English

Scaffold-Induced Molecular Graph (SIMG): Effective Graph Sampling Methods for High-Throughput Computational Drug Discovery

Quantitative Methods 2021-09-13 v1 Biomolecules

Abstract

Scaffold based drug discovery (SBDD) is a technique for drug discovery which pins chemical scaffolds as the framework of design. Scaffolds, or molecular frameworks, organize the design of compounds into local neighborhoods. We formalize scaffold based drug discovery into a network design. Utilizing docking data from SARS-CoV-2 virtual screening studies and JAK2 kinase assay data, we showcase how a scaffold based conception of chemical space is intuitive for design. Lastly, we highlight the utility of scaffold based networks for chemical space as a potential solution to the intractable enumeration problem of chemical space by working inductively on local neighborhoods.

Keywords

Cite

@article{arxiv.2109.05012,
  title  = {Scaffold-Induced Molecular Graph (SIMG): Effective Graph Sampling Methods for High-Throughput Computational Drug Discovery},
  author = {Austin Clyde and Ashka Shah and Max Zvyagin and Arvind Ramanathan and Rick Stevens},
  journal= {arXiv preprint arXiv:2109.05012},
  year   = {2021}
}
R2 v1 2026-06-24T05:52:05.713Z