W248 Nucleic Acids Research, 2008, Vol. 36, Web Server issue the aligned fragments together, and is the noise param- eter, which determines how strictly structural similarity is applied. For low -values, pFlexAna matches only frag- ments that are highly similar. For high -values, it also matches fragments with weak similarity and ignores small diﬀerences. Based on our experiences, -values between 0.2 and 0.4 work well for proteins with reasonably high- sequence homology (40% or higher). For proteins that are even more distantly related, we ﬁnd -values up to 0.8 to be useful as well, though this may lead to false positive matches in some cases. Output pFlexAna identiﬁes pairs of fragments—one fragment from each protein—that show signiﬁcant conformational similarity. They are listed in a table and grouped into clusters, according to the similarity of the geometric transformation that aligns the fragment pair. See Figure 3 for an example. Two or more fragment pairs may move together and form a semi-rigid domain. By categorizing fragment pairs that are moving together versus moving independently, clustering helps to characterize conforma- tional changes caused by domain movements or correlated motions. For each aligned fragment pair, pFlexAna provides a static cartoon of the proteins superimposed according to the aligned pair. This highlights the movement of the proteins with respect to the aligned regions. Jmol links are also provided so that the user may view the proteins from diﬀerent angles. Finally, the transformed PDB coordinate ﬁles that align the second protein to the ﬁrst are available for download and the transformation matrices used for alignment are provided. The same information is also provided for each cluster of aligned fragment pairs. Processing To analyze the conformational changes between two protein structures, pFlexAna proceeds in two main steps. In the ﬁrst step, it identiﬁes pairs of fragments that are structurally similar. These fragment pairs serve as rigid cores for superimposing the two proteins and detecting conformational changes with respect to the cores. In the second step, pFlexAna clusters the aligned fragment pairs into ‘super-alignments’, according to the similarity of geometric transformations that align two fragments in a pair. The result is that the dominant conformational changes occur between the clusters, while the smaller conformational changes occur within a cluster. We now describe the two steps in greater detail below. To identify structurally similar fragment pairs, pFlexAna uses an all-against-all approach that eﬀectively compares every contiguous fragment from one protein with that from the other. First, we match the residues of the two proteins by ‘sliding’ one protein against the other (Figure 4). For each sliding position, let P and P0 represent the matched residues from the two proteins, respectively. We generate all contiguous fragments of P and P0 and check their structural similarity by applying a reliable statistical test (4). Brieﬂy, this test uses a Gaussian noise model to represent acceptable deviations in atomic coordinates between two putatively similar protein frag- ments. Two fragments are considered statistically diﬀerent if their coordinates deviate too much according to the Gaussian model. We then assign to each residue a ﬂexibility score that incorporates information from all fragment comparisons that involve this residue. A high score indicates greater rigidity. Finally, each pair of aligned fragments must pass the following ﬁlter: the fragments must consist entirely of residues whose ﬂex- ibility scores are above a threshold, and they must be longer than a given minimum length. Intuitively, this ﬁlter ensures that such a pair of fragments and all sub- fragments contained in them are structurally identical up to statistical variations. The minimum length requirement is imposed to avoid accidental structural matches. One advantage of our method is that it highlights the genuine conformational changes by suppressing the spurious ones due to noise. More details on this method and its advantages are available in ref. (4). Since we perform an Figure 3. A screenshot showing the pFlexAna result for the mal- tose-binding protein. The pose of the protein is diﬀerent from that in Figure 2. Figure 4. Sliding one protein against the other.