扭結蛋白是一種複雜的蛋白質摺疊構型。其中，SPOUT蛋白質家族是最著名的例子之一。在先前的研究中，已經藉由有限的蛋白結構來建立SPOUT家族的演化樹。如今，已有更多的SPOUT蛋白結構被解析，使我們更進一步分析SPOUT家族的演化。本研究中，我們使用了PSI-CD-HIT將已知的SPOUT結構進行分群至不同的子家族中，然後使用DALI將個子家族進行結構相似性的分組。多重序列排比方面，同時使用了結構與序列的排比方法來進行。結構排比使用了Swiss-PDB viewer來進行，而序列排比則使用MAFFT，並且同時去除了SPOUT結構域以外的結構域。在結構排比中，我們檢查了SPOUT結構域在結構上的一致性，並且以二級結構作為參照來改進結構的多重排比。之後使用了MrBayes來建立結構演化樹，以及RAxML來建立序列演化樹。最後運用GRASP來重建SPOUT可能的先祖蛋白序列以及用MODELLER來模擬其可能的結構。總體而言，我們改進了SPOUT家族的結構演化樹，並且提供了重建的先祖蛋白序列以及其模型作為進一步研究中合成蛋白的參考。

The knotted proteins are intricate protein foldings. Among these, the SPOUT superfamily is one of the best-known examples of knotted protein structures. The phylogenetic tree of the SPOUT superfamily has been demonstrated by applying limited structures in the previous study. Nowadays, more SPOUT protein structures are solved allowing us to improve the phylogenetic analysis.
In this study, we use the PSI-CD-HIT to cluster the SPOUT structures into different subfamilies and use DALI for the structural similarity grouping of subfamilies. Both structural and sequence alignment methods are used to generate the multiple sequence alignment (MSA). The Swiss-PDB viewer is used for the structural alignment and the MAFFT is used for sequence alignment. The extra domains besides the SPOUT domain are restricted. We examined the conservation of SPOUT domain structure and use secondary structures as references to improve the structural MSA. The structure phylogenetic tree is made by MrBayes and the sequence phylogenetic tree is processed by RAxML. The ancestral sequences of the SPOUT superfamily are reconstructed by the GRASP and models of ancestral sequences are made by MODELLER.
Collectively, we improved the structure phylogenetic tree of the SPOUT superfamily and provide the reconstructed ancestral sequences and the predicted models as references for protein synthesis in further studies.

Abstract ii
Contents iv
1. Introduction 1
1-1. Knot proteins 1
1-2. Categories of knotted protein 3
1-3. SPOUT family 5
1-4. The Bayesian inference and the MCMC Chains 10
1-5. The phylogenetic analysis of SPOUT. 14
1-6. Motivation 16
2. Methods 18
2-1. Collecting known SPOUT PDB dataset 18
2-2. Clustering with CD-HIT and PSI-CD-HIT 18
2-2-1. CD-HIT 18
2-2-2. PSI-CD-HIT 19
2-3. Identified knots by KnotProt 2.0 database 19
2-3-1. Knot regions identify by KnotProt 19
2-3-2. Process custom structure in KnotProt 20
2-4. Structure search by DALI 20
2-4-1. DALI database search 20
2-4-2. DALI Pairwise comparison 22
2-5. BLAST 22
2-5-1. BLAST database search 22
2-5-2. BLAST pairwise comparison 23
2-6. Swiss-PDB viewer 24
2-6-1. Multiple structure alignment by Swiss-PDB viewer v4.1 [50] 24
2-6-2. Manual improvement 24
2-7. Multiple Sequence Alignment by MAFFT 25
2-8. Phylogenetic analysis by MrBayes & RAxML 25
2-8-1. MrBayes 25
2-8-2. RAxML 28
2-9. Ancestral sequence prediction by GRASP 29
2-10. Protein modeling 30
2-10-1. swiss-model 30
2-10-2. MODELLER 30
2-10-3. Remove indel domain and add a modified loop 30
3. Results 32
3-1. The SPOUT PDB dataset clustering 32
3-2. Knot identifying by KnotProt 33
3-3. The DALI Search in PDB Database 39
3-4. The Pairwise Comparison of DALI and BLAST 41
3-5. The Multiple Structure Alignment 45
3-6. MrBayes Phylogenetic Tree Results 56
3-7. The Sequence Phylogenetic Analysis 61
3-8. Ancestral Sequence Reconstruction 69
3-9. The Modeling of Reconstructed Ancestral Proteins 72
4. Discussion 81
4-1. The Comparison of the Phylogenetic Trees 81
4-2. The importance of crossing loop in the protein knot 92
4-3. The common ancestor of SPOUT protein 94
5. Conclusion 97
References 98
Appendix 104

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