Protein-nucleotide Interactions Research Articles

Structural Basis of Nucleotide Selectivity in Pyruvate Kinase

Nucleoside triphosphates are indispensable in numerous biological processes, with enzymes involved in their biogenesis playing pivotal roles in cell proliferation. Pyruvate kinase (PYK), commonly regarded as the terminal glycolytic enzyme that generates ATP in tandem with pyruvate, is also capable of synthesizing a wide range of nucleoside triphosphates from their diphosphate precursors. Despite their substrate promiscuity, some PYKs show preference towards specific nucleotides, suggesting an underlying mechanism for differentiating nucleotide bases. However, the thorough characterization of this mechanism has been hindered by the paucity of nucleotide-bound PYK structures. Here, we present crystal structures of Streptococcus pneumoniae PYK in complex with four different nucleotides. These structures facilitate direct comparison of the protein-nucleotide interactions and offer structural insights into its pronounced selectivity for GTP synthesis. Notably, this selectivity is dependent on a sequence motif in the nucleotide recognition site that is widely present among prokaryotic PYKs, particularly in Firmicutes species. We show that pneumococcal cell growth is significantly impaired when expressing a PYK variant with compromised GTP and UTP synthesis activity, underscoring the importance of PYK in maintaining nucleotide homeostasis. Our findings collectively advance our understanding of PYK biochemistry and prokaryotic metabolism.

Inosine-Induced Base Pairing Diversity during Reverse Transcription.

A-to-I editing catalyzed by adenosine deaminase acting on RNAs impacts numerous physiological and biochemical processes that are essential for cellular functions and is a big contributor to the infectivity of certain RNA viruses. The outcome of this deamination leads to changes in the eukaryotic transcriptome functionally resembling A-G transitions since inosine preferentially pairs with cytosine. Moreover, hyper-editing or multiple A to G transitions in clusters were detected in measles virus. Inosine modifications either directly on viral RNA or on cellular RNA can have antiviral or pro-viral repercussions. While many of the significant roles of inosine in cellular RNAs are well understood, the effects of hyper-editing of A to I on viral polymerase activity during RNA replication remain elusive. Moreover, biological strategies such as molecular cloning and RNA-seq for transcriptomic interrogation rely on RT-polymerase chain reaction with little to no emphasis placed on the first step, reverse transcription, which may reshape the sequencing results when hypermodification is present. In this study, we systematically explore the influence of inosine modification, varying the number and position of inosines, on decoding outcomes using three different reverse transcriptases (RTs) followed by standard Sanger sequencing. We find that inosine alone or in clusters can differentially affect the RT activity. To gain structural insights into the accommodation of inosine in the polymerase site of HIV-1 reverse transcriptase (HIV-1-RT) and how this structural context affects the base pairing rules for inosine, we performed molecular dynamics simulations of the HIV-1-RT. The simulations highlight the importance of the protein-nucleotide interaction as a critical factor in deciphering the base pairing behavior of inosine clusters. This effort sets the groundwork for decrypting the physiological significance of inosine and linking the fidelity of reverse transcriptase and the possible diverse transcription outcomes of cellular RNAs and/or viral RNAs where hyper-edited inosines are present in the transcripts.

Genetically Encoded Aminocoumarin Lysine for Optical Control of Protein-Nucleotide Interactions in Zebrafish Embryos.

The strategic placement of unnatural amino acids into the active site of kinases and phosphatases has allowed for the generation of photocaged signaling proteins that offer spatiotemporal control over activation of these pathways through precise light exposure. However, deploying this technology to study cell signaling in the context of embryo development has been limited. The promise of optical control is especially useful in the early stages of an embryo where development is driven by tightly orchestrated signaling events. Here, we demonstrate light-induced activation of Protein Kinase A and a RASopathy mutant of NRAS in the zebrafish embryo using a new light-activated amino acid. We applied this approach to gain insight into the roles of these proteins in gastrulation and heart development and forge a path for further investigation of RASopathy mutant proteins in animals.

