The cadherin superfamily is a large

The cadherin superfamily is a large protein family with diverse structures and functions. Because of this diversity
and the growing biological interest in cell adhesion and signaling processes, in which many members of the
cadherin superfamily play a crucial role, it is becoming increasingly important to develop tools to manage, distribute
and analyze sequences in this protein family. Current profile and motif databases classify protein sequences
into a broad spectrum of protein superfamilies, however to provide a more specific functional annotation, the
next step should include classification of subfamilies of these protein superfamilies. Here, we present a tool that
classified greater than 90% of the proteins belonging to the cadherin superfamily found in the SWISS PROT
database. Therefore, for most members of the cadherin superfamily, this tool can assist in adding more specific
functional annotations than can be achieved with current profile and motif databases. Finally, the classification
tool and the results of our analysis were integrated into a web-accessible database (http://calcium.uhnres.
utoronto.ca/cadherin).
Introduction
Proteins in the cadherin superfamily are transmembrane
glycoproteins that are involved in many biological
functions such as cell–cell adhesion, morphogenesis,
synapse formation, cell polarization, cell sorting,
cell migration, and cell rearrangements [1–8]. Some
members of the cadherin superfamily have even been
implicated as proto-oncogenes or tumor suppressors
[9, 10]. All these members of the cadherin superfamily
share an extracellular cadherin repeat (CR), an approximately
110 amino acid peptide that mediates
Ca2+-dependent homophilic interactions between cadherin
molecules. CRs assume an immunoglobulinlike

-sandwich fold (Figure 1), which usually occur
in tandem and are separated by a linker region that
binds three Ca2+ ions [11–15]. From the raw sequence
data of the various genome projects, it is clear that
many sequences have CRs; however, the annotation
of the specific biological function is unclear as cadherins
are involved in many diverse functions.
Typically, the biological function can be inferred
from its similarity to sequences of known function in
sequence databases using single-sequence similarity
algorithms such as BLAST [16] and FASTA [17].
Such algorithms are suitable for determining highly
similar sequences, but are not sensitive enough to
capture highly divergent sequences. Therefore, many
members of an evolutionarily diverse family of proteins
may be overlooked. Within the last decade, the
sensitivity of sequence searching techniques has been
improved by profile- or motif-based analysis, which
uses information derived from multiple sequence
alignments (MSAs) to construct and search for sequence
patterns [18–20]. Unlike single-sequence similarity,
a profile or motif can exploit additional information,
such as the position and identity of residues
that are conserved throughout the family, as well as
variable insertion and deletion probabilities. The hidden
Markov model is one powerful way to express a
profile or motif because it provides a solid statistical
foundation to model information in an MSA [20].

Hasil (Bahasa Indonesia) 1:

Superfamili cadherin adalah sebuah keluarga besar protein dengan beragam struktur dan fungsi. Karena keragaman initumbuh minat biologis adhesi sel dan signaling proses, di mana banyak anggotacadherin superfamili memainkan peran penting, hal ini menjadi semakin penting untuk mengembangkan alat untuk mengelola, mendistribusikandan menganalisis urutan dalam keluarga protein ini. Database profil dan motif yang saat ini mengklasifikasikan urutan proteinke spektrum yang luas dari protein superfamilies, namun untuk memberikan penjelasan fungsional yang lebih spesifik,Langkah selanjutnya harus mencakup klasifikasi subfamili superfamilies protein ini. Di sini, kami menyajikan sebuah alat yangdiklasifikasikan lebih dari 90% protein yang milik superfamili cadherin ditemukan di SWISS PROTdatabase. Oleh karena itu, untuk sebagian besar anggota dari superfamili cadherin, alat ini dapat membantu dalam menambahkan lebih spesifikfungsional anotasi daripada yang dapat dicapai dengan database profil dan motif yang saat ini. Akhirnya, klasifikasialat dan hasil analisa kami yang terintegrasi ke dalam database diakses web (http://calcium.uhnres.UToronto.ca/cadherin).PendahuluanProtein dalam superfamili cadherin transmembranglikoprotein yang terlibat dalam banyak biologisfungsi seperti adhesi sel-sel, morphogenesis,pembentukan sinaps polarisasi sel, sel pemilahan,Migrasi sel, dan penyusunan ulang sel [1 – 8]. Beberapamembers of the cadherin superfamily have even beenimplicated as proto-oncogenes or tumor suppressors[9, 10]. All these members of the cadherin superfamilyshare an extracellular cadherin repeat (CR), an approximately110 amino acid peptide that mediatesCa2+-dependent homophilic interactions between cadherinmolecules. CRs assume an immunoglobulinlike
-sandwich fold (Figure 1), which usually occurin tandem and are separated by a linker region thatbinds three Ca2+ ions [11–15]. From the raw sequencedata of the various genome projects, it is clear thatmany sequences have CRs; however, the annotationof the specific biological function is unclear as cadherinsare involved in many diverse functions.Typically, the biological function can be inferredfrom its similarity to sequences of known function insequence databases using single-sequence similarityalgorithms such as BLAST [16] and FASTA [17].Such algorithms are suitable for determining highlysimilar sequences, but are not sensitive enough tocapture highly divergent sequences. Therefore, manymembers of an evolutionarily diverse family of proteinsmay be overlooked. Within the last decade, thesensitivity of sequence searching techniques has beenimproved by profile- or motif-based analysis, whichuses information derived from multiple sequencealignments (MSAs) to construct and search for sequencepatterns [18–20]. Unlike single-sequence similarity,a profile or motif can exploit additional information,such as the position and identity of residuesthat are conserved throughout the family, as well asvariable insertion and deletion probabilities. The hiddenMarkov model is one powerful way to express aprofile or motif because it provides a solid statisticalfoundation to model information in an MSA [20].