New Aryl Hydrocarbon Receptor Homology Model Targeted To Improve Docking Reliability
Open accessAbstract
The aryl hydrocarbon receptor (AhR) is a ligand-dependent, basic helix-loop-helix Per-ARNT-Sim (PAS) containing transcription factor that can bind and be activated by structurally diverse chemicals, including the toxic environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). As no experimentally determined structures of the AhR ligand binding domain (LBD) are available and previous homology models were only derived from apo template structures, we developed a new model based on holo X-ray structures of the hypoxia-inducible factor 2α (HIF-2α) PAS B domain, targeted to improve the accuracy of the binding site for molecular docking applications. We experimentally confirmed the ability of two HIF-2α crystallographic ligands to bind to the mAhR with relatively high affinity and demonstrated that they are AhR agonists, thus justifying the use of the holo HIF-2α structures as templates. A specific modeling/docking approach was proposed to predict the binding modes of AhR ligands in the modeled LBD. It was validated by comparison of the calculated and the experimental binding affinities of active THS ligands and TCDD for the mAhR and by functional activity analysis using several mAhR mutants generated on the basis of the modeling results. Finally the ability of the proposed approach to reproduce the different affinities of TCDD for AhRs of different species was confirmed, and a first test of its reliability in virtual screening is carried out by analyzing the correlation between the calculated and experimental binding affinities of a set of 14 PCDDs.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Experimental confirmation of predicted binding modes for TCDD and other ligands in the AHR LBD is generally lacking.
“While the binding modes of TCDD and other ligands within the AHR LBD of a given species (typically that of mouse or human AHR) have been predicted by these approaches, experimental confirmation of these proposed interactions are generally lacking.”
From Comparative Analysis of Homology Models of the Ah Receptor Ligand Binding Domain: Verification of Structure–Function Predictions by Site-Directed Mutagenesis of a Nonfunctional Receptor (2013) · cites this paper as [19]
The Introduction says the predicted TCDD binding mode was confirmed by functional analysis of mouse AHR mutants. The Results and Discussion section reports new mutagenesis data that “further confirm” that binding mode. Although the Conclusions say no experimentally determined AHR LBD structures were available, that is not the same as saying experimental confirmation of proposed interactions was generally lacking. (LLM, conf=0.84)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredHomology models of the AHR ligand-binding domain exist for only a small number of species.
“homology models of the AHR ligand-binding domain (LBD) are available for only a few species.”
From Comparative Analysis of Homology Models of the Ah Receptor Ligand Binding Domain: Verification of Structure–Function Predictions by Site-Directed Mutagenesis of a Nonfunctional Receptor (2013) · cites this paper as [19]
The Introduction (page unavailable) describes AhR LBD homology models for mouse, human, and rat and refers to models of several mammalian AhRs. It does not establish that models are available for only a few species overall. (LLM, conf=0.78)
Experimental — accuracy not yet measuredMD simulations allowed an improved description of the ligand binding modes and identification of all interacting residues.
“MD simulations allowed us to obtain an improved description of the ligand binding modes and the identification of all the interacting residues21,24,43.”
From Modeling the binding of diverse ligands within the Ah receptor ligand binding domain (2019) · cites this paper as [24]
The Results and Discussion section ('Ensemble docking approach to study ligand binding to the AhR'; page unavailable) reports that combined Monte Carlo/Stochastic Dynamics simulations clarified where TCDD was stabilized in the binding cavity and identified hydrogen bonds with Thr 283 and Gln 377. It does not claim that the simulations identified all interacting residues. (LLM, conf=0.84)
Experimental — accuracy not yet measuredPreviously, L302A and L309A mutations dramatically reduced TCDD binding activity, whereas C327A, M334A, and S359A at the entrance of the cavity only partially affected it.
“We previously observed that the L302A, L309A mutations dramatically reduced TCDD binding activity, whereas C327A, M334A and S359A, at the entrance of the cavity, only partially affected it24.”
