Non-binding Domains Research Articles

Impact of Molecular Architecture and Adsorption Density on Adhesion of Mussel-Inspired Surface Primers with Catechol-Cation Synergy.

Marine mussels secrete proteins rich in residues containing catechols and cationic amines that displace hydration layers and adhere to charged surfaces under water via a cooperative binding effect known as catechol-cation synergy. Mussel-inspired adhesives containing paired catechol and cationic functionalities are a promising class of materials for biomedical applications, but few studies address the molecular adhesion mechanism(s) of these materials. To determine whether intramolecular adjacency of these functionalities is necessary for robust adhesion, a suite of siderophore analog surface primers was synthesized with systematic variations in intramolecular spacing between catechol and cationic functionalities. Adhesion measurements conducted with a surface forces apparatus (SFA) allow adhesive failure to be distinguished from cohesive failure and show that the failure mode depends critically on the siderophore analog adsorption density. The adhesion of these molecules to muscovite mica in an aqueous electrolyte solution demonstrates that direct intramolecular adjacency of catechol and cationic functionalities is not necessary for synergistic binding. However, we show that increasing the catechol-cation spacing by incorporating nonbinding domains results in decreased adhesion, which we attribute to a decrease in the density of catechol functionalities. A mechanism for catechol-cation synergy is proposed based on electrostatically driven adsorption and subsequent binding of catechol functionalities. This work should guide the design of new adhesives for binding to charged surfaces in saline environments.

Evidence for the evolutionary steps leading to mecA-mediated β-lactam resistance in staphylococci.

The epidemiologically most important mechanism of antibiotic resistance in Staphylococcus aureus is associated with mecA–an acquired gene encoding an extra penicillin-binding protein (PBP2a) with low affinity to virtually all β-lactams. The introduction of mecA into the S. aureus chromosome has led to the emergence of methicillin-resistant S. aureus (MRSA) pandemics, responsible for high rates of mortality worldwide. Nonetheless, little is known regarding the origin and evolution of mecA. Different mecA homologues have been identified in species belonging to the Staphylococcus sciuri group representing the most primitive staphylococci. In this study we aimed to identify evolutionary steps linking these mecA precursors to the β-lactam resistance gene mecA and the resistance phenotype. We sequenced genomes of 106 S. sciuri, S. vitulinus and S. fleurettii strains and determined their oxacillin susceptibility profiles. Single-nucleotide polymorphism (SNP) analysis of the core genome was performed to assess the genetic relatedness of the isolates. Phylogenetic analysis of the mecA gene homologues and promoters was achieved through nucleotide/amino acid sequence alignments and mutation rates were estimated using a Bayesian analysis. Furthermore, the predicted structure of mecA homologue-encoded PBPs of oxacillin-susceptible and -resistant strains were compared. We showed for the first time that oxacillin resistance in the S. sciuri group has emerged multiple times and by a variety of different mechanisms. Development of resistance occurred through several steps including structural diversification of the non-binding domain of native PBPs; changes in the promoters of mecA homologues; acquisition of SCCmec and adaptation of the bacterial genetic background. Moreover, our results suggest that it was exposure to β-lactams in human-created environments that has driven evolution of native PBPs towards a resistance determinant. The evolution of β-lactam resistance in staphylococci highlights the numerous resources available to bacteria to adapt to the selective pressure of antibiotics.

High affinity truncated DNA aptamers for the development of fluorescence based progesterone biosensors

Aptamers have shown a number of potential applications in sensing and therapeutic due to the high affinity and specificity towards their target molecules. Not all the nucleotides in the full length aptamers are involved in the binding with their targets. The non-binding domain of the aptamer may affect the binding affinity of the aptamer-target complex. Mapping the aptamer binding region could increase the affinity and the specificity. In this paper, we designed aptamer-based fluorescence sensors from a truncated progesterone (P4) aptamer. Then, fluorescein and quencher labelled aptamer complementary oligonucleotide sequences were hybridized to the truncated aptamer at different sites to form duplex structures. We used fluorescence-quencher pair displacement assay upon progesterone binding for the determination of P4. One of the truncated sequences has shown high binding affinity with 16 fold increase in the dissociation constant, Kd (2.1 nM) compared to the original aptamer. The aptasensor was highly selective for P4 against similar compounds such as 17-β estradiol, bisphenol-A and vitamin D. The sensor has been applied for the detection of P4 in spiked tap water and in urine samples showing good recovery. This new developed aptamer-based fluorescence biosensor can be applied in food, pharmaceutical, and clinical industries.

