DNAJB1, which encodes the J domain, with exons 2–10 of the catalytic subunit of protein kinase A, PRKACA. This produces an enzymatically active chimeric protein J-PKAcα. We used molecular dynamics simulations and NMR to analyze the conformational landscape of native and chimeric kinase, and found an ensemble of conformations. These ranged from having the J-domain tucked under the large lobe of the kinase, similar to what was reported in the crystal structure, to others where the J-domain was dislodged from the core of the kinase and swinging free in solution. These simulated dislodged states were experimentally captured by NMR. Modeling of the different conformations revealed no obvious steric interactions of the J-domain with the rest of the RIIβ holoenzyme.In fibrolamellar hepatocellular carcinoma a single genetic deletion results in the fusion of the first exon of the heat shock protein 40,  It does not respond well to chemotherapy, and surgical resection is the primary means of treatment3. In FLC tumors there is a single, consistent genetic deletion in one copy of chromosome 195. This results in the formation of a chimeric gene, DNAJB1-PRKACA, which combines the first exon of DNAJB1, the heat-shock protein 40 with exons 2 through 10 of PRKACA, a catalytic subunit of protein kinase A4. There are 3500 statistically significant changes in the transcriptome and proteome when comparing the FLC to the adjacent normal tissue6. However, this chimera is the only detected structural alteration of the genome5. Expression of the chimera in mouse liver either by recreating the deletion by CRISPR/Cas9, or expression, in trans, by a transposon is sufficient to produce FLC7. Thus, it is considered to be the driver for the disease. The chimeric protein encoded by DNAJB1-PRKACA comprises of the J-domain of DnaJB1 , fused to the carboxyl-terminal 336 residues of the PKAcα, the protein encoded by PRKACA4. The chimeric protein, J-PKAcα, is enzymatically active.Fibrolamellar Hepatocellular Carcinoma (FLC) is a rare liver cancer usually detected in adolescents and young adultsPRKACA (encoding PKAcα), PRKACB (PKAcβ), or PRKACG (PKAcγ) and a regulatory (R) subunit dimer which comes as either RI (PRKAR1A (RIα), PRKAR1B (RIβ)) or RII (PRKAR2A (RIIα), PRKAR2B (RIIβ)) variants. In the holoenzyme, the R-subunits inhibit catalytic activity. A dimerization domain at the N-terminus of each R-subunit is joined by a flexible linker to two tandem cyclic nucleotide binding domains. An inhibitory peptide embedded within the linker of each R-subunit binds in the active site of the C-subunits. When the second messenger 3′,5′-cyclic adenosine monophosphate (cAMP) binds the R-subunits, the C-subunits are able to phosphorylate many downstream targets8 involved in a variety of cellular processes9. PKAcα is made up of a conserved catalytic core (residues 40–300) consisting of a β-strand rich small lobe and a primarily α-helical large lobe11. The substrate binding site is mostly in the large lobe while ATP binds in the cleft between the two lobes12. The catalytic core is flanked by a 50 amino acid C-terminal segment that wraps around both lobes of the core, while the small lobe is preceded by an N-terminal α-helix termed the A-helix. In the chimeric protein, the lower portion at the amino end of the A-helix is fused to the carboxyl end of the J-domain of DnaJB1  exists as a heterotetramer comprised of two catalytic (C) subunits, either 5-24) demonstrated that the architecture of the core is conserved compared to wild-type PKAcα17. The J-domain extends the A-helix and is tucked beneath the large lobe of PKAcα  simulations of both wild-type PKAcα and the J-PKAcα chimera in the ATP-bound, ADP-bound, and Apo states as well as bound to both nucleotide and substrate (ATP and the pseudosubstrate PKI5-24) to explore how the addition of the J-domain in the FLC chimera affects the kinase conformational dynamics. We find the J-domain of J-PKAcα samples a wide range of conformations in all substrate/nucleotide binding modes tested. Some conformations show similarity to the crystal structure with the J-domain tucked underneath the large lobe of the kinase, while others show extended conformations that deviated significantly from the crystal structure with the J-domain positioned away from the large lobe. These predictions were confirmed by NMR analysis of the chimeric protein. Structural modeling of different conformational states of the J-PKAcα chimera into a holoenzyme with two RIIβ subunits did not indicate any constraints on the movement of the J-domain.It is unresolved how the physiological properties of the chimera cause FLC. Transformation is not only the consequence of the increased transcription of the PRKACA with exon 1 of DNAJB1 on the conformational landscape of Protein Kinase A, we performed 1 μs MD simulations on wild-type PKAcα and the J-PKAcα chimera in the ATP-bound, ADP-bound, and Apo states as well as the tertiary ATP and PKI5-24 bound states starting from their respective crystal structure. Each simulation rapidly relaxed to a relatively stable state distinct from the starting structure. We quantified the time required for relaxation to this state by calculating the root-mean-squared-deviation (RMSD) of the backbone atoms and comparing it to the average structure over the last 50 ns of simulation time  and portions of the activation loop (residues 192 to 199). Large fluctuations were also seen in the loop connecting the A-helix to the small lobe (residues 32–37), Lys81 of the B-helix, the loop connecting helices H and I (residues 284 to 287), and residues in the C-terminal tail. Residues of the G-helix (residues 241–245) and Arg133, which are involved in substrate positioning, showed high RMSF values in all simulations except when bound to PKI. The decreased conformational flexibility of those two regions is likely the result of interactions that formed with PKI and stabilized those areas. In simulations of non-myristoylated PKAcα, the N-terminal residues (1–8) were highly dynamic  of each residue averaged over the final 800 ns of the simulation and is shown in Fig. The chimera showed similar fluctuations to PKAcα in the loop following the A-helix, the Gly-rich loop, the activation loop, the G-helix, and residues in the C-terminal tail Fig. . Additioν1) along the A-helix and the second vector (ν2) at the N-terminal end of the A-helix, which extends into the J-domain. The bending motion of the A-helix is described by the angle between these two vectors (θ1). The third vector (ν3) points from the end of the extended A-helix towards the end of the J-domain. The up/down motion on the J-domain relative to the core of the enzyme is described by the angle between ν2 and ν3 (θ2). Finally, we define a dihedral angle (θ3) given by the positions of the Cα atoms of residues Lys29 – Leu160 – Glu140 – Lys−19 that describes the shearing motion between the J-domain and the large lobe.To characterize the motions of the J-domain we defined three vectors Fig. . We chos1, is 161° in the crystal structure17, and samples values as low as 77° in the simulation . Likewise, for movement of the amino-terminus (θ2) the ATP-PKI bound chimera showed the greatest range of motion sampling angles from 62° to 121° . Both movements may be related to the shearing motion (θ3) of the J-domain, which also shows the greatest range of motion in the ATP-PKI bound simulation. During the initial 200 ns of the simulation  that is most pronounced in the ATP-PKI bound form. The bending of this helix, given by θion Fig. . The kin21° Fig. . The lar1 and θ3 . The third ATP-bound chimera simulation (CH ATP T3) did not show as great a range of conformational space, but did sample larger values of θ2 indicating a downward shift of the J-domain relative to the crystal structure.The simulations are consistent with the substrate/nucleotide binding state having an influence on the range of motions of the J-domain Fig. . However3 values ranging from 24° to 180° , three conformations from CH ATP T2  and three conformations from CH ATP T3  and each were extended for 300 ns. The results showed a wide range of states that the J-domain could sample in the ATP-bound chimera, especially in the rotation of the J-domain indicated by θ1 compared to the crystal structure (119° vs 164°). This is also accompanied by a downward motion  and a rotation  of the J-domain. Cluster 3 shows the J-domain tucked underneath the large lobe, similar to the crystal structure, but there is also a kink near Arg10 similar to cluster 2. Finally, cluster 4 shows a rotation of the J-domain in the opposite direction from the rotation in cluster 2.To further probe the range of conformations that are accessible to the J-domain, and gain insight into the relative populations of the conformations, we performed a clustering analysis based on the RMSD distance of the backbone atoms in each chimera structure. All chimera simulations were combined for a total aggregate time of 10 μs. Using an RMSD cutoff of 5 Å, the chimera simulations separated into 21 clusters with the first four clusters Fig.  accountiWe examined the frequency of transitions between the different clusters. At each time point we determined if the initial conformation transitioned to a different state  tucked underneath the core of the kinase or when in a ‘J-out’ state (as in cluster 2) when the domain is positioned far away from the catalytic core ore Fig. . This wo22. To assign the J-domain, we recombinantly synthesized and purified a DnaJB1 peptide from residue 1 to 76. The chemical shift assignments of the DnaJB1 peptide were then compared to the corresponding resonances of the J-domain in the full-length J-PKAcα. Ambiguous or overlapped peaks were assigned using the TROSY-version23 of triple-resonance experiments24 with U-2H,15N,13C labeled J-PKAcα. The direct correspondence between the resonances of the isolated constructs and the full-length J-PKAcα indicates that this domain folds independently25. To assess the global motions of J-PKAcα, we measured both the 15N longitudinal (T1) and transverse (T2) relaxation times26 . From the analysis of the relaxation times of the core of the enzyme , the ternary form of the J-PKAcα chimera reorients faster (22.9 ns) than the ternary form of wild-type PKAcα (24.0 ns). Given that the mass of the J-PKAcα chimera is larger than that of the wild-type PKAcα, one might expect the chimera to have a slower rotational correlation time in NMR. In fact, a theoretical calculation using HYDRONMR27 estimates a correlation time of 29.4 ns for the wild-type enzyme (PDB: 1ATP); while it predicts 37.4 ns for the J-PKAcα chimera (PDB: 4WB7). Since HYDRONMR assumes a rigid body reorientation of the molecule, the experimental observation of a faster rotational correlation time for the J-PKAcα chimera is consistent with the J-domain having a high degree of flexibility, in agreement with the MD results. Importantly, the plots of the T1/T2 versus residues reveal two distinct regions for J-PKAcα  which undergoes faster global reorientation.The MD simulation results indicate that the J-domain of the chimeric kinase is freely mobile. To test experimentally the conformational dynamics of the J-domain, we used NMR nuclear spin relaxation measurements. The resonance assignments for the catalytic core of the J-PKAcα fingerprint were transferred from the previous chemical shift assignments of the wild-type PKAcα amide resonances6. There are a number of possible explanations for how expression of this chimera could lead to transformation. One possibility is that the DNAJB1 promoter, which drives the chimera, may be expressing more of the C-subunit, and this is sufficient for transformation. A