The NMR chemical shift data were used as the constraints for the High Ambiguity Driven biomolecular DOCKing (HADDOCK) calculation to generate a structural model of the S100A12–V domain complex. In addition, tranilast  showed strong interaction with S100A12 in the 1H–15N HSQC titration, fluorescence experiments, and WST-1 assay. The results also indicated that tranilast was located at the binding site between S100A12 and the V domain, blocking interaction between these two proteins. Our results provide the mechanistic details for a structural model and reveal a potential precursor for an inhibitor for pro-inflammatory diseases, which could be useful for the development of new drugs.The receptor for advanced glycation end products (RAGE), a transmembrane receptor in the immunoglobulin superfamily, is involved in several inflammatory processes. RAGE induces cellular signaling pathways upon binding with various ligands, such as advanced glycation end products (AGEs), β-amyloids, and S100 proteins. The solution structure of S100A12 and the V ligand-binding region of RAGE have been reported previously. Using heteronuclear NMR spectroscopy to conduct  The authors of several studies have reported that members of the S100 protein family play regulatory roles in cells, and induce cell growth and differentiation . S100 prin vivo -1,3-benzene disulfonate) was purchased from Roche. FPS-ZM1, an inhibitor of the RAGE V domain, was purchased from Calbiochem [Luria broth was purchased from Amresco. lbiochem .2, 100 mM NaCl, 10% D2O, pH 7). Hung et al. have made available the backbone and side-chain assignments for S100A12 in specific buffer conditions  NaN3, pH 6.5) at the Biological Magnetic Resonance Bank (BMRB) (BMRB code: 19293) [2SO4) have been reported by Matsumoto et al. (BMRB code: 7364) [The HSQC spectra was collected using a Varian 700 MHz NMR spectrometer with cryogenic probes at 298 K. All titrations were carried out using the same buffer composition  , and thee: 7364) . We used15N-labeled RAGE V domain solution at molar ratios of 1:0, 1:0.33, 1:0.66, 1:1, and 1:2. The reverse titration (15N-labeled S100A12 with the addition of unlabeled RAGE V domain) was performed at molar ratios of 1:0, 1:0.25, 1:0.5, 1:0.75, and 1:1. Finally, the titration experiment with 15N-labeled S100A12 and tranilast was performed at molar ratios of 1:0, 1:0.5, 1:1, and 1:2. By overlaying the HSQC spectra at different ratios, we identified certain residues at the interface of the two molecules that had decreased intensity or perturbed chemical shift.The titration experiment was performed by adding unlabeled calcium-binding S100A12 to the HADDOCK is useful software for calculating protein–protein docking. We used it to obtain the complex structures of the S100A12–RAGE V domain and S100A12–tranilast complexes. The structural coordinates of calcium-binding S100A12 were taken from the Protein Data Bank (PDB ID: 2m9g) . The str0). The program used the following equation [Fluorescence titration can be a useful method for measuring the binding affinity of a protein–ligand interaction –54. We uequation  to calcu0 represents the fluorescence intensity of the solution in the absence of S100A12; I represents the fluorescence intensity of the solution that contained S100A12 and the RAGE V domain; I1 represents the fluorescence intensity at the end of the experiment; and Kd represents the dissociation constant. The original curve was further processed by fitting to a linear curve and the slope was calculated to obtain the dissociation constant.In Eq , I0 reprA similar approach was used with tranilast. The structure of tranilast contains a benzyl group, which exhibits obvious emission upon excitation at 333 nm. Tranilast exhibited a broad absorption peak at 335 nm in the UV spectra. By monitoring S100A12 at different concentrations (0–7.5 μM) in solution with tranilast (at a concentration of approximately 2.5 μM) and using an excitation wavelength of 333 nm, we obtained a curve and determined the extent of binding between S100A12 and tranilast.Previous studies have shown that binding between S100A12 and RAGE activates the NF-κB signaling pathway , which i4 cells/well in a 96-well plate on the day before experiments. Subsequently, the cells were incubated in a serum-free medium containing 0.1% bovine serum albumin (BSA) for 24 h, after which the proteins  or drugs (1 μM tranilast or 1 μM FPS-ZM1) were added to the serum-starved cells, which were incubated for a further 48 h. Before harvest, 1/10 volume of WST-1 was added to each well and the cells were incubated at 37°C for a further 4 h. The medium in the cell culture plate was mixed by gentle agitation on a shaker for 10 min. The absorbance was measured at 450 nm using a Synergy 2 microplate reader . The relative cell numbers were determined by the absorbance relative to that observed in the control [In this study, a WST-1 cell proliferation assay was performed according to the manual (Roche). The cells were cultured to the logarithmic growth phase, trypsinized, and seeded at a density of 1 × 10 control , 61.et al. (S100A12) and Matsumoto et al. (RAGE V) to map the binding region. An overlay of the spectra of the 15N- labeled S100A12 alone and the 15N-labeled S100A12 complex with the unlabeled RAGE V domain showed that the signals of these residues changed  as the protein complex formed. The perturbation and decreased intensity originated from the residues at the interface between S100A12 and the RAGE V domain. To determine the extent of the changes in the HSQC cross-peaks, we recorded the chemical shift of the cross-peaks in two different dimensions, 1H and 15N, in the spectra at a protein–ligand ratio of 1:0  and the complex spectra  at a ratio of 1:1. Next, we calculated the extent of perturbation using the following formula [Using a two-dimensional HSQC spectrum, we conducted the titration experiments with the assignments reported previously by Hung  formula :Chemica1H–15N HSQC spectra: (1) 15N- labeled S100A12 alone and (2) 15N- labeled S100A12 with an unlabeled RAGE V domain.0) and the intensity of the same cross-peak in the spectrum of S100A12 (labeled) bound with the unlabeled RAGE V domain (I1). To identify the residues involved in S100A12 in complex with the RAGE V domain, we plotted bar diagrams to compare the titration results, and identified cross-peak perturbation  in the binding interface  model to calculate the best site for protein binding. The final results generated the best 200 structures and divided them into a single cluster. We took the best 10 structures from the cluster and the details of the calculation are shown in The binding sites mapped using the results of the NMR titration experiment represent a region of S100A12 that forms a molecular complex with the RAGE V domain. We generated a model of the protein complex to characterize the protein–protein interactions using HADDOCK. The interaction residues exhibiting an intensity change or a chemical shift perturbation in the The binding sites between S100A12 and the RAGE V domain are shown in 1H–15N HSQC titration experiments. The 1H–15N HSQC spectra of S100A12 alone and with tranilast were compared  of approximately 3.1 ± 1.4 μM was calculated for S100A12 binding with RAGE V, and a Kd of 6.1 ± 1.4 μM was calculated for S100A12 binding with tranilast. The diagrams and curves of the fluorescence results of S100A12 titrated with the RAGE V domain and S100A12 titrated with tranilast are shown in There are three tryptophan residues in the RAGE V domain at positions 51, 61, and 72. According to NACCESS analysis, residues 51 and 72 are buried inside the RAGE V domain, and W61 is exposed on the outside of the RAGE V domain. Moreover, W61 is the only tryptophan that is located in the interface region of the RAGE V domain. Therefore, we monitored protein excitation at 295 nm, and a decrease in fluorescence intensity at 350 nm indicated changes in polarity around W61. The charge surrounding W61 became more positive . The titWith increasing concentration of S100A12  , as showet al. [et al. [1H–15N HSQC titration to show that it interacts with S100A12. As shown in The interaction between S100A12 and RAGE V activates several downstream signaling pathways resulting in different biological responses in cells. For example, in 1999 Hofmann et al.  reported [et al.  also shod of tranilast was lower than that of RAGE V with S100A12, it still represents a potential precursor for the development of new inhibitors. Further evaluation using the WST-1 assay indicated that tranilast efficiently inhibited cell proliferation in vitro. Our results have provided structural insight into the S100A12–RAGE V complex and identified a precursor for the development of new drugs. These results may be useful for the generation of therapies that focus on RAGE and S100 protein-related diseases.Moreover, using fluorescence titration measurement we obtained the dissociation constants for both S100A12–RAGE and S100A12–tranilast. Although the KS1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 FigThe molecular weight difference was approximately 2.6 Da owing to a disulfide bond inside the V domain of RAGE.(TIF)Click here for additional data file.S4 Fig1H–15N HSQC spectra of 0.5 mM 15N-labeled RAGE V domain (red) and RAGE V domain titrated with 0.5 mM tranilast (green).Overlay of the (TIF)Click here for additional data file.S5 FigWe replicated the experiment with 2.5 μM tranilast and titrated with S100A12 protein. We colored the linear curve in a different color for each replication. The dissociation constant was approximately 6.1 ± 1.4 μM.(TIF)Click here for additional data file.S6 FigWe replicated the experiment with the 1.5 μM RAGE V domain and titrated with S100A12 protein. We colored the linear curve in different colors for each replication. The dissociation constant was approximately 3.1 ± 1.4 μM.(TIF)Click here for additional data file.S7 FigWe used the RAGE V domain from the Protein Data Bank (PDB code: 2e5e) and labeled the binding sites with different colors .(TIF)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S1 TableThe picture shows the rationalization of the residues in the complex structure and the data indicate the percentage of allowed and disallowed regions. Only 1.2% (4 residues) were disallowed. Furthermore, the G-Factors also indicate that the result is a reasonable region because the overall average was only 0.1 .(TIF)Click here for additional data file.S2 TableThe diagram was constructed on the PROCHECK website. The picture shows the rationalization of the residues in the complex structure and the data indicate the percentage of allowed and disallowed regions. Only 1.24% (2 residues) were disallowed. Furthermore, the G-Factors also indicate that the result is a reasonable region because the overall average was only -0.09 .(TIF)Click here for additional data file.


