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Validation strategies for target prediction methods.

Briefings in bioinformatics

Mathai N, Chen Y, Kirchmair J.
PMID: 31220208
Brief Bioinform. 2020 May 21;21(3):791-802. doi: 10.1093/bib/bbz026.

Computational methods for target prediction, based on molecular similarity and network-based approaches, machine learning, docking and others, have evolved as valuable and powerful tools to aid the challenging task of mode of action identification for bioactive small molecules such...

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Mathai N, Chen Y, Kirchmair J. Validation strategies for target prediction methods. Brief Bioinform. 2020;21(3):791-802doi: 10.1093/bib/bbz026.
Mathai, N., Chen, Y., & Kirchmair, J. (2020). Validation strategies for target prediction methods. Briefings in bioinformatics, 21(3), 791-802. https://doi.org/10.1093/bib/bbz026
Mathai, Neann, et al. "Validation strategies for target prediction methods." Briefings in bioinformatics vol. 21,3 (2020): 791-802. doi: https://doi.org/10.1093/bib/bbz026
Mathai N, Chen Y, Kirchmair J. Validation strategies for target prediction methods. Brief Bioinform. 2020 May 21;21(3):791-802. doi: 10.1093/bib/bbz026. PMID: 31220208; PMCID: PMC7299289.
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Small-world phenomena in chemical library networks: application to fragment-based drug discovery.

Journal of chemical information and modeling

Tanaka N, Ohno K, Niimi T, Moritomo A, Mori K, Orita M.
PMID: 19961207
J Chem Inf Model. 2009 Dec;49(12):2677-86. doi: 10.1021/ci900123v.

A wide variety of networks in various fields have been characterized as small-world networks. In scale-free networks, a representative class of small-world networks, numbers of contacts (degree distributions) of nodes follow power laws. Although several examples of power-law distributions...

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Tanaka N, Ohno K, Niimi T, et al. Small-world phenomena in chemical library networks: application to fragment-based drug discovery. J Chem Inf Model. 2009;49(12):2677-86doi: 10.1021/ci900123v.
Tanaka, N., Ohno, K., Niimi, T., Moritomo, A., Mori, K., & Orita, M. (2009). Small-world phenomena in chemical library networks: application to fragment-based drug discovery. Journal of chemical information and modeling, 49(12), 2677-86. https://doi.org/10.1021/ci900123v
Tanaka, Naoki, et al. "Small-world phenomena in chemical library networks: application to fragment-based drug discovery." Journal of chemical information and modeling vol. 49,12 (2009): 2677-86. doi: https://doi.org/10.1021/ci900123v
Tanaka N, Ohno K, Niimi T, Moritomo A, Mori K, Orita M. Small-world phenomena in chemical library networks: application to fragment-based drug discovery. J Chem Inf Model. 2009 Dec;49(12):2677-86. doi: 10.1021/ci900123v. PMID: 19961207.
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Next generation diversity-oriented synthesis: a paradigm shift from chemical diversity to biological diversity.

Organic & biomolecular chemistry

Pavlinov I, Gerlach EM, Aldrich LN.
PMID: 30328455
Org Biomol Chem. 2019 Feb 13;17(7):1608-1623. doi: 10.1039/c8ob02327a.

Diversity-oriented synthesis has historically focused on the generation of small-molecule collections with considerable scaffold, stereochemical, and appendage diversity. Recently, this focus has begun to shift to the production of small-molecule libraries with diverse biological activities. It is currently not...

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Pavlinov I, Gerlach EM, Aldrich LN. Next generation diversity-oriented synthesis: a paradigm shift from chemical diversity to biological diversity. Org Biomol Chem. 2019;17(7):1608-1623doi: 10.1039/c8ob02327a.
Pavlinov, I., Gerlach, E. M., & Aldrich, L. N. (2019). Next generation diversity-oriented synthesis: a paradigm shift from chemical diversity to biological diversity. Organic & biomolecular chemistry, 17(7), 1608-1623. https://doi.org/10.1039/c8ob02327a
Pavlinov, Ivan, et al. "Next generation diversity-oriented synthesis: a paradigm shift from chemical diversity to biological diversity." Organic & biomolecular chemistry vol. 17,7 (2019): 1608-1623. doi: https://doi.org/10.1039/c8ob02327a
Pavlinov I, Gerlach EM, Aldrich LN. Next generation diversity-oriented synthesis: a paradigm shift from chemical diversity to biological diversity. Org Biomol Chem. 2019 Feb 13;17(7):1608-1623. doi: 10.1039/c8ob02327a. PMID: 30328455.
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Targeted protein degradation: A promise for undruggable proteins.

