Antibodies blocking cytoadhesion are important mediators of malaria immunity acquired by endemic populations. The development of a PfEMP1 based vaccine mimicking natural acquired immunity depends on a thorough understanding of the evolved PfEMP1 diversity, balancing antigenic variation against conserved receptor binding affinities. This study redefines and reclassifies the domains of PfEMP1 from seven genomes. Analysis of domains in 399 different PfEMP1 sequences allowed identification of several novel domain classes, and a high degree of PfEMP1 domain compositional order, including conserved domain cassettes not always associated with the established group A–E division of PfEMP1. A novel iterative homology block (HB) detection method was applied, allowing identification of 628 conserved minimal PfEMP1 building blocks, describing on average 83% of a PfEMP1 sequence. Using the HBs, similarities between domain classes were determined, and Duffy binding-like (DBL) domain subclasses were found in many cases to be hybrids of major domain classes. Related to this, a recombination hotspot was uncovered between DBL subdomains S2 and S3. The VarDom server is introduced, from which information on domain classes and homology blocks can be retrieved, and new sequences can be classified. Several conserved sequence elements were found, including: (1) residues conserved in all DBL domains predicted to interact and hold together the three DBL subdomains, (2) potential integrin binding sites in DBLα domains, (3) an acylation motif conserved in group A var genes suggesting N-terminal N-myristoylation, (4) PfEMP1 inter-domain regions proposed to be elastic disordered structures, and (5) several conserved predicted phosphorylation sites. Ideally, this comprehensive categorization of PfEMP1 will provide a platform for future studies on var/PfEMP1 expression and function.The  About one million African children die from malaria every year. The severity of malaria infections in part depends on which type of the parasitic protein PfEMP1 is expressed on the surface of the infected red blood cells. Natural immunity to malaria is mediated through antibodies to PfEMP1. Therefore hopes for a malaria vaccine based on PfEMP1 proteins have been raised. However, the large sequence variation among PfEMP1 molecules has caused great difficulties in executing and interpreting studies on PfEMP1. Here, we present an extensive sequence analysis of all currently available PfEMP1 sequences and show that PfEMP1 variation is ordered and can be categorized at different levels. In this way, PfEMP1 belong to group A–E and are composed of up to four components, each component containing specific DBL or CIDR domain subclasses, which in some cases form entire conserved domain combinations. Finally, each PfEMP1 can be described in high detail as a combination of 628 homology blocks. This dissection of PfEMP1 diversity also enables predictions of several functional sequence motifs relevant to the fold of PfEMP1 proteins and their ability to bind human receptors. We therefore believe that this description of PfEMP1 diversity is necessary and helpful for the design and interpretation of future PfEMP1 studies. Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) mediates adhesion of infected erythrocytes (IE) to various host cells on the vascular lining, during the blood stage of malaria infection var genes are situated in subtelomeric regions close to other variant antigen-encoding genes such as the rif and stevor gene families, while the remaining ∼40% are found centrally in the chromosomes. Based on sequence similarity, var 5′ UTR sequences can be divided into upstream sequence (UPS) classes A, B, C or E. These UPS classes correlate with chromosomal position of the genes, as well as domain complexity of the encoded PfEMP1 var/PfEMP1, and two intermediate groups B/A and B/C, that contain var/PfEMP1 with chromosomal position or domain composition different from that predicted from their UPS class. The hyper-variable var gene repertoire is to a large extent generated by frequent meiotic ectopic recombination in the mosquito abdomen, probably facilitated by alignment of var genes in the nuclear periphery var gene repertoire during human infection var genes, var1 and var2csa, that were conserved in all three genomes, and a semi-conserved gene, var3, found in IT4 and 3D7. The three conserved var genes are more than 75% identical over multiple domains, whereas most other PfEMP1 (even proteins with the same domain architecture) display less than 50% amino acid sequence identity between individual domains Var2csa is particularly unique as it has a unique UPSE, encodes unique Duffy binding-like (DBL) domains, as well as a distinct acidic terminal segment (ATS) The majority of the parasite's ∼60 PfEMP1-encoding var repertoires, each reflecting the worldwide var diversity that has ensured the optimal survival of the parasite population. The clinical significance of the described var groups has been demonstrated in several studies, and indicates the existence of underlying functional differences in adhesion characteristics of the expressed PfEMP1 variants. This relationship is best illustrated by the malaria syndrome occurring in pregnant women, which is precipitated by the accumulation, in the placenta, of parasites expressing VAR2CSA that mediates binding to proteoglycans on syncytiotrophoblasts var genes have been linked to disease severity in studies of expression of these variants in patients with symptomatic and asymptomatic infections Thus, parasite genomes appear to harbor essentially similar In contrast to pregnancy malaria, it is still unclear which human receptor binding, if any particular, is linked to severe forms of childhood malaria. Parasite adhesion has been demonstrated to endothelial cells, immune system cells, uninfected erythrocytes and platelets. Several human cell receptors, including the extensively studied CD36 and intercellular adhesion molecule 1 (ICAM-1), have been implicated in adhesion, although no consensus on association between receptor binding and severe malaria has been reached , RAJ116 from India (7.3× coverage), IGH-CR14 from India (10.19× coverage), and the Ghanaian isolate PFCLIN (8× coverage). Domain architectures of 399 PfEMP1 are aligned, revealing conserved domain architectural features. The homology block concept, first described by Smith et al. (2000) In this work, PfEMP1 repertoires from seven genomes are annotated with updated domain boundary definitions. The data includes four thoroughly sequenced var gene sequence analysis was based on two different bioinformatics approaches. First, phylogenetic trees were constructed using re-assessed PfEMP1 domain borders, with the aim of reclassifying and annotating the main PfEMP1 features UPS, NTS, DBL, CIDR and ATS. Secondly, a novel iterative homology detection method, defining a set of homology blocks, was used to describe domain similarities and to guide var gene recombination site and functional predictions.The In total 399 PfEMP1 sequences were annotated and their domains aligned. The alignments confirmed what recent studies of the DBL fold var genes were analyzed by two different methods: Markov clustering (MCL) The 5′ upstream sequences of var sequences varied between the seven studied genomes (39 to 63), the genomes contained similar var UPS distributions , although only limited information on chromosomal location was available. Based on domain annotation of the extracellular part of PfEMP1 , and component 4 was found in both group A and B but rarely C.Although the number of available ibutions , and as f PfEMP1 , these cPfEMP1 inter-domain (ID) sequences were also aligned and classified. Most ID sequences were found to flank component 3, and characteristic for these sequences were long Pro-rich stretches, charged polyAsp/Glu stretches, and an amino acid composition biased towards Ala, Asp, Glu, Pro, Lys, and Val. The sequences downstream of component 3 could be classified, and were either of a M3A type if flanked by component 4, or M3AB if flanked by TM-ATS . Due to The function of the ID sequences is unknown, although one possibility is that these regions confer elasticity to the PfEMP1 proteins, as suggested for similar sequence in the PEVK region of the human striated muscle protein titin . The PEVK region of titin contains several PPAK domains, a 26–28 residue repeat consisting of low-complexity sequence biased towards Pro, Ala, Val, Lys, and Glu, and these domains are interspersed by polyGlu regions. The PEVK region length is correlated with elongation ability of sarcomeres in striated muscle The PfEMP1 ID regions are found in lengths up to ∼200 residues, and the amino acid composition is very similar to the one found in titin PEVK. Hits to the Pfam PPAK domain definition The redefinition of domain borders, and the large increase in sequence data, called for a detailed subclassification of PfEMP1 domains. This was done by a distance tree analysis described in detail in var genes predominantly recombine separately.Annotation of the PfEMP1 using detailed DBL and CIDR subclassification  showed tIn conclusion, the phylogenetic domain analysis allowed classification of all PfEMP1 domains, and defined several novel domain classes. In addition, PfEMP1 domain variation was described in an unprecedented level of detail, by the allocation of the DBL and CIDR domains into subclasses. This classification is based on domain similarities averaged over the whole domains, opposed to local similarities which may vary across the length of the domains, as described in the homology block analysis below. The validity of the classification must be experimentally tested, but the association between domain and UPS class suggests, that at least some of the domain subclasses confer specialized cytoadhesion properties.Conserved domain compositional features in PfEMP1 molecules were studied in alignments of annotated PfEMP1 