Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Conserved Glutamate Residues Glu-343 and Glu-519 Provide Mechanistic Insights into Cation/Nucleoside Cotransport by Human Concentrative Nucleoside Transporter hCNT3

Human concentrative nucleoside transporter 3 (hCNT3) utilizes electrochemical gradients of both Na⁺ and H⁺ to accumulate pyrimidine and purine nucleosides within cells. We have employed radioisotope flux and electrophysiological techniques in combination with site-directed mutagenesis and heterologous expression in Xenopus oocytes to identify two conserved pore-lining glutamate residues (Glu-343 and Glu-519) with essential roles in hCNT3 Na⁺/nucleoside and H⁺/nucleoside cotransport. Mutation of Glu-343 and Glu-519 to aspartate, glutamine, and cysteine severely compromised hCNT3 transport function, and changes included altered nucleoside and cation activation kinetics (all mutants), loss or impairment of H⁺ dependence (all mutants), shift in Na⁺:nucleoside stoichiometry from 2:1 to 1:1 (E519C), complete loss of catalytic activity (E519Q) and, similar to the corresponding mutant in Na⁺-specific hCNT1, uncoupled Na⁺ currents (E343Q). Consistent with close-proximity integration of cation/solute-binding sites within a common cation/permeant translocation pore, mutation of Glu-343 and Glu-519 also altered hCNT3 nucleoside transport selectivity. Both residues were accessible to the external medium and inhibited by p-chloromercuribenzene sulfonate when converted to cysteine.Physiologic nucleosides and the majority of synthetic nucleoside analogs with antineoplastic and/or antiviral activity are hydrophilic molecules that require specialized plasma membrane nucleoside transporter (NT)³ proteins for transport into or out of cells (1–4). NT-mediated transport is required for nucleoside metabolism by salvage pathways and is a critical determinant of the pharmacologic actions of nucleoside drugs (3–6). By regulating adenosine availability to purinoreceptors, NTs also modulate a diverse array of physiological processes, including neurotransmission, immune responses, platelet aggregation, renal function, and coronary vasodilation (4, 6, 7). Two structurally unrelated NT families of integral membrane proteins exist in human and other mammalian cells and tissues as follows: the SLC28 concentrative nucleoside transporter (CNT) family and the SLC29 equilibrative nucleoside transporter (ENT) family (3, 4, 6, 8, 9). ENTs are normally present in most, possibly all, cell types (4, 6, 8). CNTs, in contrast, are found predominantly in intestinal and renal epithelia and other specialized cell types, where they have important roles in absorption, secretion, distribution, and elimination of nucleosides and nucleoside drugs (1–3, 5, 6, 9).The CNT protein family in humans is represented by three members, hCNT1, hCNT2, and hCNT3. Belonging to a CNT subfamily phylogenetically distinct from hCNT1/2, hCNT3 utilizes electrochemical gradients of both Na⁺ and H⁺ to accumulate a broad range of pyrimidine and purine nucleosides and nucleoside drugs within cells (10, 11). hCNT1 and hCNT2, in contrast, are Na⁺-specific and transport pyrimidine and purine nucleosides, respectively (11–13). Together, hCNT1–3 account for the three major concentrative nucleoside transport processes of human and other mammalian cells. Nonmammalian members of the CNT protein family that have been characterized functionally include hfCNT, a second member of the CNT3 subfamily from the ancient marine prevertebrate the Pacific hagfish Eptatretus stouti (14), CeCNT3 from Caenorhabditis elegans (15), CaCNT from Candida albicans (16), and the bacterial nucleoside transporter NupC from Escherichia coli (17). hfCNT is Na⁺- but not H⁺-coupled, whereas CeCNT3, CaCNT, and NupC are exclusively H⁺-coupled. Na⁺:nucleoside coupling stoichiometries are 1:1 for hCNT1 and hCNT2 and 2:1 for hCNT3 and hfCNT3 (11, 14). H⁺:nucleoside coupling ratios for hCNT3 and CaCNT are 1:1 (11, 16).Although much progress has been made in molecular studies of ENT proteins (4, 6, 8), studies of structurally and functionally important regions and residues within the CNT protein family are still at an early stage. Topological investigations suggest that hCNT1–3 and other eukaryote CNT family members have a 13 (or possibly 15)-transmembrane helix (TM) architecture, and multiple alignments reveal strong sequence similarities within the C-terminal half of the proteins (18). Prokaryotic CNTs lack the first three TMs of their eukaryotic counterparts, and functional expression of N-terminally truncated human and rat CNT1 in Xenopus oocytes has established that these three TMs are not required for Na⁺-dependent uridine transport activity (18). Consistent with this finding, chimeric studies involving hCNT1 and hfCNT (14) and hCNT1 