Gene conversions are frequent but not under positive selection in the Siglec gene families of primates.

Siglecs are cell surface proteins that belong to the immunoglobulin superfamily and which bind sialic acids. They are composed of two groups, the conserved Siglecs and the CD33-related Siglecs. Previous studies have reported the occurrence of gene conversions between human CD33-related Siglecs and suggested that these conversions are adaptive because they increase the diversity of these immunoglobulin-related genes. Here, we analyze the Siglec genes of five primate species and show that gene conversions are not observed between conserved Siglec genes but that they are frequent between primate CD33-related Siglecs. The gene conversions between CD33-related Siglec genes only occur between similar genes and equally frequently in sialic acid binding and nonbinding domains. Furthermore, dN/dS ratio tests show that most of the Ig-like V-type 1 and the Ig-like C2-type 1 domains of Siglec genes evolve either neutrally or under purifying selection and that gene conversions were not responsible for the positively selected regions detected in the Ig-like V-type1 domain of the human SIGLEC7 and SIGLEC9 genes. Our results suggest that the frequent gene conversions between CD33-related Siglec genes are simply a consequence of the high degree of sequence similarity of these genes and that they are not adaptive.

A structure-based protocol for learning the family-specific mechanisms of membrane-binding domains

Motivation: Peripheral membrane-targeting domain (MTD) families, such as C1-, C2- and PH domains, play a key role in signal transduction and membrane trafficking by dynamically translocating their parent proteins to specific plasma membranes when changes in lipid composition occur. It is, however, difficult to determine the subset of domains within families displaying this property, as sequence motifs signifying the membrane binding properties are not well defined. For this reason, procedures based on sequence similarity alone are often insufficient in computational identification of MTDs within families (yielding less than 65% accuracy even with a sequence identity of 70%).Results: We present a machine learning protocol for determining membrane-targeting properties achieving 85–90% accuracy in separating binding and non-binding domains within families. Our model is based on features from both sequence and structure, thereby incorporation statistics obtained from the entire domain family and domain-specific physical quantities such as surface electrostatics. In addition, by using the enriched rules in alternating decision tree classifiers, we are able to determine the meaning of the assigned function labels in terms of biological mechanisms.Conclusions: The high accuracy of the learned models and good agreement between the rules discovered using the ADtree classifier and mechanisms reported in the literature reflect the value of machine learning protocols in both prediction and biological knowledge discovery. Our protocol can thus potentially be used as a general function annotation and knowledge mining tool for other protein domains.Availability: metador.bioengr.uic.eduContact: huilu@uic.edu

Prediction of small molecule binding property of protein domains with Bayesian classifiers based on Markov chains

Accurate computational methods that can help to predict biological function of a protein from its sequence are of great interest to research biologists and pharmaceutical companies. One approach to assume the function of proteins is to predict the interactions between proteins and other molecules. In this work, we propose a machine learning method that uses a primary sequence of a domain to predict its propensity for interaction with small molecules. By curating the Pfam database with respect to the small molecule binding ability of its component domains, we have constructed a dataset of small molecule binding and non-binding domains. This dataset was then used as training set to learn a Bayesian classifier, which should distinguish members of each class. The domain sequences of both classes are modelled with Markov chains. In a Jack-knife test, our classification procedure achieved the predictive accuracies of 77.2% and 66.7% for binding and non-binding classes respectively. We demonstrate the applicability of our classifier by using it to identify previously unknown small molecule binding domains. Our predictions are available as supplementary material and can provide very useful information to drug discovery specialists. Given the ubiquitous and essential role small molecules play in biological processes, our method is important for identifying pharmaceutically relevant components of complete proteomes. The software is available from the author upon request.

