Structures of the σ2 receptor enable docking for bioactive ligand discovery
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Abstract
The σ 2 receptor has attracted intense interest in cancer imaging 1, psychiatric disease 2, neuropathic pain 3-5 and other areas of biology 6,7. Here we determined the crystal structure of this receptor in complex with the clinical candidate roluperidone 2 and the tool compound PB28 8. These structures templated a large-scale docking screen of 490 million virtual molecules, of which 484 compounds were synthesized and tested. We identified 127 new chemotypes with affinities superior to 1 μM, 31 of which had affinities superior to 50 nM. The hit rate fell smoothly and monotonically with docking score. We optimized three hits for potency and selectivity, and achieved affinities that ranged from 3 to 48 nM, with up to 250-fold selectivity versus the σ 1 receptor. Crystal structures of two ligands bound to the σ 2 receptor confirmed the docked poses. To investigate the contribution of the σ 2 receptor in pain, two potent σ 2-selective ligands and one potent σ 1/σ 2 non-selective ligand were tested for efficacy in a mouse model of neuropathic pain. All three ligands showed time-dependent decreases in mechanical hypersensitivity in the spared nerve injury model 9, suggesting that the σ 2 receptor has a role in nociception. This study illustrates the opportunities for rapid discovery of in vivo probes through structure-based screens of ultra large libraries, enabling study of underexplored areas of biology.
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Cites
UCSF Chimera—A visualization system for exploratory research and analysis
Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20084 · Cited by 45,260 · see citing works
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Wickham, H. (2016) · Use R! · doi:10.1007/978-3-319-24277-4 · Cited by 33,612 · see citing works
[20] Processing of X-ray diffraction data collected in oscillation mode
Otwinowski, Z., & Minor, W. (1997) · Methods in Enzymology · doi:10.1016/s0076-6879(97)76066-x · Cited by 33,475 · see citing works
Features and development of Coot
Emsley, P., Lohkamp, B., Scott, W. G., & Cowtan, K. D. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444910007493 · Cited by 27,510 · see citing works
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., et al. (2019) · Journal of Open Source Software · doi:10.21105/joss.01686 · Cited by 22,138 · see citing works
<i>Phaser</i> crystallographic software
McCoy, A. J., Grosse-Kunstleve, R. W., Adams, P. D., Winn, M. D., Storoni, L. C., & Read, R. J. (2007) · Journal of Applied Crystallography · doi:10.1107/s0021889807021206 · Cited by 20,612 · see citing works
Kabsch, W. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909047337 · Cited by 16,463 · see citing works
NMRPipe: A multidimensional spectral processing system based on UNIX pipes
Delaglio, F., Grzesiek, S., Vuister, G. W., Zhu, G., Pfeifer, J., & Bax, A. (1995) · Journal of Biomolecular NMR · doi:10.1007/bf00197809 · Cited by 15,994 · see citing works
Wickham, H. (2016) · Use R! · doi:10.1007/978-3-319-24277-4_9 · Cited by 12,675 · see citing works
<b>brms</b> : An <i>R</i> Package for Bayesian Multilevel Models Using <i>Stan</i>
Bürkner, P.-C. (2017) · Journal of Statistical Software · doi:10.18637/jss.v080.i01 · Cited by 9,476 · see citing works
<i>Stan</i> : A Probabilistic Programming Language
Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., & Riddell, A. (2017) · Journal of Statistical Software · doi:10.18637/jss.v076.i01 · Cited by 7,754 · see citing works
Quantitative assessment of tactile allodynia in the rat paw
Chaplan, S. R., Bach, F. W., Pogrel, J. W., Chung, J. M., & Yaksh, T. L. (1994) · Journal of Neuroscience Methods · doi:10.1016/0165-0270(94)90144-9 · Cited by 7,740 · see citing works
T-Coffee: A novel method for fast and accurate multiple sequence alignment.
Notredame, C., Higgins, D., & Heringa, J. (2000) · Journal of Molecular Biology · doi:10.1006/jmbi.2000.4042 · Cited by 7,321 · see citing works
Liebschner, D. C., Afonine, P. V., Baker, M. L., Bunkòczi, G., Chen, V. B., Croll, T. I., Hintze, B. J., Hung, L., Jain, S., McCoy, A. J., et al. (2019) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798319011471 · Cited by 6,709 · see citing works
A new force field for molecular mechanical simulation of nucleic acids and proteins
Weiner, S. J., Kollman, P. A., Case, D. A., Singh, U. C., Ghio, C., Alagona, G., Profeta, S., & Weiner, P. K. (1984) · Journal of the American Chemical Society · doi:10.1021/ja00315a051 · Cited by 4,641 · see citing works
A SARS-CoV-2 protein interaction map reveals targets for drug repurposing
Gordon, D. E., Jang, G. M., Bouhaddou, M., Xu, J., Obernier, K., White, K. M., O’Meara, M. J., Rezelj, V. V., Guo, J. Z., Swaney, D. L., et al. (2020) · Nature · doi:10.1038/s41586-020-2286-9 · Cited by 4,405 · see citing works
Self-citationA Completely Reimplemented MPI Bioinformatics Toolkit with a New HHpred Server at its Core
Zimmermann, L., Stephens, A., Nam, S.-Z., Rau, D., Kübler, J., Lozajic, M., Gabler, F., Söding, J., Lupas, A. N., & Alva, V. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2017.12.007 · Cited by 2,522 · see citing works
OPM database and PPM web server: resources for positioning of proteins in membranes
Lomize, M. A., Pogozheva, I. D., Joo, H., Mosberg, H. I., & Lomize, A. L. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr703 · Cited by 2,176 · see citing works
Crystal structure of the µ-opioid receptor bound to a morphinan antagonist
Manglik, A., Kruse, A. C., Kobilka, T. S., Thian, F. S., Mathiesen, J. M., Sunahara, R. K., Pardo, L., Weis, W. I., Kobilka, B. K., & Granier, S. (2012) · Nature · doi:10.1038/nature10954 · Cited by 1,362 · see citing works
Self-citationUltra-large library docking for discovering new chemotypes
Lyu, J., Wang, S., Balius, T. E., Singh, I., Levit, A., Moroz, Y. S., O’Meara, M. J., Che, T., Algaa, E., Tolmachova, K., et al. (2019) · Nature · doi:10.1038/s41586-019-0917-9 · Cited by 998 · see citing works
Self-citationAutomated docking with grid‐based energy evaluation
Meng, E. C., Shoichet, B. K., & Kuntz, I. D. (1992) · Journal of Computational Chemistry · doi:10.1002/jcc.540130412 · Cited by 956 · see citing works
Self-citationR-squared for Bayesian Regression Models
Gelman, A., Goodrich, B., Gabry, J., & Vehtari, A. (2018) · The American Statistician · doi:10.1080/00031305.2018.1549100 · Cited by 924 · see citing works
Purification, molecular cloning, and expression of the mammalian sigma1-binding site.
