Large-scale bioactivity/SAR Open Data has recently become available, and this has allowed new analyses and approaches to be developed to help address the productivity and translational gaps of current drug discovery. One of the current limitations of these data is the relative sparsity of reported interactions per protein target, and complexities in establishing clear relationships between bioactivity and targets using bioinformatics tools. We detail in this paper the indexing of targets by the structural domains that bind (or are likely to bind) the ligand within a full-length protein. Specifically, we present a simple heuristic to map small molecule binding to Pfam domains. This profiling can be applied to all proteins within a genome to give some indications of the potential pharmacological modulation and regulation of all proteins.In this implementation of our heuristic, ligand binding to protein targets from the ChEMBL database was mapped to structural domains as defined by profiles contained within the Pfam-A database. Our mapping suggests that the majority of assay targets within the current version of the ChEMBL database bind ligands through a small number of highly prevalent domains, and conversely the majority of Pfam domains sampled by our data play no currently established role in ligand binding. Validation studies, carried out firstly against Uniprot entries with expert binding-site annotation and secondly against entries in the wwPDB repository of crystallographic protein structures, demonstrate that our simple heuristic maps ligand binding to the correct domain in about 90 percent of all assessed cases. Using the mappings obtained with our heuristic, we have assembled ligand sets associated with each Pfam domain.Small molecule binding has been mapped to Pfam-A domains of protein targets in the ChEMBL bioactivity database. The result of this mapping is an enriched annotation of small molecule bioactivity data and a grouping of activity classes following the Pfam-A specifications of protein domains. This is valuable for data-focused approaches in drug discovery, for example when extrapolating potential targets of a small molecule with known activity against one or few targets, or in the assessment of a potential target for drug discovery or screening studies. Research in the field of drug discovery is increasingly driven by the data mining of large-scale pharmacological, screening, patent, literature and other bioactivity data. Such approaches have led to interesting concepts that challenge historical dogma - for example the view that many small molecules and indeed drugs exert their effect through interactions with multiple rather than a single target . New tarThe discipline of combining small molecule bioactivity, the 'ligand space', with bioinformatics analyses of the 'target space' is also known under the name chemogenomics ,5. ChemoStructural domains are independent folding units that form the basic evolutionary and architectural 'building blocks' of proteins . While tet al. [The domain content of a human protein-protein interaction dataset has been described in a study by Patil et al. . Accordiet al.  : the median proportion of Pfam residues relative to sequence length is 0.72. In comparison, this ratio is 0.69 for all protein targets in the ChEMBL database, including non-human protein targets. Previous works suggests that proteins consist mainly of highly structured regions [In order to assess the impact of incomplete annotation for our set of ChEMBL targets, we determined for each target the number of residues belonging to a Pfam domain as a fraction of the number of residues in the overall protein sequence. We found that for the entire set of human proteins, the median of this fraction is 0.50 and about a quarter of all proteins have less than 20 percent of all residues assigned to a Pfam domain. The low ratio of residues within Pfam domains is likely due to incomplete coverage of Pfam-A models for the human proteome. For human protein targets in the ChEMBL database, the ratio of residues within Pfam domains is significantly higher . We queried Uniprot to retrieve all binding site information available for human protein targets in the ChEMBL database. The query was limited to human proteins to avoid a bias for targets with orthologs in the ChEMBL target dictionary, yielding binding site information for 1,428 targets. A comparison of binding site residue positions and Pfam domain boundaries revealed that 1,290 (88.4%) of annotated binding sites from UniprotKB/Swiss-Prot lie completely within a Pfam domain and only 36 (2.5%) entirely outside. Binding sites defined by a set of residues of which some are within and others outside of a Pfam domain are likely associated with the Pfam domain and therefore support our proposal that small molecule binding is associated to conserved sequence defined domains. The empirical cumulative distribution function (CDF) shown in Figure Given that about half of all proteins in the ChEMBL target dictionary have more than one domain, we investigated ways to expand our mapping of small molecule binding from targets with only a single domain to targets with multiple domains. We had observed with high probability that small molecule binding in single domain protein takes place between the boundaries of a domain. We prepared a set of single domain protein targets from the ChEMBL data base by selecting each protein that had at least one ligand tested against it in a binding assay with a reported activity value less or equal 50 μM . The occurrence of a domain in this set is thus a validation of a domain's potential to mediate a small molecule binding interaction. In the following, we consider all domains from this set as 'seed' domains with the potential to mediate small molecule binding. If such a 'seed' domain co-occurs with one or more 'non-seed' domains, our mapping defaults to this previously established seed domain. Hence, the mapping follows a heuristic based on the assumption that domains with known ligands take precedence over domains that do not occur in single domain proteins with known ligands. For example, in protein kinase Akt-3 Q9Y243), which also contains a Pkinase_C and PH domain, the target of small molecule binding is the Pkinase domain. In total, our mapping covers 197,642 activities. A table with all mappings is provided in Additional file 43, whichWe benchmarked our mapping against manually curated binding site annotations from Uniprot and also against annotation extracted from crystallographic structures in PDBe. We queried the PDBe for protein structures with ligands matching our predictions and identified 217 entries that could be used to evaluate our mapping for multi-domain proteins. The comparison with binding site annotation retrieved from Uniprot was carried out in the same fashion and we identified 511 entries that could be used to evaluate the mapping. We considered predictions correct if at least half of all binding residues are located within the predicted domain. Details of the benchmarking are discussed in the Methods Section Validation. Unsurprisingly, the accuracy of predictions made for single domain targets is high . For multi-domain proteins, the accuracy is at around 88 percent for both benchmarks. Benchmarking results of this validation are summarized in Table One limitation to our approach is its blindness towards ligand-binding Pfam domains that always occur in combination with at least one other Pfam domain. To account for the most important cases, we identified all Pfam domains that occur only in combination with other domains and occur one hundred or more times in the ChEMBL target dictionary. Based on a PDBe database survey of those domains . Hence, the distributions obtained here can be exploited to assess the binding potential of a given small molecule to a Pfam domain family, based on a combination of simple descriptors. To retain predictive power, this approach requires that the scope of the search is limited to a selection of domains. Prior knowledge about a given small molecule can instruct the selection of domains, for example if information about co-localization with protein complexes is available.We conducted a survey of the chemical space occupied by ligands of given Pfam domains. Here, we focus on 6 Pfam domains of high relevance for drug discovery, protein kinase (Pkinase), tyrosine kinase (Pkinase_Tyr), cytochrome p450 (p450), retroviral aspartyl protease (RVP), sodium neurotransmitter symporter (SNF) and the serine protease trypsin (Trypsin). For each of these, Figure In this study, we show that small molecule binding sites are associated with the regions in a protein that map to a Pfam domain, and hence typically have a discrete structure defined by a conserved sequence profile. We exploit this knowledge to map small molecule binding to Pfam domains in single- and multi-domain proteins. The integration of small molecule bioactivity data from the ChEMBL database and (predicted) structural data from Pfam will drive cross-linking across databases and deeper semantic annotation for chemical biology. In addition, our mapping allowed for an analysis of the distribution of known small molecule ligands per Pfam domain. The power-law behavior of this distribution mirrors the genomic distribution of protein folds and the incremental progression of drug discovery.The heuristic presented here is simple and efficient. However, the mapping does not address two naturally occurring edge cases. Firstly, a number of Pfam domains occur only in combination with other domains and hence are not picked up in the initial seeding step. We address this partially by manually including such domains if they occur in more than one hundred ChEMBL targets. The second case is the relatively rare occurrence of ligand binding at the interface of domains, as discussed in the section on mapping small molecule binding to multidomain proteins.One incentive to annotate recorded activities of small molecules against multi-domain proteins is a phenomenon we term 'domain poisoning' - where the presence of a common 'spectator domain' links together targets on the basis of sequence searches, but the ligand-binding domain is absent from the identified homologue. To avoid false positives, we were previously forced to use very conservative cut-offs for sequence similarity  No validated domain, ii) only one validated domain (or multiple copies thereof), iii) more than one validated domain. Case i) results in no mapping, case ii) assigns all ligands to the validated domain. In the case iii) that more than one validated domain occurs in a protein we did not assign any mapping. A summary of all co-occurrences of validated Pfam-A domains is provided in Additional file Practically, the mapping was carried out as follows. For all targets in the ChEMBL target dictionary, we collected activities measured in binding assays that are linked directly and unambiguously to a single target.  