Encoding and transducing the synaptic or extrasynaptic origin of NMDA receptor signals to the nucleus.

The activation of N-methyl-D-aspartate-receptors (NMDARs) in synapses provides plasticity and cell survival signals, whereas NMDARs residing in the neuronal membrane outside synapses trigger neurodegeneration. At present, it is unclear how these opposing signals are transduced to and discriminated by the nucleus. In this study, we demonstrate that Jacob is a protein messenger that encodes the origin of synaptic versus extrasynaptic NMDAR signals and delivers them to the nucleus. Exclusively synaptic, but not extrasynaptic, NMDAR activation induces phosphorylation of Jacob at serine-180 by ERK1/2. Long-distance trafficking of Jacob from synaptic, but not extrasynaptic, sites depends on ERK activity, and association with fragments of the intermediate filament α-internexin hinders dephosphorylation of the Jacob/ERK complex during nuclear transit. In the nucleus, the phosphorylation state of Jacob determines whether it induces cell death or promotes cell survival and enhances synaptic plasticity.

Jacob-induced transcriptional inactivation of CREB promotes Aß-induced synapse loss in Alzheimer's disease.

Synaptic dysfunction caused by soluble ß-amyloid peptide (Aß) is a hallmark of early-stage Alzheimer's disease (AD), and is tightly linked to cognitive decline. By yet unknown mechanisms, Aß suppresses the transcriptional activity of cAMP-responsive element-binding protein (CREB), a master regulator of cell survival and plasticity-related gene expression. Here, we report that Aß elicits nucleocytoplasmic trafficking of Jacob, a protein that connects a NMDA-receptor-derived signalosome to CREB, in AD patient brains and mouse hippocampal neurons. Aß-regulated trafficking of Jacob induces transcriptional inactivation of CREB leading to impairment and loss of synapses in mouse models of AD. The small chemical compound Nitarsone selectively hinders the assembly of a Jacob/LIM-only 4 (LMO4)/ Protein phosphatase 1 (PP1) signalosome and thereby restores CREB transcriptional activity. Nitarsone prevents impairment of synaptic plasticity as well as cognitive decline in mouse models of AD. Collectively, the data suggest targeting Jacob protein-induced CREB shutoff as a therapeutic avenue against early synaptic dysfunction in AD.

RhoG facilitates a conformational transition in the guanine nucleotide exchange factor complex DOCK5/ELMO1 to an open state.

The dedicator of cytokinesis (DOCK)/engulfment and cell motility (ELMO) complex serves as a guanine nucleotide exchange factor (GEF) for the GTPase Rac. RhoG, another GTPase, activates the ELMO-DOCK-Rac pathway during engulfment and migration. Recent cryo-EM structures of the DOCK2/ELMO1 and DOCK2/ELMO1/Rac1 complexes have identified closed and open conformations that are key to understanding the autoinhibition mechanism. Nevertheless, the structural details of RhoG-mediated activation of the DOCK/ELMO complex remain elusive. Herein, we present cryo-EM structures of DOCK5/ELMO1 alone and in complex with RhoG and Rac1. The DOCK5/ELMO1 structure exhibits a closed conformation similar to that of DOCK2/ELMO1, suggesting a shared regulatory mechanism of the autoinhibitory state across DOCK-A/B subfamilies (DOCK1-5). Conversely, the RhoG/DOCK5/ELMO1/Rac1 complex adopts an open conformation that differs from that of the DOCK2/ELMO1/Rac1 complex, with RhoG binding to both ELMO1 and DOCK5. The alignment of the DOCK5 phosphatidylinositol (3,4,5)-trisphosphate binding site with the RhoG C-terminal lipidation site suggests simultaneous binding of RhoG and DOCK5/ELMO1 to the plasma membrane. Structural comparison of the apo and RhoG-bound states revealed that RhoG facilitates a closed-to-open state conformational change of DOCK5/ELMO1. Biochemical and surface plasmon resonance (SPR) assays confirm that RhoG enhances the Rac GEF activity of DOCK5/ELMO1 and increases its binding affinity for Rac1. Further analysis of structural variability underscored the conformational flexibility of the DOCK5/ELMO1/Rac1 complex core, potentially facilitating the proximity of the DOCK5 GEF domain to the plasma membrane. These findings elucidate the structural mechanism underlying the RhoG-induced allosteric activation and membrane binding of the DOCK/ELMO complex.