Subsequently, different recombinant spidroins were spun into fibers through wet-spinning via a custom-made continuous post-drawing device. Mechanical tests of the synthetic fibers with four parameters  demonstrated that the extensibility of the fibers showed a positive correlation with spidroin size, consequently resulting in the extensibility of N-Sc4-C fiber ranked the highest (58.76%) among four fibers. Raman data revealed the relationship between secondary structure content and mechanical properties. The data here provide a deeper insight into the relationship between the function and structure of Flag silk for future design of artificial fibers.Spider silk is an attractive biopolymer with numerous potential applications due to its remarkable characteristics. Among the six categories of spider silks, flagelliform (Flag) spider silk possesses longer and more repetitive core domains than others, therefore performing the highest extensibility. To investigate the correlation between the recombinant spidroin size and the synthetic fiber properties, four recombinant proteins with different sizes [N-Scn-C ( Summary: A study of the relationship between the structure and property of synthetic spider silk-like fibers, which aims to aid with the designing of functional artificial fibers. Orb-weaving spiders can produce up to six kinds of silk and one sticky aggregate for different tasks . Spider n repeat motifs  that form β-turns, juxtaposed to (GGX)n motifs and spacer motifs that form helices and β-sheets. These motifs combine to form spring-like spirals that provide the excellent extensibility of Flag (Flagelliform spidroin (Flag) contains (GPGGX) of Flag . Flag ha of Flag . Therefon=1-4), were constructed, expressed and spun to the silk-like fiber by wet spinning. The spun fiber was subjected to continuous post-drawing by a custom-made device. This study shows that the mechanical properties (such as extensibility and toughness) are improved by the increase of functional repetitive domains. The best elongation is obtained from N-Sc4-C (58.76%), while the highest strength belongs to N-Sc3-C (107.54 MPa). The Raman data illustrates the mechanical test results from the structural respect. This study may indicate the correlation between the size of recombinant spidroin and the mechanical properties of the synthetic Flag fibers, which might be applied for various medical or industrial settings.Here, the aim of this study is to illustrate the correlation between the length of the functional repetitive domain and mechanical properties of the synthetic Flag fibers. Four recombinant Flag spidroin with different sizes, like N-Scn-C (Araneus ventricosus (A.v.) genomic library and aligned with the only accessible Flag repetitive domain sequence (A.v.Flag-CT) in the database (GenBank: EF025541) . The Sc amino acid sequence showed GPGGX and GGX  motifs were contained, which were also conserved within Flag spidroin from Nephila clavipes (N.c.)  in one repeat domain, our Flag silk gene contained less pentapeptide repetitive motifs , Nephila madagascariensis (N.m.), or Nephila clavipes (N.c.) (A Flag repetitive domain gene (Sc) encoding 231 amino acids  was screF025541) . The seqs (N.c.) . When coe motifs . Two vale motifs , were foe motifs . The Flas (N.c.) .Fig. 1.n=1-4) was constructed to produce the silk-like fibers. The N/C domains of the recombinant Flag spidroin were chosen from the MaSp2 as their structures and functional roles have already been reported and analyzed  were constructed: N-Sc1-C, N-Sc2-C, N-Sc3-C and N-Sc4-C shown in C. The coanalyzed .Fig. 2.in vivo (E. coli.The intein-mediated purification with chitin binding tag (IMPACT) system was chosen to purify the recombinant spidroin A Evans . N-termiin vivo . Althougin vivo . After oin vivo B. In accin vivo  the yielin vivo C are difThe lyophilized spidroin was re-solubilized in HFIP . The spiThe inner morphology of the fibers was determined by scanning electronic microscopy (SEM). Fiber samples were immersed in liquid nitrogen and subjected to brittle fracture . In thisFig. S2 shows the morphology of one fiber of each type under the light microscope, and the diameter of fibers was calculated. The stress-strain curves and mechanical testing data  are shown in Table S1)  . The spiable S1) . Interesable S1)  comparede S1) 3; B. We spe1) . From the divided peaks, the secondary structural fractions in fibers could be calculated via accounting the area of the peak  were constructed with the N/C non-repetitive domains  and the repetitive domain Sc . Meanwhile, another construct Sc1 was constructed without the terminal domain N/C as a control. The CD spectra of the Sc1 and N-Sc1-C were done to detect their secondary structure in PB buffer and HFIP . From the CD spectra we speculated that the N/C domain plays a functional role for the structure of the Sc1 in PB buffer or HFIP, and the HFIP may affect the protein structure. Though HFIP may change the protein structure, some reports proved that the conserved C-terminal domain of spider tubuliform spidroin 1 contributed to extensibility in synthetic fibers even in HFIP  and breaking stress (41.5 MPa). With the increase of repetitive domain Sc, which contains many GPGGX and GGX motifs contributing to extensibility , the proInterestingly, the N-Sc3-C fibers had the smaller diameter, though they showed the best strength. We speculated that the moderate molecule weight of N-Sc3-C spidroin supplies better overall organization. This may cause its diameter to be smaller than the others and contain the most β-sheet content (38.34%), providing a higher strength. Besides, some unknown mechanisms might exist resulting in these unusual changes. Further studies on these mechanisms may help to produce fibers that meet the specific requirements in various settings. Some reports also claim that synthetic fibers with small diameters have better properties than others with a large diameter . Apart fThe mechanical tests and Raman data analysis indicated there might be a molecular weight threshold of the functional repetitive domain relating to extensibility of the silk. In this study, the largest protein (N-Sc4-C: 99 kDa) possessed the highest extensibility. When compared to the native Flag silk with >200% extensibility, our constructed fibers were lower since the native Flag silk proteins were usually larger than 360 kDa . This fuIn this study, we investigated the correlation between the recombinant spidroin size and the synthetic fiber properties. Besides, the relationship between the structure and function of repetitive domain in synthetic fibers was also studied. Four different sizes of recombinant spidroin were constructed and generated into fibers by wet-spinning using a custom-made post-drawing device. The fiber morphology, mechanical properties, and secondary structure were comprehensively evaluated. The results indicated that the extensibility of the synthetic fibers was in positive correlation with the recombinant Flag spidroin size, and may imply a potential threshold of the protein size for excellent extensibility of the fibers . Furthermore, our study showed the relationship between the function and structure of the synthetic fibers, which was useful for functional protein design with various extensibility. In addition, these synthetic fibers from Flag spidroin with acceptable mechanical properties may provide a promising potential as the biomaterial for specific applications.Araneus ventricosus (A.v.) genomic library  and two enzyme recognition sites, BsaІ and BfuAІ, were added to amino-terminal (N) and carboxy-terminal (C) of the silk gene in pET32, respectively, to make clone pETSc1 with NdeІ and XhoІ. The N and C terminal non-repetitive domains were obtained according to the major ampullate spidroin 2 (MaSp2) of Argiope trifasciata and Argiope aurantia, by using E. coli gene codon .Chemical reagents and kits were purchased from Sangon . All restriction enzymes were purchased from New England BioLabs . The gene of the Flag repetitive domain was screened from an  library , and theBsaI/PstI and BfuAI/PstI followed by Sc1 insertion. The same procedures were used to generate pETSc3 and pETSc4. The N terminal non-repetitive domain was amplified by primers N-1 (5′-GGGAATTCATATGGGTGAACAAGGTGGTCTGTC-3′) and N-2 (5′-ACCGGTGGTCTCGCCAGCGTACGGGCCACGACCGCCTG-3′); while C terminal non-repetitive domain was amplified by primers C-1 (5′-GGCACCTGCTTCTGGCGGTGGTCAACGTGGTCCTCGCTC-3′) and C-2 (5′-GGCCTCGAGGCTCTTCCGCAACCCAGAGCCTGAGTCAG-3′). Underlining shows the site of restriction enzymes, NdeI, BsaI, BfuAI, XhoI, respectively. The N and C non-repetitive domains were cloned into the pETSc by NdeІ/BsaІ and BfuAІ/XhoІ, resulting in pET-N-Sc1-C, pET-N-Sc2-C, pET-N-Sc3-C and pET-N-Sc4-C, respectively.The cloning strategy was performed as previously described . Brieflyn=1-4) were digested by NdeІ and SapІ and ligated into pTWIN1 resulting in pT-N-Sc1-C, pT-N-Sc2-C, pT-N-Sc3-C and pT-N-Sc4-C, respectively. All the recombinant plasmids were sequenced.To construct the expression vector, the recombinant plasmids pET-N-Scn-C  to a final concentration of 0.8 mM. Upon induction, the temperature was decreased to 25°C for 16 h. The collected overnight cells were re-suspended in a lysis buffer  by 20% (w/v), lysed by a pressure homogenizer JN-3000 plus  at 1300 bar, and was further incubated for an additional 1 h at room temperature. Cell lysates were clarified by centrifugation at 21,000×g for 20 min and the supernatants were dialyzed in a column buffer .All expression clones (pT-N-Scn-C) in BL21 (DE3) cells were cultured overnight in 10 ml of Luria broth (LB) containing 100 μg/ml ampicillin in a shaking incubator at 37°C. The overnight culture was inoculated into 1 liter of LB containing 100 μg/ml ampicillin. When the ODThe purification of the silk proteins was performed according to the N-terminal cleavage protocol of the intein mediated purification with an affinity chitin-binding tag (IMPACT) system (New England Biolabs). All the purification buffers contained 4 M urea and the elution buffer added 100 mM DTT additionally. The IMPACT system carries an intein-chitin binding domain (intein-CBD) tag for one-step purification using a chitin resin. The target protein can be specifically released from the tag through induction of intein cleavage by the addition of a thiol-containing buffer (we used DTT) and elute from the column. Thus, the target protein can be collected without any extra tag. The purified recombinant spidroin was dialyzed in pure water to remove salts and centrifugation and freeze-drying.The lyophilized proteins were re-solubilized in HFIP (hexafluoroisopropanol) to make a 15∼20% (wt/v) spinning drop. The spinning drop was moved into a syringe and injected by a pump  into a coagulation bath. The spinning rate was 20 μl/min and the coagulation solvent was 90% methanol (v/v). The silk-like fiber was spun and drawn from the bath by a custom made device . There wBefore the mechanical tests, all fibers were fixed on testing cards and checked by the light microscope to ensure the fibers were of uneven thickness. The diameters of fibers were measured by Image Tool software. The mechanical tests of the synthetic fibers were conducted on a UTM T150  from Agilent. The gage length was 6 mm and the starting load strength was 750 μN. A minimum ten samples were tested for each type of silk.The secondary structures of the fibers were determined using Micro-Raman Spectroscopy System . For each sample, at least seven fibers were tested to assess sample uniformity, and the spectral decomposition of the amide I region was analyzed by the peak-fit software to calculate the secondary structure composition .