High Throughput Functional Assays of the Variant Antigen PfEMP1 Reveal a Single Domain in the 3D7 Plasmodium falciparum Genome that Binds ICAM1 with High Affinity and Is Targeted by Naturally Acquired Neutralizing Antibodies

Plasmodium falciparum–infected erythrocytes bind endothelial receptors to sequester in vascular beds, and binding to ICAM1 has been implicated in cerebral malaria. Binding to ICAM1 may be mediated by the variant surface antigen family PfEMP1: for example, 6 of 21 DBLβC2 domains from the IT4 strain PfEMP1 repertoire were shown to bind ICAM1, and the PfEMP1 containing these 6 domains are all classified as Group B or C type. In this study, we surveyed binding of ICAM1 to 16 DBLβC2 domains of the 3D7 strain PfEMP1 repertoire, using a high throughput Bioplex assay format. Only one DBL2βC2 domain from the Group A PfEMP1 PF11_0521 showed strong specific binding. Among these 16 domains, DBL2βC2PF11_0521 best preserved the residues previously identified as conserved in ICAM1-binding versus non-binding domains. Our analyses further highlighted the potential role of conserved residues within predominantly non-conserved flexible loops in adhesion, and, therefore, as targets for intervention. Our studies also suggest that the structural/functional DBLβC2 domain involved in ICAM1 binding includes about 80 amino acid residues upstream of the previously suggested DBLβC2 domain. DBL2βC2PF11_0521 binding to ICAM1 was inhibited by immune sera from east Africa but not by control US sera. Neutralizing antibodies were uncommon in children but common in immune adults from east Africa. Inhibition of binding was much more efficient than reversal of binding, indicating a strong interaction between DBL2βC2PF11_0521 and ICAM1. Our high throughput approach will significantly accelerate studies of PfEMP1 binding domains and protective antibody responses.

Relaxed Constraint and Evolutionary Rate Variation between Basic Helix-Loop-Helix Floral Anthocyanin Regulators in Ipomoea

Regulatory genes are believed to play a large role in morphological diversification and are often characterized by elevated rates of evolution. Whether this rapid evolution is primarily due to adaptive differentiation or relaxed selective constraint remains an open question. We attempted to distinguish between these alternative outcomes in 2 transcription factors known to regulate the expression of anthocyanin pigmentation genes in flowers. We cloned the full-length coding region from 2 basic helix-loop-helix transcription factors from several species of Ipomoea with diverse flower colors and determined the selective forces operating on them. In both genes, rapidly evolving sites and indel mutations are clustered in nonbinding domains, but the extent of rate acceleration in these domains is reduced relative to most previously characterized plant transcription factors. Moreover, codon models of substitution rates and models evaluating the magnitude of change to physical amino acid properties demonstrate little evidence for adaptive evolution and suggest that elevated nonsynonymous substitution rates in these domains represent relaxed selective constraint. Although both genes show qualitatively similar patterns, their rates of evolution differ significantly due to an increased rate of nonsynonymous substitutions in the nonbinding domains in one copy, suggesting substantial differences in functional constraint on each gene. In general, these results provide additional evidence demonstrating that decreased constraint as opposed to positive selection is largely responsible for the frequently observed pattern of rapid evolution in particular domains of plant transcription factors. More specifically, they suggest that most of the amino acid substitutions are neutral and do not implicate a role for natural selection on these regulatory genes in the diversification of flower color in Ipomoea.