A highly divergent enteric calicivirus in a bovine calf in India.

A highly divergent bovine calicivirus was identified in an Indian calf with enteritis. The whole genome of this virus was sequenced, revealing distinct amino acid motifs in the polyprotein encoded by open reading frame 1 (ORF1) that are unique to caliciviruses. Phylogenetic analysis showed that it was related to members of the genus Nebovirus of the family Caliciviridae. Although it showed only 33.7-34.2% sequence identity in the VP1 protein to the nebovirus prototype strains, it showed 90.6% identity in VP1 to Kirklareli virus, a nebovirus detected in calves with enteritis in Turkey in 2012. An in-house-designed and optimized reverse transcription polymerase chain reaction (RT-PCR) assay was used to screen 120 archived bovine diarrhoeic fecal samples, 40 each from the Indian states of Uttar Pradesh, Haryana, and Himachal Pradesh, revealing frequent circulation of these divergent caliciviruses in the bovine population, with an overall positivity rate of 64.17% (77/120). This underscores the importance of conducting a comprehensive investigation of the prevalence of these divergent caliciviruses and assessing their associations with other pathogens responsible for enteritis in India.

Mice deficient in synaptic protease neurotrypsin show impaired spaced long-term potentiation and blunted learning-induced modulation of dendritic spines.

Neurotrypsin (NT) is a neuronal trypsin-like serine protease whose mutations cause severe mental retardation in humans. NT is activated in vitro by Hebbian-like conjunction of pre- and postsynaptic activities, which promotes the formation of dendritic filopodia via proteolytic cleavage of the proteoglycan agrin. Here, we investigated the functional importance of this mechanism for synaptic plasticity, learning, and extinction of memory. We report that juvenile neurotrypsin-deficient (NT-/-) mice exhibit impaired long-term potentiation induced by a spaced stimulation protocol designed to probe the generation of new filopodia and their conversion into functional synapses. Behaviorally, juvenile NT-/- mice show impaired contextual fear memory and have a sociability deficit. The latter persists in aged NT-/- mice, which, unlike juvenile mice, show normal recall but impaired extinction of contextual fear memories. Structurally, juvenile mutants exhibit reduced spine density in the CA1 region, fewer thin spines, and no modulation in the density of dendritic spines following fear conditioning and extinction in contrast to wild-type littermates. The head width of thin spines is reduced in both juvenile and aged NT-/- mice. In vivo delivery of adeno-associated virus expressing an NT-generated fragment of agrin, agrin-22, but not a shorter agrin-15, elevates the spine density in NT-/- mice. Moreover, agrin-22 co-aggregates with pre- and postsynaptic markers and increases the density and size of presynaptic boutons and presynaptic puncta, corroborating the view that agrin-22 supports the synaptic growth.

A novel consensus-based computational pipeline for screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including Omicron variant.

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to evolve carrying flexible amino acid substitutions in the spike protein's receptor binding domain (RBD). These substitutions modify the binding of the SARS-CoV-2 to human angiotensin-converting enzyme 2 (hACE2) receptor and have been implicated in altered host fitness, transmissibility, and efficacy against antibody therapeutics and vaccines. Reliably predicting the binding strength of SARS-CoV-2 variants RBD to hACE2 receptor and neutralizing antibodies (NAbs) can help assessing their fitness, and rapid deployment of effective antibody therapeutics, respectively. Here, we introduced a two-step computational framework with 3-fold validation that first identified dissociation constant as a reliable predictor of binding affinity in hetero- dimeric and trimeric protein complexes. The second step implements dissociation constant as descriptor of the binding strengths of SARS-CoV-2 variants RBD to hACE2 and NAbs. Then, we examined several variants of concerns (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron and demonstrated that these VOCs RBD bind to the hACE2 with enhanced affinity. Furthermore, the binding affinity of Omicron variant's RBD was reduced with majority of the RBD-directed NAbs, which is highly consistent with the experimental neutralization data. By studying the atomic contacts between RBD and NAbs, we revealed the molecular footprints of four NAbs (GH-12, P2B-1A1, Asarnow_3D11, and C118)-that may likely neutralize the recently emerged Omicron variant-facilitating enhanced binding affinity. Finally, our findings suggest a computational pathway that could aid researchers identify a range of current NAbs that may be effective against emerging SARS-CoV-2 variants.

Insights into the evolutionary forces that shape the codon usage in the viral genome segments encoding intrinsically disordered protein regions.

