Dissecting the role of the different domains revealed that the Rbg1 TGS domain is essential for the recruitment of this factor in polysomes, supporting further the implication of these conserved factors in translation.Developmentally Regulated GTP-binding (DRG) proteins are highly conserved GTPases that associate with DRG Family Regulatory Proteins (DFRP). The resulting complexes have recently been shown to participate in eukaryotic translation. The structure of the Rbg1 GTPase, a yeast DRG protein, in complex with the C-terminal region of its DFRP partner, Tma46, was solved by X-ray diffraction. These data reveal that DRG proteins are multimodular factors with three additional domains, helix–turn–helix (HTH), S5D2L and TGS, packing against the GTPase platform. Surprisingly, the S5D2L domain is inserted in the middle of the GTPase sequence. In contrast, the region of Tma46 interacting with Rbg1 adopts an extended conformation typical of intrinsically unstructured proteins and contacts the GTPase and TGS domains. Functional analyses demonstrate that the various domains of Rbg1, as well as Tma46, modulate the GTPase activity of Rbg1 and contribute to the function of these proteins  Small G-proteins have been extensively characterized and found to act as important molecular switches through changes in conformation related to the presence and nature of the bound nucleotide . In particular, the conformational changes occurring as a result of GTP hydrolysis has been shown to transduce cellular signals to downstream effectors mainly through changes in switch I (G2) and II (G3) regions  as it was found associated to ribosome ,19. It ain vitro and in vivo with the oncogenic T-cell acute lymphoblastic leukemia  protein, a basic helix–loop–helix (bHLH) transcription factor involved in cell growth and differentiation  and human OLA1 of the YyaF/YchF subfamily (PDB ID 2OHF), the only structure available so far for a DRG subfamily member being the NMR solution structure of the C-terminal TGS of human Drg1 (PDB ID 2EKI). Our crystal structure revealed the presence of novel domains in Rbg1 and uncovered the mode of interaction of Rbg1 with Tma46. Based on this information, in vitro and in vivo assays allowed us to dissect the role of the Rbg1–Tma46 domains and interactions in GTPase function and polysome recruitment.To gain further insights into the function of Rbg1 and Tma46 and the mode of interaction of these two proteins, we decided to investigate the structure of this heterodimer. Only a few structures of GTPase of the OBG subfamily are currently known. This includes Plasmids were constructed using standard cloning strategies or by site-directed mutagenesis using the QuickChange strategy  with minor modifications to manufacturer’s instructions. For expression constructs, an iterative trial and error process starting from plasmids encoding His6-tagged complete Rbg1 and full-length Tma46 was used. Protein yields, subunit interaction and homogeneity were assessed by gel electrophoresis after purification on Ni–NTA. When necessary, mass spectrometry analyses, apparent fragment sizes and sequence comparisons were used in an attempt to define suitable domain borders. For protein production, expression plasmids were transformed into BL21-CodonPlus (DE3)-RIPL. In some instances, glycerol stocks of the transformed bacteria were stored at −80°C until use. Material obtained from plasmids encoding stable and well-expressed products were tested for crystallization. Yeast plasmids were constructed as described above and contained genes expressed under the control of their native promoters. All constructs were verified by sequencing.Supplementary Table S1 while oligonucleotides used to prepare these constructs are listed in Supplementary Table S2.All plasmids used in this study are listed in 205–345 selenomethionine-substituted protein was obtained by using the autoinduction method , 50 mM Tris pH 8.0]. After washing the column with 10 bed volumes of Buffer A, proteins were eluted with a gradient of imidazole (20–500 mM) using an ÄKTA Purifier . Protein containing fractions were pooled and concentrated at 4°C to a final volume of 1–2 ml using Amicon Ultra centrifugal filter devices. The concentrate was directly loaded onto a pre-equilibrated size exclusion column [Sephadex 200 or 75 (16/60 or 26/60) columns] at 4°C and the protein eluted in buffer S  at rates of ∼ 1.0 ml/min using an ÄKTA Prime system. Purified proteins were then pooled and concentrated to 20–60 mg/ml by ultrafiltration at 4°C using the Amicon concentrator before flash-freezing in liquid nitrogen and storing at −80°C. The purification protocol for the selenomethionine-substituted proteins was as above except that in the last step of the purification 5 mM concentration of DTT was included to prevent selenomethionine oxidation.Protein expression was induced by growth in autoinduction media [Formedium ] plus kan method ,29. Smaln method  except t205–345 complex were obtained by the vapor diffusion method. The drops were setup at 4°C with 1 μl of 60 mg/ml of protein and 1 μl of reservoir solution . Three dimensional rectangular crystals with typical dimensions 0.3 × 0.05 × 0.02 mm grew in about 2 weeks. The X-ray diffraction data for the native and selenomethionine derivative were collected from single crystals at the beam line ID14-4  and scaled with SCALA in the CCP4 suite . Heavy aThermal shift assays were performed using protein samples at ∼0.05 mM in buffer S with 5 × Sypro Orange (Sigma), with or without 0.2 mM GDP, GTP or 0.5 mM GTPγS in wells of MicroAmp 96-well Fast Optical Reaction plate (Applied Biosystems). Fluorescence was measured from 20°C to 85°C in increments of 1°C in a T7500 Fast Real-Time PCR system (Applied Biosystems). Results were analyzed using the GraphPad Prism 4 software (GraphPad Software Inc.).2) were incubated with GTP (Sigma Aldrich) for 1 h at 37°C in Microtest 96-well flat bottom plates (Sarstedt). An amount of 200 μl of Malachite green reagent was added in all wells and the absorbance readings at 630 nm were measured immediately in a Wallac Victor2 1420 Multilabel Counter. A phosphate standard prepared from KH2PO4 and blank with no protein were included on the plate. The latter background was subtracted from the protein sample readings. Data were fitted to Michaelis–Menten equation using non-linear regression in GraphPad Prism 4 to determine the kinetics.GTP hydrolysis assays using Malachite green  were perSupplementary Table S3. Strains containing a single disrupted and epitope-tagged gene were obtained by transformation with TAP-tag  of 0.1. Three microliters of these cultures and 10-fold serial dilutions were spotted onto agar plates containing complete synthetic media minus leucine. Plates were incubated at 37°C and 30°C for 3 or 4 days, and cell growth was determined by visual inspection and documented by photography.For growth assays, yeast cultures were grown to saturation in selective liquid media. The cultures were then diluted in water to an optical density at 600 nm  or IgG coupled to Dynabeads on a rotor at 4°C for 2 h. Beads were pelleted and washed extensively with IPP150 buffer . Proteins bound to the beads were eluted with SDS–PAGE sample buffer by boiling for 5 min.Logarithmically growing yeast cells in selective medium at 30°C were resuspended in lysis buffer containing 10 mM Tris–HCl pH 7.5, 150 mM NaCl, 5 mM MgClPolysomes were analyzed essentially as described previously .To obtain recombinant Rbg1 and Tma46, or truncated derivatives thereof, for structural and functional analyses, we constructed artificial operons encoding various versions of 6His-tagged Rbg1 followed by Tma46. Initially, full-length Rbg1 and Tma46 were used. The two proteins copurified indicating that no yeast-specific factor or compound was necessary to allow their interaction. However, low complex yields and truncated forms of Tma46 were observed. Mass spectrometry analyses and estimation of apparent molecular weights, together with sequence analyses delineating borders of conserved domains, provided rough estimates of the missing regions. After several iterative cycles of construct optimization, a plasmid expressing efficiently and without apparent degradation 6His-tagged full-length (fl) Rbg1 together with the C-terminal region of Tma46 (amino acids 205–345) encompassing the DFRP region was obtained.205–345 complex  includes two molecules of the complex in the asymmetric unit although the complex behaves as a heterodimer by size-exclusion chromatography. The asymmetric unit contains Rbg1 molecules A and B interacting with Tma46 molecules C and D, respectively; molecule AC is used hereafter for the structural description. The data collection and refinement statistics are as given in The X-ray crystal structure of proteins obtained with the latter construct was solved to 2.67 Å resolution by the