Article

From Latent Manifolds to Functional Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework for Family-Targeted Kinase Inhibitor Design

2026-01-07

Abstract excerpt

The design of selective kinase inhibitors remains a formidable challenge due to the high structural conservation of the ATP-binding site across the kinome. While modern generative AI has enabled rapid exploration of chemical space, many advanced models operate as black boxes, obscuring the chemical rationale behind design choices and limiting interpretability. To explore these bottlenecks, we present a modular, ge...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 15c421da-8d37-586c-acda-1cd851a64e6a
DOI: 10.64898/2026.01.06.698033

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

From Latent Manifolds to Functional Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework for Family-Targeted Kinase Inhibitor DesignDOI 10.64898/2026.01.06.698033Read

From Latent Manifolds to Functional Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework for Family-Targeted Kinase Inhibitor DesignSemantic proximity Read

EvoSynth: Enabling Multi-Target Drug Discovery through Latent Evolutionary Optimization and Synthesis-Aware PrioritizationSemantic proximity Read

Pocket-based molecule generation with an SE(3)-equivariant language model leads to a potent and selective HPK1 inhibitor with <i>in vivo</i> efficacySemantic proximity Read

Programming Biomolecular Interactions with All-Atom Generative ModelSemantic proximity Read

Structure-free, site-resolved contrastive learning extends small-molecule discovery beyond the reach of structure-based modelingSemantic proximity Read

DrugHIVE: Target-specific spatial drug design and optimization with a hierarchical generative modelSemantic proximity Read

Systematic Benchmarking of Kinase Bioactivity Models Across Splitting Strategies and Protein RepresentationsSemantic proximity Read

Generative AI for Drug Discovery and Protein Design: The Next Frontier in AI-Driven Molecular ScienceSemantic proximity Read

Generative Drug Design in a Loop with dtSFMSemantic proximity Read

ProChoreo: <i>de novo</i> Binder Design from Conformational Ensembles with Generative Deep LearningSemantic proximity Read

Bayesian active learning-aided structure-based virtual screening reveals novel inhibitors of mutant IDH1.Semantic proximity Read

A Drug–Target Specificity Foundation Model for Off-target Prediction, Repurposing, and Generative DesignSemantic proximity Read