Phylogenetic distribution, structural analysis and interaction of nucleotide excision repair proteins in cyanobacteria

Cyanobacteria are photosynthetic Gram-negative, oxygen evolving prokaryotes with cosmopolitan distribution. Ultraviolet radiation (UVR) and other abiotic stresses result in DNA lesions in cyanobacteria. Nucleotide excision repair (NER) pathway removes the DNA lesions produced by UVR to normal DNA sequence. In cyanobacteria, detailed knowledge about NER proteins is poorly studied. Therefore, we have studied the NER proteins in cyanobacteria. Analyses of 289 amino acids sequence from 77 cyanobacterial species have revealed the presence of a minimum of one copy of NER protein in their genome. Phylogenetic analysis of NER protein shows that UvrD has maximal rate of amino acid substitutions which resulted in increased branch length. The motif analysis shows that UvrABC proteins is more conserved than UvrD, Further, UvrA with UvrB protein interacts with each other and form stable complex which have DNA binding domain on the surface of the complex. UvrB also have DNA binding domain. Positive electrostatic potential was found in the DNA binding region, which is followed by negative and neutral electrostatic potential. Additionally, the surface accessibility values at the DNA strands of T5-T6 dimer binding site were maximal. Protein nucleotide interaction shows the strong binding of T5-T6 dimer with NER proteins of Synechocystis sp. PCC 6803. This process repairs the UV-induced DNA lesions in dark when photoreactivation is inactive. Regulation of NER proteins protect cyanobacterial genome and maintain the fitness of organism under different abiotic stresses.

Molecular Modeling of Subtype-Specific Tat Protein Signatures to Predict Tat-TAR Interactions That May Be Involved in HIV-Associated Neurocognitive Disorders.

HIV-1 is responsible for a spectrum of neurocognitive deficits defined as HIV-associated neurocognitive disorders (HAND). The HIV transactivator of transcription (Tat) protein plays a key role in the neuropathophysiology of HAND. The Tat protein functions by transactivation of viral genes through its interaction with the transactivation response (TAR) RNA element. Subtype-specific Tat protein signatures including C31S, R57S and Q63E present in Tat subtype C has previously been linked to a lowered neuropathophysiology compared to Tat subtype B. In this study, we attempted to understand the molecular mechanism by which Tat subtype-specific variation, particularly, C31S, R57S, and Q63E influence the Tat-TAR interaction. We performed molecular modeling to generate accurate three-dimensional protein structures of the HIV-1 Tat subtypes C and B using the Swiss model webserver. Thereafter, we performed a molecular docking of the TAR RNA element to each of the Tat subtypes B and C protein structures using the HDOCK webserver. Our findings indicate that Tat subtype B had a higher affinity for the TAR RNA element compared to Tat subtype C based on a higher docking score of −187.37, a higher binding free energy value of −9834.63 ± 216.17 kJ/mol, and a higher number of protein–nucleotide interactions of 26. Furthermore, Tat subtype B displayed more flexible regions when bound to the TAR element and this flexibility could account for the stronger affinity of Tat subtype B to TAR. From the Tat signatures linked to neuropathogenesis, only R57/R57S are involved in Tat-TAR interaction. Due to the lack of electrostatic interactions observed between Tat subtype C and TAR, weaker affinity is observed, and this may contribute to a lower level of neuropathophysiology observed in subtype C infection.

Advances in enzyme-mediated proximity labeling and its potential for plant research.

Cellular processes rely on the intimate interplay of different molecules, including DNA, RNA, proteins, and metabolites. Obtaining and integrating data on their abundance and dynamics at high temporal and spatial resolution are essential for our understanding of plant growth and development. In the past decade, enzymatic proximity labeling (PL) has emerged as a powerful tool to study local protein and nucleotide ensembles, discover protein–protein and protein–nucleotide interactions, and resolve questions about protein localization and membrane topology. An ever-growing number and continuous improvement of enzymes and methods keep broadening the spectrum of possible applications for PL and make it more accessible to different organisms, including plants. While initial PL experiments in plants required high expression levels and long labeling times, recently developed faster enzymes now enable PL of proteins on a cell type-specific level, even with low-abundant baits, and in different plant species. Moreover, expanding the use of PL for additional purposes, such as identification of locus-specific gene regulators or high-resolution electron microscopy may now be in reach. In this review, we give an overview of currently available PL enzymes and their applications in mammalian cell culture and plants. We discuss the challenges and limitations of PL methods and highlight open questions and possible future directions for PL in plants.

Analysis of Protein Intermolecular Interactions with MAFFT-DASH.