sequences. Alignments guided by conserved C-terminal and N-terminal domain architectures are given in var genes var1, var2csa and var3  were found in other group A var genes . Taken together, this indicates that var1 often is found as truncated gene, and that the particular functional properties of VAR1 may have moved to other PfEMP1 variants. Similarly, a VAR3 sequence corresponding to 80% of the exon1 as well as exon2 was found in the 3′ end of RAJ116var03, consistent with how DBLζ and DBLε domains are positioned in other PfEMP1. The domain composition variation within the three most conserved var genes highlight the importance of ectopic recombination of large single or multi domain elements for the generation of PfEMP1 diversity.The three conserved P. falciparum genomes as well as in P. reichenowi.Among the novel domain composition phenomena, domain cassette 5  was the Interestingly, nearly all DBLζ and DBLε domains were found in C-terminal domain cassettes  and often occurred in genes encoding CIDRγ1/2/9 domains (approx. three of four CIDRγ1/2/9 domains flank DBLζ and DBLε domains). The unambiguous partition of DBLε subclasses and the positional and compositional similarities between different DBLε, could suggest that specialized functions reside in these structures.In the PfEMP1 N-terminal, DBLα subclasses correlated well with the subclasses of their neighboring CIDR domain . As expeSeveral more elusive domain architectural constraints were observed, which may crystallize into domain cassettes if higher sequence depth is acquired. These included the group A specific domain combinations DBLα1.4-CIDRα1.6/7-DBLβ3, which both could represent the core of what have been proposed as VAR4  were able to define a set of ten homology blocks with an average length of 21 amino acids, conserved in all DBL domain classes var genes, as the short homology blocks are less inclined to group unrelated sequences which may be forced together in longer domain alignments.DBL domains consist of hyper-variable and conserved regions, as previously described The term homology block (HB) refers to a sequence profile defined from a multiple sequence alignment, here described by a hidden Markov model (HMM) Starting from a full sequence database, homology blocks were one after one first defined and then excluded from the database. Each homology block was defined to be the sequence profile with the highest number of occurrences in the database, i.e. the most conserved sequence, with boundaries optimized to match this criterion. Sequence similarity was assessed with HMM log-odds scores, and a significance threshold of S≥9.97 bits was used for all homology blocks, to ensure that each member of a homology block was at least 1000 times more likely to be related to the sequence profile, than to a random sequence with amino acid frequencies as in the database. Thus, a set of homology blocks was defined, where each homology block comprises all related sequence stretches in the database. The method is described in detail in P. falciparum genomes were in the dataset, and the main interest was to determine sequence features conserved in most of these genomes.The analysis was performed on a database with 311 PfEMP1 sequences containing information on the entire molecule or a full exon1. Twenty DBL containing paralogs were also included to enable estimates of evolutionary relationships. The minimal length of the homology blocks was set to seven amino acids, as this is approximately the length required to reach the sequence similarity significance threshold. Sequences with less than five homologs in the database were not included in the homology block set, since PfEMP1 from more than seven Characteristics for the resulting 628 homology blocks are shown in 88 PfEMP1 were not in the HB definition sequence set, and when the 628 defined homology blocks were predicted in these proteins, 82.5% (SD ±4.9%) of each PfEMP1 were on average covered by HBs, similar to the coverage in the definition sequences , showinghttp://www.cbs.dtu.dk/services/VarDom/ In the following, the HB distribution in PfEMP1 is presented, and several references are made to specific homology blocks. These blocks as well as the sequences they occur in can be inspected using the VarDom server.The VarDom server was developed to provide an interactive graphical interface to analyze information on domain classes, homology blocks and their distribution in PfEMP1 sequences. Alignments and other related files can be downloaded, and it is possible to submit new sequences to annotate them with domains and homology blocks, to classify them and relate them to other sequence groups in the seven genomes: The five most prevalent homology blocks in PfEMP1 (HB1–5) were present in nearly all DBL domains. The relative positions of these five HBs in DBL domains were conserved , and witSide chains in conserved amino acid positions were mainly directed towards other conserved parts, although some were pointing outwards probably to interact with other less conserved domain parts . Functioet al. (2000) HB1–5 were found among the 10 homology blocks defined by Smith Homology blocks specific for all CIDR domains were also found, and they were present in the most conserved part of CIDR, the designated minimal CD36 binding region or M2 et al. (2008) Side chains of conserved residues in HB1, 8 and 10 were mainly directed towards the center of the CIDR three-helix bundle , where tJust as PfEMP1 can be represented as strings of amino acid symbols or strings of domain names, they can be represented at an intermediate level as a string of homology blocks. To study similarities between DBL domains, the homology block sequences of 1043 DBL domains, consisting of 378 different HBs, were studied . OccurreMany of the domain classes derived from trees based on amino acid alignments , were alDomain subclasses  could ofDBLα1.3 of VAR3 contained HB17 and HB19 which were characteristic for DBLα domains  S1, but DBLpam1 and 2 shared homology blocks with DBLα/β/ζ, while DBLpam4 and to a high degree DBLpam5 and 6 shared blocks with DBLγ/δ/ε . InteresSimilarities between major DBL classes also varied considerably across the length of the domains , and a mIn the N-terminal, a clear division was found between DBLα/β/ζ and DBLγ/δ/ε, best defined by HB11 and HB13, respectively , S2a. AtThe C-terminal of DBL domains could also be divided into two major groups, consisting of the S3 subdomains of DBLα/δ and DBLζ/β/γ/ε, respectively , S3. DBLN- and C-terminal ends of several major DBL domain classes thus appear to have different sequence similarities, most likely reflecting that the sequences have been joined through recombination, often with a break point around HB2, and they therefore have different evolutionary histories. Phylogenetic classification based on whole domain sequence alignments will tend to be an average of such different histories.Identification of adjacent genetic regions with different evolutionary histories is a widely used method for detecting recombination break points in distantly related sequences Relations among sequences of the S3 DBL subdomain clearly differed from those of S1 and S2 . DBLα anvar gene has been found to be the target for protective antibodies In agreement with the homology block analysis, the division between DBLα/β/ζ and DBLγ/δ/ε was well supported by bootstrap values in both S1 and S2, as was the separation of each of the domain classes DBLα, β, and ζ , suggesting that IE can bind to αvβ3 integrins Integrins are a family of cell surface membrane receptors, mediating binding to the extracellular matrix, as well as interacting with plasma proteins and counter receptors on other cells, thereby involving them in basic processes such as cell adhesion, cell migration and cell-cell communication. Integrins are heterodimers composed of two membrane anchored subunits, α and β of which the human genome encodes 18 and 8 variants respectively, combining into 24 known, human receptors The amino acid trimer motif Arg-Gly-Asp (RGD) is commonly found in integrin binding proteins, including disintegrins, ornatin, and many extracellular matrix proteins. The RGD motif mediates binding to several integrin receptor variants, a binding which often can be out-competed by synthetic RGD peptides, confirming the surprising simplicity of this adhesive interaction −6, cumulative binomial distribution with x = 23 motifs, p(RGD) = (244 motifs / 4099411 AA), n = 138055 AA). PfEMP1 domains from seven genomes were then searched, and significantly higher numbers of RGD motifs than what should be expected for random reasons (taking the skewed PfEMP1 amino acid distribution into account) were found in DBLα0  = 1.77*10−4, n = 98157 AA) and to a lesser degree in NTS  = 1.77*10−4, n = 20511 AA). Only one motif was found per DBLα0 domain, and all seven genomes had RGD-containing DBLα0 domains. Interestingly all RGD motifs were evenly distributed in three fixed positions in DBLα0: (1) HB19 position 6–8, (2) HB12 position 14–16 and (3) HB7 position 15–17.The 3D7 proteome was searched for occurrences of the RGD motif, and a high number of motifs was found to be present in PfEMP1 , and especially RGD position 2 and 3 were exposed on a loop in subdomain S3, between the helices covered by HB1 and HB2, held in place by several Cys residues.PfEMP1 similarity to disintegrin and ornatin was found by searching 311 PfEMP1 against the Pfam domain database et al. (1998) The finding of two independent significant sequence features pointing towards integrin binding, and on top of this, the co-localization of these features in DBLα0, suggests that some DBLα0 domains are likely to mediate integrin binding, which may also be the phenomenon observed by Siano In relation to this, pentamidine is an RGD analogue used for treatment of many pathogen-caused diseases including malaria 158 homology blocks found in 552 CIDR domains were aligned and clustered by HB composition . CIDR