and hCNT3 (19) have demonstrated that residues involved in Na⁺- and H⁺-coupling reside in the C-terminal half of the protein. Present in this region of the transporter, but of unknown function, is a highly conserved (G/A)XKX₃NEFVA(Y/M/F) motif common to all eukaryote and prokaryote CNTs.By virtue of their negative charge and consequent ability to interact directly with coupling cations and/or participate in cation-induced and other protein conformational transitions, glutamate and aspartate residues play key functional and structural roles in a broad spectrum of mammalian and bacterial cation-coupled transporters (20–30). Little, however, is known about their role in CNTs. This study builds upon a recent mutagenesis study of conserved glutamate and aspartate residues in hCNT1 (31) to undertake a parallel in depth investigation of corresponding residues in hCNT3. By employing the multifunctional capability of hCNT3 as a template for these studies, this study provides novel mechanistic insights into the molecular mechanism(s) of CNT-mediated cation/nucleoside cotransport, including the role of the (G/A)XKX₃NEFVA(Y/M/F) motif.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Repeated Domains of Leptospira Immunoglobulin-like Proteins Interact with Elastin and Tropoelastin

Leptospira spp., the causative agents of leptospirosis, adhere to components of the extracellular matrix, a pivotal role for colonization of host tissues during infection. Previously, we and others have shown that Leptospira immunoglobulin-like proteins (Lig) of Leptospira spp. bind to fibronectin, laminin, collagen, and fibrinogen. In this study, we report that Leptospira can be immobilized by human tropoelastin (HTE) or elastin from different tissues, including lung, skin, and blood vessels, and that Lig proteins can bind to HTE or elastin. Moreover, both elastin and HTE bind to the same LigB immunoglobulin-like domains, including LigBCon4, LigBCen7′–8, LigBCen9, and LigBCen12 as demonstrated by enzyme-linked immunosorbent assay (ELISA) and competition ELISAs. The LigB immunoglobulin-like domain binds to the 17th to 27th exons of HTE (17–27HTE) as determined by ELISA (LigBCon4, K_D = 0.50 μm; LigBCen7′–8, K_D = 0.82 μm; LigBCen9, K_D = 1.54 μm; and LigBCen12, K_D = 0.73 μm). The interaction of LigBCon4 and 17–27HTE was further confirmed by steady state fluorescence spectroscopy (K_D = 0.49 μm) and ITC (K_D = 0.54 μm). Furthermore, the binding was enthalpy-driven and affected by environmental pH, indicating it is a charge-charge interaction. The binding affinity of LigBCon4D341N to 17–27HTE was 4.6-fold less than that of wild type LigBCon4. In summary, we show that Lig proteins of Leptospira spp. interact with elastin and HTE, and we conclude this interaction may contribute to Leptospira adhesion to host tissues during infection.Pathogenic Leptospira spp. are spirochetes that cause leptospirosis, a serious infectious disease of people and animals (1, 2). Weil syndrome, the severe form of leptospiral infection, leads to multiorgan damage, including liver failure (jaundice), renal failure (nephritis), pulmonary hemorrhage, meningitis, abortion, and uveitis (3, 4). Furthermore, this disease is not only prevalent in many developing countries, it is reemerging in the United States (3). Although leptospirosis is a serious worldwide zoonotic disease, the pathogenic mechanisms of Leptospira infection remain enigmatic. Recent breakthroughs in applying genetic tools to Leptospira may facilitate studies on the molecular pathogenesis of leptospirosis (5–8).The attachment of pathogenic Leptospira spp. to host tissues is critical in the early phase of Leptospira infection. Leptospira spp. adhere to host tissues to overcome mechanical defense systems at tissue surfaces and to initiate colonization of specific tissues, such as the lung, kidney, and liver. Leptospira invade hosts tissues through mucous membranes or injured epidermis, coming in contact with subepithelial tissues. Here, certain bacterial outer surface proteins serve as microbial surface components recognizing adhesive matrix molecules (MSCRAMMs)² to mediate the binding of bacteria to different extracellular matrices (ECMs) of host cells (9). Several leptospiral MSCRAMMs have been identified (10–18), and we speculate that more will be identified in the near future.Lig proteins are distributed on the outer surface of pathogenic Leptospira, and the expression of Lig protein is only found in low passage strains (14, 16, 17), probably induced by environmental cues such as osmotic or temperature changes (19). Lig proteins can bind to fibrinogen and a variety of ECMs, including fibronectin (Fn), laminin, and collagen, thereby mediating adhesion to host cells (20–23). Lig proteins also constitute good vaccine candidates (24–26).Elastin