The activity type was required to be either of the following: Ki, Kd, ICValidation was carried out against data from Uniprot as well as PDBe. Uniprot lists manually curated positions of residues that participate in ligand binding while information about residues in close proximity to the bound ligand can be extracted from PDBe using the algorithm PDBeMotif . BindingIn some few cases, small molecule bioactivities reported in ChEMBL are mapped to Uniprot identifiers that represent fragments of a protein. This might be due to annotation errors, or the lack of a Uniprot entry representing the full-length protein. These cases can be problematic for our mapping. As an example, some activities extracted from an article on phosphodiesterase inhibitors (PubMed 8027992) map to the Uniprot identifier Q864F1. This identifier represents an N-terminal fragment of the pig phosphodiesterase 5, containing only the GAF domain and, crucially, missing the PDEase_I domain. Thus, small molecule binding is incorrectly mapped to the GAF domain. We identified five critical protein fragments in the ChEMBL target dictionary and removed these manually before applying our mapping algorithm. A list of these targets and justification for removal is provided in Additional file http://www.rickwash.com/papers/cscw08-appendix/powerlaw.R to calculate the goodness-of-fit and corresponding p-Value. For the maximum-likelihood calculations we use the functions pareto.lnorm.llr, pareto.exp.llr and pareto.weibull.llr. Visualizations were created using the script plplot.py. All functions except powerlaw.R were provided by Aaron Clauset and Cosma Shalizi http://tuvalu.santafe.edu/~aaronc/powerlaws/.Statistical analysis was carried out in R  unless oWe selected ligands from mappings for 6 Pfam domains and retrieved pre-calculated descriptor values from the compound_properties table within the ChEMBL database. To prepare the data for scaling to unit variance, we excluded as outliers the first and hundredth percentile of each descriptor value distribution (see Additional file https://github.com/fak/mapChEMBLPfam. Pfam domain annotations and estimated domain boundaries for all protein entries were retrieved from http://pfam.sanger.ac.uk/protein/X?output=xml where X is the Uniprot accession of a query protein. The corresponding function can be found as getPfamDomains.py in the code repository. Binding site annotations from Uniprot were retrieved from http://www.uniprot.org/uniprot/X.xml, where X is the Uniprot accession of a ChEMBL target. Residues in close proximity to the bound ligand were retrieved from PDBeMotif using a query submitted to http://www.ebi.ac.uk/pdbe-site/pdbemotif/hitlist.xml. The corresponding deposited functions are called queryUniprot.py and queryPDB.py, respectively. We used SIFTS [The workflow for this study was implemented in python and R. The code is deposited at ed SIFTS  to transed SIFTS  with theThe authors declare that they have no competing interests.Conceived and designed the experiments: JPO, FAK. Implemented the mapping: FAK. Analyzed the data: FAK, RR. Wrote the paper: JPO, FAK.Domain annotations for the ChEMBL target dictionary. Tab-delimited file. The column 'uniprot' provides the Uniprot identifier, the column 'pfam' the Pfam identifier, 'start' and 'end' the start and end positions of the respective domain in the Uniprot sequence.Click here for fileTable of mapped interactions. Tab-delimited file. The column 'activity' provides the value of the ChEMBL field activity_id, 'domain' the mapped Pfam-A domain, 'molregno' the identifier for the small molecule, 'uniprot' provides the Uniprot identifier and 'maptype' indicates whether the protein target is a single- or multi-domain protein.Click here for fileRenderings of small molecule binding at the interface of Pfam-A domains. This is a folder containing graphics in JPG format.Click here for fileSession files of small molecule binding at the interface of Pfam-A domains. Zipped folder containing Qt-MG session files and required PDB files.Click here for fileOutlier selection for PCA. Boxplots show distributions of descriptor values for all molecules in the analysis. Red lines indicate chosen cut-offs for outlier selection.Click here for fileList of conflicts between 'seed' domains occurring within the same target. Tab delimited file. The column 'uniprot' provides the Uniprot identifier, the column 'conflict' the seed domains co-occurring in the specified protein.Click here for fileManually removed protein targets. This is a text file listing all entries that were manually removed before mapping small molecule binding. Reasons for the removal are indicated for each identifier.Click here for file


Von Willebrand factor A (VWA) domains are versatile protein interaction domains with N and C termini in close proximity placing spatial constraints on overall protein structure. The 1.2 Å crystal structures of a collagen VI VWA domain and a disease-causing point mutant show C-terminal extensions that place the N and C termini at opposite ends. This allows a “beads-on-a-string” arrangement of multiple VWA domains as observed for ten N-terminal domains of the collagen VI α3 chain. The extension is linked to the core domain by a salt bridge and two hydrophobic patches. Comparison of the wild-type and a muscular dystrophy-associated mutant structure identifies a potential perturbation of a protein interaction interface and indeed, the secretion of mutant collagen VI tetramers is affected. Homology modeling is used to locate a number of disease-associated mutations and analyze their structural impact, which will allow mechanistic analysis of collagen-VI-associated muscular dystrophy phenotypes. •The structure of a VWA domain (N5) of collagen VI at 1.2 Å is presented•N and C termini of the domain are at opposite ends•The structure with a myopathy-causing mutation shows altered interaction interface•The impact of mutations in collagen VI VWA domains was analyzed Becker et al. describe a crystal structure of a von Willebrand factor A (VWA) domain, which has a C-terminal extension that places the N- and C-termini at opposite ends not seen before for A domains. This allows a “beads-on-a-string” arrangement of multiple VWA domains as observed for the collagen VI α3 chain. Von Willebrand factor A (VWA) domains consist of about 200 amino acid residues and act as interaction modules in many intra- and extracellular proteins, e.g., in copines, integrins, von Willebrand factor, complement factors B and C2, matrilins, and collagens  were identified that are highly homologous to the α3 chain . All colCollagen VI microfibril formation has been studied in molecules made up by the classical chains . In a stCOL6A1, COL6A2, and COL6A3 genes lead to the musculoskeletal diseases Bethlem myopathy (BM) and Ullrich congenital muscular dystrophy (UCMD);  reports 35 missense mutations in the exons encoding the N-and C-terminal VWA domains of the collagen α3 chain. One of these missense mutations, R1064Q in human (R1064Qh) that is located in the N5 domain, was found in an UCMD patient (m), which corresponds to human R1064Qh. We studied the impact of the mutation on the secretion of the single VWA domain and the secretion and assembly of collagen VI tetramers. The structural information was used to model other collagen VI VWA domains and to evaluate the impact of known mutations on the domain structures, thereby providing a basis for genotype-phenotype analysis.To date, the Leiden open variation database  of less than 0.6 Å with the α3N5 domain. The largest deviations result from three- or four-amino acid insertions in the α3N7 and α3N10 domains located in the loop prior to the β6 strand and the α6 helix, respectively. The resulting structures were analyzed for conserved features of the interactions between the core domains and the C-terminal extensions that were seen in the α3N5 domain . The intTo further analyze the C-terminal extension, sequence alignments of tandem VWA domains were performed . In murim in mouse was inserted into the murine collagen VI α3N5 domain by mutagenesis PCR and the crystal structure of the corresponding recombinant protein was determined at 1.2 Å resolution . The difference in crystal packing is likely to contribute to the differences between wild-type and mutant structures in the C-terminal extension. The charge difference in the mutant and the difference in crystal packing also indicate the possibility that this mutation may alter intra- or intermolecular interactions and therefore disturb the assembly of collagen VI. Such surface exposed mutations differ from mutations in the core of VWA domain structures, e.g., the many mutations in the matrilin-3 VWA domain that cause multiple epiphyseal dysplasia (MED) due to endoplasmic reticulum (ER) stress and the unfolded protein response  cells (We studied the influence of the R1061QA) cells A. The wim mutation on secretion and assembly of full-length collagen VI, the mutation was introduced into the murine full-length collagen VI α3 chain (N9-C5 region). The wild-type and the mutated constructs were used for transfection of SaOS-2 cells, which produce collagen VI α1 and α2, but not α3, mRNAs . The point mutations were mapped onto the mouse collagen VI α3N5 domain structure  according to the manufacturer’s instructions . Wild-type and mutated DNA were digested with NheI and BamHI and cloned into a modified pET 15b expression vector (Novagen) containing an N-terminal One-STrEP-tag followed by a thrombin cleavage site. Both constructs were sequenced and used for transformation of E. coli BL21 Rosetta cells (Novagen). Single colonies were cultured overnight at 37°C in 10 ml LB-medium and 50 μg/ml ampicillin for selection. The overnight cultures were used to inoculate 8 l LB-medium containing 50 μg/ml ampicillin and the cultures were grown to A600 = 0.4–0.6 at 37°C. Subsequently, protein expression was induced by adding isopropyl-β-D-1-thiogalactopyranoside (IPTG) to a final concentration of 1 mM and the cultures were incubated overnight at 28°C. After harvesting, the cells were resuspended in 50 ml lysis buffer  and lysed by sonication. Insoluble material was removed by centrifugation at 15,000 rpm and 4°C and the supernatant applied to a Streptactin column (IBA). After washing with lysis buffer, the recombinant protein was eluted with the same buffer containing 2.5 mM desthiobiotin. The One-STrEP-tag was removed by thrombin digestion using a kit (Novagen). Cleaved protein was separated from thrombin and remaining uncleaved material by size exclusion chromatography on a Superdex 75 16/60 column. Peak fractions were pooled, analyzed by SDS-PAGE, and concentrated by ultrafiltration to 14 mg/ml (wild-type) and 15.3 mg/ml (R1061Qm), respectively.The borders of the collagen VI α3N5 domain were chosen according to the exon sequence. The identity between the murine and the human sequence is 85%. The murine sequence was chosen to be able to take advantage of the mouse as a model organism in future experiments. A DNA fragment encoding the murine collagen VI α3N5 domain with 5′-terminal NheI and 3′-terminal BamHI restriction sites was amplified by PCR using the primers 5′-CTAGCTAGCTCAGGTGAAAAGGATGTGGTG-3′ (forward) and 5′-CGCGGATCCTTAACCTGCACCTGTTGAGGGC-3′ (reverse), respectively. After digestion with NheI and BamHI, the PCR fragment was cloned into the pBluescript II KS (+) vector (Stratgene). This plasmid served as a template for a mutagenesis PCR to insert the R1061Qm-mutation [see above]) were cut with NheI and BamHI and inserted into a modified pCEP-Pu vector containing an N-terminal BM-40 signal peptide followed by a One-STrEP-tag (IBA). The murine collagen VI α3 N9-C5 region was generated by PCR and cloned with 5′-terminal SpeI and 3′-terminal NotI restriction sites using the primers 5′-GGACTAGTCTCAGCTGACATTATTTTCCTTATT G-3′ (forward) and 5′-GAATGCGGCCGCTTAAACTGTTAACTCAGGACTACACATC-3′ (reverse). The amplified PCR fragment was ligated into a modified pcDNA6 vector (Invitrogen) containing an N-terminal BM40 signal sequence. To insert the R1061Qm mutation, a cDNA fragment encoding the region between the two internal restriction sites NdeI and SbfI was amplified by PCR using the primers 5′-CCCTAACCACATATGTTAGTGGAG-3′ (forward) and 5′-CCTTAGCTCCTGCAGGGCCCCTTC-3′ (reverse), respectively. This fragment was used as a template for a mutagenesis PCR (see above). The mutated PCR fragment was digested with NdeI and SbfI and ligated into the collagen VI α3 N9-C5 region and subsequently cloned into the modified pcDNA6 vector (Invitrogen). The constructs of the wild-type and mutated N5 domain were used for transfection of 293EBNA cells and the wild-type and mutated α3 constructs were used for transfection of the SaOS-2 human osteosarcoma cell line using FuGENE HD transfection reagent (Promega). Cells were cultured in Dulbecco’s modified Eagle’s medium containing 10% (v/v) fetal calf serum and 0.5 μg/ml puromycin (293EBNA) or 5 μg/ml blasticidin S hydrochloride (SaOS-2) for selection. L-ascorbic acid and L-ascorbic acid 2-phosphate