To visualize the dynamic domain motion of class-I CDH from Phanerochaete chrysosporium (PcCDH) during catalysis using high-speed atomic force microscopy, the apo-form of PcCDH was anchored to a heme-immobilized flat gold surface that can fix the orientation of the CYT domain. b-type heme. To directly visualize the dynamic domain motion of class-I CDH from Phanerochaete chrysosporium (PcCDH) during catalysis using high-speed atomic force microscopy, the apo-form of PcCDH was anchored to a heme-immobilized flat gold surface that can specifically fix the orientation of the CYT domain. The two domains of CDH are found to be immobile in the absence of cellobiose, whereas the addition of cellobiose triggers an interdomain flip-flop motion involving domain–domain association and dissociation. Our results indicate that dynamic motion of a dual domain enzyme during catalysis induces efficient electron transfer to an external electron acceptor.Cellobiose dehydrogenase (CDH) is a dual domain flavocytochrome, which consists of a dehydrogenase (DH) domain containing a flavin adenine dinucleotide and a cytochrome (CYT) domain containing  Cellobiose dehydrogenases (CDHs),b-type heme (iron protoporphyrin IX).13 The domains are connected by a long flexible linker (b in the CYT domain via interdomain electron transfer (IET). The reduced form of CYT then donates the electrons to an external electron acceptor such as LPMO.15 Two electrons have been proposed to be transferred from the DH domain to the CYT domain through a ping-pong mechanism on the basis of previous kinetic studies.17 Two conformational snapshots of CDH in closed and open states are also determined by X-ray crystal structure analysis of full-length CDH. However, the closed and open structures are obtained from the different species, Myriococcum thermophilum (MtCDH) and Neurospora crassa (NcCDH), respectively  domain containing flavin adenine dinucleotide (FAD) and a cytochrome (CYT) domain containing e linker . The DH y Fig. S1.18 The n23 We herein report direct visualization of the dynamic motion of class-I CDH from the basidiomycete Phanerochaete chrysosporium (PcCDH) by HS-AFM. To anchor and orient CDH on a flat surface for AFM imaging, we applied a technique for reconstitution of hemoproteins on a heme-immobilized surface via the heme–heme pocket interaction  to obtain a fundamental understanding of the structure and function of CDH. HS-AFM has recently been proven to be a powerful imaging technique capable of capturing dynamic motion of biomolecules temporally at the sub-second timescale and at sub-molecular lateral resolution.eraction .24–27 ThPcCDH, which has higher uniformity in terms of structure. Deglycosylated PcCDH with characteristic absorption maxima at 380, 421, 450, 529, and 570 nm originating from FAD and ferric heme (hemin) was adjusted to pH 1.5 with an acidic solution to remove both cofactors  or ferric cytochrome c as an oxidant according to the literature30   measurements , cellobiose and cellobino-1,5-lactone in the solution were analyzed by ESI-TOF MS. The conversion of cellobiose into cellobiono-1,5-lactone was confirmed under aerobic conditions, thereby indicating that PcCDH linked on the gold surface exhibits the inherent enzymatic activity using O2 as an electron acceptor.We tested the activity of PcCDH immobilized on the gold surface during the catalytic reaction using the HS-AFM technique. In the absence of cellobiose, immobilized PcCDH is imaged as a round-shaped object with a height of 6–8 nm  and the open state (ca. 10 nm) of PcCDH. By contrast, the changes in the height profile were not detected by HS-AFM measurements. The DH domain, which is linked via a flexible linker, moves rapidly in the open state, and thus the height of the domain in rapid motion cannot be precisely measured using HS-AFM. The tip vibration would force the moving DH domain to remain near the surface in the fast scan mode.We then carried out real-time imaging of the domain motion of  Movie S1. These me Fig. S1.18 Surprf motion . Each Pc Fig. S10. The avePcCDH was analyzed at different concentrations of cellobiose  averaged through 300 ms × 250 frames for each molecule. The decrease in the CC value represents the difference between the two sequential images of the focused enzyme in the movie. In the absence of cellobiose, the CC value of PcCDH is distributed around 0.97, suggesting the immobility of PcCDH in the absence of the substrate. The CC values are gradually shifted from 0.96 to 0.88 as the concentration of cellobiose increases from 50 to 200 μM (PcCDH becomes more intense. Furthermore, when cellobiose is removed from the observation cell by exchanging the buffer, the CC value shifts to 0.97, which is similar to that observed in the absence of cellobiose (Fig. S11 and Movie S6PcCDHs. Therefore, the degree of the motion in PcCDH anchored on the gold surface increases in a cellobiose-dose-dependent manner, indicating that cellobiose binding followed by the reaction initiates the dynamic motion of the two domains.To clarify the evidence that the cellobiose molecule triggers the domain motion, the degree of the motion in o 200 μM . The dec36PcCDH is expected to be in the closed or open state when the heme is oxidized or reduced, respectively. The HS-AFM study for PcCDH in situ gives us sequential views of the domain motions between the closed and open states during catalysis involving the cycle between the oxidation and reduction of the heme. The movement of the DH domain of PcCDH is centered on the CYT domain during the cycle of the closed–open–closed states. The DH domain apparently moves back to similar positions approximately within 1 s, as estimated from the sequential HS-AFM images. The previous study using the small-angle X-ray scattering analysis indicates that in the presence of the inhibitor molecules, the conformational population of the open state increases relative to that of the closed state in both MtCDH and NcCDH.18 The small angle neutron scattering study revealed that glycosylated NcCDHIIA, which has a C-terminal carbohydrate binding module, has an extended conformation in the fully oxidized state.37 In the present study, we can directly observe single-molecule domain motion of deglycosylated PcCDH triggered by binding of cellobiose. Therefore, the flip-flop domain motions of CDH appear to be strongly related to shuttling of electrons from cellobiose to a terminal electron acceptor.In the oxidative depolymerization of cellulose, the DH domain of CDH is known to accept two electrons from cellobiose and then reduces the CYT domain through one-electron IET. The catalytic cycle of CDH through a ping-pong mechanism involving five steps has been proposed as shown in PcCDH can be immobilized on a flat gold surface via the CYT domain with a controlled orientation via the heme–heme pocket interaction and can still remain catalytically active toward cellobiose oxidation. In addition, this strategy enables the two domains of anchored PcCDH to retain a degree of freedom in terms of interdomain motions required for the catalysis. As a result, we have directly visualized the interdomain flip-flop motions of PcCDH triggered by the binding of cellobiose in situ using the HS-AFM technique. This observation implies that the flip-flop motion of the two domains in PcCDH regulates the electron transfer process to the terminal electron acceptor, thereby harmonizing the entire electron relay through the enzymes in the oxidative process of cellulose depolymerization in vivo. The present method visualizing the domain motion of CDH on the flat surface by HS-AFM should be useful for investigating the dynamic motion of other multi-domain redox-active heme enzymes such as P450BM3.38 Our approach demonstrates that HS-AFM will provide novel insight into understanding the dynamic mechanism of enzyme catalysis including electron transfer as well as structural changes coupled with chemical reactions and photoactivation.39In this work, our data provide the first demonstration that


Results suggest that tethering of domains in multi-domain proteins influences the structural, dynamic and energetic properties of the constituent protein domains. 50% of the protein domain pairs show significant structural deviations while 90% of the protein domain pairs show differences in dynamics and 12% of the residues show differences in the energetics. To gain further insights on the influence of tethering on the function of the domains, 4 pairs of homologous protein domains, where one of them is a full-length single-domain protein and the other protein domain is a part of a multi-domain protein, were studied. Analyses showed that identical and structurally equivalent functional residues show differential dynamics in homologous protein domains; though comparable dynamics between in-silico generated chimera protein and multi-domain proteins were observed. From these observations, the differences observed in the functions of homologous proteins could be attributed to the presence of tethered domain. Overall, we conclude that tethered domains in multi-domain proteins not only provide stability or folding advantages but also influence pathways resulting in differences in function or regulatory properties.The majority of the proteins encoded in the genomes of eukaryotes contain more than one domain. Reasons for high prevalence of multi-domain proteins in various organisms have been attributed to higher stability and functional and folding advantages over single-domain proteins. Despite these advantages, many proteins are composed of only one domain while their homologous domains are part of multi-domain proteins. In the study presented here, differences in the properties of protein domains in single-domain and multi-domain systems and their influence on functions are discussed. We studied 20 pairs of identical protein domains, which were crystallized in two forms ( High prevalence of multi-domain proteins in proteomes has been attributed to higher stability and functional and folding advantages of the multi-domain proteins. Influence of tethering of domains on the overall properties of proteins has been well studied but its influence on the properties of the constituent domains is largely unaddressed. Here, we investigate the influence of tethering of domains in multi-domain proteins on the structural, dynamics and energetics properties of the constituent domains and its implications on the functions of proteins. To this end, comparative analyses were carried out for identical protein domains crystallized in tethered and untethered forms. Also, comparative analyses of single-domain proteins and their homologous multi-domain proteins were performed. The analyses suggest that tethering influences the structural, dynamic and energetic properties of constituent protein domains. Our observations hint at regulation of protein domains by tethered domains in multi-domain systems, which may manifest at the differential function observed between single-domain and homologous multi-domain proteins. A large proportion of proteins, coded in the genomes of diverse organisms, is constituted of more than one domain , 2. MultOften domains in multi-domain proteins interact with one another. The role of domain-domain interfaces has been implicated in long-range allostery regulation –12, the a) tethered to other protein domains and (b) tethered to fewer protein domains than (a) or not tethered to any protein domain were studied. For example, full-length rat DNA polymerase β consists of three domains . Crystal structures are available for full-length protein (PDB id: 1BPD) and the two C-terminal domains (PDB id: 1RPL) . For the study, we have compared the properties of the