is a component of ECM critical to tissue elasticity and resilience and is abundant in skin, lung, blood vessels, placenta, uterus, and other tissues (27–29). Tropoelastin is the soluble precursor of elastin (28). During the major phase of elastogenesis, multiple tropoelastin molecules associate through coacervation (30–32). Because of the abundance of elastin or tropoelastin on the surface of host cells, several bacterial MSCRAMMs use elastin and/or tropoelastin to mediate adhesion during the infection process (33–35).Because leptospiral infection is known to cause severe pulmonary hemorrhage (36, 37) and abortion (38), we hypothesize that some leptospiral MSCRAMMs may interact with elastin and/or tropoelastin in these elastin-rich tissues. This is the first report that Lig proteins of Leptospira interact with elastin and tropoelastin, and the interactions are mediated by several specific immunoglobulin-like domains of Lig proteins, including LigBCon4, LigBCen7′–8, LigBCen9, and LigBCen12, which bind to the 17th to 27th exons of human tropoelastin (HTE).     

Vinyl Sulfones as Antiparasitic Agents and a Structural Basis for Drug Design

Cysteine proteases of the papain superfamily are implicated in a number of cellular processes and are important virulence factors in the pathogenesis of parasitic disease. These enzymes have therefore emerged as promising targets for antiparasitic drugs. We report the crystal structures of three major parasite cysteine proteases, cruzain, falcipain-3, and the first reported structure of rhodesain, in complex with a class of potent, small molecule, cysteine protease inhibitors, the vinyl sulfones. These data, in conjunction with comparative inhibition kinetics, provide insight into the molecular mechanisms that drive cysteine protease inhibition by vinyl sulfones, the binding specificity of these important proteases and the potential of vinyl sulfones as antiparasitic drugs.Sleeping sickness (African trypanosomiasis), caused by Trypanosoma brucei, and malaria, caused by Plasmodium falciparum, are significant, parasitic diseases of sub-Saharan Africa (1). Chagas'' disease (South American trypanosomiasis), caused by Trypanosoma cruzi, affects approximately, 16–18 million people in South and Central America. For all three of these protozoan diseases, resistance and toxicity to current therapies makes treatment increasingly problematic, and thus the development of new drugs is an important priority (2–4).T. cruzi, T. brucei, and P. falciparum produce an array of potential target enzymes implicated in pathogenesis and host cell invasion, including a number of essential and closely related papain-family cysteine proteases (5, 6). Inhibitors of cruzain and rhodesain, major cathepsin L-like papain-family cysteine proteases of T. cruzi and T. brucei rhodesiense (7–10) display considerable antitrypanosomal activity (11, 12), and some classes have been shown to cure T. cruzi infection in mouse models (11, 13, 14).In P. falciparum, the papain-family cysteine proteases falcipain-2 (FP-2)⁶ and falcipain-3 (FP-3) are known to catalyze the proteolysis of host hemoglobin, a process that is essential for the development of erythrocytic parasites (15–17). Specific inhibitors, targeted to both enzymes, display antiplasmodial activity (18). However, although the abnormal phenotype of FP-2 knock-outs is “rescued” during later stages of trophozoite development (17), FP-3 has proved recalcitrant to gene knock-out (16) suggesting a critical function for this enzyme and underscoring its potential as a drug target.Sequence analyses and substrate profiling identify cruzain, rhodesain, and FP-3 as cathepsin L-like, and several studies describe classes of small molecule inhibitors that target multiple cathepsin L-like cysteine proteases, some with overlapping antiparasitic activity (19–22). Among these small molecules, vinyl sulfones have been shown to be effective inhibitors of a number of papain family-like cysteine proteases (19, 23–27). Vinyl sulfones have many desirable attributes, including selectivity for cysteine proteases over serine proteases, stable inactivation of the target enzyme, and relative inertness in the absence of the protease target active site (25). This class has also been shown to have desirable pharmacokinetic and safety profiles in rodents, dogs, and primates (28, 29). We have determined the crystal structures of cruzain, rhodesain, and FP-3 bound to vinyl sulfone inhibitors and performed inhibition kinetics for each enzyme. Our results highlight key areas of interaction between proteases and inhibitors. These results help validate the vinyl sulfones as a class of antiparasitic drugs and provide structural insights to facilitate the design or modification of other small molecule inhibitor scaffolds.     

