Koutsoukas A - Search Results

1

Approaches for machine learning intermolecular interaction energies and application to energy components from symmetry adapted perturbation theory.

Metcalf DP, Koutsoukas A, Spronk SA, Claus BL, Loughney DA, Johnson SR, Cheney DL, Sherrill CD. Metcalf DP, et al. Among authors: koutsoukas a. J Chem Phys. 2020 Feb 21;152(7):074103. doi: 10.1063/1.5142636. J Chem Phys. 2020. PMID: 32087645

2

AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials.

Glick ZL, Metcalf DP, Koutsoukas A, Spronk SA, Cheney DL, Sherrill CD. Glick ZL, et al. Among authors: koutsoukas a. J Chem Phys. 2020 Jul 28;153(4):044112. doi: 10.1063/5.0011521. J Chem Phys. 2020. PMID: 32752707

3

CLIFF: A component-based, machine-learned, intermolecular force field.

Schriber JB, Nascimento DR, Koutsoukas A, Spronk SA, Cheney DL, Sherrill CD. Schriber JB, et al. Among authors: koutsoukas a. J Chem Phys. 2021 May 14;154(18):184110. doi: 10.1063/5.0042989. J Chem Phys. 2021. PMID: 34241025

4

Cartesian message passing neural networks for directional properties: Fast and transferable atomic multipoles.

Glick ZL, Koutsoukas A, Cheney DL, Sherrill CD. Glick ZL, et al. Among authors: koutsoukas a. J Chem Phys. 2021 Jun 14;154(22):224103. doi: 10.1063/5.0050444. J Chem Phys. 2021. PMID: 34241239

5

In-Silico Extraction of Design Ideas Using MMPA-by-QSAR and its Application on ADME Endpoints.

Koutsoukas A, Chang G, Keefer CE. Koutsoukas A, et al. J Chem Inf Model. 2019 Jan 28;59(1):477-485. doi: 10.1021/acs.jcim.8b00520. Epub 2018 Dec 12. J Chem Inf Model. 2019. PMID: 30497262

6

How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space.

Koutsoukas A, Paricharak S, Galloway WR, Spring DR, Ijzerman AP, Glen RC, Marcus D, Bender A. Koutsoukas A, et al. J Chem Inf Model. 2014 Jan 27;54(1):230-42. doi: 10.1021/ci400469u. Epub 2013 Dec 13. J Chem Inf Model. 2014. PMID: 24289493

7

Chemogenomics approaches to rationalizing the mode-of-action of traditional Chinese and Ayurvedic medicines.

Mohd Fauzi F, Koutsoukas A, Lowe R, Joshi K, Fan TP, Glen RC, Bender A. Mohd Fauzi F, et al. Among authors: koutsoukas a. J Chem Inf Model. 2013 Mar 25;53(3):661-73. doi: 10.1021/ci3005513. Epub 2013 Feb 18. J Chem Inf Model. 2013. PMID: 23351136

8

In silico target predictions: defining a benchmarking data set and comparison of performance of the multiclass Naïve Bayes and Parzen-Rosenblatt window.

Koutsoukas A, Lowe R, Kalantarmotamedi Y, Mussa HY, Klaffke W, Mitchell JB, Glen RC, Bender A. Koutsoukas A, et al. J Chem Inf Model. 2013 Aug 26;53(8):1957-66. doi: 10.1021/ci300435j. Epub 2013 Jul 24. J Chem Inf Model. 2013. PMID: 23829430

9

Extending in silico mechanism-of-action analysis by annotating targets with pathways: application to cellular cytotoxicity readouts.

Liggi S, Drakakis G, Koutsoukas A, Cortes-Ciriano I, Martínez-Alonso P, Malliavin TE, Velazquez-Campoy A, Brewerton SC, Bodkin MJ, Evans DA, Glen RC, Carrodeguas JA, Bender A. Liggi S, et al. Among authors: koutsoukas a. Future Med Chem. 2014;6(18):2029-56. doi: 10.4155/fmc.14.137. Future Med Chem. 2014. PMID: 25531967

10

Computer-aided (in silico) approaches in the mode-of-action analysis and safety assessment of ostarine and 4-methylamphetamine.

Mohd Fauzi F, Koutsoukas A, Cunningham A, Gallegos A, Sedefov R, Bender A. Mohd Fauzi F, et al. Among authors: koutsoukas a. Hum Psychopharmacol. 2013 Jul;28(4):365-78. doi: 10.1002/hup.2322. Hum Psychopharmacol. 2013. PMID: 23881885

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