University of Groningen Aggregate, automate, assemble Kroon, Peter

University of Groningen

Aggregate, automate, assemble

Kroon, Peter

DOI:

10.33612/diss.132963667

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Publication date: 2020

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):

Kroon, P. (2020). Aggregate, automate, assemble. University of Groningen. https://doi.org/10.33612/diss.132963667

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Aggregate

Assemble

Automate

Peter Cornelis Kroon

Aggregate, assemble, automate

PhD thesis

to obtain the degree of PhD at the

University of Groningen

on the authority of the

Rector Magnificus prof. C. Wijmenga

and in accordance with

the decision by the College of Deans.

This thesis will be defended in public on

Friday 12 June 2020 at 12:45 hours

by

Peter Cornelis Kroon

born on 6 November 1990

in Groningen, the Netherlands

The work described in this thesis was performed in the molecular dynamics

research group of the Groningen biomolecular sciences and biotechnology

institute, and the systems chemistry research group of the Stratingh institute

for chemistry, both at the University of Groningen, the Netherlands.

This work was funded by the Zernike institute for advanced materials at the

University of Groningen, the Netherlands.

ISBN: 978-94-034-2581-8 (printed version)

ISBN: 978-94-034-2580-1 (electronic version)

Printing: Ridderprint, www.ridderprint.nl

Cover: Randy Wind, Native Development

Copyright © 2020 Peter C Kroon

Aggregate, assemble, automate

PhD thesis

to obtain the degree of PhD at the

University of Groningen

on the authority of the

Rector Magnificus prof. C. Wijmenga

and in accordance with

the decision by the College of Deans.

This thesis will be defended in public on

Friday 02 October 2020 at 12:45 hours

by

Peter Cornelis Kroon

born on 6 November 1990

in Groningen, the Netherlands

Supervisors

Prof. S.J. Marrink

Prof. S. Otto

Assessment Committee

Prof. P.R. Onck

Prof. L.R.B. Schomaker

Prof. D.P. Tieleman

5

Contents

1 - Introduction

. . . 8

References

. . . 12

2 - Martinize 2 – VerMoUTH

. . . . 16

2.1 Introduction

. . . . 18

2.2 Implementation

. . . 22

2.2.1 Step 1: Parse input. . . . 23

2.2.2 Step 2: Identify and repair. . . . 23

2.2.3 Step 3: Resolution transformation . . . 25

2.2.4 Step 4: Create topology. . . . 27

2.2.5 Step 5: Post-processing. . . . 28

2.2.6 Step 6: Write output . . . 28

2.3 Graph algorithms

. . . 28

2.3.1 Largest common induced subgraph. . . . 29

2.3.2 Graph covering . . . 31

2.4 Examples

. . . . 31

2.4.1 A small linear peptide, Neurokinin A . . . 32

2.4.2 A cyclic peptide with post-translational modifications, Pneumocandin B0 . . 34

2.5 Conclusions and Outlook

. . . . 36

2.6 References

. . . 37

Appendix A: Sample code. . . 41

Appendix B: Sample code. . . 48

3 - Cartographer

. . . . 54

3.1 Introduction

. . . . 56

3.1.1 Existing clustering methods and considerations . . . 59

3.1.2 K-means clustering. . . . 60

3.1.3 Hierarchical clustering . . . 61

3.1.4 Graph coarse-graining . . . 61

3.1.5 Robust Perron cluster analysis . . . 61

3.2 Methods and Results

. . . 62

3.2.1 Training data . . . 63

3.2.2 Machine learning. . . . 63

3.2.3 Clustering validation. . . . 66

3.2.4 Produced mappings . . . 69

6

3.4 Conclusions

. . . 73

3.5 Acknowledgements

. . . . 74

3.6 References

. . . 74

Appendix A: Expert mappings for seven molecules . . . 78

Appendix B: Rounding to the nearest rational number. . . 82

4 - Self-replicating dynamic covalent macrocycles

. . . . 84

4.1 Introduction

. . . . 86

4.2 Results

. . . . 88

4.2.1 UA MD simulations . . . 88

4.2.2 CG MD simulations. . . . 89

4.3 Discussion and conclusions

. . . 92

4.4 Acknowledgements

. . . . 93

4.5 References

. . . 93

Appendix A: Methods . . . 96

Appendix B: Martini force field parameters. . . 99

5 - Summary

. . . 104

6 - Samenvatting

. . . 106

7 - Glossary

. . . 110