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Showing 1 to 12 of 36 entries
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Reply to Douglass and Spiegel: A suite of mathematical solutions to describe ternary complex formation and their application to targeted protein degredation by heterobifunctional ligands.

The Journal of biological chemistry

Han B.
PMID: 33837729
J Biol Chem. 2021 Jan-Jun;296:100330. doi: 10.1016/j.jbc.2021.100330. Epub 2021 Mar 10.

No abstract available.

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Han B. Reply to Douglass and Spiegel: A suite of mathematical solutions to describe ternary complex formation and their application to targeted protein degredation by heterobifunctional ligands. J Biol Chem. 2021;296:100330doi: 10.1016/j.jbc.2021.100330.
Han, B. (2021). Reply to Douglass and Spiegel: A suite of mathematical solutions to describe ternary complex formation and their application to targeted protein degredation by heterobifunctional ligands. The Journal of biological chemistry, 296100330. https://doi.org/10.1016/j.jbc.2021.100330
Han, Bomie. "Reply to Douglass and Spiegel: A suite of mathematical solutions to describe ternary complex formation and their application to targeted protein degredation by heterobifunctional ligands." The Journal of biological chemistry vol. 296 (2021): 100330. doi: https://doi.org/10.1016/j.jbc.2021.100330
Han B. Reply to Douglass and Spiegel: A suite of mathematical solutions to describe ternary complex formation and their application to targeted protein degredation by heterobifunctional ligands. J Biol Chem. 2021 Jan-Jun;296:100330. doi: 10.1016/j.jbc.2021.100330. Epub 2021 Mar 10. PMID: 33837729; PMCID: PMC7960536.
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An integrated computational approach to identify GC minor groove binders using various molecular docking scoring functions, dynamics simulations and binding free energy calculations.

Journal of biomolecular structure & dynamics

Soni MN, Kumar SP, S R KJ, Rawal RM, Pandya HA.
PMID: 31502527
J Biomol Struct Dyn. 2020 Aug;38(13):3838-3855. doi: 10.1080/07391102.2019.1664331. Epub 2019 Oct 08.

Understanding the DNA-ligand interaction mechanism is of utmost importance to design selective inhibitors targeting the GC- and AT-rich DNA. This forms a primary strategy to block the association of transcription factors to promoters and subsequently, reduce the expression of...

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Soni MN, Kumar SP, S R KJ, et al. An integrated computational approach to identify GC minor groove binders using various molecular docking scoring functions, dynamics simulations and binding free energy calculations. J Biomol Struct Dyn. 2019;38(13):3838-3855doi: 10.1080/07391102.2019.1664331.
Soni, M. N., Kumar, S. P., S R, K. J., Rawal, R. M., & Pandya, H. A. (2020). An integrated computational approach to identify GC minor groove binders using various molecular docking scoring functions, dynamics simulations and binding free energy calculations. Journal of biomolecular structure & dynamics, 38(13), 3838-3855. https://doi.org/10.1080/07391102.2019.1664331
Soni, Mehul N, et al. "An integrated computational approach to identify GC minor groove binders using various molecular docking scoring functions, dynamics simulations and binding free energy calculations." Journal of biomolecular structure & dynamics vol. 38,13 (2020): 3838-3855. doi: https://doi.org/10.1080/07391102.2019.1664331
Soni MN, Kumar SP, S R KJ, Rawal RM, Pandya HA. An integrated computational approach to identify GC minor groove binders using various molecular docking scoring functions, dynamics simulations and binding free energy calculations. J Biomol Struct Dyn. 2020 Aug;38(13):3838-3855. doi: 10.1080/07391102.2019.1664331. Epub 2019 Oct 08. PMID: 31502527.
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Adaptive mining and model building of medicinal chemistry data with a multi-metric perspective.

Future medicinal chemistry

Brown JB.
PMID: 29966447
Future Med Chem. 2018 Aug 01;10(16):1885-1887. doi: 10.4155/fmc-2018-0188. Epub 2018 Jul 03.

No abstract available.