doIn M2, which for some CIDRα has been proven to mediate CD36 binding Using the VarDom server, two HBs were found in the helix-loop of the MC179 CIDRα structure: HB32 covering helix a and b , which is required for protein transport to the host erythrocyte NTS homology blocks were aligned and sorted according to HB composition  NTS. TwoHB155 and HB264 were found in the N-terminal of group A PfEMP1, containing the characteristic motif MGxxx[S/T] required for the lipid modification N-myristoylation  NTS. N-tP. falciparum share the common eukaryotic motif MGxxx[S/T] P. falciparum proteins are N-myristoylated. The two homology blocks, HB155 and HB264 were present in 41 PfEMP1 N-terminals  than other PfEMP1 N-terminals . Other tin vivo.The potentially affected group A PfEMP1 have been associated with severe malaria 52 homology blocks had more than 50% of their occurrences in inter-domain regions, i.e. outside defined domains. Three of the most frequent inter-domain homology blocks are shown in The Cys-containing M3 regions (M3A and M3AB) were found to be positionally linked to the upstream CIDR domain, while the amino acid composition correlated more highly with the downstream domain architecture. Two homology blocks were able to capture most occurrences of the two Cys-residues found after CIDRβ and γ, despite of the surrounding low-complexity sequence, seeing that a few other positions besides the Cys were conserved  M3.Homology blocks of the conserved ATS were aligned and sorted according to domain composition, to describe variation in the intracellular part of PfEMP1  ATS. ATSATSvar1, ATSB17, and the ATS of VAR2CSA, were characterized by lacking the final three homology blocks conserved in all other ATS .var2csa genes in the HB3 genome had an ATSB14 more similar to the ATS of non-VAR2CSA PfEMP1, however these were truncated before the final three homology blocks. Other VAR2CSA ATS had normal length but contained unique sequences instead of the three conserved homology blocks. The five var1 genes possessing an exon 2, were all flanked by a 3′UTR encoding the three missing homology blocks. Compared to a common ATS, ATSvar1 was missing ∼150 AA, ATSB17 was lacking ∼100 AA, whereas the ATS of VAR2CSA was missing or differed from the final 100–130 AA.ATSB17 was found in six group C PfEMP1, distributed in six genomes (not IT4), and containing several DBLβ/γ domains. The two The finding that VAR1 and VAR2CSA both have a shortened ATS, could suggest that ATSvar1 is functional despite of truncation, and question the hypothesis that VAR1 exclusively exists as a pseudogene.The final three ATS homology blocks could be a non-essential functional element in PfEMP1, for example acting as signal peptide during transport to the erythrocyte membrane, which would result in differences for VAR1, VAR2CSA, and ATSB17 PfEMP1, compared to other PfEMP1.Phosphorylation occurs mainly at three types of residues: Ser, Thr and Tyr, and all three residues were markedly conserved in several homology blocks. Phosphorylation is a common modification of proteins expressed during the erythrocyte stages, and has been associated with differences in IE adhesion properties Judging from phosphorylation site predictions and conservation levels in the homology blocks, some examples of conserved potential phosphorylation sites were, in DBL domains : HB19 poIt will be interesting to see if some of these sites are surface-exposed and thus accessible to kinases, as the introduction of large, negatively charged phosphate groups could result in conformational changes, or contribute to charged binding surfaces, and thus result in functional and antigenic variation.Homology block sequences of full-length PfEMP1 were aligned, to determine HB associations with specific positions in the whole proteins, as well as to find groups of PfEMP1 with similar HB compositions. Sequences were sorted according to NJ-clustering based on Manhattan distances between feature vectors consisting of exon 1 HB counts. The homology block alignment shown in var genes were not clear enough to form separate clades in the tree, though homology blocks specific for UPSA-flanked var were observed in both ends of the alignment  conserved residues predicted to be phosphorylation sites, and (4) PfEMP1 inter-domain regions, which are proposed to be elastic disordered structures.Several conserved elements were described by the homology blocks, including: (1) DBL domain core interactions conserved in all DBL domains, holding the subdomains together, (2) an acylation motif found to be conserved in group A The novel iterative homology block detection method is potentially applicable to any protein dataset, and would be especially suitable for compositional analysis of other frequently recombining gene families.var expression data from microarrays and short high through-put sequence reads or the design of recombinant proteins for immunizations or functional studies could all benefit from this detailed account of PfEMP1 diversity and ultimately aid the development of PfEMP1 based malaria interventions.The VarDom server was introduced, where all presented information on domain classes and homology blocks can be retrieved, and new sequences can be classified and related to other PfEMP1 proteins in the seven genomes. Ideally, the server will allow better interpretation and facilitate the development of new approaches in PfEMP1 research. For example analysis of var genes and var gene containing contigs were retrieved using BLAST, from NCBI nucleotide database and from genome assemblies of P. falciparum clones 3D7, HB3, DD2, IT4/FCR3, PFCLIN, RAJ116, IGH and P. Reichenowi clone PREICH at PlasmoDB, Broad and Sanger Institute servers, querying 3D7 var sequences. For all var genes with intact N-terminal segments, 2000 bp 5′ UTRs were also retrieved where possible. In total 399 annotated genes and open reading frames spanning over the length of at least two DBL/CIDR domains were kept for the sequence alignment and distance tree analysis, whereas the homology block dataset consisted of the 311 full length or exon1 sequences, as well as 20 DBL-containing paralogs from Plasmodium falciparum, vivax, yoelii and knowlesi. For meaningful interpretations, the first approach required sequence lengths spanning at least two PfEMP1 features, whereas the latter, was based on whole or exon1 sequences to avoid generating false homology block break-points. Nucleotide sequences of all var genes analyzed in this study are available in Annotated Large phylogenies comprising all DBL or CIDR sequences were inferred by multiple sequence alignment using MUSCLE (version 3.7) followed by application of the neighbor-joining algorithm implemented in MEGA (version 4.0.2) Major domain-class sequences were further subclassified through a recursive process involving: (1) re-alignment of sequences, (2) construction of a maximum likelihood tree, and (3) split of sequences into two clusters at a tree bipartition validated by at least 50% of the bootstraps. If a suitable bipartition was found, the process would be repeated for each of the two formed clusters. If the sequences on the other hand were not divided, they were all assigned to the same subclass and given a number. In addition to bootstrap support, two other properties were used to evaluate bipartitions and determine if and where the trees should be split: the number of genomes represented in each cluster, and the within-cluster average distance (WCAD), which was used as a measure for the relatedness of clustered sequences. See Multiple sequence alignments of PfEMP1 domains were performed with AQUA Sequences were aligned with MAFFT (version 6.240) using the L-INS-i algorithm for multiple sequence alignment var genes was reached   reached .Trees were rendered and edited using Dendroscope (version 2.3) The iterative homology search procedure used for defining the set of 628 homology blocks is described in Alignment of homology blocks was performed with a python implementation of the Smith-Waterman algorithm with linear (non-affine) gap penalty and a substitution matrix of the identity type To estimate trees based on homology block composition, homology block feature vectors were constructed for each sequence, either binary  or with counts (PfEMP1 tree), and accordingly distances were calculated as either Hamming or Manhattan distances. Trees were constructed as extended 50% majority rule consensus trees, based on 1000 neighbor joining bootstrap trees, built from distance matrix using ordinary neighbor joining implemented in Clearcut (version 1.0.8) Sequence logos were generated using WebLogo (version 2.8) Phosphorylation sites were predicted using NetPhos 2.0 Dataset S1Var gene sequences.Var gene cDNA encoding the PfEMP1 analyzed in this study. Sequence names in this fasta-file are the same as used everywhere else in this study, as well as on the VarDom server.(2.84 MB TXT)Click here for additional data file.Figure S1Major DBL and CIDR domain classes. (A) NJ tree based on amino acid alignment of 1242 DBL sequences. Blue dots mark branches dividing DBL domains into six major groups and four N-terminal VAR2CSA DBL classes. (B) NJ tree based on amino acid alignment of 655 CIDR sequences. Blue dots mark branches dividing CIDR domains into four major groups as well as the CIDRα1 and CIDRpam subclasses. Leaf names are omitted from the figure to improve graphical presentation.