Histone Lysine Methyltransferases-Conformational Dynamics and Selective Inhibitor Design for Chromatin-Modifying Enzymes in Lymphomas and Melanomas

Abstract

The long-term objective of this project is to advance the understanding of the biology, therapeutic potential and availability of small molecule drugs for cancer-implicated histone lysine methyltransferases (HKMTs) EZH2 (lymphoma and melanoma target) and SETDB1 (melanoma target). The immediate objective of this project is to present to the scientific community a number of novel small molecule binding modes and pockets in those protein targets, as well as novel small molecule chemical probe scaffolds to hit them. In this report, I show the preparation and data collection in tens of thousands of molecular dynamics trajectories on the distributed computing system Folding@home, and generation of dynamic models of the conformational ensembles of EZH2 and EED, both in apo, and in-complex form (PRC2 complex). I successfully deployed a semi-automatic Markov state model building pipeline on a pilot model system SETD8, hence creating a well sampled, prototypical Markov state model, from which to seed conformations for this project and extract reaction coordinates for adaptive and enhanced sampling simulation runs. I am continuing to refine the models, while building a small molecule ensemble pocket detection docking free energy calculations pipeline to select candidates for screening.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2018
Accession Number
AD1093711

Entities

People

  • Rafal Wiewiora

Organizations

  • Weill Cornell Medicine

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Chemistry
  • Computational Biology
  • Computational Science
  • Crystal Structure
  • Diseases And Disorders
  • Dynamics
  • Energy
  • Free Energy
  • Hidden Markov Models
  • Machine Learning
  • Markov Models
  • Mathematical Models
  • Molecular Dynamics
  • Neoplasms
  • Simulations
  • Small Molecules
  • Trajectories

Fields of Study

  • Chemistry

Readers

  • Distributed Systems and Data Platform Development
  • Molecular and Cellular Biology
  • Molecular and genetic basis of cancer.