Cell chemical biology

Samarasinghe KTG, Crews CM.
PMID: 34004187
Cell Chem Biol. 2021 Jul 15;28(7):934-951. doi: 10.1016/j.chembiol.2021.04.011. Epub 2021 May 17.

Protein homeostasis, or "proteostasis," is indispensable for a balanced, healthy environment within the cell. However, when natural proteostasis mechanisms are overwhelmed from excessive loads of dysregulated proteins, their accumulation can lead to disease initiation and progression. Recently, the induced...

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Samarasinghe KTG, Crews CM. Targeted protein degradation: A promise for undruggable proteins. Cell Chem Biol. 2021;28(7):934-951doi: 10.1016/j.chembiol.2021.04.011.
Samarasinghe, K. T. G., & Crews, C. M. (2021). Targeted protein degradation: A promise for undruggable proteins. Cell chemical biology, 28(7), 934-951. https://doi.org/10.1016/j.chembiol.2021.04.011
Samarasinghe, Kusal T G, and Crews, Craig M. "Targeted protein degradation: A promise for undruggable proteins." Cell chemical biology vol. 28,7 (2021): 934-951. doi: https://doi.org/10.1016/j.chembiol.2021.04.011
Samarasinghe KTG, Crews CM. Targeted protein degradation: A promise for undruggable proteins. Cell Chem Biol. 2021 Jul 15;28(7):934-951. doi: 10.1016/j.chembiol.2021.04.011. Epub 2021 May 17. PMID: 34004187; PMCID: PMC8286327.
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Rapid Identification of Potential Drug Candidates from Multi-Million Compounds' Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening.

Molecules (Basel, Switzerland)

Szilágyi K, Flachner B, Hajdú I, Szaszkó M, Dobi K, Lőrincz Z, Cseh S, Dormán G.
PMID: 34577064
Molecules. 2021 Sep 15;26(18). doi: 10.3390/molecules26185593.

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost-effective approach in early drug discovery. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compounds' databases....

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Szilágyi K, Flachner B, Hajdú I, et al. Rapid Identification of Potential Drug Candidates from Multi-Million Compounds' Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening. Molecules. 2021;26(18)doi: 10.3390/molecules26185593.
Szilágyi, K., Flachner, B., Hajdú, I., Szaszkó, M., Dobi, K., Lőrincz, Z., Cseh, S., & Dormán, G. (2021). Rapid Identification of Potential Drug Candidates from Multi-Million Compounds' Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening. Molecules (Basel, Switzerland), 26(18), . https://doi.org/10.3390/molecules26185593
Szilágyi, Katalin, et al. "Rapid Identification of Potential Drug Candidates from Multi-Million Compounds' Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening." Molecules (Basel, Switzerland) vol. 26,18 (2021). doi: https://doi.org/10.3390/molecules26185593
Szilágyi K, Flachner B, Hajdú I, Szaszkó M, Dobi K, Lőrincz Z, Cseh S, Dormán G. Rapid Identification of Potential Drug Candidates from Multi-Million Compounds' Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening. Molecules. 2021 Sep 15;26(18). doi: 10.3390/molecules26185593. PMID: 34577064; PMCID: PMC8468386.
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The expanding world of small molecule microarrays.

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

Uttamchandani M, Yao SQ.
PMID: 20857353
Methods Mol Biol. 2010;669:1-15. doi: 10.1007/978-1-60761-845-4_1.

Speed and throughput are vital ingredients for discovery-driven, "-omics" research. The small molecule microarray is one such platform, which delivers phenomenal screening throughput and capabilities. The concept at the heart of the technology is elegant, yet simple: by presenting...