(2.49 MB PNG)Click here for additional data file.Figure S2Trees showing subclassification of all major PfEMP1 domain classes. ML trees based on amino acid alignments of each of the following domain classes are shown in panels A–M: DBLα0, α1, β, δ, ε, γ, ζ; CIDRα, β, γ, δ; NTS; ATS. Sequence names as well as start and stop position of the domains are given in the trees, followed by classification of the domain. Panel N and O: Assignment of sequences to UPS groups by Markov clustering (N) and neighbor joining (O). The UPS groups were named as indicated by the text color. The background colors show the group membership assigned by Kraemer et al. 2007 N) The branch labels show the fraction of Markov clusters with this group present. (O) The branch labels show the bootstrap values as fractions of 1000 bootstraps. Monophyletic subgroups with a bootstrap support above 0.7 and containing sequences from at least four different strains of P. falciparum are highlighted with thick red branches. Some subgroups were further expanded (without bootstrap support) to form larger monophyletic groups: UPSA2 and UPSB3 are expanded to include additional sequences annotated to UPSA2 and UPSB3 respectively by Kraemer et al. 2007 (1.11 MB ZIP)Click here for additional data file.Figure S3PfEMP1 domain class logos. Sequence conservation logos for major PfEMP1 domain classes (panel A–Z): CIDRα, α1, α2, α3, β, δ, γ, pam; DBLα0, α1 (without α1.3), α1.3, β, δ, ε , ε1, ε2, ε11, ε13, εpam4, εpam5, γ, pam1, pam2, pam3, ζ; NTSA, NTSB, and M3AB.(2.42 MB ZIP)Click here for additional data file.Figure S4Annotated PfEMP1 sequences aligned according to C-terminal (A) and N-terminal (B) domain compositions. Gene names, parasite genome, 5′ UPS classes, PfEMP1 domain annotation  and origin of sequence data (if sequence is not previously reported as var gene) are given. Sequences which partially contain unexpected identical sequence stretches to other sequences suggesting an incorrect contig assembly are noted “HBD” followed by the name of the potentially redundant sequence. Red arrows indicate component 1–4. Frames indicate clusters of correlated domain classes. 1:VAR1; 2: VAR2CSA; 3: VAR3; 4: DBLζ and DBLε domain combinations of component 4; 5: Cassette 10; 6: Cassette 6; 7: Cassette 9; 8: Cassette 5; 9: Other Group A PfEMP1 all containing component 2; 10: Cassette 8; 11: Group B and C genes containing component 2; 12: Group B and C PfEMP1 with no component 2 or 4; 13: Cassette 14; 14: Cassette 17,21 and 22; 15: DBLα1-CIDR subclass correlations including cassette 11,13,15 and 16; 16: DBLα0 subclasses associated with CIDRα3 subclasses; 17: DBLα0 subclasses associated with CIDRα2 subclasses. N-terminal segment (NTS), Duffy binding-like (DBL), Cys-rich inter-domain region (CIDR) and acidic terminal segment (ATS) are named according to the distance tree classification. Inter domains are annotated as either short if <32 AA (green) or long if >31 (yellow) and “A” or “B” if encoding M3A or M3AB.(0.15 MB PDF)Click here for additional data file.Figure S5Schematic representation of annotated var genes sorted by genome origin. Gene names, 5′UTR class, domain architecture and origin of sequence data (if sequence is not previously reported as var gene) is given. Sequences are noted “F” (Fragment) in comments if predicted not to span a full length exon1, and “HBD” if incorrect contig assembly is suspected followed by the name of the sequence which partially contains unexpected identical sequence stretches. N-terminal segment (NTS), Duffy binding-like (DBL), Cys-rich inter-domain region (CIDR) and acidic terminal segment (ATS) are named according to the distance tree classification.(0.05 MB PDF)Click here for additional data file.Figure S6Phylogenetic trees for DBL subdomains S1, S2 and S3, as in  but with labels. Edge values are fractions of 1000 bootstraps, and each subdomain is given as: protein name, start position, end position, and the domain class the subdomain is a part of.(0.22 MB PDF)Click here for additional data file.Figure S7Homology block alignments. Homology block alignments for (panel A–E): DBL, CIDR, NTS, ATS, and whole PfEMP1, with details of (0.82 MB ZIP)Click here for additional data file.Figure S8Tree in  with labels. Bootstrap values are given as fractions of 1000 bootstraps.(0.33 MB PDF)Click here for additional data file.Table S1Examples of HB combinations specific for DBL and CIDR domain classes. Domain counts and number of matches of the HB combination are given for the sequence set with 311 PfEMP1 sequences. The domain combination  signifies a sequence where both HB17 and HB19 are present. These homology blocks are suggested for use in oligonucleotide array design, as well as for functional analysis of the domain types. The list is not exhaustive, and can be supplemented using (0.11 MB PDF)Click here for additional data file.Table S2Homology blocks specific for component 1–4 . Homology block numbers are given in parenthesis, and number of occurrences in the component with 311 sequences, is given next to the number of occurrences elsewhere. These homology blocks are suggested for use in oligonucleotide array design, as well as for functional analysis of the components. The table is not exhaustive.(0.09 MB PDF)Click here for additional data file.Text S1PfEMP1 domain classification by alignment and distance tree analysis.(0.15 MB PDF)Click here for additional data file.Text S2Defining PfEMP1 homology blocks.(0.81 MB PDF)Click here for additional data file.Text S3PfEMP1 DBL domain relations to CIDR and paralog DBL domains.(0.31 MB PDF)Click here for additional data file.


In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding.In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins.Our study provides qualitative information about induced fit. These results could be of help for flexible docking. Most of biochemical reactions inherent to the life of a cell are mediated by protein-protein interactions, e. g. the recognition of a substrate by an enzyme, or an antigen by an antibody. Protein-protein interaction is influenced by several factors like the size and shape of the interface, shape complementarity between interacting proteins or hydrophobicity ,2. InterThe prediction of protein-protein interactions is a current challenge. Some bioinformatic methods have been developed in order to predict whether or not two proteins interact -25. WhenThe extend of induced fit modification in protein-protein complexes has been previously studied. A study made by Betts and Sternberg in 1999 revealed that, in a dataset of 39 protein-protein complexes, a half exhibited substantial movements, when compared to pairs of similar proteins solved by different groups . It has via a structural alphabet developed in our lab. We consider a set of protein-protein complexes for which the crystallographic structures of both the complex and free partners are available, and quantify the structural changes in terms of structural letter modifications. We also use a control set of 14 protein pairs for which the structures has been independently determined by a different team, as in , specifically describe β-strands. Letters [a] and [A] are the most regular, [a] being slightly shorter. It has been shown that linear helices are encoded by runs of [A], and curved helices are encoded by runs of [a] , , , , , , [F], and [J].The 27 structural letters, named , are shown on Figure s of [a] . The 18  letters . It has msdintra . Figure control set to assess the local structural changes observed in a data set of 68 protein-protein complexes, denoted as the complex set. In the control set, 1,128 structural letters are modified out of 4,072(28%). The total number of structural letter pairs considered in the complex set is 32,356. Overall, 20,679 structural letters are unchanged (64%), and 11,677 are changed (36%). This proportion is significantly greater than the proportion in the control set, as assessed by a Chi-square test .A set 14 protein pairs solved by different groups is used as a dev threshold  and 11% of the complex set is modified . These proportions are significantly different as assessed by a Chi-square test .If we consider the 8 groups of structural letters with a 1 Å rmsdThe global compositions of bound and unbound chains, in terms of structural letters, are similar (data not shown), except for helical letters [A] and [a]: bound conformations have more [a] and less [A] than unbound conformations.complex set: enzyme-substrate, antibody-antigen, and others. Table There are 3 classes of complexes in the control set. Thus, on the limited number of structures available (10 antibody-antigen complexes), this class of proteins shows only moderate modifications upon protein-protein binding. The 'other' class experiences the highest percentage of structural letter changes (40%). This class encompasses different kind of complexes . The enzyme class has an intermediate behavior with 32% of modifications. In their study, Daily et al found that 20% of the residues in enzymes are significantly modified upon binding  and [a], and 1.6 Å between [D] and [S]. Furthermore, the structural letters have different intrinsic variability, as measured by the rmsdintra. The rmsdintra of the structural alphabet varies from 0.08 Å for letter [A], to 0.91 Å for letter [F] [The structural alphabet provides a simplified but detailed description of the protein backbone. As shown on Figure tter [F] . The condev associated to the structural letter change between bound and unbound forms. For the measure using classical rmsd, we computed local Cα rmsd in a sliding window of four residues along the protein. The reason why we choose a size of four residues for the sliding window is because the structural letters are four-residue long. The results of this comparison on the complex set is shown in Figure intra, instead of rmsddev, which is a measure of the intrinsic variability of each structural letter. A few cases of identical structural letters correspond to high local rmsd. These cases correspond to fragments that are surrounded by structural letter substitutions. For example, fragment 64–69 of the R chain of the ligand part of complex 1WQ1 is encoded by QFO in the unbound form and FFE in the bound form. The fragment encoded by the central F has a local rmsd equal to 1.9Å. The case of different structural letter between bound and unbound forms is called a structural letter substitution . Among 598 isolated substitutions associated with rmsd dev greater than 1 Å, 418 