The Druggable Genome: Evaluation of Drug Targets in Clinical Trials Suggests Major Shifts in Molecular Class and Indication
Abstract
The largest innovations within pharmaceutical development come through new compounds that have unique and novel modes of action. These innovations commonly involve expanding the protein space targeted by pharmaceutical agents. At present, information about drugs and drug targets is available online via public databases such as DrugBank and the Therapeutic Targets Database. However, this information is biased, understandably so, toward established drugs and drug-target interactions. To gain a better overview of the drug-targeted portion of the human proteome and the directions of current drug development, we developed a data set of clinical trial drug-target interactions based on CenterWatch's Drugs in Clinical Trials Database, one of the largest databases of its kind. Our curation identified 475 potentially novel clinical trial drug targets. This review aims to identify trends in drug development based on the potentially novel targets currently being explored in clinical trials.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Small molecule drugs target only 2-5% of the human genome, so alternative therapies are necessary.
“Although the research of small molecule drug delivery has established a solid foundation, the target of small molecule drugs accounts for only 2–5% of the human genome, so the development of other alternative therapies is necessary.293”
From Smart nanoparticles for cancer therapy (2023) · cites this paper as [293]
Cites
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 · see citing works
Goodman & Gilman's The Pharmacological Basis of Therapeutics
Brunton, L. L. (1985) · Cited by 7,321 · see citing works
DrugBank: a comprehensive resource for in silico drug discovery and exploration
Wishart, D. S. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj067 · Cited by 3,892 · see citing works
How to improve R&D productivity: the pharmaceutical industry's grand challenge
Paul, S. M., Mytelka, D. S., Dunwiddie, C. T., Persinger, C. C., Munos, B. H., Lindborg, S. R., & Schacht, A. L. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3078 · Cited by 3,566 · see citing works
How many drug targets are there?
Overington, J. P., Al-Lazikani, B., & Hopkins, A. L. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2199 · Cited by 3,505 · see citing works
Hopkins, A. L., & Groom, C. R. (2002) · Nature Reviews Drug Discovery · doi:10.1038/nrd892 · Cited by 3,305 · see citing works
Targeting cancer with small molecule kinase inhibitors
Zhang, J., Yang, P. L., & Gray, N. S. (2008) · Nature reviews. Cancer · doi:10.1038/nrc2559 · Cited by 2,586 · see citing works
A postmodern moral tale: the ethics of research relationships
Somerville, M. (2002) · Nature reviews. Drug discovery · doi:10.1038/nrd773 · Cited by 2,175 · see citing works
DrugBank 3.0: a comprehensive resource for 'Omics' research on drugs
Knox, C., Law, V., Jewison, T., Liu, P., Ly, S., Frolkis, A., Pon, A., Banco, K., Mak, C., Neveu, V., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1126 · Cited by 1,832 · see citing works
Interleukin-1-receptor antagonist in type 2 diabetes mellitus
Larsen, C. M., Faulenbach, M., Vaag, A., Vølund, A., Ehses, J. A., Seifert, B., Mandrup-Poulsen, T., & Donath, M. Y. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa065213 · Cited by 1,798 · see citing works
Structural diversity of G protein-coupled receptors and significance for drug discovery
Lagerström, M. C., & Schiöth, H. B. (2008) · Nature Reviews Drug Discovery · doi:10.1038/nrd2518 · Cited by 1,489 · see citing works
Self-citationReorganizing the protein space at the Universal Protein Resource (UniProt)
The UniProt Consortium (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr981 · Cited by 1,223 · see citing works
The protein tyrosine kinase family of the human genome
Robinson, D. R., Wu, Y., & Lin, S. (2000) · Oncogene · doi:10.1038/sj.onc.1203957 · Cited by 1,179 · see citing works
Alzheimer's disease: strategies for disease modification
Citron, M. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd2896 · Cited by 1,060 · see citing works
A transposase strategy for creating libraries of circularly permuted proteins
Mehta, M., Liu, S., & Silberg, J. J. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks060 · Cited by 1,042 · see citing works