second possibility is that the loss of the amino-terminal myristoylation motif, affects the catalytic rate or localization of PKAcα. A third possibility is that the presence of the J-domain at the amino terminus alters the subcellular localization or binding partners of the C-subunit and/or the PKA holoenzymes. A fourth possibility is that the addition of the J-domain at the amino terminus affects the dynamics and thereby potentially the specificity of the kinase for nucleotide or substrate. A final possibility is the J-domain alters the finely tuned regulation of the PKA holoenzyme. We favor the hypothesis that the addition of the J-domain in some way alters the kinase dynamics, activity, regulation, or localization since the cancer has never been reported with just loss of the amino terminus, just loss of myristoylation on the second glycine, nor with the addition of any other amino terminus. Here, we have focused attention on the dynamic effects of adding the J-domain to the amino-terminal end of PKAcα, the C-subunit of protein kinase A.There is compelling evidence that the J-PKAcα chimera is the main driver for the development of FLC21, and the presence of the J-domain does not prevent formation of the holoenzymes. Thus, rather than affecting the interactions with the regulatory subunits, it is possible that addition of the J-domain alters the conformational landscape of the chimera and the resulting holoenzymes. The higher B-factors in the J-domain17 implied a large degree of conformational flexibility. Both simulations and experiment have shown that point mutations in PKAcα far from the active site can affect kinase activity allosterically though decoupling of dynamics29, implying that motions of the J-domain could influence the allosteric network in J-PKAcα and thereby alter its activity. In this work, we performed several microseconds of MD simulations exploring the conformational states adopted by the kinase and J-domains. We found that a primary conformation, accounting for 62% of all structures sampled by chimera MD trajectories, resembled the crystal structure where the J-domain was tucked underneath the large lobe of the kinase. Nonetheless, we also found an ensemble of chimera conformations in which the J-domain was dislodged from the core of the enzyme allowing it to swing freely in solution. These states were not captured by the X-ray crystal structure, but were confirmed using NMR. The flexible conformations appear to be independent of the nucleotide/substrate binding mode as they were observed in ATP, ADP, Apo, and ATP-PKI bound states. Focusing on the ATP-bound state, we showed that 1 μs of simulation time was not sufficient to obtained a converged ensemble of J-domain configurations as different 1 μs simulations showed a wide variability in the J-domain motions  which convert PKI5-24 from inhibitor to substrate. The crystal structure of PKAcα also includes the myristoylation at the N-terminus as well as the mutation K7C. In all wild-type PKAcα simulations the cysteine at position 7 was mutated back to a lysine using the Schrodinger Maestro software suite (Maestro 10 (2016) Schrödinger, Inc., Portland, OR). AMP-PNP was either mutated to ATP or ADP or removed for the Apo state. 2 Mg2+ ions were retained for the ATP simulations, 1 for the ADP simulations, and removed for the Apo simulations. SP20 was mutated back to PKI5-24 in simulations of the tertiary state. The chimeric J-PKAcα systems were built using chain A of the crystal structure, PBD ID: 4WB717 in which the protein is bound to ATP, several Zn2+ ions, and PKI5-24. As with the wild-type PKAcα simulations, J-PKAcα chimera was simulated in the ATP, ADP, and Apo states as well as the tertiary state with ATP and PKI5-24 bound. Zn2+ ions associated with nucleotide were converted to Mg2+ ions, with other Zn2+ ions removed. All structures were phosphorylated at S139, T197 and S338 . Structures were processed using the Protein Preparation Wizard in Maestro (Maestro 10 (2016) Schrödinger, Inc., Portland, OR), solvated in a rectangular box with SPC waters, and sodium or chloride ions were added for electrostatic neutrality. Simulations were performed using the Desmond MD Package30 using the OPLS3 force field31. Each system was subject to energy minimization using the steepest decent method. An initial 100 ps Brownian Dynamics simulation at constant volume and a temperature of 10 K with heavy atoms constrained was performed. Subsequent equilibration included a 12 ps simulation at constant volume and at 10 K with heavy atoms restrained, followed by a 12 ps simulation at constant pressure with heavy atoms restrained, and finally a heating simulation in which the restraints were gradually relaxed and the system heated to 300 K over 24 ps. Production simulations were performed for 1 μs or 300 ns with system snapshots saved every 50 ps.MD simulations were performed to observe the structural dynamics of J-PKAcα chimera and determine how they differ from wild-type PKAcα. Each protein (wild-type and chimera) was simulated in the ATP-bound, ADP-bound, and Apo forms as well as the tertiary state bound to both ATP and pseudosubstrate PKI32. Representative structures were taken as the structure with the smallest average RMSD distance to every other member of the cluster.All simulations were aggregated to generate distinct clusters of conformational states. Helices E (Residues 140–160) and F (Residues 217–233) where used to align all trajectories to the initial crystal structure. Analysis was performed on the protein backbone atoms first using the GROMACS analysis tool ‘gmx rms’ to compute the root-mean-square-deviation between all structures in the trajectory. The GROMACS utility ‘gmx cluster’ was then used to cluster the structures using a cutoff of 5 Å and the gromos clustering methodology2H,15N-labeled J-PKAcα was expressed using the E. coli BL-21(DE3) bacterial strain in M9 medium containing 15NH4Cl as the sole nitrogen source and transferred to an 80% 2H containing M9 media. His-tagged J-PKAcα was purified using TALON Metal Affinity Resin (Clontech). The His-tag was removed using a modified TEV protease protocol33  vector. An affinity His-tag was engineered after the sequence separated by a thrombin cleavage site. E. coli strain BL-21 was used as a bacterial host for the overexpression. The purified fusion protein was cleaved using thrombin protease, diluting 500 units of enzyme in 0.5 ml into cold PBS buffer . The cleavage reaction was monitored by SDS-PAGE. Upon completion the thrombin was inactivated by adding of 1 mM PMSF. The NMR samples of ternary complexes were prepared using 2H,15N labeled J-PKAcα and wild-type PKAcα in a 2:1 ratio with PKI5-24 and in the presence of 12 mM of ATPγN. The proteins were solubilized in 250 μl of 95% H2O and 5% D2O buffer solution, containing 20 mM potassium phosphate, 180 mM KCl, 10 mM MgCl2 (pH = 6.5). The final sample concentrations were 180 μM and 250 μM for the chimera and the wild-type kinase complexes, respectively. Uniformly 2H,15N,13C labeled DnaJB1 was prepared in 250 μl of 95% H2O and 5% D2O in 20 mM potassium phosphate buffer with 180 mM KCl and 10 mM MgCl2 (pH 7.0) to a final concentration of 200 μM.High-level expression of J-PKAcα in E. coli was achieved by the construction of pET28a(+) vector that contained the protein gene subcloned prior to a phage T7 RNA polymerase promoter. A TEV protease cleavage sequence was engineered between the Histidine (His) tag sequence and target gene. Uniformly 35 and HNCACB36 experiments. Longitudinal (T1) and transverse (T2) relaxation times were evaluated by monitoring the signal intensity decay of the amide resonances in the series of 2D spectra using the pulse sequences described by Zhu et al.37. The spectra were recorded in an interleaved manner for both T1 and T2. The spectral dimensions were 3466 Hz (F1) and 14423 Hz (F2). For both T1 and T2, the relaxation decay was sampled for 8 different delays. For each T1 value, the order of the relaxation delay was randomized  with 32 scans per FID. For T2, the relaxation delays were 8.1, 16.2, 24.3, 32.4, 40.5, 48.6, 56.7, and 64.8 ms with 96 scans per FID. Least-squares fitting of the decay curves was carried out with the downhill simplex algorithm implemented into SPARKY (Goddard and Kneller). Backbone assignments of J-PKAcα was achieved by overlay the resonances of the previously assigned wild-type PKAcα and transferring the resonance assignments of DnaJB1. All NMR data were processed using the NMRPipe suite of programs38.NMR experiments were carried out on 850 and 900 MHz Bruker spectrometers equipped with a cryogenic probe. The temperature was held constant at 300 K. Resonance assignments of the amide fingerprint of J-PKAcα was carried out by transferring the previous assignments from wild-type PKAcα. The DnaJB1 amide fingerprint and side chains were assigned using a combination of 3D CBCACONHSupplementary Information


Aedes albopictus enhanced due to the epistatic mutational changes in its envelope protein. In our study, we evaluated the prevalence of intrinsically disordered proteins (IDPs) and IDP regions (IDPRs) in CHIKV proteome. IDPs/IDPRs are known as members of a ‘Dark Proteome’ that defined as a set of polypeptide segments or whole protein without unique three-dimensional structure within the cellular milieu but with significant biological functions, such as cell cycle regulation, control of signaling pathways, and maintenance of viral proteomes. However, the intrinsically disordered aspects of CHIKV proteome and roles of IDPs/IDPRs in the pathogenic mechanism of this important virus have not been evaluated as of yet. There are no existing reports on the analysis of intrinsic disorder status of CHIKV. To fulfil this goal, we have analyzed the abundance and functionality of IDPs/IDPRs in CHIKV proteins, involved in the replication and maturation. It is likely that these IDPs/IDPRs can serve as novel targets for disorder based drug design.Chikungunya virus (CHIKV) is a mosquito-borne alphavirus. The outbreak of CHIKV infection has been seen in many tropical and subtropical regions of the biosphere. Current reports evidenced that after outbreaks in 2005–06, the fitness of this virus propagating in  Aedes aegypti and Aedes albopictus)1 and is disseminated at a higher rate in tropical regions. A Makonde word ‘Chikungunya’, which means: ‘The one which bends up’2, is taken from the Bantu language. The first epidemic of this disease was recognized in Tanzania in 1952. Since then, it had been considered as a tropical neglected disease3, despite the fact that in past 50 years, innumerable cases of re-emergence of CHIKV have been documented in the African and Asian continents4. However, after its recent outbreaks and the disease severity, it is listed now as a category C priority pathogen in US National Institute of Allergy and Infectious Diseases (NIAID)5. The main manifestations are flu-like symptoms, such as fever, headache, joint pain, and difficulties in movement2. The CHIKV infection has a rapid onset and it gets cleared in 5–7 days6. The fitness of this virus propagating in Aedes albopictus is enhanced due to the epistatic mutational changes in its envelope protein8. Dong et al., also explained the infection pattern of CHIKV in midguts and salivary glands of two different strains of Aedes aegypti, Higgs white eyes (HWE) and Orlando, Florida (ORL)9. Mutational pressure is generally high in the viral genome, and similar patterns are observed in CHIKV and Zika virus10.Chikungunya fever is triggered by an arthropod-borne virus (arbovirus) known as Chikungunya virus (CHIKV) that is transmitted by mosquitoes (11 organises as 