correspond to local rmsd lower than 0.5 Å i. e., 70%. If we consider only stretched substitutions, this ratio is only 15% (116 out of 753). This effect is thus more frequently seen in isolated substitutions than in stretched substitutions. This can be globally assessed by the Pearson correlation coefficient between local rmsd and rmsddev: 0.50 for isolated substitutions and 0.87 for stretched substitutions. These cases correspond to fragments with low rmsd but encoded by highly dissimilar structural letters. They are due to the stochastic nature of the structural encoding using a HMM.Structural deformations between bound and unbound forms is usually assessed using classical rmsd computation. In that section, we show a comparison between the assessment of deformation using the structural alphabet and classical rmsd. The measure of deformation using the structural alphabet is given by the rmsdn Figure  and 3c. n Figure  and subsdev alone cannot be used to quantify the structural change. This analysis tells us that although the structural alphabet offers a unique original tool to detect and qualitatively describe structural deformation, this information has to be combined with the local rmsd in order to properly measure the deformation.A consequence is that the rmsdcomplex set, 3,746 are thus defined as interface residues. Interface residues then represent 12% of the whole dataset (i. e. both surface and core residues).The interface regions are defined using Voronoi tessellations. Among the 32,356 residues in the interface set is compared to the global composition of the complex set on Figure complex set. It is in agreement with the study of Ansari et al  but some particular letters are not:  (strand ends). The statistical significance of structural letter preference for interface regions is assessed by Z-scores computation, illustrated on Figure The local structure composition of the ri et al  who show-16).A total of 3,746 structural letters are involved in the interface: 2,217 (59%) are unchanged and 1,529 (41%) are changed. If we consider the 8 groups of Figure interface set than in the control set, we compute Z-scores (data not shown). All the structural letters, except [a], are more modified in the interface set than in the control set. The difference is significant for 19 letters out of 27, particularly high for letters I, Q, J, and K.To assess if each individual letter undergo more substitutions in the control set, helical letters  experience the highest Nsub, around 3–5. It means that these letters are replaced, on average, by three to five different letters. Extended letter  have Nsub around 2. Among the structural letters that describe coils, only letters  have a Nsub greater or equal to 2. It indicates that the expected variations in structural sequences caused by experimental error and natural protein flexibility affect preferentially helices, strands in a lesser extend, and a few coil letters. It is known that loop regions are more flexible that regular secondary structures. The variations observed in helix and strand structural sequences may be due to the fact that our structural alphabet offers a very detailed description of these regions.The number of possible substitutions (Nsub) for each type of structural letters are reported in Table control and the interface sets: high Nsub for helical letters, some of the extended letters and a few coil letters. However, the Nsub computed from the the complex set are higher than the Nsub computed from the control set. The interface region analysis results, in a majority of cases, in higher Nsub than in the complex set, confirming that interface regions undergo more various structural changes. The Nsub are one to two points greater in the interface set than in the control set, except for letters [J] (+4.3), [R] (+2.9) and [E] (+2.8), resulting in Nsub greater than 5 for these letters. On the contrary, letter [D] has the lowest Nsub, equal to 2. This analysis thus reveals that some structural letters are particularly affected by the binding .The same global tendency is observed in the complex set, 25% of the fragments have local rmsd greater than 0.2 Å, and 35% if we restrict to the interface fragments. It thus appears that interface regions undergo more severe local changes than the rest of the structure.The quantitative measurement of structural letter changes is assessed using the local rmsd. In the control set, 5% of the fragments show a local rmsd greater than 0.2 Å. We will then use 0.2 Å as a threshold to select significant local deformations. In the interface set depending on the structural encoding. For each structural letter, we collect the local rmsd and display the number of structural letters affected by a local rmsd in a given range. The unbound form is taken as a reference for this analysis. Helical structural letters  experience very few local rmsd greater than 0.2 Å, indicating that α-helices are very stable local structures and are barely affected by the interaction. Among them, letter [Z], which is found at helix borders, shows the highest proportion of local rmsd greater than 0.2 Å. Extended letters  exhibit higher rmsd, indicating that these local structures are more likely to be modified upon binding, especially letter [L]. The highest number of high local rmsd are observed in coil letters, in particular in letters . Some coil letters, like , are barely affected by the binding.Figure It thus appears that the severity of local deformation is not uniform among the structural letters, in particular among structural letters describing coils. Some structural letters are more likely to be affected by the formation of protein-protein complex.Now that we have shown that some structural letters are preferentially affected upon binding, the next step is to analyze the resulting conformation after binding, namely the structural letter substitutions. Figure For example, extended letters  display high probabilities to be substituted into letter  upon binding. The probability for letter [Z] to be transformed into [V] in the interface region upon binding is 8.8%, whereas it is 28.6% for the inverse transformation from [V] to [Z]. This arises from the normalization with respect to the unbound form needed for the probability computation. The substitution count table is nearly symmetrical, as shown in additional file Many substitutions occur within the helical group , and, in a lesser extend, in the extended group . These substitutions are responsible for subtle modifications of regular secondary structures, like illustrated in Figure The structural alphabet thus provides a new way to describe local structural changes as the substitution of a structural letter by another one. It is the first time, to our knowledge, that such a qualitative description is reported.α rmsd equal to 0.7 Å between bound and unbound forms and 47% of the structural letters are modified. A structural modification of region 98–106 includes 2 substitutions associated to local rmsd greater than 1.5 Å: [H] to [O] and [L] to [Q]. A less severe substitution  occurs from [I] and [D]. 1WQ1, shown in Figure α rmsd is 1.1 Å and its percentage of structural letter substitution is 51%. In region 28–39, a run of 7 successive structural letters undergo modifications greater than 0.5 Å, whereas in region 58–70, a run of 8 successive structural letters are strongly modified. Region 58–70 involves letters , which are over-modified in interface regions. 1ACB, shown in Figure Figure α rmsd for chymotrypsin (receptor) is 1.75 Å and the percentage of structural letter substitution is 37%. For eglin (the ligand), global Cα rmsd is 1.5 Å and 45% of the structural letters are modified. Both modifications involve letters  which are significantly more modified in the interface set than in the control set. 1DE4, shown in Figure α rmsd equal to 1.65 Å and 49% of structural letter substitution. The transferrin receptor (ligand) has a global Cα rmsd equal to 1.6 Å and 41% of its structural letters are modified upon binding. Both regions involve letters .Structural modifications occur in both partners: region 186–197 in chymotrypsin and region 38–50 in eglin part. The global CA last illustration of the conformational change analysis using the structural alphabet is shown in Figure • we look for structural motifs at least four structural letter long ;• the motif should be present in the bound forms of at least two complexes from different classes. We consider the 3 classes from Table • the motif should be located in totality at the protein-protein interfaces of the complexes;• we do not consider runs of helical letters  or extended letters . Helices and strands being highly abundant in 3D structures, these motifs may be non significant;• a significant local deformation should be seen, at the considered motif, in at least one complex;• the local rmsd between the bound fragments covered by the motif should be lower than the local rmsd between unbound fragments.