The Database of Aligned Structural Homologs (DASH) is a tool for efficiently navigating the Protein Data Bank (PDB) by means of pre-computed pairwise structural alignments. We recently showed that, by integrating DASH structural alignments with the multiple sequence alignment (MSA) software MAFFT, we were able to significantly improve MSA accuracy without dramatically increasing manual or computational complexity. In the latest DASH update, such queries are not limited to PDB entries but can also be launched from user-provided protein coordinates. Here, we describe a further extension of DASH that retrieves intermolecular interactions of all structurally similar domains in the PDB to a query domain of interest. We illustrate these new features using a model of the NYN domain of the ribonuclease N4BP1 as an example. We show that the protein-nucleotide interactions returned are distributed on the surface of the NYN domain in an asymmetric manner, roughly centered on the known nuclease active site.

Boosting Granular Support Vector Machines for the Accurate Prediction of Protein-Nucleotide Binding Sites.

The accurate identification of protein-ligand binding sites helps elucidate protein function and facilitate the design of new drugs. Machine-learning-based methods have been widely used for the prediction of protein-ligand binding sites. Nevertheless, the severe class imbalance phenomenon, where the number of nonbinding (majority) residues is far greater than that of binding (minority) residues, has a negative impact on the performance of such machine-learning-based predictors. In this study, we aim to relieve the negative impact of class imbalance by Boosting Multiple Granular Support Vector Machines (BGSVM). In BGSVM, each base SVM is trained on a granular training subset consisting of all minority samples and some reasonably selected majority samples. The efficacy of BGSVM for dealing with class imbalance was validated by benchmarking it with several typical imbalance learning algorithms. We further implemented a protein-nucleotide binding site predictor, called BGSVM-NUC, with the BGSVM algorithm. Rigorous cross-validation and independent validation tests for five types of proteinnucleotide interactions demonstrated that the proposed BGSVM-NUC achieves promising prediction performance and outperforms several popular sequence-based protein-nucleotide binding site predictors. The BGSVM-NUC web server is freely available at http://csbio.njust.edu.cn/bioinf/BGSVM-NUC/ for academic use.

Thermodynamics of helix formation in small peptides of varying length in vacuo, in implicit solvent, and in explicit solvent.

Helix formation plays a critical role in the functionality of proteins. Various biological processes such as protein-ligand, protein-protein, and protein-nucleotide interactions are strongly influenced by the conformational stability of peptides. Small peptides represent ideal models to study the process of helix formation due to their small size and simple structures. As is widely known in the biophysical community, different amino acids have different propensities for helix formation. In this work, we used model peptides to study the peptide-length dependence and the sequence dependence of the thermodynamic profiles along the helix formation pathway in vacuo and in water. The peptides showed interesting unfolding behavior in vacuo, as this process was found to be protonation-state dependent, sequence-length dependent, and to change when residues in the peptide were mutated. Ionizable group protonation alters helix propensity by changing the degree of charge-charge repulsion in the peptide. Longer sequences tend to form more hydrogen bonds and are more likely to form helical structures. Mutation of an alanine residue to another naturally occurring amino acid changes the interactions within the peptide, which in turn alters its helix-forming tendency. By contrast, solvation leads to the generation of protein-solvent hydrogen bonds, which compensate for the energy penalty associated with the deformation of backbone hydrogen bonds in the extended conformation. Flat free-energy profiles were obtained for all mutated peptides of various lengths. Although several implicit-solvent models were able to reproduce free energies of helix formation in explicit solvent, the conformational ensembles varied with the solvent model applied, particularly in terms of the populations of secondary structures and the formation of backbone hydrogen bonds. Also, due to the absence of explicit descriptions of solvent molecules and thus protein-solvent hydrogen bonds in implicit-solvent models, they did not yield accurate hydrogen-bonding profiles.

An efficient proteome-wide strategy for discovery and characterization of cellular nucleotide-protein interactions

Metabolite-protein interactions define the output of metabolic pathways and regulate many cellular processes. Although diseases are often characterized by distortions in metabolic processes, efficient means to discover and study such interactions directly in cells have been lacking. A stringent implementation of proteome-wide Cellular Thermal Shift Assay (CETSA) was developed and applied to key cellular nucleotides, where previously experimentally confirmed protein-nucleotide interactions were well recaptured. Many predicted, but never experimentally confirmed, as well as novel protein-nucleotide interactions were discovered. Interactions included a range of different protein families where nucleotides serve as substrates, products, co-factors or regulators. In cells exposed to thymidine, a limiting precursor for DNA synthesis, both dose- and time-dependence of the intracellular binding events for sequentially generated thymidine metabolites were revealed. Interactions included known cancer targets in deoxyribonucleotide metabolism as well as novel interacting proteins. This stringent CETSA based strategy will be applicable for a wide range of metabolites and will therefore greatly facilitate the discovery and studies of interactions and specificities of the many metabolites in human cells that remain uncharacterized.