sesquimagnesium salt hydrate were added to SaOS-2 cells every 1–2 days to a final concentration of 0.25 mM and 0.45 mM, respectively.The collagen VI α3N5 domain constructs (wild-type and with R1064QCell extracts and culture medium of transfected and nontransfected 293EBNA cells were reduced with 5% β-mercaptoethanol and subjected to SDS-PAGE on 12% (w/v) SDS-polyacrylamide gels. Cell extracts and culture medium of transfected SaOS-2 cells were supplemented with SDS-containing loading buffer and urea to a final concentration of 2M and subjected to electrophoresis on 0.5% (w/v) agarose/2.4% (w/v) polyacrylamide composite gels  under no2O2.For immunoblots, the proteins were transferred to nitrocellulose. After blocking with Tris-buffered saline containing 5% milk powder (single N5 domain) or 1% BSA and 5% milk powder (α3 N9-C5), the nitrocellulose membrane was incubated with an antibody against the strep-tag (gift from Birgit Kobbe) to detect the single N5 domain or an affinity-purified antibody against the murine collagen VI α3 C terminus to detect the α3 N9-C5 region. Bound antibodies were detected by enhanced chemoluminescence using peroxidase-conjugated swine anti-rabbit immunoglobulin G (Dako), 3-aminophthalhydrazide (1.25 mM), p-coumaric acid (225 mM), and 0.01% Hm mutant was observed in 0.2 M sodium chloride, 0.1 M phosphate/citrate (pH 4.2), 20% w/v PEG 8000 in the 0.1:0.1 ratio. The crystal of collagen VI α3N5 grew to the dimensions of 170 μm × 100 μm × 50 μm, whereas crystals of R1061Qm grew to the dimensions of 100 μm × 90 μm × 40 μm in 1 week. All crystals were cryoprotected with 30% (v/v) glycerol and flash-frozen in liquid nitrogen for storage. X-ray diffraction data were collected at 100 K using the beamline ID24 at Diamond  at a wavelength of λ = 0.97780 with a Pilates 6M detector.Crystallization experiments were performed at room temperature using the sitting-drop vapor diffusion method. A crystal of collagen VI α3N5 was observed in 0.1 M sodium cacodylate (pH 6.5), 1 M tri-sodium citrate using the 0.2:0.1 ratio, whereas a crystal of the R1061Q1 and had unit cell dimensions of a = 37.7, b = 58.6, c = 39.3, alpha = 90°, beta = 113°, gamma = 90°. The Mathews coefficient is 1.74 and the solvent content is 29.4% with one molecule in the asymmetric unit.A complete data set of collagen VI α3N5 was collected to 1.2 Å resolution (0.15° oscillation with 0.2 s exposure time). The data were integrated and processed with iMOSFLM  from them was collected to 1.2 Å resolution (0.15° oscillation with 0.1 s exposure time). The data were integrated and processed with XIA  was modified and all side chain residues pruned to Cβ atoms using the program CHAINSAW in CCP4. The output was used as a search model in PHASER (The structure of VWF A2 (Protein Data Bank code n PHASER  for the n PHASER  and compn PHASER . The inin PHASER . Furtherm mutant was solved using PHASER with the fully refined native structure of collagen VI α3N5. The structure was refined with PHENIX and model built with COOT (m) shows that 92.1 (93.2) % of non-Gly and non-Pro residues are in the most favored regions and 6.7 (5.6) % are in the additionally allowed regions. The remaining 1.2% is due to two residues, R1061 and S1070, which are in the generously allowed regions.The mutant structure R1061Qith COOT . Table 1ith COOT . The RamHomology modeling of the human collagen VI VWA domains was carried out using Modeler 4.12  in UCSF Sequences were downloaded from the ENSEMBL mouse genome browser (GRCm38). For the alignments, the complete preceding VWA domain, the linker region, and the beginning of the next VWA domain were used. Multiple sequence alignments were performed using the PILEUP program of the WISCONSIN PACKAGE version 10.3 (Accelrys), using the parameters GapWeight: 6 and GapLengthWeight: 1 for


Finegoldia magna, which share a common origin and therefore represent an interesting evolutionary system, have been thoroughly studied structurally and functionally. Their albumin-binding sites have been mapped and these domains form the basis for a wide range of protein engineering approaches. By substitution-mutagenesis they have been engineered to achieve a broader specificity, an increased stability or an improved binding affinity, respectively. Furthermore, novel binding sites have been incorporated either by replacing the original albumin-binding surface, or by complementing it with a novel interaction interface. Combinatorial protein libraries, where several residues have been randomized simultaneously, have generated a large number of new variants with desired binding characteristics. The albumin-binding domain has also been utilized to explore the relationship between three-dimensional structure and amino acid sequence. Proteins with latent structural information built into their sequence, where a single amino acid substitution shifts the equilibrium in favor of a different fold with a new function, have been designed. Altogether, these examples illustrate the versatility of the albumin-binding domain as a scaffold for protein engineering.The albumin-binding domain is a small, three-helical protein domain found in various surface proteins expressed by gram-positive bacteria. Albumin binding is important in bacterial pathogenesis and several homologous domains have been identified. Such albumin-binding regions have been used for protein purification or immobilization. Moreover, improvement of the pharmacokinetics, through the non-covalent association to albumin, by fusing such domains to therapeutic proteins has been shown to be successful. Domains derived from streptococcal protein G and protein PAB from  Staphylococcus aureus and is called Ebh  [in vivo. An additional mechanism of albumin binding was recently identified when it was shown that human serum albumin (HSA) adsorbed to bacteria could bind to and inactivate the antibacterial chemokine MIG/CXCL9 (monokine-induced by gamma-interferon/CXC ligand), which is released by activated epithelium [Many gram-positive bacteria express surface proteins with ability to bind serum proteins . The sur Q2FYJ6) , 8. Thes Q2FYJ6) , are in ithelium . This alStreptococcal protein G (SPG), which binds to immunoglobulins and albumins of several species, is expressed on the surface of certain streptococcal strains –13 and iHistorically, the most widespread use of SPG has been as a biotechnological tool mainly used for affinity purification of immunoglobulins exploiting the broad species- and subclass specificity of its immunoglobulin-binding domains , 21. AlbFinegoldia magna (F. magna) has been thoroughly investigated both structurally and functionally [F. magna and, consequently, it is believed to have evolved to bind HSA with higher affinity than its predecessor. In contrast, streptococci expressing G148-ABD have much broader host specificity and this domain binds albumin from several non-primates better than ALB8-GA [Several homologous albumin-binding domains have been identified in surface proteins from different bacterial species. The sequence diversity among these is illustrated by the 16 homologues included in tionally , 25, 26.tionally . G148-ABAccumulated structural data on G148-ABD  and the To localize the binding site, surface exposed residues or combinations of residues pointing in different directions have been substituted with alanine and subjected to a binding analysis to HSA and an evaluation of secondary structure content by circular dichroism spectroscopy . In the in vitro selection systems such as phage display. Similar efforts, for example using the structurally related Z-domain [Both G148-ABD and ALB8-GA are, despite their small size, very stable domains in themselves, without any additional stabilizing features such as bound ions or disulfide bridges. A compact hydrophobic core has been suggested to be responsible for the high melting temperature and the high tolerance to both high and low pH and treatment with guanidium hydrochloride , 31, 32.Z-domain  as a scaZ-domain .The well-defined sequence space that the albumin-binding domains represent offers an opportunity to address sequence determinants for their natural phenotypic variations. It has been proposed that a phenylalanine in position 21 of ALB8-GA  is respoSurprisingly, all selection strategies showed a clear preference for the same variant, called phage-selected domain 1 (PSD-1) . PSD-1 iNot only bacteria can benefit from albumin binding, for example a large number of studies have demonstrated its potential as a mean to achieve longer half-lives of therapeutic proteins . AlbuminD) for HSA of 120 fM [Inspired by the promising features of G148-ABD as a half-life prolonging fusion partner for protein therapeutics, it has been subjected to affinity maturation for HSA to enable further improvements of the pharmacokinetics . In thisf 120 fM , improvef 120 fM . ABD035,f 120 fM . A beneff 120 fM  describein vivo to achieve significantly improved pharmacokinetics of the protein of interest [Y22A, [S19A, Y21A, K23A; [Both G148-ABD and ABD035 have successfully been evaluated as half-life extending fusion partners interest , 45. Intt [Y22A, ); represt [Y22A, . This hat [Y22A, . HoweverA, K23A;  demonstrA, K23A; . The bacA, K23A; . Assays To improve its properties as an affinity ligand for purification or depletion of albumin, G148-ABD has been engineered for improved tolerance to alkaline conditions to withstand harsh cleaning of chromatographic equipment . A straiMeasles virus phosphoprotein P, which is a stable protein framework that was identified based on its structural similarity to the Z-domain and its encouraging physiochemical properties [Novel binding sites can be engineered into a protein domain to achieve a desired molecular recognition function while retaining the favorable biophysical properties of the scaffold protein. The most widespread three-helical protein scaffold is the Z-domain, in which the inherent immunoglobulin-binding site has been randomized to generate libraries of so called Affibody molecules that can be selected to bind a wide range of target proteins and provide affinity proteins for various applications . Anotheroperties .in silico methods [G148-ABD has been used as a scaffold to generate both mono- and bisp methods . These r methods ,  and that the affinity maturation resulted in a roughly 100-fold improved TNF-α-binding. An interesting finding in the variants selected for TNF-α and HSA was a common, charge-switching, K36E substitution that was also observed during affinity maturation of G148-ABD for HSA [The bispecific library has also been screened for binders to tumor necrosis factor alpha (TNF-α) . An initaneously , demonst for HSA . HoweverHER3-3 in HER3-3 binds HER3 with a KD of 10 nM and HSA with 0.4 nM). The binding site on HER3 was shown to overlap with its ligand-binding site, indicating a potential anti-proliferative effect on HER3-overexpressing cells. Currently, variants with sub-nanomolar affinity for both their target protein and HSA are under development (unpublished data). Together, these selections demonstrate that albumin binding can be retained despite randomization of a large number of residues in helix one and three. Up till now no binders with ability to bind albumin and the target simultaneously have been identified and no selections have been designed to address this property. Presumably, simultaneous binding would require a specific geometry of the target and the binding epitope in relation to the albumin-binding site, which has not yet been fulfilled for the currently evaluated target proteins.In an effort to expand the single domain bispecific concept to a cancer-related target protein, binders to the epidermal growth factor receptor 3 (HER3) have been selected . In contA30 and the immunoglobulin-binding GB30 (A77 and GB77 or GA88 and GB88; A88 and GB88 could determine both the fold and function of the domains.Albumin-binding domains and other small domains have proven to be attractive model systems for experimental and theoretical