5′UTR-nsP1-nsP2-nsP3-nsP4-J-C-E3-E2-6K-E1-polyA-3′UTR12. It has two open reading frames (ORFs) placed between the 5′and 3′ UTRs. First ORF  encodes four non-structural proteins, nsP1 , nsP2 , nsP3 , and nsP4 13 14.CHIKV is a small spherical (diameter of about 60–70 nm) shaped virus having a single-stranded positive-sense RNA genome 15. Most of the dark proteome are IDPs of hybrid proteins containing ordered domains and IDPRs16, which show specific functions without being folded into unique 3D structure under physiological conditions17. It is known, hydrophobic interaction plays a driving force in protein folding18. Since IDPs/IDPRs are more hydrophilic than ordered proteins19, this could be one of the reasons for their disorderness20. These proteins exist as highly dynamic conformational ensembles and can attain highly diverse conformations, such as random coils, molten globules, pre-molten globules, flexible linkers, and much more25. A globular structure attained by the ordered proteins that typically prevent the formation of aggregate or misfolding because of the frustrations in amino acid sequence compositions26. IDPs/IDPRs are promiscuous binders that can be involved in numerous interactions with many partners, thereby acting as an important hub in protein-protein interaction networks to regulate multiple signaling pathways at a time29. Many IDPs/IDPRs show disorder to order transition after binding to their partners32. For example, transactivation domain of c-Myb is intrinsically disordered in its unbound form, but after interaction with KIX, this domain gains an α-helical conformation33. Some IDPs/IDPRs facilitating the interaction with partners are known as molecular recognition features (MoRFs). Most of the viral disordered proteins show MoRF regions. For example, structural and non-structural proteins of Zika virus has MoRF regions that regulate the functionality of this virus34.The prime focus of our article is to analyse the dark proteome of CHIKV. The dark proteome defined as proteins not amenable to structure determination by conventional methods, such as x-ray crystallography and electron microscopy35. Despite this fly-casting mechanism, it was proposed that some disordered systems such as transactivation domain of c-Myb region, cannot speed up the recognition events between an IDP and its partner36. In recent studies, it is evidenced IDPs/IDPRs play a vital role in the establishment of several macromolecular complexes37 and also serve as assembly hubs38. Furthermore, it is recognized now that disordered regions represent new and attractive targets for drug design42. For example, IDPRs in c-Myc are the new targets for the development of drugs to cure cancer44. In our work, we have analyzed the dark proteome of CHIKV and evaluated disordered regions of viral proteins in terms of their functional significance.Being disordered, these proteins increase the probability of binding to their partners by providing greater capture radii; i.e., utilizing a binding mode known as a fly-casting mechanism45. One should keep in mind though, that the crystallization process typically requires various additives, such as PEG, high salt concentration, and many more, that might affect protein structure. IDPs/IDPRs are highly flexible and therefore characterized by the lack of specific electron densities. Since crystal structure of most of the CHIKV proteins are not reported at Protein Data Bank (PDB), we used limited crystallographic structural information that is currently available for a macro domain of nsP3 (PDB ID: 3GPG)46, nsP2 protease domain (PDB ID: 3TRK), and an envelope glycoprotein complex 47. In light of the limited structural information, the use of computational analysis to observe disordered regions of the query protein may deliver great advantages23.X-ray crystallography represents a unique technique for the determination of the 3D structure of proteins. It is based on the analysis of the scattering patterns of X-rays, which reads electron density maps to understand protein 3D structure48. There are three cleavage sites lie between the residue 535–536, 1333–1334, and 1863–1864 in the P1234  based on the outputs of four predictors in nsP1 protein  and guanylyltransferase (GTase) domains that have the role in 5′ capping, attachment of replication complex to the cytosolic membrane, induction of tapered pseudopodium-like structure, and in the synthesis of subgenomic RNAein Fig.  is 15.14ein Fig. , which d53. In the viral replication, nsP2 display three key roles as helicase, triphosphatase, and protease54. nsP2 has two domains, N-terminal and C-terminal. The N-terminal domain shows NTPase-dependent helicase activity having helicase sequence motifs, such as motif 1 (residues 715–733), motif 1A (residues 738–752), motif 2 (residues 782–791), motif 3 (residues 811–818), motif 4 (residues 839–848), motif 5 (residues 908–929), and motif 6 (residues 940–954)54. The N-terminal domain is also associated with the NTPase-dependent RTPase activity to remove phosphate from the 59th terminus of nascent RNA that acts as a substrate for capping reaction54. It also has nucleolar localization signal (NoLS region) and nuclear localization signal (NLS motif), positioned at residues 1005–1024 and 1182–1186, respectively55.nsP2 protein. This is the largest CHIKV protein that plays an important role in the pathogenic mechanism and in the life cycle of the virus56. It consists of two structural domains, such as a protease domain (residues 471–605) and a methyltransferase-like domain (residues 606–791). These two domains function as a single unit and are crucial for protease activity57. The functional mechanism of protease domain is related to deprotonation of a thiol group of cysteine residue from catalytic dyad at the active site (Cys1013 and His1083)59. The crystal structure of nsP2 protease domain of CHIKV have resolved (PDB ID: 3TRK)  is a papain-like protease domain, known as cysteine protease (thiol protease). However, a recent report revealed that in CHIKV, a cysteine residue can be catalytically replaced by serine. Hence, this study suggests that protease domain of CHIKV is not a papain-like proteaseRK) Fig. . AlthougRK) Fig. . HoweverRK) Fig. .2+ binding domain, and the C-terminal variable tail domain. The crystal structure of macro domain (160 residues) has been resolved (PDB ID: 3GPG)46, where residues 30–37 represent a loop region and residues Thr111, Gly112, and Val113 form a binding site. The macro domain can interact with both mono and poly ADP-ribose and with RNA as well60. It has the ability to hydrolyze small substrate analog ADP-ribose-1-phosphate. A small Zn2+ binding domain follows macrodomain and contains four conserved cysteines  where Cys263 and Cys265 are situated in the loop between the last two α-helices, crucial for replication61. Both macro domain and Zn2+ binding domain play a key role as regulators for the processing of non-structural polyprotein61. The third proline-rich C-tail domain is 205 residues long. It provides an insertion site for marker proteins. During the infection, components of stress granules G3BP1 and G3BP2 (host cells) directly bind to nsP3 protein to arrest RNA translation, and the interaction of G3BPs with nsP3 inhibits the stress granules formation62. Two short conserved repeat sequences near the C-terminal region of nsP3 interact with G3BPs. This interaction results in the depletion of G3BPs which leads to a reduction in CHIKV replication63. In disorder analysis, we found that the PPID value of this protein is 38.49%  tail in template-independent manner65. A recent report revealed that nsP4 is required for RNA synthesis assisted by other non-structural protein and possibly play a role in proper folding65. The N-terminal region (100 residues long) of nsP4 forms a partly unstructured domain, is necessary for the proper functioning of nsP4. This partly unstructured domain is followed by the catalytic domain with the established polymerase fold. A catalytic triad of GDD polymerase motif  is also important for polymerase activity66. The disorder analysis of this whole protein  enzyme in CHIKV. It inhibits the phosphorylation at Serein Fig.  gives thein Fig. , but theein Fig. . Therefo67. The highly disordered N-terminal domain enriched with positively charged amino acid residues  with high proline content. It has ribosome binding region (91–100 amino acid residues) that involved in protein-protein interaction. This domain also binds to the genomic RNA via 18 amino acid long coiled-coil α-helix68 and is required for the dimerization of capsid protein that negatively regulates host transcription67. This N-terminal domain is also involved in the interaction with RNA bound capsid proteins to form nucleocapsid core assembly in the cytoplasm of infected cells67. The nucleocapsids are then secreted out to the plasma membrane to interact with the C-terminal region of E2 for the initiation of virion budding. Residues 81–105 at the N- terminal domain of CP interact with RNA to form Capsid-RNA complex69. The C-terminal domain possesses a serine protease activity and is characterized by a chymotrypsin-like fold. This domain autoproteolytically cleaves CP from the nascent structural polyprotein. The report suggests that the C-terminal domain has numerous conserved amino acids, including a catalytic triad His139, Asp161, and Ser213, involved in the autoproteolytic activity that occurs at Trp261. Close to the substrate binding site of protease, a hydrophobic pocket is present, where binding of capsid to endodomain of the E2 glycoprotein occurs70. The predicted disordered analysis at the cleavage junction for CP is shown in Fig. Capsid protein. Capsid protein (CP) of alphavirus has an N-terminal RNA binding domain (residues 1–113) and the C-terminal protease domain (residues 114–261). The N-terminal domain constitutes two nuclear localization signal (NLS), residues 60–77 and 84–99. Although capsid protein is a cytoplasmic protein, it is assumed that its NLS may be involved in translocation of CP to the host nucleus71. The envelope polyprotein encoded by CHIKV has four proteins arranged as E3-E2-6K-E1. Crystal structure of immature glycoprotein complex has been resolved (PDB ID: 3N40)  protein. p62 precursor protein is a premature complex of E3-E2 protein. Processing and maturation of the glycosylated pE2 and E1 proteins takes place at the ER of infected host cells, where the polysaccharide chains are embedded on the surface of the envelope proteins to regulate cell receptor recognition, cell attachment, and entry into host membrane after viral fusion40) Fig. . It formlex Fig. .47. E3 protein helps in the structural stability of E2 glycoprotein through modification of A and B domains in such a way that it can create a groove to accommodate fusion loop47. Another important function of E3 is to protect and stabilize the immature trimer (p62-E1) complex from acidic environment73. It also helps in low pH-mediated endocytosis of spikes (three E2-E1 heterodimers). Numerous polar residues are present at the N-terminal region , required for the translocation and processing of p62 into ER lumen74. This signal plays a major role in trimer formation among E3-E2-E175. The disorder analysis of E3 protein 47. The E1 protein is N-glycosylated at position N14173. It consists of three domains I, II, and III. The Domain II has a fusion loop (residues 893–910) at its tip, essential for the association of E1 and E2 glycoproteins. This fusion loop forms two H-bonds, first, between Ala92 of E1 and His226 of E2 (Domain B) and second, between Phe87 of E1 and His29 of (Domain A)47. The structure of CHIKV envelope is made up of spikes (three E2-E1 