Resistance gene-guided genome mining reveals the roseopurpurins as inhibitors of cyclin-dependent kinases.

With the significant increase in the availability of microbial genome sequences in recent years, resistance gene-guided genome mining has emerged as a powerful approach for identifying natural products with specific bioactivities. Here, we present the use of this approach to reveal the roseopurpurins as potent inhibitors of cyclin-dependent kinases (CDKs), a class of cell cycle regulators implicated in multiple cancers. We identified a biosynthetic gene cluster (BGC) with a putative resistance gene with homology to human CDK2. Using targeted gene disruption and transcription factor overexpression in Aspergillus uvarum, and heterologous expression of the BGC in Aspergillus nidulans, we demonstrated that roseopurpurin C (1) is produced by this cluster and characterized its biosynthesis. We determined the potency, specificity, and mechanism of action of 1 as well as multiple intermediates and shunt products produced from the BGC. We show that 1 inhibits human CDK2 with a Kiapp of 44 nM, demonstrates selectivity for clinically relevant members of the CDK family, and induces G1 cell cycle arrest in HCT116 cells. Structural analysis of 1 complexed with CDK2 revealed the molecular basis of ATP-competitive inhibition.

Deep neural network affinity model for BACE inhibitors in D3R Grand Challenge 4.

Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) offered a unique opportunity for designing and testing novel methodology for accurate docking and affinity prediction of ligands in an open and blinded manner. We participated in the beta-secretase 1 (BACE) Subchallenge which is comprised of cross-docking and redocking of 20 macrocyclic ligands to BACE and predicting binding affinity for 154 macrocyclic ligands. For this challenge, we developed machine learning models trained specifically on BACE. We developed a deep neural network (DNN) model that used a combination of both structure and ligand-based features that outperformed simpler machine learning models. According to the results released by D3R, we achieved a Spearman's rank correlation coefficient of 0.43(7) for predicting the affinity of 154 ligands. We describe the formulation of our machine learning strategy in detail. We compared the performance of DNN with linear regression, random forest, and support vector machines using ligand-based, structure-based, and combining both ligand and structure-based features. We compared different structures for our DNN and found that performance was highly dependent on fine optimization of the L2 regularization hyperparameter, alpha. We also developed a novel metric of ligand three-dimensional similarity inspired by crystallographic difference density maps to match ligands without crystal structures to similar ligands with known crystal structures. This report demonstrates that detailed parameterization, careful data training and implementation, and extensive feature analysis are necessary to obtain strong performance with more complex machine learning methods. Post hoc analysis shows that scoring functions based only on ligand features are competitive with those also using structural features. Our DNN approach tied for fifth in predicting BACE-ligand binding affinities.

RORγ Structural Plasticity and Druggability.

Retinoic acid receptor-related orphan receptor γ (RORγ) is a transcription factor regulating the expression of the pro-inflammatory cytokine IL-17 in human T helper 17 (Th17) cells. Activating RORγ can induce multiple IL-17-mediated autoimmune diseases but may also be useful for anticancer therapy. Its deep immunological functions make RORɣ an attractive drug target. Over 100 crystal structures have been published describing atomic interactions between RORɣ and agonists and inverse agonists. In this review, we focus on the role of dynamic properties and plasticity of the RORɣ orthosteric and allosteric binding sites by examining structural information from crystal structures and simulated models. We discuss the possible influences of allosteric ligands on the orthosteric binding site. We find that high structural plasticity favors the druggability of RORɣ, especially for allosteric ligands.

Recent Insights from Molecular Dynamics Simulations for G Protein-Coupled Receptor Drug Discovery.

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. Some ligands that bind to GPCRs activate different downstream signaling pathways. G protein activation, or -arrestin biased signaling, involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. -arrestin biased signaling has become a hot target for structure-based drug discovery. However, challenges include that there are few crystal structures available in the Protein Data Bank and that GPCRs are highly dynamic. Hence, molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators' interactions with receptors and ligands. Here, we highlight recent MD simulation studies and enhanced sampling methods used to study biased G protein-coupled receptor signaling and their conformational dynamics as well as applications to drug discovery.