Variation in the ligand binding domains of the CD94/NKG2 family of receptors in the squirrel monkey

Natural killer cells are regulated, in part, by cell surface expression of the inhibitory CD94/NKG2A heterodimer and the activating CD94/NKG2C heterodimer. In the present study, we characterize the CD94/NKG2 family in the squirrel monkey, a New World monkey species. Full-length CD94, NKG2A, and NKG2CE complementary deoxyribonucleic acid molecules were identified in three unrelated squirrel monkeys. Three alternatively spliced forms of CD94 were detected in which part of intron 4 was included in the mature transcript, suggesting evolutionary pressure for changes in the corresponding loop 3 region of the lectin domain in squirrel monkeys. Squirrel monkey NKG2A contains a three-nucleotide indel that results in an additional amino acid in the predicted NKG2A protein compared to NKG2A in other species. This NKG2A insertion tracks to loop five of the lectin domain, as is seen with the recently described marmoset NKG2CE indel. Transmembrane-deleted forms of CD94 and NKG2CE were also expressed in the squirrel monkey. Analysis of full-length squirrel monkey and additional primate CD94/NKG2 sequences demonstrated statistically significant increases in the Ka/Ks ratio in the putative major histocompatibility complex E (MHC-E) binding domain compared to the non-binding domain. Furthermore, positive selection was detected in the MHC-E binding domain of primate NKG2 family members, and purifying selection was detected in the primate CD94 binding domain. Purifying selection was also detected in the nonbinding domains of primate CD94 and NKG2 molecules.

Prediction of Ras-effector interactions using position energy matrices

One of the more challenging problems in biology is to determine the cellular protein interaction network. Progress has been made to predict protein-protein interactions based on structural information, assuming that structural similar proteins interact in a similar way. In a previous publication, we have determined a genome-wide Ras-effector interaction network based on homology models, with a high accuracy of predicting binding and non-binding domains. However, for a prediction on a genome-wide scale, homology modelling is a time-consuming process. Therefore, we here successfully developed a faster method using position energy matrices, where based on different Ras-effector X-ray template structures, all amino acids in the effector binding domain are sequentially mutated to all other amino acid residues and the effect on binding energy is calculated. Those pre-calculated matrices can then be used to score for binding any Ras or effector sequences. Based on position energy matrices, the sequences of putative Ras-binding domains can be scanned quickly to calculate an energy sum value. By calibrating energy sum values using quantitative experimental binding data, thresholds can be defined and thus non-binding domains can be excluded quickly. Sequences which have energy sum values above this threshold are considered to be potential binding domains, and could be further analysed using homology modelling. This prediction method could be applied to other protein families sharing conserved interaction types, in order to determine in a fast way large scale cellular protein interaction networks. Thus, it could have an important impact on future in silico structural genomics approaches, in particular with regard to increasing structural proteomics efforts, aiming to determine all possible domain folds and interaction types. All matrices are deposited in the ADAN database (http://adan-embl.ibmc.umh.es/). Supplementary data are available at Bioinformatics online.

Mapping Netrin Receptor Binding Reveals Domains of Unc5 Regulating Its Tyrosine Phosphorylation

Netrin and its receptors Unc5 and deleted in colorectal carcinoma (DCC) regulate axon guidance and cell migration. We defined domains involved in the interactions between netrin-1, DCC, and Unc5c. We show that Unc5 requires both Ig domains to interact with netrin. DCC binds through the fourth fibronectin type III domain, whereas netrin binds through multiple domains to both receptors. We examined the functional consequences of removing the netrin binding and nonbinding domains from Unc5 in vitro and in vivo. In human embryonic kidney 293 cells, removal of the netrin binding second Ig domain causes an increase in basal tyrosine phosphorylation, whereas removal of the netrin nonbinding thrombospondin domains decreases tyrosine phosphorylation. Moreover, experiments in Caenorhabditis elegans indicate that both netrin binding and nonbinding domains are necessary for phenotypic rescue of an unc-5 loss of function mutation.

Improved Chemical Strategies for the Targeted Therapy of Cancer

AbstractFor Abstract see ChemInform Abstract in Full Text.