heterodimers). Eighty such spikes are present in a CHIKV virion, and those spikes mediate membrane fusion to deliver the viral genome into the host cell. The viral fusion is triggered by low pH (~5.5 to 6.0) dependent secretory pathway of endocytosis73. This is the reason why E1 fusion protein is expressed with E2 protein. However, disorder analysis of E1 protein  (at 234th residue) has been identified in E2 protein that triggers the initiation of conformational changes in the E1-E2 complex47. The disorder analysis of E2 protein ein Fig.  shows thein Fig.  only. Th57. The disorder analysis of this protein  and V264A (E2) polymorphism7.CHIKV proteins play important role in the regulation of viral life cycle, pathogenic mechanisms, and immune evasionAedes agepty & Aedes albopictus7. Fusion loop is disordered in nature that helps in dimer (E1 and E2 protein) formation. A recent study evidenced the mutational changes happen in the E1 and E2 proteins that are identified as K211E and A226V (E1) and V264A (E2) polymorphism7. These mutational changes are confined to the loop region of envelope protein, which is disordered in nature. They enhance the fitness of CHIKV residing in Indian Aedes agepty & Aedes albopictus. These mutations direct the conformational changes in the E1 protein. The current study suggests that IDPRs play a vital role in the structural flexibility and functional diversity of the CHIKV proteome and play diverse biological roles, such as cell cycle regulation, signaling, and protein stability of viral proteome. Therefore, we concluded that the disordered side of CHIKV proteome may provide a new angle to consider the pathogenic characteristic and virus-host interaction mechanism. In our study, we found that the N-terminal domain of capsid protein is completely disordered. This domain is required for the nucleocapsid assembly. Furthermore, the C-terminal domains of nsP3, E2 and E3 proteins have functional disordered regions. Since the role of IDPRs is well characterized in the regulation of life cycle of viruses, research has moved towards the development of the disorder based drug discovery strategies. The abundant disordered regions in CHIKV proteome could be an attractive target for drug designing. Since there is no vaccine/drug against chikungunya virus, a detailed analysis of CHIKV proteome is necessary to develop new drug by targeting the disordered regions.It has been found that mutational changes occur in the disordered loop regions of E1 and E2 protein. These mutational changes trigger the conformational change in E1 protein to enhance the fitness of CHIKV propagating in Indian ® pool , as well as IUPred79, DisoPred80, DisEMBL81, GlobPlot82, SPRITZ83, and much more84. To evaluate the precision of disorder predictors, several aforementioned tools were compared within the frames of the Critical Assessment of Protein Structure Prediction (CASP)85. It was also indicated that because different predictors consider the occurrence of the intrinsic disorder in proteins from diverse perspectives, it is sagacious to use several computational tools to catch on the profusion of intrinsic disordered17. Typically, disorder predictors consider residues and regions as intrinsically disordered if their disorder score is above the 0.5 thresholds. The peculiarities of all predictors were considered while calculating the mean of all predictors.For disorder analysis, we used a reviewed polyprotein sequence of the S27-African CHIKV prototype, because this strain is a most causative strain of Chikungunya disease [UniProt ID: Q8JUX6 and Q8JUX5]. Previously, for disorder analysis, several specialized predictors have been developed, for example, PONDR® VSL286 gives one of the more accurate evaluations of disordered regions in a query protein, whereas PONDR® VLXT is known as the most sensitive predictor for finding disordered based interaction sites87, and a meta-predictor PONDR-FIT as is more accurate than its individual component predictors, such as PONDR® VLS277, PONDR® VLXT78, IUPred, FoldIndex, TopIDP. In our study, we have used PONDR® FIT76, PONDR® VSL277, and PONDR® VLXT78 for disordered analysis in polyprotein of CHIKV. Several reports suggested that IDPs/IDPRs play a central role in various molecular recognition events and in protein-protein interaction networks92. Some IDPs/IDPRs can undergo at least partial disorder-to-order transitions, when they get involved in interactions with specific binding partners that are needed for recognition, signaling, control, and regulation95.PONDRSupplementary Information


Preparedness planning for a veterinary crisis is important to be fast and effective in the eradication of disease. For countries with a large export of animals and animal products, each extra day in an epidemic will cost millions of Euros due to the closure of export markets. This is important for the Danish husbandry industry, especially the swine industry, which had an export of €4.4 billion in 2012. The purposes of this project were to (1) develop an iterative tool with the aim of estimating the resources needed during an outbreak of foot-and-mouth disease (FMD) in Denmark, (2) identify areas, which can delay the control of the disease. The tool developed should easily be updated, when knowledge is gained from other veterinary crises or during an outbreak of FMD. The stochastic simulation model DTU-DADS was used to simulate spread of FMD in Denmark. For each task occurring during an epidemic of FMD, the time and personnel needed per herd was estimated by a working group with expertise in contingency and crisis management. By combining this information, an iterative model was created to calculate the needed personnel on a daily basis during the epidemic. The needed personnel was predicted to peak within the first week with a requirement of approximately 123 (65–175) veterinarians, 33 (23–64) technicians, and 36 (26–49) administrative staff on day 2, while the personnel needed in the Danish Emergency Management Agency  was predicted to be 174 (58–464), mostly recruits. The time needed for surveillance visits was predicted to be the most influential factor in the calculations. Based on results from a stochastic simulation model, it was possible to create an iterative model to estimate the requirements for personnel during an FMD outbreak in Denmark. The model can easily be adjusted, when new information on resources appears from management of other crisis or from new model runs. Following the directive, EU member states are obliged to use a stamping out policy, involving quarantine, movement restrictions, zoning, and slaughter and disposal of all affected herds, followed by cleaning and disinfection (CD) of the farm. Additional control measures can be used, for example, preemptive culling or vaccination, after approval of the plan by the European Commission regulatory committee Standing Committee on the Food Chain and Animal Health.Foot-and-mouth disease (FMD) is a highly contagious disease, which is known to spread easily within and between herds and cause severe economic losses in each herd as well as in the country . The conPreparedness planning for a veterinary crisis, such as an FMD outbreak, is important in order to be fast and effective in the eradication of the disease. For countries with a large export of animals and animal products, each extra day in an epidemic will cost millions of Euros due to the closure of export markets. This is of utmost importance for the Danish swine industry, which had a yearly export of €4.4 billion in 2012 (Modeling results have previously been used to inform decision-making related to disease control options –14. ModeGeering and Lubroth  describeThe purposes of this project were (1) to develop an iterative tool with the aim of estimating the resources needed during an outbreak of FMD in Denmark and (2) to identify areas, which can be bottle necks in the veterinary administration, and thereby delay the control of the disease and the time to regain disease free status and the access to export markets. The tool developed should easily be updated, when new knowledge is gain from other veterinary crises or during an outbreak of FMD.The DTU-DADS model (version 0.16) was used to simulate spread of FMD in Denmark , 20.From the official Danish central herd register, all Danish herds registered with cattle, swine, sheep, or goat in the period from October 1st 2006 to September 30th 2007 were extracted and used in the model. This period was used to avoid influence of the blue tongue outbreak in Denmark, which started in October 2007. For each herd, a unique identification number, the herd type, the numbers of animals of different types, and the UTM geo-coordinates was extracted. In total, 23,550 cattle herds, 11,473 swine herds, and 15,830 sheep or goat herds were included. Sheep and goat herds were grouped in one category, called sheep, as there are a limited number of goat herds in Denmark, and they are considered to be handled similar to sheep herds during an epidemic. Furthermore, herds were described as different types, cattle herds as milking or beef cattle, sheep herds as commercial or hobby herds, and swine herds as 19 different herd types, based on their SPF status and their production type (Spread of disease was modeled to occur through seven different spread mechanisms: (1) direct contact, i.e., animal movements, (2) indirect medium risk contacts, i.e., veterinarians, artificial inseminators, or milk controllers, (3) indirect low risk contacts, i.e., visitors, feed stuff/rendering trucks, (4) abattoir trucks, (5) milk tankers, (6) markets, and (7) local spread.Based on movement data from the period October 2006 to September 2007, the rate of movement per day for the individual herd was used as λ in a Poisson distribution simulating spread of disease. Similarly, the rate of abattoir deliveries was calculated for the individual herd and used as λ in a Poisson distribution simulating the risk of spread on the abattoir route. Contrary, the pick-up of milk from dairy herds was simulated as a Poisson distribution with λ = 0.6 for all dairy herds. Indirect medium and low risk contacts were simulated with different λ for different herd types , 19. MarDetection of the first infected herd was simulated to occur between day 18 and 23 after the disease was introduced, with a mode of 21 days. Thereafter, the disease could be detected either from the farmer or veterinarian (basic surveillance) or from surveillance by official veterinarians as result of tracing contacts from infected herds or as surveillance in the protection or surveillance zones. The probabilities of detection by each type of surveillance were assumed to be dependent on the herd type, as different species show more or less clinical signs .After detection of disease, a set of control measures must be applied based on the EU council directive 2003/85/EC. These include depopulation of all detected herds, CD of infected properties, tracing (back and forward) of contacts, and establishment of protection (3 km) and surveillance (10 km) zones around detected herds. In both zones, movements of animals are prohibited and all herds must be surveyed at least twice in the protection zone and once in the surveillance zone, before the zones can be lifted.In the model, herds were assumed to be depopulated as soon as capacity was available. A daily capacity for depopulation of 2,400 ruminants and 4,800 swine was estimated by the industry and the Veterinary and Food administration based on experiences with other diseases . AnimalsFurthermore, a 3-day national standstill for all animal movements was modeled, based on the Danish contingency plan for FMD.One thousand