the observed distances and the ideal distances. The score is divided by the number of speciﬁed interactions plus one, and its square root is taken. Overlap score (V). Considering the overlap deﬁnition described in the matrix construction section above, perfect overlap is equal to the vector length of the smaller SSE in a pair. First, we calculate the overlap for each SSE pair if interaction between them is deﬁned in the query matrix. Then, we sum over the squares of the diﬀerences between overlap lengths and vector lengths of smaller SSEs. The score is also divided by the number of speciﬁed interac- tions plus one, and its square root is taken. Length score (L). We deﬁne the length of SSE as the length of SSE vector in A˚ , rather than the number of residues of SSE. This makes all the three scores (D, V and L) comparable and measured in A˚ . First, we com- puted all the lengths for b-strands and helices for the motif hits. Then, we calculate the median of b-strand length and the median of helix length. The median of SSE length represents the length tendency of SSE of the query structure pattern. Second, we sum over the squares of diﬀerences between observed SSE lengths and their median lengths. The score is divided by the number of SSEs in the query matrix plus one, and its square root is taken. We combine the three scores in the following function: Score ¼ 1 ½ðWD DÞ þ ðWV VÞ þ L þ 1 Here, the weights WD and WV were set as 4.5 and 2.5, respectively to balance the three scores giving the best per- formance in our test. Apparently, when all the sums of deviations from ideal values are close to 0, the score is close to 1 (maximum score). When the distances deviate from ideal, the score decreases to 0. ProSMoS WEB SERVER Target database Databases used in ProSMoS server are: PDB, PDB90 (identity 90%), PDB70 (identity 70%), SCOP, SCOP40 (representative PDB structures with no more than 40% sequence identity) and SCOP95 (identity 95%). We pre-calculated SSE assignment for each entry in these spatial structure databases and converted 3D structures into 2D meta-matrix databases to be queried by the ProSMoS server. Input ProSMoS server runs in two modes: (i) motif search start- ing from a user-deﬁned interaction matrix; and (ii) motif search with an atomic coordinate ﬁle for a protein struc- ture. In the ﬁrst mode, the input query matrix should be designed by a user based on the set of rules described above. In the second mode, user can input PDB ID, SCOP ID or upload a structure ﬁle in PDB format. Nucleic Acids Research, 2009, Vol. 37, Web Server issue W529 The server will generate the interaction matrix from the structure. In the ﬁrst mode, user supplies a query matrix. Format of the matrix is checked by ProSMoS for usability. After the initial check, the search with the query matrix is performed against the target database selected by user. The ﬁrst mode is more ﬂexible and yields the best results if the user has a clear understanding of the structure pattern of interest, and speciﬁes the essential structure constraints while omitting minor details. Such supervised query matrix construction generates high-quality results. The second mode is more suitable for users who are not conﬁdent in manual meta-matrix deﬁnition. After the meta-matrix is automatically produced by the server from the input coordinate ﬁle, an options is given to reﬁne the matrix by (i) specifying the length restrictions on SSEs (e.g. in order to remove short unessential elements), and by (ii) setting the distance cutoﬀ for ﬁltering out unessen- tial interaction between SSEs. While the matrix generated after this step can be used ‘as is’ to initiate searches, the option is provided to edit the matrix manually. It is recommended that this step is taken. Automatically constructed matrix may be too constrained on the query PDB ﬁle and will include some SSEs not essential for the fold (insertions to the common core). Search results with such matrix will be too restrictive. Therefore, it is beneﬁ- cial to reﬁne the query matrix by removing non-essential SSEs, revising the b-sheet and handedness information, or editing interactions between SSEs. Output Output is the list of proteins in PDB or SCOP matching the query matrix. All structure motifs matching the query are comprehensively listed and ranked by the ProSMoS score. For each motif, the corresponding PDB ID, protein name, SCOP domain ID, description of domain and the ranges of residue numbers that deﬁne motif SSEs are pro- vided. Each motif can be visualized on the ﬂy with PyMOL. The PyMOL script displays the Ca trace of a structure with the backbone colored in gray, each motif SSE colored in red, the ﬁrst residue in the ﬁrst SSE in the motif colored in green, and ﬁrst residues of all other motif SSEs colored in purple. In addition, we provide the lists of SCOP superfamilies and folds for the found motifs. Here, we use the ferredoxin-like fold (10,19) to illustrate the output of the ProSMoS Server. Ferrodoxin-like fold is a wide-spread a + b two-layer sandwich with the SSEs order babbab. Four b-strands form an antiparallel b-sheet and two a-helices pack against one side of this sheet (Figure 1B). The query meta-matrix for the ferredoxin- like fold is shown on Figure 1C. This query is very per- missive, as the goal is to ﬁnd all possible candidates. In the interaction matrix, other than the interactions between the b-strands in the same b-sheet, we only required that the ﬁrst helix and the second helix should have interactions with the fourth strand and the ﬁrst strand respectively. All other interactions are not speciﬁed (X symbol). Additionally, we did not set the SSE length limitation. A search of this query matrix against the PDB (26 January 2009, 53 305 entries) found 2291 PDB hits containing 8299