Structure-Based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces.

Recently it has been shown that cancer mutations selectively target protein-protein interactions. We hypothesized that mutations affecting distinct protein interactions involving established cancer genes could contribute to tumor heterogeneity, and that novel mechanistic insights might be gained into tumorigenesis by investigating protein interactions under positive selection in cancer. To identify protein interactions under positive selection in cancer, we mapped over 1.2 million nonsynonymous somatic cancer mutations onto 4,896 experimentally determined protein structures and analyzed their spatial distribution. In total, 20% of mutations on the surface of known cancer genes perturbed protein-protein interactions (PPIs), and this enrichment for PPI interfaces was observed for both tumor suppressors (Odds Ratio 1.28, P-value < 10−4) and oncogenes (Odds Ratio 1.17, P-value < 10−3). To study this further, we constructed a bipartite network representing structurally resolved PPIs from all available human complexes in the Protein Data Bank (2,864 proteins, 3,072 PPIs). Analysis of frequently mutated cancer genes within this network revealed that tumor-suppressors, but not oncogenes, are significantly enriched with functional mutations in homo-oligomerization regions (Odds Ratio 3.68, P-Value < 10−8). We present two important examples, TP53 and beta-2-microglobulin, for which the patterns of somatic mutations at interfaces provide insights into specifically perturbed biological circuits. In patients with TP53 mutations, patient survival correlated with the specific interactions that were perturbed. Moreover, we investigated mutations at the interface of protein-nucleotide interactions and observed an unexpected number of missense mutations but not silent mutations occurring within DNA and RNA binding sites. Finally, we provide a resource of 3,072 PPI interfaces ranked according to their mutation rates. Analysis of this list highlights 282 novel candidate cancer genes that encode proteins participating in interactions that are perturbed recurrently across tumors. In summary, mutation of specific protein interactions is an important contributor to tumor heterogeneity and may have important implications for clinical outcomes.

Global discovery of protein kinases and other nucleotide-binding proteins by mass spectrometry.

Nucleotide-binding proteins, such as protein kinases, ATPases and GTP-binding proteins, are among the most important families of proteins that are involved in a number of pivotal cellular processes. However, global study of the structure, function, and expression level of nucleotide-binding proteins as well as protein-nucleotide interactions can hardly be achieved with the use of conventional approaches owing to enormous diversity of the nucleotide-binding protein family. Recent advances in mass spectrometry (MS) instrumentation, coupled with a variety of nucleotide-binding protein enrichment methods, rendered MS-based proteomics a powerful tool for the comprehensive characterizations of the nucleotide-binding proteome, especially the kinome. Here, we review the recent developments in the use of mass spectrometry, together with general and widely used affinity enrichment approaches, for the proteome-wide capture, identification and quantification of nucleotide-binding proteins, including protein kinases, ATPases, GTPases, and other nucleotide-binding proteins. The working principles, advantages, and limitations of each enrichment platform in identifying nucleotide-binding proteins as well as profiling protein-nucleotide interactions are summarized. The perspectives in developing novel MS-based nucleotide-binding protein detection platform are also discussed. © 2014 Wiley Periodicals, Inc. Mass Spec Rev 35:601-619, 2016.

A new supervised over-sampling algorithm with application to protein-nucleotide binding residue prediction.

Protein-nucleotide interactions are ubiquitous in a wide variety of biological processes. Accurately identifying interaction residues solely from protein sequences is useful for both protein function annotation and drug design, especially in the post-genomic era, as large volumes of protein data have not been functionally annotated. Protein-nucleotide binding residue prediction is a typical imbalanced learning problem, where binding residues are extremely fewer in number than non-binding residues. Alleviating the severity of class imbalance has been demonstrated to be a promising means of improving the prediction performance of a machine-learning-based predictor for class imbalance problems. However, little attention has been paid to the negative impact of class imbalance on protein-nucleotide binding residue prediction. In this study, we propose a new supervised over-sampling algorithm that synthesizes additional minority class samples to address class imbalance. The experimental results from protein-nucleotide interaction datasets demonstrate that the proposed supervised over-sampling algorithm can relieve the severity of class imbalance and help to improve prediction performance. Based on the proposed over-sampling algorithm, a predictor, called TargetSOS, is implemented for protein-nucleotide binding residue prediction. Cross-validation tests and independent validation tests demonstrate the effectiveness of TargetSOS. The web-server and datasets used in this study are freely available at http://www.csbio.sjtu.edu.cn/bioinf/TargetSOS/.

