Taxonomic diversity-based domain interaction prediction

Erdem TÜRK, (Muğla Sıtkı Koçman Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Muğla, Türkiye)
Barış Ethem SÜZEK (Muğla Sıtkı Koçman Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Muğla, Türkiye)
Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi
2 1
Yıl: 2019 Cilt: 25 Sayı: 2 Sayfa Aralığı: 215 - 222 Metin Dili: İngilizce DOI: 10.5505/pajes.2018.18828 İndeks Tarihi: 30-06-2020

Taxonomic diversity-based domain interaction prediction

Öz:
Identification of protein domain-domain interactions (DDIs) is anessential step in understanding proteins’ functional and structural roles.MirrorTree is a DDI prediction method that is based on the principle ofinteracting proteins’ co-evolution. However, this method is sensitive totaxonomic diversity and evolutionary span within the two proteinhomolog sets compared to predict DDI. In this work, we propose a newMirrorTree-based DDI prediction method, namely Taxonomic Diversitybased Domain Interaction Prediction (TAXDIP). TAXDIP improves theMirrorTree method by adding a sampling step that favorsrepresentation of higher-level taxonomic ranks (e.g. family over species)in two protein homolog sets prior to their comparison. This additionalstep ensures increased evolutionary span within protein homolog sets.TAXDIP is first assessed using a set containing 6,514 positive(interacting) domain pairs and a negative (non-interacting) set of equalsize containing randomly generated domain pairs with no knowninteractions. TAXDIP achieved 71.0% sensitivity and 63.0% specificityon this set. Next, a benchmark-set containing 500 interacting and 500non-interacting domain pairs is used to compare the performance ofTAXDIP against DDI prediction methods ME and RDFF. TAXDIP showedbetter sensitivity and specificity than RDFF. While TAXDIP’s sensitivityis better than ME, its specificity remained below ME. In conclusion,TAXDIP, with its performance, is a viable alternative to existingprediction methods. Furthermore, given TAXDIP’s true predictions areoverlapping with, and furthermore, complementing other DDIprediction methods, TAXDIP has a strong position in becoming part of ameta-DDI prediction method that combines multiple methods to build aconsensus prediction.
Anahtar Kelime:

Taksonomik çeşitlilik tabanlı protein altünite etkileşim tahmini

Öz:
Protein altünite-altünite etkileşimlerinin (AAE) belirlenmesi, proteinlerin fonksiyonel ve yapısal rollerinin anlaşılmasında önemli bir adımdır. MirrorTree, etkileşen proteinlerin birlikte-evrimi prensibine dayanan, bir AAE tahmin yöntemidir. Ancak bu yöntem, AAE tahmin etmek için karşılaştırılan iki protein homolog kümesindeki taksonomik çeşitliliğe ve evrimsel açıklığa duyarlıdır. Bu çalışmada Taksonomik Çeşitliliğe Dayalı Protein Altünite Etkileşimi Tahmini (TAXDIP) olarak adlandırılan MirrorTree tabanlı yeni bir protein AAE tahmin yöntemi önermekteyiz. TAXDIP, iki protein homolog kümesini karşılaştırmadan önce, bunlarda daha yüksek düzeydeki taksonomik sıraların (ör. Tür yerine Aile) temsil edilmesini destekleyen bir örnekleme adımı ekleyerek, protein homolog kümeleri içindeki evrimsel kapsamın artmasını sağlar. TAXDIP öncelikle deneysel olarak doğrulanmış 6.514 pozitif (etkileşimli) altünite çiftini ve aynı sayıda, bilinen etkileşimleri olmayan, rastgele oluşturulmuş negatif (etkileşmeyen) altünite çiftini içeren bir küme kullanılarak değerlendirildi. TAXDIP bu kümede %71,0 duyarlılık ve %63,0 özgüllük elde etti. Daha sonra, TAXDIP'in performansının ME ve RDFF adlı AAE tahmin yöntemiyle karşılaştırılması için, 500 etkileşimli ve 500 etkileşmeyen altünite çiftini içeren, bir kıyaslama kümesi kullanıldı. TAXDIP RDFF’den daha iyi duyarlılık ve özgüllük gösterdi. TAXDIP’in duyarlılığı ME’den daha iyi olsa da, özgüllüğü ME’nin altında kaldı. Sonuç olarak, TAXDIP göstermiş olduğu performansla mevcut tahmin yöntemlerine uygun bir alternatiftir. Ayrıca, TAXDIP’in diğer tahmin yöntemleriyle örtüşen ve dahası onları tamamlayan doğru AAE tahminleri, onu birçok yöntemi bir araya getiren bir meta-AAE tahmin yönteminin parçası olma konusunda güçlü bir konuma getirmektedir.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
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APA TÜRK E, SÜZEK B (2019). Taxonomic diversity-based domain interaction prediction. , 215 - 222. 10.5505/pajes.2018.18828
Chicago TÜRK ERDEM,SÜZEK Barış Ethem Taxonomic diversity-based domain interaction prediction. (2019): 215 - 222. 10.5505/pajes.2018.18828
MLA TÜRK ERDEM,SÜZEK Barış Ethem Taxonomic diversity-based domain interaction prediction. , 2019, ss.215 - 222. 10.5505/pajes.2018.18828
AMA TÜRK E,SÜZEK B Taxonomic diversity-based domain interaction prediction. . 2019; 215 - 222. 10.5505/pajes.2018.18828
Vancouver TÜRK E,SÜZEK B Taxonomic diversity-based domain interaction prediction. . 2019; 215 - 222. 10.5505/pajes.2018.18828
IEEE TÜRK E,SÜZEK B "Taxonomic diversity-based domain interaction prediction." , ss.215 - 222, 2019. 10.5505/pajes.2018.18828
ISNAD TÜRK, ERDEM - SÜZEK, Barış Ethem. "Taxonomic diversity-based domain interaction prediction". (2019), 215-222. https://doi.org/10.5505/pajes.2018.18828
APA TÜRK E, SÜZEK B (2019). Taxonomic diversity-based domain interaction prediction. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 25(2), 215 - 222. 10.5505/pajes.2018.18828
Chicago TÜRK ERDEM,SÜZEK Barış Ethem Taxonomic diversity-based domain interaction prediction. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 25, no.2 (2019): 215 - 222. 10.5505/pajes.2018.18828
MLA TÜRK ERDEM,SÜZEK Barış Ethem Taxonomic diversity-based domain interaction prediction. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol.25, no.2, 2019, ss.215 - 222. 10.5505/pajes.2018.18828
AMA TÜRK E,SÜZEK B Taxonomic diversity-based domain interaction prediction. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2019; 25(2): 215 - 222. 10.5505/pajes.2018.18828
Vancouver TÜRK E,SÜZEK B Taxonomic diversity-based domain interaction prediction. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2019; 25(2): 215 - 222. 10.5505/pajes.2018.18828
IEEE TÜRK E,SÜZEK B "Taxonomic diversity-based domain interaction prediction." Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 25, ss.215 - 222, 2019. 10.5505/pajes.2018.18828
ISNAD TÜRK, ERDEM - SÜZEK, Barış Ethem. "Taxonomic diversity-based domain interaction prediction". Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 25/2 (2019), 215-222. https://doi.org/10.5505/pajes.2018.18828
Sayfa Oluşturulma Tarihi
23-04-2024 12:28

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