second and third domains in the two crystal forms. This comparison allowed us to study the influence of the first domain on the second as well as the third domains. Further comparative dynamics analyses of homologous protein domains were carried out to understand the functional relevance of tethering of domains. Analyses reveal an intricate coupling between the domains in multi-domain systems leading to alteration in dynamics in 18 protein pairs. Structural and energetics differences were observed in half the numbers of cases studied. Differential dynamics were observed for identical and structurally equivalent functional residues of the homologous protein domain pairs. Our observations strongly suggest that tethering of domains in multi-domain proteins changes the properties of constituent domains, thus regulating the function of the entire protein.For this, identical protein domains crystallized in two forms (a) tethered to other protein domains (henceforth referred as MD) and (b) tethered to fewer protein domains than (a) or not tethered to any protein domain (henceforth referred as ID). Distributions of RMSD and GDT values for the 20 protein domain pairs are shown in Fig 2A. To delineate the differences arising due to differences in crystal packing, RMSD and GDT distributions of the protein domain pairs were compared with the control dataset 1. The control dataset 1 consists of pairs of identical monomeric proteins. Distributions of structural deviation of the protein domain pairs and control dataset 1 were observed to be significantly different , p-value: 8.14e-06 (100-GDT), Fig 2B and 2C). This suggests that structural deviations observed in the protein domain pairs are likely to be due to tethering of domains and not due to crystallization artefact. The upper quartile limits of RMSD (RMSD > 1Å) and GDT (100-GDT > 5) distributions of the control dataset 1 were taken as a cut-off to identify the protein domain pairs with significantly different conformations. RMSD and GDT distributions of the protein domain pairs suggest subtle changes in global conformation of the common protein domains for 10 cases (100-GDT ≤ 5) while 10 cases show substantial changes in the conformation (100-GDT > 5) .Differences in the conformation of domains were observed in comparative structural analyses of identical protein domain pairs crystallized in two forms . Further analysis of the regions with significant structural deviation shows ~14% of such regions harbors functional residues while ~24% harbors domain-domain interface residues. Functional significance of ~62% of the residues cannot be commented upon . It has to be noted that structural deviations were observed independently of the number of domain-domain interface residues. For example, despite no interaction between the domains in fibronectin, structural deviations are observed . The observations suggest that tethering of domains can alter the conformation of the constituent domains, with many residues apart from domain-domain interface residues showing significant structural deviation.Since GDT and RMSD give an estimation of structural deviation over the entire length of a protein domain, significant structural deviations at local short stretches can be missed out. All the protein domain pairs were analyzed to identify stretches of residues showing significant structural deviation . Four categories of pairs were observed: (i) only domain-domain interface showed significant structural deviation, (ii) regions other than the domain-domain interface showed structural deviation but no structural deviations were observed at the domain-domain interface, (iii) structural deviations were observed both at domain-domain interface and regions other than the domain-domain interface and, (iv) no significant structural deviation was observed between the protein domain pairs. Representative examples of the 4 case types are shown in et al. have shown that network property, namely residue centrality of hemoglobin and NtrC differ between the inactive and the active state of the proteins [Fig 3A). Interface residues also show differences in the coc score between MD and ID  . Since interface residues form intensive contacts at the domain-domain interface in MD, we expected the coc scores to be lower for interface residues in ID than MD, but ~ 30% of the residues show higher coc in ID than MD . This observation suggests that rewiring of intra-domain residue-residue contacts of interface residues results on tethering of domains. Distribution of coc scores of non-interface residues is also observed to be different between MD and ID  , implying that on tethering of domains in a multi-domain system, many residues which are not part of interface region also undergo changes in the residue-residue contacts. The functional residues did not show a significant difference in the coc distribution . It has to noted that ~7% (291 residues out of 4284 residues) of residues show significant differences in centrality score –centrality score (ID)| > 1.5) . These 291 residues belong to 12 domain pairs in the dataset. Only ~3% of these 291 residues form a part of domain-domain interface regions. Many residues showing a significant difference in coc score –centrality score (ID)| > 1.5) showed low structural deviation  implying that rewiring of the residue-residue contact can happen without any significant structural deviation. An example of the coc distribution of a domain pair (fibronectin) is shown in Fig 3D. Fibronectin domain shows differences in centrality score both at the domain-domain interface residues  as well as residues other than domain-domain interface residues .Previous analyses by del Sol proteins . Residue two-sample KS test, p-value < 2.2e-16). To ensure that the differences are not an artefact of crystal packing, flexibility profiles of ID and MD were compared with two control datasets namely control dataset 2 and control dataset 3 respectively. The control dataset 2 was generated by in silico removal of the tethered domains from MD. The domains in the control dataset 2 (referred to as AD) are essentially identical to ID in sequence as well as length. The flexibility profiles of ID and AD were observed to be similar . The control dataset 3 was generated by in silico ligation of the ID with the tethered domain of MD. This was achieved by superimposing the ID onto MD, followed by in silico removal of the common domain from MD and then ligation of the remaining domains of MD with ID. The multi-domains in the control dataset 3 (referred to as swapped domain) are essentially identical to MD in sequence and length. The flexibility profiles of MD and swapped domains were also observed to be similar . The similarity of the flexibility profiles of the protein domain pairs and the control datasets ensured that the differences observed in the flexibility profiles of MD and ID are a consequence of the tethering of the domains in multi-domain systems than a crystallization artefact.Normal mode analysis was used to study the extent of influence of tethering on the dynamics of the constituent domains. Normal modes, accounting for 80% variance of the protein motion, were calculated for each MD and ID of the 20 protein domain pairs. To compare the flexibility of MD and ID normalized summed square fluctuation values were compared. The flexibility profiles were observed to be statistically different for all the domain pairs, except two . ~32% of the residues show higher flexibility in ID than in MD, while ~22% of the residues have higher flexibility in MD than in ID. The rest of the residues have comparable flexibilities. Higher variance in the distribution of flexibility of residues is observed for MD than ID . The higher variance of the flexibility of residues in MD implies that many residues in MD show higher/lower flexibility than the mean flexibilty. To ascertain further, how the flexibility profiles of interface residues and functional residues differ in MD and ID, the flexibility distribution of the interface residues and functional residues were compared. The interface residues generally show higher flexibility in ID than MD . A majority of interface residues (~70%) have higher flexibility in ID than in MD. But interestingly, ~30% of interface residues have comparable flexibility in MD and ID. Thus, some of the interface residues retain their rigidity in the isolated state as well. ~36% of the functional residues have higher flexibility in ID than MD while ~18% have higher flexibility in MD than ID . Hence many functional residues are rigid in MD than ID. Many residues which are neither part of interface nor functional residues show differences in the flexibility profile . To ascertain whether the residues showing differences in fluctuation in MD and ID show structural deviation as well, we calculated the correlation between the two. A poor correlation  was observed between the differences in fluctuation and structural deviation, suggesting tethering of domains can alter the dynamic properties of protein domain without significant structural conformation change.The flexibility of the residues was observed to be different in MD and ID . This observation implies that residues show tight coupling (|cross-correlation| ≥ 0.7) in the case of MD but no or weak coupling in the ID (|cross-correlation| < 0.7). Moreover, clusters of high correlation were observed in the case of MD; which often corresponded to sub-domains or domains or super-secondary structures in the spatial coordinate. The matrices of MD and ID were observed to have a low similarity (low Rv coefficient) for all the domain pairs except two . A representative example (fibronectin) is shown in Fig 5C and cross-correlation matrices for 20 protein domain pairs are shown in S4 Fig. To ensure that differences are not observed due to crystal packing or other artefact, Rv coefficient between cross-correlation of ID and control dataset 2 and cross-correlation between MD and control dataset 2 were calculated . The comparison ruled out any other factor apart from tethering for the behavior observed. An important point to note here is that this characteristic has been observed irrespective of the number of interactions between the domains. For example, the domains in rat DNA polymerase β do not interact with each other but still, low Rv coefficient is observed .Residue-residue communication in protein domains is important for the function and structural integrity of proteins. Residues can relay information to other residues either by forming contacts or through synchronization of dynamics. To understand the influence of tethered domain on the synchronization of dynamics of residues in protein domain, the extent of correlation of fluctuation among residues (henceforth referred as cross-correlation) was studied. Higher number of residues with high cross-correlation value (|cross-correlation| ≥ 0.7) was observed for MD (~22%) as compared to ID (~10%) . While weak or no coupling was observed for side-chains of residues in ID. Thus, molecular dynamics analysis for 3 pairs showed that higher cross-correlation between residues in MD is manifested not only at the backbone level, as observed also from NMA, but also at the side-chain level. All the observations imply that tethering of domains in multi-domain proteins alters the flexibility as well as the synchronization of the fluctuations of residues of the constituent domains.Molecular dynamic studies were carried out for 3 domain pairs from the dataset to study the synchronization of motions in the domain at all-atom level. These 3 pairs of domains were selected based on the number of interfacial residues between the domains. Tight coupling of motions was observed not only