Protection against ß-amyloid neurotoxicity by a non-toxic endogenous N-terminal ß-amyloid fragment and its active hexapeptide core sequence.

High levels (µM) of beta amyloid (Aß) oligomers are known to trigger neurotoxic effects, leading to synaptic impairment, behavioral deficits, and apoptotic cell death. The hydrophobic C-terminal domain of Aß, together with sequences critical for oligomer formation, is essential for this neurotoxicity. However, Aß at low levels (pM-nM) has been shown to function as a positive neuromodulator and this activity resides in the hydrophilic N-terminal domain of Aß. An N-terminal Aß fragment (1-15/16), found in cerebrospinal fluid, was also shown to be a highly active neuromodulator and to reverse Aß-induced impairments of long-term potentiation. Here, we show the impact of this N-terminal Aß fragment and a shorter hexapeptide core sequence in the Aß fragment (Aßcore: 10-15) to protect or reverse Aß-induced neuronal toxicity, fear memory deficits and apoptotic death. The neuroprotective effects of the N-terminal Aß fragment and Aßcore on Aß-induced changes in mitochondrial function, oxidative stress, and apoptotic neuronal death were demonstrated via mitochondrial membrane potential, live reactive oxygen species, DNA fragmentation and cell survival assays using a model neuroblastoma cell line (differentiated NG108-15) and mouse hippocampal neuron cultures. The protective action of the N-terminal Aß fragment and Aßcore against spatial memory processing deficits in amyloid precursor protein/PSEN1 (5XFAD) mice was demonstrated in contextual fear conditioning. Stabilized derivatives of the N-terminal Aßcore were also shown to be fully protective against Aß-triggered oxidative stress. Together, these findings indicate an endogenous neuroprotective role for the N-terminal Aß fragment, while active stabilized N-terminal Aßcore derivatives offer the potential for therapeutic application.

Structural and Biophysical Characterization of the Mycobacterium tuberculosis Protein Rv0577, a Protein Associated with Neutral Red Staining of Virulent Tuberculosis Strains and Homologue of the Streptomyces coelicolor Protein KbpA.

Mycobacterium tuberculosis protein Rv0577 is a prominent antigen in tuberculosis patients, the component responsible for neutral red staining of virulent strains of M. tuberculosis, a putative component in a methylglyoxal detoxification pathway, and an agonist of toll-like receptor 2. It also has an amino acid sequence that is 36% identical to that of Streptomyces coelicolor AfsK-binding protein A (KbpA), a component in the complex secondary metabolite pathways in the Streptomyces genus. To gain insight into the biological function of Rv0577 and the family of KpbA kinase regulators, the crystal structure for Rv0577 was determined to a resolution of 1.75 Å, binding properties with neutral red and deoxyadenosine were surveyed, backbone dynamics were measured, and thermal stability was assayed by circular dichroism spectroscopy. The protein is composed of four approximate repeats with a ßαßßß topology arranged radially in consecutive pairs to form two continuous eight-strand ß-sheets capped on both ends with an α-helix. The two ß-sheets intersect in the center at roughly a right angle and form two asymmetric deep "saddles" that may serve to bind ligands. Nuclear magnetic resonance chemical shift perturbation experiments show that neutral red and deoxyadenosine bind to Rv0577. Binding to deoxyadenosine is weaker with an estimated dissociation constants of 4.1 ± 0.3 mM for saddle 1. Heteronuclear steady-state {1H}-15N nuclear Overhauser effect, T1, and T2 values were generally uniform throughout the sequence with only a few modest pockets of differences. Circular dichroism spectroscopy characterization of the thermal stability of Rv0577 indicated irreversible unfolding upon heating with an estimated melting temperature of 56 °C.