Hanner, M., Moebius, F. F., Flandorfer, A., Knaus, H. G., Striessnig, J., Kempner, E. S., & Glossmann, H. H. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.15.8072 · Cited by 918 · see citing works
Automated design of ligands to polypharmacological profiles
Besnard, J., Ruda, G. F., Setola, V., Abecassis, K., Rodriguiz, R. M., Huang, X.-P., Norval, S., Sassano, M. F., Shin, A. I., Webster, L. A., et al. (2012) · Nature · doi:10.1038/nature11691 · Cited by 832 · 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
Self-citationCrystallizing membrane proteins using lipidic mesophases
Caffrey, M., & Cherezov, V. (2009) · Nature Protocols · doi:10.1038/nprot.2009.31 · Cited by 673 · see citing works
Polder maps: improving OMIT maps by excluding bulk solvent
Liebschner, D. C., Afonine, P. V., Moriarty, N. W., Poon, B. K., Sobolev, O. V., Terwilliger, T. C., & Adams, P. D. (2017) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798316018210 · Cited by 670 · 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
Transient Mammalian Cell Transfection with Polyethylenimine (PEI)
Longo, P. A., Kavran, J. M., Kim, S. K., & Leahy, D. J. (2013) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-418687-3.00018-5 · Cited by 590 · see citing works
Structure of the D2 dopamine receptor bound to the atypical antipsychotic drug risperidone
Wang, S., Che, T., Levit, A., Shoichet, B. K., Wacker, D., & Roth, B. L. (2018) · Nature · doi:10.1038/nature25758 · Cited by 487 · see citing works
Self-citationSigma-1 and sigma-2 receptors are expressed in a wide variety of human and rodent tumor cell lines.
Vilner, B. J., John, C. S., & Bowen, W. D. (1995) · PubMed · Cited by 484 · see citing works
Crystal structure of the human σ1 receptor
Schmidt, H. R., Zheng, S., Gurpinar, E., Koehl, A., Manglik, A., & Kruse, A. C. (2016) · Nature · doi:10.1038/nature17391 · Cited by 482 · see citing works
Self-citationDissociation of the Opioid Receptor Mechanisms that Control Mechanical and Heat Pain
Scherrer, G., Imamachi, N., Cao, Y. Q., Contet, C., Mennicken, F., O’Donnell, D., Kieffer, B. L., & Basbaum, A. I. (2009) · Cell · doi:10.1016/j.cell.2009.04.019 · Cited by 463 · see citing works
Self-citationHellewell, S. B., Bruce, A., Feinstein, G. I., Orringer, J. S., Williams, W. C., & Bowen, W. D. (1994) · European Journal of Pharmacology Molecular Pharmacology · doi:10.1016/0922-4106(94)90115-5 · Cited by 438 · see citing works
Hellewell, S. B., & Bowen, W. D. (1990) · Brain Research · doi:10.1016/0006-8993(90)91143-5 · Cited by 390 · see citing works
Impact of GPCR Structures on Drug Discovery
Congreve, M., de Graaf, C., Swain, N. A., & Tate, C. G. (2020) · Cell · doi:10.1016/j.cell.2020.03.003 · Cited by 380 · see citing works
Mahdessian, H., Taxiarchis, A., Popov, S., Silveira, A., Franco-Cereceda, A., Hamsten, A., Eriksson, P., & van't Hooft, F. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1323785111 · Cited by 369 · see citing works
GPCRdb in 2021: integrating GPCR sequence, structure and function
Kooistra, A. J., Mordalski, S., Pándy-Szekeres, G., Esguerra, M., Mamyrbekov, A., Munk, C., Keserű, G. M., & Gloriam, D. E. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1080 · Cited by 351 · see citing works
Rapid Context-Dependent Ligand Desolvation in Molecular Docking
Mysinger, M. M., & Shoichet, B. K. (2010) · Journal of Chemical Information and Modeling · doi:10.1021/ci100214a · Cited by 323 · see citing works
Self-citationSpared nerve injury model of neuropathic pain in the mouse: a behavioral and anatomic analysis
Shields, S. D., Eckert, W. A., & Basbaum, A. I. (2003) · Journal of Pain · doi:10.1067/s1526-5900(03)00781-8 · Cited by 322 · see citing works
Self-citationVirtual discovery of melatonin receptor ligands to modulate circadian rhythms
Stein, R. M., Kang, H. J., McCorvy, J. D., Glatfelter, G. C., Jones, A., Che, T., Slocum, S. T., Huang, X., Savych, O., Moroz, Y. S., et al. (2020) · Nature · doi:10.1038/s41586-020-2027-0 · Cited by 306 · see citing works
Self-citationAllosteric ligands for the pharmacologically dark receptors GPR68 and GPR65
Huang, X.-P., Karpiak, J., Kroeze, W. K., Zhu, H., Chen, X., Moy, S. S., Saddoris, K. A., Nikolova, V. D., Farrell, M. S., Wang, S., et al. (2015) · Nature · doi:10.1038/nature15699 · Cited by 284 · see citing works
Self-citationtidybayes: Tidy Data and Geoms for Bayesian Models
Kay, M. (2018) · Figshare · doi:10.5281/zenodo.1308151 · Cited by 283 · see citing works
Identification of the gene that codes for the σ 2 receptor
Alon, A., Schmidt, H. R., Wood, M. D., Sahn, J. J., Martin, S. F., & Kruse, A. C. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705154114 · Cited by 275 · see citing works
Self-citationDecision Making in Structure-Based Drug Discovery: Visual Inspection of Docking Results
Fischer, A., Smieško, M., Sellner, M. S., & Lill, M. A. (2021) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.0c02227 · Cited by 243 · see citing works
Structure-Based Discovery of A 2A Adenosine Receptor Ligands