cattle herds were randomly chosen and used to initiate the spread of disease (index herds). Epidemics starting in cattle herds have previously been shown to create some of the largest outbreaks under the simulated circumstances , 19.For each index herd, one iteration was run, resulting in 1,000 epidemic simulations. The outcome of the model included, for every iteration and for every day in the epidemic, which herds were detected, which herds were depopulated, and which herds were surveyed. Of the 1,000 simulated epidemics, in 19 cases, the disease did not spread from the first infected herd and was not detected, resulting in 981 simulated epidemics in total.A working-group of 12 personsEstimates for resources during an outbreak were divided in resources for detected herds, suspected herds, surveyed herds, and local crisis centers Tables  and 2. Np,t,a is the estimated team for a given type of personnel, task, and species, and Kt,a is the number of animals (or herds) of a given species that a team can handle per day for the given task.Based on the daily outputs from the simulation model, personnel for valuation of herds for each day (i) in the epidemic was calculated as the total type of personnel (p) needed, i.e., the numbers of VETs, TECHs, ADMs, and staff from DEMA, for a given task (t), here valuation, and a given species (a) as:valuation is the number of VETs in the valuation team and Kvaluation is the number of herds a valuation team can handle in one day . The CDPs were assumed to be used in cattle and swine herds only, based on the limited herd sizes of Danish sheep and goat herds.The number of veterinarians needed for the cleaning and disinfection point (CDP) of the herd was calculated as:CI is the numbers of veterinarians in the team used for CI in the herd and KCI is the number of herds a CI team can handle in one day. Because of the limited size of Danish sheep herds, CI and blood sampling was assumed to be included in the culling of the animals in sheep herds.The numbers of veterinarians used for clinical inspection (CI) in detected cattle and swine was calculated as:CD is the numbers of veterinarians in the team used for initial CD of the herd and KCD is the number of herds a CD team can handle in 1 day.The numbers of veterinarians used for preliminary CD of detected herds was calculated as:FCD is the time period over which the FCD is taking place and KFCD is the number of herds a FCD team can handle in 1 day. This value is then included every day over the durationFCD.The following final cleaning and disinfection (FCD) of herds was assumed to be done by private commercial cleaning companies, but under guidance and acceptance by the official veterinarians. Therefore, for each species, a certain time was needed for the veterinarians, but spread over a 3 week period of time, as few hours are needed a day. This was calculated as:When an epidemic is running, there will be suspicion of disease, also in herds that are not infected. Suspicions (SI), which are following detected with FMD as result of investigation, will in the model be counted as detected herds. However, there will be suspicion of FMD in non-infected herds as well.As the simulation model only simulate spread of infection, we do not have information on non-infected SI from the model. Therefore, a conservative estimate based on data from the UK 2001 epidemic was used, i.e., five SI per detected herd was assumed for the numbers of inspections based on passive surveillance .SI is the number of veterinarians used in the team investigating a suspicion and KSI is the number of herds a suspicion inspection team can handle in 1 day.The SI were randomly distributed over a period of 10 days, starting the day after a herd was detected in the model. As it is not known in which herd type a suspicion will occur, we could not take herd type into account for SI. The number of veterinarians needed to inspect SI of FMD was calculated as:zoneSurv was the numbers of veterinarian needed for a surveillance visits. No difference was assumed between herd types for surveillance visits. From the output of the simulation model, the day of the surveillance visit was extracted and, therefore, eventual waiting time for a surveillance visit was already accounted for.The numbers of veterinarians needed for surveillance in traced herds and in herds in the protection or surveillance zones (zoneSurv) were calculated as:VET,management are veterinarians working in the management of the group, LCCVET,suspecison are veterinarians working suspicisons, LCCVET,EPI are veterinarians working with epidemiology of the epidemic, LCCVET,depop are veterinarians working with depopulation of detected herds, LCCVET,move are veterinarians working with movement restrictions in the zones, and LCCVET,comp are veterinarians working with educating new staff during the epidemic.During an epidemic, a LCC will be created according to the Danish veterinary contingency plan . The numSimilarly, the needed numbers of technicians, administrative staff, and personnel from DEMA were calculated for each day and each task in the epidemic, and summed over all tasks resulting in the daily needs for personnel. Furthermore, the needs for rendering capacity was calculated for ruminants and non-ruminants, and the needed equipment for culling and testing was calculated, however, not included in this paper. Details from these calculations can be obtained from the authors.The simulation model as well as the calculations of resources was run using the freeware R . All estThe influence of estimates on the required number of staff during an outbreak was investigated by decreasing or increasing the number of vets, technicians, and administrative staff as described in Table The simulated epidemics had a median size of 22 5–95%: 2–155) infected and detected herds (Figure 55 infectBased on the results from the simulation models, we estimated that the need for personnel in the regions would peak in the first couple of days with a median of 116 veterinarians, 22 technicians needed, while the need for administrative personnel would peak a little later with a need for a median of 45 administrative personnel 21 days in the epidemic Figures . FurtherFrom the sensitivity analyses Table , it was Based on results from a stochastic simulation model, it was possible to create a model in R to estimate the requirements for personnel during an FMD outbreak in Denmark. The model can easily be adjusted, when new information on resources appear from management of other crisis, or when new simulation results are available from new model runs in peacetime. Furthermore, it is possible to adjust the model during a crisis, when model results from daily runs of the stochastic simulation model gives more precise estimates on the specific epidemic, or when adjustments in management procedures becomes available.It was not surprising to find that especially the number of staff needed for surveillance visit influenced our results, as the numbers of herds in zones are so large. This was also in line with what was found by Garner et al. . This meA peak for veterinarians was predicted very early in the epidemic Figure . HoweverThe resources estimated here were based on simulated epidemics and were shown to follow the simulated epidemic peaks closely Figures , 2 and 5Our estimates were based on daily outputs from 981 simulated epidemics under a basic control strategy, e.g., the strategy expected to be used, if an outbreak would occur tomorrow. However, in very large epidemics, there is a probability that decision makers would not choose to stick to the basic control strategy, but would most likely add extra control measures such as preemptive culling or emergency vaccination, and therefore, the resources needed in the extreme epidemics would change.Surprisingly, it was shown that there was a very high need for recruits from the DEMA used in the CD of detected herds Figure , which mBefore the UK 2001 outbreak of FMD, the UK State Veterinary Service used two scenarios in their contingency planning, one moderate scenario with 10 simultaneous outbreaks and 1 severe outbreak, also with 10 simultaneous outbreaks, but with a large herd density. And they found a need for 235 veterinary officers, which they extrapolated to around 300 in more severe outbreaks. During the UK 2001 outbreak, 57 premises were infected before the first herd was diagnosed, leading to an almost immediate need for all state veterinary officers. Before the end of the outbreak, another 2,500 temporary veterinary inspectors were appointed, nearly 70 from abroad, and another 700 foreign government vets and secondees assisted in periods .Based on the experience in the UK, we could fear that we are underestimating the needs during an FMD crisis in Denmark. However, even though we were interested in estimating manpower and materials needed, we were also aware that we can end up with even larger epidemics. Therefore, it was important for us to create a model, which can easily be adjusted during a crisis in an iterative process. Each time new information become available, regarding the epidemic or the resources needed, it can be fed into the model, and new outputs can be calculated. For example, if the compositions of the veterinary teams for different tasks are changed, we will change the inputs in the model and rerun it. Or if we rerun the stochastic model with historic data from the first 10 days of the epidemic, we will have more precise estimates on the further development of the epidemic and that can be put into the resource model.The results of our estimations seem somewhat lower than what was estimated in Australia . Direct The calculation of resources needed is an iterative process. The simulation model includes assumptions regarding resources, to simulate realistic epidemics, as scarce resources will prolong the epidemics. After assuming the available resources, we then calculate the daily needs. Naturally, this seems like a circular argument. However, in the simulation model, resources are roughly set as numbers of animals or herds that can be processed daily for either depopulation or surveillance. In the resource calculation presented here, we go into details regarding the teams for each task, the time needed, and look at number of herds and numbers of animals to process. The influence of the assumptions regarding resources has previously been described for depopulation  and survOne of the assumptions was that all three veterinary regions would be involved from the beginning of the epidemic. While this was not truly realistic, the influence of this assumption was assumed to be limited, as many parameters even in the LCC depended on the numbers of herds and animals involved in the epidemic rather than the numbers of LCC. However, overall, we did estimate a clear decrease in the manpower needed for veterinarians as well as technicians and administrative staff. Therefore, an adjustment of the model taking region into account will be considered in future versions of the model.In the current estimations, the very basic needs during an epidemic were estimated. Traveling time between herds was taken into account in the estimates Table , while lAB, SM, and MJ in study design; AB and TH developed the model; and all the authors contributed to the results and discussion. AB wrote the manuscript, and all the authors commented and approved the final version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Myotilin is a component of the sarcomere where it plays an important role in organisation and maintenance of Z-disk integrity. This involves direct binding to F-actin and filamin C, a function mediated by its Ig domain