TMSEG: Novel prediction of transmembrane helices

Bernhofer, Michael; Kloppmann, Edda; Reeb, Jonas; Rost, Burkhard

doi:10.1002/prot.25155

Cited by 51 publications

(47 citation statements)

References 46 publications

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“…This analysis revealed that the previously developed servers are not completely adequate for membrane proteins, which emphasizes the importance of developing specialized tools to discriminate mutations for different topological regions of membrane proteins. The topology information can be obtained from the available structure prediction tools such as TMHMM, MemBrain, TMSeg, MemConP etc.…”

Section: Resultsmentioning

confidence: 99%

Statistical analysis of disease‐causing and neutral mutations in human membrane proteins

et al. 2019

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Mutations in transmembrane proteins (TMPs) have diverse effects on their structure and functions, which may lead to various diseases. In this present study, we have investigated variations in human membrane proteins and found that negatively charged to positively charged/polar and nonpolar to nonpolar changes are dominant in disease‐causing and neutral mutations, respectively. Further, we analyzed the top 10 preferred mutations in 14 different disease classes and found that each class has at least two Arg mutations. Moreover, in cardiovascular diseases and congenital disorders of metabolism, Cys mutations occur more frequently in single‐pass proteins, whereas Arg and nonpolar residues are more frequently substituted in multi‐pass membrane proteins. The immune system diseases are enriched in C → R and C → Y mutations in inside and outside regions. On the other hand, in the membrane region, E → K and R → Q mutations are prevalent. The comparison of mutations in topologically similar regions of globular and membrane proteins showed that Ser and Thr mutations cause deleterious effects in membrane regions, whereas Cys and charged residues, Asp and Arg are prevalent in the buried regions of globular proteins. Our comprehensive analysis of disease‐associated mutations in transmembrane proteins will be useful for developing prediction tools.

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Section: Resultsmentioning

confidence: 99%

Statistical analysis of disease‐causing and neutral mutations in human membrane proteins

et al. 2019

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“…We used bioinformatics tools that searched for similarities between Babo1 and verified transmembrane proteins, utilized algorithms that were trained on transmembrane protein datasets, and also analyzed Babo1 only based on its sequence of amino acid residues. The battery of applied programs included TMSEG (Bernhofer et al , ), PolyPhobius (Käll et al , ; Käll et al , ), Phobius (Käll et al , ; Käll et al , ), MEMSAT3 (Jones et al , ), MEMSAT‐SVM (Nugent and Jones, ), PHDhtm (Rost et al , ; Combet et al , ), TMHMM (Krogh et al , ), TMpred (Hofmann and Stoffel, ), DAS‐TMfilter (Cserzo et al , ), MINNOU (Cao et al , ), TBBpred (Natt et al , ), PRED‐TMR2 (Pasquier and Hamodrakas, ), and the Kyte and Doolittle hydrophobicity plot (Kyte and Doolittle, ). However, no transmembrane spanning segments have been identified and all of these programs predicted that Babo1 is not a transmembrane protein.…”

Section: Resultsmentioning

confidence: 99%

Babo1, formerly Vop1 and Cop1/2, is no eyespot photoreceptor but a basal body protein illuminating cell division in Volvox carteri

Heyde

Hallmann

2020

The Plant Journal

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In photosynthetic organisms many processes are light dependent and sensing of light requires light-sensitive proteins. The supposed eyespot photoreceptor protein Babo1 (formerly Vop1) has previously been classified as an opsin due to the capacity for binding retinal. Here, we analyze Babo1 and provide evidence that it is no opsin. Due to the localization at the basal bodies, the former Vop1 and Cop1/2 proteins were renamed V.c. Babo1 and C.r. Babo1. We reveal a large family of more than 60 Babo1-related proteins from a wide range of species. The detailed subcellular localization of fluorescence-tagged Babo1 shows that it accumulates at the basal apparatus. More precisely, it is located predominantly at the basal bodies and to a lesser extent at the four strands of rootlet microtubules. We trace Babo1 during basal body separation and cell division. Dynamic structural rearrangements of Babo1 particularly occur right before the first cell division. In four-celled embryos Babo1 was exclusively found at the oldest basal bodies of the embryo and on the corresponding d-roots. The unequal distribution of Babo1 in four-celled embryos could be an integral part of a geometrical system in early embryogenesis, which establishes the anterior-posterior polarity and influences the spatial arrangement of all embryonic structures and characteristics. Due to its retinal-binding capacity, Babo1 could also be responsible for the unequal distribution of retinoids, knowing that such concentration gradients of retinoids can be essential for the correct patterning during embryogenesis of more complex organisms. Thus, our findings push the Babo1 research in another direction.

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“…In terms of per-family view even more misleading is the number of 49% of all human protein families associated with the plasma membrane ( Fig. S1) when fewer than 25% of all human proteins have a membrane helix, and only 13% have more than one transmembrane helix [21]. Thus, we apparently cannot estimate the spectrum of localizations for an organism from experimental and homology-inferred annotations alone.…”

Section: Localization Reliably Inferred For 81% Of the Human Protein mentioning

confidence: 96%

Spectrum of protein localization in proteomes captures evolutionary relation between species

Marot-Lassauzaie

Goldberg

Rost

2019

Preprint

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The native subcellular localization or cellular compartment of a protein is the one in which it acts most often; it is one aspect of protein function. Do ten eukaryotic model organisms differ in their location spectrum, i.e. the fraction of its proteome in each of its seven major compartments? As experimental annotations of locations remain biased and incomplete, we need prediction methods to answer this question. To gauge the bias of prediction methods, we merged all available experimental annotations for the human proteome. In doing so, we found important values in both Swiss-Prot and the Human Protein Atlas (HPA). After systematic bias corrections, the complete but faulty prediction methods appeared to be more appropriate to compare location spectra between species than the incomplete more accurate experimental data. This work compared the location spectra for ten eukaryotes: Homo sapiens, Gorilla gorilla, Pan troglodytes, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Anopheles gambiae, Caenorhabitis elegans, Saccharomyces cerevisiae and Schizosaccharomyces pombe. Overall, the predicted location spectra were similar. However, the detailed differences were significant enough to plot trees and 2D (PCA) maps relating the ten organisms using a simple Euclidean distance in seven states, corresponding to the seven studied localization classes. The relations based on the simple predicted location spectra captured aspects of cross-species comparisons usually revealed only by much more detailed evolutionary comparisons.

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TMSEG: Novel prediction of transmembrane helices

Cited by 51 publications

References 46 publications

Statistical analysis of disease‐causing and neutral mutations in human membrane proteins

Statistical analysis of disease‐causing and neutral mutations in human membrane proteins

Babo1, formerly Vop1 and Cop1/2, is no eyespot photoreceptor but a basal body protein illuminating cell division in Volvox carteri

Spectrum of protein localization in proteomes captures evolutionary relation between species

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