between the C-alpha of residues but also between the side-chains of residues in MD  but ~12%  of the residues showed differences in the single residue level frustration (SRLF) with 5 residues  showing drastic substitution from high frustration to minimal frustration and vice-versa. These 12% residues are distributed over the entire domain dataset i.e. each domain pair have at least one residue showing different frustration indices. Residues apart from domain-domain interface residues and functional residues were also observed to differ in the frustration index . Moreover, differences in the frustration index of MD and ID were observed to be independent of the structural deviation observed. Equivalent numbers of substitutions were observed at structural deviation greater than 1Å and lower than or equal to 1Å . Similar trends as that of SRLF were observed for configurational frustration and mutational frustration  but a higher number of contacts showed differences in configurational frustration type as compared to mutational frustration type. Many residues which are neither domain-domain interface residues nor associated with function showed differences in the frustration type of contact . The differences suggest that when a protein domain tethers to another domain not only the stability of entire domain [The frustration indices were calculated for the 20 protein domain pairs. Though the distribution of SRLF of MD and ID were observed to be largely comparable  Fig A but ~12e domain  but the e domain –20.a) phosphoribosylanthranilate isomerase from E. coli (PDB id: 1PII) and Jonesia denitrificans (PDB id: 4WUI), (b) cyclophilin from Bos taurus (PDB id: 1IHG) and Homo sapiens (PDB id: 3ICH), (c) sialidase from Micromonospora viridifaciens (PDB id: 1EUT) and Homo sapiens (PDB id: 1SO7) and, (d) hexokinase-1 from Homo sapiens (PDB id: 1HKC) and Saccharomyces cerevisiae (PDB id: 3B8A) were studied. The four domain pairs have sequence identity in the range of 27–56% with RMSDs in the range of 1.3–2.2Å . Since the homologous proteins differ in their amino acid sequences, only the dynamic properties of the protein were compared. The dynamics of the proteins were studied using normal mode analysis. For the comparative analysis, in-silico multi-domain chimeras of the single-domain proteins were generated. This was achieved by superposing the single-domain protein on the multi-domain protein, followed by in-silico removal of the homologous domain from the multi-domain protein and ligation of the domains. This in-silico protein will henceforth be referred as a chimera. For the hexokinase-1 protein, since the two-functional domains show gene duplication, the chimera was generated by superposing the single-domain on both the domains of multi-domain. Thus the two halves of the chimera of hexokinase-1 are identical. The flexibility and the cross-correlation coefficient of the functional residues were compared between single-domain proteins, multi-domain proteins and the chimeras for understanding the influence of tethering of domains on the function of proteins. Only topologically equivalent and identical functional residues of the homologous domain pairs were compared to minimize the influence of nature of residues.To understand further the influence of tethering of domains on the function of proteins, a comparative analysis was performed for homologous domain pairs, where one member is a single-domain protein while the other member is a part of a multi-domain protein. Both the members are full-length gene products. Four pairs of proteins namely . Residues important for function or structural integrity are known to show lower flexibility [Fig 8). The flexibility of functional residues in the multi-domain protein and the chimera is observed to be similar  except in the case of sialidase. This observation implies that increase in the rigidity of functional residues is a consequence of tethering of domains in multi-domain proteins. The differences in the flexibility of the functional residues can contribute towards differences reported in the functions of homologous protein domains, which are discussed later. To further understand the alteration in the dynamic properties of the domain, cross-correlation of the functional residues were studied. High correlation of motions was observed among functional residues for multi-domain protein in comparison to single-domain proteins . The single-domain proteins showed weaker cross-correlation among residues for all the cases . The cross-correlation between functional residues was comparable between the multi-domain and chimera for all the cases, except hexokinase-1 . The observations suggest that alteration in the synchronization of motion is a consequence of tethering.Normalized square fluctuations of functional residues were compared between the single-domain and multi-domain proteins. The functional residues have lower flexibility  in both single-domain and multi-domain proteins . This differential dynamics can provide a rationale for the lower sensitivity towards cyclosporin of the multi-domain protein in comparison to single-domain protein. The closing movement of the functional residues in the single-domain protein can hold the ligand better than the observed motion of the residues in the multi-domain protein. The single-domain hexokinase-1 protein has higher Km (300 μM) [Fig 9D). Weaker correlation between residues in single-domain hexokinase-1 as compared to multi-domain hexokinase-1 can explain the different Km, despite identical binding protein. From these analyses, we argue that tethering of domains influences the function of the constituent domains.For cyclophilin, the multi-domain protein is known to be less sensitive to cyclosporin as compared to single-domain cyclophilin . Detaile(300 μM)  as compa(300 μM) . The gluS10A Fig). It has to be noted that while constructing the chimera of the yeast hexokinase-1, a stretch of 9 amino acids from the C-terminal of the first domain and a stretch of 9 amino acids from the N-terminal of the second domain were removed to relieve short contacts at the domain-domain interface region and linker region. To ensure that the differences are not observed due to this specific amino-acids deletions, the flexibility profile of the natural single-domain yeast hexokinase-1  was compared with the in-silico generated model of the yeast single-domain hexokinase-1 with 9 amino acids deleted from the N-terminal  and the in-silico generated model of the yeast single-domain hexokinase-1 with 9 amino acids deleted from the C-terminal . The flexibility profiles were observed to be identical , implying that the differences in the flexibility profile are only due to the tethering of domains and not due to deletion of the amino-acids. The observations suggest that the differences observed in the constituent domains of multi-domain protein depend on the order of the domain in the multi-domain proteins. The cross-correlation between the functional residues in the N-terminal and C-terminal domain also differs . A number of positively correlated motions were observed in the C-terminal domain than in N-terminal domain. 6 pairs of functional residues viz. 173–210, 173–211, 174–210, 173–211, 176–210 and 176–211 exhibit anti-correlation motion in the N-terminal domain while the same residue pairs exhibit positively correlated motion in the C-terminal domain. We hypothesize that the differences in the nature of correlation of the fluctuation of the functional residues in the N-terminal and C-terminal domain may have given rise to the differential functional activity of the two domains in human hexokinase-1 at the first duplication event during evolution. The C-terminal of the human hexokinase-1 is catalytically active while N-terminal is catalytically inactive.Chimera hexokinase-1 also exhibited an interesting feature. Though the structure and sequence of the two protein domains in the chimeric hexokinase-1 is identical, the domains exhibited different flexibility profile , it can be concluded that dynamic allosteric regulation of domains is an intrinsic property of multi-domain proteins. This observation reinforces reports by others in literature that allostery is an intrinsic property of globular protein and allosteric regulation is prevalent in many multi-domain proteins [To gain further insights on how tethering of domains influences the function of proteins, comparative dynamics analyses were carried out for 4 pairs of homologous domains, where a member in a pair is a multi-domain protein and the other member is a single-domain protein which is a homologue of one of the domains in the other protein in the pair. In each pair, only identical and structurally equivalent functional residues were analyzed. Functional residues were observed to be more rigid in all the multi-domain proteins than the single-domain proteins. This rigidity of functional residues is observed due to superseding of the low-frequency local motion of the single-domain protein by the low frequency global domain-domain motion in the multi-domain proteins. The low-frequency global domain motion alters the synchronization of residue-residue motion of functional residues in multi-domain proteins as compared to single-domain homologues. Differences in the catalytic activity reported for these homologous domain pairs can be a manifestation of these alteration in fluctuations. Combined with our observations on the identical domain pairs, it can be concluded that tethered domains in multi-domain proteins influence the function of domains by affecting the dynamics of the domains. Identical functional residues were observed to have different dynamics depending on the domain order, as exemplified by the chimera hexokinase-1 in our study. The N-terminal and the C-terminal domains of the chimera hexokinase are identical in sequence and conformation, but the flexibility and the synchronization between functional residues differ between the two domains. Similar observation was made by Kirubarkaran ny cases . These oproteins , 34–36. Table A and B in S1 Text), we believe that the effects depend on the presence of linker than the length of the linker. Role of linker residues in the allosteric communication between domains has been suggested by others as well in the literature [Alterations in the covalent structure of proteins such as post-translational modifications are known for causing changes in the conformation and/or nature of dynamics at the site of modification and around –40. For terature , 44–47. Table C in S1 Text) were obtained. The small number of entries in the dataset is the reflection of the rigorous quality checks we have employed and the relatively small number of multi-domain proteins in the PDB and SCOPe database (21% of the dataset). It is also important to note that the longer member in each pair need not be a full-length gene product. For all the analyses, various features of the common domains of each pair have been compared. Information on function-associated residues  was taken from the literature survey and UNIPROT [The dataset for the analyses was prepared using domain definition available in SCOPe 2.03 ver. . All the UNIPROT . Domain  UNIPROT . Domain-Table D in S1 Text).SCOPe 2.03 database was screened for protein entries solved using X-ray crystallography, having a single chain in both asymmetric and biological unit and not bound to any other macromolecule. Crystal structures of only full-length proteins were selected. The selected proteins were clustered using local alignment tool of CD-HIT  at 25% sControl dataset 1: All the protein domain entries in SCOPe 2.03 [OPe 2.03 , whose sOPe 2.03  and pairControl dataset 2: The control dataset 2 was