pair. While the structures of these two individual domains are known, information about their relative orientation and flexibility remains limited. We set on to characterise the Ig domain pair of myotilin with emphasis on its molecular structure, dynamics and phylogeny. First, sequence conservation analysis of myotilin shed light on the molecular basis of myotilinopathies and revealed several motifs in Ig domains found also in I-band proteins. In particular, a highly conserved Glu344 mapping to Ig domain linker, was identified as a critical component of the inter-domain hinge mechanism. Next, SAXS and molecular dynamics revealed that Ig domain pair exists as a multi-conformation species with dynamic exchange between extended and compact orientations. Mutation of AKE motif to AAA further confirmed its impact on inter-domain flexibility. We hypothesise that the conformational plasticity of the Ig domain pair in its unbound form is part of the binding partner recognition mechanism. Movement is vital to all living organisms, from the transport of single molecules in cells to the movement of the entire organism. In vertebrates, skeletal muscle is essential for all voluntary movements such as walking, running, swimming or flying. Involuntary movements, such as those occurring in cardiac muscle resulting in contraction of the heart (beating), or those occurring in smooth muscle resulting in peristalsis are fundamental to the viability of the organism.2. The precise ultra-structural order of these filaments is of outmost importance for converting the molecular interactions produced by actin and myosin in each sarcomere into efficient contraction at the macroscopic level. Titin and nebulin  act as a general blueprint for sarcomere assembly and length, due to their outstanding size and modular architecture. Sarcomere is on both ends delimited with Z-discs, which act as passive transducers of the generated tension. This is also the spot of actin filament crosslinking, primarily by the α-actinin, however other signalling, stretch-sensing and actin-binding proteins are involved, for example myotilin, filamin C, ZASP/cypher/oracle, FATZ/myozenin/calsarcin and many others3.Muscles are composed of repetitive isotropic (I) and anisotropic (A) bands, giving them a striped appearance. Here, the smallest periodic unit, termed sarcomere, is composed of actin and myosin filaments which together with other accessory proteins form the sarcomeric cytoskeleton4. Both myopalladin and myotilin have restricted expression profile, with the highest expression in the skeletal and cardiac muscle5, in contrast to palladin, which shows much wider expression pattern both in skeletal and non-skeletal tissues, depending on the expressed isoform7. Myotilin is comprised of two C2-type Ig domains and a unique serine-rich N-terminal region4, while palladin and myopalladin host up to five Ig domains, where the two most C-terminal domains share high homology with the Ig domains of myotilin and two most N-terminal domains are mostly related to the N2B region of titin5  together with actin, α-actinin-2, filamin C, FATZ and ZASP21. Recent results reported that it is highly mobile not only in the Z-bodies but also in the Z-bands and possesses ability of dynamic exchange with the cytoplasmic pool of proteins, indicating important role in initial organisation and maintenance of Z-disc22.Myotilin is thought to play a role in anchoring and stabilising actin filaments at the Z-disc, and is involved in the organisation and maintenance of Z-disk integrity26  was constructed and showed similar results. The Bio-NJ tree calculated using maximum likelihood approach showed the expected evolutionary relationship between species with a good branch support for main branches indicating a reliable sequence alignment  is located at the N-terminus of both Ig domains and has already been found in Ig domains of other proteins from the I-band43. Interestingly, conserved proline residues, first identified at the border of fibronectin type III domains of tenascin, were shown to prevent non-specific self-association and aggregation of their cognate proteins44. We speculate that similar effects could be also present in myotilin. The NxxG motif (x = any residue) present at the β-hairpin turn connecting the F and G strands, is a central part of the N-terminal network of conserved residues. Similarly to the PPxf motif, it is found in the N-conserved type of I-band Ig domains33. Together with the PxP motif, located at the BC loop on both domains, these motifs form a conserved N-terminal network of residues , represent the most conserved part of the molecule Fig. , which iues Fig. . Overall341AKEHKR346) and corresponding repeats in myopalladin (1165AKEVKK1170) and palladin (1227AKEAHK1232) revealed that Ala, Lys and Glu residues are highly conserved within this region with an overall basic character. Interestingly, highly conserved Glu is also characteristic for I-band linker regions where it sometimes merges with PPxf to form the EPPxf motif. Mutational studies of this motif within the titin Ig65–70 domain repeats suggested that it is not a determinant of inter-domain orientation33, however latest studies of tandem titin Ig67–68 repeats indicate that it is important for titin global dynamics38. While myotilin lacks the combined EPPxf motif, the PPxf motif could nevertheless be involved in inter-domain dynamics. Even more, similar inter-domain dynamics are expected for domain pairs Ig1–2 (myotilin) and Ig4-Ig5  due to their high sequence similarity and linker length. Linker regions within other Ig domain pairs of myopalladin/palladin are longer  indicating a higher degree of flexibility.Next, inspection of alignment of the linker region within tandem Ig domain repeat of myotilin sequence  and the C-terminal part (residues 441–498) display lower conservation scores. While those two regions contain functionally important sites  at the highest concentration indicates some concentration effect, however this did not obstruct further analysis  was employed. SAXS data of MYOTIg1–2 construct encompassing the two Ig domains was measured using highly purified samples of myotilin Ig domains at different concentrations. Slightly increased radius of gyration (R0 = 15.34 ± 0.06 a.u. and Rg = 2.57 ± 0.10 nm. Pair-density distribution function P(r), displays a bell-shaped bimodal profile, typical for a multi-domain protein. The fit of P(r) to experimental data shows good match and smooth decay to P(r) = 0 and represents particle with maximum linear dimension Dmax = 9.37 nm  are in excellent agreement with the values determined by Guinier approximation. Other parameters derived from scattering data are given in Table max and Rg values of MYOTIg1–2 are between those of a fully extended Ig8–9 pair (Dmax = 10.10 nm) and semi-extended Ig6–7 pair of filamin C (Dmax = 8.60 nm)49, suggesting that the MYOTIg1–2 pair adopts a slightly more compact form than the fully extended Ig8–9.Guinier region analysis of the scattering curve showed linear fit  of filamin A31, both in its compact and slightly more extended/flexible migfilin peptide-bound form, myotilin Ig domain pair is significantly more flexible, similarly as Ig domain pairs Ig12–13 and Ig22–23 of filamin A51 A51 Fig. . Here, i2 and inter-domain clashes. For rigid body fitting, the ab initio three-dimensional low-resolution molecular envelope was reconstructed using DAMMIF. Next, the most probable averaged model was calculated with the DAMAVER set of programs, showing a »dumbbell« shape with dimensions of approximately 10 × 4.5 nm. Subsequently, rigid body modelling using CORAL was performed, showing relatively good chi value (χ2 = 2.957), however with a slight mismatch at the higher angles . Radius of gyration distribution plot shows three peaks with maxima ranging from 2.3 nm (compact), 2.7 nm (average extended), and 3.0 nm representing fully extended species  and MultiFoXS approaches were employed to fit the theoretical scattering intensities  to the experimental scattering data. EOM results indicate various inter-domain orientations which are represented by four models ranging from more compact to a more extended arrangement, fitting the experimental scattering with a low chi value (χ2 = 1.120) in comparison with the rigid body modelling  and employed MultiFoXS server to explore the multiple conformations by conformational sampling with rapidly exploring random trees (RRT) search. Here, the linker residues were assigned as flexible. This significantly improved the fitting to the experimental data for 4-state model, showing lowered chi value  value is indicative of high residue flexibility. For several other proteins, results of such simulations have already been proved to be in good agreement with NMR measurements and all-atom MD simulations aimed to determine flexible regionsble Fig. . FluctuaDetailed analysis of fluctuations in domain arrangement was analysed using two 10 ns all-atom MD simulations. Here, the Ig1–2 domain pair moved from an extended to a more compact arrangement, followed again by a transition to regain a locally more extended form. In case of simulation 1, we observed almost complete regain to extended orientation Fig. , whereas344EHKR347 represents a hinge, where the main chain bond rotation results in the domain torsion , in concert with other hinge residues, plays an important role in hinge mechanism of myotilin, where its main dihedral ψ angle changes by 54° as measured by the DynDom server. Moreover, formation of intra-domain interactions via hydrogen bonds was observed between Lys343 and Ile375 and between Pro376/Ala429 and Glu344 . Further analysis of the extended and compact conformations from the all-atom MD simulations revealed that the residue stretch ion Fig. . This hi344 Fig. . Remarkaant Fig. . DistribTherefore, our data clearly demonstrates a connection between conserved motifs and myotilin dynamics on a level of intra-domain contacts involving residues within the conserved motifs.53. Studies of the titin N-terminal Z1Z2, located within the Z-disc34, have revealed important implications of inter-domain dynamics in unbound state for interaction with binding partner telethonin35. Also, compact domain-domain interactions of filamins54, as well as inter-molecular interaction between Ig24 domains leading to dimerisation56, were found to be functionally important. For example, relative orientation and inter-domain contacts of filamin Ig domains 16–24 (Rod 2 region) play an important role in ligand binding regulation by the β sheet augmentation mechanism30. Additional example of such multi-domain protein is myomesin, located at the M-band. Crystal structures of its poly-tandem Ig9–13 domains revealed structured, α-helical linkers between domains, which restrict domain flexibility. These domain-connecting linkers possess a spring-like mechanism – they unfold upon applied tension and again refold when tension is reduced58.To date, great effort has been put in studies of mechanical and structural properties of sarcomeric proteins located within the I-band and Z-disk, particularly with regard to their single and poly-tandem Ig domain regions which are known to be able to adopt different relative orientations and in turn affect the flexibility and elasticity of their cognate proteins. In particular, the main focus of the research has been elastic I-band region of titin and inter-domain interactions of filamins. Results have shown essential impact of titin domain unfolding, stability and inter-domain mobility on mechanical properties directly correlated to muscle contraction and elasticityHere, we have focused on a small family of Z-disc proteins, composed