Journal Publications

- Claude Bernard -

“The joy of discovery is certainly the liveliest that the mind of man can ever feel”

PUBLICATIONS

57. Van Den Driessche G, Fourches D. Adverse drug reactions triggered by the common HLA-B*57:01 variant: virtual screening of DrugBank using 3D molecular docking. Journal of Cheminformatics. 2018, In Press. Read Here.

 

56. Mahapatra D, Franzosa JA, Roell K, Kuenemann MA, Houck KA, Reif DM, Fourches D, Kullman SW. Confirmation of high-throughput screening data and novel mechanistic insights into VDR-xenobiotic interactions by orthogonal assays. Sci Rep. 2018, 8, 8883. Read Here.

 

55. Rachel Marceau West, Wenbin Lu, Daniel M. Rotroff, Melaine Kuenemann, Sheng-Mao Chang, Michael J. Wagner, John B. Buse, Alison Motsinger-Reif, Denis Fourches, Jung-Ying Tzeng. Identifying individual risk rare variants using protein structure-guided local tests (POINT). 2018, Preprint. Read Here.

 

54. La MK, Sedykh A, Fourches D, Muratov E, Tropsha A. Predicting Adverse Drug Effects from Literature- and Database-Mined Assertions.Drug Saf. 2018. Read Here.

 

53. Borrel A, Kleinstreuer N, Fourches D. Exploring Drug Spaced with ChemMaps.com. Bioinformatics. 2018. Read Here.

 

52. Kuenemann MA, Spears PA, Orndorff PE, Fourches D. In silico Predicted Glucose-1-phosphate Uridylyltransferase (GalU) Inhibitors Block a Key Pathway Required for Listeria Virulence. Mol. Inf. 2018, 37, 1800004. Read Here.

 

51. Kuenemann M. A., Fourches D. Cheminformatics Analysis of Dynamic WNK-Inhibitor Interactions. Mol. Inf. 2018, 37, 1700138. Read Here.

 

50. Tova N. Williams, Melaine A. Kuenemann, George A. Van Den Driessche, Antony J. Williams, Denis Fourches, and Harold S. Freeman. Toward the Rational Design of Sustainable Hair Dyes Using Cheminformatics Approaches: Step 1. Database Development and Analysis. ACS Sustainable Chem. Eng., 2018, 6, 2344–2352. Read Here.

 

49. Van Den Driessche G, Fourches D. Adverse drug reactions triggered by the common HLA-B*57:01 variant: virtual screening of DrugBank using 3D molecular docking. Journal of Cheminformatics. 2018. Read Here.

 

48. Fourches, D. Reaction: Molecular Modeling for Novel Antibacterials. Chem. 2017, 3, 13-14. Read Here.

 

47. Borrel, A.; Fourches, D.; RealityConvert: A tool for preparing 3D models of biochemical structures for augmented and virtual reality. Bioinformatics. 2017, 33, 3816–3818. Read Here.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

46. Jeremy Ash and Denis Fourches. Characterizing the Chemical Space of ERK2 Kinase
Inhibitors Using Descriptors Computed from Molecular Dynamics Trajectories. J Chem Inf Model. 2017, 57, 1286-1299. ACS Editor's Choice. Read Here

 

 

 

 

 

 

 

 

 

 

45. Kuenemann, M. A.; Szymczyk, M.; Chen, Y.; Sultana, N.; Hinks, D.; Freeman, H. S.; Williams, A. J.; Fourches, D.; Vinueza, N. R. Weaver's historic accessible collection of synthetic dyes: a cheminformatics analysis. Chem. Sci. 2017, 8, 4334-4339. Read Here

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

44. George Van Den Driessche and Denis Fourches. Adverse drug reactions triggered by the common HLA-B*57:01 variant: a molecular docking study. Journal of Cheminformatics, 2017, 9:1-13. Read Here

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

43. Melaine Kuenemann and Denis Fourches. Cheminformatics Modeling of Amine Solutions for
Assessing their CO2 Absorption Properties. Molecular Informatics, 2017, 36:1-13. Read Here

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

42.  Alves VM, Muratov E, Capuzzi S, Politi R, Low Y, Braga R, Zakharov A, Sedykh A, Mokshyna E, Farag S, Andrade C, Kuz'min V, Fourches D, Tropsha A.  Alarms about structural alerts. Green Chem., 2016,18, 4348-4360. Read here

 

41. Braga RC, Alves VM, Silva MF, Muratov E, Fourches D, Lião LM, Tropsha A, Andrade CH. Pred-hERG: A Novel web-Accessible Computational Tool for Predicting Cardiac Toxicity. Mol Inform. 2015 Oct;34(10):698-701.

 

40. Fourches D, Muratov E, Tropsha A. Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation. J Chem Inf Model. 2016 Jul 25;56(7):1243-52

 

39. Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg SA, Slavov S, Hu X, Judson RS. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environ Health Perspect. 2016 Jul;124(7):1023-33.

 

38. Elkins JM, Fedele V, Szklarz M, Abdul Azeez KR, Salah E, Mikolajczyk J, Romanov S, Sepetov N, Huang XP, Roth BL, Al Haj Zen A, Fourches D, Muratov E, Tropsha A, Morris J, Teicher BA, Kunkel M, Polley E, Lackey KE, Atkinson FL, Overington JP, Bamborough P, Müller S, Price DJ, Willson TM, Drewry DH, Knapp S, Zuercher WJ. Comprehensive characterization of the Published Kinase Inhibitor Set. Nat Biotechnol. 2016 Jan;34(1):95-103.

 

37. L.Low, O.Caster, T.Bergvall, D.Fourches, X.Zang, G.Norén, I.Rusyn, R.Edwards, A.Tropsha. Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome. J Am Med Inform Assoc, 2016, 23(5), 968-78.

 

36. D.Fourches, D.Pu, L.Li, H.Zhou, Q.Mu, G.Su, B.Yan, and A.Tropsha. Computer-Aided Design of Carbon Nanotubes with the Desired Bioactivity and Safety Profiles. Nanotoxicology, 2016, 10(3), 374-83.

 

35. D.Fourches, E. Muratov, A.Tropsha. Curation of Chemogenomics Data. Nature Chemical Biology. 2015, 11, 535.

 

34. O.Isayev, D.Fourches, E.Muratov, S.Curtarolo, A.Tropsha. Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints. ACS Chemistry of Materials, 2015, 27 (3), 735–743. ACS Editor’s Choice

 

33. V.M.Alves, E.N.Muratov, D.Fourches, J.Strickland, N.Kleinstreuer, C.H.Andrade, and A.Tropsha. QSAR Models of Skin Permeability and their Application to Identifying Potentially Hazardous Chemicals. Chemosphere. EHP. Toxicol Appl Pharmacol., 2015, In Press.

 

32. V.M.Alves, E.N.Muratov, D.Fourches, J.Strickland, N.Kleinstreuer, C.H.Andrade, and A.Tropsha. QSAR Models of Skin Sensitization their Application to Identifying Potentially Hazardous Chemicals. Toxicol Appl Pharmacol., 2015, In Press.

 

31. N.C.Baker, D.Fourches, and A.Tropsha. Drug side effect profiles as molecular descriptors for predictive cheminformatics modeling. Molecular Informatics, 2015, In Press.

 

30. D.Fourches, R.Politi, A.Tropsha. Target-Specific Native/Decoy Pose Classifier Improves the Accuracy of Ligand Ranking in the CSAR2013 Benchmark. J. Chem. Inf. Model. 2014, In Press

 

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