Storage stability of the solution formulation of sCD4 determined by DSC in comparison with two functional assays

Differential scanning calorimetry (DSC) was used, in conjunction with two functional assays that monitor binding, in a storage stability study on a protein of pharmaceutical interest, the soluble form of the T-lymphocyte multidomain surface receptor, sCD4. DSC monitored structural changes in binding and non-binding domains. ELISA, using the monoclonal antibody OKT4a, and frontal elution affinity chromatography, using the HIV surface glycoprotein, gp120, monitored function of the binding domain. The stability of sCD4 in a solution formulation was followed for up to 30 days at five differentpHs ranging from 5.0 to 7.9 and five different temperatures ranging from −70‡C to 40‡C. While the overall trends observed with the three techniques were the same, the ELISA data were somewhat less reproducible than those for the other methods. Furthermore, the results suggest that DSC is more sensitive to structural changes that would reduce the protein's bioactivity. The results of this study indicate DSC's utility, in conjunction with quantitative functional analysis, in the formulation of protein-containing pharmaceuticals or foods, especially those containing multiple-domain proteins.

Theoretical estimation of the calcium-binding constants for proteins from the troponin C superfamily based on a secondary structure prediction method I. Estimation procedure

Proteins belonging to the TNC superfamily are known to be built of two, three, four, or six domains of closely similar amino acid sequences. Each domain binds no more than one calcium ion and shows a characteristic helix-loop-helix structure when in the calcium-bound state. Conformational properties of all the domains known so far have been analysed by us using a secondary structure prediction method (Garnier, J., Osguthorpe, D.J. & Robson, B. (1978). J. molec. Biol. 120, 97). Significant differences in distribution of residues predicted as being in the helical, beta-turn, and coil conformations have been found between the strongly, weakly, and non-binding domains. We could determine the ideal prediction pattern characteristic for the domains with the highest affinity for calcium. On the basis of our analysis and observations made by other authors we worked out a few simple rules which made it possible to compare conformational properties of a given domain with the ideal reference pattern and estimate, in this way, the Ca2+-binding constant of the domain. In native proteins the domains are known to be organized in pairs. The Ca2+-binding constant for a two-domain region could be evaluated from the sum of the estimation points attributed to each of its components. Using our method it is possible to predict the binding constants of typical domains and two-domain regins with a precision of one order of magnitude. Data on amino acid sequences and calcium-binding constants of all known proteins, believed to be the members of the TNC superfamily, have been reviewed. References to virtually all papers published on this subject before the end of 1987 are given.

Protein-kinase-C-catalyzed phosphorylation of the microtubule-binding domain of microtubule-associated protein 2 inhibits its ability to induce tubulin polymerization.

It has previously been demonstrated that microtubule-associated protein 2 (MAP2) is a good substrate for the purified protein kinase C [Tsuyama, S., Bramblett, G. T., Huang, K.-P. & Flavin, M. (1986) J. Biol. Chem. 261, 4110-4116; Akiyama, T., Nishida, E., Ishida, J., Saji, N., Ogawara, H., Hoshi, M., Miyata, Y. & Sakai, H. (1986) J. Biol. Chem. 261, 15648-15651]. We have shown here that phosphorylation of MAP2, catalyzed by protein kinase C, reduces the ability to induce tubulin polymerization. MAP2 is divided into two domains by digestion with alpha-chymotrypsin; the microtubule-binding and the non-binding (projection) domains. The limited chymotryptic digestion following phosphorylation of MAP2 by protein kinase C has shown that both the domains of MAP2 were phosphorylated by protein kinase C, 50-60% of the incorporated phosphates being detected in the microtubule-binding domain. Polypeptide fragments, containing the microtubule-binding domain of MAP2, were purified by DEAE-cellulose column chromatography after chymotryptic digestion of MAP2. The purified microtubule-binding fragments were competent to polymerize tubulin, and served as good substrates for protein kinase C. The phosphorylation of the microtubule-binding fragments by protein kinase C reduced their ability to induce tubulin polymerization. These results suggest that the ability of MAP2 to induce tubulin polymerization is inhibited by phosphorylation of the microtubule-binding domain catalyzed by protein kinase C.