α rmsd for the corresponding fragment is 1.4 Å between unbound forms and 0.7 Å only between bound forms. Complex 1AHW undergoes only minor conformational change, as assessed by the rmsd equal to 0.4 Å, and a similar unbound structural motif: GOIJ. Complex 1BVN is modified up to an amount of 0.8 Å, starting from a different structural motif: SGRF. The underlying amino-acid sequences are 'LQHGESP' (1AHW) and 'VIDLGGE' (1BVN). Structural motif LLGI is seen in one 'other' complex, 1GRN (complex between a G-protein and a GTPase activation domain) and one enzyme/substrate complex, 1UDI. Both complexes are significantly modified by the binding: 1.9 Å rmsd for 1GRN, from KPQL to LLGI, and 1UDI, in a lesser extend: 0.9 Å rmsd, from LNNG to LLGI. Local rmsd are equal to 2.2 and 0.8 Å before and after binding respectively. Underlying amino-acid sequences are 'YVPTVFD' (1GRN) and 'QLVIQES' (1UDI). These examples highlight the usefulness of the structural alphabet for further analysis studies using larger data sets.Using these criteria, we extracted common bound motifs from proteins with unrelated function. With the rmsd criterion, we select cases where the conformational change induced by the binding put the bound structures closer than the unbound structures, what we call "local structural convergence". Given the limited amount of data we have, and the stringent criteria we applied , we found only a few cases of local structural convergence. Two examples are illustrated in Figure versus 2 in the control set). Concerning the severity of the substitutions, letters  are subject to major modifications.This study reveals that the structural alphabet offers a new way to investigate local deformations induced by the protein-protein interaction. Classical studies revealed that interface regions preferentially involve loops. Here, we show that two structural letters forming helix ends  are preferred at the interface and that only a part of the structural letters describing the loops, , are preferred at the interface. Letters  are particularly affected by the binding  used in this study is described in Table control set is needed. We consider the control set of 14 protein pairs used by Daily and coworkers [To distinguish the structural deformation induced by protein-protein binding from the experimental uncertainty and the expected variations due to protein flexibility, a oworkers :• 5 protein pairs independently crystallized by different groups: 2CBA/1CAM, 1VDQ/1HEL, 1UNE/1MKT, 1EY0/1STN, and 1TPH/1TPW.• 9 pairs of allosteric proteins independently crystallized in the same form: 3CHY/1JBE, 1GDD/1BOF, 1GPB/8GPB, 4HHB/1A3N, 1T48/1T49, 1OIW/1YZK, 1VG8/1T91, 1XTS/1XTR, and 2TRT/2TCT.In this study, the ligand and receptor of each complex, in bound and unbound forms, are simplified into structural letter sequences using HMM-SA and the Viterbi algorithm ,36. LocaA total of 156 couples of bound/unbound chains are used to analyze the local structural changes induced by the protein-protein binding. The principle of the study is illustrated in Figure global rmsd- or for a fragment of the protein -a local rmsd. In this study local and global rmsd are computed using Cα atoms only, using the ProFit software [A classical measure of conformational change is the rmsd (root-mean square deviation), i. e., the mean deviation of atom positions after otimal superimposition of two structures. The rmsd can be computed for the whole protein -a software .rmsddev, as defined in [dev has been computed from 500 fragment pairs randomly chosen in the two structural letters. The rmsdintra, computed in the same way, measures the intrinsic variability of each structural letter.As explained in the Results section, a general distance between two different structural letters is given by the fined in . The rmsdev. Note that the difference between these two rmsd is that the local rmsd is computed for each pair of fragments using proFit, whereas the rmsddev is taken from a pre-computed table, by considering only the structural encoding of the fragments.The structural distance between two fragments of four residues can then be measured using the local rmsd or the rmsdx to letter y is then given by:The use of unbound/bound pairs allows to study the structural modifications as an oriented process: a protein evolves from the unbound state, toward the bound state. The probability to move from letter Nbound(x → y) denotes the number of structural letter x in the unbound form that are replaced by structural letter y in the bound form, and Nunbound(x) denotes the total number of structural letter x in the unbound form. When x = y, this quantity is the probability of being unchanged. Here, we consider that the unbound state is the starting state and the bound state is the final state. Then, the unbound state will be taken as a reference for the computation, and the resulting matrix might be asymmetrical.where The number of possible substitutions for each structural letter can then be computed from the substitution probabilities:H(x) is the Shannon entropy for letter x:were N sub equal to 1 indicates that structural letter x is integrally transformed into one structural letter (it can be itself). The maximum theoretical N sub is 27: it means that structural letter x is transformed into all the 27 structural letters, with equal probabilities.A α, with default parameters. Two residues are in contact if their Voronoi cells share a surface with non-zero area. A structural letter is a four residue fragment. The correspondence is made between a four residue fragment and its third Cα.The local modifications induced by protein-protein binding are studied in more details at the receptor-ligand binding interface. Interfaces are detected using Voronoi tessellations. Voronoi tessellations are a way to divide the space around a given set of points into cells. The Voronoi cell around a point contains all the points that are closer to this point than the others. Voronoi tessellations are used to study contacts within proteins, without the use of threshold distance . Here, Vinterface set.The structural modifications are studied in more details in the interfaces. We will refer to this part of the data as the To study the over-representation of the different structural letters in the interface regions, we compute Zscores defined by:Nobs(x) denotes the observed number of letter x in the interface set and Nexp(x) denotes the expected number of x in the interface if the compositions of interface and non-interface regions were similar:x in non-interface region and Ninter the number of structural letter of any type in the interface set.Nobs(x) the number of structural letter x that is modified upon binding in the interface set, and x to be modified in the control set, and x in unbound form in the interface set.Zscores are similarly computed to assess the over-modification of a given structural letter, with Zscores are expected to follow a Gaussian distribution with mean equal to zero and standard deviation of 1. Significance thresholds are corrected to take the multiple tests into account.JM and HL carried out the comparisons of structural sequences. JM and LR carried out the analysis of the results. ACC and JM conceived the study. All authors read and approved the final manuscript.Structural letter substitution counts in the interface region. This figure presents the counts of structural letter substitutions corresponding to local rmsd greater than 0.2Å, restricted to the interface region. The normalization with respect to the unbound form results in the substitution probability matrix presented in Figure Click here for file


Chitinases are prevalent in life and are found in species including archaea, bacteria, fungi, plants, and animals. They break down chitin, which is the second most abundant carbohydrate in nature after cellulose. Hence, they are important for maintaining a balance between carbon and nitrogen trapped as insoluble chitin in biomass. Chitinases are classified into two families, 18 and 19 glycoside hydrolases. In addition to a catalytic domain, which is a triosephosphate isomerase barrel, many family 18 chitinases contain another module, i.e., chitinase insertion domain. While numerous studies focus on the biological role of the catalytic domain in chitinase activity, the function of the chitinase insertion domain is not completely understood. Bioinformatics offers an important avenue in which to facilitate understanding the role of residues within the chitinase insertion domain in chitinase function.Twenty-seven chitinase insertion domain sequences, which include four experimentally determined structures and span five kingdoms, were aligned and analyzed using a modified sequence entropy parameter. Thirty-two positions with conserved residues were identified. The role of these conserved residues was explored by conducting a structural analysis of a number of holo-enzymes. Hydrogen bonding and van der Waals calculations revealed a distinct subset of four conserved residues constituting two sequence motifs that interact with oligosaccharides. The other conserved residues may be key to the structure, folding, and stability of this domain.Sequence and structural studies of the chitinase insertion domains conducted within the framework of evolution identified four conserved residues which clearly interact with the substrates. Furthermore, evolutionary studies propose a link between the appearance of the chitinase insertion domain and the function of family 18 chitinases in the subfamily A. Chitin is composed of units of N-acetyl-D-glucos-2-amine, which are linked by β-1,4 glycosidic bonds Chitin  Coccidioides immitis (C. immitis) Based on amino acid sequence similarity, chitinases are classified into families 18 and 19 of glycoside hydrolases (GH) S. marcescens chitinase C (chiC), belonging to the subfamily B, has a catalytic domain, a fibronectin type III-like domain, and a chitin-binding domain S. marcescens and Bacillus circulans (B. circulans) Family 18 chitinases can be classified into three subfamilies A, B, and C, in terms of the amino acid sequence similarity 8-barrel fold and has been found in many different proteins, most of which are enzymes. The TIM barrel domains share low sequence identity and have a diverse range of functions. The specific enzyme activity is determined by the eight loops at the carboxyl end of β-strands The TIM barrel domain consists of an (α/β)The CID is the only family in the CID superfamily and is classified as having an FKBP-like fold in the SCOP database  [30]. ThS. marcescens chitinase A (chiA) (PDB code: 1CTN/1FFR) has an additional N-terminal domain S. marcescens chitinase B (chiB) (PDB code: 1E15/1UR9) has one extra C-terminal domain In addition to the TIM domain and the CID, some bacterial chitinases in the subfamily A involved in chitin degradation contain one or two additional domains involved in substrate-binding S. marcescens chiA S. marcescens