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Development and Application of Computational Methods in Antitubercular Drug Design: Identification of Novel Inhibitors of Ribonucleotide Reductase
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Organic Pharmaceutical Chemistry.
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Tuberculosis kills approximately 1.7 million people each year around the world making it one of the most lethal infectious diseases. This thesis concerns the development of two computational tools that can support the early stages of drug discovery, and their use in an anti-tubercular drug discovery program.

One of the tools developed is a statistical molecular design (SMD) approach that generates information-rich libraries biased towards a lead structure. The other metod is a post-filtering technique to increase the success of virtual screening, has also been developed. Both methods have been validated using literature data.

Ribonucleotide reductase (RNR) has been identified as a potential anti-tubercular target, and our focus has been to develop small-molecule inhibitors of this target. The enzyme consists of two subunits (a large R1 and a small R2 subunit) that have to associate in order to generate a bioactive complex. It had previously been shown that a heptapeptide corresponding to the small R2 subunits C-terminal inhibited the enzyme. In order to investigate the requirements for inhibitory effect of the peptide a library was designed using the developed SMD approach. The designed library was synthesized and evaluated for biological activity and an OPLS-DA model was derived to understand which positions were most important for activity.

In order to identify small-molecule inhibitors of RNR a combined shape- and structure-based virtual screen was performed, employing ROCS, GlideXP and the developed post-filtering technique. Starting from a library of 1.5 million compounds 24 was acquired and evaluated for enzymatic activity. The best compounds were almost as potent as the starting peptide, but considerably more drug-like.

 

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis , 2009. , p. 68
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 91
National Category
Medicinal Chemistry
Research subject
Medicinal Chemistry
Identifiers
URN: urn:nbn:se:uu:diva-99173ISBN: 978-91-554-7460-7 (print)OAI: oai:DiVA.org:uu-99173DiVA, id: diva2:207664
Public defence
2009-04-24, B22, BMC, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2009-04-02 Created: 2009-03-09 Last updated: 2018-01-13Bibliographically approved
List of papers
1. Focused hierarchical design of peptide libraries - follow the lead
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2007 (English)In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 21, no 10-11, p. 486-495Article in journal (Refereed) Published
Abstract [en]

A novel design strategy based on the hierarchical design of experiments (HDoE) method named focused hierarchical design of experiments (FHDoE) is presented. FHDoE combine two design layers and use focused substitutions to increase the probability of obtaining active peptides when designing libraries through a selection of compounds biased towards a lead structure. Increasing the number of peptides with measurable activity will increase the information gained and the likelihood of constructing good quantitative structure-activity relationship (QSAR) models. The utility of the novel design method is verified using two different approaches. First, a library designed with the novel FHDoE method was compared with libraries generated from classical positional scanning techniques (e.g., alanine scan) as well as with general and centered minimum analog peptide sets (MAPS) libraries by using an example found in the literature. Secondly, the same design strategies were applied to a dataset of 58 angiotensin converting enzyme (ACE) dipeptide inhibitors. QSAR models were generated from designed sublibraries and the activities of the remaining compounds were predicted. These two examples show that the use of FHDoE renders peptide libraries close in physicochemical space to the native ligand, yielding a more thorough screening of the area of interest as compared to the classical positional scans and fractional factorial design (FFD). It is also shown that an FHDoE library of six dipeptides could produce a QSAR model that better described the requisites of high activity ACE inhibitors than could QSAR models built from either a nine-dipeptide library designed with MAPS or a 58-dipeptide library.

Keywords
design of experiments, peptide library design, hierarchical design, amino acid z-scales, PCA
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-17025 (URN)10.1002/cem.1069 (DOI)000250873300009 ()
Available from: 2008-06-15 Created: 2008-06-15 Last updated: 2018-01-12Bibliographically approved
2. Design, synthesis and evaluation of peptide inhibitors of Mycobacterium tuberculosis ribonucleotide reductase
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2007 (English)In: Journal of Peptide Science, ISSN 1075-2617, E-ISSN 1099-1387, Vol. 13, no 12, p. 822-832Article in journal (Refereed) Published
Abstract [en]

Mycobacterium tuberculosis ribonucleotide reductase (RNR) is a potential target for new antitubercular drugs. Herein we describe the synthesis and evaluation of peptide inhibitors of RNR derived from the C-terminus of the small subunit of M. tuberculosis RNR. An N-terminal truncation, an alanine scan and a novel statistical molecular design (SMD) approach based on the heptapeptide Ac-Glu-Asp-Asp-Asp-Trp-Asp-Phe-OH were applied in this study. The alanine scan showed that TrP5 and Phe7 were important for inhibitory potency. A quantitative structure relationship (QSAR) model was developed based on the synthesized peptides which showed that a negative charge in positions 2, 3, and 6 is beneficial for inhibitory potency. Finally, in position 5 the model coefficients indicate that there is room for a larger side chain., as compared to Trp5.

Keywords
mycobacterium tuberculosis, ribonucleotide reductase, peptide inhibitors, alanine scan, statistical molecular design, structure activity relationships, FHDoE
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-14261 (URN)10.1002/psc.906 (DOI)000252000600007 ()17918768 (PubMedID)
Available from: 2008-05-29 Created: 2008-05-29 Last updated: 2018-01-12Bibliographically approved
3.
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4. Identification of novel non-peptidic inhibitors of M. tuberculosis ribonucleotide reductase via a combined shape and structure based virtual screen
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(English)Manuscript (Other (popular science, discussion, etc.))
Identifiers
urn:nbn:se:uu:diva-99311 (URN)
Available from: 2009-03-11 Created: 2009-03-11 Last updated: 2010-01-14

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