SIRAS method using a selenomethionine-substituted protein. The final model of the Rbg1fl–Tma46The Rbg1 structure shows a domain organization that includes the well-conserved G-domain , an N-terminal helix–turn–helix (HTH) domain (1–44) which lies adjacent to another domain formed by a 65-residue long insertion (176–240) between G3 and G4 of the G-domain and the TGS domain at the C-terminus (294–369) .Figure The G-domain of Rbg1 is highly similar to the well-conserved GTP-binding domain of other GTPases, in particular proteins Obg, YchF, FeoB, HflX, Ras-related proteins or Era, which all belong to the TRAFAC class of GTPases. The G-domain contains five α-helices  and six β-strands . The G1 motif  is located on the loop connecting β1 to α3, G2 (Switch I) in between α3 and β2, G3  at the end of β3 strand, G4 in β10 and G5 motif in β11 . While tSupplementary Figure S1). The bacterial 30S ribosomal S5 subunit protein C-terminal domain is structurally the most similar to S5D2L domain, aligning with an RMSD of 2.2 Å over 51 residues although the sequence identity was very low (12%). Interestingly, the residues Gly and Arg of the S5 subunit protein known to cause ribosomal ambiguity when mutated , comprises a previously unnoticed HTH domain at the N-terminal of Rbg1. While the HTH and S5D2L structures form a single globular protuberance emanating from the G domain, we refer to them as independent domains, as sequence phylogeny and functional data (see below) indicate that they behave as separate entities. The HTH is stabilized mainly by a hydrophobic zipper between the two helices, five leucines positioned 3–4 residues apart in the longer helix α2 contributing to the zipper while the other side of the helix α2 makes both hydrophilic and hydrophobic interactions with the S5D2L helices α6 and α7. Additionally, the interface between α1 and α2 is also stabilized by hydrogen bonds between Glu12 (α1)–Arg39 (α2) and Glu14 (α1) and His27 (α2).The C-terminal TGS domain (294–369) has predominantly β sheet structure with five β strands (β12–β16) and two helices, α10 and α11 . SuperimThe HTH, S5D2L and TGS domains lie on the distal part of the GTP-binding pocket  and 2. E205–345 in the complex with Rbg1 that we could model into the electron density are located as mainly four helices  and a short β strand which forms β sheet structure with adjacent β strands β2, β3, β1, β4, β10 and β11 from the G-domain of Rbg1. Tma46 helices envelops Rbg1 forming an extended and extensive interface (buried surface area in the interface ∼2978 Å2) contacting the G-domain  and the TGS domain (helices α3 and α4) with no contacts with the S5D2L and HTH domains .One of the most prominent interacting surfaces between Rbg1 and Tma46 comprises α8 helix of Rbg1 (between G4 and G5 motifs), which inserts between helices α1 and α2 of Tma46 themselves interacting in turn also with Rbg1 α5 and α9 respectively. Helix α2 is longest in the fragment of Tma46 solved, and extends from the Rbg1 G-domain to the TGS domain that it contacts with its C-terminal end. Interestingly, the interface between Tma46 α2 and Rbg1 α8/α9 consists mainly of aromatic ring containing residues, which form a π-stacking interaction. Specifically, Tyr264 (α8) and Trp278 (α9) of Rbg1 form stacking interactions with Phe246, Trp249 and His253 of α2 of Tma46  with an alanine linker of sufficient length to bridge helices α1 and α3. We first tested whether these mutants were functional by assaying their ability to complement the triple mutant Δgir2Δtma46Δslh1 for its slow growth phenotype, a feature exacerbated at 37°C  was assessed by western blotting  to a detectable level, indicating that all mutants are able to interact with Rbg1, albeit with much reduced affinity. Overexpressed Δα3–ß now complemented efficiently the TMA46 deletion while the Δα2 construct complemented well independently of the vector used . In contrast, the Δα2–ß and Δα1–α2 mutants were unable to rescue the Tma46 function even when overexpressed . Overall, these data suggest that interaction of Tma46 with Rbg1 is important to provide activity, even though we cannot formerly exclude Rbg-independent function of Tma46. More importantly, these data demonstrate that interaction of Rbg1 with Tma46 is not sufficient to provide activity. These results demonstrate further that none of the Tma46 elements (helices α1–α4 and ß strand) is absolutely essential for interaction and function. The presence of superfluous elements, demonstrated by the lack of functional phenotype and effect on interaction of several mutants, may ensure an extremely tight binding. Elimination of individual elements had different impact either as a result of different effect on affinity or because they contribute to additional function(s) beside interaction. The simultaneous removal of several elements always had stronger effect than removing individually these elements supporting the idea that they contribute in an additive manner to Rbg1 binding. Interestingly, increasing protein expression of interaction defective mutant was sufficient to restore Rbg1 binding suggesting that complex formation is controlled by the concentration of the two partners. However, even in such context, the larger deletions (Δα2–ß or Δα1–α2) were unable to complement a Tma46 deletion. This indicates that Tma46 is not simply sticking to Rbg1 but participates actively in the complex function, possibly by strengthening the contacts between the G and TGS domains of Rbg1 and/or by directly impacting on Rbg1 GTPase activity.We next assessed whether these mutations of Tma46 affect interaction with Rbg1 blotting C and D. in vitro without the help of GAPs or GEFs, unlike Ras-like proteins  was used. No increase in the unfolding temperature of this mutant protein was seen in the presence of nucleotide. Since this mutation was designed to abrogate nucleotide binding, this observation confirms that the shift in Tm observed for the wild-type Rbg1fl–Tma46205–345 complex is indeed due to the protein–nucleotide complex formation.DRG proteins have been shown to bind GTP and GDP ,48. Moreproteins . To inveproteins A. Nucleo205–345 complex shows a weak GTP hydrolysis activity . Consistent with the analysis of the Δα2 deletion, these mutants interacted with Rbg1 as well as wild-type Tma46 . Thus, we conclude that specific contacts between Tma46 and Rbg1 are important to stimulate the GTPase activity of the latter in vitro and impact on Rbg1–Tma46 function in vivo.We next analyzed the GTP hydrolytic activity of free-, and Tma46-bound-, Rbg1. The Rbg1fl–Tma46activity , with paactivity ,50 and aactivity . A catal in vivo  did not  in vivo B confirm complex . For com complex . The inc complex . FurtherRBG1 gene inserted in a yeast vector. As deletion of the S5D2L removes an internal part of the protein, two mutants were built incorporating one or two glycine residues at the deletion point to allow sufficient flexibility and length of the polypeptide backbone to allow folding.The structure of the Rbg1–Tma46 heterodimer indicates that Rbg1 comprises four domains. The GTPase domain is the largest of them forming a platform surrounded by protuberances corresponding to the HTH, S5D2L and TGS domains. Previous analyses indicated that the GTPase and TGS domains of Rbg1 were essential for its function . HoweverΔrbg1Δrbg2Δslh1 strain  or a form of Rbg1 lacking the S5D2L still interacted with Tma46. In contrast, deletion of the TGS prevented Tma46–Rbg1 interaction . Interestingly, the TGS domain by itself was sufficient to interact with Tma46. Unfortunately, the effect of deleting the HTH domain could not be addressed in this assay because the corresponding protein was poorly expressed in E. coli.We next analyzed the roles of the different Rbg1 domains in mediating interaction with Tma46. Plasmids encoding full-length or truncated versions of Rbg1 together with regions encompassing the C-terminus of Tma46 (residues 154–345 or 205–345) were constructed. After expression in staining C. This ain vivo, we introduced the shuttle plasmids encoding HA-tagged truncated versions of Rbg1 in a yeast Δrbg1 strain expressing Tma46–TAP. Coprecipitation of the two proteins was assayed as described above . All mutants displayed a significant GTP hydrolytic activity albeit with reduced rate compared to the wild-type protein .E. coli ribosome and is, interestingly, the target of mutations affecting translational fidelity ; Ministerio de Ciencia e Innovación ; Conselleria de Sanitat, Generalitat Valenciana [AP-001/10 and ACOMP/2012/039 to J.B.]; CSIC [200820I020 to J.B.]; European Union 6th Framework programs 3D Repertoire [contract LSHG-CT-2005-512028 to J.B. and B.S.]; CERBM-IGBMC (to B.S.); CNRS (to B.S.); Ligue Contre le Cancer [Equipe Labellisée 2011 to B.S.]. Funding for open access charge: CERBM GIE.Postdoctoral fellowship from the Conflict of interest statement. None declared.