A high-throughput method to examine protein-nucleotide interactions identifies targets of the bacterial transcriptional regulatory protein fur.

The Ferric uptake regulatory protein (Fur) is a transcriptional regulatory protein that functions to control gene transcription in response to iron in a number of pathogenic bacteria. In this study, we applied a label-free, quantitative and high-throughput analysis method, Interferometric Reflectance Imaging Sensor (IRIS), to rapidly characterize Fur-DNA interactions in vitro with predicted Fur binding sequences in the genome of Neisseria gonorrhoeae, the causative agent of the sexually transmitted disease gonorrhea. IRIS can easily be applied to examine multiple protein-protein, protein-nucleotide and nucleotide-nucleotide complexes simultaneously and demonstrated here that seventy percent of the predicted Fur boxes in promoter regions of iron-induced genes bound to Fur in vitro with a range of affinities as observed using this microarray screening technology. Combining binding data with mRNA expression levels in a gonococcal fur mutant strain allowed us to identify five new gonococcal genes under Fur-mediated direct regulation.

Computational and Biomolecular NMR Guided Design of Peptide Theraputics for Influenza A

Peptidomimetic drugs are a rapidly growing field for treatment of disease. With the current screening-based approach yielding fewer and fewer drug candidates, peptide drugs appear to be the next frontier of disease treatment. Still, the issues of structural stability and half-life exist for peptides due to the vast number of proteases in the cell. We combine computational structure-guided design and solution NMR techniques including 19F NMR to rapidly design and screen peptide inhibitors for both protein:protein interactions (PPI) and protein:nucleotide interactions (PNI). Structural stability is greatly increased by utilizing D-amino acids at alpha helix termini, which also may enhance metabolic half-life. Both PPI and PNI interfering peptides demonstrate promising binding activity to target sites.

Probing the amino acids critical for protein oligomerisation and protein–nucleotide interaction in Mycobacterium tuberculosis PII protein through integration of computational and experimental approaches

We investigated the interacting amino acids critical for the stability and ATP binding of Mycobacterium tuberculosis PII protein through a series of site specific mutagenesis experiments. We assessed the effect of mutants using glutaraldehyde crosslinking and size exclusion chromatography and isothermal titration calorimetry. Mutations in the amino acid pair R60–E62 affecting central electrostatic interaction resulted in insoluble proteins. Multiple sequence alignment of PII orthologs displayed a conserved pattern of charged residues at these positions. Mutation of amino acid D97 to a neutral residue was tolerated whereas positive charge was not acceptable. Mutation of R107 alone had no effect on trimer formation. However, the combination of neutral residues both at positions 97 and 107 was not acceptable even with the pair at 60–62 intact. Reversal of charge polarity could partially restore the interaction. The residues including K90, R101 and R103 with potential to form H-bonds to ATP are conserved throughout across numerous orthologs of PII but when mutated to Alanine, they did not show significant differences in the total free energy change of the interaction as examined through isothermal titration calorimetry. The ATP binding pattern showed anti-cooperativity using three-site binding model. We observed compensatory effect in enthalpy and entropy changes and these may represent structural adjustments to accommodate ATP in the cavity even in absence of some interactions to perform the requisite function. In this respect these small differences between the PII orthologs may have evolved to suite species specific physiological niches.

Nucleotide binding architecture for secreted cytotoxic endoribonucleases

Vertebrate secreted RNases are small cationic protein endowed with an endoribonuclease activity that belong to the RNase A superfamily and display diverse cytotoxic activities. In an effort to unravel their mechanism of action, we have analysed their nucleotide binding recognition patterns. General shared features with other nucleotide binding proteins were deduced from overall statistics on the available structure complexes at the Protein Data Bank and compared with the particularities of selected representative endoribonuclease families. Results were compared with other endoribonuclease representative families and with the overall protein-nucleotide interaction features. Preferred amino acids and atom types involved in pair bonding interactions were identified, defining the spatial motives for phosphate, base and ribose building blocks. Together with the conserved catalytic triad at the active site, variability was observed for secondary binding subsites that may contribute to the proper substrate alignment and could explain the distinct substrate preference patterns. Highly conserved binding patterns were identified for the pyrimidine and purine subsites at the main and secondary base subsites. Particular substitution could be ascribed to specific adenine or guanine specificities. Distribution of evolutionary conserved residues were compared to search for the structure determinants that underlie their diverse catalytic efficiency and those that may account for putative physiological substrate targets or other non-catalytic biological activities that contribute to the antipathogen role of the RNases involved in the host defence system. A side by side comparison with another endoribonuclease superfamily of secreted cytotoxic proteins, the microbial RNases, was carried on to analyse the common features and peculiarities that rule their substrate recognition. The data provides the structural basis for the development of applied therapies targeting cellular nucleotide polymers.