of myotilin, myopalladin and palladin. Myotilin is the smallest member of the family with the two Ig domains, compared to a modular proteins myopalladin and palladin, which possess up to five Ig domains. To date, only a limited structural and mechano-dynamical data exist for this family; while structures of single myotilin Ig1 ref.  and Ig2 34. Since myotilin Ig domains present an important interaction site for prominent proteins of the sarcomere like F-actin and filamin C, Ig domain flexibility could be a prerequisite for is interaction capabilities in the unbound state. We propose that conformational plasticity of Ig domains is part of the binding partner recognition mechanism similarly as reported for Z1Z2 upon binding to telethonin34.SAXS data, which allowed us to produce averaged low-resolution molecular envelope of tandem myotilin Ig domains, revealed »dumbbell« shape with an almost extended domain conformation. Flexibility analysis using dimensionless Kratky plot suggests a certain degree of conformational plasticity, which was confirmed using ensemble optimisation method (EOM) and MultiFoXS approaches. Use of these methods significantly improved fitting to the experimental data, compared to the rigid body modelling, and showed that myotilin Ig domains in solution can be described as a multi-conformation species that adopt various relative orientations resulting in a compact or more extended forms. However, these states are not equally populated since in the predominant form (50 %) the Ig domain pair adopts a semi-extended orientation. Interestingly, a preferential orientation has also been reported for the Z1Z2 domain pair of titin with implications in selective recruitment of the binding partner telethonin9, we did not observe species with molecular weight corresponding to the mass of the dimer , which indicates that the concentration effect described above was not a consequence of oligomerisation. Different construct design used in our and in previously reported studies suggests that regions outside of the Ig1–2 domain pair promote dimer formation and/or that the conditions used do not favour the formation of a stable dimer. For example, study of Salmikangas et. al showed that construct encompassing residues 229–441 is able to dimerise8. On the other hand, another study revealed that smallest fragment of myotilin with the ability to dimerise is 345–498 . Correct assembly was verified by DNA sequencing (GATC Biotech). For protein expression E. coli strain BL31[DE3] was used. Briefly, cells were grown at 37 °C in LB media supplemented with ampicillin (100 µg/mL) to an OD600 of approximately 0.6. After cooling to 20 °C recombinant protein expression was induced by addition of IPTG to a final concentration of 0.5 mM. After 16 h cells were collected by centrifugation, resuspended in lysis buffer , and lysed by sonication. Soluble fraction was obtained by centrifugation  and applied onto HiTrap IMAC FF column . After washing  the bound proteins were eluted by gradually raising imidazole concentration to 500 mM. His6-tag was removed by incubation of the pooled eluates containing MYOTIg1–2 with GST-tagged HRV-3C protease  during overnight dialysis at 4 °C against the dialysis buffer . The His6-tag free MYOTIg1–2 was recovered as a flow-through after applying the cleavage mixture onto HiTrap IMAC FF and GSTrap FF columns to remove uncleaved MYOTIg1–2 and HRV-3C protease, respectively. Final purification step was size-exclusion chromatography on a Superdex 75 10/300 column  equilibrated in buffer 20 mM HEPES, 150 mM NaCl, 5 % glycerol, 1 mM DTT, pH 7.4. The purity of the final samples was assessed by SDS-PAGE  was cloned into pETM-14 vector (EMBL) to create fusion construct with the plasmid-encoded N-terminal His61. Input parameters for constructing phylogenetic trees were: LG substitutional model, Bio-NJ as initial tree, Nearest-Neighbour-Interchange (NNI) as tree inference heuristic method and branch support calculated with 100 bootstrap replicates. Calculated trees were graphically edited using FigTree software (http://tree.bio.ed.ac.uk/software/figtree/). Conservation scores for each myotilin residue in the multiple sequence alignment (MSA) were calculated using the Scorecons server62. Disorder tendency prediction was performed using the GeneSilico MetaDisorder server63.For evolutionary analysis, two sets of data were prepared: (1) complete myotilin sequences  was measured in the range from 0.03 < s < 5.0 Å, where s = 4π sinθ/λ and λ = 1 Å, at the distance between sample and detector of 2.867 m. Background scattering was subtracted, data reduced, normalised according to the measured concentration and extrapolated to infinite dilution using the two lowest measured concentrations using PRIMUS65 module of the ATSAS software package66. Forward scattering (I0) and radius of gyration (Rg) were obtained by fitting the linear Guinier region of the data. Pair distribution function P(r) with the corresponding maximum particle size parameter (Dmax) was determined using GNOM program67. The dimensionless Kratky plots were generated by the use of data from SASBDB50 for BSA (accession code: SASDBT4), filamin A Ig20-Ig21 (accession code: SASDAH8), filamin A Ig20-Ig21+migfilin (accession code: SASDAG8) and filamin A Ig22-Ig23 (accession code: SASDAU3).SAXS data for purified construct MYOTIg1–2 was collected at ESRF beamline BM29 BioSaxs  equipped with the Pilatus 1M detector. Samples were measured at concentrations of 3.67, 7.00 and 14.12 mg/mL in buffer 20 mM Naab initio modelling was performed 20 times using the program DAMMIF68, where scattering from the calculated envelopes were fitted against the experimental scattering and evaluated by the chi values. The most typical envelope was selected by comparing the normalised spatial discrepancy (NSD) values between pairs of envelopes  and Ig2 (PDB accession code: 2KKQ) were used to fit SAXS scattering data using program CORAL66. Linker residues were designated as dummy atoms. Ab initio calculated envelope was superposed to the rigid body model using SUPCOMB program70.For reconstruction of theoretical molecular envelope 71 with enforced P1 symmetry while the linker between Ig domains was again designated as dummy atoms. Conformations consistent with scattering data were selected from the pool of 50 000 models using a genetic algorithm. The flexibility analysis was independently repeated three times; all runs gave comparable results. For comparative analysis MultiFoXS server72 was used where I-TASSER structure was used as the input model; residues Leu341, Ala342, Lys343, Glu344, His345, Lys346, Arg347 were designated as flexible residues. More than 10 000 conformations were calculated and scored with the rapidly exploring random trees (RRT) search to extract only those conformations, which adequately describe observed system. All structure figures were prepared using PyMOL .Flexibility analysis was performed using EOM2.1 program73 and the best model was selected on the basis of its Z-score. This model was then used to analyse structure fluctuations as well as in molecular dynamics simulations. Same model was used for the in silico mutagenesis, which was performed in PyMOL, to obtain model with the mutated AKE motif to AAA.Models of tandem Ig domains were calculated using I-TASSER74. RMSF values of the 2000 frames were analysed in terms of distance between Ig domains  vs. number of frames.Fluctuations of relative orientation between the tandem Ig domains were predicted using CABS-Flex server which implements structure coarse-graining and Monte Carlo dynamics sampling scheme75 with CHARMM-27 force-field. Initial structure was solvated and neutralised (by adding Na+ or Cl− ions) and the topology was generated using psfgen. Equilibration was done at 300 K using constant temperature Langevin dynamics, constant pressure via Noose-Hoover Langevin piston and Particle Mesh Edward for full-system periodic electrostatics. Energy minimisation was done for 500 steps of conjugate gradients. Time-step was set to 2 fs. The length of the final production run was 10 ns. MD trajectories were analysed using VMD76 where end-to-end distances were measured. Further trajectory analysis was done using the DynDom server77 to reveal hinge residues which could participate in the torsion mechanism of conformational switching and to calculate rotation angle of inter-domain bending. Inter- and intra-domain interactions via hydrogen bonding were analysed and graphically presented using Cytoscape78 coupled with UCSF Chimera79 and structureViz80 programs.All-atom molecular dynamics (MD) simulations were performed using NAMD 2.1 program suiteSupplementary InformationSupplementary Information


Drosophila melanogaster and other arthropods, MWH-related proteins are also identified here in some nematodes (including Caenorhabditis elegans), and are shown to be related to a novel MWH-related formin (MWHF) subtype. One surprising result of this work is the discovery that a family of pleckstrin homology domain-containing formins (PHCFs) is represented in many vertebrates, but is strikingly absent from placental mammals. Consistent with a relatively recent loss of this formin, the human genome retains fragments of a defunct homologous formin gene.Formins are a widespread family of eukaryotic cytoskeleton-organizing proteins. Many species encode multiple formin isoforms, and for animals, much of this reflects the presence of multiple conserved subtypes. Earlier phylogenetic analyses identified seven major formin subtypes in animals , but left a handful of formins, particularly from nematodes, unassigned. In this new analysis drawing from genomic data from a wider range of taxa, nine formin subtypes are identified that encompass all the animal formins analyzed here. Included in this analysis are Multiple Wing Hairs proteins (MWH), which bear homology to formin N-terminal domains. Originally identified in  Formins are best known as regulators of actin filament dynamics. These proteins are critical for the assembly of a variety of actin-based cellular structures, including but not limited to cytokinetic contractile rings, stress fibers, and cables that mediate actin-dependent intracellular transport (reviewed in –3). Of cThe defining feature of formin proteins is a ~ 350 amino acid residue actin-binding formin homology-2 (FH2) domain that is often paired with an upstream proline-rich formin homology-1 (FH1) domain –14. ThesThe Diaphanous-related formins (Drfs) are a subset of these proteins that have additional conserved regions N-terminal to their FH1 domain, including a RhoGTPase-binding domain (G-domain) followed by a diaphanous inhibitory domain (DID), and a dimerization domain (DD). The DD promotes homodimerization, while the DID of many Drfs binds to a C-terminal WH2-like motif  to hold the formin in an autoinhibited state . Relief It should also be noted that the designation "Drf" is something of a misnomer, as a distinct diaphanous  subtype of formins represents just one of many Drf-type formins. In fact, the majority of metaozoan formins are Drfs, but a significant minority of formins are non-Drfs that diverge from this domain organization. In such non-Drfs, one or more conserved N-terminal domains are absent, often to be replaced by other folds, such as structurally distinct GTPase-binding domains, or postsynaptic density protein 95/ Drosophila disc large tumor suppressor 1/zonula occludens-1 protein (PDZ) domains . These aNematostella vectensis that was unique among known animal formins for the presence of N- and C-terminal pleckstrin homology (PH) domains [Caenorhabditis elegans, whose only formin homology is a highly divergent FH2 