To understand the molecular basis of higher potency and selectivity of these inhibitors, here, we present molecular dynamics simulation results of CDK5/p25 and CDK2/CyclinE complexed with a series of cyclobutyl-substituted imidazole inhibitors and roscovitine. The atomic details of the stereospecificity and selectivity of these inhibitors are obtained from energetics and binding characteristics to the CDK binding pocket. The study not only complements the experimental findings, but also provides a wealth of detailed information that could help the structure-based drug designing processes.Cyclin-dependent kinases (CDKs) belong to the CMGC subfamily of protein kinases and play crucial roles in eukaryotic cell division cycle. At least seven different CDKs have been reported to be implicated in the cell cycle regulation in vertebrates. These CDKs are highly homologous and contain a conserved catalytic core. This makes the design of inhibitors specific for a particular CDK difficult. There is, however, growing need for CDK5 specific inhibitors to treat various neurodegenerative diseases. Recently, cis-substituted cyclobutyl-4-aminoimidazole inhibitors have been identified as potent CDK5 inhibitors that gave up to 30-fold selectivity over CDK2. Available IC CDK5 do not follow this mode of activation. The activity of CDK5 is restricted to nervous system by the localization of its activators p25/p35/p39, the binding of which makes CDK5 fully active without the subsequent requirement of phosphorylation of the activation loop residue Cyclin-dependent kinases (CDKs) play crucial roles in eukaryotic cell division cycle. They belong to the CMGC subfamily of protein kinases and assist the γ-phosphate transfer from ATP to peptide substrates CDKs are highly homologous and contain a conserved catalytic core. For example, CDK2 and CDK5 share a sequence homology of 60%, with the substrate binding pocket alone showing nearly 93% sequence similarity Due to their key regulatory roles, CDKs have become important pharmaceutical targets for inhibitor design In vivo and in vitro studies have shown distinctly different inhibitory effects of these molecules on CDK2 and CDK5 50 values of these inhibitors.The initial structures of inhibitor-bound CDK2/Cyclin E and CDK5/p25 complexes were obtained by docking the inhibitors in the available crystal structures of active CDK2 (PDB ID: 1W98) and CDK5 (PDB ID: 3O0G) via fits to the electrostatic potentials obtained from the calculated wave functions. The missing interaction parameters in the inhibitors were generated using antechamber tools in Amber As the kinase inhibition assay was performed in active complexes, the CDK-inhibitor interactions were examined in presence of the activators, cyclin E and p25 for CDK2 and CDK5, respectively. For this purpose, the crystal structure coordinates of cis-OH and cis-N-acetyl were extracted from their bound complex with CDK2  of the inhibitors were calculated by Molecular Mechanics Poisson Boltzmann Surface Area (MMPBSA) approach i.e. last 10 ns trajectory). The binding free energy of an inhibitor is obtained by taking the difference between the free energies of the protein-inhibitor complex (Gcomplex), the unbound protein (Greceptor), and the inhibitor (Gligand):Binding free energies , entropic contribution, and solvation free energy due to the binding of ligand to receptor for the formation of complex:The ΔGMM) takes care of the electrostatic and van der Waal’s interactions between protein and ligand. The ΔGsolv is estimated by solving the linearised Poisson Boltzman equation for each of the three states (ΔGpolar) and adding an empirical term for hydrophobic contributions to it (ΔGnonpolar). The hydrophobic contribution is calculated from the solvent accessible surface area. It is customary to neglect the entropic contribution (TΔS), as the calculations involve binding of similar type of ligands to the receptor. Hence, the computed values will be termed as the relative binding free energies. The experimental free energy of binding values (ΔGexpt) was determined from the IC50 values by using the equation: ΔG = −RTlnIC50.The MM gas phase energy term  of the inhibitor-bound CDK complexes from the starting structures. The convergence of RMSD values at approximately 5 ns of the simulation time indicates that the systems were well equilibrated and have attained stability . InteresThe analyses of local fluctuations of the CDK residues also suggest a stronger protein-inhibitor interaction in cis-OH, as exemplified by the lower B-factor values of the functionally relevant loops and helices . For exaTo obtain a better understanding of the interactions, we compared the average structures of the cis- and trans-OH bound CDK2 and CDK5 complexes. This is shown in The binding of inhibitors to CDKs was further amplified by calculating their average interaction energies over the final 10 ns simulation trajectory. The total interaction energy of cis-OH was found to be much greater than trans-OH in both CDK2 and CDK5 complexes . Individvia MMPBSA method. binding are in very good agreement with experimental data To get a quantitative comparison of the binding strengths, we computed the free energy of binding of the inhibitors to CDK2 and CDK5 from the simulation-generated trajectories in vitro . To understand these differences, we carried out comparative studies of cis-OH and cis-N-acetyl bound active CDK2 and CDK5 complexes. The N-acetyl bound CDK complexes were simulated for 50 ns and the stability were assured from the convergence of energy components and RMSDs from the crystal structures (data not shown). The comparison of local fluctuation of the protein residues implies a stronger protein-inhibitor interaction in cis-N-acetyl bound CDKs, particularly in CDK5 complex  of the pocket  and mappTo check if the other two CDK2 variants contribute to pocket volume, even though they reside exterior to the binding pocket, we created the mutants, CDK2:L83C and CDK2:H84D. These complexes were also simulated for 50 ns after equilibration. The computed volumes and electrostatic potential map of these mutants are also included in The binding of N-acetyl inhibitor to CDKs is also compared with the binding of commercially available CDK inhibitor, roscovitine The calculation of residue-level interaction energies reflects a similar trend . Even thCis-substituted cyclobutyl-4-aminoimidazole inhibitors have been identified as novel CDK5 inhibitors that gave improved enzyme and cellular potency with many fold selectivity over CDK2. The molecular basis of higher potency and selectivity of this class of inhibitors over commercially available drugs is also unknown. Here we present atomic-level details of the interactions of some of these CDK-inhibitor complexes to understand these differences. Results suggest that the aminoimidazole inhibitors can reach deep into the substrate-binding pocket through the linker cyclobutyl group. Moreover, they involve in strong electrostatic interactions with CDK residues Lys33, Asp145/Asn144 that reside at the base of the cavity. The better selectivity of these inhibitors for CDK5 mainly stems from the variant residues Cys83, Asp84, Asn144, which modulate the interaction network by subtly restructuring the binding pocket and realigning the allosteric residues, Lys33, Lys89. This turns the CDK5 pocket more electropositive and smaller in volume for more favourable interactions with molecules carrying multiple electronegative sites.The results are validated by comparing the computed free energy of binding of the imidazole inhibitors to CDKs with the available experimental values. Moreover, the mode of binding of the commercially available drug, roscovitine to CDKs in the simulated complexes is also compared to the available crystal structure. An excellent match has been observed in both instances, which tempted us to conclude that the future strategy for designing more potent and specific CDK inhibitors could involve the incorporation of polar functional groups at the tip of the inhibitor molecules, which can go deep into the binding pocket through a hydrophobic linker.Figure S1α root mean squared deviations (RMSD) of CDKs bound to cis- and trans-OH inhibitors. Time evolution is shown for final 35 ns for cis-OH-CDK2 (black), trans-OH-CDK2 (red), cis-OH-CDK5 (green), and trans-OH-CDK5 (blue) complexes.The C(TIF)Click here for additional data file.Figure S2RMSDs of the inhibitors bound to CDKs. Black: cis-OH bound to CDK2, red: trans-OH bound to CDK2, green: cis-OH bound to CDK5, blue: trans-OH bound to CDK5.(TIF)Click here for additional data file.Figure S3The time evolution of the salt-bridge between Asp145/Asn144 and Lys33 in CDKs. Results are shown for the distances (A) between carboxyl group of Asp145 and the side chain amino group of Lys33 in CDK2 and (B) between amide group of Asn144 and the side chain amino group of Lys33 in CDK5. Color scheme: Red for cis-OH bound and black for trans-OH bound CDK complex. See (TIF)Click here for additional data file.Figure S4Time evolution of the interaction of cis−/trans-OH inhibitor with (A) Asp145 in CDK2 and (B) Asn144 in CDK5. Interactions are shown in terms of the distance between the hydroxyl group of the inhibitors and the backbone NH of Asp145/Asn144. Color scheme is similar to (TIF)Click here for additional data file.Figure S5Time evolution of the interaction of cis- and trans-OH inhibitors with Lys33 in CDK5. Interactions are shown in terms of the distance between the hydroxyl group of the inhibitors and the side chain N of Lys33. Color scheme is similar to (TIF)Click here for additional data file.Figure S6Comparison of local fluctuations of (A) CDK2 and (B) CDK5 residues bound to cis-OH (black) and cis-N-acetyl (red) inhibitors.(TIF)Click here for additional data file.Figure S7Comparison of local fluctuations of CDK2 (black) and CDK5 (red) residues bound to cis-N-acetyl inhibitor.(TIF)Click here for additional data file.Figure S8Time evolution of the interaction of cis-OH (black) and cis-N-acetyl (red) inhibitors with Lys33 in CDK5. Interactions are shown in terms of the distances between the side chain N of Lys33 and hydroxyl group of cis-OH and nitrogen of N-acetyl, respectively. See (TIF)Click here for additional data file.Figure S9Orientations of residues around N-acetyl inhibitor in (A) CDK2 (B) CDK5 (C) CDK2:L83C variant, and (D) CDK2:H84D variant. Figure clearly shows the intrusion of residue K89 into the CDK5 binding pocket in panel (B). A similar change of orientation of K89 is also seen in the variant CDK2:H84D (panel D). Color scheme is similar to (TIF)Click here for additional data file.Figure S10Time evolution of the interaction of cis-OH (black) and cis-N-acetyl (red) inhibitors with (A) Asp145 and (B) Lys33 in CDK2. Interactions are shown in terms of the distance between the hydroxyl group of cis-OH and nitrogen of N-acetyl with the backbone NH of Asp145 and the side chain N of Lys33, respectively. See (TIF)Click here for additional data file.Figure S11Time evolution of the solvent accessible surface area of the binding pocket of CDK2 (black), CDK5 (red), CDK2:L83C mutant (green), and CDK2:H84D mutant (blue).(TIF)Click here for additional data file.Figure S12Time evolution of the interaction of roscovitine (black) and cis-N-acetyl (red) inhibitor with Lys33 in (A) CDK2 and (B) CDK5. Interactions are shown in terms of the distances between the side chain N of Lys33 and closest roscovitine atom and nitrogen of N-acetyl, respectively.(TIF)Click here for additional data file.Table S1List of systems studied.(DOC)Click here for additional data file.Table S2Average distance and energy between cyclobutyl ring of inhibitor and phenyl ring of CDK:Phe80. For distance calculations, centre of masses are considered.(DOC)Click here for additional data file.File S1Full reference 27.(DOC)Click here for additional data file.