Carlsson, J., Yoo, L. S., Gao, Z.-G., Irwin, J. J., Shoichet, B. K., & Jacobson, K. A. (2010) · Journal of Medicinal Chemistry · doi:10.1021/jm100240h · Cited by 229 · see citing works
Self-citationAccumulation of 8,9-unsaturated sterols drives oligodendrocyte formation and remyelination
Hubler, Z., Allimuthu, D., Bederman, I., Elitt, M. S., Madhavan, M., Allan, K. C., Shick, H. E., Garrison, E., T. Karl, M., Factor, D. C., et al. (2018) · Nature · doi:10.1038/s41586-018-0360-3 · Cited by 226 · see citing works
Identification of Cholesterol-Regulating Genes by Targeted RNAi Screening
Bartz, F., Kern, L., Erz, D., Zhu, M., Gilbert, D., Meinhof, T., Wirkner, U., Erfle, H., Muckenthaler, M., Pepperkok, R., et al. (2009) · Cell Metabolism · doi:10.1016/j.cmet.2009.05.009 · Cited by 198 · see citing works
Schuller, M., Correy, G. J., Gahbauer, S., Fearon, D., Wu, T., Díaz, R. E., Young, I. D., Martins, L. C., Smith, D. H., Schulze‐Gahmen, U., et al. (2021) · Science Advances · doi:10.1126/sciadv.abf8711 · Cited by 195 · see citing works
Self-citationGeneration and phenotypic analysis of sigma receptor type I (σ1) knockout mice
Vives, F. L., Codony, X., Tovar, V., Lavado, A., Giménez, E., Cozar, P., Cantero, M., Dordal, A., Hernández, E., Pérez-Gómez, R., et al. (2003) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2003.02950.x · Cited by 189 · see citing works
Romero, L. I., Zamanillo, D., Nadal, X., Sánchez-Arroyos, R., Rivera‐Arconada, I., Dordal, A., Montero, A., Muro, A., Bura, A., Segalés, C., et al. (2012) · British Journal of Pharmacology · doi:10.1111/j.1476-5381.2012.01942.x · Cited by 185 · see citing works
The Molecular Function of σ Receptors: Past, Present, and Future
Schmidt, H. R., & Kruse, A. C. (2019) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2019.07.006 · Cited by 176 · see citing works
Self-citationAdvances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges
Kufareva, I., Katritch, V., Stevens, R., & Abagyan, R. (2014) · Structure · doi:10.1016/j.str.2014.06.012 · Cited by 167 · see citing works
de la Puente, B., Nadal, X., Portillo-Salido, E. F., Sánchez-Arroyos, R., Ovalle, S., Palacios, G., Muro, A., Romero, L. I., Entrena, J. M., Baeyens, J. M., et al. (2009) · Pain · doi:10.1016/j.pain.2009.05.013 · Cited by 166 · see citing works
Potential applications for sigma receptor ligands in cancer diagnosis and therapy
van Waarde, A., Rybczynska, A. A., Ramakrishnan, N. K., Ishiwata, K., Elsinga, P. H., & Dierckx, R. (2014) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/j.bbamem.2014.08.022 · Cited by 156 · see citing works
An Integrated Framework Advancing Membrane Protein Modeling and Design
Alford, R. F., Leman, J. K., Weitzner, B. D., Duran, A. M., Tilley, D. C., Elazar, A., & Gray, J. J. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004398 · Cited by 151 · see citing works
Riad, A., Zeng, C., Weng, C.-C., Winters, H. D., Xu, K., Makvandi, M., Metz, T., Carlin, S., & Mach, R. H. (2018) · Scientific Reports · doi:10.1038/s41598-018-35430-3 · Cited by 144 · see citing works
Formalin-induced pain is reduced in σ1 receptor knockout mice
Cendán, C. M., Pujalte, J. M., Portillo-Salido, E. F., Montoliu, L., & Baeyens, J. M. (2005) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2005.01.036 · Cited by 141 · see citing works
Property-Unmatched Decoys in Docking Benchmarks
Stein, R. M., Ying, Y., Balius, T. E., O’Meara, M. J., Lyu, J., Young, J., Tang, K. G., Shoichet, B. K., & Irwin, J. J. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c00598 · Cited by 136 · see citing works
Self-citationElectrostatic Contributions to Heat Capacity Changes of DNA-Ligand Binding
Gallagher, K., & Sharp, K. A. (1998) · Biophysical Journal · doi:10.1016/s0006-3495(98)77566-6 · Cited by 135 · see citing works
Exploiting Ordered Waters in Molecular Docking
Huang, N., & Shoichet, B. K. (2008) · Journal of Medicinal Chemistry · doi:10.1021/jm8006239 · Cited by 129 · see citing works
Self-citationBruna, J., Videla, S., Argyriou, A. A., Velasco, R., Villoria, J., Santos, C., Nadal, C., Cavaletti, G., Alberti, P., Briani, C., et al. (2017) · Neurotherapeutics · doi:10.1007/s13311-017-0572-5 · Cited by 124 · see citing works
Azzariti, A., Colabufo, N. A., Berardi, F., Porcelli, L., Niso, M., Simone, G. M., Perrone, R., & Paradiso, A. (2006) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-05-0402 · Cited by 112 · see citing works
Grundman, M., Morgan, R. E., Lickliter, J. D., Schneider, L. S., DeKosky, S. T., Izzo, N. J., Guttendorf, R. J., Higgin, M., Pribyl, J., Mozzoni, K., et al. (2018) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1016/j.trci.2018.11.001 · Cited by 111 · see citing works
Davidson, M., Saoud, J. B., Staner, C., Noël, N., Luthringer, E., Werner, S., Reilly, J. G., Schaffhauser, J.-Y., Rabinowitz, J., Weiser, M., et al. (2017) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2017.17010122 · Cited by 104 · see citing works
Sigma 2 Receptor/Tmem97 Agonists Produce Long Lasting Antineuropathic Pain Effects in Mice