Non-invasive intravital imaging of cellular differentiation with a bright red-excitable fluorescent protein.

A method for non-invasive visualization of genetically labeled cells in animal disease models with micrometer-level resolution would greatly facilitate development of cell-based therapies. Imaging of fluorescent proteins (FPs) using red excitation light in the 'optical window' above 600 nm is one potential method for visualizing implanted cells. However, previous efforts to engineer FPs with peak excitation beyond 600 nm have resulted in undesirable reductions in brightness. Here we report three new red-excitable monomeric FPs obtained by structure-guided mutagenesis of mNeptune. Two of these, mNeptune2 and mNeptune2.5, demonstrate improved maturation and brighter fluorescence than mNeptune, whereas the third, mCardinal, has a red-shifted excitation spectrum without reduction in brightness. We show that mCardinal can be used to non-invasively and longitudinally visualize the differentiation of myoblasts into myocytes in living mice with high anatomical detail.

Specificity and mechanism of TonB-dependent ferric catecholate uptake by Fiu.

We studied the Escherichia coli outer membrane protein Fiu, a presumed transporter of monomeric ferric catecholates, by introducing Cys residues in its surface loops and modifying them with fluorescein maleimide (FM). Fiu-FM bound iron complexes of the tricatecholate siderophore enterobactin (FeEnt) and glucosylated enterobactin (FeGEnt), their dicatecholate degradation product Fe(DHBS)2 (FeEnt*), the monocatecholates dihydroxybenzoic acid (FeDHBA) and dihydroxybenzoyl serine (FeDHBS), and the siderophore antibiotics cefiderocol (FDC) and MB-1. Unlike high-affinity ligand-gated porins (LGPs), Fiu-FM had only micromolar affinity for iron complexes. Its apparent KD values for FeDHBS, FeDHBA, FeEnt*, FeEnt, FeGEnt, FeFDC, and FeMB-1 were 0.1, 0.7, 0.7, 1.0, 0.3, 0.4, and 4 µM, respectively. Despite its broad binding abilities, the transport repertoires of E. coli Fiu, as well as those of Cir and FepA, were less broad. Fiu only transported FeEnt*. Cir transported FeEnt* and FeDHBS (weakly); FepA transported FeEnt, FeEnt*, and FeDHBA. Both Cir and FepA bound FeGEnt, albeit with lower affinity. Related transporters of Acinetobacter baumannii (PiuA, PirA, BauA) had similarly moderate affinity and broad specificity for di- or monomeric ferric catecholates. Both microbiological and radioisotopic experiments showed Fiu's exclusive transport of FeEnt*, rather than ferric monocatecholate compounds. Molecular docking and molecular dynamics simulations predicted three binding sites for FeEnt*in the external vestibule of Fiu, and a fourth site deeper in its interior. Alanine scanning mutagenesis in the outermost sites (1a, 1b, and 2) decreased FeEnt* binding affinity as much as 20-fold and reduced or eliminated FeEnt* uptake. Finally, the molecular dynamics simulations suggested a pathway of FeEnt* movement through Fiu that may generally describe the process of metal transport by TonB-dependent receptors.

