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Showing 1 to 12 of 37 entries
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DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies.

Bioinformatics (Oxford, England)

Fu C, Jin G, Gao J, Zhu R, Ballesteros-Villagrana E, Wong ST.
PMID: 23681121
Bioinformatics. 2013 Jul 15;29(14):1834-6. doi: 10.1093/bioinformatics/btt279. Epub 2013 May 15.

SUMMARY: Systematic studies of drug repositioning require the integration of multi-level drug data, including basic chemical information (such as SMILES), drug targets, target-related signaling pathways, clinical trial information and Food and Drug Administration (FDA)-approval information, to predict new potential...

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Fu C, Jin G, Gao J, et al. DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies. Bioinformatics. 2013;29(14):1834-6doi: 10.1093/bioinformatics/btt279.
Fu, C., Jin, G., Gao, J., Zhu, R., Ballesteros-Villagrana, E., & Wong, S. T. (2013). DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies. Bioinformatics (Oxford, England), 29(14), 1834-6. https://doi.org/10.1093/bioinformatics/btt279
Fu, Changhe, et al. "DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies." Bioinformatics (Oxford, England) vol. 29,14 (2013): 1834-6. doi: https://doi.org/10.1093/bioinformatics/btt279
Fu C, Jin G, Gao J, Zhu R, Ballesteros-Villagrana E, Wong ST. DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies. Bioinformatics. 2013 Jul 15;29(14):1834-6. doi: 10.1093/bioinformatics/btt279. Epub 2013 May 15. PMID: 23681121; PMCID: PMC3702253.
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Drug repurposing from the perspective of pharmaceutical companies.

British journal of pharmacology

Cha Y, Erez T, Reynolds IJ, Kumar D, Ross J, Koytiger G, Kusko R, Zeskind B, Risso S, Kagan E, Papapetropoulos S, Grossman I, Laifenfeld D.
PMID: 28369768
Br J Pharmacol. 2018 Jan;175(2):168-180. doi: 10.1111/bph.13798. Epub 2017 May 18.

Drug repurposing holds the potential to bring medications with known safety profiles to new patient populations. Numerous examples exist for the identification of new indications for existing molecules, most stemming from serendipitous findings or focused recent efforts specifically limited...

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Cha Y, Erez T, Reynolds IJ, et al. Drug repurposing from the perspective of pharmaceutical companies. Br J Pharmacol. 2017;175(2):168-180doi: 10.1111/bph.13798.
Cha, Y., Erez, T., Reynolds, I. J., Kumar, D., Ross, J., Koytiger, G., Kusko, R., Zeskind, B., Risso, S., Kagan, E., Papapetropoulos, S., Grossman, I., & Laifenfeld, D. (2018). Drug repurposing from the perspective of pharmaceutical companies. British journal of pharmacology, 175(2), 168-180. https://doi.org/10.1111/bph.13798
Cha, Y, et al. "Drug repurposing from the perspective of pharmaceutical companies." British journal of pharmacology vol. 175,2 (2018): 168-180. doi: https://doi.org/10.1111/bph.13798
Cha Y, Erez T, Reynolds IJ, Kumar D, Ross J, Koytiger G, Kusko R, Zeskind B, Risso S, Kagan E, Papapetropoulos S, Grossman I, Laifenfeld D. Drug repurposing from the perspective of pharmaceutical companies. Br J Pharmacol. 2018 Jan;175(2):168-180. doi: 10.1111/bph.13798. Epub 2017 May 18. PMID: 28369768; PMCID: PMC5758385.
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Taking Advantage of Databases.

Methods in molecular biology (Clifton, N.J.)

Myatt GJ, Quigley DP.
PMID: 27311475
Methods Mol Biol. 2016;1425:383-430. doi: 10.1007/978-1-4939-3609-0_17.

Toxicity databases are a useful resource to support hazard and risk assessment. They are used to retrieve historical studies for compounds of interest and to support toxicity predictions where no data exists. Toxicity predictions are either based upon study...

