Bioinformatics Institute (BII) A*STAR Singapore Frank Eisenhaber - - PowerPoint PPT Presentation

Bioinformatics Institute (BII)

A*STAR Singapore

Frank Eisenhaber www.bii.a-star.edu.sg franke@bii.a-star.edu.sg Singapore, 13th December 2017

New insights into TM-proteins sequence – structure - function

Wong et al., 2010, PLoS Computational Biology, 6(7), doi:10.1371/journal.pcbi.1000867 Wong et al., 2011, Biology Direct, 6(57), doi:10.1186/1745-6150-6-57 Wong et al., 2012, Nucleic Acids Research, 40, W370–W375, doi:10.1093/nar/gks379 Wong et al., 2014, BMC Bioinformatics 15, 166, doi:10.1186/1471-2105-15-166 Baker et al., 2017, BMC Biology, 15, 66, doi 10.1186/s12915-017-0404-4

Transmembrane helices. A “negative-not- inside/negative-outside rule” complements the “positive- inside rule”.

James Baker1,2, Wing Cheong-Wong1, Birgit Eisenhaber1, Jim Warwicker2*, Frank Eisenhaber1*

1BII at A*STAR, Singapore 2MIB at Manchester, UK 3

Inside the cytoplasm Outside the cytoplasm Lipid bilayer Interface Interface

Introduction

4

Intra-membrane helix Inside flank Outside flank

Non-polar (hydrophobic)

Positive charge enrichment Polar in both flanks Tryptophan enrichment at both interfaces

Introduction

Tyrosine enrichment

5 Ulmschneider,M.B. and Sansom,M.S.P. (2001) Amino acid distributions in integral membrane protein structures. Biochim.

• Biophys. Acta - Biomembr., 1512, 1–14.

“Problems” in previous study

• Negative residues are especially rare,

even in the flanks

2500 5000 7500 10000 L V A I G F S T R C K Y M W Q N H E D Residue count

1709 human TMHs ±5 residues (single- pass)

6

New methods for this study

• Segregate single-pass and multi-pass + other segregation
• Cross reference experimental and predictive datasets
• Align from the center (removes bias)
• New normalisation – independent, percentage based
• OLD: If we have a residue, where and what is it likely

to be?

• NEW: If we have a residue X, where is it likely to be?

pi,r = ai,r max

r

ar

( )

qi,r = 100× ai,r ai

abundance = a amino acid type = i certain sequence position = r

7

5 10 15 20

• 15 -10
• 5

5 10 15 Relative percentage Distance from centre of helix

Results

qi,r = 100× ai,r ai

Positive, inside Negative, outside

8

If we have a residue X, where is it likely to be?

Results

9

At which membranes negative charges follow the negative-not- inside/negative-outside rule?

• Single-pass graphically.
• Multi-pass not graphically present, but statistically present

in most cases.

1 2 3 4 5 6 7

• 30
• 20
• 10

10 20 30 Percentage distribution Distance from centre of helix Single-pass (1194 helices) Multi-pass (12331 helices from 2093 proteins) 1 2 3 4 5 6 7

• 30
• 20
• 10

10 20 30 Percentage distribution Distance from centre of helix

Positive Negative Leucine

Results

10

Inner flank Inner leaflet Outer leaflet Outer flank Inner flank Inner leaflet Outer leaflet Outer flank Single-pass Multi-pass

Intra-membrane helix Inside flank Outside flank Outer leaflet Inner leaflet

Higher leucine propensity

Suppression of negative charge

Our Findings

Lower leucine propensity

Increasing cysteine propensity*

11

Preference for negative charge

Conclusions

• A “negative-not-inside/negative-
• utside rule” complements the

“positive-inside rule”.

• Leucine intra-helix propensity

reflects leaflet asymmetry.

• Multi-pass helices are very

different (on average) to single- pass helices.

12

Bac ackground con

• nsid

iderations

• Homology is a hypothesis about common evolutionary origin
• Similarity is a measurable fact
• Long stretches of similarity versus local resemblances (physiologically

constrained to form rudimentary structure) Similarity measure as a proxy to homology and its limitation

Similarity score High Moderate Low By chance Very high Convergent evolution

• r

Common ancestry E-value cutoff

Bac ackground con

• nsid

iderations

Issues with non-globular sequences

Convergent evolution Common ancestry

• Sequence homology concept is not directly applicable to non-

globular sequences.

• Signal-peptides/transmembrane helices (SP/TM) belong to this class
• Mimics the appearance of hydrophobic core match

Alignment of homologous structures

• Strictosidine synthase
• Dissopropyflurophosphatase
• Serum paraoxonase
• Drp35
• Regucalcin

APMAP

Long stretches of similarity of long globular segment

Unrelated hits with a similar TM segment

Local resemblance of short non-globular segment

Se Sequence comple lexit ity of

• f SP

SP/T /TM

% of low-complexity TMs α-helices Signal peptides Single- spanning TMs Multi- spanning TMs Results of SEG (12/2.2/2.5) :

SP/TM have lower complexity than α-helices (12~33% versus 3%)

Open-ended questions :

• Should all TMs be excluded? What about multi-membrane proteins like GPCR?
• Should all single-spanning TM be excluded?
• What about those with ‘a few’ TMs?

Membrane anchors, functional TMs, α-helices, low-complexity segments

Rela lationship ip am among th the TM helic lices, fu functional l α-helic ices an and lo low-comple lexit ity se segments

• Overlap of functional α- and TM- helices extents the sequence

homology concept for membrane proteins

• SEG samples low hydrophobicity space and hence insufficient to

distinguish ‘simple’ or ‘complex’ TMs

Multi-spanning membrane proteins can harbor simple TM helices

TM propertie ies in in multi-spannin ing membrane proteins

Mask ratio (No. of masked TMs/Total TMs) Count On average, each sequence has 8 TM helices For 2202 TCDB sequences Original sequence Masked sequence Simple TMs being masked Find simple TMs Mask ratio for 2202 sequences

Con

• nclusions
• TMs are either simple (likely of convergent evolution) or complex (likely of

common ancestry).

• Signal peptides and simple TMs can attract unrelated hits. Simple TMs

should be quantitatively excluded from similarity searches using the z- score criteria.

• Complex TMs embody ancestry information and justified for the

application of sequence homology concept.

• Simple TMs are found in membrane proteins regardless of membrane
• topology. The caveat is that it occurs more frequently in low-spanning
• nes.

BII Yearbook 2017

• Thanks to Betty and all contributors
• Timeline of BII’s history

Bioinformatics Institute: Status in 2017

Thank you !!