A distinct structural feature, where structural segments in a protein dimer or higher oligomer were shared between two or more chains of a protein structure, characterizes 3D domain swapping. 3D domain swapping was observed as a key mediator of numerous functional mechanisms and play pathogenic role in various diseases including conformational diseases like amyloidosis, Alzheimer's disease, Parkinson's disease and prion diseases. We report the first study with a focus on identifying functional classes, pathways and diseases mediated by 3D domain swapping in the human proteome.P-value < 0.05).We used a panel of four enrichment tools with two different ontologies and two annotations database to derive biological and clinical relevant information associated with 3D domain swapping. Protein domain enrichment analysis followed by Gene Ontology (GO) term enrichment analysis revealed the functional repertoire of proteins involved in swapping. Pathway analysis using KEGG annotations revealed diverse pathway associations of human proteins involved in 3D domain swapping. Disease Ontology was used to find statistically significant associations with proteins in swapped conformation and various disease categories (We report meta-analysis results of a literature-curated dataset of human gene products involved in 3D domain swapping and discuss new insights about the functional repertoire, pathway associations and disease implications of proteins involved in 3D domain swapping.Our integrated bioinformatics pipeline comprising of four different enrichment tools, two ontologies and two annotations revealed new insights into the functional and disease correlations with 3D domain swapping. GO term enrichment were used to infer terms associated with three different GO categories. Protein domain enrichment was used to identify conserved domains enriched in swapped proteins. Pathway enrichment analysis using KEGG annotations revealed that proteins with swapped conformations are present in all six classes of KEGG BRITE hierarchy and significantly enriched KEGG pathways were observed in five classes. Five major classes of disease were found to be associated with 3D domain swapping using functional disease ontology based enrichment analysis. Five classes of human diseases: cancer, diseases of the respiratory or pulmonary system, degenerative diseases of the central nervous system, vascular disease and encephalitis were found to be significant. In conclusion, our study shows that bioinformatics based analytical approaches using curated data can enhance the understanding of functional and disease implications of 3D domain swapping. We used complete set of human proteins from 3DSwap database and examined statistically significant domains, biological process, cellular component, molecular function, biological pathways and diseases using enrichment methods. From a bioinformatics perspective, this manuscript is a case study that leverage application of robust bioinformatics methods to gain new functional and therapeutic insights from a protein structural mechanism.Computationally efficient classification, annotation and prediction algorithms are rapidly improving our understanding of protein sequence-structure-function relationships. Analysis of such relationships often helps in our understanding of novel sequence or structural features in the regulation of a particular function including molecular pathways and various disease mechanisms. Cells attain its functional integrity with the help of molecular mechanisms including protein-protein interactions -7. Prote3D domain swapping is a unique protein structural phenomenon with implications in function, form and disease Figure . Only twIrrespective of numerous biochemical and computational studies focused on the molecular basis of 3D domain swapping ,34-52, aP-value was calculated. In SEA-based approach, annotation terms of subset of genes were assessed one at a time against a list of background genes. An enrichment p-value was calculated by comparing the observed frequency of an annotation term with the frequency expected by chance and individual terms beyond the p-value cut-off . BiNGO [2 χtests [Enrichment analysis plays an important role in knowledge-based bioinformatics approaches ,55. In t). BiNGO , FunctAs). BiNGO , Onto-ex). BiNGO ,67 are e). BiNGO  and topG). BiNGO  employ t). BiNGO . For exa). BiNGO . A varie). BiNGO ,72, hype). BiNGO , binomiaχ2 tests  or combiχ2 tests  and Ontoχ2 tests ,67 for sχ2 tests ,76.Gene ontology enrichment and pathway enrichment analysis, using ontologies or annotations derived from a subset of genes characterized from an experimental or computational study, generally applied to infer new biological insights, which was otherwise impossible with candidate gene-centric approaches. Due to the generic nature of statistical methods used in enrichment analysis, current set of enrichment algorithms and related statistical methods can be used to infer enrichment from annotation databases. Enrichment calculations are currently available for various types of annotations. Annotations of protein domains , pathwtools, two ontologies and two annotation databases for inferring functional and disease insights from list of human proteins involved in 3D domain swapping. Protein domain enrichment was performed using DAVID 6.7. Protein domain annotations were derived from Pfam database, a database of evolutionarily conserved protein domain coordinates. Ontologizer 2.0, a GO term enrichment tool with command-line interface and improved statistical method for deriving GO terms enriched in a given list of proteins was used in this study. SubPathwayMiner, an R package that internally handles KEGG annotations for pathway enrichment analysis were used to derive statistically significant pathways associated with the dataset. Enriched disease ontology terms were identified using Functional Disease Ontology server that consults Disease Ontology and it's derivative disease-ontology lite for identifying significant diseases. 0 H= List of curated proteins with swapped conformations are not associated with any class of protein domains, gene ontology terms, KEGG pathways or disease ontology terms. We tested our null hypothesis individually using four different tools and associated annotations or ontologies. P-value from enrichment analyses were obtained using default statistical settings of different tools employed in this study. Protein domain enrichment P-values were derived from DAVID using a modified Fisher Exact P-value, called EASE score [P-values were derived using Ontologizer 2.0 and corrected using Bonferroni method [P-values. Disease enrichment analysis was performed using Functional Disease Ontology server and it uses a Fisher's exact test for deriving P-values.This study utilized four SE score . GO termi method . KEGG paHomo sapiens. A cursory look at 3DSwap database for the taxonomic spread would indicate that the largest fraction was from humans (25.6%)  Figure . Human pProtein domain enrichment analysis was performed using DAVID . KEGG paTo perform protein domain enrichment analysis, domains were identified in proteins involved in 3D domain swapping and a list of protein domains was obtained. This list of protein domains was compared against a reference dataset of protein domains associated with complete human proteome. Protein domain enrichment analysis was performed to understand statistically significant, conserved, functional modules associated with proteins involved in 3D domain swapping. Dataset of 45 Uniprot identifiers were used for protein domain enrichment analysis using Pfam annotations. DAVID version 6.7 with default settings was used for the analysis.x is also annotated to all parent terms of x, and this often leads to false enrichment calculations. Such relationships  were taken into account in Ontologizer 2.0 using parent-child inheritance concepts [Homo sapiens) specific GO enrichment analysis and pathway analysis. GO enrichment analysis was performed using the following parameters using Ontologizer 2.0: Gene Ontology annotations were derived from human-specific annotation data (gene_association.goa_human) [GO term enrichment analysis in this study was performed using Ontologizer 2.0, a multifunctional tool for GO term enrichment analysis. Ontologizer was selected due to the improved statistical approximation methods incorporated in it. A brief description of the method is provided here. Generic GO enrichment tools calculate the enrichment of a GO term with respect to the list of genes in the dataset and the background population using the probability of drawing the same or higher number of genes annotated to a given term. This basic concept was implemented using statistical test involving the upper tail of the hypergeometric distribution or one-tailed Fisher's exact test. Such methods do not consider relationships between the annotation terms. GO is defined as a directed acyclic graph (DAG), with various levels of relationships between the terms. Due to DAG architecture of GO, a gene or gene product annotated with a term concepts . Detaileconcepts ,84. Dataa_human) , multiplPathway enrichment analysis using KEGG pathway annotations were performed to understand the role of proteins in 3D domain swapping conformation in various biological pathways. UNIPROT Identifiers were mapped to Entrez gene identifiers using custom Perl scripts and used as the input in R package SubPathwayMiner  for pathThe disease ontology tem enrichment analysis was performed using Functional Disease Ontology server . List of3D domain swapping is a structural mechanism employed by a variety of protein structures to form oligomeric assemblies. These oligomers were often associated with aggregation diseases or proteinopathies in humans. Parkinson's diseases and Alzheimer's diseases are two major neurodegenerative diseases due to phenotypic impact of 3D domain swapping. Hitherto, no comprehensive study has been reported to analyze the impact of all proteins involved in 3D domain swapping from a whole proteome-wide or genome-wide perspective due to unavailability of a well-defined, curated dataset. We performed the initial investigation of proteins involved in 3D domain swapping in the level of protein domains, Gene Ontology, KEGG pathways and Disease Ontology. Our approach helped to understand enriched protein domains, Gene Ontology terms, biological pathways and Disease Ontology terms mediated by these proteins and their role in mediating various human diseases.Statistically significant protein domains associated with swapped proteins in the human proteome is provided Table , GO termvia 3D domain swapping. Machine learning algorithms and computational approaches may help to predict