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Brown JB. Adaptive mining and model building of medicinal chemistry data with a multi-metric perspective. Future Med Chem. 2018;10(16):1885-1887doi: 10.4155/fmc-2018-0188.
Brown, J. B. (2018). Adaptive mining and model building of medicinal chemistry data with a multi-metric perspective. Future medicinal chemistry, 10(16), 1885-1887. https://doi.org/10.4155/fmc-2018-0188
Brown, J B. "Adaptive mining and model building of medicinal chemistry data with a multi-metric perspective." Future medicinal chemistry vol. 10,16 (2018): 1885-1887. doi: https://doi.org/10.4155/fmc-2018-0188
Brown JB. Adaptive mining and model building of medicinal chemistry data with a multi-metric perspective. Future Med Chem. 2018 Aug 01;10(16):1885-1887. doi: 10.4155/fmc-2018-0188. Epub 2018 Jul 03. PMID: 29966447.
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Webina: an open-source library and web app that runs AutoDock Vina entirely in the web browser.

Bioinformatics (Oxford, England)

Kochnev Y, Hellemann E, Cassidy KC, Durrant JD.
PMID: 32559277
Bioinformatics. 2020 Aug 15;36(16):4513-4515. doi: 10.1093/bioinformatics/btaa579.

MOTIVATION: Molecular docking is a computational technique for predicting how a small molecule might bind a macromolecular target. Among docking programs, AutoDock Vina is particularly popular. Like many docking programs, Vina requires users to download/install an executable file and...

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Kochnev Y, Hellemann E, Cassidy KC, et al. Webina: an open-source library and web app that runs AutoDock Vina entirely in the web browser. Bioinformatics. 2020;36(16):4513-4515doi: 10.1093/bioinformatics/btaa579.
Kochnev, Y., Hellemann, E., Cassidy, K. C., & Durrant, J. D. (2020). Webina: an open-source library and web app that runs AutoDock Vina entirely in the web browser. Bioinformatics (Oxford, England), 36(16), 4513-4515. https://doi.org/10.1093/bioinformatics/btaa579
Kochnev, Yuri, et al. "Webina: an open-source library and web app that runs AutoDock Vina entirely in the web browser." Bioinformatics (Oxford, England) vol. 36,16 (2020): 4513-4515. doi: https://doi.org/10.1093/bioinformatics/btaa579
Kochnev Y, Hellemann E, Cassidy KC, Durrant JD. Webina: an open-source library and web app that runs AutoDock Vina entirely in the web browser. Bioinformatics. 2020 Aug 15;36(16):4513-4515. doi: 10.1093/bioinformatics/btaa579. PMID: 32559277; PMCID: PMC7575045.
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Docking of Covalent Ligands: Challenges and Approaches.

Molecular informatics

Sotriffer C.
PMID: 29927068
Mol Inform. 2018 Sep;37(9):e1800062. doi: 10.1002/minf.201800062. Epub 2018 Jun 21.

Covalent ligands have recently regained considerable attention in drug discovery. The rational design of such ligands, however, is still faced with particular challenges, mostly related to the fact that covalent bond formation is a quantum mechanical phenomenon which cannot...

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Sotriffer C. Docking of Covalent Ligands: Challenges and Approaches. Mol Inform. 2018;37(9):e1800062doi: 10.1002/minf.201800062.
Sotriffer, C. (2018). Docking of Covalent Ligands: Challenges and Approaches. Molecular informatics, 37(9), e1800062. https://doi.org/10.1002/minf.201800062
Sotriffer, Christoph. "Docking of Covalent Ligands: Challenges and Approaches." Molecular informatics vol. 37,9 (2018): e1800062. doi: https://doi.org/10.1002/minf.201800062
Sotriffer C. Docking of Covalent Ligands: Challenges and Approaches. Mol Inform. 2018 Sep;37(9):e1800062. doi: 10.1002/minf.201800062. Epub 2018 Jun 21. PMID: 29927068.
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Topological DNA Tetrahedron Encapsulated Gold Nanoparticle Enables Precise Ligand Engineering for Targeted Cell Imaging.

Analytical chemistry

Tang D, Fan W, Xiong M, Li M, Xiong B, Zhang XB.
PMID: 34910458
Anal Chem. 2021 Dec 28;93(51):17036-17042. doi: 10.1021/acs.analchem.1c03682. Epub 2021 Dec 15.

Ligand-functionalized plasmonic nanoparticles have been widely used for targeted imaging in living systems. However, ligand presentation and encoding on the nanoparticle's surface in a stoichiometrically controllable manner remains a great challenge. Herein, we propose a method to construct ligand-engineered...