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Myatt GJ, Quigley DP. Taking Advantage of Databases. Methods Mol Biol. 2016;1425:383-430doi: 10.1007/978-1-4939-3609-0_17.
Myatt, G. J., & Quigley, D. P. (2016). Taking Advantage of Databases. Methods in molecular biology (Clifton, N.J.), 1425383-430. https://doi.org/10.1007/978-1-4939-3609-0_17
Myatt, Glenn J, and Quigley, Donald P. "Taking Advantage of Databases." Methods in molecular biology (Clifton, N.J.) vol. 1425 (2016): 383-430. doi: https://doi.org/10.1007/978-1-4939-3609-0_17
Myatt GJ, Quigley DP. Taking Advantage of Databases. Methods Mol Biol. 2016;1425:383-430. doi: 10.1007/978-1-4939-3609-0_17. PMID: 27311475.
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Improving data mining strategies for drug design.

Future medicinal chemistry

Bajorath J.
PMID: 24575962
Future Med Chem. 2014 Mar;6(3):255-7. doi: 10.4155/fmc.13.208.

No abstract available.

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Bajorath J. Improving data mining strategies for drug design. Future Med Chem. 2014;6(3):255-7doi: 10.4155/fmc.13.208.
Bajorath, J. (2014). Improving data mining strategies for drug design. Future medicinal chemistry, 6(3), 255-7. https://doi.org/10.4155/fmc.13.208
Bajorath, Jürgen. "Improving data mining strategies for drug design." Future medicinal chemistry vol. 6,3 (2014): 255-7. doi: https://doi.org/10.4155/fmc.13.208
Bajorath J. Improving data mining strategies for drug design. Future Med Chem. 2014 Mar;6(3):255-7. doi: 10.4155/fmc.13.208. PMID: 24575962.
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On the Unreported-Profile-is-Negative Assumption for Predictive Cheminformatics.

IEEE/ACM transactions on computational biology and bioinformatics

Lan C, Chandrasekaran SN, Huan J.
PMID: 31056508
IEEE/ACM Trans Comput Biol Bioinform. 2020 Jul-Aug;17(4):1352-1363. doi: 10.1109/TCBB.2019.2913855. Epub 2019 Apr 30.

In cheminformatics, compound-target binding profiles has been a main source of data for research. For data repositories that only provide positive profiles, a popular assumption is that unreported profiles are all negative. In this paper, we caution the audience...

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Lan C, Chandrasekaran SN, Huan J. On the Unreported-Profile-is-Negative Assumption for Predictive Cheminformatics. IEEE/ACM Trans Comput Biol Bioinform. 2019;17(4):1352-1363doi: 10.1109/TCBB.2019.2913855.
Lan, C., Chandrasekaran, S. N., & Huan, J. (2020). On the Unreported-Profile-is-Negative Assumption for Predictive Cheminformatics. IEEE/ACM transactions on computational biology and bioinformatics, 17(4), 1352-1363. https://doi.org/10.1109/TCBB.2019.2913855
Lan, Chao, et al. "On the Unreported-Profile-is-Negative Assumption for Predictive Cheminformatics." IEEE/ACM transactions on computational biology and bioinformatics vol. 17,4 (2020): 1352-1363. doi: https://doi.org/10.1109/TCBB.2019.2913855
Lan C, Chandrasekaran SN, Huan J. On the Unreported-Profile-is-Negative Assumption for Predictive Cheminformatics. IEEE/ACM Trans Comput Biol Bioinform. 2020 Jul-Aug;17(4):1352-1363. doi: 10.1109/TCBB.2019.2913855. Epub 2019 Apr 30. PMID: 31056508.
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A systematic approach to orient the human protein-protein interaction network.

Nature communications

Silverbush D, Sharan R.
PMID: 31289271
Nat Commun. 2019 Jul 09;10(1):3015. doi: 10.1038/s41467-019-10887-6.