Trends in the exploitation of novel drug targets
Rask-Andersen, M., Almén, M. S., & Schiöth, H. B. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3478 · Cited by 853 · see citing works
Self-citationSaier, M. H. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj001 · Cited by 848 · see citing works
Drugs, their targets and the nature and number of drug targets
Imming, P., Sinning, C., & Meyer, A. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2132 · Cited by 833 · see citing works
A Functional-Phylogenetic Classification System for Transmembrane Solute Transporters
Saier, M. H. (2000) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.64.2.354-411.2000 · Cited by 827 · see citing works
Almén, M. S., Nordström, K. J. V., Fredriksson, R., & Schiöth, H. B. (2009) · BMC Biology · doi:10.1186/1741-7007-7-50 · Cited by 601 · see citing works
Self-citationWebb, E. C. (1992) · Academic Press eBooks · Cited by 452 · see citing works
Thomsen, W. J., Grottick, A. J., Menzaghi, F., Saldana, H. R., Espitia, S. A., Yuskin, D., Whelan, K. T., Martin, M. W., Morgan, M. E., Chen, W., et al. (2008) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1124/jpet.107.133348 · Cited by 403 · see citing works
Evidence for Irreversible Inhibition of Glycogen Synthase Kinase-3β by Tideglusib
Domı́nguez, J. M., Fuertes, A., Orozco, L., del Monte-Millán, M., Delgado, E., & Medina, M. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.306472 · Cited by 249 · see citing works
Genomic sciences and the medicine of tomorrow
Drews, J. (1996) · Nature Biotechnology · doi:10.1038/nbt1196-1516 · Cited by 246 · see citing works
Limitations in anti-obesity drug development: the critical role of hunger-promoting neurons
Dietrich, M. O., & Horváth, T. L. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd3739 · Cited by 202 · see citing works
Garcia, J. M., Friend, J., & Allen, S. (2012) · Supportive Care in Cancer · doi:10.1007/s00520-012-1500-1 · Cited by 169 · see citing works
Modulation of GSK-3 as a Therapeutic Strategy on Tau Pathologies
Medina, M., Garrido, J. J., & Wandosell, F. G. (2011) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2011.00024 · Cited by 124 · see citing works
Keynote review: Is declining innovation in the pharmaceutical industry a myth?
Schmid, E. F., & Smith, D. A. (2005) · Drug Discovery Today · doi:10.1016/s1359-6446(05)03524-5 · Cited by 96 · see citing works
Assessment of the anti-obesity effects of the TNP-470 analog, CKD-732
Kim, Y. M., An, J. J., Jin, Y. J., Rhee, Y., Soo, B., Lee, H. C., & Lim, S.-K. (2007) · Journal of Molecular Endocrinology · doi:10.1677/jme.1.02165 · Cited by 68 · see citing works
Anti‐CD3 mAbs for treatment of type 1 diabetes
Kaufman, A. C., & Herold, K. C. (2009) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.933 · Cited by 59 · see citing works
Outlook for the next 5 years in drug innovation
Berggren, R., Møller, M., Moss, R. A., Poda, P., & Śmietana, K. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd3744 · Cited by 55 · see citing works
Fumagillin Reduces Adipose Tissue Formation in Murine Models of Nutritionally Induced Obesity
Lijnen, H. R., Frederix, L., & HOEF, B. V. (2010) · Obesity · doi:10.1038/oby.2009.503 · Cited by 48 · see citing works
Recent advances in the pathophysiology and pharmacological treatment of obesity
Chugh, P. K., & Sharma, S. (2012) · Journal of Clinical Pharmacy and Therapeutics · doi:10.1111/j.1365-2710.2012.01347.x · Cited by 33 · see citing works
Toll-like receptor blocker slows beta cell death in type 1 diabetes
Aldridge, S. (2012) · Nature Biotechnology · doi:10.1038/nbt0212-124c · Cited by 14 · see citing works
Sources of Cancer Research Funding in the United States
McGeary, M., & Burstein, M. C. (1999) · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Trends in GPCR drug discovery: new agents, targets and indications
Hauser, A. S., Attwood, M. M., Rask‐Andersen, M., Schiöth, H. B., & Gloriam, D. E. I. (2017) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2017.178 · Cited by 2,609 · see citing works
Self-citationThe evolution of commercial drug delivery technologies
Vargason, A. M., Anselmo, A. C., & Mitragotri, S. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00698-w · Cited by 1,361 · see citing works
G Protein-Coupled Receptors as Targets for Approved Drugs: How Many Targets and How Many Drugs?