chiA, the thermal stability was reduced, the specific activity was decreased, the pH optimum was shifted lower, and the catalytic activity towards long chitin derivatives was lost As known previously, the TIM barrel is considered the catalytic domain in family 18 chitinases To identify the specific functional residues on the CID, a multiple sequence and structure alignment of this domain was constructed. The sequence search process revealed that this domain exists in a wide range of organisms. Conservation and hydropathy analysis revealed that four conserved residues, constituting two distinct sequence motifs, interact with the substrate. Furthermore, extensive comparisons among different family 18 chitinases demonstrated that the TIM domains + CID can bind long-chain substrates by providing a deep substrate-binding cleft, while this may not be the case for the enzymes with the TIM domain alone. In general additional modules fused to a catalytic domain may play a role in substrate specificity by providing a specific binding site or shaping the active site to recognize a substrate with a different shape or size B. circulans chitinase A1 (PDB code: 1ITX), C. immitis chitinase (PDB code: 1D2K), and human chitotriosidase (PDB code: 1LG1) was generated by MUSCLE in Jalview  was proposed to catalyze the substrate hydrolysis following the ‘slide and bend mechanism’ as previously described for a long-chain substrate 6Vibrio harveyi chitinase A is considered as an endochitinase based on the current literature S. marcescens chiA, an exochitinase S. marcescens chiB, it was proposed that binding of substrate causes the −1 sugar ring to distort to a boat conformation and rotation of Asp142 towards Glu144, thus enabling hydrogen bonding between the acetamido group, Asp142, and Glu144. Later on the oxazolinium ion intermediate was hydrolyzed, leading to protonation of Glu144 and rotation of Asp142, which shares a proton with Asp140 S. marcescens chiA, after the substrate glycosidic bond is protonated, Asp313 which interacts with Asp311 moves to another position where it interacts with the proton donor residue Glu315, forcing the acetamido group of −1 sugar to rotate. Subsequently, the water molecule that forms hydrogen bonds with Tyr390 and the NH of the acetamido group is displaced to a position which allows hydrolysis to complete S. marcescens chiA , Tyr267 and Arg269 both form hydrogen bonding indirectly by Asp213 with +1 site, and Glu297 directly with −2 site; and Met300 forms a hydrophobic interaction with the substrate  [44]. The.g. 21% in 1ITX). With the exception of some residues which interact with sugar, many of them exist in the hydrophobic core, which may be important for folding and stability. Aromatic residues have been found to play an important role in stabilizing of proteins and peptides The other highly conserved neutral positions contain mostly alanine, glycine, or proline; the latter two frequently occur in the structure of β-turns Elizabethkingia meningoseptica (PDB code: 1EOM) and the NAGase from Streptomyces plicatus (PDB code: 1EDT) are composed of one TIM domain. They break down the glycosidic bond of (NAG)2 to NAG, therefore, they do not have complete chitinolytic activities. In the crystal structure of 1EOM in complex with biantennary octa-saccharide, only the reducing end NAG and two mannoses of the tri-mannose core are in direct contact with the protein Both the NAGase from S. marcescens chiA  was not involved in the saccharide-binding S. marcescens chiA and chiB, B. circulans chitinase A1, and Aspergillus fumigatus chitinase B (PDB code: 1W9P) are ‘bacterial-type’ exochitinases with a deep or even a tunnel-shaped substrate-binding cleft, formed by the TIM barrel and CID S. marcescens chiC Hevea brasiliensis) (PDB code: 1HVQ) ScCTS1 from Saccharomyces cerevisiae (PDB code: 2UY2) Parkia platycephala seeds (PDB code: 2GSJ) Pyrococcus furiosus (PDB code: 2DSK) In CAZy database S. marcescens chiA, a processive exochitinase S. marcescens chiC, which acts as a non-processive endochitinase Structures of TIM domain alone, TIM domain + CID, and TIM domain + CID + N- (or C-) terminal domain align very well with their respective counterparts (data not shown). Interactions between residues and substrates are shown in The ubiquitous TIM barrel fold is adopted by seven enzyme superfamilies, one of which is the TIM barrel GH Since the CID sequences are present in all of sixty archaeal, bacterial, and eukaryal genomes in this study, it is possible that the CIDs were present in the Last Universal Common Ancestor (LUCA) 1) with the incorporation of the CID to form a subfamily A chitinase and 2) with the other domains (e.g. chitin-binding domain) to form a subfamily B chitinase. In the first route, this double-domain chitinase evolved in archaea, bacteria, fungi, plants, and animals, as well as the triple-domain chitinase with the fusion of N- or C- terminal domain in S. marcescens. Subsequently, the double-domain chitinase gene was mutated to have novel functions in animals In the study conducted by Nagano et al. family 18 GH were divided into two functional groups; F4 includes chitinases and F5 includes both hevamine and NAGase e.g.>3) saccharide substrates. Because of the wide distribution in diverse organisms and the high conservation of the CID, we can identify the sequence and predict the structure of this domain in family 18 chitinases in the subfamily A. An evolutionary scheme is presented which places the emergence of the CID in the context of chitinase function; with the addition of the CID leading to an evolutionary shift of the protein from a non-chitinolytic protein, or a NAGase, to a subfamily A or B family 18 chitinase. We also identify a group of conserved hydrophobic residues in the core which we propose are important for folding and structural stability. Research on the role of the CID in function to test this hypothesis can be carried out using a myriad of experimental and computational techniques such as molecular modelling, in vitro and in silico binding studies coupled to site-directed mutagenesis, enzymatic assays, and crystallization of the holo-proteins.Four conserved amino acids identified in this study are proposed to be essential for binding with the substrate and they form two distinguishable sequence motifs. The CID may have inserted into the TIM domain to facilitate orienting and binding to longer (B. circulans chitinase A1 (1ITX), C. immitis chitinase (1D2K), and human chitotriosidase (1LG1) were used as query sequences in PSI-BLAST to search for distant relatives. They represent chitinases within the kingdoms of Bacteria, Fungi, and Animalia, respectively. A plant or archaeal structure was not available at the time however the PSI-BLAST searches did identify plant and archaeal chitinases for inclusion in our study. An initial multiple sequence alignment was made using MUSCLE - multiple protein sequence alignment program in Jalview  The CID regions within the structures of three proteins: An initial structure alignment containing the CIDs from 1ITX, 1D2K, and 1LG1 was generated with the online CE-MC - multiple protein structure alignment program http://compbio.soe.ucsc.edu/SAM_T08/T08-query.html) To verify our sequence and structure alignment, eight representatives of family 18 chitinases structures  were superimposed with CE-MC method The number of each residue in each position was calculated and analyzed by SigmaPlot 10.0 (SYSTAT Software Inc.). The entropy value was calculated by the following equation:Pj(i) is the fractional occurence of amino acid type j at each site, and m is the number of amino acid types used in the particular analysis C(i) = 1−S(i)/ln(m) http://scop.mrc-lmb.cam.ac.uk/scop/) and CAZy (http://www.cazy.org/fam/GH18.html) were chosen to compare the structure and function of chitinases and chitinase-like proteins (see http://www.rcsb.org). All PDB files were visualized and analyzed in either Insight II, version 2005 , Pymol, version 0.99 , or Rasmol, version 2.7. Hydrogen bond calculations and van der Waals radii were determined with Insight II.Select structures from the designated family 18 chitinases in SCOP  was performed with the sixty CID sequences, because the program can produce a multiple sequence alignment of divergent sequences and Cladogram or Phylogram to visualize the evolutionary relationships In order to investigate the evolutionary relationship of the CID sequences from different lineages of life, the ClustalW2 program  and the two conserved motifs on the CIDs. The structures were superimposed with the CE-MC method. (A) The eight structures 1HKM, 1LJY, 1ITX, 1D2K, 1FFR, 1UR9, 1KFW, and 1NWT are coloured in red, orange, yellow, green, blue, cyan, purple, and black, respectively. The aligned, blue, and cyan parts are TIM domain + CID, N-terminal domain on 1FFR, and C-terminal domain on 1UR9, respectively. (B) The two residues in the YxR motif are shown in red and orange, respectively; and the two residues in the [E/D]xx[V/I] motif are shown in yellow and blue, respectively.(4.45 MB TIF)Click here for additional data file.Figure S2The larger multiple sequence alignment of sixty CID sequences from various species. The alignment was generated by MUSCLE in Jalview. It is not edited according to the three model structures. The two conserved motifs YxR and [E/D]xx[V/I] are highlighted in the red frames and the four conserved positions are labelled with red stars. The species names and GI numbers refer to (3.57 MB TIF)Click here for additional data file.Table S1List of twenty-one family 18 chitinases and chitinase-like proteins from plants, bacteria, fungi, and animals. Structures in bold are described and compared in the text.(0.06 MB DOC)Click here for additional data file.Table S2List of the sequence names, species name, and GI numbers of thirty-three more CID sequences that are included in the phylogenetic tree  and the (0.05 MB DOC)Click here for additional data file.