The protein-protein interaction (PPI) network of an organism serves as a skeleton for its signaling circuitry, which mediates cellular response to environmental and genetic cues. Understanding this circuitry could improve the prediction of gene function and cellular behavior in...

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Silverbush D, Sharan R. A systematic approach to orient the human protein-protein interaction network. Nat Commun. 2019;10(1):3015doi: 10.1038/s41467-019-10887-6.
Silverbush, D., & Sharan, R. (2019). A systematic approach to orient the human protein-protein interaction network. Nature communications, 10(1), 3015. https://doi.org/10.1038/s41467-019-10887-6
Silverbush, Dana, and Sharan, Roded. "A systematic approach to orient the human protein-protein interaction network." Nature communications vol. 10,1 (2019): 3015. doi: https://doi.org/10.1038/s41467-019-10887-6
Silverbush D, Sharan R. A systematic approach to orient the human protein-protein interaction network. Nat Commun. 2019 Jul 09;10(1):3015. doi: 10.1038/s41467-019-10887-6. PMID: 31289271; PMCID: PMC6617457.
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The CSD Drug Subset: The Changing Chemistry and Crystallography of Small Molecule Pharmaceuticals.

Journal of pharmaceutical sciences

Bryant MJ, Black SN, Blade H, Docherty R, Maloney AGP, Taylor SC.
PMID: 30615878
J Pharm Sci. 2019 May;108(5):1655-1662. doi: 10.1016/j.xphs.2018.12.011. Epub 2019 Jan 05.

We report the generation and statistical analysis of the CSD drug subset: a subset of the Cambridge Structural Database (CSD) consisting of every published small-molecule crystal structure containing an approved drug molecule. By making use of InChI matching, a...

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Bryant MJ, Black SN, Blade H, et al. The CSD Drug Subset: The Changing Chemistry and Crystallography of Small Molecule Pharmaceuticals. J Pharm Sci. 2019;108(5):1655-1662doi: 10.1016/j.xphs.2018.12.011.
Bryant, M. J., Black, S. N., Blade, H., Docherty, R., Maloney, A. G. P., & Taylor, S. C. (2019). The CSD Drug Subset: The Changing Chemistry and Crystallography of Small Molecule Pharmaceuticals. Journal of pharmaceutical sciences, 108(5), 1655-1662. https://doi.org/10.1016/j.xphs.2018.12.011
Bryant, Mathew J, et al. "The CSD Drug Subset: The Changing Chemistry and Crystallography of Small Molecule Pharmaceuticals." Journal of pharmaceutical sciences vol. 108,5 (2019): 1655-1662. doi: https://doi.org/10.1016/j.xphs.2018.12.011
Bryant MJ, Black SN, Blade H, Docherty R, Maloney AGP, Taylor SC. The CSD Drug Subset: The Changing Chemistry and Crystallography of Small Molecule Pharmaceuticals. J Pharm Sci. 2019 May;108(5):1655-1662. doi: 10.1016/j.xphs.2018.12.011. Epub 2019 Jan 05. PMID: 30615878.
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Prediction of synthetic accessibility based on commercially available compound databases.

Journal of chemical information and modeling

Fukunishi Y, Kurosawa T, Mikami Y, Nakamura H.
PMID: 25420000
J Chem Inf Model. 2014 Dec 22;54(12):3259-67. doi: 10.1021/ci500568d. Epub 2014 Dec 03.

A compound's synthetic accessibility (SA) is an important aspect of drug design, since in some cases computer-designed compounds cannot be synthesized. There have been several reports on SA prediction, most of which have focused on the difficulties of synthetic...

