Sequence-Structure Similarity: Do Sequentially Identical Peptide Fragments have Similar Three-Dimensional Structures?

The rapidly growing structure databases enhance the probability of finding identical sequences sharing structural similarity. Structure prediction methods are being used extensively to abridge the gap between known protein sequences and the solved structures which is essential to understand its specific biochemical and cellular functions. In this work, we plan to study the ambiguity between sequence-structure relationships and examine if sequentially identical peptide fragments adopt similar three-dimensional structures. Fragments of varying lengths (five to ten residues) were used to observe the behavior of sequence and its three-dimensional structures. The STAMP program was used to superpose the three-dimensional structures and the two parameters (Sequence Structure Similarity Score (Sc) and Root Mean Square Deviation value) were employed to classify them into three categories: similar, intermediate and dissimilar structures. Furthermore, the same approach was carried out on all the three-dimensional protein structures solved in the two organisms, Mycobacterium tuberculosis and Plasmodium falciparum to validate our results.

Recent Developments in the Chemistry and Biology of G-Quadruplexes with Reference to the DNA Groove Binders

DNA is the chemotherapeutic target for treating diseases of genetic origin. Besides well-known double-helical structures (A, B, Z, parallel stranded-DNA etc.), DNA is capable of forming several multi-stranded structures (triplex, tetraplex, i-motif etc.) which have unique biological significance. The G-rich 3'-ends of chromosomes, called telomeres, are synthesized by telomerase, a ribonucleoprotein, and over-expression of telomerase is associated with cancer. The activity of telomerase is suppressed if the G-rich region is folded into the four stranded structures, called G-quadruplexes (G4-DNAs) using small synthetic ligands. Thus design and synthesis of new G4-DNA ligands is an attractive strategy to combat cancer. G4-DNA forming sequences are also prevalent in other genomic regions of biological significance including promoter regions of several oncogenes. Effective gene regulation may be achieved by inducing a G4-DNA structure within the G-rich promoter sequences. To date, several G4-DNA stabilizing ligands are known. DNA groove binders interact with the duplex B-DNA through the grooves (major and minor groove) in a sequence-specific manner. Some of the groove binders are known to stabilize the G4-DNA. However, this is a relatively under explored field of research. In this review, we focus on the recent advances in the understanding of the G4-DNA structures, particularly made from the human telomeric DNA stretches. We summarize the results of various investigations of the interaction of various organic ligands with the G4-DNA while highlighting the importance of groove binder-G4-DNA interactions.

Averting biodiversity collapse in tropical forest protected areas

The rapid disruption of tropical forests probably imperils global biodiversity more than any other contemporary phenomenon(1-3). With deforestation advancing quickly, protected areas are increasingly becoming final refuges for threatened species and natural ecosystem processes. However, many protected areas in the tropics are themselves vulnerable to human encroachment and other environmental stresses(4-9). As pressures mount, it is vital to know whether existing reserves can sustain their biodiversity. A critical constraint in addressing this question has been that data describing a broad array of biodiversity groups have been unavailable for a sufficiently large and representative sample of reserves. Here we present a uniquely comprehensive data set on changes over the past 20 to 30 years in 31 functional groups of species and 21 potential drivers of environmental change, for 60 protected areas stratified across the world's major tropical regions. Our analysis reveals great variation in reserve `health': about half of all reserves have been effective or performed passably, but the rest are experiencing an erosion of biodiversity that is often alarmingly widespread taxonomically and functionally. Habitat disruption, hunting and forest-product exploitation were the strongest predictors of declining reserve health. Crucially, environmental changes immediately outside reserves seemed nearly as important as those inside in determining their ecological fate, with changes inside reserves strongly mirroring those occurring around them. These findings suggest that tropical protected areas are often intimately linked ecologically to their surrounding habitats, and that a failure to stem broad-scale loss and degradation of such habitats could sharply increase the likelihood of serious biodiversity declines.