folding studies , 56, 57.ing GB30 . Next, tA88 and GB88 facilitated the design of a new pair of sequences with an impressive 95% identity (GA95 and GB95; A95 and GB95, which only differ in three positions, demonstrated that a single amino acid substitution could cause a conformational switch between the two functionally diverse folds [Analysis of the geometries of the non-identical residues in NMR-structures of Gse folds . A follose folds . These sse folds , 64.in vitro selection of desired variants. Even though more than 50% of the residues have been substituted in these efforts, many generated variants retain the favorable fold and stability of the original domain. Several beneficial sequence modifications have been discovered and structurally important residues that cannot easily be modified have been identified. The current detailed understanding of this defined sequence space provides a basis for further protein engineering efforts. Promising characteristics found in engineered domains might be combined and structural characterization of more variants would be useful for future efforts in this direction. Clever protein engineering strategies applied to a small protein domain with favorable biophysical properties such as the albumin-binding domain provides many exciting future opportunities for biophysicists or bioinformaticians engaged in the relationships between sequence, structure and function of proteins, as well as for protein engineers interested in new therapeutic applications.Despite the small size, albumin-binding domains have successfully been engineered for several purposes. To date, more than a hundred engineered variants with altered specificity, improved affinity or stability and even new binding specificities have been reported. Large libraries of domains with diversified surface patches or shuffled homologous sequences have been displayed on phages, on ribosomes and on the surfaces of bacterial cells to facilitate


KCNH channels form an important family of voltage gated potassium channels. These channels include a N-terminal Per-Arnt-Sim (PAS) domain with unknown function. In other proteins PAS domains are implicated in cellular responses to environmental queues through small molecule binding or involvement in signaling cascades. To better understand their role we characterized the structural properties of several channel PAS domains. We determined high resolution structures of PAS domains from the mouse EAG (mEAG), drosophila ELK (dELK) and human ERG (hERG) channels and also of the hERG domain without the first nine amino acids. We analyzed these structures for features connected to ligand binding and signaling in other PAS domains. In particular, we have found cavities in the hERG and mEAG structures that share similarities with the ligand binding sites from other PAS domains. These cavities are lined by polar and apolar chemical groups and display potential flexibility in their volume. We have also found that the hydrophobic patch on the domain β-sheet is a conserved feature and appears to drive the formation of protein-protein contacts. In addition, the structures of the dELK domain and of the truncated hERG domain revealed the presence of N-terminal helices. These helices are equivalent to the helix described in the hERG NMR structures and are known to be important for channel function. Overall, these channel domains retain many of the PAS domain characteristics known to be important for cell signaling. We have determined the structures of two domains, from the mouse EAG and drosophila ELK channels. We have also re-determined the structure of the PAS domain from the hERG channel at a higher resolution and determined the structure of the same domain without the first 10 amino acids. We have analyzed and compared these structures to establish the existence of potential binding sites for small molecules. We have also defined the structural features that are shared with other PAS domains, as well as the characteristics that are unique to PAS domains in channels.drosophila ELK (dELK) channels were cloned, expressed and purified as previously described PAS domains from mouse EAG (mEAG) and PAS domain from the human ERG domain was cloned, expressed and purified as previously described Crystals of mEAG and dELK were obtained as previously described +/K+ tartrate, 100 mM Hepes pH 7.0) containing increasing amounts of glycerol (5–20%) and 1 mM guaiaretic acid.Crystals of hERG PAS domain were obtained in similar conditions to the previously described Initial crystallization conditions for Δ9-hERG  involved screening at 20°C using commercial formulations. Two crystallization conditions were identified: 0.1 M potassium thiocyanate, 30% (w/v) PEG MME 2000 and 0.15 M potassium bromide, 30% (w/v) PEG MME 2000. Both conditions were optimized by fine-grid and additive screening and larger crystals were obtained at room temperature with 0.1 M potassium thiocyanate, 30% (w/v) PEG MME 2000 and 0.5–2.0% (w/v) benzamidine.HCl.Data were collected at ID14-4 and ID14-1 (ESRF) and PXIII (SLS). Datasets were processed with Mosflm http://sts-fw.bioengr.uic.edu/castp/calculation.php) reveals the presence of two adjacent cavities connected by a ∼2 Å wide gap, but for the purpose of this study they will be discussed as a single feature  . A compa feature . This ca feature . Its totlar face . The polUnlike the cavity in the hERG PAS domain, which is dominated by apolar side-chains, in PAS domains known to bind small molecule ligands, and for which structures of complexes are available, the residues forming the binding cavity quite often include polar residues To better understand the structural features of the cavities present within the hydrophobic core of the KCNH PAS domains we have determined the domain structures from two different channels: the mouse EAG1 (mEAG) channel and the drosophila ELK (dELK) channel. Initial crystallization trials, with domain constructs equivalent to the one defined for the hERG PAS domain structure, failed. Crystals of mEAG PAS domain were obtained by removing the first 26 residues of the domain 10 helix and adjacent regions; the conformation of this whole stretch is similar across the three domains but the stretch is a repositioned in mEAG and dELK relative to hERG. The dELK structure also includes an N-terminal helix packed against the domain β-sheet (discussed below).The asymmetric unit cell of mEAG PAS domain crystals contains four copies which, excluding the N- and C-termini, are very similar to each other (rmsd for main-chain atoms of residues 28 to132 varying between 0.2 and 0.6 Å). In the dELK PAS domain crystals, the asymmetric unit contains two very similar copies . Overall, the PAS domains of hERG, dELK and mEAG show a strong structural similarity , with a 3) (3), one (23 Å3) or none. The cavities detected in dELK do not overlap with the cavity in hERG and, importantly, their small size and apparent instability (the cavities appear and disappear in the different models) lead us to consider that they are not a conserved feature and not related to the binding sites seen in other PAS domains. In support of this conclusion, a recent analysis 3, which most likely reflect small packing defects in the core of the structures. The lack of a preformed cavity in the dELK domain, at the same site as in hERG, appears to result from the presence of several large side-chains in that region  in the hydrophobic core of the structures displays two different side-chain conformations; to account for the possible influence of this flexibility on the volume of any potential cavities, we generated two different models (each with a unique side-chain conformation) for each structure in the asymmetric unit and calculated the volume of cavities by CASTp. The CASTp server analysis revealed three very small cavities in the core of the protein of one of the generated models  , while it region . A largeAs discussed above, in dELK a histidine (H129) replaces the cavity lining phenylalanine present in hERG (F129). The absence of a cavity in dELK leaves the histidine side-chain buried in the domain hydrophobic core surrounded, within 5 Å, by the side-chains of several apolar residues  and two cysteines (C66 and C108) . The sta3 to a maximum of ∼136 Å3  ; this reThe mEAG PAS serine (S65), which replaces hERG C64 in the core of the domain, is positioned near the cavity region and the serine main-chain carbonyl group participates on the cavity lining . HoweverThere are also two other regions of the hERG PAS domain that are of functional interest and which were analyzed in the new structures: the hydrophobic patch on the surface of the β-sheet and the N-terminus of the channel. The hydrophobic patch on the β-sheet of the hERG PAS domain is thought to mediate interactions between the domain and other regions of the channel, while the N-terminus (∼20 residues) has been shown to be crucial for determining the characteristically slow deactivation (closing of the channel gate) seen in the hERG channel.2 in hERG and ∼1500 Å2 in mEAG. In hERG two domains pack almost face-to-face through their β-sheets  which packs its apolar face against the hydrophobic patch on the surface of the β-sheet . While tBased on these observations we generated a construct of the hERG PAS domain that started at residue 10, the Δ9-hERG PAS; this protein was crystallized and we solved its structure at 2.12 Å resolution . While t+ channels.A defining feature of KCNH channels is the presence of N-terminal PAS domains. However, despite many years of functional studies, the role of these domains remains unclear. In this study we have determined the structures of the PAS domains from the drosophila ELK and mouse EAG channels and also a structure of the hERG PAS domain adopting a new conformation. These structures have allowed us to solidify our understanding of the structural properties of PAS domains in KOur analysis of the hERG, dELK and mEAG PAS domain structures revealed strong parallels with other functionally better characterized PAS domains. In many PAS domains the β-sheet mediates interactions, through a patch of hydrophobic residues, with either other PAS domain β-sheets or with non-PAS domain regions Another parallel between the channel PAS domains and other PAS domains 3), which can be considered as defects in the packing of the hydrophobic core of the protein 3) are modest relative to the 730 Å3 of the binding site that holds FMN in the phototropin-LOV1 domain (PDB code 1N9L) 3; PDB code 2QHK- unpublished) or in the DctB sensor domain  3 are uncommon structural features, amounting to less than 5% of the total number of cavities found An issue we have examined in this study is the existence of potential ligand binding sites in the PAS domains of KCNH channels. The structures we have determined provide a mixed response. First, the mEAG and hERG PAS domains display cavities in the same region where other PAS domains have ligand binding sites. In contrast, dELK does not have a preformed cavity; it shows just small openings  channels. Highlighted residues are part of the hydrophobic core of the hERG PAS domain. Residues highlighted in green indicate positions that in dELK, mEAG and zfERG are occupied by polar residues.(TIF)Click here for additional data file.Figure S2Superposition of PAS domain structures from hERG (redbrick) and dELK (blue). Cavity in hERG is shown as redbrick wireframe. Residues in dELK which occupy the space taken by cavity in hERG are shown as blue stick with corresponding atomic Van der Waals volume as a dot representation.(TIF)Click here for additional data file.Figure S3Hydrophobic patch in channel PAS domains. View of the hydrophobic patches on the β-sheets of the PAS domain from the three different channels: a) hERG, b) mEAG and c) dELK. Residues forming patches are shown as stick and are labeled. d) Packing of N-terminal helix against hydrophobic patch in dELK PAS domain. Residues involved in interaction are shown as stick.(TIF)Click here for additional data file.