Sahn, J. J., Mejia, G. L., Ray, P. R., Martin, S. F., & Price, T. J. (2017) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.7b00200 · Cited by 100 · see citing works
Ebrahimi‐Fakhari, D., Wahlster, L., Bartz, F., Werenbeck-Ueding, J., Praggastis, M., Zhang, J., Joggerst-Thomalla, B., Theiß, S., Grimm, D., Ory, D. S., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw204 · Cited by 98 · see citing works
Solórzano, C., Villafuerte, D. B., Meda, K., Cevikbas, F., Braz, J. M., Sharif‐Naeini, R., Juarez-Salinas, D. L., Llewellyn‐Smith, I. J., Guan, Z., & Basbaum, A. I. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.2955-14.2015 · Cited by 89 · see citing works
Self-citationAntinociceptive effects of haloperidol and its metabolites in the formalin test in mice
Cendán, C. M., Pujalte, J. M., Portillo-Salido, E. F., & Baeyens, J. M. (2005) · Psychopharmacology · doi:10.1007/s00213-005-0127-z · Cited by 87 · see citing works
Negri, A., Rives, M., Caspers, M. J., Prisinzano, T. E., Javitch, J. A., & Filizola, M. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400019t · Cited by 65 · see citing works
Structural basis for human sterol isomerase in cholesterol biosynthesis and multidrug recognition
Long, T., Hassan, A., Thompson, B. M., McDonald, J. G., Wang, J., & Li, X. (2019) · Nature Communications · doi:10.1038/s41467-019-10279-w · Cited by 65 · see citing works
Vázquez‐Rosa, E., Watson, M. R., Sahn, J. J., Hodges, T. R., Schroeder, R. E., Cintrón-Pérez, C. J., Shin, M., Yin, T. C., Emery, J. L., Martin, S. F., et al. (2018) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.8b00543 · Cited by 65 · see citing works
TM6SF2 and MAC30, new enzyme homologs in sterol metabolism and common metabolic disease
Sanchez-Pulido, L., & Ponting, C. P. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00439 · Cited by 63 · see citing works
Ligand Strain Energy in Large Library Docking
Gu, S., Smith, M. S., Ying, Y., Irwin, J. J., & Shoichet, B. K. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.1c00368 · Cited by 60 · see citing works
Self-citationDocking Screens for Dual Inhibitors of Disparate Drug Targets for Parkinson’s Disease
Jaiteh, M., Zeifman, A. A., Saarinen, M., Svenningsson, P., Brea, J. M., Loza, M. I., & Carlsson, J. (2018) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.8b00204 · Cited by 59 · see citing works
Emerging structural biology of lipid G protein‐coupled receptors
Audet, M., & Stevens, R. C. (2018) · Protein Science · doi:10.1002/pro.3509 · Cited by 55 · see citing works
Investigational sigma-1 receptor antagonists for the treatment of pain
Vela, J. M., Merlos, M., & Almansa, C. (2015) · Expert Opinion on Investigational Drugs · doi:10.1517/13543784.2015.1048334 · Cited by 54 · see citing works
Intagliata, S., Sharma, A., King, T. I., Mésangeau, C., Seminerio, M. J., Chin, F. T., Wilson, L., Matsumoto, R. R., McLaughlin, J. P., Avery, B. A., et al. (2020) · The AAPS Journal · doi:10.1208/s12248-020-00472-x · Cited by 49 · see citing works
Structure-based discovery of potent and selective melatonin receptor agonists
Patel, N., Huang, X., Grandner, J. M., Johansson, L. C., Stauch, B., McCorvy, J. D., Liu, Y., Roth, B. L., & Katritch, V. (2020) · eLife · doi:10.7554/elife.53779 · Cited by 48 · see citing works
Self-citationSelectivity Challenges in Docking Screens for GPCR Targets and Antitargets
Weiss, D. R., Karpiak, J. D., Huang, X., Sassano, M. F., Lyu, J., Roth, B. L., & Shoichet, B. K. (2018) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.8b00718 · Cited by 45 · see citing works
Self-citationSmall molecule modulators of σ2R/Tmem97 reduce alcohol withdrawal-induced behaviors
Scott, L. L., Sahn, J. J., Ferragud, A., Yen, R. C., Satarasinghe, P., Wood, M. D., Hodges, T. R., Shi, T., Prakash, B. A., Friese, K. M., et al. (2018) · Neuropsychopharmacology · doi:10.1038/s41386-018-0067-z · Cited by 42 · see citing works
Schuller, M., Correy, G. J., Gahbauer, S., Fearon, D., Wu, T., Díaz, R. E., Young, I. D., Martins, L. C., Smith, D. H., Schulze‐Gahmen, U., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.24.393405 · Cited by 38 · see citing works
Self-citationCognitive Effects of MIN-101 in Patients With Schizophrenia and Negative Symptoms
Keefe, R. S. E., Harvey, P. D., Khan, A., Saoud, J. B., Staner, C., Davidson, M., & Luthringer, R. (2018) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.17m11753 · Cited by 36 · see citing works
Quadir, S. G., Tanino, S. M., Rohl, C. D., Sahn, J. J., Yao, E. J., Cruz, L. R., Cottone, P., Martin, S. F., & Sabino, V. (2020) · Neuropharmacology · doi:10.1016/j.neuropharm.2020.108409 · Cited by 35 · see citing works
New σ and 5-HT1A Receptor Ligands: ω-(Tetralin-1-yl)-n-alkylamine Derivatives
Berardi, F., Colabufo, N. A., Giudice, G. D., Perrone, R., Tortorella, V., Govoni, S. M., & Lucchi, L. (1996) · Journal of Medicinal Chemistry · doi:10.1021/jm950409c · Cited by 34 · see citing works
Nastasi, G., Miceli, C., Pittalà, V., Modica, M. N., Prezzavento, O., Romeo, G., Rescifina, A., Marrazzo, A., & Amata, E. (2017) · Journal of Cheminformatics · doi:10.1186/s13321-017-0191-5 · Cited by 31 · see citing works