Sriram, K., & Insel, P. A. (2018) · Molecular Pharmacology · doi:10.1124/mol.117.111062 · Cited by 1,258 · see citing works
Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation
Zhou, H., & Pang, X. (2018) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00305 · Cited by 1,184 · see citing works
Smart nanoparticles for cancer therapy
Sun, L., Liu, H., Ye, Y., Lei, Y., Islam, R., Tan, S., Tong, R., Miao, Y.-B., & Cai, L. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01642-x · Cited by 1,073 · see citing works
GPCRdb: an information system for G protein-coupled receptors
Ísberg, V., Mordalski, S., Munk, C., Rataj, K., Harpsøe, K., Hauser, A. S., Vroling, B., Bojarski, A. J., Vriend, G., & Gloriam, D. E. I. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1178 · Cited by 1,067 · see citing works
The druggable genome and support for target identification and validation in drug development
Finan, C., Gaulton, A., Krüger, F. A., Lumbers, R. T., Shah, T., Engmann, J., Galver, L., Kelley, R., Karlsson, A., Santos, R., et al. (2017) · Science Translational Medicine · doi:10.1126/scitranslmed.aag1166 · Cited by 1,011 · see citing works
FDA-approved small-molecule kinase inhibitors
Wu, P., Nielsen, T. E., & Clausen, M. H. (2015) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2015.04.005 · Cited by 1,028 · see citing works
Pawson, A. J., Sharman, J. L., Benson, H. E., Faccenda, E., Alexander, S. P. H., Buneman, O. P., Davenport, A. P., McGrath, J. C., Peters, J. A., Southan, C., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1143 · Cited by 845 · see citing works
SLC Transporters as Therapeutic Targets: Emerging Opportunities
Lin, L., Yee, S. W., Kim, R. B., & Giacomini, K. M. (2015) · Nature Reviews Drug Discovery · doi:10.1038/nrd4626 · Cited by 835 · see citing works
Trends in kinase drug discovery: targets, indications and inhibitor design
Attwood, M. M., Fabbro, D., Sokolov, A. V., Knapp, S., & Schiöth, H. B. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00252-y · Cited by 807 · see citing works
Self-citationPRESTO-Tango as an open-source resource for interrogation of the druggable human GPCRome
Kroeze, W. K., Sassano, M. F., Huang, X.-P., Lansu, K., McCorvy, J. D., Giguère, P. M., Sciaky, N., & Roth, B. L. (2015) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.3014 · Cited by 755 · see citing works
Pharmacogenomics of GPCR Drug Targets
Hauser, A. S., Chavali, S., Masuho, I., Jahn, L. J., Martemyanov, K. A., Gloriam, D. E. I., & Babu, M. M. (2017) · Cell · doi:10.1016/j.cell.2017.11.033 · Cited by 611 · see citing works
Allosteric sodium in class A GPCR signaling
Katritch, V., Fenalti, G., Abola, E. E., Roth, B. L., Cherezov, V., & Stevens, R. C. (2014) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2014.03.002 · Cited by 516 · see citing works
International Union of Basic and Clinical Pharmacology. XCIV. Adhesion G Protein–Coupled Receptors
Hamann, J., Aust, G., Araç, D., Engel, F. B., Formstone, C. J., Fredriksson, R., Hall, R. A., Harty, B. L., Kirchhoff, C., Knapp, B., et al. (2015) · Pharmacological Reviews · doi:10.1124/pr.114.009647 · Cited by 489 · see citing works
Self-citationEmerging Diversity in Lipid–Protein Interactions
Corradi, V., Sejdiu, B. I., Galloso, H. M., Abdizadeh, H., Noskov, S. Y., Marrink, . J., & Tieleman, D. P. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00451 · Cited by 458 · see citing works
Recent developments of HDAC inhibitors: Emerging indications and novel molecules
Bondarev, A. D., Attwood, M. M., Jonsson, J., Chubarev, V. N., Tarasov, V. V., & Schiöth, H. B. (2021) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.14889 · Cited by 440 · see citing works
Self-citationThe Concise Guide to PHARMACOLOGY 2013/14: Enzymes