Many well-represented domains recognize primary sequences usually less than 10 amino acids in length, called Short Linear Motifs (SLiMs). Accurate prediction of SLiMs has been difficult because they are short (often < 10 amino acids) and highly degenerate. In this study, we combined scoring matrixes derived from peptide library and conservation analysis to identify protein classes enriched of functional SLiMs recognized by SH2, SH3, PDZ and S/T kinase domains.Our combined approach revealed that SLiMs are highly conserved in proteins from functional classes that are known to interact with a specific domain, but that they are not conserved in most other protein groups. We found that SLiMs recognized by SH2 domains were highly conserved in receptor kinases/phosphatases, adaptor molecules, and tyrosine kinases/phosphatases, that SLiMs recognized by SH3 domains were highly conserved in cytoskeletal and cytoskeletal-associated proteins, that SLiMs recognized by PDZ domains were highly conserved in membrane proteins such as channels and receptors, and that SLiMs recognized by S/T kinase domains were highly conserved in adaptor molecules, S/T kinases/phosphatases, and proteins involved in transcription or cell cycle control. We studied Tyr-SLiMs recognized by SH2 domains in more detail, and found that SH2-recognized Tyr-SLiMs on the cytoplasmic side of membrane proteins are more highly conserved than those on the extra-cellular side. Also, we found that SH2-recognized Tyr-SLiMs that are associated with SH3 motifs and a tyrosine kinase phosphorylation motif are more highly conserved.The interactome of protein domains is reflected by the evolutionary conservation of SLiMs recognized by these domains. Combining scoring matrixes derived from peptide libraries and conservation analysis, we would be able to find those protein groups that are more likely to interact with specific domains. To address this issue, we conducted a global statistical analysis on the conservation of SLiMs recognized by SH2, SH3, PDZ and S/T kinase domains  scores (which measures the relative conservation of a motif) than those sites that do not bind to SH2 domains , including EGFR, IR, KIT, PDGFRB, IGF-IR, VEGFR2, ERBB2, FGFR1, HGFR, RET and TKR-A. We manually extracted interactions from the literature between one of these RTKs and one of the 21 SH2 domains we are studying here, which yielded a total of 76 interactions involving 56 unique Tyr-SLiMs (refer to Table S1 for detail). Using our SLiM conservation calculation, we found that reported SH2 binding sites have significantly higher  ln of SLiMs in proteins from reported binding groups to the SH2 selectivity values of SLiMs in proteins from groups that are not reported to bind. We found that less than 40% of non-binding SLiMs have a selectivity value > 5, whereas over 80% of binding SLiMs have a selectivity value greater than 5. Higher selectivity values correspond to a higher specificity of interaction Figure . These rR) scores, compared to Tyr-SLiMs in PLC-γ1 binding proteins  score was observed for SH2-recognized (SH2 selectivity ≥5.0) Tyr-SLiMs in cell cycle control proteins  have significantly higher ln(CR) score than those not recognized by SH2 domains ; 11 of these are statistically significant (p < 0.05). In the receptor kinase and phosphatase group, 8 cases showed a significant increase in ln(CR) score. However, no significant increase in ln(CR) score was observed in the cell cycle control protein group  have a higher average ln in representative protein functional classes taken from the Hprd database Figure . Those fFor SH3-recognized SLiMs Figure .Consistent with biochemical evidences that PDZ domains frequently interact with membrane proteins, we found that PDZ domain-recognized SLiMs Figure . Our resAs shown in Figure Remarkably, most functional classes of proteins with a significant conservation signal were highly specific for the signal within one group of domains, but not in other groups. For example, receptor kinase/phosphatase group show conservation signal only in SH2 domain group and transcription factors only in Ser/Thr kinase domain group Figure  NevertheR) score between SLiMs with high selectivity and those with low selectivity. We also compared functional classes that are frequent, occasional or rare interaction partners for each domain by setting thresholds for the percentage of proteins in the functional class that either interact with or become phosphorylated by proteins containing that domain  score between SLiMs with upper-medium to medium selectivity values and SLiMs with low selectivity values showed similar trends, but were less significant . In the above experiments, SLiMs for SH2 domains, PDZ domains or S/T Kinases with selectivity values of < 5, 5–10, 10–15, and > 15 were assigned to the categories of low, medium, upper medium and high selectivity, respectively; SLiMs with SH3 selectivity values of < 3, 3–6, 6–9, and > 9 were assigned to the categories of low, medium, upper medium and high selectivity, respectively.In order to further examine the specificity of the conservation signal, we calculated the conservation profile of SLiMs in each protein functional class by calculating the difference in ln and adaptor molecules have both SH2 and SH3 domains, and it has been suggested that proteins containing multiple SH3 binding sites are more likely to be tyrosine phosphorylated and bind to SH2 domains as supported by biochemical studies ,11. ConsWe further divided signal transduction groups into subgroups according to sub-cellular localization. Under selections for both the kinase motif and SH3 binding motifs, a high level of SLiM conservation was most manifest in signal transduction proteins localized to the cytoplasm or plasma membrane, but conversation of SLiMs was weaker for those proteins localized to the nucleus Figure . This isThese findings support the hypothesis that tyrosine kinases and SH3 domains are frequently coupled to SH2 domain signaling. The coupling between a tyrosine kinase and SH2 domains is expected, since an SH2 domain can only bind to a Tyr-SLiM after the tyrosine residue has been phosphorylated by a Tyr-kinase. However, the coupling between SH2 and SH3 domains might be less direct. Either a sequential model or a cooperative model, depending on whether the target tyrosine residue is phosphorylated before the interaction, may be used to explain the coupling between SH2 and SH3 domains Figure . In the Protein-protein interactions mediated by SLiMs have a widespread influence on cellular functions,13. In tHelicobacter pylori can be phosphorylated by Src and associates with Shp2 , then CR of the SLiM among different species is calculated as:If CR score greater than 1 indicates the SLiM is CR times more conserved than the average level of the protein. A score smaller than 1 indicates 1/CR times greater variability between species. Note that the number k may be different for different SLiMs according to the pair-wise Blast results.A CThis method may not be suitable for SLiMs longer than 10 amino acids, since it assumes that most residues in the SLiM could influence the interaction. This may not be the case in longer sequences where only a small subset of the residues is critical to binding. This method was first developed in our lab and has demonstrated its effectiveness in another research where SLFor a putative SLiM, the selectivity value for domains were calculated as the product of enrichment values from peptide library experiments ,44. For Please see Additional File The authors declare that they have no competing interests.SR was involved in design and planning of the experiments, has done the computational analysis and drafted the manuscript. GY, YH and YW were involved in carrying out experiments and computational analysis. YL was involved in planning of the experiments. ZC was involved in design and planning of the experiments, drafted the manuscript and headed the project. All authors have read and approved the final manuscript.Additional methods and results. This additional file presents additional methods and results related to this article.Click here for file