Drug Discovery in Low Data Regimes: Leveraging a Computational Pipeline for the Discovery of Novel SARS-CoV-2 Nsp14-MTase Inhibitors.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to significant global morbidity and mortality. A crucial viral protein, the non-structural protein 14 (nsp14), catalyzes the methylation of viral RNA and plays a critical role in viral genome replication and transcription. Due to the low mutation rate in the nsp region among various SARS-CoV-2 variants, nsp14 has emerged as a promising therapeutic target. However, discovering potential inhibitors remains a challenge. In this work, we introduce a computational pipeline for the rapid and efficient identification of potential nsp14 inhibitors by leveraging virtual screening and the NCI open compound collection, which contains 250,000 freely available molecules for researchers worldwide. The introduced pipeline provides a cost-effective and efficient approach for early-stage drug discovery by allowing researchers to evaluate promising molecules without incurring synthesis expenses. Our pipeline successfully identified seven promising candidates after experimentally validating only 40 compounds. Notably, we discovered NSC620333, a compound that exhibits a strong binding affinity to nsp14 with a dissociation constant of 427 ± 84 nM. In addition, we gained new insights into the structure and function of this protein through molecular dynamics simulations. We identified new conformational states of the protein and determined that residues Phe367, Tyr368, and Gln354 within the binding pocket serve as stabilizing residues for novel ligand interactions. We also found that metal coordination complexes are crucial for the overall function of the binding pocket. Lastly, we present the solved crystal structure of the nsp14-MTase complexed with SS148 (PDB:8BWU), a potent inhibitor of methyltransferase activity at the nanomolar level (IC50 value of 70 ± 6 nM). Our computational pipeline accurately predicted the binding pose of SS148, demonstrating its effectiveness and potential in accelerating drug discovery efforts against SARS-CoV-2 and other emerging viruses.

Ferritin protein nanocage ion channels: gating by N-terminal extensions.

Ferritin protein nanocages, self-assembled from four-α-helix bundle subunits, use Fe(2+) and oxygen to synthesize encapsulated, ferric oxide minerals. Ferritin minerals are iron concentrates stored for cell growth. Ferritins are also antioxidants, scavenging Fenton chemistry reactants. Channels for iron entry and exit consist of helical hairpin segments surrounding the 3-fold symmetry axes of the ferritin nanocages. We now report structural differences caused by amino acid substitutions in the Fe(2+) ion entry and exit channels and at the cytoplasmic pores, from high resolution (1.3-1.8 Å) protein crystal structures of the eukaryotic model ferritin, frog M. Mutations that eliminate conserved ionic or hydrophobic interactions between Arg-72 and Asp-122 and between Leu-110 and Leu-134 increase flexibility in the ion channels, cytoplasmic pores, and/or the N-terminal extensions of the helix bundles. Decreased ion binding in the channels and changes in ordered water are also observed. Protein structural changes coincide with increased Fe(2+) exit from dissolved, ferric minerals inside ferritin protein cages; Fe(2+) exit from ferritin cages depends on a complex, surface-limited process to reduce and dissolve the ferric mineral. High concentrations of bovine serum albumin or lysozyme (protein crowders) to mimic the cytoplasm restored Fe(2+) exit in the variants to wild type. The data suggest that fluctuations in pore structure control gating. The newly identified role of the ferritin subunit N-terminal extensions in gating Fe(2+) exit from the cytoplasmic pores strengthens the structural and functional analogies between ferritin ion channels in the water-soluble protein assembly and membrane protein ion channels gated by cytoplasmic N-terminal peptides.

Development, Characterization, and Structural Analysis of a Genetically Encoded Red Fluorescent Peroxynitrite Biosensor.

Boronic acid-containing fluorescent molecules have been widely used to sense hydrogen peroxide and peroxynitrite, which are important reactive oxygen and nitrogen species in biological systems. However, it has been challenging to gain specificity. Our previous studies developed genetically encoded, green fluorescent peroxynitrite biosensors by genetically incorporating a boronic acid-containing noncanonical amino acid (ncAA), p-boronophenylalanine (pBoF), into the chromophore of circularly permuted green fluorescent proteins (cpGFPs). In this work, we introduced pBoF to amino acid residues spatially close to the chromophore of an enhanced circularly permuted red fluorescent protein (ecpApple). Our effort has resulted in two responsive ecpApple mutants: one bestows reactivity toward both peroxynitrite and hydrogen peroxide, while the other, namely, pnRFP, is a selective red fluorescent peroxynitrite biosensor. We characterized pnRFP in vitro and in live mammalian cells. We further studied the structure and sensing mechanism of pnRFP using X-ray crystallography, 11B-NMR, and computational methods. The boron atom in pnRFP adopts an sp2-hybridization geometry in a hydrophobic pocket, and the reaction of pnRFP with peroxynitrite generates a product with a twisted chromophore, corroborating the observed "turn-off" fluorescence response. Thus, this study extends the color palette of genetically encoded peroxynitrite biosensors, provides insight into the response mechanism of the new biosensor, and demonstrates the versatility of using protein scaffolds to modulate chemoreactivity.

