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Full-Text Articles in Medicinal-Pharmaceutical Chemistry
Interpretable Machine Learning Models For Molecular Design Of Tyrosine Kinase Inhibitors Using Variational Autoencoders And Perturbation-Based Approach Of Chemical Space Exploration, Keerthi Krishnan, Ryan Kassab, Steve Agajanian, Gennady M. Verkhivker
Interpretable Machine Learning Models For Molecular Design Of Tyrosine Kinase Inhibitors Using Variational Autoencoders And Perturbation-Based Approach Of Chemical Space Exploration, Keerthi Krishnan, Ryan Kassab, Steve Agajanian, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
In the current study, we introduce an integrative machine learning strategy for the autonomous molecular design of protein kinase inhibitors using variational autoencoders and a novel cluster-based perturbation approach for exploration of the chemical latent space. The proposed strategy combines autoencoder-based embedding of small molecules with a cluster-based perturbation approach for efficient navigation of the latent space and a feature-based kinase inhibition likelihood classifier that guides optimization of the molecular properties and targeted molecular design. In the proposed generative approach, molecules sharing similar structures tend to cluster in the latent space, and interpolating between two molecules in the latent space …
Ensemble-Based Modeling And Rigidity Decomposition Of Allosteric Interaction Networks And Communication Pathways In Cyclin-Dependent Kinases: Differentiating Kinase Clients Of The Hsp90-Cdc37 Chaperone, Gabrielle Stetz, Amanda Tse, Gennady M. Verkhivker
Ensemble-Based Modeling And Rigidity Decomposition Of Allosteric Interaction Networks And Communication Pathways In Cyclin-Dependent Kinases: Differentiating Kinase Clients Of The Hsp90-Cdc37 Chaperone, Gabrielle Stetz, Amanda Tse, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
The overarching goal of delineating molecular principles underlying differentiation of protein kinase clients and chaperone-based modulation of kinase activity is fundamental to understanding activity of many oncogenic kinases that require chaperoning of Hsp70 and Hsp90 systems to attain a functionally competent active form. Despite structural similarities and common activation mechanisms shared by cyclin-dependent kinase (CDK) proteins, members of this family can exhibit vastly different chaperone preferences. The molecular determinants underlying chaperone dependencies of protein kinases are not fully understood as structurally similar kinases may often elicit distinct regulatory responses to the chaperone. The regulatory divergences observed for members of CDK …