generated by in-silico removal of the uncommon domain from MD of domains pairs. The length and sequence of the domains (referred as AD) are identical to ID. This dataset was generated to study the impact of crystal packing on dynamics of proteins.Control dataset 3: The control dataset 3 was generated by superimposing the ID onto MD followed by in-silico removal of the common domain from MD and ligation of the superimposed ID with the uncommon domain of MD. The length and sequence of the domains (referred as swapped domains) are identical to MD. This dataset was generated to study the impact of crystal packing on dynamics of proteins.Root Mean Square Deviation (RMSD) and Global Distance Test–Total Score (GDT-TS) [Proteins in the datasets were structurally aligned using TM-align . For the(GDT-TS)  score we(GDT-TS) , with a For studying structural variation at the local level, regions of residues that show significant structural deviation as compared to other regions of the structure were compared. For this, the distance between corresponding Cα atoms of the protein pairs after superimposing the structure onto each other was calculated. All the residues, whose distance between corresponding Cα(s) is more than twice the standard deviation from the mean of the distance distribution of all the residues, were identified as region showing significant structural deviation. For homologous protein domain pair, only RMSD has been calculated to quantify the structural differences.To capture differences, if any, in residue-residue communication within proteins; undirected and unweighted networks of protein structures were constructed. The network was constructed for repaired structures (refer following section on dynamics). Each node in the network represents Cα and each edge represents the interaction between the nodes provided the distance between Cα atoms is less than or equal to 5Å. Network property namely communicability centrality was calculated using NetworkX  module ov coefficient [v coefficient measures the closeness of a set of points represented as a matrix. It is a multivariate generalization of Pearson correlation coefficient.To study dynamics of domains, we have used two approaches namely normal mode analysis (NMA) and molecular dynamics. Crystal structures were energy minimized using GROMACS package  with confficient . Rv coefMolecular dynamics was performed to study the correlation of fluctuation at the all-atom level for 3 pairs. Molecular dynamics was performed using GROMACS package. The proteins were simulated using Charmm 27 force field  and SPC Associative Memory Hamiltonian with Water-mediated interaction energy function (AMW) [Energetics calculation was performed only for a dataset of identical protein domains. As the homologous protein domains differ in sequence identity, it is futile to compare their energetics. Frustratometer algorithm  was usedon (AMW) . Then thon (AMW) .Single Residue Level Frustration (SRLF).AMW is a coarse-grained energy function where the backbone is represented as Cα, O and the side chain is reduced to Cβ, the position of N and C is generated considering the ideal geometry of the peptide bond. AMW energy function consists of five non-local energy terms namely Lennard-Jones 6–12 potential, H-bond potential, compactness potential, burial potential and water-mediated interaction potential. A pair of amino acids is considered to form a contact if the inter Cα distance is less than or equal to 5Å. Each contact is perturbed either by mutating each interacting residue pair to every other amino acid pair but keeping all other interaction parameters same as the native structure. Then the effective energy of the native contact is compared with the decoys to access the energetic stability of the contact to mutation. So, it provides a qualitative measure of the energetic feasibility of mutation of such contacts. The frustration index calculated by this method is termed as mutational frustration index. Another way of perturbing the contacts is by displacing the location of each contact thus sampling the possible configurations which can be taken by the contacts during folding. The frustration index calculated in such a way is termed as configurational frustration index. Similar to contacts, each residue is perturbed to every other amino acid and other configurations to evaluate the stability of residue in the native structure to all these perturbation. The frustration index calculated by this method is termed as All the statistical analyses were performed using R package.S1 Fig(A) 9 pairs out of 20 protein domain pairs show structural deviations at regions other than domain-domain interface residues. Such regions are encircled in black while the domain-domain interface residues are represented in sticks. These deviations were observed irrespective of the number of domain-domain interface residues. (B) Cartoon representation of fibronectin (MD is colored in bright orange and ID is colored in blue). The domains in fibronectin are observed to be non-interacting.(TIF)Click here for additional data file.S2 Fig(A) Normalized coc distribution for the functional residues. The X-axis represents the coc of MD and the Y-axis represents the coc of ID. The solid line in the plot represents the unity line. (B) Scatter plot of the absolute difference of coc of MD and ID and the structural deviation between corresponding Cα. The solid line is drawn at the absolute difference of coc of 1.5. Values above 1.5 signify the significant difference between coc of MD and ID.(TIF)Click here for additional data file.S3 FigA) Distribution of normalized square fluctuations of ID and the control dataset 2 (AD). The two distributions are similar . (B) Distribution of normalized square fluctuations of MD and the control dataset 3 (Swapped domain). The two distributions are similar . (C) Scatter plot of the normalized square fluctuation of all the non-functional and non-interface residues, The X-axis represents the normalized square fluctuation for MD and the Y-axis represents the normalized square fluctuation for ID. The solid line in the plot represents the unity line. (D) Distribution of absolute difference in normalized square fluctuation and the structural deviation between corresponding Cα. Spearman correlation coefficient for the distribution is 0.25. The inset shows the expanded view of the dense region.((TIF)Click here for additional data file.S4 FigThe first and the third column represent the cross-correlation matrices for MD in domain pairs. The second and the fourth column represent the cross-correlation matrices for the corresponding ID of domain pairs. The residues have been observed to be tightly dynamically coupled in MD as compared to ID. The color bar represents the cross-correlation value. The X-axis and the Y-axis represent the residue number.(TIF)Click here for additional data file.S5 Figv coefficients have been plotted. Rv coefficients have been calculated for cross-correlation matrices of MD and the control dataset 2 (AD), cross-correlation matrices of MD and ID, and cross-correlation matrices of ID and the control dataset 2 (AD). The high Rv coefficient for ID and SD implies that the low Rv coefficients observe for MD and ID are not a manifestation of crystallization artefact.For all the domain pairs, three R(TIF)Click here for additional data file.S6 FigA) Selenocysteine elongation factor (B) Fibronectin (C) DNA repair and recombination protein radA protein. Cartoon representations of the domain pairs are shown on the extreme left, with common domain colored blue. The left side matrices represent the cross-correlation of the residues at C-alpha level and the right matrices represent the cross-correlation at the all-atom level. The first rows in  represent MD and the second rows in  represent ID. The color bars represent the cross-correlation value.For three domain pairs, molecular dynamic simulations were carried out for 400 ns. ((TIF)Click here for additional data file.S7 Fig(A) single residue level frustration (SRLF) (B) configurational frustration index and (C) mutational frustration index. The left panel represents functional residues, centre panel represents interface residues and the right panel represents non-interface and non-functional residues for all domain pairs. The X-axis represents the frustration index for MD and the Y-axis represents the frustration index for ID. Residues which are minimally frustrated (MF) in both MD and ID are represented as a green filled circle, residues which are neutrally frustrated (NF) in both MD and ID are represented as blue filled circle and residues which are highly frustrated (HF) in both MD and ID are represented as red filled circles. The residues showing the difference in the type of frustration between MD and ID are represented as a yellow filled circle. The dotted lines have been drawn to represent the cut-off used for the definition of frustration index .Scatter plot of the distribution of (TIF)Click here for additional data file.S8 FigA) phosphoribosylanthranilate isomerase, (B) cyclophilin, (C) sialidase and, (D) hexokinase-1. The X-axis represents the normalized square fluctuation for multi-domain protein (MD) and the Y-axis represents the normalized square fluctuation for chimera protein. The solid line in all the plots represents the unity line.Scatter plots for functional residues of ((TIF)Click here for additional data file.S9 FigIn the upper left panel and the upper right panel, the Cα residues are represented as blue spheres and the directionality and the magnitude of the first mode of motion for functional residues is represented by a red arrow. Longer the arrow higher is the magnitude of the motion. The upper centre panel represents the space-fill representation of the functional residues (cyclosporin binding pocket). The lower left and right panel represents the cross-correlation matrices for functional residues for multi-domain and the single-domain protein respectively. The pocket closing movement of the protein in single-domain protein is superseded by the global domain movement.(TIF)Click here for additional data file.S10 FigA) Distribution of normalized square fluctuation of the N-terminal (3b8a_art_N) and C-terminal (3b8a_art_C) of the chimeric hexokinase-1. Certain residues show differences in the flexibility between the two domains. (B) Distribution of normalized square fluctuation of the full-length yeast hexokinase-1 (3b8a), yeast hexokinase-1 with 9 residues removed from the N-terminal (3b8a_N) and yeast hexokinase-1 with 9 residues removed from the C-terminal (3b8a_C). The distributions are highly similar, suggesting that the amino-acids deletions do not affect the flexibility profile. (C) Cross-correlation plot of the functional residues of chimeric proteins. The numbering of the functional residues has been kept same for the N-terminal and the C-terminal domain. The solid line separates the X-axis and the Y-axis into the N-terminal and the C-terminal domain. The X-axis and the Y-axis represent the residue number of the functional residues.((TIF)Click here for additional data file.S1 TextTable A. SCOP fold annotations, number of interface residues, length of the linker, size of the domain and the nature of differences observed for the identical domain pair dataset. Table B. SCOP fold annotations, number of interface residues, length of the linker, size of the domain and the nature of differences observed for the homologous domain pair dataset. Table C. PDB codes and macromolecule name of pairs of same proteins used for the analysis with their respective resolution (Å). Table D. PDB codes of homologous domains pairs with their resolution (Å).(DOCX)Click here for additional data file.