Alexander, S. P. H., Benson, H. E., Faccenda, E., Pawson, A. J., Sharman, J. L., Spedding, M., Peters, J. A., Harmar, A. J., & Collaborators, C. (2013) · British Journal of Pharmacology · doi:10.1111/bph.12451 · Cited by 423 · see citing works
DGIdb 2.0: mining clinically relevant drug–gene interactions
Wagner, A. H., Coffman, A. C., Ainscough, B. J., Spies, N. C., Skidmore, Z. L., Campbell, K. M., Krysiak, K., Pan, D., McMichael, J. F., Eldred, J. M., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1165 · Cited by 413 · see citing works
Drug Affinity Responsive Target Stability (DARTS) for Small-Molecule Target Identification
Pai, M. Y., Lomenick, B., Hwang, H., Schiestl, R. H., McBride, W. H., Loo, J. A., & Huang, J. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-2269-7_22 · Cited by 362 · see citing works
How Beyond Rule of 5 Drugs and Clinical Candidates Bind to Their Targets
Doak, B. C., Zheng, J., Dobritzsch, D., & Kihlberg, J. O. (2015) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5b01286 · Cited by 345 · see citing works
Drugging Membrane Protein Interactions
Yin, H. H., & Flynn, A. D. (2016) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-092115-025322 · Cited by 342 · see citing works
Cell permeability beyond the rule of 5
Matsson, P., Doak, B. C., Over, B., & Kihlberg, J. O. (2016) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2016.03.013 · Cited by 300 · see citing works
In silico design of novel probes for the atypical opioid receptor MRGPRX2
Lansu, K., Karpiak, J., Liu, J., Huang, X.-P., McCorvy, J. D., Kroeze, W. K., Che, T., Nagase, H., Carroll, F. I., Jin, J., et al. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2334 · Cited by 293 · see citing works
Dahlén, A. D., Dashi, G., Maslov, I. O., Attwood, M. M., Jonsson, J., Trukhan, V., & Schiöth, H. B. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.807548 · Cited by 280 · see citing works
Self-citationNanobodies to Study G Protein–Coupled Receptor Structure and Function
Manglik, A., Kobilka, B. K., & Steyaert, J. (2016) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010716-104710 · Cited by 257 · see citing works
Vijayan, R., He, P., Modi, V., Duong‐Ly, K. C., Ma, H., Peterson, J. R., Dunbrack, R. L., & Levy, R. M. (2014) · Journal of Medicinal Chemistry · doi:10.1021/jm501603h · Cited by 255 · see citing works
The Life of Pi Star: Exploring the Exciting and Forbidden Worlds of the Benzophenone Photophore
Dormán, G., Nakamura, H., Pulsipher, A., & Prestwich, G. D. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00342 · Cited by 249 · see citing works
Sebastiano, M. R., Doak, B. C., Backlund, M., Poongavanam, V., Over, B., Ermondi, G., Caron, G., Matsson, P., & Kihlberg, J. O. (2018) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.8b00347 · Cited by 238 · see citing works
Drugging Undruggable Molecular Cancer Targets
Lazo, J. S., & Sharlow, E. R. (2015) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010715-103440 · Cited by 225 · see citing works
ErbB/HER protein-tyrosine kinases: Structures and small molecule inhibitors
Roskoski, R. J. (2014) · Pharmacological Research · doi:10.1016/j.phrs.2014.06.001 · Cited by 217 · see citing works
GPCRdb: the G protein‐coupled receptor database – an introduction
Munk, C., Ísberg, V., Mordalski, S., Harpsøe, K., Rataj, K., Hauser, A. S., Kolb, P., Bojarski, A. J., Vriend, G., & Gloriam, D. E. I. (2016) · British Journal of Pharmacology · doi:10.1111/bph.13509 · Cited by 212 · see citing works
Systematic functional profiling of transcription factor networks in Cryptococcus neoformans
Jung, K., Yang, D., Maeng, S., Lee, K.-T., So, Y.-S., Hong, J., Choi, J., Byun, H.-J., Kim, H., Bang, S., et al. (2015) · Nature Communications · doi:10.1038/ncomms7757 · Cited by 200 · see citing works
Advances in kinase targeting: current clinical use and clinical trials