From Modeling the binding of diverse ligands within the Ah receptor ligand binding domain (2019) · cites this paper as [24]
The Results and Discussion section (page unavailable) reports dramatically reduced TCDD binding for L302A and L309A, an approximately 40% reduction for S359A, and partial reductions for C327A and M334A. It places Ser 359 at the cavity entrance but does not establish that Cys 327 and Met 334 are there too. (LLM, conf=0.82)
Experimental — accuracy not yet measuredHomology models of the AHR LBD have revealed key structural features and, when combined with site-directed mutagenesis and functional assays, have helped identify amino acids important for ligand binding and ligand-dependent activation.
“These theoretical models not only have revealed key structural aspects of the domain, but when coupled with site directed mutagenesis and functional analysis, have proven to be helpful in identifying amino acids important in ligand binding and ligand-dependent AHR activation (12,17-19,21).”
The authors and others have used crystal and NMR structures of homologous protein domains to build homology models of the AHR LBD.
“While the lack of any three-dimensional structure information on the AHR ligand binding domain (LBD) has prevented detailed molecular analysis of the mechanisms of AHR ligand binding, we and others have used the availability of crystal and nuclear magnetic resonance (NMR) structures of homologous protein domains to develop homology models of the AHR LBD for such analysis (12,17-20).”
The absence of three-dimensional structure information for the AHR LBD has prevented detailed molecular analysis of AHR ligand binding mechanisms.
“While the lack of any three-dimensional structure information on the AHR ligand binding domain (LBD) has prevented detailed molecular analysis of the mechanisms of AHR ligand binding, we and others have used the availability of crystal and nuclear magnetic resonance (NMR) structures of homologous protein domains to develop homology models of the AHR LBD for such analysis (12,17-20).”
Homology models have been used in molecular docking to study interactions of known agonists within the AHR LBD and in virtual screening of putative ligands.
“More recently, these models have been used in molecular docking studies in an attempt to elucidate the detailed interactions of some known ligands (agonists) within the AHR LBD as well as in the virtual screening of collections of putative ligands (12,18-20,22-25).”
Employment of PAS-B structures of HIF-2α in complex with ligands as templates greatly improved the quality of the modeled binding site, and inclusion of receptor flexibility in docking enabled better description of the binding event.
“Not only did the employment of PAS-B structures of the homologous HIF-2α protein in complex with ligands as templates for modeling greatly improve the quality of the modeled binding site, but the inclusion of a certain degree of receptor flexibility in docking calculations enabled us and other investigators to better describe the binding event19,24–26.”
From Modeling the binding of diverse ligands within the Ah receptor ligand binding domain (2019) · cites this paper as [24]
Similar ligand binding-decreasing effects were reported by other groups following point mutations of these key pocket residues.
“Similar ligand binding-decreasing effects were reported by other groups following point mutations of these key pocket residues39,43,44.”
From Structural basis for the ligand-dependent activation of heterodimeric AHR-ARNT complex (2025) · cites this paper as [44]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192 · see citing works
PROCHECK: a program to check the stereochemical quality of protein structures
Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993) · Journal of Applied Crystallography · doi:10.1107/s0021889892009944 · Cited by 24,581 · see citing works
Comparative Protein Modelling by Satisfaction of Spatial Restraints
Šali, A., & Blundell, T. L. (1993) · Journal of Molecular Biology · doi:10.1006/jmbi.1993.1626 · Cited by 12,977 · see citing works
Friesner, R. A., Banks, J. L., Murphy, R. B., Halgren, T. A., Klicic, J. J., Mainz, D. T., Repasky, M. P., Knoll, E. H., Shelley, M., Perry, J. K., et al. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm0306430 · Cited by 10,057 · see citing works
Friesner, R. A., Murphy, R. B., Repasky, M. P., Frye, L. L., Greenwood, J. R., Halgren, T. A., Sanschagrin, P. C., & Mainz, D. T. (2006) · Journal of Medicinal Chemistry · doi:10.1021/jm051256o · Cited by 6,964 · see citing works