Novel De-Acylative Ring Opening of 3-Acetyl and 3-Bromo Acetyl Coumarins

Reaction of 3-acetyl and 3-bromoacetyl coumarins with hydrazine hydrate has resulted in the ring opening of the coumarin moiety. The reaction was attempted with a view to obtain some new pyridazinones and pyrazolones. The reaction did not proceed via the expected pathway instead led to the formation of salicyl azines, the structure of which has been confirmed by single crystal X-ray studies.

Heat Shock Protein 90 Inhibitors as Broad Spectrum Anti-Infectives

Combating stress is one of the prime requirements for any organism. For parasitic microbes, stress levels are highest during the growth inside the host. Their survival depends on their ability to acclimatize and adapt to new environmental conditions. Robust cellular machinery for stress response is, therefore, both critical and essential especially for pathogenic microorganisms. Microbes have cleverly exploited stress proteins as virulence factors for pathogenesis in their hosts. Owing to its ability to sense and respond to the stress conditions, Heat shock protein 90 (Hsp90) is one of the key stress proteins utilized by parasitic microbes. There are growing evidences for the critical role played by Hsp90 in the growth of pathogenic organisms like Candida, Giardia, Plasmodium, Trypanosoma, and others. This review, therefore, explores potential of exploiting Hsp90 as a target for the treatment of infectious diseases. This molecular chaperone has already gained attention as an effective anti-cancer drug target. As a result, a lot of research has been done at laboratory, preclinical and clinical levels for several Hsp90 inhibitors as potential anti-cancer drugs. In addition, lot of data pertaining to toxicity studies, pharmacokinetics and pharmacodynamics studies, dosage regime, drug related toxicities, dose limiting toxicities as well as adverse drug reactions are available for Hsp90 inhibitors. Therefore, repurposing/repositioning strategies are also being explored for these compounds which have gone through advanced stage clinical trials. This review presents a comprehensive summary of current status of development of Hsp90 as a drug target and its inhibitors as candidate anti-infectives. A particular emphasis is laid on the possibility of repositioning strategies coupled with pharmaceutical solutions required for fulfilling needs for ever growing pharmaceutical infectious disease market.

Surfactant free, non-aqueous method, for the deposition of ZnO nanoparticle thin films on Si(100) substrate with tunable ultraviolet (UV) emission

We report, strong ultraviolet (UV) emission from ZnO nanoparticle thin film obtained by a green synthesis, where the film is formed by the microwave irradiation of the alcohol solution of the precursor. The deposition is carried out in non-aqueous medium without the use of any surfactant, and the film formation is quick (5 min). The film is uniform comprising of mono-disperse nanoparticles having a narrow size distribution (15-22 nm), and that cover over an entire area (625 mm(2)) of the substrate. The growth rate is comparatively high (30-70 nm/min). It is possible to tune the morphology of the films and the UV emission by varying the process parameters. The growth mechanism is discussed precisely and schematic of the growth process is provided.

Process Development for Functionalization of Cotton with Silver Nanoparticles Synthesized by Bio-based Approaches

Cotton is a widely used raw material for textiles but drawbacks regarding their poor mechanical properties often limit their applications as functional materials. The present investigation involved process development for one step coating of cotton with silver nanoparticles (SNP) synthesized using Azadirachta indica and Citrus limon extract to develop functional textiles. Addition of starch to functional textiles led to efficient binding of nanoparticles to fabric and led to drastic decrease in release of silver from fabricated textiles after ten washing cycles enhancing their environment friendliness. Differential scanning calorimetry, scanning electron microscopy, FT-IR analysis and mechanical studies demonstrated efficient binding of nanoparticles to fabric through bio-based processes. The functionalized textiles developed by the bio-based methods showed significant antibacterial activity against E. coli and S. aureus (with 99% microbial reduction). Present work offers a simple procedure for coating SNP using bio-based approaches with promising applications in specialized functions.