Rask‐Andersen, M., Zhang, J., Fabbro, D., & Schiöth, H. B. (2014) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2014.09.007 · Cited by 181 · see citing works
Self-citationMechanisms of adhesion G protein–coupled receptor activation
Vizurraga, A., Adhikari, R., Yeung, J., Yu, M., & Tall, G. G. (2020) · Journal of Biological Chemistry · doi:10.1074/jbc.rev120.007423 · Cited by 179 · see citing works
Systematic functional analysis of kinases in the fungal pathogen Cryptococcus neoformans
Lee, K.-T., So, Y.-S., Yang, D., Jung, K.-W., Choi, J., Lee, D., Kwon, H., Jang, J., Wang, L. L., Cha, S., et al. (2016) · Nature Communications · doi:10.1038/ncomms12766 · Cited by 166 · see citing works
Design and Challenges of Radiopharmaceuticals
Vermeulen, K., Vandamme, M., Bormans, G. M., & Cleeren, F. (2019) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2019.07.001 · Cited by 152 · see citing works
An update on extra-oral bitter taste receptors
Tuzim, K., & Korolczuk, A. (2021) · Journal of Translational Medicine · doi:10.1186/s12967-021-03067-y · Cited by 144 · see citing works
Peptide-based protease inhibitors from plants
Hellinger, R., & Gruber, C. W. (2019) · Drug Discovery Today · doi:10.1016/j.drudis.2019.05.026 · Cited by 140 · see citing works
18F-Labeled Peptides: The Future Is Bright
Richter, S., & Wuest, F. R. (2014) · Molecules · doi:10.3390/molecules191220536 · Cited by 136 · see citing works
Azam, S., Haque, M. E., Jakaria, M., Jo, S.-H., Kim, I., & Choi, D. (2020) · Cells · doi:10.3390/cells9020506 · Cited by 124 · see citing works
muTarget : A platform linking gene expression changes and mutation status in solid tumors
Nagy, Á. M., & Győrffy, B. (2020) · International Journal of Cancer · doi:10.1002/ijc.33283 · Cited by 124 · see citing works
Host-Directed Therapies for Tuberculosis: Figure 1.Preprint
Tobin, D. M. (2015) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a021196 · Cited by 119 · see citing works
Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning
Wildenhain, J., Spitzer, M., Dolma, S., Jarvik, N., White, R., Roy, M. M., Griffiths, E., Bellows, D. S., Wright, G. D., & Tyers, M. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.003 · Cited by 122 · see citing works
Strategic Approaches to Improvise Peptide Drugs as Next Generation Therapeutics
Barman, P., Joshi, S., Sharma, S., Preet, S., Sharma, S., & Saini, A. (2023) · International Journal of Peptide Research and Therapeutics · doi:10.1007/s10989-023-10524-3 · Cited by 122 · see citing works
SZDB: A Database for Schizophrenia Genetic Research
Wu, Y., Yao, Y., & Luo, X. (2016) · Schizophrenia Bulletin · doi:10.1093/schbul/sbw102 · Cited by 113 · see citing works
Rahmati, S., Abovsky, M., Pastrello, C., & Jurišica, I. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1082 · Cited by 118 · see citing works
Heifetz, A., Chudyk, E. I., Gleave, L., Aldeghi, M., Cherezov, V., Fedorov, D. G., Biggin, P. C., & Bodkin, M. J. (2015) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5b00644 · Cited by 116 · see citing works
Soluble ligands as drug targets
Attwood, M. M., Jonsson, J., Rask‐Andersen, M., & Schiöth, H. B. (2020) · Nature Reviews Drug Discovery · doi:10.1038/s41573-020-0078-4 · Cited by 110 · see citing works
Self-citationGi/o-Protein Coupled Receptors in the Aging Brain
de Oliveira, P. G., Ramos, M. L., Amaro, A. J. M., Dias, R. A., & Vieira, S. I. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00089 · Cited by 106 · see citing works
Disciplined approach to drug discovery and early development
Plenge, R. M. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aaf2608 · Cited by 100 · see citing works
The impact of in silico screening in the discovery of novel and safer drug candidates
Rognan, D. (2017) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2017.02.034 · Cited by 99 · see citing works
Opportunities and guidelines for discovery of orally absorbed drugs in beyond rule of 5 space