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Uttamchandani M, Yao SQ. The expanding world of small molecule microarrays. Methods Mol Biol. 2010;669:1-15doi: 10.1007/978-1-60761-845-4_1.
Uttamchandani, M., & Yao, S. Q. (2010). The expanding world of small molecule microarrays. Methods in molecular biology (Clifton, N.J.), 6691-15. https://doi.org/10.1007/978-1-60761-845-4_1
Uttamchandani, Mahesh, and Yao, Shao Q. "The expanding world of small molecule microarrays." Methods in molecular biology (Clifton, N.J.) vol. 669 (2010): 1-15. doi: https://doi.org/10.1007/978-1-60761-845-4_1
Uttamchandani M, Yao SQ. The expanding world of small molecule microarrays. Methods Mol Biol. 2010;669:1-15. doi: 10.1007/978-1-60761-845-4_1. PMID: 20857353.
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QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics.

BMC bioinformatics

O'Reilly PG, Wen Q, Bankhead P, Dunne PD, McArt DG, McPherson S, Hamilton PW, Mills KI, Zhang SD.
PMID: 27143038
BMC Bioinformatics. 2016 May 04;17(1):198. doi: 10.1186/s12859-016-1062-1.

BACKGROUND: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds,...

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O'Reilly PG, Wen Q, Bankhead P, et al. QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics. BMC Bioinformatics. 2016;17(1):198doi: 10.1186/s12859-016-1062-1.
O'Reilly, P. G., Wen, Q., Bankhead, P., Dunne, P. D., McArt, D. G., McPherson, S., Hamilton, P. W., Mills, K. I., & Zhang, S. D. (2016). QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics. BMC bioinformatics, 17(1), 198. https://doi.org/10.1186/s12859-016-1062-1
O'Reilly, Paul G, et al. "QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics." BMC bioinformatics vol. 17,1 (2016): 198. doi: https://doi.org/10.1186/s12859-016-1062-1
O'Reilly PG, Wen Q, Bankhead P, Dunne PD, McArt DG, McPherson S, Hamilton PW, Mills KI, Zhang SD. QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics. BMC Bioinformatics. 2016 May 04;17(1):198. doi: 10.1186/s12859-016-1062-1. PMID: 27143038; PMCID: PMC4855472.
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Engineering the Next Generation of Matched Models for Chemical Translational Biology.

Chembiochem : a European journal of chemical biology

Downes DP.
PMID: 33184916
Chembiochem. 2021 Feb 15;22(4):642. doi: 10.1002/cbic.202000520. Epub 2020 Nov 13.

In order to achieve patient personalization and translate compounds through the discovery phase into the clinic, high throughput test models should be designed to be as closely matched to the patient as possible. Engineering high throughput and physiologically relevant...

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Downes DP. Engineering the Next Generation of Matched Models for Chemical Translational Biology. Chembiochem. 2020;22(4):642doi: 10.1002/cbic.202000520.
Downes, D. P. (2021). Engineering the Next Generation of Matched Models for Chemical Translational Biology. Chembiochem : a European journal of chemical biology, 22(4), 642. https://doi.org/10.1002/cbic.202000520
Downes, Daniel P. "Engineering the Next Generation of Matched Models for Chemical Translational Biology." Chembiochem : a European journal of chemical biology vol. 22,4 (2021): 642. doi: https://doi.org/10.1002/cbic.202000520
Downes DP. Engineering the Next Generation of Matched Models for Chemical Translational Biology. Chembiochem. 2021 Feb 15;22(4):642. doi: 10.1002/cbic.202000520. Epub 2020 Nov 13. PMID: 33184916.
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Drug startups coalesce around condensates.

Nature biotechnology

Dolgin E.
PMID: 33564162
Nat Biotechnol. 2021 Feb;39(2):123-125. doi: 10.1038/s41587-021-00828-4.

No abstract available.

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Dolgin E. Drug startups coalesce around condensates. Nat Biotechnol. 2021;39(2):123-125doi: 10.1038/s41587-021-00828-4.
Dolgin, E. (2021). Drug startups coalesce around condensates. Nature biotechnology, 39(2), 123-125. https://doi.org/10.1038/s41587-021-00828-4
Dolgin, Elie. "Drug startups coalesce around condensates." Nature biotechnology vol. 39,2 (2021): 123-125. doi: https://doi.org/10.1038/s41587-021-00828-4
Dolgin E. Drug startups coalesce around condensates. Nat Biotechnol. 2021 Feb;39(2):123-125. doi: 10.1038/s41587-021-00828-4. PMID: 33564162.
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Next Generation of Small-Molecule Fluorogenic Probes for Bioimaging.