more proteins with features of 3D domain swapping [Proteins involved in 3D-domain swapping represents a large collection of proteins with a variety of functional and regulatory roles in the cell. Due to limitation in crystallizing structures in the swapped conformation, currently available repertoire of proteins in the swapped conformation may represent only a small fraction of proteins that may perform its molecular role swapping ,52. HereProtein domain enrichment analysis reveals that five protein domain families were enriched in the dataset , diseases of the respiratory or pulmonary system , degenerative diseases of the central nervous system , vascular disease  and encephalitis (rabies). Neurodegenerative diseases are well-known to have strong association with 3D domain swapping, but insights into other diseases indicates that there could be more proteins with disease association and 3D domain swapping, beyond the currently well-known group of conformational diseases. Detailed table with Disease Ontology term (disease), genes associated with each disease and Domain swapping is a key pathophysiological mechanism mediating conformational disease. A detailed account of functional repertoire, molecular pathways and spectrum of diseases affected by this mechanism remains elusive. We used enrichment calculations to understand the aspects using a curated dataset of proteins involved in 3D domain swapping. Our analysis was performed using a dataset of 45 unique human proteins derived from 3DSwap knowledgebase . This daDue to oligomeric features of swapping, earlier studies have indicated that 3D domain swapping plays a crucial role in conformational diseases or deposition diseases and proteinopathies. There was limited insight on structure-function relationship of proteins involved in domain swapping due to unavailability of a large dataset to objectively analyze functional or disease implications implicated by 3D domain swapping. Proteins encoded in the human genome and reported to be involved in 3D domain swapping were analyzed in detail to understand the role of gene products in various classes of diseases, beyond conformation diseases or proteinopathies. Mapping and enrichment analysis of human proteins involved in 3D domain swapping to KEGG pathways in 'disease' class and Disease Ontology indicates that these proteins play a significant role in various other diseases categories along with well-known neurodegenerative or conformational diseases.Availability of genome-scale sequence data and annotations were considered as the ideal resource for gaining new insights from a plethora of biological data. Structural mechanisms can gain new insights about the functional aspects by mapping and database-wide enrichment analysis using annotations. In a similar way, functional mechanism may also gain new insight by using knowledge-based approaches employed in this study. In summary, the present study reports the application of knowledge-based approaches to understand new functional insights about a structural mechanism. Starting from an initial dataset of protein structures, the present study shows the importance and impact of the data integration and data mining to derive biologically relevant interpretations of global trends of a structural mechanism from sequence, functional and disease perspective. Further new insights are obtained from a translational perspective by focusing on proteins involved in 3D domain swapping in the human genome. 3D domain swapping is a unique phenomenon and may affect availability of active sites and binding sites required to impart the biological function depending on the swapped conformation. Perhaps, future drug design studies should consider these important aspects while developing therapeutics for various disease categories where 3D domain swapping is observed.In the current era of personal genomes and network medicine, clinical and therapeutic approaches are utilizing integrated approaches for the understanding of disease states and pathophysiological mechanisms. Complex disease states are often triggered by perturbations in multiple pathways by multiple genes -94. ProtInsights obtained from our disease ontology analysis indicates that 3D domain swapping is not just confined to neurodegenerative diseases, proteins in swapped conformation play a significant role in several other classes of diseases like cancer, vascular disease, pulmonary disease etc. Enrichment results discussed in this paper will be useful in such studies in the future from biochemical, functional, structural and therapeutic perspective. Our analysis also indicates that further genome-specific analysis of proteins involved in 3D domain swapping, using comparative genome analysis framework, may also add further understanding of functional, structural and pathophysiological manifestations of 3D domain swapping.3D domain swapping is an important structural mechanism associated with a diverse set of proteins involved in multitude of biological processes and molecular functions and diseases including proteinopathies. This phenomenon is often studied from the perspective of protein structure and its impact on biological pathways, correlations with biological functions and association with classes of diseases other conformational diseases were largely unknown. We performed a knowledge-based analysis of human proteins involved in 3D domain swapping to find the key functions, pathways and diseases associated with 3D domain swapping. Our study was limited to 45 unique proteins involved in 3D domain swapping. 3D domain swapping is a functionally relevant phenomenon due to its primary role in protein oligomerization; proteins with swapped oligomeric states are being identified on a regular basis using crystallography experiments. Effective algorithms that can predict swapping from structural and sequence information may also help to identify more proteins in swapped confirmation. As more proteins are being characterized in swapped conformation, performing such knowledge-based analysis using new proteins, improved annotations and enhanced ontologies may reveal additional functional classes, pathways and disease. In summary, we showed results from an initial investigation to understand conserved protein domains, functional repertoire, pathways and diseases mediated by 3D domain swapping in human proteome.The authors declare that they have no competing interests.KS curated the data, performed the analysis and compiled the first draft of the manuscript. RS conceived the project, designed the curation strategy, discussed the approaches and provided critical comments to the manuscript. All authors read and approved the final manuscript.Supplementary Table 1Click here for fileFigure S2Click here for fileFigure S3Click here for file


Geolycosa sp. (Araneae:Lycosidae), excavate vertical burrows and inhabit them throughout their lives or, in the case of males, until they mature and wander in search of mates. Three species: G. fatifera Kurata, G. missouriensis Banks, and G. rogersi Wallace were studied to understand how and at what expense the burrowing is accomplished. Normal and high-speed videography coupled with scanning electron microscopy revealed (a) that the convex surfaces of the two fangs, together, constitute the digging tool, (b) that boluses of soil are transported to the burrow entrance on the anterior surfaces of the chelicerae held there by the pedipalps, and (c) that each bolus is either incorporated into the growing turret or flung away, propelled by the forelegs. To elucidate the energetics of burrow construction, burrow volumes were calculated and then the costs associated with dislodging, elevating, and throwing the known volumes of soil were measured. A typical Geolycosa burrow, at a volume of 23.6 ± 2.0 ml and a depth of 13.2 ± 0.7 cm, required the removal of 918 boluses each weighing about 34 mg. The aggregate dislodging cost was close to 1.9 Joules in sand/sandy loam and 5.6 J in clayey subsoil, the work against gravity necessary to raise all of the boluses to the surface was about 0.13 J, and the aggregate cost of flinging the boluses was close to 0.014 J. Assuming that the ratio of external work to metabolic cost of external work is between 0.20 and 0.25 in spiders, the real cost of burrow construction would be between 8 J and 29 J, depending primarily on soil type. This is a small but not negligible cost when placed in the context of reproductive effort: a single Geolycosa egg, dozens to hundreds of which are produced in a clutch, contains about 10 J.Burrowing wolf spiders,  Geolycosa, but also a few elsewhere in the family (e.g. Hogna carolinensis) are obligate burrowers, constructing approximately vertical burrows that can be 15–30 body lengths in depth  excavate cavities in the ground and use them for retreats during various phases of their lives , the presumed or demonstrated benefits of inhabiting a burrow are at least these:Predator avoidance/defense Constrained terrestrial dispersal Reduced prey availability Reduced detectability by potential mates And at the same time, there are presumed or demonstrated costs:Geolycosa during excavation were elucidated. The techniques and costs are closely linked not only in the physiology of the spiders, but also in the methods of analysis - the loosening of soil from the walls of the growing burrow, the transport of the packets (boluses) of soil to the surface, and the ejection of the boluses from the mouth of the burrow are behaviorally and energetically distinct phases of the process of excavation.In this study, the energetic costs of burrow construction were studied and the techniques used by Geolycosa fatifera (Kurata 1939), G. missouriensis (Banks 1895), and G. rogersiin situ or captured at sites in Mississippi, USA were the subjects of this study. In the laboratory, where temperature varied between 20° C and 25° C and humidity was unregulated, those that had been captured were briefly held in 5 × 8.5 cm (142-ml) plastic vials before being transferred to test environments (described below) or killed and preserved in 95% ethyl alcohol. Ultimately, all were killed and preserved; voucher specimens have been deposited in the Mississippi Entomological Museum.Three species: In the field, burrows were filled with either Plaster of Paris (CaSO4∼0.5H2O) or leadenriched solder; these materials were allowed to solidify and the casts were extracted. Depth and diameter were determined using a ruler and calipers, and volume was found via fluid displacement in a graduated cylinder.Both in the field and in the laboratory, the boluses of sand/sandy loam that spiders had ejected from the mouths of their burrows during excavation were collected. For each of 9 burrows , the