Wiederstein, M., & Sippl, M. J. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm290 · Cited by 5,909 · see citing works
Halgren, T. A., Murphy, R. B., Friesner, R. A., Beard, H. S., Frye, L. L., Pollard, W. T., & Banks, J. L. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm030644s · Cited by 5,280 · see citing works
Semianalytical treatment of solvation for molecular mechanics and dynamics
Still, W. C., Tempczyk, A., Hawley, R. C., & Hendrickson, T. F. (1990) · Journal of the American Chemical Society · doi:10.1021/ja00172a038 · Cited by 3,653 · see citing works
Comparative Protein Structure Modeling of Genes and Genomes
Martí-Renom, M. A., Stuart, A. C., Fiser, A., Sánchez, R., Melo, F., & Šali, A. (2000) · Annual Review of Biophysics and Biomolecular Structure · doi:10.1146/annurev.biophys.29.1.291 · Cited by 3,169 · see citing works
Analytical molecular surface calculation
Connolly, M. L. (1983) · Journal of Applied Crystallography · doi:10.1107/s0021889883010985 · Cited by 2,536 · see citing works
Poland, A., & Knutson, J. C. (1982) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev.pa.22.040182.002505 · Cited by 2,515 · see citing works
Statistical potential for assessment and prediction of protein structures
Shen, M., & Šali, A. (2006) · Protein Science · doi:10.1110/ps.062416606 · Cited by 2,294 · see citing works
Recognition of errors in three‐dimensional structures of proteins
Sippl, M. J. (1993) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340170404 · Cited by 2,156 · see citing works
Modeling of loops in protein structures
Fiser, A., Do, R. K. G., & Šali, A. (2000) · Protein Science · doi:10.1110/ps.9.9.1753 · Cited by 2,116 · see citing works
Molecular Modelling: Principles and Applications
Leach, A. R. (1996) · Cited by 1,944 · see citing works
Denison, M. S., & Nagy, S. R. (2003) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev.pharmtox.43.100901.135828 · Cited by 1,895 · see citing works
Self-citationSafe, S. (1990) · Critical Reviews in Toxicology · doi:10.3109/10408449009089873 · Cited by 1,871 · see citing works
Molecular Modelling: Principles and Applications
Valverde, J. R. (2001) · Briefings in Bioinformatics · doi:10.1093/bib/2.2.199 · Cited by 1,865 · see citing works
A Critical Assessment of Docking Programs and Scoring Functions
Warren, G. L., Andrews, C. W., Capelli, A., Clarke, B., LaLonde, J. M., Lambert, M. H., Lindvall, M., Nevins, N., Semus, S. F., Senger, S., et al. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm050362n · Cited by 1,840 · see citing works
Dundas, J., Ouyang, Z., Tseng, J., Binkowski, A., Turpaz, Y., & Liang, J. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl282 · Cited by 1,725 · see citing works
CASTp: Computed Atlas of Surface Topography of proteins
Binkowski, T. A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg512 · Cited by 1,673 · see citing works
Poland, A., Glover, E., & Kende, A. S. (1976) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(17)33205-2 · Cited by 1,370 · see citing works
AH RECEPTOR SIGNALING PATHWAYS
Schmidt, J. V., & Bradfield, C. A. (1996) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev.cellbio.12.1.55 · Cited by 899 · see citing works
Safe, S. H. (1986) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev.pa.26.040186.002103 · Cited by 710 · see citing works
The Search for Endogenous Activators of the Aryl Hydrocarbon Receptor
Nguyen, L. P., & Bradfield, C. A. (2007) · Chemical Research in Toxicology · doi:10.1021/tx7001965 · Cited by 705 · see citing works
Advances and Challenges in Protein-Ligand Docking
Huang, S., & Zou, X. (2010) · International Journal of Molecular Sciences · doi:10.3390/ijms11083016 · Cited by 645 · see citing works
The mammalian basic helix–loop–helix/PAS family of transcriptional regulators
Kewley, R. J., Whitelaw, M. L., & Chapman‐Smith, A. (2003) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/s1357-2725(03)00211-5 · Cited by 590 · see citing works
Ligand binding and activation of the Ah receptor
Denison, M. S., Pandini, A., Nagy, S. R., Baldwin, E. P., & Bonati, L. (2002) · Chemico-Biological Interactions · doi:10.1016/s0009-2797(02)00063-7 · Cited by 485 · see citing works
Self-citationHomology modeling in drug discovery: current trends and applications
Cavasotto, C. N., & Phatak, S. S. (2009) · Drug Discovery Today · doi:10.1016/j.drudis.2009.04.006 · Cited by 484 · see citing works
Dioxin binding activities of polymorphic forms of mouse and human arylhydrocarbon receptors.