RVX-208 is a recently reported inhibitor of bromo and extraterminal (BET) family proteins (including BRD2-4 and BRDT) with selectivity for the second bromodomain (BD2), currently in phase III clinical trials. Despite of its promising antitumor activity, due to the conserved folds of the first and second bromodomains (BD1 and BD2), the detailed selectivity mechanism of RVX-208 towards BD2 over BD1 is still unknown. To elucidate selective inhibition mechanism of RVX-208 to BD2, microsecond molecular dynamics simulations were performed in this study for BRD2-BD1, BRD2-BD2 and BRD4-BD1 with and without RVX-208, respectively. Binding free energy calculations show that there exists strongest interaction between RVX-208 and BRD2-BD2. Leu383 and Asn429 are two most important residues of BRD2-BD2 for binding to RVX-208. Structural network analysis reveals that RVX-208 can shorten the communication path of ZA and BC loops in BRD2-BD2 pocket, making pocket more suitable to accommodate RVX-208. Additionally, different behaviors of His433 (Asp160 in BRD2-BD1) and Val435 (Ile162 in BRD2-BD1) in BRD2-BD2 are key factors responsible for selective binding of RVX-208 to BRD2-BD2. The proposed selective inhibition mechanism of RVX-208 to BRD2-BD2 can be helpful for rational design of novel selective inhibitors of the second bromodomain of BET family proteins. Despite sequence diversity, all BRD modules share a conserved fold comprised by a four-helix bundle , linked by ZA and BC loops that contribute to substrate specificity3. Cocrystal structures with peptide substrates demonstrated that the acetylated lysine was recognized by a central hydrophobic cavity and anchored by hydrogen bonds to an asparagine residue present in most BRDs6. With acetylation motifs often found in macromolecular complexes implicated in DNA repair, chromatin remodeling and cell-cycle control9, the architecture of acetyl-lysine pockets of BRDs makes them attractive targets for the design of potent inhibitors14.Bromodomains (BRDs) are protein modulators that specifically recognize acetylated lysine-containing sequences as an “epigenetic reader”. To date, 61 different BRDs from 46 nuclear and cytoplasmic proteins were discovered and could be divided into eight families based on their sequence and structural similarity15 and NUT midline carcinoma16. Inhibiting the recognition interaction between bromodomain and acetyl-lysine by small molecules is considered as an effective approach to halt tumor development. Over the past decade, many diverse inhibitors of BET proteins have exhibited significant antitumor activity20 and five of them  have entered clinical trials. But the problem is that all the inhibitors reported to date were multi-target or multi-domain except for RVX-208. Structural analyses show that not only all four BET proteins but also two homologous bromodomains (BD1/2) of each protein are highly conserved1, and selective inhibition of either BD1 or BD2 can result in distinct transcriptional outcomes28. For instance, BD1-selective inhibition by olinone was shown to promote oligodendrocyte differentiation, but which did not occur upon inhibition of both domains27. The domain-specific inhibitors against BETs are highly needed to avoid adverse effects of prolonged pan-BET inhibition.The bromo and extraterminal  proteins, as transcriptional regulators, are closely associated with the occurring and development of cancers such as lung cancer50 of 510 nM for BD2 and 170-fold lower than that to BD121. As the first selective BRD-BD2 inhibitor, RVX-208 is currently undergoing phase III clinical trials for treating the cardiovascular disease, but the potential molecular mechanism of RVX-208 selectively inhibiting BD2 is still unclear. Although the development of computational methods especially molecular dynamics (MD) simulations makes the explanation of drug selectivity mechanism possible31, a crucial factor affecting result accuracy is the simulation timescale, as emphasized by Shaw et al.34. By the unbiased MD simulations, Hou et al.35 also revealed that structural characteristics provided by the microsecond timescale were distinct from that by nanosecond simulations. Therefore, in order to observe the dynamic characteristics of protein more reliable, long time simulation is greatly needed. Microsecond molecular dynamics simulations were performed in this study to investigate the binding modes of RVX-208 with bromodomain of BET proteins and to elucidate the selective inhibition mechanism of RVX-208 to the second bromodomain of bromo and extraterminal proteins.RVX-208 was a domain-selective inhibitor reported recently, with IC18. The calculated contact number of RVX-208 with hydrophobic residues of BD1 and BD2 of BRD2 almost keeps constant during the simulation  and three apo-BDs . The constructed complex of BRD2-BD1-RVX-208 and the structure of RVX-208 were shown in Fig. ion Fig. , left. Fion Fig. , right aion Fig.  of BRD2-ion Fig. . The valion Fig. . OverallGGB and ΔGPB in BRD2-BD2 system were lower than that in two BD1 systems (BRD2-BD1 and BRD4-BD1), suggesting stronger binding affinity of RVX-208 with BD2. The calculated binding free energies  between BDs and RVX-208 in three systems exhibit a consistent order with experimental results 21. Among the individual terms, van der Waals interaction (ΔEvdw) predominates the total energy, while the nonpolar solvation term (ΔGsol_np_PB) contributes marginally to inhibitor binding. The overall electrostatics, however, disfavors complex formation. These results confirm that ligand association with poorly solvated binding pocket is dominantly driven by van der Waals interactions36. Considering the minor ΔGsol_np_PB difference between BD1 and BD2 systems, from the perspective of energy, energetic origin of RVX-208 selective for BD2 is thus mainly from the higher ΔEvdw.Here, the binding free energy of BRD4-BD1 and RVX-208 was calculated. In Table 16. From Figs The total binding free energy was further decomposed into per-residue contribution of BD Fig. . The higZA and BC loops are two regions responsible for binding to RVX-208. However, they are not continuous in the sequence or structure, but distribute on both sides of RVX-208 in the space. To study how ZA and BC loops communicate in RVX-208-binding complex and how the communication affects RVX-208’s selectivity, two representative residues identified by energy decomposition, Leu110 (at ZA loop) and Asn156 (at BC loop), were used as terminal residues in the shortest path Fig. . Figure 38. The higher flexibility decreasing of ZA loop of BD2 relative to BD1 indicated that BD2 pocket might undergo conformational rearrangement due to the binding of RVX-208. Additionally, we used the betweenness to characterize the residue-residue relevance in protein topology network. Figure et al.39 have found that the selectivity of a drug is dominated by the induced-fit process during the drug binding. Based on the above analyses, it can be seen that RVX-208 may initially bind to BD1/2 by conformational selection mechanism and preferentially interact with the preorganized pocket residues. It may be then accompanied by RVX-208-induced stabilization of ZA and BC loops via an induced fit in BRD2-BD2 system, resulting in the highly connected bromodomain. In this context, the steric barrier for movement away from the RVX-208-bound state may increase, effectively locking BD2 into a specific stable conformation. Therefore, RVX-208 selectivity is likely to result from ligand-induced structural stabilization by an induced fit mechanism.We firstly aligned crystal structures of apo-BD1 with holo-BD1, and apo-BD2 with holo-BD2 Fig. . Herein,Evdw in Table 2) 2-OH moiety of RVX-208 could significantly affect its BD2 selectivity21. Hence, we expect that the sufficient contact of inhibitors to solvent at the above position is essential for its selectivity for BD2, and should be taken into much account in the design of selective inhibitors.Next, we compared the detailed interactions of RVX-208 with BD1 and BD2. The representative conformation of each complex was extracted from their equilibrated trajectory by clustering analysis  and Asp160 (His433 in BD2) in BRD2-BD1 system, both of which were distinguishable residues between BD1 and BD2 2-OH group and BD2, the replacement of this group by -OH or -H can dramatically reduce its selectivity, as reported previously21. In our study, compared to BRD2-BD1 system, -O(CH2) 2-OH of RVX-208 is more prone to point out to the solvent in BRD2-BD2 system. In addition, RVX-297, a compound found by Hansen et al.40, differs from RVX-208 only with the -O(CH2)2-OH replaced by -O(CH2)2-pyrrolidine. However, BD2-selectivity of the former increases by more than two times, further emphasizing the importance of hydrophilic groups in the structure of selective inhibitors. Thirdly, in the inhibitor structure, the functional group with large volume should not occur near Val435. The comparison analysis of Ile162 (BRD2-BD1) and Val435 (BRD2-BD2) shows that the large moiety may prevent inhibitor from entering into the bottom of BD2 pocket, thus disturbing the stable binding of protein and inhibitor. Finally, interactions between inhibitors and His433 need to be much considered. His433, a