pooled mass of 10 oven-dried boluses was measured and divided by 10 to arrive at an average dry mass/bolus. To know the wet mass of these boluses, freshly collected sand/sandy loam was collected, weighed, and then oven-dried to constant mass; the resulting water loss data allowed back-calculation from dry mass of pellets to wet mass of pellets. These data and the volumes of burrows allowed calculation of the approximate number of boluses a spider would have to collect, form, carry to the surface, and eject to complete excavation of a burrow of known volume.In the laboratory, a spider whose digging behavior was to be studied was released into a circular arena (diameter: 12 cm) containing 4– 5 cm of lightly compacted soil. To stimulate burrowing behavior , a hemisG. missouriensis specimens were captured. The soil was approximately 20 cm deep, again with a depression in the surface to foster burrowing at a predictable location. Once a spider's burrowing had progressed to a depth of several cm, its behavior at the burrow entrance was videotaped both in color at 30 frames per second and in monochrome at 500 frames per second . The highspeed video was analyzed at 15 frames per second (about a 33-fold slowing) and frame by frame. Motions of parts of the spider and of the material it was ejecting were analyzed with the help of image analysis software .The spiders' motions in casting away the materials they had excavated in their burrows were far too rapid to analyze using video captured at 30 frames per second. To study these motions, each spider was placed into a circular arena (diameter: 12 cm) containing lightly dampened sand/sandy loam collected at the site in Holmes County State Park (Mississippi) where most of the Geolycosa sp. with wear on those of Rabidosa rabida , a wolf spider of approximately the same size, but with much less inclination to construct burrows , with the abrasive surface of the sandpaper facing upward. As a spider dug downward in the latter situation it encountered first soil, then a single layer of paper tissue (Kimwipes®EX-L) that served to mark where digging had occurred, and finally the abrasive barrier or the foam block. The fangs of spiders that were subjects in this experiment, some of which burrowed to the sandpaper and others of which burrowed only in the loam or to the foam block, were later inspected under SEM for conspicuous wear.Specimens to be viewed with the SEM were preserved in 100% EtOH, then freeze-dried, and finally sputter-coated with gold and palladium in a ratio of 80:20.To develop a complete estimate of the energy expenditures required to excavate a burrow of average depth and volume, one needs independent measures of the costs of dislodging the substrate, of transporting the substrate to the surface, and of dispersing the substrate once it is outside the deepening burrow.Geolycosa for experimental purposes, a piece of brass was machined so that its bottom edge, the part that would come into contact with soil, was of the same dimensions and shape as the distal parts of the spider's chelicerae with the fangs partially flexed  In these tests, the brass pseudo-fangs were held nearly perpendicular to the soil surface where they exerted a constant downward force that could be adjusted by changing the position of a counterweight . Reinforcing the conclusion that the fangs are the primary tools used to loosen soil are two further results. First, visible wear on the fangs of Rabidosa rabida, a species of wolf spider in which burrowing is uncommon, was minor when compared to the complete absence of wear on newly exposed fangs whereas visible wear on the fangs of burrowing wolf spiders (Geolycosa spp.) was conspicuous when the same comparison was made (Video sequences captured at 30 frames per second showed that during excavation a was made  were subwas made . The oriwas made  indicatewas made .Video 2). In both the field and the lab, the ejected boluses landed 6–50 cm from the burrow entrance, sometimes roughly evenly distributed in all directions and sometimes concentrated in a fan-shaped debris field spanning an arc of about 60 degrees.In terms of process, the spider loosened substrate, formed it into a pellet or bolus, and carried it to the surface on the anterior face of its chelicerae held there by the pedipalps . At the Burrow volumes and number of boluses. The burrow depths and volumes of 5 G. rogersi, 6 G. missouriensis, and 7 G. fatifera were measured. A one-way ANOVA on burrow depths . Tukey's Multiple Comparison Test revealed only one significant pair-wise comparison, between G. missouriensis and G. fatifera . Despite this significant difference, for subsequent calculations the mean of the pooled depths, 13.16 ± 0.74 cm , was used. Although a oneway ANOVA on burrow volume , Tukey's Multiple Comparison Test revealed no significant pair-wise differences at α=0.05. Consequently, for convenience in later calculations, the mean value for the pooled volumes, 23.56 ± 2.02 ml, was used.w depths  showed tw volume  showed tG. missouriensis was found was 1.370 g/ml and for the clayey subsoil where G. fatifera was found was 1.301 g/ml; the average of these, 1.34 g/ml, was taken as the working value for substrate density. The pellets ejected from field- and laboratoryexcavated burrows had masses of 0.0344 ± 0.0070 g. The product of burrow volume and substrate density gave a value of 31.57 g for the mass of substrate ejected during the construction of an average burrow. Dividing this by the average mass of an ejected pellet revealed that the number of pellets a spider had to form, carry to the surface, and eject during burrow excavation was 917.7.Substrate density for the sand/sandy loam where Dislodging soil from burrow walls. It takes work (force applied over distance) to do the scraping required to dislodge soil from the walls of a growing burrow. 1,5 = 1234, P < 0.0001; clayey soil: F1,5 = 74.77, P = 0.0003) and from each other . On fine sandy loam, the greater the work the greater the mass of the dislodged product . product ; the slo1,10 = 13.50, P = 0.0043).This predictable relationship did not hold for work done on the more resistant clayey soil; in that case, no significant relationship was found between work done and soil dislodged . The sandy loam and clayey soil slopes were significantly different from each other .Work against gravity is the product of the mass being moved upward, the vertical distance moved, and the acceleration of gravity. In the present case, for each trip the mass was the sum of the spider's mass (0.144 ± 0.041 g) and the average pellet mass (0.0344 g), the average distance was 0.0789 m, and as always gravity was 9.81 m/sDispersing the boluses of substrate. When a spider throws a bolus of substrate, it uses its forelegs to accelerate the bolus. The work done during this acceleration gives the bolus its kinetic energy, calculated as:m is the mass that was accelerated to velocity v. The kinetic energy of the bolus just after the spider released it was an accurate measure of the work used to propel the bolus. Frame-by-frame analysis of 10 bolus trajectories revealed velocities of 0.939 ± 0.119 m/s and, using the mean mass of a bolus as 0.0344 g, gave an average work per ejected bolus of 1.52 × 10-5 J. Multiplying that by 918 boluses gave 0.0139 J as the total cost of ejecting the substrate during burrow excavation.The external work done by the spider while excavating its burrow included the work of loosening the sandy loam (1.9 J) or clayey soil (5.6 J), making multiple trips to the surface carrying boluses of substrate and the spider itself (0.13 J), and throwing the boluses away from the burrow entrance (0.014 J). The total of these costs, approximately 2.0 J in sandy loam or 5.8 J in clayey soil, constituted only the external work done by the spider; the costs did not include the additional physiological costs (the metabolic energy expended but lost as heat) incurred while doing the external work. Thus the total physiological cost of doing external work was the sum of the external work and the energy lost as heat.Geolycosa probably lies between 4 and 5× the measured external work: for sandy loam, 8–10 J; for clayey soil, 23–29 J.The above distinction refers to muscle efficiency, the ratio of external work to total metabolic energy expenditure which can vary from 0 to 1 and which, under experimental conditions, usually lies between 0.20 to 0.25 ; G. missouriensis, 133 and 179  optimization. A relatively simple reciprocal transplantation experiment will help to clarify the causes of the burrow depth difference.Animals are known to optimize their behaviors and energy expenditures; for example, adjusting territory size in response to resource richness (e.g. in hummingbirds:


Modular polyketide synthases are multifunctional megasynthases which biosynthesize a variety of secondary metabolites using various combinations of dehydratase (DH), ketoreductase (KR) and enoyl-reductase (ER) domains. During the catalysis of various reductive steps these domains act on a substrate moiety which is covalently attached to the phosphopantetheine (P-pant) group of the holo-Acyl Carrier Protein (holo-ACP) domain, thus necessitating the formation of holo-ACP:DH and holo-ACP:KR complexes. Even though three dimensional structures are available for DH, KR and ACP domains, no structures are available for DH or KR domains in complex with ACP or substrate moieties. Since Ser of holo-ACP is covalently attached to a large phosphopantetheine group, obtaining complexes involving holo-ACP by standard protein-protein docking has been a difficult task.E.Coli FAS. In case of KR domain, the substrate binding site identified by our simulations was in proximity of the known stereo-specificity determining residues.We have modeled the holo-ACP:DH and holo-ACP:KR complexes for identifying specific residues on DH and KR domains which are involved in interaction with ACP, phosphopantetheine and substrate moiety. A novel combination of protein-protein and protein-ligand docking has been used to first model complexes involving apo-ACP and then dock the phosphopantetheine and substrate moieties using covalent connectivity between ACP, phosphopantetheine and substrate moiety as constraints. The holo-ACP:DH and holo-ACP:KR complexes obtained from docking have been further refined by restraint free explicit solvent MD simulations to incorporate effects of ligand and receptor flexibilities. The results from 50 ns MD simulations reveal that substrate enters into a deep tunnel in DH domain while in case of KR domain the substrate binds a shallow surface exposed cavity. Interestingly, in case of DH domain the predicted binding site overlapped with the binding site in the inhibitor bound crystal