Harvey, P. D., Saoud, J. B., Luthringer, R., Moroz, S., Blazhevych, Y., Ștefănescu, C., & Davidson, M. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.08.029 · Cited by 31 · see citing works
Abate, C., Niso, M., Abatematteo, F. S., Contino, M., Colabufo, N. A., & Berardi, F. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.589810 · Cited by 30 · see citing works
Simplified LC-MS Method for Analysis of Sterols in Biological Samples
Skubic, C., Vovk, I., Rozman, D., & Križman, M. (2020) · Molecules · doi:10.3390/molecules25184116 · Cited by 28 · see citing works
Chu, U. B., & Ruoho, A. E. (2015) · Current Protocols in Pharmacology · doi:10.1002/0471141755.ph0134s71 · Cited by 27 · see citing works
Muralidharan, A., Samoshkin, A., Convertino, M., Piltonen, M., Gris, P., Wang, J., Jiang, C., Klares, R., Linton, A. A., Ji, R., et al. (2021) · British Journal of Pharmacology · doi:10.1111/bph.15463 · Cited by 5 · see citing works
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Computational approaches streamlining drug discovery
Sadybekov, A., & Katritch, V. (2023) · Nature · doi:10.1038/s41586-023-05905-z · Cited by 1,342 · see citing works
A practical guide to large-scale docking
Bender, B. J., Gahbauer, S., Luttens, A., Lyu, J., Webb, C. M., Stein, R. M., Fink, E. A., Balius, T. E., Carlsson, J., Irwin, J. J., et al. (2021) · Nature Protocols · doi:10.1038/s41596-021-00597-z · Cited by 546 · see citing works
Self-citationThe 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 511 · see citing works
ZINC-22─A Free Multi-Billion-Scale Database of Tangible Compounds for Ligand Discovery
Tingle, B. I., Tang, K. G., Castanon, M., Gutierrez, J. J., Khurelbaatar, M., Dandarchuluun, C., Moroz, Y. S., & Irwin, J. J. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.2c01253 · Cited by 314 · see citing works
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Lyu, J., Irwin, J. J., & Shoichet, B. K. (2023) · Nature Chemical Biology · doi:10.1038/s41589-022-01234-w · Cited by 193 · see citing works
Self-citationAlphaFold2 structures guide prospective ligand discovery
Lyu, J., Kapolka, N. J., Gumpper, R. H., Alon, A., Wang, L., Jain, M. K., Barros-Álvarez, X., Sakamoto, K., Kim, Y., DiBerto, J. F., et al. (2024) · Science · doi:10.1126/science.adn6354 · Cited by 182 · see citing works
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Singh, I., Seth, A., Billesbølle, C. B., Bráz, J. M., Rodriguiz, R. M., Roy, K., Bekele, B., Craik, V., Huang, X., Boytsov, D., et al. (2023) · Cell · doi:10.1016/j.cell.2023.04.010 · Cited by 99 · see citing works
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Casey, A. B., Cui, M., Booth, R. G., & Canal, C. E. (2022) · Biochemical Pharmacology · doi:10.1016/j.bcp.2022.115028 · Cited by 94 · see citing works
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Wei, H., & McCammon, J. A. (2024) · npj Drug Discovery. · doi:10.1038/s44386-024-00001-2 · Cited by 94 · see citing works
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Zhu, H., Zhang, Y., Li, W., & Huang, N. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232415961 · Cited by 80 · see citing works
TRPA1 modulation by Sigma-1 receptor prevents oxaliplatin-induced painful peripheral neuropathy
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Cui, Z., Zhang, N., Zhou, T., Zhou, X., Meng, H., Yu, Y., Zhang, Z., Zhang, Y., Wang, W., & Liu, Y. (2023) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.3c00591 · Cited by 66 · see citing works
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Large library docking identifies positive allosteric modulators of the calcium-sensing receptor
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Large library docking for novel SARS‐CoV ‐2 main protease non‐covalent and covalent inhibitors
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Self-citationSystematic Investigation of Docking Failures in Large-Scale Structure-Based Virtual Screening
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The Science and Art of Structure-Based Virtual Screening
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Gryniukova, A., Kaiser, F., Myziuk, I., Alieksieieva, D. O., Leberecht, C., Heym, P. P., Tarkhanova, O. O., Moroz, Y. S., Borysko, P., & Haupt, V. J. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.3c00128 · Cited by 34 · see citing works
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Large-Scale Docking in the Cloud
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Self-citationAssessing Boltz-2 Performance for the Binding Classification of Docking Hits
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Structural enzymology of cholesterol biosynthesis and storage
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Popov, K. I., Wellnitz, J., Maxfield, T., & Tropsha, A. (2023) · Molecular Informatics · doi:10.1002/minf.202300207 · Cited by 29 · see citing works
The Sigma Receptors in Alzheimer’s Disease: New Potential Targets for Diagnosis and Therapy