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Fukunishi Y, Kurosawa T, Mikami Y, et al. Prediction of synthetic accessibility based on commercially available compound databases. J Chem Inf Model. 2014;54(12):3259-67doi: 10.1021/ci500568d.
Fukunishi, Y., Kurosawa, T., Mikami, Y., & Nakamura, H. (2014). Prediction of synthetic accessibility based on commercially available compound databases. Journal of chemical information and modeling, 54(12), 3259-67. https://doi.org/10.1021/ci500568d
Fukunishi, Yoshifumi, et al. "Prediction of synthetic accessibility based on commercially available compound databases." Journal of chemical information and modeling vol. 54,12 (2014): 3259-67. doi: https://doi.org/10.1021/ci500568d
Fukunishi Y, Kurosawa T, Mikami Y, Nakamura H. Prediction of synthetic accessibility based on commercially available compound databases. J Chem Inf Model. 2014 Dec 22;54(12):3259-67. doi: 10.1021/ci500568d. Epub 2014 Dec 03. PMID: 25420000.
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Medicinal and Biological Chemistry (MBC) Library: An Efficient Source of New Hits.

Journal of chemical information and modeling

Sebastián-Pérez V, Roca C, Awale M, Reymond JL, Martinez A, Gil C, Campillo NE.
PMID: 28813151
J Chem Inf Model. 2017 Sep 25;57(9):2143-2151. doi: 10.1021/acs.jcim.7b00401. Epub 2017 Aug 30.

Identification of new hits is one of the biggest challenges in drug discovery. Creating a library of well-characterized drug-like compounds is a key step in this process. Our group has developed an in-house chemical library called the Medicinal and...

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Sebastián-Pérez V, Roca C, Awale M, et al. Medicinal and Biological Chemistry (MBC) Library: An Efficient Source of New Hits. J Chem Inf Model. 2017;57(9):2143-2151doi: 10.1021/acs.jcim.7b00401.
Sebastián-Pérez, V., Roca, C., Awale, M., Reymond, J. L., Martinez, A., Gil, C., & Campillo, N. E. (2017). Medicinal and Biological Chemistry (MBC) Library: An Efficient Source of New Hits. Journal of chemical information and modeling, 57(9), 2143-2151. https://doi.org/10.1021/acs.jcim.7b00401
Sebastián-Pérez, Víctor, et al. "Medicinal and Biological Chemistry (MBC) Library: An Efficient Source of New Hits." Journal of chemical information and modeling vol. 57,9 (2017): 2143-2151. doi: https://doi.org/10.1021/acs.jcim.7b00401
Sebastián-Pérez V, Roca C, Awale M, Reymond JL, Martinez A, Gil C, Campillo NE. Medicinal and Biological Chemistry (MBC) Library: An Efficient Source of New Hits. J Chem Inf Model. 2017 Sep 25;57(9):2143-2151. doi: 10.1021/acs.jcim.7b00401. Epub 2017 Aug 30. PMID: 28813151.
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Drug databases and their contributions to drug repurposing.

Genomics

Masoudi-Sobhanzadeh Y, Omidi Y, Amanlou M, Masoudi-Nejad A.
PMID: 31226485
Genomics. 2020 Mar;112(2):1087-1095. doi: 10.1016/j.ygeno.2019.06.021. Epub 2019 Jun 18.

Drug repurposing is an interesting field in the drug discovery scope because of reducing time and cost. It is also considered as an appropriate method for finding medications for orphan and rare diseases. Hence, many researchers have proposed novel...

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Masoudi-Sobhanzadeh Y, Omidi Y, Amanlou M, et al. Drug databases and their contributions to drug repurposing. Genomics. 2019;112(2):1087-1095doi: 10.1016/j.ygeno.2019.06.021.
Masoudi-Sobhanzadeh, Y., Omidi, Y., Amanlou, M., & Masoudi-Nejad, A. (2020). Drug databases and their contributions to drug repurposing. Genomics, 112(2), 1087-1095. https://doi.org/10.1016/j.ygeno.2019.06.021
Masoudi-Sobhanzadeh, Yosef, et al. "Drug databases and their contributions to drug repurposing." Genomics vol. 112,2 (2020): 1087-1095. doi: https://doi.org/10.1016/j.ygeno.2019.06.021
Masoudi-Sobhanzadeh Y, Omidi Y, Amanlou M, Masoudi-Nejad A. Drug databases and their contributions to drug repurposing. Genomics. 2020 Mar;112(2):1087-1095. doi: 10.1016/j.ygeno.2019.06.021. Epub 2019 Jun 18. PMID: 31226485.
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Platform for Unified Molecular Analysis: PUMA.