structure of FabZ, the DH domain from We have modeled the holo-ACP:DH and holo-ACP:KR complexes and identified the specific residues on DH and KR domains which are involved in interaction with ACP, phosphopantetheine and substrate moiety. Analysis of the conservation profile of binding pocket residues in homologous sequences of DH and KR domains indicated that, these results can also be extrapolated to reductive domains of other modular PKS clusters. Polyketides are secondary metabolites that constitute a major class of pharmaceutically important compounds. The biosynthesis is catalyzed by multi-functional enzymes using an assembly line mechanism. The various domains in these multi-functional enzymes are arranged as modules where each module catalyzes the addition of one extender unit. Each module is constituted by a set of domains responsible for adding and modifying the extender unit. The biosynthetic intermediate is covalently attached to Acyl Carrier Protein (ACP) domain by a thioester linkage and is transferred from one catalytic site to another. The condensation of extender unit with the elongating polyketide chain is brought about by ketosynthase (KS) and Acyltransferase (AT) domain. The beta-keto product formed by action of KS and AT domain can be further modified by a combination of ketoreductase (KR), dehydratase (DH) and enoyl-reductase (ER) domains to form a hydroxyl group (KR only), a double bond (KR and DH) or a single bond  containing moiety . Althouget al[Recently the structure of dehydratase from the fourth module of erythromycin synthase was solved by Keatinge Clay . The stret al. These sKetoreductases reduce the beta carboxyl to a hydroxyl group and thereby introduce a chiral center in the polyketide products. Thus, they are responsible for determining the chirality of the polyketide product . Earlier). The structure for the Tylosin KR has also been reported by Keatinge Clay recently [Recently, Keatinge-Clay & Stroud have solved the crystal structures of KR domain from first module of erythromycin synthase which constituted two sub-domains, the structural and catalytic sub-domain, both showing Rossmann fold similar to SDR family of enzymes, in spite of low sequence similarity . The strrecently . Tylosinrecently . Recentlrecently ,15.The DH and KR domains carry out their catalytic activity on the ACP bound substrate moiety. Even though, the crystal structures are available for DH and KR domains of modular PKS , no struThe modeling of substrate bound holo-ACP:DH complex was carried out in several steps involving protein-protein docking of apo-ACP:DH complexes, docking of P-pant group, docking of substrate moiety and finally formation of required covalent bonds and energy minimization/refinement of the substrate bound complex as described in methods section  in the DH domains. As described earlier in the methods section, the substrate for DH domain was docked as two separate fragments . The set of 267 complexes obtained with a positive RPscore were further analyzed to identify the complexes satisfying functional constraints. The functional requirement for catalysis by KR domain necessitates the 20 Å long P-pant group attached to the Ser of ACP to reach the active site pocket of KR domain. Therefore, the complexes were filtered with a distance constraint of 20 Å between catalytic Ser 46 of ACP and the catalytic Tyr 1813 of KR domain. It may be noted that, in case of apo-ACP:DH docking study, distance constraints between Ser 46 of ACP and residues on DH domain were used because experimental studies had suggested involvement of corresponding residues in ACP recognition. However, no such information was available about the interacting residues involved in binding of ACP to the KR domain. Therefore, only the 20 Å distance constraint between Cα atom of Ser 46 of ACP and Cα atom of catalytic Tyr 1813 of KR was used to filter the complexes having positive RPscore. This functional constraint yielded six complexes that satisfied the criteria and the best scoring complex was chosen as the final apo-ACP:KR complex. The top panel in Figure , all these solutions fall into the same shallow cavity leading to the catalytic residues and binding energy of these solutions varies in the range of −1.75 to −6.13 kcal/mol. Even though cluster 8 was best solution in terms of minimum binding energy as well as distances, it had a steric clash between P-pant group and catalytic Tyrosine. Thus, the next best solution cluster 14 was chosen for modeling the holo-ACP:KR complex by formation of required covalent bond between Ser 46 and P-pant moiety. The middle panel of Figure In order to model the holo-ACP:KR complex, the P-pant moiety was docked on the final apo-ACP:KR complex obtained from protein-protein docking. Docking of P-pant moiety by AutoDock on the apo-ACP:KR complex resulted in 250 bound conformations belonging to 150 different clusters (RMSD cutoff of 2 Å). The lower left panel in Additional file 8In order to build the substrate bound holo-ACP:KR complex, the diketide substrate moiety was docked onto the holo-ACP:KR complex subject to the constraint that, the terminal carboxyl carbon of the substrate will be covalently bonded to the S atom in P-pant and also the beta keto group of the substrate will be in close proximity of the catalytic residues in the KR domain. The various bound conformations of the substrate obtained from AutoDock were grouped into 15 clusters (RMSD within a cluster <2 Å) with different binding energy values. Additional file Analysis of the apo-ACP:KR complex indicated that the charged residues in KR domains formed contacts with hydroxyl or carboxyl moiety of the substrate while the hydrophobic residues were observed to interact with methyl groups. In case of P-pant moiety, the charged residues in KR domain interact with the charged phosphate group as well as carboxyl atoms while the non-polar residues interact with the methyl groups of P-pant. Table The substrate bound holo-ACP:KR complex obtained from docking and energy minimization studies was further refined using molecular dynamics simulations in the explicit solvent environment for a period of 50 ns. Detailed analysis of the conformations obtained from 50 ns simulations indicated that the entire complex showed a backbone RMSD in the range of 3.0 to 5.0 Å from the starting structure. The conformation of the bound substrate and its orientation with respect to the catalytic residues of KR domain was also analyzed to investigate whether the binding pose of the substrate identified by docking and energy minimization was stable during the explicit solvent MD simulation. As can be seen from the lower left panel in Figure , even in the complete module structure, ACP can bind to the same sites as predicted by docking and there are no steric clashes of ACP with any other domain in the module. It is interesting to note that the ACP binding site on KR domain is located in a void surrounded by KR, DH, AT and KS domains.The holo-ACP:DH as well as holo-ACP:KR complexes obtained by our study gave the position of ACP domain with respect to DH and KR domains but in a modular PKS the ACP would bind to a complete module structure comprising other domains also. Thus, it was necessary to check if the predicted site of ACP binding on each of these domains is also available in the three dimensional structure of the complete PKS module or occluded by other catalytic domains. Since, no complete module structure is available for PKS, the structure for complete module 4 of erythromycin PKS was modeled using FAS as template using SBSPKS web-server . The apoIn this study, the binding of DH and KR domains to their cognate apo-ACP domains has been modeled using protein-protein docking methods. The energetically favorable solutions obtained from docking studies have been further filtered to satisfy functional constraints like proximity of catalytic Ser of ACP to active sites of DH and KR domains. The apo-ACP:DH and apo-ACP:KR complexes generated by this approach have been utilized to model holo-ACP:DH and holo-ACP:KR complexes by docking of P-pant moiety and substrate fragments. The protein-ligand docking for modeling holo-ACP complexes has also been carried out based on functional constraints of covalent linkage between Ser of ACP, P-pant and substrate moiety. Since, the protein-protein and protein-ligand docking do not incorporate protein flexibility, the holo-ACP complexes obtained from docking studies have been subjected to unrestrained molecular dynamics simulations in explicit solvent environment for a period of 20 ns. Interestingly, the holo-ACP:DH and holo-ACP:KR complexes were found to be stable even during unrestrained MD simulations.This study gives an insight into how ACP binds to DH and KR domains and also how the substrate moieties are swung into the active sites by P-pant arm of ACP. It was found that substrate enters into a deep tunnel in case of DH domain while in case of KR domain the substrate binds in a shallow cavity exposed to the surface. Based on these modeling studies, the specific residues on DH and KR domains involved in interaction with ACP, P-pant and substrate moiety have been identified. The substrate binding site on DH domain identified from the current modeling study has been validated by comparison with the crystallographically determined bound conformation of the mechanism based inhibitor of FabA protein. Similarly, in case of KR domain, the substrate is positioned in proximity to the known sequence motifs responsible for epimerization as well as stereo-chemical control, as explained earlier. Even though, the current modeling study has been carried out for DH and KR domains from erythromycin synthase, analysis of conservation profile of binding pocket residues indicate that the results might be extrapolated to DH and KR domains of other PKS clusters also.in silico modeling of substrate bound apo-ACP:DH and apo- ACP:KR complexes involved several steps which are illustrated in the flowchart depicted in Figure The DH and KR domains carry out their catalytic activity on a polyketide intermediate which is covalently attached to the P-pant moiety of the holo-ACP. TherefoThe cognate ACP for the crystal structure of DH domain of erythromycin synthase is the ACP from module 4 while ACP from module 1 of erythromycin is the cognate ACP for the crystal structure of the KR domain. Since, no crystal or NMR structures were available for these two ACPs, NMR structure (PDB ID 2JU2) of the ACP from module 2 of erythromycin PKS was Docking of the structural models of apo ACP domains without P-pant onto the crystal structures of DH and KR domain was carried out using the protein-protein docking software FTDOCK version 2 . During In order to model