domain that has resisted previous assignment to a conserved formin subtype [Drosophila melanogaster shares incomplete similarity to formins, with sequence homologous to the N-terminal domains of Drfs, but lacking FH1, FH2, or other conserved C-terminal formin homology [Based on phylogenetic analyses of FH2 domains, metazoan Drf and non-Drf formins can be further subdivided into seven subtypes that are conserved across multiple phyla , 18. Usi domains . Nematod subtype . Finallyhomology , 24. As homology .The availability of more complete genomic data from a wider range of taxa provided an opportunity to revisit the phylogeny of this important family of cytoskeleton-organizing proteins. As presented here, a broader sampling of formins helped reveal two new groups that were not previously recognized as being broadly distributed across metazoans, and tied the origins of MWH- and FOZI-1-related proteins to specific formin subtypes. Additionally, evidence is presented of an ancestral formin from one of these novel families that was lost recently from the lineage containing the placental mammals.Homo sapiens, Mus musculus, Monodelphis domestica, Gallus gallus, Danio rerio, Ciona intestinalis, Strongylocentrotus purpuratus, Drosophila melanogaster, Limulus polyphemus, Crassostrea gigas, Lottia gigantea, Helobdella robusta, and Amphimedon queenslandica; the Ensembl Genomes website (www.ensemblgenomes.org) [Daphnia pulex, Capitella teleta, Nematostella vectensis, Mnemiopsis leidyi, Trichoplax adhaerens, and Amphimedon queenslandica; the WormBase website  [Caenorhabditis elegans; and the WormBase ParaSite  [Ascaris suum, Strongyloides ratti, Romanomermis culicivorax, Trichuris suis, Clonorchis sinensis, and Echinococcus granulosus. Searches were conducted using standard search parameters. To ensure all FH2 domains were detected, each species was subject to search queries based on FH2 domains from the M. musculus formins DAAM1, DIAPH1, FMN2, GRID2IP, FHDC1 (an INF-subtype formin), INF2, FMNL1, and FHOD1, the S. purpuratus formin LOC100890634 (a pleckstrin homology domain-containing formin), and the C. elegans FOZI-1 (a divergent FMNL-subtype protein). Searches were not conducted using a representative of the novel MWH-related formin (MWHF) subtype, as these proteins were not initially recognized as a distinct subtype. However, the similarity between MWHF and FMNL proteins makes it unlikely that any formins were missed due to this omission. All identified formins are listed by species in Formins were identified through searches for FH2 domains in species for which at least a draft genomic sequence was available. Specifically, protein databases and translated nucleotide databases were searched using the Basic Local Alignment Search Tool (BLAST) . Publicames.org)  for Daphn WS252)  for Caenn WBPS6)  for AscaD. melanogaster MWH. Positive hits of high significance, as occurred with other arthropods, were accepted with no further confirmation. Positive hits of marginal significance that were found for certain nematodes were further tested by using the nematode sequences as the basis for additional queries. Proteins for which reversed queries identified other MWH proteins were considered to be MWH homologs. All identified MWH proteins are also listed by species in The same species were searched for MWH homologs by querying for homology to predicted DID and DD sequences of Subsequent domain and multiple sequence alignment analyses suggested some predicted FH2 domain sequences were incomplete, while others were not coupled with expected additional regions of formin homology. Such cases were almost always based on gene predictions, rather than isolated cDNA sequences. Working on the assumption that these reflected errors in annotation, the genomic sequences were examined for additional formin-coding sequence, as follows. In cases of presumed internal gaps of the FH2 domain, predicted intron sequences that occupied gap regions were translated in three frames and searched for FH2 similarity, and any identified unambiguous FH2-coding sequence was restored. Formins for which this was done are labeled "inferred" in Formin and MWH amino acid sequences were subject to Conserved Domain Searches (CDS)  by compaM. musculus DIAPH1, DIAPH2, DIAPH3, DAAM1, DAAM2, FHOD1, FHOD3, FMNL1, FMNL2, FMNL3, and INF2, D. melanogaster DIA, DAAM, FRL, and FHOS, and C. elegans FHOD-1 and FRL-1 [DAD and other WH2-like motifs were only rarely identified by CDS, and were missed in many cases where DAD and WH2 motifs were shown to exist in previous studies. Similarly, attempts to identify these motifs using the Eukaryotic Linear Motif resource  were alsnd FRL-1 , 14, 17.2) website (www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index) [S. ratti FOZI-1-like protein SRAE_2000156800.For positive identification of other structural domains, formin sequences N-terminal to FH1 domains, formin sequences C-terminal to FH2 domains, and entire MWH sequences, were submitted to the Protein HomologY Recognition Engine 2 (PHYREd=index) . Only doFH2 domain amino acid sequences were aligned by the ClustalW method  using MeEvolutionary histories for aligned FH2 domain, DID-DD, or DID sequences were inferred using the Maximum Likelihood (ML) method in the MEGA6 program . Out of www.genomicus.biologie.ens.fr/genomicus-84.01/cgi-bin/search.pl) [CBLN4 and MC3R genes, respectively, of the opossum M. domestica as references in comparison to all available bilaterian genomes.Gene order in chromosomal neighborhoods of various vertebrate species were examined using the Genomicus v84.01 website (arch.pl) . DepictiTo analyze the phylogeny of metazoan formins, BLAST searches  were useThese FH2 domain amino acid sequences were aligned . Within Strongly supported nodes also appeared within putative subtypes, but these nodes rarely separated multiple formins from a single species, as would be expected if they defined additional formin subtypes. The only exception found in both the ML and NJ trees was a node within the FMN subtype that divided multiple mollusk, annelid, and cnidarian FMN homologs into two groups, potentially indicating a further conserved subdivision of the FMN subtype. However, the relationship of formins from other phyla to these putative subtypes was not clear, and this was not investigated further.N. vectensis that, based on FH2 domain sequence, was unrelated to any of the seven metazoan formin subtypes known at that time. This formin also differed from other metazoan formins in having N- and C-terminal PH domains. From the broader sampling of species here, additional PH domain-containing formins (PHCFs) were revealed in additional metazoans. Analysis of these proteins using the PHYRE2 website [A. queenslandica also has N- and C-terminal PH domains, specifically a tandem pair in the N-terminus and a single C-terminal one  showedrsupials . For thersupials . To probrsupials . Notablyng frame , all conA ninth cluster of formins in each FH2 phylogenetic tree was linked with, but separated from, the FMNL proteins by well-supported nodes with bootstrap values > 85 in all trees  and formin homology-3 (FH3) domain [D. melanogaster MWH protein using the PHYRE2 website [The product of the ) domain , 24. In ) domain . Analysi website  predicteD. melanogaster MWH and C. elegans MWH-related F53B3.3 were also included in ML and NJ phylogenetic trees estimated using Drf-formin DID-DD sequences. Consistent with an earlier effort that was unable to assign MWH to a particular formin subtype [green circles).The DID-DD sequences of  subtype , neitherred asterisks). All other formins encode tryptophan at these positions, but the FMNL and MWHF proteins substitute phenylalanine for the second tryptophan. Less striking, but also unique for the FMNL and MWHF homologs, is the presence of proline at the fourth residue position upstream of the first conserved tryptophan (blue triangle).The close position of FMNL and MWHF proteins on phylogenetic trees implies a particular relatedness between these two groups of formins. Casual inspection of aligned DID-DD and FH2 sequences  reveals A distinctive feature of MWHF proteins compared to most other Drf-type formins is that they lack any detectable DAD- or WH2-like motifs C-terminal to their FH2 domains . This isC. elegans proteins [A. suum fell into one of five subtypes  (C. elegans) were examined as part of a larger array of bilaterian species, most of these also grouped with one of these five subtypes  . When FHsubtypes , with a ic trees . This ma formins .C. elegans. Based on analysis using the PHYRE2 database, these proteins lack any formin homology outside their FH2 domain, but encode two N-terminal zinc fingers   revealedThe purpose of this study was to address lingering questions about the relatedness of a handful of formin and formin-related proteins, particularly nematode formins, MWH, and a PH domain-containing formin of cnidaria. To improve upon earlier studies, this analysis included formins from metazoan phyla not previously analyzed , and from additional species from phyla only rarely analyzed in other studies (mollusca and annelida). Two major findings were discovery that the metazoan formin family is more diverse than previously appreciated, and that all formins and formin-related proteins are members of evolutionarily conserved subtypes that were likely present at the very origins of metazoa.N. vectensis and the non-metazoan choanoflagellate Monosiga brevicollis [D. melanogaster MWH protein Click here for additional data file.S1 Text(TXT)Click here for additional data file.S1 FigThe evolutionary history for 100 FH2 domain amino acid sequences from representatives of eleven metazoan phyla was inferred by the NJ method for 343 amino acid positions occupied in ≥ 95% of sequences. All bootstrap values are indicated, and the scale bar indicates the number of substitutions per site for branch lengths. As found in the corresponding ML tree , nine gr(TIF)Click here for additional data file.S2 FigThe evolutionary history for 227 FH2 domain amino acid sequences was inferred by the ML method for 295 amino acid positions occupied in ≥ 95% of sequences. All bootstrap values are indicated, and the scale bar indicates the number of substitutions per site for branch lengths. Asterisks (*) indicate formins for which a partial FH2 domain sequence was used for this analysis. All formins, with the exception of three nematode proteins, fell into one of nine conserved subtypes.(TIF)Click here for additional data file.S3 FigA. suum lacked a detectable MWH-related protein, the DID-DD of the C. elegans MWH-related F53B3.3 was included in this analysis. Results shown here match those of the corresponding ML phylogenetic tree Click here for additional data file.S4 Fig(A) NJ phylogenetic tree of DIDs. The evolutionary history for 48 DIDs was inferred by the NJ method for 164 amino acid positions occupied in ≥ 90% of sequences. All bootstrap values are shown, and the scale bar indicates the number of substitutions per site for branch lengths. Based on DID sequences, formins segregated into the same subtypes as observed after analysis of their FH2 domain sequences ((B) ML phylogenetic tree of DIDs. The evolutionary history of the same sequences was also inferred by the ML method. Similar to the NJ tree, most formins segregated into the same subtypes. The exception was a disruption of the DIAPH subtype by the internal placement of the branch leading to the FHOD subtype formins.DID sequences from Drf-type DIAPH, DAAM, FMNL, MWHF, and INF formins, and non-Drf-type FHOD formins from the indicated species were identified and aligned (equences . (B) ML (TIF)Click here for additional data file.