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Tang D, Fan W, Xiong M, et al. Topological DNA Tetrahedron Encapsulated Gold Nanoparticle Enables Precise Ligand Engineering for Targeted Cell Imaging. Anal Chem. 2021;93(51):17036-17042doi: 10.1021/acs.analchem.1c03682.
Tang, D., Fan, W., Xiong, M., Li, M., Xiong, B., & Zhang, X. B. (2021). Topological DNA Tetrahedron Encapsulated Gold Nanoparticle Enables Precise Ligand Engineering for Targeted Cell Imaging. Analytical chemistry, 93(51), 17036-17042. https://doi.org/10.1021/acs.analchem.1c03682
Tang, Decui, et al. "Topological DNA Tetrahedron Encapsulated Gold Nanoparticle Enables Precise Ligand Engineering for Targeted Cell Imaging." Analytical chemistry vol. 93,51 (2021): 17036-17042. doi: https://doi.org/10.1021/acs.analchem.1c03682
Tang D, Fan W, Xiong M, Li M, Xiong B, Zhang XB. Topological DNA Tetrahedron Encapsulated Gold Nanoparticle Enables Precise Ligand Engineering for Targeted Cell Imaging. Anal Chem. 2021 Dec 28;93(51):17036-17042. doi: 10.1021/acs.analchem.1c03682. Epub 2021 Dec 15. PMID: 34910458.
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Balancing Data on Deep Learning-Based Proteochemometric Activity Classification.

Journal of chemical information and modeling

Lopez-Del Rio A, Picart-Armada S, Perera-Lluna A.
PMID: 33779173
J Chem Inf Model. 2021 Apr 26;61(4):1657-1669. doi: 10.1021/acs.jcim.1c00086. Epub 2021 Mar 29.

In silico analysis of biological activity data has become an essential technique in pharmaceutical development. Specifically, the so-called proteochemometric models aim to share information between targets in machine learning ligand-target activity prediction models. However, bioactivity data sets used in...

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Lopez-Del Rio A, Picart-Armada S, Perera-Lluna A. Balancing Data on Deep Learning-Based Proteochemometric Activity Classification. J Chem Inf Model. 2021;61(4):1657-1669doi: 10.1021/acs.jcim.1c00086.
Lopez-Del Rio, A., Picart-Armada, S., & Perera-Lluna, A. (2021). Balancing Data on Deep Learning-Based Proteochemometric Activity Classification. Journal of chemical information and modeling, 61(4), 1657-1669. https://doi.org/10.1021/acs.jcim.1c00086
Lopez-Del Rio, Angela, et al. "Balancing Data on Deep Learning-Based Proteochemometric Activity Classification." Journal of chemical information and modeling vol. 61,4 (2021): 1657-1669. doi: https://doi.org/10.1021/acs.jcim.1c00086
Lopez-Del Rio A, Picart-Armada S, Perera-Lluna A. Balancing Data on Deep Learning-Based Proteochemometric Activity Classification. J Chem Inf Model. 2021 Apr 26;61(4):1657-1669. doi: 10.1021/acs.jcim.1c00086. Epub 2021 Mar 29. PMID: 33779173; PMCID: PMC8594867.
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Discovery of Natural Compounds as Potential Inhibitors of Human Carbonic Anhydrase II: An Integrated Virtual Screening, Docking, and Molecular Dynamics Simulation Study.

Omics : a journal of integrative biology

Anjum F, Ali F, Mohammad T, Shafie A, Akhtar O, Abdullaev B, Hassan I.
PMID: 34255561
OMICS. 2021 Aug;25(8):513-524. doi: 10.1089/omi.2021.0059. Epub 2021 Jul 13.

Carbonic anhydrase II (CAII) is one of the zinc metalloenzymes that catalyze the reversible hydration of carbon dioxide, leading to the formation of bicarbonate and proton. CAII plays a significant role in health and disease. For example, CAII helps...

