Frequently Asked Questions (F.A.Q.)

ArchDB is a classification of loops extracted from known protein structures. The classification of loops in archDB is based in the length of the loop, its conformation (φ and ψ backbone dihedral angles of the residues in the loop), the distance between the extremes of the loop, the bracing secondary structures of the loop and the geometry defined by the super-secondary structure motif (the loop itself plus the bracing secondary structures)
We have defined a loop as a super-secondary structural motif, consisting of an aperiodic structure connecting two sequential periodic secondary structures. In ArchDB, is the basic unit for classification. For the ArchDB classification purposes, a loop is defined by the number of residues forming the aperiodic structure, its conformation (φ and ψ backbone dihedral angles of the residues in the aperiodic structure), the bracing secondary structures of the loop, and the geometry of the loop.
The geometry of the loop is defined by four internal coordinates (D, δ, θ, ρ) extracted from the orientation of the principal vectors (M1, M2) that define the bracing secondary structures (see Oliva et al. 1997):
  • D: Distance. The euclidian distance between the boundaries of the aperiodic structure.
  • δ: Delta (hoist) angle. The angle between M1 and D.
  • θ: Theta (packing) angle. The angle between M1 and M2.
  • ρ: Rho (meridian) angle. The angle between M2 and the plane Γ defined by the vector M1 and the normal to the plane formed by M1 and D.
The previous version of ArchDB (Espadaler et al. 2004) only used the Density Search (DS) clustering method, allowing for a potential extension of ± 1 residue in the aperiodic structure of the arch within clusters, representing the potential variability in residue length of geometrically similar loops. Due to the enormous increase of experimental data, implementing such potential extension was timely unfeasible in the current version of the database.
However, the variability feature implemented in the previous version of the database is a requirement if one pretends to identify geometrically similar loops with different residue length. To surmount this problem, in the current version of the database, we implemented a new clustering approach, the Markov CLustering algorithm (MCL) that makes feasible to cluster together loops with different residue length. The DS clustering is maintained for consistency with the previous version of the database, and to enlarge the coverage of clustered loops.
The Density Search clustering method used in ArchDB is based upon the density or mode-seeking technique (searching for regions containing a relatively dense concentration of loops), a version of single-linkage analysis (Everitt, 1974). Basically, the DS algorithm detects regions with a high density of loops in a features space defined by the length, bracing secondary structures, conformation and geometry of the loops. All loops in DS clustering have identical bracing secondary structures and number of amino-acids in the aperiodic structure of the arch, a consensus conformation (nearly identical), and a similar geometry.
The Markov CLustering algorithm (MCL) is a graph-based clustering algorithm. The idea behind the MCL algorithm is to simulate a flow of information within the graph, enhancing the flow where the current is strong and hindering it where the current is weak. If natural groups are present in the graph, then streams across borders between different groups will fade out. In MCL, the flow is controlled expanding and inflating the stochastic (Markov) matrix that represents the graph (see Van Dongen 2008).
In ArchDB such graph is built considering loops as vertices and setting an edge between two loops if their conformation and geometry are similar. An edge between two loops is established when all the following conditions are met:
  1. a minimum percentage of identical phi/psi angles of the loops. This percentage ranges from 95% to 98%
  2. similar geometrical parameters. Geometrical variation allowed between two linked loops is defined by the four geometric parameters:
    • Distance D: ΔD ≤ 1 Å
    • Delta angle: Δδ ≤ 15°
    • Theta angle: Δθ ≤ 15°
    • Rho angle: Δρ ≤ 25°
Then natural groups in the cluster revealed by MCL algorithm correspond to groups of loops with similar geometric properties. These groups were enforced to be disjoint (non-overlapping). However, in comparison with Density Search (DS), MCL allows loops of different length (number of amino-acids in the aperiodic structure of the arch) in the same cluster. Hence, all loops in MCL clustering have identical bracing secondary structures, a number of amino-acids in the aperiodic structure within a certain range, a consensus conformation, and a similar geometry.
A class represents different clusters of loops (sub-classes) with identical conformation in the segment defined by the aperiodic structure region plus a minimum of 2 residues of the bracing secondary structures.
If a loop has a 'direct' assignation it means that the loop strcuture (exctracted from the corresponding PDB file) was directly used during the classification. In other words, such loop structure had undergone the classification process by DS and MCL algorithms (but it does not mean that such loop was actually classified).
When two chains of a PDB file have identical sequences (i.e.: A, B) only one of them (i.e.: A) is handled during the clustering process. Then the classification obtained for the loops of the processed chain (i.e.: A) is transferred by ‘identity’ to the corresponding loops of the non-processed chain (i.e.: B).