Journal of chemical information and modeling

González-Medina M, Medina-Franco JL.
PMID: 28737911
J Chem Inf Model. 2017 Aug 28;57(8):1735-1740. doi: 10.1021/acs.jcim.7b00253. Epub 2017 Aug 08.

We introduce a free platform for chemoinformatic-based diversity analysis and visualization of chemical space of user supplied data sets. Platform for Unified Molecular Analysis (PUMA) integrates metrics used to characterize compound databases including visualization of chemical space, scaffold content,...

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González-Medina M, Medina-Franco JL. Platform for Unified Molecular Analysis: PUMA. J Chem Inf Model. 2017;57(8):1735-1740doi: 10.1021/acs.jcim.7b00253.
González-Medina, M., & Medina-Franco, J. L. (2017). Platform for Unified Molecular Analysis: PUMA. Journal of chemical information and modeling, 57(8), 1735-1740. https://doi.org/10.1021/acs.jcim.7b00253
González-Medina, Mariana, and Medina-Franco, José L. "Platform for Unified Molecular Analysis: PUMA." Journal of chemical information and modeling vol. 57,8 (2017): 1735-1740. doi: https://doi.org/10.1021/acs.jcim.7b00253
González-Medina M, Medina-Franco JL. Platform for Unified Molecular Analysis: PUMA. J Chem Inf Model. 2017 Aug 28;57(8):1735-1740. doi: 10.1021/acs.jcim.7b00253. Epub 2017 Aug 08. PMID: 28737911.
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Connection Map for Compounds (CMC): A Server for Combinatorial Drug Toxicity and Efficacy Analysis.

Journal of chemical information and modeling

Liu L, Tsompana M, Wang Y, Wu D, Zhu L, Zhu R.
PMID: 27508329
J Chem Inf Model. 2016 Sep 26;56(9):1615-21. doi: 10.1021/acs.jcim.6b00397. Epub 2016 Aug 19.

Drug discovery and development is a costly and time-consuming process with a high risk for failure resulting primarily from a drug's associated clinical safety and efficacy potential. Identifying and eliminating inapt candidate drugs as early as possible is an...

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Liu L, Tsompana M, Wang Y, et al. Connection Map for Compounds (CMC): A Server for Combinatorial Drug Toxicity and Efficacy Analysis. J Chem Inf Model. 2016;56(9):1615-21doi: 10.1021/acs.jcim.6b00397.
Liu, L., Tsompana, M., Wang, Y., Wu, D., Zhu, L., & Zhu, R. (2016). Connection Map for Compounds (CMC): A Server for Combinatorial Drug Toxicity and Efficacy Analysis. Journal of chemical information and modeling, 56(9), 1615-21. https://doi.org/10.1021/acs.jcim.6b00397
Liu, Lei, et al. "Connection Map for Compounds (CMC): A Server for Combinatorial Drug Toxicity and Efficacy Analysis." Journal of chemical information and modeling vol. 56,9 (2016): 1615-21. doi: https://doi.org/10.1021/acs.jcim.6b00397
Liu L, Tsompana M, Wang Y, Wu D, Zhu L, Zhu R. Connection Map for Compounds (CMC): A Server for Combinatorial Drug Toxicity and Efficacy Analysis. J Chem Inf Model. 2016 Sep 26;56(9):1615-21. doi: 10.1021/acs.jcim.6b00397. Epub 2016 Aug 19. PMID: 27508329.
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Showing 1 to 12 of 37 entries