Poongavanam, V., Doak, B. C., & Kihlberg, J. O. (2018) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2018.05.010 · Cited by 98 · see citing works
HDX-MS guided drug discovery: small molecules and biopharmaceuticals
Marciano, D. P., Dharmarajan, V., & Griffin, P. R. (2014) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2014.08.007 · Cited by 97 · see citing works
Chassagne, F., Cabanac, G., Hubert, G., David, B., & Marti, G. (2019) · Phytochemistry Reviews · doi:10.1007/s11101-019-09606-2 · Cited by 96 · see citing works
Zheng, P., Li, J., & Kros, J. M. (2017) · Medicinal Research Reviews · doi:10.1002/med.21463 · Cited by 97 · see citing works
Poongavanam, V., Danelius, E., Peintner, S., Alcaraz, L., Caron, G., Cummings, M. D., Wlodek, S. T., Erdélyi, M., Hawkins, P. C. D., Ermondi, G., et al. (2018) · ACS Omega · doi:10.1021/acsomega.8b01379 · Cited by 92 · see citing works
Targeting the schizophrenia genome: a fast track strategy from GWAS to clinic
Lencz, T., & Malhotra, A. K. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.28 · Cited by 91 · see citing works
Intracellular Transfer of Na+ in an Active-State G-Protein-Coupled Receptor
Vickery, O. N., Carvalheda, C. A., Zaidi, S. A., Pisliakov, A. V., Katritch, V., & Zachariae, U. (2017) · Structure · doi:10.1016/j.str.2017.11.013 · Cited by 86 · see citing works
Synaptic changes induced by melanocortin signalling
Caruso, V., Lagerström, M. C., Olszewski, P. K., Fredriksson, R., & Schiöth, H. B. (2014) · Nature reviews. Neuroscience · doi:10.1038/nrn3657 · Cited by 89 · see citing works
Self-citationMiller, R. L., Thompson, A. A., Trapella, C., Guerrini, R., Malfacini, D., Patel, N., Han, G. W., Cherezov, V., Calò, G., Katritch, V., et al. (2015) · Structure · doi:10.1016/j.str.2015.07.024 · Cited by 81 · see citing works
Understanding Membrane Protein Drug Targets in Computational Perspective
Gong, J., Chen, Y., Pu, F., Sun, P., He, F., Zhang, L., Li, Y., Ma, Z., & Wang, H. (2018) · Current Drug Targets · doi:10.2174/1389450120666181204164721 · Cited by 79 · see citing works
Diallinas, G. (2014) · Frontiers in Pharmacology · doi:10.3389/fphar.2014.00207 · Cited by 75 · see citing works
In vitro expression and analysis of the 826 human G protein-coupled receptors
Lv, X., Liu, J., Shi, Q., Tan, Q., Wu, D., Skinner, J. J., Walker, A. L., Zhao, L., Gu, X.-X., Chen, N., et al. (2016) · Protein & Cell · doi:10.1007/s13238-016-0263-8 · Cited by 72 · see citing works
Bondarev, A. D., Attwood, M. M., Jonsson, J., Chubarev, V. N., Tarasov, V. V., Liu, W., & Schiöth, H. B. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.1057083 · Cited by 73 · see citing works
Self-citationComputational design of thermostabilizing point mutations for G protein-coupled receptors
Popov, P. A., Peng, Y., Shen, L., Stevens, R. C., Cherezov, V., Liu, Z., & Katritch, V. (2018) · eLife · doi:10.7554/elife.34729 · Cited by 71 · see citing works
Cardoso, R. V., Pereira, P. R., Freitas, C. S., & Paschoalin, V. M. F. (2022) · Pharmaceutics · doi:10.3390/pharmaceutics14122808 · Cited by 69 · see citing works
Insel, P. A., Wilderman, A. S., Zambon, A. C., Snead, A. N., Murray, F., Aroonsakool, N., McDonald, D., Zhou, S. M., McCann, T., Zhang, L., et al. (2015) · Molecular Pharmacology · doi:10.1124/mol.115.098129 · Cited by 66 · see citing works
HTS-compatible FRET-based conformational sensors clarify membrane receptor activation
Scholler, P., Moreno‐Delgado, D., Lecat‐Guillet, N., Doumazane, E., Monnier, C., Charrier‐Savournin, F., Fabre, L., Chouvet, C., Soldevila, S., Lamarque, L., et al. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2286 · Cited by 66 · see citing works
Orphan Drugs and Their Impact on Pharmaceutical Development
Attwood, M. M., Rask‐Andersen, M., & Schiöth, H. B. (2018) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2018.03.003 · Cited by 66 · see citing works