Computational approaches for the design of modulators targeting protein-protein interactions.

BACKGROUND: Protein-protein interactions (PPIs) are intriguing targets for designing novel small-molecule inhibitors. The role of PPIs in various infectious and neurodegenerative disorders makes them potential therapeutic targets . Despite being portrayed as undruggable targets, due to their flat surfaces, disorderedness, and lack of grooves. Recent progresses in computational biology have led researchers to reconsider PPIs in drug discovery. AREAS COVERED: In this review, we introduce in-silico methods used to identify PPI interfaces and present an in-depth overview of various computational methodologies that are successfully applied to annotate the PPIs. We also discuss several successful case studies that use computational tools to understand PPIs modulation and their key roles in various physiological processes. EXPERT OPINION: Computational methods face challenges due to the inherent flexibility of proteins, which makes them expensive, and result in the use of rigid models. This problem becomes more significant in PPIs due to their flexible and flat interfaces. Computational methods like molecular dynamics (MD) simulation and machine learning can integrate the chemical structure data into biochemical and can be used for target identification and modulation. These computational methodologies have been crucial in understanding the structure of PPIs, designing PPI modulators, discovering new drug targets, and predicting treatment outcomes.

A Bright, Nontoxic, and Non-aggregating red Fluorescent Protein for Long-Term Labeling of Fine Structures in Neurons.

Red fluorescent proteins are useful as morphological markers in neurons, often complementing green fluorescent protein-based probes of neuronal activity. However, commonly used red fluorescent proteins show aggregation and toxicity in neurons or are dim. We report the engineering of a bright red fluorescent protein, Crimson, that enables long-term morphological labeling of neurons without aggregation or toxicity. Crimson is similar to mCherry and mKate2 in fluorescence spectra but is 100 and 28% greater in molecular brightness, respectively. We used a membrane-localized Crimson-CAAX to label thin neurites, dendritic spines and filopodia, enhancing detection of these small structures compared to cytosolic markers.

Bee-safe peptidomimetic acaricides achieved by comparative genomics.

The devastating Varroa mite (Varroa destructor Anderson and Trueman) is an obligatory ectoparasite of the honey bee, contributing to significant colony losses in North America and throughout the world. The limited number of conventional acaricides to reduce Varroa mites and prevent disease in honey bee colonies is challenged with wide-spread resistance and low target-site selectivity. Here, we propose a biorational approach using comparative genomics for the development of honey bee-safe and selective acaricides targeting the Varroa mite-specific neuropeptidergic system regulated by proctolin, which is lacking in the honey bee. Proctolin is a highly conserved pentapeptide RYLPT (Arg-Tyr-Leu-Pro-Thr) known to act through a G protein-coupled receptor to elicit myotropic activity in arthropod species. A total of 33 different peptidomimetic and peptide variants were tested on the Varroa mite proctolin receptor. Ligand docking model and mutagenesis studies revealed the importance of the core aromatic residue Tyr2 in the proctolin ligand. Peptidomimetics were observed to have significant oral toxicity leading to the paralysis and death of Varroa mites, while there were no negative effects observed for honey bees. We have demonstrated that a taxon-specific physiological target identified by advanced genomics information offers an opportunity to develop Varroa mite-selective acaricides, hence, expedited translational processes.

A review of epidemiology and public health control measures of COVID-19 variants in Hong Kong, December 2020 to June 2021.