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Structure-Based Design of a Chemical Probe Set for the 5-HT 5A Serotonin Receptor
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Self-citationDeep Machine Learning for Computer-Aided Drug Design
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Applications of machine learning in computer-aided drug discovery
Turzo, S. B. A., Hantz, E. R., & Lindert, S. (2022) · QRB Discovery · doi:10.1017/qrd.2022.12 · Cited by 29 · see citing works
Cao, D., Zhang, P., & Wang, S. (2024) · Neuron · doi:10.1016/j.neuron.2024.01.004 · Cited by 26 · see citing works
Turgutalp, B., Bhattarai, P., Erçeti̇n, T., Luise, C., Reis, R., Gürdal, E. E., Isaak, A., Biriken, D., Dinter, E., Si̇pahi̇, H., et al. (2022) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.2c01003 · Cited by 26 · see citing works
Wilson, L., Alleyne, A. R., Eans, S. O., Cirino, T. J., Stacy, H. M., Mottinelli, M., Intagliata, S., McCurdy, C. R., & McLaughlin, J. P. (2022) · Molecules · doi:10.3390/molecules27113617 · Cited by 25 · see citing works
Regression-Based Active Learning for Accessible Acceleration of Ultra-Large Library Docking
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σ2 Receptor and Its Role in Cancer with Focus on a MultiTarget Directed Ligand (MTDL) Approach
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Cecchini, D., Nigam, A., Tang, M., Reis, J., Koop, M., Gottinger, A., Nicoll, C. R., Wang, Y., Jayaraj, A., Cinaroglu, S. S., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.25.537981 · Cited by 24 · see citing works
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Edwards, A. M., Owen, D. R., Zhang, L., Young, D. W., Willson, T. M., Wellnitz, J., Wang, Y., Walsh, J. J., Vernet, E., Tropsha, A., et al. (2025) · Nature Reviews Chemistry · doi:10.1038/s41570-025-00737-z · Cited by 26 · see citing works
Moesgaard, L., Pedersen, M. L., Nielsen, C. U., & Kongsted, J. (2023) · Scientific Reports · doi:10.1038/s41598-023-48281-4 · Cited by 23 · see citing works
A Database for Large-Scale Docking and Experimental Results
Hall, B. W., Tummino, T. A., Tang, K. G., Mailhot, O., Castanon, M., Irwin, J. J., & Shoichet, B. K. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c00394 · Cited by 21 · see citing works
Self-citationAn equivariant generative framework for molecular graph-structure Co-design
Zhang, Z., Liu, Q., Lee, C., Hsieh, C., & Chen, E. (2023) · Chemical Science · doi:10.1039/d3sc02538a · Cited by 23 · see citing works
Identifying Artifacts from Large Library Docking
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Self-citationFentanyl Structure as a Scaffold for Opioid/Non-Opioid Multitarget Analgesics
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Balius, T. E., Tan, Y.-H., & Chakrabarti, M. (2023) · Journal of Computational Chemistry · doi:10.1002/jcc.27218 · Cited by 19 · see citing works
On the Difficulty to Rescore Hits from Ultralarge Docking Screens
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Virtual Screening in the Cloud Identifies Potent and Selective ROS1 Kinase Inhibitors
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Exploring the combinatorial explosion of amine–acid reaction space via graph editing
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Protein Structure-Based Organic Chemistry-Driven Ligand Design from Ultralarge Chemical Spaces
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New perspective of small-molecule antiviral drugs development for RNA viruses
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AlphaFold2 structures template ligand discoveryPreprint
Lyu, J., Kapolka, N. J., Gumpper, R. H., Alon, A., Wang, L., Jain, M. K., Barros-Álvarez, X., Sakamoto, K., Kim, Y., DiBerto, J. F., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.20.572662 · Cited by 18 · see citing works
Self-citationAI-Designed Molecules in Drug Discovery, Structural Novelty Evaluation, and Implications
Xie, S., Zhu, H., & Huang, N. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c00921 · Cited by 17 · see citing works
Augmented BindingNet dataset for enhanced ligand binding pose predictions using deep learning
Zhu, H., Li, X., Chen, B., & Huang, N. (2025) · npj Drug Discovery. · doi:10.1038/s44386-024-00003-0 · Cited by 16 · see citing works
Detomasi, T. C., Degotte, G., Huang, S., Suryawanshi, R. K., Diallo, A., Lizzadro, L., Belinchón, F. J. Z., Taha, T. Y., Li, J., Richards, A., et al. (2025) · Science Advances · doi:10.1126/sciadv.adt7836 · Cited by 16 · see citing works
Self-citationKim, H. Y., Lee, J. Y., Hsieh, C., Riad, A., Izzo, N. J., Catalano, S. M., Graham, T. J. A., & Mach, R. H. (2022) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.2c00191 · Cited by 16 · see citing works
Virtual library docking for cannabinoid-1 receptor agonists with reduced side effects
Tummino, T. A., Iliopoulos‐Tsoutsouvas, C., Braz, J. M., O’Brien, E. S., Stein, R. M., Craik, V., Tran, N. K., Ganapathy, S., Liu, F., Shiimura, Y., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-57136-7 · Cited by 25 · see citing works