Biochemistry

Li L, Sun H.
PMID: 31603310
Biochemistry. 2020 Jan 28;59(3):216-217. doi: 10.1021/acs.biochem.9b00831. Epub 2019 Oct 11.

No abstract available.

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Li L, Sun H. Next Generation of Small-Molecule Fluorogenic Probes for Bioimaging. Biochemistry. 2019;59(3):216-217doi: 10.1021/acs.biochem.9b00831.
Li, L., & Sun, H. (2020). Next Generation of Small-Molecule Fluorogenic Probes for Bioimaging. Biochemistry, 59(3), 216-217. https://doi.org/10.1021/acs.biochem.9b00831
Li, Lin, and Sun, Hongyan. "Next Generation of Small-Molecule Fluorogenic Probes for Bioimaging." Biochemistry vol. 59,3 (2020): 216-217. doi: https://doi.org/10.1021/acs.biochem.9b00831
Li L, Sun H. Next Generation of Small-Molecule Fluorogenic Probes for Bioimaging. Biochemistry. 2020 Jan 28;59(3):216-217. doi: 10.1021/acs.biochem.9b00831. Epub 2019 Oct 11. PMID: 31603310.
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Where Do Recent Small Molecule Clinical Development Candidates Come From?.

Journal of medicinal chemistry

Brown DG, Boström J.
PMID: 29920198
J Med Chem. 2018 Nov 08;61(21):9442-9468. doi: 10.1021/acs.jmedchem.8b00675. Epub 2018 Jul 09.

An analysis of 66 published clinical candidates from Journal of Medicinal Chemistry has been conducted to shed light on which lead generation strategies are most frequently employed in identifying drug candidates. The most frequent lead generation strategy (producing a...

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Brown DG, Boström J. Where Do Recent Small Molecule Clinical Development Candidates Come From?. J Med Chem. 2018;61(21):9442-9468doi: 10.1021/acs.jmedchem.8b00675.
Brown, D. G., & Boström, J. (2018). Where Do Recent Small Molecule Clinical Development Candidates Come From?. Journal of medicinal chemistry, 61(21), 9442-9468. https://doi.org/10.1021/acs.jmedchem.8b00675
Brown, Dean G, and Boström, Jonas. "Where Do Recent Small Molecule Clinical Development Candidates Come From?." Journal of medicinal chemistry vol. 61,21 (2018): 9442-9468. doi: https://doi.org/10.1021/acs.jmedchem.8b00675
Brown DG, Boström J. Where Do Recent Small Molecule Clinical Development Candidates Come From?. J Med Chem. 2018 Nov 08;61(21):9442-9468. doi: 10.1021/acs.jmedchem.8b00675. Epub 2018 Jul 09. PMID: 29920198.
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Don't Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models.

Molecules (Basel, Switzerland)

Humbeck L, Morawietz T, Sturm N, Zalewski A, Harnqvist S, Heyndrickx W, Holmes M, Beck B.
PMID: 34834051
Molecules. 2021 Nov 18;26(22). doi: 10.3390/molecules26226959.

Machine learning models predicting the bioactivity of chemical compounds belong nowadays to the standard tools of cheminformaticians and computational medicinal chemists. Multi-task and federated learning are promising machine learning approaches that allow privacy-preserving usage of large amounts of data...

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Humbeck L, Morawietz T, Sturm N, et al. Don't Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models. Molecules. 2021;26(22)doi: 10.3390/molecules26226959.
Humbeck, L., Morawietz, T., Sturm, N., Zalewski, A., Harnqvist, S., Heyndrickx, W., Holmes, M., & Beck, B. (2021). Don't Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models. Molecules (Basel, Switzerland), 26(22), . https://doi.org/10.3390/molecules26226959
Humbeck, Lina, et al. "Don't Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models." Molecules (Basel, Switzerland) vol. 26,22 (2021). doi: https://doi.org/10.3390/molecules26226959
Humbeck L, Morawietz T, Sturm N, Zalewski A, Harnqvist S, Heyndrickx W, Holmes M, Beck B. Don't Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models. Molecules. 2021 Nov 18;26(22). doi: 10.3390/molecules26226959. PMID: 34834051; PMCID: PMC8620420.
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Showing 1 to 12 of 12 entries