E. coli histidine kinase reveal how external stimuli drive helical bending motions to control asymmetric movements of the catalytic domains.Step-by-step structures of a prototypical  Escherichia coli response to envelope stress. The structural ensemble, which includes the Michaelis complex, unveils HK activation as a highly dynamic process, in which HAMP modulates the segmental mobility of the central HK α-helices to promote a strong conformational and dynamical asymmetry that characterizes the kinase-active state. A mechanical model based on our structural and biochemical data provides insights into HAMP-mediated signal transduction, the autophosphorylation reaction mechanism, and the symmetry-dependent control of HK kinase/phosphatase functional states.Histidine kinases (HKs) are dimeric receptors that participate in most adaptive responses to environmental changes in prokaryotes. Although it is well established that stimulus perception triggers autophosphorylation in many HKs, little is known on how the input signal propagates through the HAMP domain to control the transient interaction between the histidine-containing and ATP-binding domains during the catalytic reaction. Here we report crystal structures of the full cytoplasmic region of CpxA, a prototypical HK involved in  Bacteria use two-component signal transduction systems (TCSs), composed of a histidine kinase (HK) and a downstream response regulator (RR), to perceive a broad range of external stimuli and trigger an appropriate response. Prototypical HKs are transmembrane homodimeric receptors with an external sensor region coupled to a cytoplasmic catalytic core through an adaptor HAMP domain. By a mechanism that is still poorly understood, the external input signal propagates through the HAMP domain to control the activity of the catalytic domain, which adds a phosphate tag, first to the HK itself (“autophosphorylation”), ready for subsequent transfer to the RR. In this study, we report the first detailed structures of the full cytoplasmic domain of a prototypical HK, CpxA, which is involved in the detection and response to damage of the cell envelope of Escherichia coli. The structures provide snapshots of different kinase states along the autophosphorylation reaction. Our combined genetic, biochemical, and structural data point to a mechanical model for HK activation in which the input signal induces coordinated helical motions that regulate catalysis by asymmetrically repositioning the catalytic domains. Bacteria commonly use two-component signal transduction pathways to couple environmental stimuli to adaptive responses HKs are homodimeric receptors with a modular architecture, which in its simplest form consists of a sensor domain and a cytoplasmic transmitter core. Whereas the signal-dependent sensor domains are highly variable, the transmitter core is more conserved. It contains a dimerization and histidine phosphotransfer (DHp) domain coupled to a catalytic ATP-binding (CA) domain. Mainly depending on the cellular location of the sensor domain , a wide variety of HK architectures exists Escherichia coli CpxA, the HK component of the Cpx signaling system that regulates an envelope stress response in E. coliin vivoin vitroTo gain insight into the mode of action of prototypical HKs, we chose to focus on E. coli CpxA (CpxAHDC), encompassing the HAMP signaling domain (residues 188–237) and the DHp and CA domains of the catalytic core (residues 238–457), has been produced as recombinant protein for structural studies (HDC (or the point mutant CpxAHDC_M228V) in complex with nucleotides have been determined in five distinct crystalline environments  linked by a long connector  from both protomers also assemble into a four-helix bundle (a and d are occupied by hydrophobic residues. Besides the presence of a heptad repeat stutter at Leu232 2) (3 connects through a short flexible linker (residues 300–304) to the CA domain  , in a veA domain . These cA domain  that incHDC is highly asymmetric, not only by a different orientation of the CA domains, but also as a consequence of two potential bending points in the central helix α2  is retained in a fixed—inactive—conformation close to the DHp helices (α2 from subunit B and α3 from subunit A) through a relatively large contact interface , the other CA domain with apparent unrestrained mobility adopts disparate orientations (2) corresponds to the autophosphorylating Michaelis complex (see below). This strongly suggests a highly dynamic autophosphorylation process, leading primarily to a single phosphorylation event per homodimer, a feature already described for various HKs in vitro autokinase activity assays show that CpxAHDC phosphorylation is never complete . It is interesting to note that a conserved glutamate at the equivalent position of CpxA Asn356 acts as a general base in the catalytic reaction of ATPases from the GHKL superfamily, which share a similar ATP-binding domain with HKs Also important is the interaction between Glu249 and Asn356 across the DHp–CA interface , which ctrans-autophosphorylation for CpxA  and VicK  and residues Leu242, Ile246, and Leu250 from helix α2 (in the opposite monomer), accounting for a larger DHp–CA domain interface. Interestingly, some of these residues correspond to the a and d core positions of the DHp coiled-coil, which become partially accessible in one of the monomers due to the asymmetric conformation (see below).In addition to the polar interactions described above, two hydrophobic residues from the CA domain (Phe403 in the F box and Leu419 in the G2 box) play a key dual role in stabilizing the DHp–CA interface for both the active and inactive CA conformations . In the HDC homodimer exhibited half-occupation of the active site in some crystal forms, and in these cases, only the less mobile CA domains  consistently displayed a bound nucleotide covered by the lid loop  and therefore displays constitutive kinase activity, was randomly mutagenized and transformed into a cpxA-null strain background. In these cells, the high β-galactosidase activity of the transcriptional fusion (correlated to the kinase activity) provided a means to isolate intragenic suppressors that confer a kinase-deficient/phosphatase-dominant  phenotype, easily monitored on X-gal containing plates. From 48 Lac− colonies examined, the identified mutations were reconstructed into the wild-type cpxA gene and their in vivo activity was evaluated , which partially disrupts the overall HAMP structure. Thus, in contrast to wild-type CpxAHDC, CpxAHDC_M228V is mainly dimeric in solution, with a relatively constant Rg value at different protein concentrations  of the HAMP domain, we set up a genetic screening to search for mutations that affect the CpxA kinase activity valuated . The strvaluated . In vitring CpxR , at leasing CpxR . Becauseing CpxR . Consisttrations .2 helix, the overall bending movement would arise from segmental helical mobility. Thus, the movements of the central part of helix α2  in each monomer differ from those of the HAMP domain  and the membrane-distal part of the DHp domain , both of which rotate as separate rigid bodies. As a consequence, in the asymmetric (kinase-active) state, the C-terminus of α3 in one monomer moves away from the central part of α2 in the other monomer, thus partially exposing hydrophobic core residues  and expressed in E. coli BLI5 cells. His-tagged CpxAHDC was purified by immobilized metal affinity chromatography followed by gel filtration using standard procedures. For the production of seleno-methionyl (SeMet) CpxAHDC, the same plasmid was transformed into the autotrophic E. coli B834 (DE3) strain. Differing only in the growth media, SelenoMet Medium (MDL), and L-selenomethionine (50 mg/L) instead of LB, SetMet proteins were purified exactly as the unlabeled ones. Mass spectrometry was used to confirm SeMet incorporation. Full-length CpxA was expressed, solubilized, and purified as described previously CpxAPurified proteins were concentrated using ultrafiltration VivaSpin devices  to ∼15 mg/ml prior crystallization trials. Crystals were obtained by vapor diffusion at 18°C. All crystal forms grew under similar crystallization conditions , with the exception of the two monoclinic forms, which were obtained using a solution containing 100 mM Tris-HCl (pH 8.5), 25%(w/v) PEG3350, and 200 mM lithium sulphate as precipitant. In most of the cases, crystals appeared in a few days and reached their maximum size within 2 wk.XDSPointless, and scaling with Aimless from the CCP4 software package Data were collected at ESRF and Soleil synchrotron beamlines . Data we121) and hexagonal (P6122) crystal forms. Se atom substructure and phases were estimated using the AutoSol wizard of PHENIXCoot1) was solved by SAD from a Pt derivative dataset at 4.1 Å resolution. Heavy atom positions and phases were estimated using truncated data at 6.5 Å resolution  with the AutoSol wizard. Despite the poor quality of the experimental map, it was possible to locate the CA domains and build a main-chain trace for the rest of the protein. Given the nonisomorphism between the Pt-derivative and the native dataset at 3.65 Å resolution, an extensive rigid body refinement was necessary to reorient the three dimers present in the native ASU prior to further refinement. Monoclinic crystal forms were determined by molecular replacement with PhaserBusterMolProbityPyMOLDiffraction data from Se-labeled protein crystals were used to solve the structures of the trigonal  glycerol, and 0.5 mM TECP.SAXS data were collected at 20°C at beamline BM29 at the ESRF. Data reduction and analysis following the standard procedures were performed using the ATSAS program package cpxA from pIV3cpxA cpxA about 1.5-fold in strains grown in LB at 37°C in the absence of arabinose . The deletion of the periplasmic sensor domain of CpxA was made by the one-step site-directed deletion method 5′-ATCTAGATTCACCGCTATTACTGCTGATTGTCACCATG-3′ and 5′-TAGATCTAACCCATTGTAGTTTTGGTTGTAGTTGTG-3′. The PCR fragment was first treated with DpnI, and then with XbaI before ligation and transformation. The resulting plasmid, pLCBAΔP, encoded a CpxA variant in which the residues 29–163 are substituted by NLDS. Error-prone PCR was performed using the GeneMorph II Random Mutagenesis kit (Agilent Technologies) according to the manufacturer's instructions. Amplification using about 325 ng of cpxAΔP gene as DNA template and 20 thermal cycles was performed to aim for 1∼3 mutations/kb. The purified PCR fragment was digested, ligated into pLCB, and transformed into NS54 E. coli strain. Approximately 20,000 transformants were platted on LB-agar containing X-gal and 48 white colonies were picked for confirming the linkage of the Lac− phenotype to the plasmid. After DNA sequencing, single suppressor mutations were moved by site-directed mutagenesis on the wild-type cpxA gene cloned into pLCBA. To validate the genetic analysis, β-galactosidase activities conferred by the single mutant cpxA alleles were assayed in vivo in NS54 strain.Plasmid pLCBA was constructed by subcloning NS54 cells harboring the various pLCB derivatives were grown overnight in LB medium containing