Ema, M., Ohe, N., Suzuki, M., Mimura, J., Sogawa, K., Ikawa, S., & Fujii-Kuriyama, Y. (1994) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(18)46990-6 · Cited by 329 · see citing works
Utility of homology models in the drug discovery process
Hillisch, A., Pineda, L. F., & Hilgenfeld, R. (2004) · Drug Discovery Today · doi:10.1016/s1359-6446(04)03196-4 · Cited by 315 · see citing works
Artificial ligand binding within the HIF2α PAS-B domain of the HIF2 transcription factor
Scheuermann, T. H., Tomchick, D. R., Machius, M., Guo, Y., Bruick, R. K., & Gardner, K. H. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0808092106 · Cited by 301 · see citing works
McGovern, S. L., & Shoichet, B. K. (2003) · Journal of Medicinal Chemistry · doi:10.1021/jm0300330 · Cited by 276 · see citing works
Denison, M. S., & Heath-Pagliuso, S. (1998) · Bulletin of Environmental Contamination and Toxicology · doi:10.1007/pl00002973 · Cited by 258 · see citing works
Self-citationManaging protein flexibility in docking and its applications
B‐Rao, C., Subramanian, J., & Sharma, S. (2009) · Drug Discovery Today · doi:10.1016/j.drudis.2009.01.003 · Cited by 233 · see citing works
Ma, Q. (2001) · Current Drug Metabolism · doi:10.2174/1389200013338603 · Cited by 232 · see citing works
Erbel, P. J. A., Card, P. B., Karakuzu, O., Bruick, R. K., & Gardner, K. H. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2533374100 · Cited by 227 · see citing works
MM-GB/SA Rescoring of Docking Poses in Structure-Based Lead Optimization
Guimarães, C. R. W., & Cardozo, M. G. (2008) · Journal of Chemical Information and Modeling · doi:10.1021/ci800004w · Cited by 220 · see citing works
Current Protocols in Toxicology
Kietzmann, M. (2001) · Toxicon · doi:10.1016/s0041-0101(00)00185-9 · Cited by 206 · see citing works
Rescoring docking hit lists for model cavity sites: predictions and experimental testing.
Graves, A. P., Shivakumar, D., Boyce, S. E., Jacobson, M., Case, D., & Shoichet, B. (2008) · Journal of Molecular Biology · doi:10.1016/j.jmb.2008.01.049 · Cited by 184 · see citing works
AMBER torsional parameters for the peptide backbone
McDonald, D. Q., & Still, W. C. (1992) · Tetrahedron Letters · doi:10.1016/0040-4039(93)88034-g · Cited by 173 · see citing works
A rapidly convergent simulation method: Mixed Monte Carlo/stochastic dynamics
Guarnieri, F., & Still, W. C. (1994) · Journal of Computational Chemistry · doi:10.1002/jcc.540151111 · Cited by 168 · see citing works
Pandini, A., Denison, M. S., Song, Y., Soshilov, A. A., & Bonati, L. (2007) · Biochemistry · doi:10.1021/bi061460t · Cited by 160 · see citing works
Self-citationContinuum Secondary Structure Captures Protein Flexibility
Andersen, C. A. F., Palmer, A. G. I., Brunak, S., & Rost, B. (2002) · Structure · doi:10.1016/s0969-2126(02)00700-1 · Cited by 153 · see citing works
Structure and Interactions of PAS Kinase N-Terminal PAS Domain
Amezcua, C. A., Harper, S. M., Rutter, J. P., & Gardner, K. H. (2002) · Structure · doi:10.1016/s0969-2126(02)00857-2 · Cited by 150 · see citing works
Bisson, W. H., Koch, D. C., O’Donnell, E. F., Khalil, S. M., Kerkvliet, N. I., Tanguay, R. L., Abagyan, R., & Kolluri, S. K. (2009) · Journal of Medicinal Chemistry · doi:10.1021/jm900199u · Cited by 149 · see citing works
Card, P. B., Erbel, P. J. A., & Gardner, K. H. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.08.043 · Cited by 139 · see citing works
