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1. Introduction
2. The concept of information
3. Three related concepts
4. What the three concepts have in common
5. Example
6. Brand A
7. Brand B
8. Comparative variety
9. Diversity, variety, uncertainty, choice
10. Application to protein sequences
11. Multiple sequence alignment
12. Hb family - multiple sequence alignment
13. 2nd Example
14. Portion of Hb MSA, positions 13, 18, and 21
15. Amino acid counts
16. Brand "Hb MSA position 13"
17. Brand "Hb MSA position 18"
18. Brand "Hb MSA position 21"
19. Comparative variety
20. Calculating "effective number"
21. Counting kinds - entropy
22. Counting kinds - uncertainty
23. Entropy - definition
24. Purpose
25. Sequence variation in Hb
26. Variability of sequences from selected families
27. The nature of variation
28. Three examples of nonsense
29. Comparison to English sentences
30. Lower entropy
31. What kinds of patters reduce entropy?
32. Conservative substitutions
33. Amino acid substitution matrices
34. Blosum62 matrix
35. Extracting similarity
36. Amino acid similarity circle
37. Information
38. Characteristics of information
39. How is information measured?
40. Measuring information from a "stand in"
41. Two correlated collections
42. Example: codon middle base and hydrophobicity
43. Genetic code vs. amino acid hydrophobicity
44. Codon properties
45. Codon properties - comparison
46. Collection 1 - codon middle base
47. Brand codon - middle-base
48. Collection 2 - amino acid solubility
49. Brand amino acid - water solubility
50. Correlation between R-Y and hydrophobicity
51. Matches/mismatches between properties
52. Brand correlated
53. What distribution results from random association
54. Brand no-correlation
55. Technical definition of information
56. Brands correlated vs. uncorrelated
57. Hydrophobicity information provided by middle base
58. Meaning of entropy and information - summary
59. Application - blast
60. Blast - bit score
61. Application - correlated substitutions
62. Multiple sequence alignment
63. Old concept: strict constraints
64. New concept: few constraints
65. Hypothetical multiple sequence alignment
66. Zooming in, MSA
67. Zooming in equilibrium site
68. Conserved site
69. Correlations
70. Results
71. Experimental tests
72. Proteins are very tolerant of mutations
73. A minority of amino acid sites dictates structure
74. Sequence similarity
75. Protein sequences have patterns
76. Sequence and structure
77. Structure is more preserved than sequence
78. 1RHD sequence alignment
79. 1RHD sub-sequence alignment
80. Chain path of entire molecule
81. Beta-alpha-beta motifs in 1RHD (1)
82. Two fold symmetry axis
83. Beta-alpha-beta motifs in 1RHD (2)
84. Beta-alpha-beta motifs in 1RHD (3)
85. How much does a family of proteins vary?
86. How much do similar protein structures differ?
87. 3-d match closeness
88. Representation of degree of agreement
89. Structure prediction
90. Sequence determines structure
91. Structures are more conserved than sequences
92. One structure for a sequence family is enough
93. How is a structure predicted?
94. Gallery of faces
95. Components of faces
96. Artist's renditions
97. Second structure prediction
98. Gallery of proteins
99. Components of proteins
100. Unknown structure
101. Fragments of extended chain
102. Placement
103. Folded chain creation
104. Touch up
105. Successful de novo prediction characteristics
106. The line up
107. Example: experiment vs. prediction (1)
108. Example: experiment vs. prediction (2)
109. Example: experiment vs. prediction (3)
110. Example: experiment vs. predictionX
111. Example: experiment, prediction and predictionX
112. Context
113. Aggregated vs. globular
114. Sequence and context determine structure
115. References
116. References: Mr. Peanut
117. References: monkeys typing
118. References: genetic code
119. References: ranganathan
120. References: police artist
121. References: Casp
122. References: Velcro

Topics Covered

• Concept of information
• Variation in protein sequences
• Patterns
• Comparison with language
• Measuring information
• Genetic code
• Correlated substitutions
• Proteins' high tolerance for substitutions
• Protein structure prediction
• Dependence of structure on environment

Links

Series:

• Using Bioinformatics in the Exploration of Genetic Diversity

Categories:

• Biochemistry

Talk Citation

Swanson, R. (2017, October 31). Information content in sequences and its relation to protein structure prediction [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved November 14, 2024, from https://doi.org/10.69645/SKRI2193.
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Publication History

• Published on October 1, 2007
• Reviewed on October 31, 2017

Financial Disclosures

• Dr. Rosemarie Swanson has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.