Intrinsically disordered regions/proteins (IDRs) are abundant across all the domains of life, where they perform important regulatory roles and supplement the biological functions of structured proteins/regions (SRs). Despite the multifunctionality features of IDRs, several interrogations on the evolution of viral genomic regions encoding IDRs in diverse viral proteins remain unreciprocated. To fill this gap, we benchmarked the findings of two most widely used and reliable intrinsic disorder prediction algorithms (IUPred2A and ESpritz) to a dataset of 6108 reference viral proteomes to unravel the multifaceted evolutionary forces that shape the codon usage in the viral genomic regions encoding for IDRs and SRs. We found persuasive evidence that the natural selection predominantly governs the evolution of codon usage in regions encoding IDRs by most of the viruses. In addition, we confirm not only that codon usage in regions encoding IDRs is less optimized for the protein synthesis machinery (transfer RNAs pool) of their host than for those encoding SRs, but also that the selective constraints imposed by codon bias sustain this reduced optimization in IDRs. Our analysis also establishes that IDRs in viruses are likely to tolerate more translational errors than SRs. All these findings hold true, irrespective of the disorder prediction algorithms used to classify IDRs. In conclusion, our study offers a novel perspective on the evolution of viral IDRs and the evolutionary adaptability to multiple taxonomically divergent hosts.

Evolutionary and codon usage preference insights into spike glycoprotein of SARS-CoV-2.

Interaction of SARS-CoV-2 spike glycoprotein with the ACE2 cell receptor is very crucial for virus attachment to human cells. Selected mutations in SARS-CoV-2 S-protein are reported to strengthen its binding affinity to mammalian ACE2. The N501T mutation in SARS-CoV-2-CTD furnishes better support to hotspot 353 in comparison with SARS-CoV and shows higher affinity for receptor binding. Recombination analysis exhibited higher recombination events in SARS-CoV-2 strains, irrespective of their geographical origin or hosts. Investigation further supports a common origin among SARS-CoV-2 and its predecessors, SARS-CoV and bat-SARS-like-CoV. The recombination events suggest a constant exchange of genetic material among the co-infecting viruses in possible reservoirs and human hosts before SARS-CoV-2 emerged. Furthermore, a comprehensive analysis of codon usage bias (CUB) in SARS-CoV-2 revealed significant CUB among the S-genes of different beta-coronaviruses governed majorly by natural selection and mutation pressure. Various indices of codon usage of S-genes helped in quantifying its adaptability in other animal hosts. These findings might help in identifying potential experimental animal models for investigating pathogenicity for drugs and vaccine development experiments.

ProFitFun: a protein tertiary structure fitness function for quantifying the accuracies of model structures.

MOTIVATION: An accurate estimation of the quality of protein model structures typifies as a cornerstone in protein structure prediction regimes. Despite the recent groundbreaking success in the field of protein structure prediction, there are certain prospects for the improvement in model quality estimation at multiple stages of protein structure prediction and thus, to further push the prediction accuracy. Here, a novel approach, named ProFitFun, for assessing the quality of protein models is proposed by harnessing the sequence and structural features of experimental protein structures in terms of the preferences of backbone dihedral angles and relative surface accessibility of their amino acid residues at the tripeptide level. The proposed approach leverages upon the backbone dihedral angle and surface accessibility preferences of the residues by accounting for its N-terminal and C-terminal neighbors in the protein structure. These preferences are used to evaluate protein structures through a machine learning approach and tested on an extensive dataset of diverse proteins. RESULTS: The approach was extensively validated on a large test dataset (n = 25 005) of protein structures, comprising 23 661 models of 82 non-homologous proteins and 1344 non-homologous experimental structures. In addition, an external dataset of 40 000 models of 200 non-homologous proteins was also used for the validation of the proposed method. Both datasets were further used for benchmarking the proposed method with four different state-of-the-art methods for protein structure quality assessment. In the benchmarking, the proposed method outperformed some state-of-the-art methods in terms of Spearman's and Pearson's correlation coefficients, average GDT-TS loss, sum of z-scores and average absolute difference of predictions over corresponding observed values. The high accuracy of the proposed approach promises a potential use of the sequence and structural features in computational protein design. AVAILABILITY AND IMPLEMENTATION: http://github.com/KYZ-LSB/ProTerS-FitFun. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future.