Classified loops are assigned to redundant PDB sequences through sequence homology by BLAST1. The hits used for the annotation had ot satisfy a minimum percentage of identity according to the length of the alignment (above the twilight-zone curve, as described by Rost2). Only structures with a 100% sequence coverage in the loop region were assigned by this procedure.

1Altschul, S.F., Madden, T.K., Schäffer, A.A., Zhang, J., Zhang, Z, Miller, W & Lipman, D.J. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucl. Acids Res., 25(17), 3380-3402.
2Rost, B. (1999) Twilight zone of protein sequence alignments. Protein Eng., 12(2), 85-94.
For the MCL clustering we initially set five different length groups: small, between 0 and 4 residues; medium, between 4 and 6 residues; large, between 7 and 13 residues, extra-large, between 14 and 20 residues; and extra-extra-large for loops of 21 residues or more. The large population of loops with four residues recommended to cluster them into both the small and the medium group. Hence, a four-residues-length loop may be clustered in sub-classes of the small and the medium groups. This is represented by the notation 4S (in the small groups) and 4M (in the medium groups). Particularly, a 4S sub-class may contain loops within the range of 2-4 residues (including sub-classes constituted exclusively by 4-residues-length loops), while a 4M sub-class may contain loops within the range of 4-6 residues (excluding sub-classes constituted exclusively by 4-residues-length loops, which will be classified in the 4S clusters).
This is because a protein can have more than one of such external DB annotations. In ArchDB, the loop inherits all the annotations from the region of the PDB chain of which the loop is part of. Then, the total number of annotations for a group of loops can exceed the number of loops in such group.
The separated atoms correspond to what PDB understands as HETATM. This are amino acids that do not fit inside the regular 20.
There are 3 different coloring variants for the 3D view (not including the default coloring by secondary structure):
  • Amino Acid: This scheme adds one color per Amino acid. Individual aminoacids can be identified by the use of the Labels button
  • Shapely: This scheme colors Amino acids according to their traditional properties. The code reads as follows:
    Amino Acid(s)Color
    ASP, GLU bright red
    CIS, MET yellow
    LYS, ARG blue
    SER, THR orange
    PHE, TYR mid blue
    ASN, GLN cyan
    GLY light grey
    LEU, VAL, ILE green
    ALA dark grey
    TRP pink
    HIS pale blue
    PRO flesh
  • Polar: The polar coloring view does not distinguish the sign of the charge, it assigns true to charges and false to non-charged Amino acids.
For some databases it does not make a lot of sense to build a standalone search over ArchDB. For instance, searching by taxid will only reveal the experimental bias over certain species, which would not be very useful when searching for structural properties of proteins.
A loop of length 0 representes two correlative seconday structures (as assigned by DSSP) with no aperiodic structure residues between their boundaries. Thus, it can be found between two secondary structures of different type, like a shift from H (alpha-helix) to G (helix-3:10) or a transition between a beta-strand and an alpha-helix.
The sequence consensus string uses PROSITE format, where positions in sequence are delimited by a dash (-) and the different accepted possibilities for a given sequence position are shown between squared brackets; wildcard positions are represented by an X.
Clustering of loop subclasses is based on the Ramanchandran phi/psi angles and loop geometry. A 9x9 matrix of phi/psi angle is defined as shown in the following table. The codes are explained in the table legend.
-180-135-90-45 0  45 90 135 180
  • *: forbidden region
  • a: alpha helix
  • l: left handed alpha helix
  • b: beta strand
  • p: beta proline
  • g: gamma
  • e: epsilon
  • l/g: bridge region between left handed and gamma helices
    (written as 'v' in loops multiple alignment)
  • b/p: bridge region between beta strand and beta proline
    (written as 'x' in loops multiple alignment)
Several special symbols can be used in the Ramachandran consensus string:
  • dash (-): represents a cys-proline.
  • dot (.): represents a position for which no consensus was achieved.
The assignation of external codes to loops varies depending on the source database:
  • taxid and enzyme: These two relations are directly assigned to the full chain. This means that the relation is extracted directly from the PDB source and assigned to all the loops of that specific chain.
  • uniprot and SCOP: These relations are directly assigned positionally. This means that the relation between a PDB chain and those codes is assigned through direct reference by any of the mentioned databases but only to the specified position of the chain. Only loops fully inside the assigned region are assigned that specific reference (both loop limits belong to the assignation).
  • GO and Drugbank: These relations are assigned through uniprot. In those two cases, it is the uniprot assignation the one that links a PDB to those databases. Thus, the assignation is dependent of the same conditions as the uniprot assignation.
Finally, the assignation of external databases to classes or subclasses is fully dependent on the assignation of the loops contained in those classes/subclasses.
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