Fragment Binding Pose Predictions Using Unbiased Simulations
and Markov-State Models
Posted on 2019-08-22 - 18:35
Predicting
the costructure of small-molecule ligands and their
respective target proteins has been a long-standing problem in drug
discovery. For weak binding compounds typically identified in fragment-based
screening (FBS) campaigns, determination of the correct binding site
and correct binding mode is usually done experimentally via X-ray
crystallography. For many targets of pharmaceutical interest, however,
establishing an X-ray system which allows for sufficient throughput
to support a drug discovery project is not possible. In this case,
exploration of fragment hits becomes a very laborious and consequently
slow process with the generation of protein/ligand cocrystal structures
as the bottleneck of the entire process. In this work, we introduce
a computational method which is able to reliably predict binding sites
and binding modes of fragment-like small molecules using solely the
structure of the apoprotein and the ligand’s chemical structure
as input information. The method is based on molecular dynamics simulations
and Markov-state models and can be run as a fully automated protocol
requiring minimal human intervention. We describe the application
of the method to a representative subset of different target classes
and fragments from historical FBS efforts at Boehringer Ingelheim
and discuss its potential integration into the overall fragment-based
drug discovery workflow.
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Linker, Stephanie
Maria; Magarkar, Aniket; Köfinger, Jürgen; Hummer, Gerhard; Seeliger, Daniel (2019). Fragment Binding Pose Predictions Using Unbiased Simulations
and Markov-State Models. ACS Publications. Collection. https://doi.org/10.1021/acs.jctc.9b00069
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AUTHORS (5)
SL
Stephanie
Maria Linker
AM
Aniket Magarkar
JK
Jürgen Köfinger
GH
Gerhard Hummer
DS
Daniel Seeliger
KEYWORDS
target classestarget proteinsdrug discoveryfragment-based drug discovery workflowinput informationUnbiased Simulationsfragment-based screeningFBS effortsbinding sitesmethodbinding modesmall-molecule ligandsMarkov-State ModelsMarkov-state modelsbinding compoundsbinding modesrepresentative subsetX-ray crystallographydynamics simulationsbinding sitefragment hitsdrug discovery projectFragment Binding Pose PredictionsX-ray systemBoehringer Ingelheim