Mason, G., Farrell, K., Keys, B., et al. (1986) · Toxicology · doi:10.1016/0300-483x(86)90101-0 · Cited by 138 · see citing works
Molecular Docking Screens Using Comparative Models of Proteins
Fan, H., Irwin, J. J., Webb, B. M., Klebe, G., Shoichet, B. K., & Sali, A. (2009) · Journal of Chemical Information and Modeling · doi:10.1021/ci9003706 · Cited by 135 · see citing works
Pandini, A., Soshilov, A. A., Song, Y., Zhao, J., Bonati, L., & Denison, M. S. (2009) · Biochemistry · doi:10.1021/bi900259z · Cited by 124 · see citing works
Self-citationPrinciples of ligand binding within a completely buried cavity in HIF2α PAS-B
Key, J., Scheuermann, T. H., Anderson, P., Daggett, V., & Gardner, K. (2009) · Journal of the American Chemical Society · doi:10.1021/ja9073062 · Cited by 119 · see citing works
Comparison of recombinant cell bioassays for the detection of Ah receptor agonists
Han, D., Nagy, S. R., & Denison, M. S. (2004) · BioFactors · doi:10.1002/biof.5520200102 · Cited by 114 · see citing works
Self-citationPredicting the accuracy of protein–ligand docking on homology models
Bordogna, A., Pandini, A., & Bonati, L. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21601 · Cited by 107 · see citing works
Self-citationRole of the Per/Arnt/Sim Domains in Ligand-dependent Transformation of the Aryl Hydrocarbon Receptor
Soshilov, A., & Denison, M. S. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m802414200 · Cited by 99 · see citing works
Self-citationIdentification of a Novel Domain in the Aryl Hydrocarbon Receptor Required for DNA Binding
Fukunaga, B. N., & Hankinson, O. (1996) · Journal of Biological Chemistry · doi:10.1074/jbc.271.7.3743 · Cited by 91 · see citing works
Tartari, C. J., Gunby, R. H., Coluccia, A. M. L., et al. (2007) · Journal of Biological Chemistry · doi:10.1074/jbc.m706067200 · Cited by 77 · see citing works
Denison, M. S., Wilkinson, C. F., & Okey, A. B. (1986) · Chemosphere · doi:10.1016/0045-6535(86)90452-2 · Cited by 70 · see citing works
Self-citationEnsemble Docking from Homology Models
Novoa, E. M., de Pouplana, L. R., Barril, X., & Orozco, M. (2010) · Journal of Chemical Theory and Computation · doi:10.1021/ct100246y · Cited by 67 · see citing works
Identification of amino acid residues in the Ah receptor involved in ligand binding
Goryo, K., Suzuki, A., Carpio, C. A. D., Siizaki, K., Kuriyama, E., Mikami, Y., Kinoshita, K., Yasumoto, K., Rannug, A., Miyamoto, A., et al. (2007) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2006.12.227 · Cited by 64 · see citing works
A model for recognition of polychlorinated dibenzo‐<i>p</i>‐dioxins by the aryl hydrocarbon receptor
Procopio, M., Lahm, A., Tramontano, A., Bonati, L., & Pitea, D. (2002) · European Journal of Biochemistry · doi:10.1046/j.0014-2956.2002.02619.x · Cited by 61 · see citing works
Self-citationAnalysis of the Aryl Hydrocarbon Receptor (<scp>Ah</scp><scp>R</scp>) Signal Transduction Pathway
Denison, M. S., Rogers, J. M., Rushing, S. R., Jones, C. L., Tetangco, S. C., & Heath‐Pagliuso, S. (2002) · Current Protocols in Toxicology · doi:10.1002/0471140856.tx0408s11 · Cited by 55 · see citing works
Self-citationMurray, I. A., Flaveny, C. A., Chiaro, C. R., Sharma, A. K., Tanos, R. S., Schroeder, J. C., Amin, S. G., Bisson, W. H., Kolluri, S. K., & Perdew, G. H. (2011) · Molecular Pharmacology · doi:10.1124/mol.110.069369 · Cited by 53 · see citing works