The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent innovations especially using artificial intelligence (AI) and machine learning. AI-based model systems could improve pattern recognition of disease spread in populations and predictions of outbreaks in different geographical locations. A variable and a minimal amount of data are available for the signs and symptoms of Covid-19, allowing a composite of maximum likelihood algorithms to be employed to enhance the accuracy of disease diagnosis and to identify potential drugs. AI-based forecasting and predictions are expected to complement traditional approaches by helping public health officials to select better response and preparedness measures against Covid-19 cases. AI-based approaches have helped address the key issues but a significant impact on the global healthcare industry is yet to be achieved. The capability of AI to address the challenges may make it a key player in the operation of healthcare systems in future. Here, we present an overview of the prospective applications of the AI model systems in healthcare settings during the ongoing Covid-19 pandemic.

Antiferromagnetically coupled double perovskite as an efficient and robust catalyst for visible light driven water splitting at neutral pH.

Green and sustainable energy production through renewable sources is an enormously exciting field of research. Herein, we report an A-site lanthanum doped oxygen excess ruthenate (predominantly Ru5+-ions) double perovskite system, CaLaScRuO6+δ (CLSR), as an excellent photocatalyst for water splitting. The well characterized polycrystalline compound shows canted antiferromagnetic (AFM) behavior due to the existence of disordered Ru-ions at the B-site. Based on density functional theory + U (Hubbard U) calculations, we have estimated various magnetic exchange interactions and found that the ground state is antiferromagnetic in nature which is in perfect agreement with our experimental results. Detailed analysis of the electronic structure further reveals that the present system belongs to the family of charge transfer semiconductors with an energy gap of ∼0.45 eV. Finally, the material is found to proficiently work for the oxygen evolution reaction (OER) via visible-light driven water splitting at neutral pH in an ecofriendly manner.

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: Implications for future surveillance programmes.

Understanding the origin of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unresolved issue for scientific communities all over the world. Understanding the mechanism of virus entry to the host cells is crucial to deciphering the susceptibility profiles of animal species to SARS-CoV-2. The interaction of SARS-CoV-2 ligands (receptor-binding domain on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the SARS-CoV-2 spike protein can bind to a wide range of vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Furthermore, the current study facilitated the identification of genetic determinants that may differentiate susceptible from resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified bat species' susceptibility to SARS-CoV-2. The current study's findings highlight the importance of intensive surveillance programmes aimed at identifying susceptible hosts, especially those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

Comprehensive Intrinsic Disorder Analysis of 6108 Viral Proteomes: From the Extent of Intrinsic Disorder Penetrance to Functional Annotation of Disordered Viral Proteins.

Much of our understanding of proteins and proteomes comes from the traditional protein structure-function paradigm. However, in the last 2 decades, both computational and experimental studies have provided evidence that a large fraction of functional proteomes across different domains of life consists of intrinsically disordered proteins, thus triggering a quest to unravel and decipher protein intrinsic disorder. Unlike structured/ordered proteins, intrinsically disordered proteins/regions (IDPs/IDRs) do not possess a well-defined structure under physiological conditions and exist as highly dynamic conformational ensembles. In spite of this peculiarity, these proteins have crucial roles in cell signaling and regulation. To date, studies on the abundance and function of IDPs/IDRs in viruses are rather limited. To fill this gap, we carried out an extensive and thorough bioinformatics analysis of 283 000 proteins from 6108 reference viral proteomes. We analyzed protein intrinsic disorder from multiple perspectives, such as abundance of IDPs/IDRs across diverse virus types, their functional annotations, and subcellular localization in taxonomically divergent hosts. We show that the content of IDPs/IDRs in viral proteomes varies broadly as a function of virus genome types and taxonomically divergent hosts. We have combined the two most commonly used and accurate IDP predictors' results with charge-hydropathy (CH) versus cumulative distribution function (CDF) plots to categorize the viral proteins according to their IDR content and physicochemical properties. Mapping of gene ontology on the disorder content of viral proteins reveals that IDPs are primarily involved in key virus-host interactions and host antiviral immune response downregulation, which are reinforced by the post-translational modifications tied to disorder-enriched viral proteins. The present study offers detailed insights into the prevalence of the intrinsic disorder in viral proteomes and provides appealing targets for the design of novel therapeutics.

Attenuation of the extracellular matrix restores microglial activity during the early stage of amyloidosis.