Self-citationDiscovery and Characterization of Novel GPR39 Agonists Allosterically Modulated by Zinc
Sato, S., Huang, X., Kroeze, W. K., & Roth, B. L. (2016) · Molecular Pharmacology · doi:10.1124/mol.116.106112 · Cited by 61 · see citing works
Histone deacetylases and their inhibitors in inflammatory diseases
Zhang, S.-Y., Zhang, L., Wen, R., Yang, N., & Zhang, T. (2024) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2024.117295 · Cited by 62 · see citing works
Integrating structural and mutagenesis data to elucidate GPCR ligand binding
Munk, C., Harpsøe, K., Hauser, A. S., Ísberg, V., & Gloriam, D. E. I. (2016) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2016.07.003 · Cited by 55 · see citing works
Schröder, M., Bullock, A. N., Fedorov, O., Bracher, F., Chaikuad, A., & Knapp, S. (2020) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.0c00898 · Cited by 55 · see citing works
Recent advances in screening of enzymes inhibitors based on capillary electrophoresis
Cheng, M., & Chen, Z. (2018) · Journal of Pharmaceutical Analysis · doi:10.1016/j.jpha.2018.05.002 · Cited by 53 · see citing works
Molecular assembly of rhodopsin with G protein-coupled receptor kinases
He, Y., Gao, X., Goswami, D., Hou, L., Pal, K., Yin, Y., Zhao, G., Ernst, O. P., Griffin, P. R., Melcher, K., et al. (2017) · Cell Research · doi:10.1038/cr.2017.72 · Cited by 52 · see citing works
Kopra, K., Vuorinen, E., Blanco, M. A., Wang, Q., Eskonen, V., Gillette, W., Pulliainen, A. T., Holderfield, M. T., & Härmä, H. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.9b05126 · Cited by 52 · see citing works
Advances in Capillary Electrophoresis-Based Enzyme Assays
Scriba, G. K. E., & Belal, F. F. (2015) · Chromatographia · doi:10.1007/s10337-015-2912-0 · Cited by 52 · see citing works
Integrating phosphoproteomics into kinase-targeted cancer therapies in precision medicine
Wu, X., Xing, X., Dowlut, D., Zeng, Y., Liu, J., & Liu, X. (2018) · Journal of Proteomics · doi:10.1016/j.jprot.2018.03.033 · Cited by 49 · see citing works
Hampel, H. J., Vergallo, A., Caraci, F., Cuello, A. C., Lemercier, P., Vellas, B. J., Giudici, K. V., Baldacci, F., Hänisch, B., Haberkamp, M., et al. (2020) · Neuropharmacology · doi:10.1016/j.neuropharm.2020.108081 · Cited by 50 · see citing works
Wu, M., Sirota, M., Butte, A., & Chen, B. (2014) · Pacific Symposium on Biocomputing · doi:10.1142/9789814644730_0008 · Cited by 55 · see citing works
Andradas, C., Blasco-Benito, S., Castillo‐Lluva, S., Dillenburg-Pilla, P., Dı́ez-Alarcia, R., Juanes-García, A., García-Taboada, E., Hernando-Llorente, R., Soriano, J., Hamann, S., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.10206 · Cited by 50 · see citing works
Rinken, A., Lavõgina, D., & Kopanchuk, S. (2017) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2017.10.004 · Cited by 49 · see citing works
Survey of Similarity-Based Prediction of Drug-Protein Interactions
Wang, C., & Kurgan, L. (2019) · Current Medicinal Chemistry · doi:10.2174/0929867326666190808154841 · Cited by 49 · see citing works
Hampel, H. J., Goetzl, E. J., Kapogiannis, D., Lista, S., & Vergallo, A. (2019) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.00310 · Cited by 47 · see citing works
Rajakumara, E., Abhishek, S., Nitin, K., Saniya, D., Bajaj, P., Schwaneberg, U., & Davari, M. D. (2022) · ACS Chemical Biology · doi:10.1021/acschembio.1c00500 · Cited by 49 · see citing works
Smith, N. J. (2015) · Frontiers in Pharmacology · doi:10.3389/fphar.2015.00275 · Cited by 47 · see citing works
Wang, C., Hu, G., Wang, K., Bryliński, M., Xie, L., & Kurgan, L. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv597 · Cited by 47 · see citing works