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Anjum F, Ali F, Mohammad T, et al. Discovery of Natural Compounds as Potential Inhibitors of Human Carbonic Anhydrase II: An Integrated Virtual Screening, Docking, and Molecular Dynamics Simulation Study. OMICS. 2021;25(8):513-524doi: 10.1089/omi.2021.0059.
Anjum, F., Ali, F., Mohammad, T., Shafie, A., Akhtar, O., Abdullaev, B., & Hassan, I. (2021). Discovery of Natural Compounds as Potential Inhibitors of Human Carbonic Anhydrase II: An Integrated Virtual Screening, Docking, and Molecular Dynamics Simulation Study. Omics : a journal of integrative biology, 25(8), 513-524. https://doi.org/10.1089/omi.2021.0059
Anjum, Farah, et al. "Discovery of Natural Compounds as Potential Inhibitors of Human Carbonic Anhydrase II: An Integrated Virtual Screening, Docking, and Molecular Dynamics Simulation Study." Omics : a journal of integrative biology vol. 25,8 (2021): 513-524. doi: https://doi.org/10.1089/omi.2021.0059
Anjum F, Ali F, Mohammad T, Shafie A, Akhtar O, Abdullaev B, Hassan I. Discovery of Natural Compounds as Potential Inhibitors of Human Carbonic Anhydrase II: An Integrated Virtual Screening, Docking, and Molecular Dynamics Simulation Study. OMICS. 2021 Aug;25(8):513-524. doi: 10.1089/omi.2021.0059. Epub 2021 Jul 13. PMID: 34255561.
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Investigating the extension of pairwise distance pharmacophore measures to triplet-based descriptors.

Journal of computer-aided molecular design

Good AC, Kuntz ID.
PMID: 8523046
J Comput Aided Mol Des. 1995 Aug;9(4):373-9. doi: 10.1007/BF00125178.

Distances between key functional groups have been used for some time as molecular descriptors in 3D database screening and clustering calculations. More recently, a number of groups have explored triplets of molecular centers to describe key ligand features in...

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Good AC, Kuntz ID. Investigating the extension of pairwise distance pharmacophore measures to triplet-based descriptors. J Comput Aided Mol Des. 1995;9(4):373-9doi: 10.1007/BF00125178.
Good, A. C., & Kuntz, I. D. (1995). Investigating the extension of pairwise distance pharmacophore measures to triplet-based descriptors. Journal of computer-aided molecular design, 9(4), 373-9. https://doi.org/10.1007/BF00125178
Good, A C, and Kuntz, I D. "Investigating the extension of pairwise distance pharmacophore measures to triplet-based descriptors." Journal of computer-aided molecular design vol. 9,4 (1995): 373-9. doi: https://doi.org/10.1007/BF00125178
Good AC, Kuntz ID. Investigating the extension of pairwise distance pharmacophore measures to triplet-based descriptors. J Comput Aided Mol Des. 1995 Aug;9(4):373-9. doi: 10.1007/BF00125178. PMID: 8523046.
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Quantitative Structure-Activity Relationship for High Affinity 5-HT1A Receptor Ligands Based on Norm Indexes.

The journal of physical chemistry. B

Jia Q, Cui X, Li L, Wang Q, Liu Y, Xia S, Ma P.
PMID: 26605982
J Phys Chem B. 2015 Dec 24;119(51):15561-7. doi: 10.1021/acs.jpcb.5b08980. Epub 2015 Dec 10.

Arylpiperazine derivatives are promising 5-hydroxytryptamine (5-HT) receptor ligands which can inhibit serotonin reuptake effectively. In this work, some norm index descriptors were proposed and further utilized to develop a model for predicting 5-HT1A receptor affinity (pKi) of 88 arylpiperazine...

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Jia Q, Cui X, Li L, et al. Quantitative Structure-Activity Relationship for High Affinity 5-HT1A Receptor Ligands Based on Norm Indexes. J Phys Chem B. 2015;119(51):15561-7doi: 10.1021/acs.jpcb.5b08980.
Jia, Q., Cui, X., Li, L., Wang, Q., Liu, Y., Xia, S., & Ma, P. (2015). Quantitative Structure-Activity Relationship for High Affinity 5-HT1A Receptor Ligands Based on Norm Indexes. The journal of physical chemistry. B, 119(51), 15561-7. https://doi.org/10.1021/acs.jpcb.5b08980
Jia, Qingzhu, et al. "Quantitative Structure-Activity Relationship for High Affinity 5-HT1A Receptor Ligands Based on Norm Indexes." The journal of physical chemistry. B vol. 119,51 (2015): 15561-7. doi: https://doi.org/10.1021/acs.jpcb.5b08980
Jia Q, Cui X, Li L, Wang Q, Liu Y, Xia S, Ma P. Quantitative Structure-Activity Relationship for High Affinity 5-HT1A Receptor Ligands Based on Norm Indexes. J Phys Chem B. 2015 Dec 24;119(51):15561-7. doi: 10.1021/acs.jpcb.5b08980. Epub 2015 Dec 10. PMID: 26605982.
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Tunable lanthanide-directed metallosupramolecular networks by exploiting coordinative flexibility through ligand stoichiometry.