In the advanced stages of Alzheimer's disease (AD), microglia are transformed to an activated phenotype with thickened and retracted processes, migrate to the site of amyloid-beta (Aß) plaques, and proliferate. In the early stages of AD, it is still poorly understood whether the microglial function is altered and which factors may regulate these changes. Here, we focused on studying microglia in the retrosplenial cortex (RSC) in 3- to 4-month-old 5xFAD mice as a transgenic mouse model of AD. At this age, there are neither Aß plaques, nor activation of microglia, nor dysregulation in the expression of genes encoding major extracellular matrix (ECM) molecules or extracellular proteases in the RSC. Still, histochemical evaluation of the fine structure of neural ECM revealed increased levels of Wisteria floribunda agglutinin labeling in holes of perineuronal nets and changes in the perimeter of ECM barriers around the holes in 5xFAD mice. Two-photon vital microscopy demonstrated normal morphology and resting motility of microglia but strongly diminished number of microglial cells that migrated to the photolesion site in 5xFAD mice. Enzymatic digestion of ECM by chondroitinase ABC (ChABC) ameliorated this defect. Accordingly, the characterization of cell surface markers by flow cytometry demonstrated altered expression of microglial CD45. Moreover, ChABC treatment reduced the invasion of myeloid-derived mononuclear cells into the RSC of 5xFAD mice. Hence, the migration of both microglia and myeloid cells is altered during the early stages of amyloidosis and can be restored at least partially by the attenuation of the ECM.

Fine structure analysis of perineuronal nets in the ketamine model of schizophrenia.

Perineuronal nets (PNNs) represent a highly condensed specialized form of brain extracellular matrix (ECM) enwrapping mostly parvalbumin-positive interneurons in the brain in a mesh-like fashion. PNNs not only regulate the onset and completion of the critical period during postnatal brain development, control cell excitability, and synaptic transmission but are also implicated in several brain disorders including schizophrenia. Holes in the perineuronal nets, harboring the synaptic contacts, along with hole-surrounding ECM barrier can be viewed as PNN compartmentalization units that might determine the properties of synapses and heterosynaptic communication. In this study, we developed a novel open-source script for Fiji (ImageJ) to semi-automatically quantify structural alterations of PNNs such as the number of PNN units, area, mean intensity of PNN marker expression in 2D and 3D, shape parameters of PNN units in the ketamine-treated Sprague-Dawley rat model of schizophrenia using high-resolution confocal microscopic images. We discovered that the mean intensity of ECM within PNN units is inversely correlated with the area and the perimeter of the PNN holes. The intensity, size, and shape of PNN units proved to be three major principal factors to describe their variability. Ketamine-treated rats had more numerous but smaller and less circular PNN units than control rats. These parameters allowed to correctly classify individual PNNs as derived from control or ketamine-treated groups with ≈85% reliability. Thus, the proposed multidimensional analysis of PNN units provided a robust and comprehensive morphometric fingerprinting of fine ECM structure abnormalities in the experimental model of schizophrenia.

A protein sequence fitness function for identifying natural and nonnatural proteins.

The infinitesimally small sequence space naturally scouted in the millions of years of evolution suggests that the natural proteins are constrained by some functional prerequisites and should differ from randomly generated sequences. We have developed a protein sequence fitness scoring function that implements sequence and corresponding secondary structural information at tripeptide levels to differentiate natural and nonnatural proteins. The proposed fitness function is extensively validated on a dataset of about 210 000 natural and nonnatural protein sequences and benchmarked with existing methods for differentiating natural and nonnatural proteins. The high sensitivity, specificity, and percentage accuracy (0.81%, 0.95%, and 91% respectively) of the fitness function demonstrates its potential application for sampling the protein sequences with higher probability of mimicking natural proteins. Moreover, the four major classes of proteins (α proteins, ß proteins, α/ß proteins, and α + ß proteins) are separately analyzed and ß proteins are found to score slightly lower as compared to other classes. Further, an analysis of about 250 designed proteins (adopted from previously reported cases) helped to define the boundaries for sampling the ideal protein sequences. The protein sequence characterization aided by the proposed fitness function could facilitate the exploration of new perspectives in the design of novel functional proteins.

LGI1 downregulation increases neuronal circuit excitability.

