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Docking of Macrocycles: Comparing Rigid and Flexible Docking in Glide
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Organic Pharmaceutical Chemistry.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Organic Pharmaceutical Chemistry.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Organic Pharmaceutical Chemistry.ORCID iD: 0000-0001-6770-0878
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Organic Pharmaceutical Chemistry.ORCID iD: 0000-0002-2885-2016
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2017 (English)In: Journal of Chemical Information and Modeling, ISSN 1549-9596, E-ISSN 1549-960X, Vol. 57, no 2, p. 190-202Article in journal (Refereed) Published
Abstract [en]

In recent years, there has been an increased interest in using macrocyclic compounds for drug discovery and development. For docking of these commonly large and flexible compounds to be addressed, a screening and a validation set were assembled from the PDB consisting of 16 and 31 macrocycle-containing protein complexes, respectively. The macrocycles were docked in Glide by rigid docking of pregenerated conformational ensembles produced by the macrocycle conformational sampling method (MCS) in Schrödinger Release 2015-3 or by direct Glide flexible docking after performing ring-templating. The two protocols were compared to rigid docking of pregenerated conformational ensembles produced by an exhaustive Monte Carlo multiple minimum (MCMM) conformational search and a shorter MCMM conformational search (MCMM-short). The docking accuracy was evaluated and expressed as the RMSD between the heavy atoms of the ligand as found in the X-ray structure after refinement and the poses obtained by the docking protocols. The median RMSD values for top-scored poses of the screening set were 0.83, 0.80, 0.88, and 0.58 Å for MCMM, MCMM-short, MCS, and Glide flexible docking, respectively. There was no statistically significant difference in the performance between rigid docking of pregenerated conformations produced by the MCS and direct docking using Glide flexible docking. However, the flexible docking protocol was 2-times faster in docking the screening set compared to that of the MCS protocol. In a final study, the new Prime-MCS method was evaluated in Schrödinger Release 2016-3. This method is faster compared that of to MCS; however, the conformations generated were found to be suboptimal for rigid docking. Therefore, on the basis of timing, accuracy, and ease of set up, standard Glide flexible docking with prior ring-templating is recommended over current gold standard protocols using rigid docking of pregenerated conformational ensembles.

Place, publisher, year, edition, pages
2017. Vol. 57, no 2, p. 190-202
National Category
Medicinal Chemistry
Identifiers
URN: urn:nbn:se:uu:diva-318050DOI: 10.1021/acs.jcim.6b00443ISI: 000395226100010PubMedID: 28079375OAI: oai:DiVA.org:uu-318050DiVA, id: diva2:1084020
Funder
Swedish Research Council, 521-2014-6711Available from: 2017-03-23 Created: 2017-03-23 Last updated: 2018-03-05Bibliographically approved
In thesis
1. Computational Studies of Macrocycles and Molecular Modeling of Hepatitis C Virus NS3 Protease Inhibitors
Open this publication in new window or tab >>Computational Studies of Macrocycles and Molecular Modeling of Hepatitis C Virus NS3 Protease Inhibitors
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Computational tools are utilized in the drug discovery process to discover, design, and optimize new therapeutics. One important approach is structure-based drug design which relies on knowledge about the 3D structure of the biological target. The first part of this work focuses on applying structure-based drug design for binding mode prediction of HCV NS3 protease inhibitors. The NS3 protease is a challenging target from a computational perspective as it contains an extended binding site. Binding mode predictions were performed for various classes of new acyclic and macrocyclic HCV NS3 protease inhibitors and was used in the design of new inhibitors. None of the synthetized inhibitors have been co-crystallized yet, which has made the evaluation of the suggested binding mode predictions challenging.

Macrocycles are an interesting compound class in drug discovery due to their unique structural architecture, which can enable access to new chemical space. Macrocycles can successfully modulate difficult therapeutic targets, as exemplified in the development of protease inhibitors. Furthermore they can improve drug-like properties, such as cell permeability and bioavailability. The second part of this thesis focuses on macrocycles from a computational point of view. A data set of 47 clinically relevant macrocycles was compiled and used in these studies. First, two different docking protocols rigid docking of pre-generated conformers and flexible docking in Glide were evaluated and compared. The results showed that flexible docking in Glide was sufficient for docking of macrocycles with respect to accuracy and speed.

The aim of the second study was to evaluate and compare the performance of the more general conformational analysis tools, MCMM and MTLMOD, with the recently developed macrocycle-specialized conformational sampling tools, Prime-MCS and MMBS. In most cases, the general conformational analysis tools (with enhanced parameter settings) performed equally well as compared to the macrocycle-specialized conformational sampling techniques. However, MMBS was superior at locating the global energy minimum conformation.

Finally, calculation of the conformational energy penalty of protein-bound macrocycles was performed. The macrocycle data set was complemented with linear analogues that are similar either with respect to physicochemical properties or 2D fingerprints. The conformational energy penalties of these linear analogues were calculated and compared to the conformational energy penalties of the macrocycles. The complete data set of macrocycles and non-macrocycles in this study differ from previously published work addressing conformational energy penalties, since it covers a more extended area of chemical space. Furthermore, there was a weak correlation between the calculated conformational energy penalties and the flexibility of the structures.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 72
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 247
Keywords
Drug discovery, HCV NS3 protease, macrocycles, conformational analysis, docking.
National Category
Medicinal Chemistry
Research subject
Medicinal Chemistry
Identifiers
urn:nbn:se:uu:diva-340865 (URN)978-91-513-0234-8 (ISBN)
Public defence
2018-03-23, B21, BMC, Husargatan 3, Uppsala, 09:15 (Swedish)
Opponent
Supervisors
Available from: 2018-03-02 Created: 2018-02-04 Last updated: 2018-04-03

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Alogheli, HibaOlanders, GustavSchaal, WesleyBrandt, PeterAnders, Karlén

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