Publisher, B. S. P. B. S. (2006) · Current Protein and Peptide Science · doi:10.2174/138920306778559368 · Cited by 49 · see citing works
Wu, B., Zhang, Y., Kong, J., Zhang, X., & Cheng, S. (2009) · Toxicology Letters · doi:10.1016/j.toxlet.2009.08.005 · Cited by 46 · see citing works
Evaluation of the utility of homology models in high throughput docking
Ferrara, P., & Jacoby, E. (2007) · Journal of Molecular Modeling · doi:10.1007/s00894-007-0207-6 · Cited by 42 · see citing works
Evidence that ligand binding is a key determinant of Ah receptor-mediated transcriptional activity
Murray, I. A., Reen, R. K., Leathery, N., Ramadoss, P., Bonati, L., Gonzalez, F. J., Peters, J. M., & Perdew, G. H. (2005) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2005.07.014 · Cited by 41 · see citing works
Self-citationHenry, E. C., & Gasiewicz, T. A. (2008) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2008.02.005 · Cited by 36 · see citing works
Petkov, P. I., Rowlands, J. C., Budinsky, R. A., Zhao, B., Denison, M. S., & Mekenyan, O. G. (2010) · SAR and QSAR in environmental research · doi:10.1080/10629360903570933 · Cited by 25 · see citing works
Self-citationJogalekar, A. S., Reiling, S., & Vaz, R. J. (2010) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/j.bmcl.2010.09.019 · Cited by 23 · see citing works
Yoshikawa, E., Miyagi, S., Dedachi, K., Ishihara‐Sugano, M., Itoh, S., & Kurita, N. (2010) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2010.06.008 · Cited by 14 · see citing works
Toxicant-receptor interactions : modulation of signal transduction and gene expression
Denison, M. S., & Helferich, W. G. (1998) · Taylor & Francis eBooks · Cited by 11 · see citing works
Self-citationMechanism based common reactivity pattern (COREPA) modeling of AhR binding affinity
Petkov, P. I., Rowlands, J. C., Budinsky, R. A., et al. (2010) · Cited by 3 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [7]Denison MS Seidel SD Rogers WJ Ziccardi M Winter GM Heath-Pagliuso S Puga A Wallace KB Natural and synthetic ligands for the Ah receptor Molecular Biology Approaches to Toxicology Taylor & Francis Philadelphia, PA 1998 393 410
Cited by
Sorted by citations
Bersten, D. C., Sullivan, A. E., Peet, D. J., & Whitelaw, M. L. (2013) · Nature Reviews Cancer · doi:10.1038/nrc3621 · Cited by 267 · see citing works
Soshilov, A. A., & Denison, M. S. (2014) · Molecular and Cellular Biology · doi:10.1128/mcb.01183-13 · Cited by 128 · see citing works
Self-citationModeling the binding of diverse ligands within the Ah receptor ligand binding domain
Giani Tagliabue, S., Faber, S. C., Motta, S., Denison, M. S., & Bonati, L. (2019) · Scientific Reports · doi:10.1038/s41598-019-47138-z · Cited by 106 · see citing works
Self-citationFraccalvieri, D., Soshilov, A. A., Karchner, S. I., Franks, D. G., Pandini, A., Bonati, L., Hahn, M. E., & Denison, M. S. (2013) · Biochemistry · doi:10.1021/bi301457f · Cited by 65 · see citing works
Self-citationStructural basis for the ligand-dependent activation of heterodimeric AHR-ARNT complex
Diao, X., Shang, Q., Guo, M., Huang, Y., Zhang, M., Chen, X., Liang, Y., Sun, X., Zhou, F., Zhuang, J., et al. (2025) · Nature communications · doi:10.1038/s41467-025-56574-7 · Cited by 72 · see citing works
“Similar ligand binding-decreasing effects were reported by other groups following point mutations of these key pocket residues 39,43,44 .”