OBJECTIVE: Leucine-rich glioma-inactivated 1 (LGI1) is a secreted transsynaptic protein that interacts presynaptically with Kv1.1 potassium channels and a disintegrin and metalloprotease (ADAM) protein 23, and postsynaptically influences α-amino-3-hydroxy-5-methylisoxazole-4-propionate receptors through a direct link with the ADAM22 cell adhesion protein. Haploinsufficiency of LGI1 or autoantibodies directed against LGI1 are associated with human epilepsy, generating the hypothesis that a subacute reduction of LGI1 is sufficient to increase network excitability. METHODS: We tested this hypothesis in ex vivo hippocampal slices and in neuronal cultures, by subacutely reducing LGI1 expression with shRNA. RESULTS: Injection of shRNA-LGI1 in the hippocampus increased dentate granule cell excitability and low-frequency facilitation of mossy fibers to CA3 pyramidal cell neurotransmission. Application of the Kv1 family blocker, α-dendrotoxin, occluded this effect, implicating the involvement of Kv1.1. This subacute reduction of LGI1 was also sufficient to increase neuronal network activity in neuronal primary culture. SIGNIFICANCE: These results indicate that a subacute reduction in LGI1 potentiates neuronal excitability and short-term synaptic plasticity, and increases neuronal network excitability, opening new avenues for the treatment of limbic encephalitis and temporal lobe epilepsies.

Fluorescent nanoprobes for the sensing of gasotransmitters hydrogen sulfide (H2S), nitric oxide (NO) and carbon monoxide (CO).

Fluorescent nanomaterials as sensing probes have experienced immense growth in recent years due to the intrinsic optical and physicochemical properties, high sensitivity, specificity, targeting ability, and suitability for medicinal applications. The fluorescent detection of gaseous signaling molecules, such as Hydrogen sulfide (H2S), nitric oxide (NO) and carbon monoxide (CO) are very important due to their potential therapeutic application. This review intends to provide the recent progress in the detection of H2S, CO and NO via fluorescent based nano probes. These probes work based on different mechanisms such as fluorescence enhancement and quenching, also defined as "turn-on" and "turn-off" responses respectively. It could be achieved through PET, FRET or ratiometric methods. In this article, we have discussed about a variety of fluorescent nanoprobes of QDS, CDs, AuNPs and UCNPS, working on the fluorescent sensing mechanisms and applicable for the detection of H2S, CO and NO in biological and environmental samples. Methods used for the detection, structural features of nanomaterials, type of fluorescence response observed, fluorescence sensing mechanism and their sensitivity are highlighted.

Allosteric Regulation in Carbon Monoxide (CO) Release: Anion Responsive CO-Releasing Molecule (CORM) Derived from (Terpyridine)phenol Manganese Tricarbonyl Complex with Colorimetric and Fluorescence Monitoring.

A new CO-releasing terpyridine based manganese(I) tricarbonyl complex, [MnBr(CO)3(terpy-C6H4OH)] (1·Mn-OH) functioning via light has been reported. For the first time, we have demonstrated the allosteric regulation concept to control the CO-releasing properties of a CO-releasing molecule (CORM). Fluoride ion is reported to function as an allosteric activator to control the rate of CO release in the CORM. Complex 1·Mn-OH represents an interesting new class of CO-releasing system that releases CO upon irradiation with blue light (410 nm) over a period of 40 min with the half-time of 9.8 min. Fluoride ion selectively binds to the phenol moiety of the complex through hydrogen bonding and deprotonates to phenolate with a color change. Interestingly in the presence of fluoride ion, the rate of CO release is fast with the half-time of less than a minute. The rate of CO release is allosterically regulated by fluoride anion and can be monitored through a color change, fluorescence, and absorption based spectral changes along with IR studies and myoglobin assay.

Where Informatics Lags Chemistry Leads.

The fact that amino acid sequences dictate the tertiary structures of proteins has been known for more than five decades. While the molecular pathways to tertiary structure are still being worked out, with the axiom that similar sequences adopt similar structures, computational methods are being developed continually in parallel, utilizing the Protein Data Bank structural repository and homologue detection strategies to predict structures of sequences of interest. The success of this approach is limited by the ability to unravel the hidden similarities among amino acid sequences. We consider here the 20 amino acids as a complete set of chemical templates in the physicochemical space of proteins and propose a new structural and chemical classification of amino acids. An integration of this perspective into the conventional evolutionary methods of similarity detection leads to an unprecedented increase in the accuracy in homologue detection, resulting in improved protein structure prediction. The performance is validated on a large data set of 11716 unique proteins, and the results are benchmarked against conventional methods. The availability of good quality protein structures helps in structure-based drug design endeavors and in establishing protein structure-function correlations.