Background: The emergence of coronavirus disease 2019 (COVID-19) variants posed considerable threats to the global public health. We reviewed the epidemiology of variant cases and control measures implemented in Hong Kong. Methods: The epidemiological characteristics and the temporal trend of the COVID-19 variant cases and local clusters in Hong Kong, and the corresponding public health control measures were reviewed. Results: Between December 2020 and June 2021, 393 variant cases were reported, including 153, 59 and 79 cases of Alpha, Beta and Delta variants with no Gamma variant. The vast majority (378, 96.2%) were imported cases. Since early June 2021, Delta variant had taken over Alpha as the dominant strain. Public health control measures, including risk-stratified quarantine and testing requirements for inbound travellers, banning of flights from extremely high-risk areas, enhanced contact tracing and quarantine, were implemented. Among the 3 clusters involving local transmissions, 2 were linked to imported cases while the source of the remaining one was unknown. Discussion: Amid the global surges of COVID-19 variants, Hong Kong had continued to limit and prevent the occurrence of community-wide outbreak. Ongoing control strategies should be constantly reviewed and adjusted in response to the global and local COVID-19 situation.

A high-performance genetically encoded fluorescent indicator for in vivo cAMP imaging.

cAMP is a key second messenger that regulates diverse cellular functions including neural plasticity. However, the spatiotemporal dynamics of intracellular cAMP in intact organisms are largely unknown due to low sensitivity and/or brightness of current genetically encoded fluorescent cAMP indicators. Here, we report the development of the new circularly permuted GFP (cpGFP)-based cAMP indicator G-Flamp1, which exhibits a large fluorescence increase (a maximum ΔF/F0 of 1100% in HEK293T cells), decent brightness, appropriate affinity (a Kd of 2.17 µM) and fast response kinetics (an association and dissociation half-time of 0.20 and 0.087 s, respectively). Furthermore, the crystal structure of the cAMP-bound G-Flamp1 reveals one linker connecting the cAMP-binding domain to cpGFP adopts a distorted ß-strand conformation that may serve as a fluorescence modulation switch. We demonstrate that G-Flamp1 enables sensitive monitoring of endogenous cAMP signals in brain regions that are implicated in learning and motor control in living organisms such as fruit flies and mice.

Co-circulation of two SARS-CoV-2 variant strains within imported pet hamsters in Hong Kong.

During the investigation of a pet shop outbreak of severe acute respiratory coronavirus 2 (SARS-CoV-2) with probable hamster-to-human transmission, the environmental and hamster samples in epidemiologically linked pet shops were found positive for SARS-CoV-2 Delta variant AY.127 strains which are phylogenetically closely related to patients and reported European strains. This interspecies' spill-over has triggered transmission in 58 patients epidemiologically linked to three pet shops. Incidentally, three dwarf hamsters imported from the Netherlands and centralized in a warehouse distributing animals to pet shops were positive for SARS-CoV-2 spike variant phylogenetically related to European B.1.258 strains from March 2020. This B.1.258 strain almost disappeared in July 2021. While no hamster-to-human transmission of B.1.258-like strain was found in this outbreak, molecular docking showed that its spike receptor-binding domain (RBD) has a similar binding energy to human ACE2 compared to that of Delta variant AY.127. Therefore, the potential of this B.1.258-related spike variant for interspecies jumping cannot be ignored. The co-circulation of B.1.258-related spike variants with Delta AY.127, which originated in Europe and was not previously found in Hong Kong, suggested that hamsters in our wholesale warehouse and retail pet shops more likely have acquired these viruses in the Netherlands or stopovers during delivery by aviation than locally. The risk of human-to-hamster reverse zoonosis by multiple SARS-CoV-2 variants leading to further adaptive spike mutations with subsequent transmission back to humans cannot be underestimated as an outbreak source of COVID-19. Testing imported pet animals susceptible to SARS-CoV-2 is warranted to prevent future outbreaks.

Fatal viral infection-associated encephalopathy in two Chinese boys: a genetically determined risk factor of thermolabile carnitine palmitoyltransferase II variants.