Woolford, C. A., Lagree, K., Xu, W., Aleynikov, T., Adhikari, H., Sánchez, H., Cullen, P. J., Lanni, F., Andes, D. R., & Mitchell, A. P. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1006487 · Cited by 46 · see citing works
Structural and Functional View of Polypharmacology
Moya‐García, A. A., Adeyelu, T. T., Krüger, F. A., Dawson, N. L., Lees, J., Overington, J. P., Orengo, C. A., & Ranea, J. A. G. (2017) · Scientific Reports · doi:10.1038/s41598-017-10012-x · Cited by 44 · see citing works
Systematic illumination of druggable genes in cancer genomes
Jiang, J., Yuan, J., Hu, Z., Zhang, Y., Zhang, T., Xu, M., Long, M., Fan, Y., Tanyi, J. L., Montone, K. T., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110400 · Cited by 46 · see citing works
Seo, Y., Kim, Y. S., Lee, K. E., Park, T. H., & Kim, Y. (2017) · PLoS ONE · doi:10.1371/journal.pone.0176851 · Cited by 45 · see citing works
Recent Advances in Effect‐directed Enzyme Assays based on Thin‐layer Chromatography
Bräm, S., & Wolfram, E. (2017) · Phytochemical Analysis · doi:10.1002/pca.2669 · Cited by 43 · see citing works
Immobilized‐enzyme reactors integrated with capillary electrophoresis for pharmaceutical research
Schejbal, J., & Glatz, Z. (2017) · Journal of Separation Science · doi:10.1002/jssc.201700905 · Cited by 43 · see citing works
Alsultan, A., Alghamdi, W. A., Alghamdi, J., Alharbi, A., Aljutayli, A., Albassam, A. A., Almazroo, O. A., & Alqahtani, S. (2020) · Saudi Pharmaceutical Journal · doi:10.1016/j.jsps.2020.08.012 · Cited by 40 · see citing works
Dynamic protein interfaces and conformational landscapes of membrane protein complexes
Kharche, S., & Sengupta, D. (2020) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2020.01.001 · Cited by 37 · see citing works
New Approaches to Difficult Drug Targets: The Phosphatase Story
Lazo, J. S., McQueeney, K. E., & Sharlow, E. R. (2017) · SLAS DISCOVERY · doi:10.1177/2472555217721142 · Cited by 36 · see citing works
Bolgár, B., & Antal, P. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1845-z · Cited by 36 · see citing works
Mutowo, P., Bento, A. P., Dedman, N., Gaulton, A., Hersey, A., Lomax, J., & Overington, J. P. (2016) · Journal of Biomedical Semantics · doi:10.1186/s13326-016-0102-0 · Cited by 36 · see citing works
NMR analysis of GPCR conformational landscapes and dynamics
Casiraghi, M., Point, É., Pozza, A., Moncoq, K., Banères, J., & Catoire, L. J. (2019) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2018.12.019 · Cited by 36 · see citing works
- Authors
- Rask-Andersen, M., Masuram, S., & Schiöth, H. B.
- Affiliations
- Department of Neuroscience and Uppsala Biomedical Center, Uppsala University, 75124 Uppsala, Sweden;
- Uppsala Monitoring Centre (SE)
- Uppsala University (SE)
- ORCID
- Schiöth, Helgi B.
- Venue
- Annual Review of Pharmacology and Toxicology
- Publisher
- Annual Reviews
- Published
- 2014-01-06
- Volume
- 54
- Issue
- 1
- Pages
- 9-26
- ISSN
- 0362-1642 (ISSN-L)
- 1545-4304
- OpenAlex
- W2147241078
- Cited by
- 282
- References
- 35
- Citations by year
- 2026: 6 · 2025: 14 · 2024: 12 · 2023: 23 · 2022: 23 · 2021: 25 · 2020: 25 · 2019: 22 · 2018: 22 · 2017: 34 · 2016: 34 · 2015: 27 · 2014: 13 · 2013: 2
- FWCI
- 2.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Annual Review of Pharmacology and Toxicology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Vetenskapsrådet
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Keywords
- druggable genome, therapeutic target, new drug development, human proteome, treatment indications, drug development trends, DrugBank
- MeSH terms
- Alzheimer Disease, Anti-Inflammatory Agents, Antineoplastic Agents, Appetite Regulation, Clinical Trials as Topic, Evaluation Studies as Topic, Humans, Hypoglycemic Agents, Genome, Human, Databases, Factual, Proteome, G-Protein-Coupled Receptor Kinases, Molecular Targeted Therapy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review