In silico fragment-based drug design with SEED

TitleIn silico fragment-based drug design with SEED
Publication TypeJournal Article
Year of Publication2018
AuthorsMarchand J.-R., Caflisch A.
JournalEuropean Journal of Medicinal Chemistry
Volume156
Start Page907
Pagination907-917
Date Published2018 Jul 17
Type of ArticleReview Article
KeywordsFragment docking, Fragment-based drug design, Screening cascade, SEED, SEED2XR, X-ray crystallography
Abstract

We report on two fragment-based drug design protocols, SEED2XR and ALTA, which start by high-throughput docking. SEED2XR is a two-stage protocol for fragment-based drug design. The first stage is in silico and consists of the automatic docking of 103-104 fragments using SEED, which requires about 1 s per fragment. SEED is a docking software developed specifically for fragment docking and binding energy evaluation by a force field with implicit solvent. In the second stage of SEED2XR, the 10-102 fragments with the most favorable predicted binding energies are validated by protein X-ray crystallography. The recent applications of SEED2XR to bromodomains demonstrate that the whole SEED2XR protocol can be carried out in about a week of working time, with hit rates ranging from 10% to 40%. Information on fragment-target interactions generated by the SEED2XR protocol or directly from SEED docking has been used for the discovery of hundreds of hits. ALTA is a computational protocol for screening which identifies candidate ligands that preserve the interactions between the optimal SEED fragments and the protein target. Medicinal chemistry optimization of ligands predicted by ALTA has resulted in pre-clinical candidates for protein kinases and bromodomains. The high-throughput, very low cost, sustainability, and high hit rate of the SEED-based protocols, unreachable by purely experimental techniques, make them perfectly suitable for both academic and industrial drug discovery research.

DOI10.1016/j.ejmech.2018.07.042
pubindex

0238

Alternate JournalEur. J. Med. Chem.
PubMed ID30064119
Highlight Role: 
Drug Design