Influenza-associated encephalopathy (IAE) is a potentially fatal neurological complication of influenza infection usually in the presence of high and persistent fever. Thermolabile carnitine palmitoyltransferase II enzyme (CPT-II) predisposes IAE, so far only described in Japanese. As the genetic origins of Japanese and Chinese are alike, similar genetic risk factors in CPT-II are expected. We report the first two unrelated Chinese patients of thermolabile CPT-II variants that underlain the persistent high fever-triggered viral infection-associated encephalopathy, multi-organ failure and death. Elevated (C16:0+C18:1)/C2 acylcarnitines ratio and the CPT2 susceptibility variant allele [p.Phe352Cys; p.Val368Ile] were detected. The asymptomatic family members of one patient also had abnormal long-chain acylcarnitines. In our experience of biochemical genetics, the elevated (C16:0+C18:1)/C2 acylcarnitines ratio is unusual and specific for thermolabile CPT-II variants. Allele frequency of [p.Phe352Cys; p.Val368Ile] among Hong Kong Chinese was 0.104, similar to Japanese data, and [p.Phe352Cys] has not been reported in Caucasians. This may explain the Asian-specific phenomenon of thermolabile CPT-II-associated IAE. We successfully demonstrated the thermolabile CPT-II variants in patients with viral infection-associated encephalopathy in another Asian population outside Japanese. The condition is likely under-recognized. With our first cases, it is envisaged that more cases will be diagnosed in subsequent years. The exact pathogenic mechanism of how other factors interplay with thermolabile CPT-II variants and high fever leading to IAE, is yet to be elucidated. Fasting and decreased intake during illness may aggravate the disease. Further studies including high risk and neonatal screening are warranted to investigate its expressivity, penetrance and temperature-dependent behaviors in thermolabile CPT-II carriers. This may lead to discovery of the therapeutic golden window by aggressive antipyretics and L-carnitine administration in avoiding the high mortality and morbidity of IAE.

Saccharomyces cerevisiae septins: supramolecular organization of heterooligomers and the mechanism of filament assembly.

Mitotic yeast cells express five septins (Cdc3, Cdc10, Cdc11, Cdc12, and Shs1/Sep7). Only Shs1 is nonessential. The four essential septins form a complex containing two copies of each, but their arrangement was not known. Single-particle analysis by EM confirmed that the heterooligomer is octameric and revealed that the subunits are arrayed in a linear rod. Identity of each subunit was determined by examining complexes lacking a given septin, by antibody decoration, and by fusion to marker proteins (GFP or maltose binding protein). The rod has the order Cdc11-Cdc12-Cdc3-Cdc10-Cdc10-Cdc3-Cdc12-Cdc11 and, hence, lacks polarity. At low ionic strength, rods assemble end-to-end to form filaments but not when Cdc11 is absent or its N terminus is altered. Filaments invariably pair into long parallel "railroad tracks." Lateral association seems to be mediated by heterotetrameric coiled coils between the paired C-terminal extensions of Cdc3 and Cdc12 projecting orthogonally from each filament. Shs1 may be able to replace Cdc11 at the end of the rod. Our findings provide insights into the molecular mechanisms underlying the function and regulation of cellular septin structures.

Structural studies of full-length receptor tyrosine kinases and their implications for drug design.

Receptor tyrosine kinases (RTKs) are important drug targets for cancer and immunological disorders. Crystal structures of individual RTK domains have contributed greatly to the structure-based drug design of clinically used drugs. Low-resolution structures from electron microscopy are now available for the RTKs, EGFR, PDGFR, and Kit. However, there are still no high-resolution structures of full-length RTKs due to the technical challenges of working with these complex, membrane proteins. Here, we review what has been learned from structural studies of these three RTKs regarding their mechanisms of ligand binding, activation, oligomerization, and inhibition. We discuss the implications for drug design. More structural data on full-length RTKs may facilitate the discovery of druggable sites and drugs with improved specificity and effectiveness against resistant mutants.