Perkins, A., Phillips, J., Kerkvliet, N., Tanguay, R., Perdew, G., Kolluri, S., & Bisson, W. (2014) · Biology · doi:10.3390/biology3040645 · Cited by 52 · see citing works
“address species selective differences in TCDD binding [6,17] and to identify potential binding patterns of agonists and antagonists of the AHR [6,13,18,19].”
BackgroundMethodInfluentialCheng, Y., Jin, U.-H., Davidson, L. A., Chapkin, R. S., Jayaraman, A., Tamamis, P., Orr, A., Allred, C., Denison, M. S., Soshilov, A., et al. (2017) · Toxicological Sciences · doi:10.1093/toxsci/kfw230 · Cited by 48 · see citing works
Self-citationNuti, R., Gargaro, M., Matino, D., Dolciami, D., Grohmann, U., Puccetti, P., Fallarino, F., & Macchiarulo, A. (2014) · Journal of Chemical Information and Modeling · doi:10.1021/ci5005459 · Cited by 45 · see citing works
Corrada, D., Soshilov, A. A., Denison, M. S., & Bonati, L. (2016) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004981 · Cited by 43 · see citing works
Self-citationFaber, S. C., Soshilov, A. A., Giani Tagliabue, S., Bonati, L., & Denison, M. S. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19092692 · Cited by 36 · see citing works
Self-citationSoshilov, A. A., Motta, S., Bonati, L., & Denison, M. S. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21072474 · Cited by 36 · see citing works
Self-citationBonati, L., Corrada, D., Giani Tagliabue, S., & Motta, S. (2017) · Current Opinion in Toxicology · doi:10.1016/j.cotox.2017.01.011 · Cited by 27 · see citing works
Self-citationIn vitro toxicity and in silico docking analysis of two novel selective AH-receptor modulators
Mahiout, S., Tagliabue, S. G., Nasri, A., Omoruyi, I. M., Pettersson, L., Bonati, L., & Pohjanvirta, R. (2018) · Toxicology in Vitro · doi:10.1016/j.tiv.2018.06.010 · Cited by 19 · see citing works
Self-citation
- Authors
- Motto, I., Bordogna, A., Soshilov, A. A., Denison, M. S., & Bonati, L.
- Affiliations
- University of Milano-Bicocca (IT)
- University of California, Davis (US)
- Corresponding author
- Bonati, Laura
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-11-02
- Volume
- 51
- Issue
- 11
- Pages
- 2868-2881
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- PMC
- PMC3263330
- OpenAlex
- W2053244650
- Semantic Scholar
- 70e844d36002a9588ce9801a751e5b0099a8c571
- Cited by
- 80
- References
- 73
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 3 · 2023: 7 · 2022: 6 · 2021: 5 · 2020: 10 · 2019: 6 · 2018: 7 · 2017: 2 · 2016: 9 · 2015: 3 · 2014: 8 · 2013: 8 · 2012: 1
- FWCI
- 5.12
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Chemical Information and Modeling (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- BOA (University of Milano-Bicocca) (submittedVersion)
- Funders
- National Institute of Environmental Health Sciences (P42ES004699, R01ES007685, ES007685, ES004699)
- 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 › Environmental Science › Health, Toxicology and Mutagenesis › Toxic Organic Pollutants Impact
- Keywords
- aryl hydrocarbon receptor, homology modeling, ligand-binding domain, 2,3,7,8-tetrachlorodibenzo-p-dioxin, polychlorinated dibenzo-p-dioxins, molecular docking, binding site prediction, virtual screening, AhR agonists, environmental pollutants
- MeSH terms
- Polychlorinated Dibenzodioxins, Endothelial PAS Domain-Containing Protein 1, Animals, Binding Sites, Binding, Competitive, Chlorocebus aethiops, Humans, Ligands, Models, Molecular, Mutation, Plasmids, Protein Binding, Recombinant Proteins, Transfection, Gene Expression, Mutagenesis, Site-Directed, Helix-Loop-Helix Motifs, Receptors, Aryl Hydrocarbon, Crystallography, X-Ray, Computational Biology, COS Cells, Electrophoretic Mobility Shift Assay, Basic Helix-Loop-Helix Proteins
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
