Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation. - Sergei Grudinin; Maria Kadukova; Andreas Eisenbarth; Simon Marillet; Frédéric Cazals (J. Comput. Aided Mol. Des., 2016)

Knodle: A Support Vector Machines-Based Automatic Perception of Organic Molecules from 3D Coordinates. - Maria Kadukova; Sergei Grudinin (J. Chem. Inf. Model., 2016)

Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization. - Maria Kadukova; Sergei Grudinin (J. Comput. Aided Mol. Des., 2017)

Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2. - Maria Kadukova; Sergei Grudinin (J. Comput. Aided Mol. Des., 2018)

Docking rigid macrocycles using Convex-PL, AutoDock Vina, and RDKit in the D3R Grand Challenge 4. - Maria Kadukova; Vladimir Chupin; Sergei Grudinin (J. Comput. Aided Mol. Des., 2020)

VoroCNN: deep convolutional neural network built on 3D Voronoi tessellation of protein structures. - Ilia Igashov; Kliment Olechnovic; Maria Kadukova; Ceslovas Venclovas; Sergei Grudinin (Bioinform., 2021)

KORP-PL: a coarse-grained knowledge-based scoring function for protein-ligand interactions. - Maria Kadukova; Karina dos Santos Machado; Pablo Chacón; Sergei Grudinin (Bioinform., 2021)

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). - Maria Kadukova (2021)

Regression-Based Active Learning for Accessible Acceleration of Ultra-Large Library Docking. - Egor Marin; Margarita Kovaleva; Maria Kadukova; Khalid Mustafin; Polina Khorn; Andrey Rogachev; Alexey Mishin; Albert Guskov; Valentin Borshchevskiy (J. Chem. Inf. Model., 2024)