A Goldilocks Computational Protocol for Inhibitor Discovery Targeting DNA Damage Responses Including Replication-Repair Functions

Authors

Davide Moiani
John A Tainer

Publication Date

1-1-2024

Journal

Frontiers in Molecular Biosciences

Abstract

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.

Keywords

DNA damage response, DNA repair, DNA replication, cancer, computational docking, computational pipeline, in silico testing, precision oncology, cancer, DNA repair, DNA damage response, DNA replication, precision oncology, computational pipeline, computational docking, in silico testing

DOI

10.3389/fmolb.2024.1442267

PMID

39669672

PMCID

PMC11635304

PubMedCentral® Posted Date

11-28-2024

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes