping, Rad51 Recombinase, Drug Discovery
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