Self-citationσ2R/TMEM97 in retinal ganglion cell degeneration
Wang, H., Peng, Z., Li, Y., Sahn, J. J., Hodges, T. R., Chou, T., Liu, Q., Zhou, X., Jiao, S., Porciatti, V., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-24537-3 · Cited by 15 · see citing works
Overlap of On‐demand Ultra‐large Combinatorial Spaces with On‐the‐shelf Drug‐like Libraries
Perebyinis, M., & Rognan, D. (2022) · Molecular Informatics · doi:10.1002/minf.202200163 · Cited by 15 · see citing works
Illuminating the understudied GPCR-ome
Majumdar, S., Chiu, Y.-T., Pickett, J. E., & Roth, B. L. (2023) · Drug Discovery Today · doi:10.1016/j.drudis.2023.103848 · Cited by 15 · see citing works
Self-citationRoy, J., Kyani, A., Hanafi, M., Xu, Y., Takyi‐Williams, J., Sun, D., Osman, E. E. A., & Neamati, N. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.2c01769 · Cited by 14 · see citing works
Xing, J., Tan, M., Leshchiner, D. R., Sun, M., Abdelgied, M., Huang, L., Paithankar, S., Uhl, K. L., Shankar, R., Lisabeth, E. M., et al. (2026) · Cell · doi:10.1016/j.cell.2026.02.016 · Cited by 18 · see citing works
Adamantane-derived scaffolds targeting the sigma-2 receptor; an in vitro and in silico study
Alamri, M. A., & Alamri, M. A. (2021) · Saudi Pharmaceutical Journal · doi:10.1016/j.jsps.2021.08.016 · Cited by 13 · see citing works
Discovery of AD258 as a Sigma Receptor Ligand with Potent Antiallodynic Activity
Dichiara, M., Ambrosio, F. A., Lee, S., Ruiz‐Cantero, M. C., Lombino, J., Coricello, A., Costa, G., Shah, D., Costanzo, G., Pasquinucci, L., et al. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.3c00959 · Cited by 13 · see citing works
Ye, N., Wang, Q., Li, Y., & Zhen, X. (2024) · Medicinal Research Reviews · doi:10.1002/med.22086 · Cited by 17 · see citing works
Martin, S. F. (2022) · Accounts of Chemical Research · doi:10.1021/acs.accounts.1c00773 · Cited by 13 · see citing works
Li, J., Félix‐Soriano, E., Wright, K. R., Shen, H., Baer, L. A., Stanford, K. I., & Guo, L. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231810846 · Cited by 13 · see citing works
Conformationally Restricted σ1 Receptor Antagonists from (−)-Isopulegol
Blicker, L., González‐Cano, R., Laurini, E., Nieto, F. R., Schmidt, J., Schepmann, D., Pricl, S., & Wünsch, B. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.2c02081 · Cited by 11 · see citing works
Hong, V. M., Rade, A., Yan, S. M., Bhaskara, A., Yousuf, M. S., Chen, M., Martin, S. F., Liebl, D. J., Price, T. J., & Kolber, B. J. (2024) · eNeuro · doi:10.1523/eneuro.0488-23.2024 · Cited by 11 · see citing works
Synthesis, Computational Insights, and Evaluation of Novel Sigma Receptors Ligands
Dichiara, M., Ambrosio, F. A., Barbaraci, C., González‐Cano, R., Costa, G., Parenti, C., Marrazzo, A., Pasquinucci, L., Cobos, E. J., Alcaro, S., et al. (2023) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.3c00074 · Cited by 11 · see citing works
Burns, M., Guadagnoli, N., & McCurdy, C. R. (2023) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2023.2216015 · Cited by 11 · see citing works
The Emerging Role of Sigma Receptors in Pain Medicine
Pergolizzi, J. V., & Varrassi, G. (2023) · Cureus · doi:10.7759/cureus.42626 · Cited by 11 · see citing works
Yao, H., Wang, X., Chi, J., Chen, H., Liu, Y., Jiayi, Y., Yu, J., Ruan, Y., Xiang, X., Pi, J., et al. (2024) · Molecules · doi:10.3390/molecules29050964 · Cited by 11 · see citing works
Self-citationVigneron, S. F., Ohno, S., Braz, J. M., Kim, J. Y., Kweon, O. S., Webb, C. M., Billesbølle, C. B., Srinivasan, K., Bhardwaj, K., Irwin, J. J., et al. (2025) · ACS Central Science · doi:10.1021/acscentsci.5c00052 · Cited by 10 · see citing works
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Sindt, F., & Rognan, D. (2026) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2026.118576 · Cited by 11 · see citing works
Christmann, U., Dı́az, J. L., Pascual, R., Bordas, M., Álvarez, I., Monroy, X., Porras, M., Yeste, S., Reinoso, R. F., Merlos, M., et al. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.3c01060 · Cited by 10 · see citing works
Knowles, L. G., Armanious, A. J., Peng, Y., Welsh, W. J., & James, M. H. (2023) · Addiction Neuroscience · doi:10.1016/j.addicn.2023.100126 · Cited by 10 · see citing works
Barbanente, A., Kopecka, J., Vitone, D., Niso, M., Rizzi, R., Cuocci, C., Abatematteo, F. S., Mastropasqua, F., Colabufo, N. A., Margiotta, N., et al. (2024) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.4c01410 · Cited by 10 · see citing works
TargetSA: adaptive simulated annealing for target-specific drug design
Xue, Z., Sun, C., Zheng, W., Lv, J., & Liu, X. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae730 · Cited by 10 · see citing works
Sigma-2 Receptor Ligand Binding Modulates Association between TSPO and TMEM97
Thejer, B. M., Infantino, V., Santarsiero, A., Pappalardo, I., Abatematteo, F. S., Teakel, S. L., Oosterum, A. V., Mach, R. H., Denora, N., Lee, B. C., et al. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24076381 · Cited by 10 · see citing works