complexes of holo-ACP with DH and KR domains, it was necessary to dock the phosphopantetheine (P-pant) group on the final structures of apo-ACP:DH and apo-ACP:KR complexes obtained by functional constraints based filtering of the high scoring solutions given by FTDOCK. However, in these complexes, ACP blocks the entrance to the active site pockets of DH and KR domains. Therefore, during the docking of phosphopantetheine group, ACP was removed from these complexes and docking was carried out on DH and KR domains alone. The docking of phosphopantetheine group onto the DH and KR complexes was carried out by using the program AutoDock version 4 . The cooThe various different P-pant bound DH and KR domains obtained from the AutoDock analysis were transformed onto the apo-ACP:DH and apo-ACP:KR complexes. This resulted in ACP:DH and ACP:KR complexes in which P-pant group was bound in different conformations and orientations. In the holo-ACP:DH and holo-ACP:KR complexes, the phosphate of the P-pant group should be covalently bonded to Ser of ACP and the terminal -SH group of P-pant should be proximal to the catalytic residues of DH or KR domains. Out of the 250 solutions obtained by docking, P-pant conformations which had the minimum distance between the S atom of P-pant and Cα of respective catalytic residues in DH/KR domains as well as between phosphate of P-pant and Ser of ACP were selected using an in-house Perl script. The P-pant bound ACP:DH and ACP:KR complexes which satisfied the above mentioned functional constraints were used to model holo-ACP:DH and holo-ACP:KR complexes by forming the required covalent bonds between the Ser of ACP and the phosphate of P-pant. The holo-ACP:DH and holo-ACP:KR complexes obtained by this approach were further energy minimized using CVFF forcefield and Insight II package.In order to model holo-ACP:DH and holo-ACP:KR complexes bound to their native substrates, the cognate substrate moieties for the DH and KR domains were docked onto the holo-ACP:DH and holo-ACP:KR complexes obtained by P-pant docking. Complexes were energy minimized after formation of covalent bonds, as mentioned earlier. The substrate for KR domain was a diketide while the substrate for DH domain was -3,7,9-trihydroxy-5-oxo-2,4,6,8 tetramethylundecanoate . The strIn case of the substrates for DH domain, the number of freely rotatable bonds was larger. Therefore, the 10 carbon atom substrate was docked as two separate fragments one after another. Additional file -1. The reference pressure was set to 1 atm using NPT ensemble over a further period of 200 ps. The equilibration was carried on till the density (~1 g/cm3) as well as temperature (~300 K) became stable. The pressure was scaled using isotropic position scaling with a pressure relaxation time of 1 ps. The production simulation was carried out for 50 ns for both the substrate bound holo-ACP:DH as well as holo-ACP:KR complexes using NPT ensemble. The non-bonded cutoff of 8 Å was used for van der Waals interactions. Particle Mesh Ewald (PME) summation [The structural models of substrate bound apo-ACP:DH and apo-ACP:KR complexes obtained from protein-protein docking and protein-ligand docking contained an unusual side chain residue where catalytic Ser of ACP was covalently bonded to acylated P-pant moiety. Antechamber module of AMBER 9  was usedummation  was usedDuring the simulation, the coordinates were saved at an interval of 1 ps. Various analyses on the MD trajectories were performed using ptraj module of AMBER 9 as well as other in-house Perl scripts.A set of 1000 structures were extracted from 50 ns trajectory with conformations taken at an interval of 50 ps. The residues contacting the substrate and P-pant moiety were calculated for each of these structures. The contacting residues included those where any atom of the residue lied within a cutoff distance of 6 Å from any atom of P-pant and substrate moieties. For each of the contacting residues, the percentage of structures in which the corresponding contact was present was reported.DM and SA designed research. SA performed the computations and analyzed data. DM and SA analyzed data and wrote the manuscript. All the authors read and approved the final manuscript.Supplementary figures.Click here for file


Striatal functions depend on the activity balance between the dopamine and glutamate neurotransmissions. Glutamate inputs activate cyclin-dependent kinase 5 (Cdk5), which inhibits postsynaptic dopamine signaling by phosphorylating DARPP-32  at Thr75 in the striatum. c-Abelson tyrosine kinase (c-Abl) is known to phosphorylate Cdk5 at Tyr15 (Tyr15-Cdk5) and thereby facilitates the Cdk5 activity. We here report that Cdk5 with Tyr15 phosphorylation (Cdk5-pTyr15) is enriched in the mouse striatum, where dopaminergic stimulation inhibited phosphorylation of Tyr15-Cdk5 by acting through the D2 class dopamine receptors. Moreover, in the 1-methyl-4-phenyl-1,2,4,6-tetrahydropyridine (MPTP) mouse model, dopamine deficiency caused increased phosphorylation of both Tyr15-Cdk5 and Thr75-DARPP-32 in the striatum, which could be attenuated by administration of L-3,4-dihydroxyphenylalanine and imatinib (STI-571), a selective c-Abl inhibitor. Our results suggest a functional link of Cdk5-pTyr15 with postsynaptic dopamine and glutamate signals through the c-Abl kinase activity in the striatum. Cyclin-dependent kinase 5 (Cdk5) is a member of the Cdk family of serine/threonine kinases and is abundantly expressed in the brain  mouse model with striatal dopamine deficiency, a c-Abl kinase inhibitor imatinib (STI-571)  were used. Mice were housed under a 12 h-light and 12 h-dark cycle with access to food and tap water Mice were injected intraperitoneally 4 times in one day with MPTP hydrochloride  at 2 h intervals  dissolved in 0.9% saline containing 0.5% carboxymethyl cellulose 3 days after administration of MPTP or saline. The used dose of L-dopa was chosen based on the findings reported previously  dissolved in 0.9% saline containing 10% dimethylsulfoxide 3 days after administration of MPTP or saline. Vehicle-treated mice received an equivalent volume of 0.9% saline containing 10% dimethylsulfoxide.3VO4, 30 mM Na4P2O7, 50 mM NaF, 0.1 mM leupeptin, 0.075 mM pepstatin A, 0.05 mg/ml trypsin inhibitor, 1 mM phenylmethanesulfonyl fluoride, 100 nM calyculin A, and 1 mM dithiothreitol. After centrifugation at 21,500 × g for 10 min, the protein lysates were resuspended in 100 mM NaH2PO4, pH 6.0, I mM EDTA, 1% 2-mercaptoethanol, 0.1% sodium dodecyl sulfate, to 1 mg/ml final protein concentration and was heated at 99°C for 3 min. Specific antibodies against Cdk5-pTyr15 , Cdk5 , DARPP-32-pThr75 , DARPP-32-pThr34 , DARPP-32  were used. The monospecificity of these antibodies was confirmed in our previous reports , A-68930 hydrochloride , SCH-23390 hydrochloride , quinpirole hydrochloride , raclopride tartrate , L-dopa (15 mg/kg) with benserazide (12.5 mg/kg), or imatinib mesylate (25 mg/kg or 10 mg/kg). Western blot analysis was carried out according to the method described previously  30 min after drug administration. They were then transcardially perfused with 0.01 M phosphate-buffered saline (PBS) at pH 7.4, followed by cold 4% paraformaldehyde in 0.1 M phosphate buffer (PB) at pH 7.4. The brains were removed, post-fixed overnight in the same fixative at 4°C, and stored in a 10–30% sucrose gradient in 0.1 M PB at 4°C for cryoprotection. Sections were cut on a cryostat at 15 μm-thickness, and stored in PBS containing 0.05% NaNFor double immunofluorescence staining Cdk5-pTyr15 and μ-opioid receptor (MOR), dual antigen detection with the TSA system was carried out according to the method that we reported previously , density measurement was made in a striatal section at the level of 0.9–1.1 mm anterior to bregma, according to the atlas of Hof et al. , imported into Adobe Photoshop CS4, and processed digitally. The optical densities of immunoreactive products were measured as gray levels on non-colored digital images , nucleus accumbens and olfactory tubercle Figure . In the P < 0.005, Student's t-test). Immunohistochemical study on frontal sections from anterior to posterior of the forebrain also showed a decreased density of Cdk5-pTyr15 staining in the striatum of mice that received apomorphine (10 mg/kg) . We next examined whether dopaminergic stimulation could cause reduced expression of Cdk5-pTyr15 by acting on the D1 or D2 class receptors , or a D1 receptor antagonist SCH-23390 (0.5 mg/ml) . By contrast, striatal levels of Cdk5-pTyr15 were significantly decreased following administration of a D2 receptor agonist quinpirole (5 mg/kg) , and they were significantly increased following administration of a D2 receptor antagonist raclopride (1 mg/kg) . These findings suggest that dopamine signal can inhibit striatal phosphorylation of Tyr15-Cdk5 and this process most likely occurs through a D2R-mediated mechanism.To test whether striatal phosphorylation of Tyr15-Cdk5 was altered by dopaminergic stimulation, we performed the western-blot assay for Cdk5-pTyr15 expression after treatment with apomorphine, an agonist for both the D1Rs and D2Rs. A significant reduction of the striatal levels of Cdk5-pTyr15 was found following administration of apomorphine at a dose of 5 mg/kg or 10 mg/kg . It was evident in the entire striatum that includes dorsal striatum, nucleus accumbens and olfactory tubercle. Western blot analysis also revealed a significant increase in the striatal levels of Cdk5-pTyr15 , but not Cdk5 , in MPTP mice as compared to saline-treated mice. It was also noted that in MPTP mice L-dopa treatment significantly attenuated the abnormally elevated striatal levels of Cdk5-pTyr15 . This antagonistic action of L-dopa on striatal phosphorylation of Tyr15-Cdk5 in MPTP mice was also found in the immunohistochemical assessment . No apparent difference in striatal levels of DARPP-32-pThr34  and DARPP-32  was found between the MPTP mice and the saline-treated mice. L-Dopa treatment significantly reduced the abnormally elevated striatal levels of DARPP-32-pThr75 in MPTP mice . Immunohistochemical analysis also documented that L-dopa reversed increased density of striatal labeling for DARPP-32-pThr75 in MPTP mice , but not 10 mg/kg (data not shown). This was consistent with the results obtained with immunohistochemistry  and immunohistochemical  analyses.We next asked if a selective c-Abl inhibitor imatinib (STI-571) could modulate striatal phosphorylation of Cdk5 and DARPP-32. Western blot analysis revealed that in MPTP mice abnormally elevated striatal levels of Cdk5-pTyr15 was significantly attenuated by administration of imatinib at a dose of 25 mg/kg  (Calabresi et al., 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.