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2020 – today
- 2024
[j8]Egor Marin
, Margarita Kovaleva, Maria Kadukova, Khalid Mustafin, Polina Khorn, Andrey Rogachev, Alexey Mishin, Albert Guskov, Valentin Borshchevskiy:
Regression-Based Active Learning for Accessible Acceleration of Ultra-Large Library Docking. J. Chem. Inf. Model. 64(7): 2612-2623 (2024)- 2021
- [b1]Maria Kadukova:
Development of novel algorithms for data-driven prediction of interactions between proteins and small molecules. (Développement de nouveaux modèles, basés sur les données, pour prédire les interactions entre protéines et petites molécules). Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation, 2021 - [j7]Maria Kadukova, Karina dos Santos Machado, Pablo Chacón, Sergei Grudinin:
KORP-PL: a coarse-grained knowledge-based scoring function for protein-ligand interactions. Bioinform. 37(7): 943-950 (2021) - [j6]Ilia Igashov, Kliment Olechnovic, Maria Kadukova, Ceslovas Venclovas, Sergei Grudinin:
VoroCNN: deep convolutional neural network built on 3D Voronoi tessellation of protein structures. Bioinform. 37(16): 2332-2339 (2021) - 2020
- [j5]Maria Kadukova, Vladimir Chupin, Sergei Grudinin:
Docking rigid macrocycles using Convex-PL, AutoDock Vina, and RDKit in the D3R Grand Challenge 4. J. Comput. Aided Mol. Des. 34(2): 191-200 (2020)
2010 – 2019
- 2018
- [j4]Maria Kadukova, Sergei Grudinin:
Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2. J. Comput. Aided Mol. Des. 32(1): 151-162 (2018) - 2017
- [j3]Maria Kadukova, Sergei Grudinin:
Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization. J. Comput. Aided Mol. Des. 31(10): 943-958 (2017) - 2016
- [j2]Sergei Grudinin, Maria Kadukova, Andreas Eisenbarth, Simon Marillet, Frédéric Cazals:
Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation. J. Comput. Aided Mol. Des. 30(9): 791-804 (2016) - [j1]Maria Kadukova, Sergei Grudinin:
Knodle: A Support Vector Machines-Based Automatic Perception of Organic Molecules from 3D Coordinates. J. Chem. Inf. Model. 56(8): 1410-1419 (2016)
Coauthor Index
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