Quantitative Structure–Activity Relationship (QSAR) Modeling of Chiral CCR2 Antagonists with a Multidimensional Space of Novel Chirality Descriptors by Ramanathan Natarajan, Ganapathy S. Natarajan, Subhash C. Basak

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Machine learning based QSAR and Molecular Dynamics simulations in the structural design and mechanism of action of imidazole derivatives with anti-melanoma activity by Rosalvo Ferreira de Oliveira Neto, Sérgio Ruschi Bergamachi Silva, Cintia Emi Yanaguibashi Leal, Edilson Beserra de Alencar Filho

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Novel (Q)SAR models for prediction of reversible and time-dependent inhibition of cytochrome P450 enzymes by Sadegh Faramarzi, Arianna Bassan, Kevin P. Cross, Xinning Yang, Glenn J. Myatt, Donna A. Volpe, Lidiya Stavitskaya

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QSPR/QSAR study of antiviral drugs modeled as multigraphs by using TI’s and MLR method to treat COVID-19 disease by Ugasini Preetha P, M. Suresh, Fikadu Tesgera Tolasa, Ebenezer Bonyah

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CombinatorixPy: Advancing mixture descriptors for computational chemistry by Rahil Ashtari Mahini, Gerardo Casanola-Martin, Stephen Szwiec, Simone A. Ludwig, Bakhtiyor Rasulev

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A Simple Machine Learning-Based Quantitative Structure–Activity Relationship Model for Predicting pIC₅₀ Inhibition Values of FLT3 Tyrosine Kinase by Jackson J. Alcázar, Ignacio Sánchez, Cristian Merino, Bruno Monasterio, Gaspar Sajuria, Diego Miranda, Felipe Díaz, Paola R. Campodónico

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One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening by James Wellnitz, Sankalp Jain, Joshua E. Hochuli, Travis Maxfield, Eugene N. Muratov, Alexander Tropsha, Alexey V. Zakharov

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Rational design of novel phenol ether derivatives as non-covalent proteasome inhibitors through 3D-QSAR, molecular docking and ADMET prediction by Miao Yuan, Hanwen Ji, Fengxin Sun, Qiang Chen, Ping Cheng

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