Luca, L. D., Lombardo, L., Mirabile, S., Marrazzo, A., Dichiara, M., Cosentino, G., Amata, E., & Gitto, R. (2023) · RSC Medicinal Chemistry · doi:10.1039/d3md00291h · Cited by 10 · see citing works
AlphaFold3 for Structure-guided Ligand DiscoveryPreprint
Menon, K. M., Davasam, A., Chen, G., Bryant, C., Deng, Z., Lam, B., Yang, C., Barcelos, D., Liu, F., Alon, A., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.04.692352 · Cited by 15 · see citing works
Self-citationMercer, R. C. C., Le, N. T. T., Fraser, D. G., Houser, M. C., Beeler, A. B., & Harris, D. A. (2024) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.4c00095 · Cited by 9 · see citing works
Introducing SpaceGA: A Search Tool to Accelerate Large Virtual Screenings of Combinatorial Libraries
Moesgaard, L., & Kongsted, J. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01308 · Cited by 9 · see citing works
Exploration of Diazaspiro Cores as Piperazine Bioisosteres in the Development of σ2 Receptor Ligands
Xu, K., Hsieh, C., Lee, J. Y., Riad, A., Izzo, N. J., Look, G. C., Catalano, S. M., & Mach, R. H. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23158259 · Cited by 9 · see citing works
Unde venisti PGRMC? Grand-Scale Biology from Early Eukaryotes and Eumetazoan Animal Origins
Cahill, M. A. (2022) · Frontiers in Bioscience-Landmark · doi:10.31083/j.fbl2711317 · Cited by 9 · see citing works
Mavlyutov, T. A., Li, J., Liu, X., Shen, H., Yang, H. M., McCurdy, C. R., Pattnaik, B. R., & Guo, L. (2022) · Genes · doi:10.3390/genes13122386 · Cited by 9 · see citing works
Anobile, D. P., Niso, M., Puerta, A., Rodrigues, S. M. F., Abatematteo, F. S., Avan, A., Abate, C., Riganti, C., & Giovannetti, E. (2022) · Molecules · doi:10.3390/molecules27051682 · Cited by 9 · see citing works
Fallica, A. N., Ciaffaglione, V., Modica, M. N., Pittalà, V., Salerno, L., Amata, E., Marrazzo, A., Romeo, G., & Intagliata, S. (2022) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2022.117032 · Cited by 9 · see citing works
Large library docking for cannabinoid-1 receptor agonists with reduced side effectsPreprint
Tummino, T. A., Iliopoulos‐Tsoutsouvas, C., Bráz, J. M., O’Brien, E. S., Stein, R. M., Craik, V., Tran, N. K., Ganapathy, S., Liu, F., Shiimura, Y., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.27.530254 · Cited by 9 · see citing works
Self-citationA bottom-up approach to find lead compounds in expansive chemical spaces
Serrano‐Morrás, Á., Bertran‐Mostazo, A., Miñarro-Lleonar, M., Comajuncosa-Creus, A., Cabello, A., Labranya, C., Escudero, C., Tian, T. V., Khutorianska, I., Radchenko, D. S., et al. (2025) · Communications Chemistry · doi:10.1038/s42004-025-01610-2 · Cited by 8 · see citing works
Self-citation
- Authors
- Alon, A., Lyu, J., Braz, J. M., Tummino, T. A., Craik, V., O’Meara, M. J., Webb, C. M., Radchenko, D. S., Moroz, Y. S., Huang, X.-P., Liu, Y., Roth, B. L., Irwin, J. J., Basbaum, A. I., Shoichet, B. K., & Kruse, A. C.
- Affiliations
- Harvard University (US)
- University of California, San Francisco (US)
- University of Michigan (US)
- Taras Shevchenko National University of Kyiv (UA)
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Basbaum, Allan I.
- Shoichet, Brian K.
- Kruse, Andrew C.
- ORCID
- Venue
- Nature
- Published
- 2021-12-08
- Volume
- 600
- Issue
- 7890
- Pages
- 759-764
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC8867396
- OpenAlex
- W4200289210
- Cited by
- 211
- References
- 92
- Citations by year
- 2026: 24 · 2025: 41 · 2024: 49 · 2023: 55 · 2022: 37 · 2021: 5
- FWCI
- 11.93
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Nature (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- U.S. Department of Energy (DE‐ AC02‐06CH11357, Contract No. DE-AC02-06CH11357., AC02‐06CH11357, 06CH11357, No. DE-AC02-06CH11357, DE-AC02-)
- Sanofi
- Vallee Foundation
- National Institutes of Health (ACB-12002, 1s10od012289-01a1, DE-AC02–06CH11357, AGM-12006)
- Defense Advanced Research Projects Agency (HR0011, HR0011-19-2-0020)
- Office of Science (Contract No. DE-AC02-06CH11357, AC02‐06CH11357, DE-AC02, No. DE-AC02-06CH11357., 06CH11357, DE-AC02-06CH11357)
- National Cancer Institute (DE-AC02-06CH11357, ACB12002, AGM-12006)
- National Institute of General Medical Sciences (S10 OD012289, R01GM133836, R01GM119185, P41GM103311, DE-AC02-06CH11357, AGM-12006, ACB-12002, T32GM007175, P30GM138396, R35GM122481, AGM-12006, P30GM138396)
- National Institute of Neurological Disorders and Stroke (R35NS097306)
- Argonne National Laboratory (DE- AC02-06-CH11357, DE-AC02, AC02–06CH11357, No. DE-AC02-06CH11357, 06CH11357, Contract No. DE-AC02-06CH11357., S10 OD012289)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Pharmacological Receptor Mechanisms and Effects
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- sigma-2 receptor, crystal structure, virtual screening, structure-based drug design, protein-ligand docking, neuropathic pain, mechanical hypersensitivity, spared nerve injury model, nociception
- MeSH terms
- Animals, Ligands, Neuralgia, Structure-Activity Relationship, Receptors, sigma, Mice
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