chloramphenicol at 37°C, subcultured (1∶100) into 5 ml of the same medium, and then grown to midlog phase at 37°C. The β-galactosidase activity of permeabilized cells was assayed as described previously HDC and phosphotransfer from full-length CpxA to CpxRN (receiver domain) were assayed by Phos-tag acrylamide gel electrophoresis. Autokinase activity assays on full-length CpxA (as Brij35 complexes) were performed using radioactive ATP as described 2) was phosphorylated with 100 µM ATP at 25°C for 20 min. Then, purified CpxRN was added to the reaction to a final concentration of 20 µM. Samples were withdrawn at various time intervals, mixed with SDS sample buffer, and kept on ice until all reactions were completed. Phospho-proteins were separated by Phos-tag acrylamide gel electrophoresis. Polyacrylamide gels were polymerized with 25 µM Phos-tag acrylamide and 50 µM MnCl2. Following electrophoresis, gels were stained with Coomassie blue and analyzed by densitometry using the software Quantity One (Biorad). Data were fitted using a nonlinear regression with program Kaleidagraph (Synergy Software).Autokinase activity on soluble CpxAHDC–ADP, orthorhombic C2221 form), 4BIV , 4BIW , 4BC0 , 4BIX , and 4BIY .The crystal structures of CpxA-nucleotide complexes described in this article have been deposited in the Protein Data Bank under accession numbers 4BIU  The trigonal crystal form was solved by SAD using Se-labeled protein crystals. Anomalous difference Fourier electron density map (yellow mesh) is contoured at the 5 σ level. Selenomethionine residues are shown as sticks. (B) MR-SAD density modified electron density map (blue mesh) calculated using structure factor anomalous differences and a partial model omitting the HAMP (residues 188–237). Final model is superposed to this unbiased electron density map contoured at the 1.5 σ level.(TIF)Click here for additional data file.Figure S2Structural superposition of the CpxA HAMP domain with those of Af1503 (TIF)Click here for additional data file.Figure S31. (B) Experimental SAXS curves for wild-type CpxAHDC at different protein concentrations in the presence of 5 mM ADP. (C) Same for the point mutant CpxAHDC_M228V. (D) Linear dependence of the radius of gyration (Rg) as a function of protein concentration for CpxAHDC (green circles) and CpxAHDC_M228V (blue circles).(A) Tetrameric form of CpxA (dimer of dimers) as observed in the hexagonal and monoclinic crystal forms. Formation of these tetramers was found to sterically interfere with the positioning of HAMP helix α(TIF)Click here for additional data file.Figure S4Cartoon representation of the ATP-binding CA domain. Highlighted in colors are the highly conserved sequence motifs  in the GHKL superfamily.(TIF)Click here for additional data file.Figure S5HDC (left) and wild-type Af1503 HAMP–EnvZ DHp chimera (right).A similar helical core bending was observed in the crystal structures of CpxA(TIF)Click here for additional data file.Figure S6HDC in complex with ATP (yellow) crystallized in the trigonal space group P3121 is very similar to that observed in the hexagonal (P6122) crystal form for either the wild-type CpxAHDC–ATP (pink) or the point mutant CpxAHDC_M228V–AMPPNP (green) complexes. The catalytic core (residues 238–455) of CpxAHDC–ATP  and CpxAHDC_M228V–AMPPNP  crystal structures can be superposed with an RMSD of 1.36 Å. More significant changes are observed, however, for the N-terminal helix of the HAMP domain due to different crystal packing environments.Structural superposition reveals that the conformation of the catalytic core of wild-type CpxA(TIF)Click here for additional data file.Figure S7HDC in complex with AMPPNP .Protein–nucleotide hydrogen-bonding interactions as observed in the crystal structure of CpxA(TIF)Click here for additional data file.Figure S8The structural superposition of CpxA DHp domain (in green) and CheA P1 domain  reveals a spatially equivalent glutamic acid that makes hydrogen-bonding interactions with Nδ of the catalytic histidine and serves to enhance nucleophilic catalysis. However, the two proteins display a different topology: whereas the two residues in CpxA are part of the conserved H-box in helix α2, they belong to different helices in CheA.(TIF)Click here for additional data file.Figure S9trans-autophosphorylating CpxAHDC  and (B) cis-autophosphorylating VicK (4I5S) crystal structures.Cartoon and schematic representations of the DHp four-helix bundle assembly and CA domain positioning in (A) (TIF)Click here for additional data file.Figure S10HDC_M228V homodimer crystallized in the monoclinic C2 crystal form . The green mesh corresponds to a 2 Å resolution σA weighted difference electron density map (mFo-DFc) contoured at the 3 σ level. The ADP molecule and the Mg2+ ion  were omitted from the model before map calculation. Also shown are residues Phe403 and Leu419 engaged in the CA–DHp interface. It can be argued that the presence of ADP (instead of ATP or AMPPNP) in the crystals might account for the observed half-occupancy. Against this hypothesis, however, the structure of CpxAHDC in complex with AMPPNP  showed the same half-occupancy pattern.Half occupation of the ATP binding sites. Cartoon representation of the single occupied ADP-binding site in the CpxA(TIF)Click here for additional data file.Table S1HDC and CpxAHDC_M228V SAXS-derived parameters.CpxA(DOCX)Click here for additional data file.


Diflavin reductases are essential proteins capable of splitting the two-electron flux from reduced pyridine nucleotides to a variety of one electron acceptors. The primary sequence of diflavin reductases shows a conserved domain organization harboring two catalytic domains bound to the FAD and FMN flavins sandwiched by one or several non-catalytic domains. The catalytic domains are analogous to existing globular proteins: the FMN domain is analogous to flavodoxins while the FAD domain resembles ferredoxin reductases. The first structural determination of one member of the diflavin reductases family raised some questions about the architecture of the enzyme during catalysis: both FMN and FAD were in perfect position for interflavin transfers but the steric hindrance of the FAD domain rapidly prompted more complex hypotheses on the possible mechanisms for the electron transfer from FMN to external acceptors. Hypotheses of domain reorganization during catalysis in the context of the different members of this family were given by many groups during the past twenty years. This review will address the recent advances in various structural approaches that have highlighted specific dynamic features of diflavin reductases. Flavoproteins represent 1%–3% of all proteins present in prokaryotic and eukaryotic genomes  and abouThis diflavin reductases family includes the NADPH-cytochrome P450 reductase , the flavoprotein subunits of bacterial sulfite reductase  and of the mammalian methionine synthase reductase , the reductase part of the nitric oxide synthase  and of cytochrome P450-BM3  and the novel reductase 1 cytoplasmic protein (NR1).c (cyt c) reductase . A. A130]. ntal CPR .More recently, the analysis of chimeric CPR combining domains from yeast and human CPR highlighted the role of interdomain interface and recognition in diflavin reductase activity and conformation . The eleInterestingly, the two opposite chimeras exhibit kinetic behaviors analogous to those of the rat nNOS mutants in which the modification of a single residue, Arg1229, located on the interface between the flavinic domains, destabilized the interdomain recognition by disrupting one specific electrostatic interaction . Like chThese chimeras combining the three NOS isoforms, different CPR or the NOS and the CPR clearly demonstrate the capacity of distant diflavin reductases to exchange individual domains while totally or partially preserving their catalytic activities. CPR and NOS, and probably other diflavin reductases, are not only sharing high structural homologies. The presence of acceptable ET capacities in these different chimeras prove that, despite the architectural complexity of the regulatory elements present in NOS but absent in the other members of the family, the ET mechanisms of all diflavin reductases may involve the same structural reorganization steps. It seems then reasonable to propose that the dynamical events hypothesized from the various biochemical analyses of NOS and CPR may as well exist in all other diflavin reductases.The above-mentioned results did not constitute a solid proof of the dynamical behavior of diflavin reductases, but they eventually cast a strong support of the existence of domains movements. In addition, the parameters controlling those movements, if partially understood in the case of the NOS, remained totally unknown for the other members of the diflavin reductase family ,92. Someet al.[236TGEE239, PDB ID: 3ES9), crystallized with three molecules in the crystallographic cell. As illustrated in c reductase activity, most probably due to the incapacity of the catalytic domains to come to a position competent for interflavin ET. Consequently, the detection of this new conformation on an incompetent form of the enzyme raises the question about its existence in the course of the catalytic cycle.In 2009, two groups published novel crystallographic structures of mutant or chimeric CPR demonstrating the existence of alternate conformations different than the hitherto unique closed conformation ,137. Thec), but nevertheless remained capable of reducing other artificial and natural acceptors such as ferricyanide and P450-3A4 with a complete conservation of the electron pathway. Interestingly, the backbone of YH is almost completely conserved (RMSD 0.9 Å and 0.46 Å for the FAD and FMN domains respectively) except for the linker domain for which only a limited number (3) of residues have their Psi and Phi angles completely changed. An analysis of the interdomain interface of YH CPR [On the other hand, our group published the structure of one of the abovementioned yeast-human chimeric CPR (YH)  values and predicted RDC values using the closed structure. This NMR study unambiguously proved that the CPR adopts the same conformation in solution and in the crystal environment. Interestingly, we also showed the high flexibility of the linker region between the FMN and connecting domain in the nanosecond timescale. The CPR can thus be described as two beads (FAD and FMN domains) forming a stable interface bridged by a flexible string. Our results are in sharp contrast with the previous SAXS/NMR analysis. This might be explained by slightly different (but yet unidentified) experimental conditions. Since the CPR enzyme used for the NMR study is fully active, we postulated that the opening of the structure required in the course of the reaction must be provoked by some (yet unknown) molecular trigger such as substrate binding or flavin reduction.Lastly, our groups revisited the solution properties of CPR by NMR . This la+) binding while open states are favored in the absence of the bound coenzyme. However, ELDOR spectroscopy describes conformational distributions exhibited by the proteins just before their internal motions are quenched by rapid freezing at 80 K. Therefore, the observed distance distribution may not represent distances between points on heavy atoms, but rather a weighted mean of the unpaired electron spin density distribution over the flavosemiquinones in absence of domain mobility. Nonetheless, the distance variations observed upon NADP+ binding and salt effects were in agreement with the SAXS experiments [Analysis of CPR dynamics using electron-electron double resonance (ELDOR) allowed a fine description of the conformational sampling of human CPR in the di-semiquinone state (one electron reduced FMN and one electron reduced FAD) . The auteriments .