BD2-specific residue, has been reported to be closely related with RVX-208 preference for BD2 over BD140. Based on the above binding mode analysis, inhibitors should be designed close to His433 and the introduction of aromatic moiety facing the imidazole ring of His433 is highly recommended. The information gained from this study will provide valuable guidance for the identification and design of new inhibitors with improved binding properties and selectivity.Now, we have understood the molecular mechanism of selective inhibition of RVX-208 towards BD2. Then, several strategies for rational design of novel selective inhibitor of the second bromodomain were proposed. Firstly, the better shape complementarity and packing with BD2 are required for selective inhibitors. This derives from energy calculation result that van der Waals term is the dominant factor for RVX-208 selectivity. In particular, Asn429 (or Asn156), as the residue with largest contribution, can interact with RVX-208 by hydrophobic and H-bond interactions. Increasing the interactions between RVX-208 and Asn429 may shorten the shortest communication path between ZA and BC loops, and make BD2 pocket more compact. Furthermore, although the formed H-bonds of RVX-208 with Asn156 of BD1 and Asn429 of BD2 had minor difference, they were reported to be essential for the acetyl-lysine interaction of histones and involved in the binding to many other BET inhibitorsIn the present study, the long-time MD simulations were performed to study the inhibition and domain-selective mechanism of RVX-208 to BRD2-BD2 and BRD2-BD1. Results showed that the binding affinity between RVX-208 and BRD2-BD2 was strongest in three systems. Leu383 and Asn429 in BRD2-BD2 system (corresponding to Leu110 and Asn156 in BRD2-BD1 system) were the most key residues for binding to RVX-208. Compared to BRD2-BD1 system, RVX-208 can shorten the shortest communication path between ZA and BC loops of BD2, making pocket readjusted more suitable for RVX-208 binding. Val435 (Ile162 in BD1) and His433 (Asp160 in BD1), as the distinguishable residues of BD2 from BD1, play a key role for selective binding of RVX-208 to BD2. These results may help in fully understanding the selectivity mechanism for inhibition of BRD2-BD2 and -BD1, and guiding the future novel selective BD2 inhibitors.43. The high conservation of BD1s in BET family has been well known from previously studies14. However, to eliminate the influence brought by slight structural difference outside inhibitor pocket between BRD4 and BRD2, we also constructed complex structure of RVX-208 and BD1 of BRD2. Considering the fact that BD1 and BD2 are highly homologous and conservative in the binding site, structure-based alignment was used to guide the complex construction of RVX-208 and BD1 of BRD2. The protein in PDB 4MR4 (BRD4-BD1 and RVX-208) as a template, was aligned to target protein PDB 2YDW41 (BRD2-BD1 and GW841819X inhibitor). Then, the original GW841819X inhibitor was deleted, and RVX-208 extracted from template was merged into target protein. Three studied complexes were finally optimized by Prime and Protein Preparation Wizard in Schrodinger suite 201544. To compare conformational changes of BDs induced by RVX-208’s binding, three apo-BD1 or -BD2 (without RVX-208) were also modeled.Prior to simulation, we first need to obtain the complex structures of RVX-208 with BD1 and BD2. At present, crystal structures of RVX-208 in complex with BD1 of human BRD4 (PDB ID: 4MR4) and BD2 of human BRD2 (PDB ID: 4MR6) are both available from Protein Data Bank45. The AMBER ff14SB46 and general Amber force fields47 were used for protein and RVX-208, respectively. The inhibitor charges were assigned using restrained electrostatic potential partial charges. The atomic type/partial charge of RVX-208 were given in Table 48 at HF/6-31 G* level. To neutralize net charges of each system, chlorine atoms were added as counter ions. TIP3P water molecules were added into the system, and the solute was at least 12 Å away from the boundary of water box. The prepared systems were minimized, heated and equilibrated. Then, 1 μs production run was carried out without any restraint in NPT ensemble. Temperature was regulated with Langevin thermostat using the “ig = −1” option to randomly set the random number seeds at each restart, avoiding synchronization effects. All the bonds involving hydrogen were constrained by SHAKE algorithm, and particle mesh ewald method49 was used to calculate long-range electrostatic interactions.MD simulations were performed using GPU-accelerated PMEMD within AMBER1451 and molecular mechanics poisson boltzmann surface area (MM-PBSA)52 methods, integrated in AMBER14 package. Herein, a total of 1000 snapshots were extracted from the last equilibrated 200 ns trajectory with a time interval of 200 ps, and calculated:Gcomplex, GBD and GRVX-208 are free energies of BD-RVX-208 complex, BD and RVX-208, respectively. G was estimated from gas-phase energy Egas and solvation free energy Gsol. Egas contains an electrostatic term (Eele) and van der Waals term (Evdw). The solvation energy is further decomposed into polar (Gsol_polar) and nonpolar solvation energies (Gsol_np). The former was calculated by solving the generalized-born/poisson-voltzmann model. Dielectric constants for solute and solvent were set to 1 and 80, respectively. The latter was estimated by solvent accessible surface area (SASA) determined using a water probe radius of 1.4 Å. The surface tension constant γ was set to 0.0072 kcal/(mol·Å2)53. Entropic contributions (S) were estimated by NMODE module of AMBER14. Residue energy decomposition was also performed to identify the important contribution residues to the total binding free energy.The binding free energy of RVX-208 and BRD2/4-BD1 or BRD2-BD2 was analyzed by both molecular mechanics generalized born surface area (MM-GBSA)α atom of a residue is considered as a node, and a weighted edge is drawn if Cα-Cα distance between a pair of residues is within a threshold distance, Rc (~7 Å). In our study, structural network was constructed by NAPS  platform54, which integrated the analysis and interactive visualization of protein contact networks. The shortest path distance between two nodes is the minimum number of nodes traversed to reach from one node to another, and displays the path of long-range interaction in the protein56. The experimental study found that the residues in the shortest path could take part in the domain-domain communication and mediate signaling transfer57. Using Floyd-Warshall algorithm, two important residues, Leu110 from ZA loop and Asn156 from BC loop, were chosen as important residues to study the shortest communication path between these two loops. The betweenness of a node is defined as the number of shortest paths that pass through this node in the network, representing a global/local centrality of this node. MD simulations have elucidated the molecular determinant underlying ligand-induced modulation of conformational dynamics, showing that structural perturbations of high centrality sites by ligand binding may be coupled to conformational rearrangements of protein pocket or even long-range regulatory domain58. Here, the betweenness parameter was used to characterize residue connectivity of apo and holo-BRD protein, especially for ZA and BC loops, which reflects the structural rearrangement of pocket induced by RVX-208.The representative structures from clustering analysis with the last 200 ns trajectory were used to construct protein structural network. CSupplementary information


Pattern formation is one of the most fundamental yet puzzling phenomena in physics and biology. We propose that traveling front pinning into concave portions of the boundary of 3-dimensional domains can serve as a generic gradient-maintaining mechanism. Such a mechanism of domain polarization arises even for scalar bistable reaction-diffusion equations, and, depending on geometry, a number of stationary fronts may be formed leading to complex spatial patterns. The main advantage of the pinning mechanism, with respect to the Turing bifurcation, is that it allows for maintaining gradients in the specific regions of the domain. By linking the instant domain shape with the spatial pattern, the mechanism can be responsible for cellular polarization and differentiation. Pattern formation is a ubiquitous phenomenon in biology and is observed at different scales , 2. SpatThere are several mathematical theories proposing potential mechanisms of polarization and pattern formation . The mosD is the diffusion coefficient, with bistable source function f(u) supplemented by the non-flux boundary condition. In 1978, Casten and Holland showed that Ω is convex , thus the function r(z) defined by z > z1 plays only an auxiliary role.The two cylindrical domains considered in ut=0 = u− = −1 or ut=0 = u+ = 1 in appropriate subregions of the considered domains and allow the evolution to proceed, until the solution reaches its stationary state. All simulations for To obtain the non-uniform stationary solutions shown in S1 FileIn this zipped directory we provide COMSOL files to reproduce all results shown in Figs (ZIP)Click here for additional data file.