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Acta Crystallographica Section B, Structural Science, Crystal Engineering and Materials
|
April 1, 2017
The evaluation of QM/MM-driven molecular docking combined with MM/GBSA calculations as a halogen-bond scoring strategy
Rafał Kurczab
Journal of Medicinal Chemistry
|
July 31, 2024
Halogen Bonding Hot Spots as a Constraint in Virtual Screening: A Case Study of 5-HT<sub>7</sub>R
Rafał Kurczab
Molecules (Basel, Switzerland)
|
April 3, 2021
Mutual Support of Ligand- and Structure-Based Approaches-To What Extent We Can Optimize the Power of Predictive Model? Case Study of Opioid Receptors
Sabina Podlewska, Rafał Kurczab
Journal of Chemical Information and Modeling
|
November 5, 2025
Developing a Hybrid Molecular Representation Combining Chemical Structure and MIR Spectral Data: A LogP Prediction Case Study
Kacper Tomaszewski, Rafał Kurczab
Plos One
|
April 7, 2017
The influence of the negative-positive ratio and screening database size on the performance of machine learning-based virtual screening
Rafał Kurczab, Andrzej J Bojarski
Journal of Chemical Information and Modeling
|
November 20, 2013
New strategy for receptor-based pharmacophore query construction: a case study for 5-HT₇ receptor ligands
Rafał Kurczab, Andrzej J Bojarski
Journal of Chemical Information and Modeling
|
September 17, 2025
From NMR to AI: Fusing <sup>1</sup>H and <sup>13</sup>C Representations for Enhanced QSPR Modeling
Arkadiusz Leniak, Wojciech Pietruś, Rafał Kurczab
Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
|
September 27, 2025
Fluorine-induced perturbations in hydrogen bond networks: Insights from FT-IR, Raman, and AIMD simulations
Wojciech Pietruś, Ewa Machalska, Rafał Kurczab
Journal of Chemical Information and Modeling
|
March 26, 2024
From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties
Arkadiusz Leniak, Wojciech Pietruś, Rafał Kurczab
Journal of Cheminformatics
|
April 9, 2013
The influence of the inactives subset generation on the performance of machine learning methods
Sabina Smusz, Rafał Kurczab, Andrzej J Bojarski
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Search research articles
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Showing results (1-10 of 83) with videos related to
Sort By:
Page
of 9
Acta Crystallographica Section B, Structural Science, Crystal Engineering and Materials
|
April 1, 2017
The evaluation of QM/MM-driven molecular docking combined with MM/GBSA calculations as a halogen-bond scoring strategy
Rafał Kurczab
Journal of Medicinal Chemistry
|
July 31, 2024
Halogen Bonding Hot Spots as a Constraint in Virtual Screening: A Case Study of 5-HT<sub>7</sub>R
Rafał Kurczab
Molecules (Basel, Switzerland)
|
April 3, 2021
Mutual Support of Ligand- and Structure-Based Approaches-To What Extent We Can Optimize the Power of Predictive Model? Case Study of Opioid Receptors
Sabina Podlewska, Rafał Kurczab
Journal of Chemical Information and Modeling
|
November 5, 2025
Developing a Hybrid Molecular Representation Combining Chemical Structure and MIR Spectral Data: A LogP Prediction Case Study
Kacper Tomaszewski, Rafał Kurczab
Plos One
|
April 7, 2017
The influence of the negative-positive ratio and screening database size on the performance of machine learning-based virtual screening
Rafał Kurczab, Andrzej J Bojarski
Journal of Chemical Information and Modeling
|
November 20, 2013
New strategy for receptor-based pharmacophore query construction: a case study for 5-HT₇ receptor ligands
Rafał Kurczab, Andrzej J Bojarski
Journal of Chemical Information and Modeling
|
September 17, 2025
From NMR to AI: Fusing <sup>1</sup>H and <sup>13</sup>C Representations for Enhanced QSPR Modeling
Arkadiusz Leniak, Wojciech Pietruś, Rafał Kurczab
Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
|
September 27, 2025
Fluorine-induced perturbations in hydrogen bond networks: Insights from FT-IR, Raman, and AIMD simulations
Wojciech Pietruś, Ewa Machalska, Rafał Kurczab
Journal of Chemical Information and Modeling
|
March 26, 2024
From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties
Arkadiusz Leniak, Wojciech Pietruś, Rafał Kurczab
Journal of Cheminformatics
|
April 9, 2013
The influence of the inactives subset generation on the performance of machine learning methods
Sabina Smusz, Rafał Kurczab, Andrzej J Bojarski
Page
of 9