Loop 2 Structure in Glycine and GABAA Receptors Plays a Key Role in Determining Ethanol Sensitivity

The present study tests the hypothesis that the structure of extracellular domain Loop 2 can markedly affect ethanol sensitivity in glycine receptors (GlyRs) and γ-aminobutyric acid type A receptors (GABA_ARs). To test this, we mutated Loop 2 in the α1 subunit of GlyRs and in the γ subunit of α1β2γ2GABA_ARs and measured the sensitivity of wild type and mutant receptors expressed in Xenopus oocytes to agonist, ethanol, and other agents using two-electrode voltage clamp. Replacing Loop 2 of α1GlyR subunits with Loop 2 from the δGABA_AR (δL2), but not the γGABA_AR subunit, reduced ethanol threshold and increased the degree of ethanol potentiation without altering general receptor function. Similarly, replacing Loop 2 of the γ subunit of GABA_ARs with δL2 shifted the ethanol threshold from 50 mm in WT to 1 mm in the GABA_A γ-δL2 mutant. These findings indicate that the structure of Loop 2 can profoundly affect ethanol sensitivity in GlyRs and GABA_ARs. The δL2 mutations did not affect GlyR or GABA_AR sensitivity, respectively, to Zn²⁺ or diazepam, which suggests that these δL2-induced changes in ethanol sensitivity do not extend to all allosteric modulators and may be specific for ethanol or ethanol-like agents. To explore molecular mechanisms underlying these results, we threaded the WT and δL2 GlyR sequences onto the x-ray structure of the bacterial Gloeobacter violaceus pentameric ligand-gated ion channel homologue (GLIC). In addition to being the first GlyR model threaded on GLIC, the juxtaposition of the two structures led to a possible mechanistic explanation for the effects of ethanol on GlyR-based on changes in Loop 2 structure.Alcohol abuse and dependence are significant problems in our society, with ∼14 million people in the United States being affected (1, 2). Alcohol causes over 100,000 deaths in the United States, and alcohol-related issues are estimated to cost nearly 200 billion dollars annually (2). To address this, considerable attention has focused on the development of medications to prevent and treat alcohol-related problems (3–5). The development of such medications would be aided by a clear understanding of the molecular structures on which ethanol acts and how these structures influence receptor sensitivity to ethanol.Ligand-gated ion channels (LGICs)² have received substantial attention as putative sites of ethanol action that cause its behavioral effects (6–12). Research in this area has focused on investigating the effects of ethanol on two large superfamilies of LGICs: 1) the Cys-loop superfamily of LGICs (13, 14), whose members include nicotinic acetylcholine, 5-hydroxytryptamine₃, γ-aminobutyric acid type A (GABA_A), γ-aminobutyric acid type C, and glycine receptors (GlyRs) (10, 11, 15–20) and 2) the glutamate superfamily, including N-methyl d-aspartate, α-amino-3-hydroxyisoxazolepropionic acid, and kainate receptors (21, 22). Recent studies have also begun investigating ethanol action in the ATP-gated P2X superfamily of LGICs (23–25).A series of studies that employed chimeric and mutagenic strategies combined with sulfhydryl-specific labeling identified key regions within Cys-loop receptors that appear to be initial targets for ethanol action that also can determine the sensitivity of the receptors to ethanol (7–12, 18, 19, 26–30). This work provides several lines of evidence that position 267 and possibly other sites in the transmembrane (TM) domain of GlyRs and homologous sites in GABA_ARs are targets for ethanol action and that mutations at these sites can influence ethanol sensitivity (8, 9, 26, 31).Growing evidence from GlyRs indicates that ethanol also acts on the extracellular domain. The initial findings came from