The catalytic cycle for ribonucleotide incorporation by human DNA Pol λ

Although most DNA polymerases discriminate against ribonucleotide triphosphaets (rNTPs) during DNA synthesis, recent studies have shown that large numbers of ribonucleotides are incorporated into the eukaryotic nuclear genome. Here, we investigate how a DNA polymerase can stably incorporate an rNTP. The X-ray crystal structure of a variant of human DNA polymerase λ reveals that the rNTP occupies the nucleotide binding pocket without distortion of the active site, despite an unfavorable interaction between the 2′-O and Tyr505 backbone carbonyl. This indicates an energetically unstable binding state for the rNTP, stabilized by additional protein–nucleotide interactions. Supporting this idea is the 200-fold lower catalytic efficiency for rNTP relative to deoxyribonucleotide triphosphate (dNTP) incorporation, reflecting a higher apparent Km value for the rNTP. Furthermore, distortion observed in the structure of the post-catalytic product complex suggests that once the bond between the α- and β-phosphates of the rNTP is broken, the unfavorable binding state of the ribonucleotide cannot be maintained. Finally, structural and biochemical evaluation of dNTP insertion onto an ribonucleotide monophosphate (rNMP)-terminated primer indicates that a primer-terminal rNMP does not impede extension. The results are relevant to how ribonucleotides are incorporated into DNA in vivo, during replication and during repair, perhaps especially in non-proliferating cells when rNTP:dNTP ratios are high.

Conformational Flexibility of Glycosylated Unstructured Peptides

Glycosylation of proteins plays an important role in molecular recognition among proteins with implications for a variety of cellular processes. The large amount of glycan variants enables interactions of exquisite specificity. Glycoproteins often are partially or fully disordered and intrinsically unstructured regions in proteins are known for mediating many protein-protein or protein-nucleotide interactions during regulation of transcription, translation, and cellular signal transduction. The question arises how conjugated glycans influence protein and peptide conformational dynamics and by that modify their biological activity. We compare the conformational dynamics of unstructured polypeptides consisting of eight glycine-serine repeat units with and without glycosylated serine units. We synthesized glycine-serine repeats with O-conjugated beta-galactose at every serine residue by solid-phase synthesis with glycosylated dipeptides as building blocks. Introducing an organic oxazine dye and tryptophan at either end of these peptides allows measurements of end-to-end contact kinetics. Upon van-der-Waals contact between dye and tryptophan fluorescence is quenched by photo induced electron transfer (PET). Fluorescence intensity fluctuations are analyzed using fluorescence correlation spectroscopy (FCS) and contact formation rate constants are determined. We studied influences from solvent viscosity and temperature on end-to-end contact formation rates and found a decrease of rate constants upon glycosylation. Arrhenius analysis of end-to-end contact rates yields enhanced activation energy for the glycosylated sample. The viscosity dependence of the relaxation rates shows that contact formation still is viscosity controlled. This study confirms previous reports that glycosylation has a significant influence on peptide dynamics mostly through steric hindrance.

Systems biochemistry approaches to vertebrate phototransduction: towards a molecular understanding of disease

Phototransduction in vertebrates represents a paradigm of signalling pathways, in particular those mediated by G-protein-coupled receptors. The variety of protein-protein, protein-ion and protein-nucleotide interactions makes up an intricate network which is finely regulated by activating-deactivating molecules and chemical modifications. The holistic systems properties of the network allow for typical adaptation mechanisms, which ultimately result in fine adjustments of sensitivity and electrical response of the photoreceptor cells to the broad range of light stimuli. In the present article, we discuss a novel bottom-up strategy to study the phototransduction cascade in rod cells starting from the underlying biochemistry. The resulting network model can be simulated and the predicted dynamic behaviour directly compared with data from electrophysiological experiments performed on a wide range of illumination conditions. The advantage of applying procedures typical of systems theory to a well-studied signalling pathway is also discussed. Finally, the potential application to the study of the molecular basis of retinal diseases is highlighted through a practical example, namely the simulation of conditions related to Leber congenital amaurosis.