Chemical communications (Cambridge, England)

Lyu G, Zhang Q, Urgel JI, Kuang G, Auwärter W, Ecija D, Barth JV, Lin N.
PMID: 26659416
Chem Commun (Camb). 2016 Jan 28;52(8):1618-21. doi: 10.1039/c5cc08526h. Epub 2015 Dec 11.

We report the self-assembly of multi-component lanthanide coordination metallosupramolecular structures on a Au(111) surface. Eu atoms coordinate with two heterotypic ligands of quarterphenyl-4,4''-dicarbonitrile and 4',4''''-(1,4-phenylene)bis(2,2':6',2''-terpyridine). For carbonitrile ligand : terpyridyl stoichiometric ratios of 0.7, Eu atoms are primarily ligated...

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Lyu G, Zhang Q, Urgel JI, et al. Tunable lanthanide-directed metallosupramolecular networks by exploiting coordinative flexibility through ligand stoichiometry. Chem Commun (Camb). 2015;52(8):1618-21doi: 10.1039/c5cc08526h.
Lyu, G., Zhang, Q., Urgel, J. I., Kuang, G., Auwärter, W., Ecija, D., Barth, J. V., & Lin, N. (2016). Tunable lanthanide-directed metallosupramolecular networks by exploiting coordinative flexibility through ligand stoichiometry. Chemical communications (Cambridge, England), 52(8), 1618-21. https://doi.org/10.1039/c5cc08526h
Lyu, Guoqing, et al. "Tunable lanthanide-directed metallosupramolecular networks by exploiting coordinative flexibility through ligand stoichiometry." Chemical communications (Cambridge, England) vol. 52,8 (2016): 1618-21. doi: https://doi.org/10.1039/c5cc08526h
Lyu G, Zhang Q, Urgel JI, Kuang G, Auwärter W, Ecija D, Barth JV, Lin N. Tunable lanthanide-directed metallosupramolecular networks by exploiting coordinative flexibility through ligand stoichiometry. Chem Commun (Camb). 2016 Jan 28;52(8):1618-21. doi: 10.1039/c5cc08526h. Epub 2015 Dec 11. PMID: 26659416.
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Cross-Mapping of Protein - Ligand Binding Data Between ChEMBL and PDBbind.

Molecular informatics

Liu Z, Li J, Liu J, Liu Y, Nie W, Han L, Li Y, Wang R.
PMID: 27490502
Mol Inform. 2015 Aug;34(8):568-76. doi: 10.1002/minf.201500010. Epub 2015 Jun 29.

The ChEMBL database is a valuable open data source, which provides a comprehensive collection of binding data, functional and ADMET properties of bioactive compounds. The PDBbind database has a more focused scope, i.e. collecting binding data for the protein-ligand...

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Liu Z, Li J, Liu J, et al. Cross-Mapping of Protein - Ligand Binding Data Between ChEMBL and PDBbind. Mol Inform. 2015;34(8):568-76doi: 10.1002/minf.201500010.
Liu, Z., Li, J., Liu, J., Liu, Y., Nie, W., Han, L., Li, Y., & Wang, R. (2015). Cross-Mapping of Protein - Ligand Binding Data Between ChEMBL and PDBbind. Molecular informatics, 34(8), 568-76. https://doi.org/10.1002/minf.201500010
Liu, Zhihai, et al. "Cross-Mapping of Protein - Ligand Binding Data Between ChEMBL and PDBbind." Molecular informatics vol. 34,8 (2015): 568-76. doi: https://doi.org/10.1002/minf.201500010
Liu Z, Li J, Liu J, Liu Y, Nie W, Han L, Li Y, Wang R. Cross-Mapping of Protein - Ligand Binding Data Between ChEMBL and PDBbind. Mol Inform. 2015 Aug;34(8):568-76. doi: 10.1002/minf.201500010. Epub 2015 Jun 29. PMID: 27490502.
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Showing 1 to 12 of 36 entries