+-bound CPR are in good agreement with the observed distances in the available closed crystal structures  and wit. The la that converge towards the existence of a wide conformational space that the human CPR may sample in solution. Furthermore, the energy landscape appears to be largely influenced by substrate binding or flavin reduction, which may reveal the complex domain rearrangement during the catalytic reaction. However, despite the huge recent progress, a thorough characterization of the CPR is still lacking that may include a better understanding of the structure and dynamics of the extended conformation and its interactions with partners and a more precise description of the time-dependent conformational change during the catalytic cycle. Similarly, the concepts developed for the CPR will have to be tested for the other related proteins.kInt and that the deshielded state is the only one competent for external ET (rate constant kExt). Using such a simple kinetic model linking for the first time conformational sampling and electron transfer they have been able to reproduce some experimental data on NOS. For example, this model explains how the slow conformational equilibrium, and hence the supposed conformational motion of the FMN domain, directly controls the intensity of the slow and fast phase of FAD reduction and the electron flux to cyt c[versus the fraction of (de)shielded state which nicely fits experimental data obtained on various nNOS forms [+ release steps are all integrated in a single step (kInt). In addition, there are experimental evidences for significant effects of flavin reduction and cofactor binding on the conformational equilibrium, which are not taken into account in the model. It seems then possible to improve the kinetic model at the expense of additional data collection for validating the increased number of elementary steps. There is no doubt that future investigations on the coupling between conformations sampling and kinetic properties of diflavin reductase will provide invaluable clues on the microscopic behavior of the enzyme at work.Different models have been proposed in the past to describe the successive electrons transfers ,144, how to cyt c. In addiOS forms . HoweverStarting from the first published CPR structure, in 1997, the scientific community has tracked avidly alternate architectures of diflavin reductases that would be compatible with ET to external acceptors. We have now plenty of evidences that, at least for CPR and NOS, reorientation of the FMN and FAD domains occurs at some stage during the electronic cycles. The alternative model described with the yeast CPR and involving the rotation of the FMN cofactor instead of the FMN domain seems not to fit with the very recent evidences of domain movements in human and rat CPR. As of today, the model involving conformational changes is really favored. The fact that several structural organizations were characterized by different methods seems to indicate that diflavin reductases may exist as a mixture of some discrete or continuous conformations in equilibrium. This equilibrium appears to be easily disturbed by mild change in working conditions, at least for the oxidized form of the CPR, suggesting that great care should be taken when comparing structural studies carried out in different laboratories. As a result the published crystallographic structures probably represent the most populated conformations depending on the enzyme considered (wild-type or mutant). Even if these crystallographic structures do not correspond to highly populated conformers in solution, they still demonstrate that reorientation of the catalytic domains occur with almost no change within the backbone of the domains themselves. This is also true for the connecting domain of CPR for which no specific role has yet been assigned. This connecting domain, as well as the various regulatory domains of NOS or MSR having more complex catalytic regulation, probably plays a very important role in the sensing mechanisms and in the control of the domains structural reorganization. The surfaces of these regulatory domains, being in direct contact with both catalytic domains, are probably the place where this information exchange takes place.That being said, we still lack information on the possible sensing mechanisms and how they are transmitted within the enzyme prior any structural reorganization. The involvement of cofactors and redox potential were described. Whether these factors are involved in changing existing conformational equilibria (by selectively binding to and lowering the energy of extended conformations) or directly impact structural points that could trigger domain reorganization is still under debate and will probably be the subject of intense and ardent research in the next years. Another open question concerns the role of the physiological acceptors in the control of these movements. From the simpler model of CPR to the more evolved NOS, the regulation of ET in diflavin reductases is of crucial importance for the enzyme and most probably to avoid electron leakage to oxygen and the consequent production of toxic ROS. It is likely that the presence or absence of these acceptors drive the equilibrium between the various conformations and therefore may also constitute some of the necessary triggers. Such propositions will probably constitute future research directions in the field of diflavin reductase mechanisms.


Synthetic lethal genetic interactions among proteins have been widely used to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions is still unclear.In this study, we demonstrated that yeast synthetic lethal genetic interactions can be explained by the genetic interactions between domains of those proteins. The domain genetic interactions rarely overlap with the domain physical interactions from iPfam database and provide a complementary view about domain relationships. Moreover, we found that domains in multidomain yeast proteins contribute to their genetic interactions differently. The domain genetic interactions help more precisely define the function related to the synthetic lethal genetic interactions, and then help understand how domains contribute to different functionalities of multidomain proteins. Using the probabilities of domain genetic interactions, we were able to predict novel yeast synthetic lethal genetic interactions. Furthermore, we had also identified novel compensatory pathways from the predicted synthetic lethal genetic interactions.The identification of domain genetic interactions helps the understanding of originality of functional relationship in SLGIs at domain level. Our study significantly improved the understanding of yeast mulitdomain proteins, the synthetic lethal genetic interactions and the functional relationships between proteins and pathways. Defining the functional relationships between proteins is one of the important tasks in the post-genomic era. A classical approach to understand gene functional relationships is producing combination mutant in two genes to observe genetic interactions . GeneticRepresenting the structures and functions of proteins, protein domains are usually regarded as building blocks of proteins and are conserved during evolution. The mutation of a gene causes the loss of function of its protein product, which may accredit to the loss of protein domains in the protein product. Then, the effect of the mutation of two genes may be caused by the loss of protein domain combinations in both protein products. We refer the phenomenon in which combined effect of mutations of two domains in two proteins differs from individual effects of mutation of each domain as domain genetic interactions. The domain genetic interactions may correlate to SLGIs. We may use the domain genetic interactions to explain and predict the SLGIs. Furthermore, in multidomain proteins, different domains may fulfill different functions independently or collaboratively. Although genetic interaction analysis provides a promising method to understand the functional relationship between proteins , we cannGenetic interactions are usually identified by mutant screens . RecentlIn our previous study , we perfBy assuming the independences among domain genetic interactions, we estimated the probabilities of domain genetic interactions using the Maximum Likelihood estimation (MLE) method. The probability of a domain pair indicates its propensity to genetically interact. The high probability of a domain pair imply that number of SLGIs including the domain interaction is high comparing to the number of protein pairs including the domain interaction that are not genetically interacted. Then, we calculated an evidence score E  for eachhttp://www.genenetworks.net, for searching and downloading. We first selected the significant domain genetic interactions with E scores greater than or equal to 2.0, which corresponds to an approximate seven fold drop of the probability of SLGIs if this domain genetic interactions is excluded. Then, we selected the domain genetic interactions with probability greater than 0.5 even though they have low E score values. Totally, we obtained 3848 domain genetic interactions of 1027 domains. Table We first applied the MLE approach to the 7475 genetic interactions with both proteins having protein domains. We were able to assign probabilities and E scores to 11,189 domain pairs. Those domain genetic interactions are available on our website, To investigate the relationship between domain genetic interactions and the domain physical interactions, we compared the 3848 significant domain genetic interactions with the domain physical interactions from the iPfam database . There aTo obtain an overview of the domain genetic interactions, we modeled the domain genetic interactions as a network, in which each node represents a domain and each link represents a genetic interaction between two domains. Then, we examined the properties of this domain genetic interaction network. The average connectivity of the network is 7.392. The domain PF00022 (Actin) has the highest connections of 186. The average shortest path among all nodes is 3.31. Comparing the size of nodes, this number is very small. Furthermore, the average node clustering coefficient of the network is 0.159. These properties indicated that the domain genetic interaction network has the small world property . These rMost proteins are multidomain proteins, which are created as a result of different