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Research article
Enrichments of Ensemble Docking Strategy Based on the Bayesian Model
Zhili Zuo
Kunming Institute of Botany Chinese Academy of Sciences
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3576-2884
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Motivation
Challenges remained in structure-based drug discovery which include protein flexibility in binding site. Thus, concerning the flexibility of proteins, docking into an ensemble of rigid conformations (ensemble docking) have been proposed with incorporation into protein flexibility with expects that it could provide higher enrichments than rigid single receptor. Here we have developed the ensemble docking strategy by using Bayesian Model algorithms, and this method is validated by three proteins: BTK, JAK and PARP. The Bayesian Model was used to integrate independent docking runs of an ensemble of rigid crystal structures and MD simulations.
Results
The structure of MD simulations outperforms the crystal structures in separating inhibitors from decoys in BTK and PARP. Further, the results demonstrated that the ensemble docking strategy has better performance than rigid single conformation.
Keywords
ensemble docking, Bayesian Model, correlation analysis, ROC curve
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CURRENT STATUS: Under Review
Version 1
Posted 05 Jan, 2021
No community comments so far
Review #1 received
Received 17 Jan, 2021
Reviewer #1 agreed
On 04 Jan, 2021
Reviewers invited
Invitations sent on 03 Jan, 2021
First submitted
On 28 Dec, 2020
Editor assigned
On 28 Dec, 2020
Submission checks complete
On 28 Dec, 2020
Editor invited
On 28 Dec, 2020
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Subject Areas
Chemical Engineering
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This preprint is under consideration at Journal of Cheminformatics. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Enrichments of Ensemble Docking Strategy Based on the Bayesian Model
Zhili Zuo
Kunming Institute of Botany Chinese Academy of Sciences
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3576-2884
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 05 Jan, 2021
No community comments so far
Review #1 received
Received 17 Jan, 2021
Reviewer #1 agreed
On 04 Jan, 2021
Reviewers invited
Invitations sent on 03 Jan, 2021
First submitted
On 28 Dec, 2020
Editor assigned
On 28 Dec, 2020
Submission checks complete
On 28 Dec, 2020
Editor invited
On 28 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Chemical Engineering
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Motivation
Challenges remained in structure-based drug discovery which include protein flexibility in binding site. Thus, concerning the flexibility of proteins, docking into an ensemble of rigid conformations (ensemble docking) have been proposed with incorporation into protein flexibility with expects that it could provide higher enrichments than rigid single receptor. Here we have developed the ensemble docking strategy by using Bayesian Model algorithms, and this method is validated by three proteins: BTK, JAK and PARP. The Bayesian Model was used to integrate independent docking runs of an ensemble of rigid crystal structures and MD simulations.
Results
The structure of MD simulations outperforms the crystal structures in separating inhibitors from decoys in BTK and PARP. Further, the results demonstrated that the ensemble docking strategy has better performance than rigid single conformation.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8