studies demonstrating that α1GlyRs are more sensitive to ethanol than are α2GlyRs despite the high (∼78%) sequence homology between α1GlyRs and α2GlyRs (32). Further work found that an alanine to serine exchange at position 52 (A52S) in Loop 2 can eliminate the difference in ethanol sensitivity between α1GlyRs and α2GlyRs (18, 20, 33). These studies also demonstrated that mutations at position 52 in α1GlyRS and the homologous position 59 in α2GlyRs controlled the sensitivity of these receptors to a novel mechanistic ethanol antagonist (20). Collectively, these studies suggest that there are multiple sites of ethanol action in α1GlyRs, with one site located in the TM domain (e.g. position 267) and another in the extracellular domain (e.g. position 52).Subsequent studies revealed that the polarity of the residue at position 52 plays a key role in determining the sensitivity of GlyRs to ethanol (20). The findings with polarity in the extracellular domain contrast with the findings at position 267 in the TM domain, where molecular volume, but not polarity, significantly affected ethanol sensitivity (9). Taken together, these findings indicate that the physical-chemical parameters of residues at positions in the extracellular and TM domains that modulate ethanol effects and/or initiate ethanol action in GlyRs are not uniform. Thus, knowledge regarding the physical-chemical properties that control agonist and ethanol sensitivity is key for understanding the relationship between the structure and the actions of ethanol in LGICs (19, 31, 34–40).GlyRs and GABA_ARs, which differ significantly in their sensitivities to ethanol, offer a potential method for identifying the structures that control ethanol sensitivity. For example, α1GlyRs do not reliably respond to ethanol concentrations less than 10 mm (32, 33, 41). Similarly, γ subunit-containing GABA_ARs (e.g. α1β2γ2), the most predominantly expressed GABA_ARs in the central nervous system, are insensitive to ethanol concentrations less than 50 mm (42, 43). In contrast, δ subunit-containing GABA_ARs (e.g. α4β3δ) have been shown to be sensitive to ethanol concentrations as low as 1–3 mm (44–51). Sequence alignment of α1GlyR, γGABA_AR, and δGABA_AR revealed differences between the Loop 2 regions of these receptor subunits. Since prior studies found that mutations of Loop 2 residues can affect ethanol sensitivity (19, 20, 39), the non-conserved residues in Loop 2 of GlyR and GABA_AR subunits could provide the physical-chemical and structural bases underlying the differences in ethanol sensitivity between these receptors.The present study tested the hypothesis that the structure of Loop 2 can markedly affect the ethanol sensitivity of GlyRs and GABA_ARs. To accomplish this, we performed multiple mutations that replaced the Loop 2 region of the α1 subunit in α1GlyRs and the Loop 2 region of the γ subunit of α1β2γ2 GABA_ARs with corresponding non-conserved residues from the δ subunit of GABA_AR and tested the sensitivity of these receptors to ethanol. As predicted, replacing Loop 2 of WT α1GlyRs with the homologous residues from the δGABA_AR subunit (δL2), but not the γGABA_AR subunit (γL2), markedly increased the sensitivity of the receptor to ethanol. Similarly, replacing the non-conserved residues of the γ subunit of α1β2γ2 GABA_ARs with δL2 also markedly increased ethanol sensitivity of GABA_ARs. These findings support the hypothesis and suggest that Loop 2 may play a role in controlling ethanol sensitivity across the Cys-loop superfamily of receptors. The findings also provide the basis for suggesting structure-function relationships in a new molecular model of the GlyR based on the bacterial Gloeobacter violaceus pentameric LGIC homologue (GLIC).     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.