genetic events, such as insertions and duplications ,26. MultFigure We also investigated the domain genetic interactions of SLGIs between SGS1 and other proteins. We found that only the PF00570 (HRDC domain) of SGS1 has significant genetic interactions with other domains. The results implied that certain functionality of SGS1 may be only due to its HRDC domain, rather than its DEAD/DEAH domain and helicase conserved C-terminal domain. Previous study showed that the HRDC domain of SGS1 is required for its cellular functions involving topoisomerases . Thus, tHaving established that there is a strong correlation between domain genetic interactions and SLGIs, we explored to predict the probabilities of protein pairs to be SLGIs using probabilities of domain genetic interactions. We were able to assign 599752 protein pairs with probabilities greater than 0. Table S1  . The PfaPm,n and domain genetic interaction Di,j as random variables. The Pm,n = 1 if two proteins i and j genetically interact and Pm,n = 0 otherwise. The Di,j = 1 if two domain i and j genetically interact and Di,j = 0 otherwise. We estimated the probabilities of potential domain interactions Pr by maximizing the likelihood of observed genetic interactions using the Expectation-Maximization (EM) algorithm  and E   using thi,j = 1) using the E and E as following (Maximization step):Then, we calculate the Pr if and only if at least one domain pair from the two proteins genetically interact . Then, we calculated the probability of two proteins genetically interacting Pr as following:We assumed that two proteins genetically interact (A pair of proteins was predicted to be SLGI only if its probability is higher than a predefined threshold.FL designed research. BL implemented the idea. FL, BL, WGC and JZH analyzed the results. All authors have read and approved the final manuscript.Table S1. Number of predicted SLGIs by MLE approach using different posterior probability thresholdClick here for fileTable S2. Summary statistics of distribution of the correlation coefficient between the cell cycle expression profiles of genetic interacting proteinsClick here for fileTable S3-5. Summary statistics of distribution of the similarities between the GO biological processes, cellular component and molecular function of genetic interacting proteinsClick here for file


When Cdk5 gene deletion was induced in nestin-expressing cells and their progeny during the wave of cortical and hippocampal gliogenesis (P2-P4), significantly fewer YFP+ cells were evident in the cortex, corpus callosum, and hippocampus. Phenotypic analysis revealed the cortical decrease was due to fewer YFP+ astrocytes and oligodendrocytes, with a slightly earlier influence seen in oligodendrocytes vs. astrocytes. This effect on cortical gliogenesis was accompanied by a decrease in YFP+ proliferative cells, but not increased cell death. The role of Cdk5 in gliogenesis appeared specific to the early postnatal period, as induction of recombination at a later postnatal period (P7-P9) resulted in no change YFP+ cell number in the cortex or hippocampus. Thus, glial cells that originate from nestin-expressing cells and their progeny require Cdk5 for proper development during the early postnatal period.The early postnatal period is a unique time of brain development, as diminishing amounts of neurogenesis coexist with waves of gliogenesis. Understanding the molecular regulation of early postnatal gliogenesis may provide clues to normal and pathological embryonic brain ontogeny, particularly in regards to the development of astrocytes and oligodendrocytes. Cyclin dependent kinase 5 (Cdk5) contributes to neuronal migration and cell cycle control during embryogenesis, and to the differentiation of neurons and oligodendrocytes during adulthood. However, Cdk5’s function in the postnatal period and within discrete progenitor lineages is unknown. Therefore, we selectively removed Cdk5 from nestin-expressing cells and their progeny by giving transgenic mice (nestin-CreERT2/R26R-YFP/CDK5 Dysregulation of oligodendrocytes and astrocytes is implicated in a growing number of neurological disorders –3. UnderSome general aspects of glia development during the early postnatal period have been established. For example, postnatal astrocytes and oligodendrocytes emerge from a variety of precursors, including radial glial cells, glioblasts in the subventricular zone, oligodendrocytic-specific progenitors, and – in some brain regions like the cerebral cortex – local sources –10. Oligin vitro evidence suggests Cdk5 may also be involved in glial development. For example, Cdk5 is expressed in both oligodendrocytes and astrocytes  ±s.e.m WT: 35.3±2.2; iCdk5: 35.8±3.5; p>0.05) or at P21 . Moreover, when the total cortical volume was factored into the total number of GFAP+YFP+ astrocytes and RIP+YFP+ oligodendrocytes, there was an identical reduction in astrogenesis and oligodendrogenesis as seen in One possible explanation for reduced gliogenesis in iCdk5 mice is reduced cortical volume. However, the total volume of the cortex did not differ between WT and iCdk5 at P14 , we examined the proportion of YFP+ cells that expressed Ki67, an endogenous proliferation marker of neuronal and glial precursors –57, and Having established that loss of Cdk5 from nestin-lineage cells via Tam from P2-P4 led to fewer cortical YFP+ astrocytes and oligodendrocytes, we turned our attention to 2 other regions of ongoing gliogenesis: the hippocampus and corpus callosum . The redSince inducible deletion of Cdk5 from nestin-lineage cells via Tam P2-P4 influenced YFP+ cells in ongoing regions of gliogenesis, we hypothesized deletion of Cdk5 from nestin-lineage cells after cessation of most gliogenesis would result in no change in YFP+ cell numbers. To test this, mice were given Tam via Tam P7-P9 and killed P14 or P21 , and thein vivo regulation of glia during the early postnatal period. It is not clear what molecular and genetic factors determine how astrocytes and oligodendrocytes populate the brain during the first weeks of postnatal life in mice. It is also unclear if the many key transcription factors, growth factors, and genetic regulators in embryogenesis are also important during the early postnatal period. An example of a protein having discrete, developmental-stage specific roles is Cdk5. Cdk5 was initially thought to be specific for neuronal development during embryogenesis [in vivo, especially in the early postnatal period. At least 2 obstacles prevented prior exploration of the regulation of postnatal gliogenesis by Cdk5. First, constitutive knockouts of Cdk5 or its activators, like p35, display increased perinatal mortality and severe developmental abnormalities [While much is known about glial and neuronal development during embryogenesis ,5,59, faogenesis , but subogenesis ,60. Despogenesis –63, it imalities ,47,64, wmalities ,32, therin vivo. As discussed below, our results confirm and extend prior work that astrocytes and oligodendrocytes are generated from nestin-expressing progenitors during the first postnatal week. Our results also show that Cdk5 in nestin-expressing progenitors are important for proper development of astrocytes and oligodendrocytes in early postnatal life.We used an inducible knockout of Cdk5 in nestin-expressing cells and their progeny ,31 to clA large body of evidence shows that astrocytes and oligodendrocytes are generated during the early postnatal period . OligodeTo this end, we utilized nestin-CreERT2/R26R-YFP mice for lineage tracking of YFP+ cells derived from nestin-expressing progenitors. We show that glial generation from nestin-lineage progenitors is confined to the first postnatal week, as we observe more than 50-fold decrease in YFP+ cells in P21 cortex between earlier Tam administration at P2-P4 and later Tam administration at P7-P9. These results support prior work showing that both oligodendrocytes and astrocytes are generated from nestin-expressing cells ,65 and iin vivo role of Cdk5 in early stages of postnatal gliogenesis was previously unknown. Here we find that inducible deletion of Cdk5 from nestin-expressing cells during the early postnatal period ultimately results in fewer recombined astrocytes and oligodendrocytes. The decrease in recombined glial cells was seen in 3 regions undergoing gliogenesis – the cortex, CA1 hippocampal region, and corpus callosum – suggesting this is not a region-specific phenomenon. There may be, however, a cell type-specific role for Cdk5 in gliogenesis. For example, the decrease in recombined GFAP+ astrocyte number takes longer to appear relative to recombined RIP+ oligodendrocytes. Specifically, we observed only a trend towards fewer YFP+ astrocytes in iCdk5 vs. WT mice at P14, but significantly fewer YFP+ oligodendrocytes at P14. The mechanism for this cell-specific reduction may differ between the two glial cell types. For example, at P21 there is a reduction in both GFAP+ and RIP+ cell types, but in oligodendrocytes there may be impaired cell fate/maturation as well. These results also support recent findings that astrocytes can also be generated locally in the postnatal cortex [In both embryonic and adult development, Cdk5 controls cell migration, differentiation, synaptic plasticity, and the cell cycle . Howeverl cortex , which cl cortex –70. Therin vitro [What could be the possible molecular and cellular mechanisms underlying how Cdk5 supports early postnatal gliogenesis from nestin-expressing progenitors? Cdk5 controls key cytoskeleton elements – such as actin-related proteins  or GFAP in vitro  to phospin vitro  and paxiin vitro . While win vitro  but rathin vitro ; thus, oin vivo [in vitro [in vivo, in vitro, and ex vivo strategies [In addition to proliferation and differentiation, Cdk5 may also support postnatal gliogenesis by regulating glial migration ,28,60. Gin vivo ,20,73 anin vitro –28 migrarategies ,74–79. Irategies ,25,50,80in vivo. As the number of cellular processes regulated by Cdk5 increases, and Cdk5 is implicated in neuron-glia interaction as a part of etiology of neurodegenerative diseases [In summary, our results demonstrate that nestin-expressing progenitors are capable of generating astrocytes and oligodendrocytes in different brain regions during a critical period of the first postnatal week in mice. Our results also show that Cdk5 is required for the proper early postnatal gliogenesis diseases ,33,81, tFigure S1Influence of Tamoxifen (Tam) administration to lactating mothers (TOM) and to mothers and pups (TOM-TOP) on Cre-mediated recombination and body weight.In TOM experiments, only mothers received Tam (see Methods). In TOM-TOP experiments, Tam was administered orally to pups and their mothers (i.p.) once a day from P2-P4 or P7-P9. (A) The percent of nestin-YFP offspring from TOM vs. TOM-TOP litters that had evidence of recombination (e.g. YFP+ cells in any brain region) is 100% in TOM-TOP mice, but lower in TOM mice. Shown are data from Tam P2-P4 and kill P21.  TOM-TOP does not negatively influence normal progression of body weight in WT and iCdk5 littermates given Tam from either P2-P4 (B) or P7-P9 (C).(TIFF)Click here for additional data file.