The effect of cell size and channel density on neuronal information encoding and energy efficiency

Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na+ and K+ channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.

Renewable Energy via Photocatalysis

The generation of renewable energy through photocatalysis is an attractive option to utilize the abundantly available solar radiation for a sustainable future. Photocatalysis refers to charge-carrier, i.e. electron and hole, mediated reactions occurring on a semiconductor surface in presence of ultraviolet or visible light radiation. Photocatalysis is a well established advanced oxidation technique for the decontamination of toxic organic pollutants to CO2 and H2O. However, the generation of energy in the form of hydrogen, hydrocarbon fuels and electricity via photocatalysis is an upcoming field with great many technical challenges towards practical implementation. This review will describe the fundamental reaction mechanism of (i) photocatalytic water splitting, (ii) photocatalytic H-2 generation in presence of different sacrificial agents, (iii) H-2 and electricity generation in a photofuel cell, (iv) photocatalytic reduction of CO2 to hydrocarbons and useful chemicals, and (v) photocatalytic water-gas shift reaction. A historic and recent perspective of the above conversion techniques, especially with regard to the development of TiO2-based and non-TiO2 materials is provided. The activity of different materials for the above reactions based on quantifiers like reaction rate, quantum yield and incident-photon-to-current efficiency is compared, and key design considerations of the ``best'' photocatalyst or photoelectrode is outlined. An overall assessment of the research area indicates that the presently achieved quantum efficiencies for the above reactions are rather moderate in the visible region, and the goal is to develop a catalyst that absorbs visible radiation, provides good charge-carrier separation, and exhibits high stability for long periods of usage.

Balanced Excitatory and Inhibitory Synaptic Currents Promote Efficient Coding and Metabolic Efficiency

A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.

Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a `footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by similar to 50% in generator potentials, to similar to 3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

Modifications in Trypsin Digestion Protocol for Increasing the Efficiency and Coverage

Standard trypsin digestion protocol of proteins followed by MALDI-MS analysis has been realized as an important tool for the identification and characterization of proteins. In this article, we proposed the elimination of the step of `staining/de-staining of gel pieces' in in-gel digestion protocol in order to improve the efficiency of trypsin digestion. Coomassie dye is known to interfere with digestion of proteins by trypsin and the procedure of staining-de-staining could result in loss of photoaffinity probe, post translational modifications and catalytic activities of enzymes. Further, we studied parameters like hydrophobicity and isoelectric point, and attempted to quantitatively relate it to the efficiency of trypsin digestion. We suggest that properties of proteins should be considered and trypsin digestion protocol should be appropriately modified as per sequence and other information.

An estimate of the number of tropical tree species

The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between similar to 40,000 and similar to 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of similar to 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of similar to 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.

Protein Structure and Function: Looking through the Network of Side-Chain Interactions

Network theory has become an excellent method of choice through which biological data are smoothly integrated to gain insights into complex biological problems. Understanding protein structure, folding, and function has been an important problem, which is being extensively investigated by the network approach. Since the sequence uniquely determines the structure, this review focuses on the networks of non-covalently connected amino acid side chains in proteins. Questions in structural biology are addressed within the framework of such a formalism. While general applications are mentioned in this review, challenging problems which have demanded the attention of scientific community for a long time, such as allostery and protein folding, are considered in greater detail. Our aim has been to explore these important problems through the eyes of networks. Various methods of constructing protein structure networks (PSN) are consolidated. They include the methods based on geometry, edges weighted by different schemes, and also bipartite network of protein-nucleic acid complexes. A number of network metrics that elegantly capture the general features as well as specific features related to phenomena, such as allostery and protein model validation, are described. Additionally, an integration of network theory with ensembles of equilibrium structures of a single protein or that of a large number of structures from the data bank has been presented to perceive complex phenomena from network perspective. Finally, we discuss briefly the capabilities, limitations, and the scope for further explorations of protein structure networks.