Identification of new candidate drugs for lung cancer using chemical–chemical interactions,chemical–protein interactions and a K-means clustering algorithm

Lung cancer, characterized by uncontrolled cell growth in the lung tissue, is the leading cause of global cancer deaths. Until now, effective treatment of this disease is limited. Many synthetic compounds have emerged with the advancement of combinatorial chemistry. Identification of effective lung cancer candidate drug compounds among them is a great challenge. Thus, it is necessary to build effective computational methods that can assist us in selecting for potential lung cancer drug compounds. In this study, a computational method was proposed to tackle this problem. The chemical–chemical interactions and chemical–protein interactions were utilized to select candidate drug compounds that have close associations with approved lung cancer drugs and lung cancer-related genes. A permutation test and K-means clustering algorithm were employed to exclude candidate drugs with low possibilities to treat lung cancer. The final analysis suggests that the remaining drug compounds have potential anti-lung cancer activities and most of them have structural dissimilarity with approved drugs for lung cancer.     

Preliminary screening of Houttuynia cordata for biological potential and chemical components using TLC and GC–MS analysis

Journal of Plant Biochemistry and Biotechnology - The objective of the study is to ascertain the biological potential and to identify the bioactive compounds of the four crude extract hexane,...     

Pollution control in pulp and paper industrial effluents using integrated chemical–biological treatment sequences

The main objective of the present study was to improve the quality of pulp and paper industrial wastewater of two local mills RAKTA and El-Ahlia, Alexandria, Egypt, and to bring their pollutant contents to safe discharge levels. Quality improvement was carried out using integrated chemical and biological treatment approaches after their optimization. Chemical treatment (alum, lime, and ferric chloride) was followed by oxidation using hydrogen peroxide and finally biological treatment using activated sludge (90 min for RAKTA and 60 min for El-Ahlia effluents). Chemical coagulation produced low-quality effluents, while pH adjustment during coagulation treatment did not enhance the quality of the effluents. Maximum removal of the tested pollutants was achieved using the integrated treatment and the pollutants recorded residual concentrations (RCs) of 34.67, 17.33, 0.13, and 0.43 mg/l and 15.0, 11.0, 0.0, and 0.13 mg/l for chemical oxygen demand (COD), biochemical oxygen demand (BOD₅), tannin and lignin, and silica in RAKTA and El-Ahlia effluents, respectively, all of which were below their maximum permissible limits (MPLs) for the safe discharge into water courses. Specific oxygen uptake rate (SOUR) and sludge volume index (SVI) values reflect good conditions and healthy activated sludge. Based on the previous results, optimized conditions were applied as bench scale on the raw effluents of RAKTA and El-Ahlia via the batch chemical and the biological treatment sequences proposed. For RAKTA effluents, the sequence was as follows: (1) coagulation with 375 mg/l FeCl₃, (2) oxidation with 50 mg/l hydrogen peroxide, and (3) biological treatment using activated sludge with 2,000 mg/l initial concentration and 90 min hydraulic retention time (HRT), while for El-Ahlia raw effluents, the sequence was (1) coagulation with 250 mg/l FeCl₃, (2) oxidation with 45 mg/l hydrogen peroxide, and (3) biological treatment using activated sludge with 2,000 mg/l initial concentration and 60 min HRT. In conclusion, results confirmed that the application of the proposed sequential treatments removed almost all COD, BOD₅, high molecular weight compounds, and silica from RAKTA and El-Ahlia influents and produced high-quality effluents, thus achieving the main objective of this study.     

Application of physical–chemical and biological–chemical methods for heavy metals removal from acid mine drainage

Acid mine drainage (AMD) represents a serious environmental problem related to sulfide minerals and coal mining. High content of toxic metals and high acidity in AMD adversely affects surface water, groundwater and soil. The abandoned mine of the Smolník deposit in Slovakia is a typical example in this respect. The quality of AMD needs to be monitored and suitable treatment methods need to be developed.The aim of this paper was to demonstrate the technical feasibility of heavy metals removal from AMD using physical–chemical and biological–chemical methods. The base of the physical–chemical method was electrowinning. The principle of the biological–chemical method was the selective sequential precipitation (SSP) of metals with the application of hydrogen sulfide produced by sulfate-reducing bacteria and sodium hydroxide solution. Both the electrowinning and SSP processes decrease the content of heavy metals in AMD. The pre-treatment of AMD by chemical iron–aluminum precipitation (in the case of electrowinning tests) and chemical iron precipitation (in the case of SSP tests) improved the selectivity of the processes. A further aim of the work was the improvement of the SSP.During the electrochemical experiments, 99% Zn removal – under metallic form – and 94% Mn removal – under MnO₂ form – both with a high degree of purity, were achieved. The SSP process reached the selective precipitation of chosen metals with 99% efficiency – Fe, Al and Mn in the form of metal hydroxides, Cu and Zn as metal sulfides. The results achieved may be used for designing a process appropriate for the selective recovery of metals from the AMD discharged from the Smolník deposit.     

Sniffing out cancer using “chemical nose” sensors

Comment on: Bajaj A, et al. Proc Nat Acad Sci 2009; 106:10912-16.     

Fractionation profiling: a fast and versatile approach for mapping vesicle proteomes and protein–protein interactions

We developed “fractionation profiling,” a method for rapid proteomic analysis of membrane vesicles and protein particles. The approach combines quantitative proteomics with subcellular fractionation to generate signature protein abundance distribution profiles. Functionally associated groups of proteins are revealed through cluster analysis. To validate the method, we first profiled >3500 proteins from HeLa cells and identified known clathrin-coated vesicle proteins with >90% accuracy. We then profiled >2400 proteins from Drosophila S2 cells, and we report the first comprehensive insect clathrin-coated vesicle proteome. Of importance, the cluster analysis extends to all profiled proteins and thus identifies a diverse range of known and novel cytosolic and membrane-associated protein complexes. We show that it also allows the detailed compositional characterization of complexes, including the delineation of subcomplexes and subunit stoichiometry. Our predictions are presented in an interactive database. Fractionation profiling is a universal method for defining the clathrin-coated vesicle proteome and may be adapted for the analysis of other types of vesicles and particles. In addition, it provides a versatile tool for the rapid generation of large-scale protein interaction maps.     

The “biological ego”. From Garrod's “chemical individuality” to Burnet's “self”

Starting from the conceptual premises of Garrod, who as long ago as 1902 spoke of chemical individuality, and of Burnet (1949), who recognized as self one's own molecular antigenic structures (as opposed to the antigenic alien: the non- self), the discovery and understanding of HLA antigens and of their extraordinarily individual and differentiated polymorphisms have gained universal recognition. Transplant medicine has now dramatically stressed, within man's knowledge of himself, the characteristic of his biological uniqueness. Today man, having become aware of being a biological antigenic-molecular individuality which is unique and different from that of all of his fellow men (except for monozygotic twins), can therefore easily consider himself a true biological Ego.Abbreviations BMT bone marrow transplantation - GVHD graft versus host disease - HLA human leukocyte antigens - MHC major histocompatibility complex - MLC mixed lymphocyte culture - MLR mixed lymphocyte reaction     

Dye–tissue interactions: mechanisms,quantification and bonding parameters for dyes used in biological staining

Staining of tissues by dyes is accomplished through various types of bonds, some of which have been poorly defined in traditional biological literature. Here, basic principles of bonding are reviewed to establish uniform terminology and definitions consistent with the field of chemistry. The concept of charge – its presence or absence, magnitude, extent of delocalization and potential for being displaced by outside forces – underlies all bonding phenomena. These same attributes influence solubility and resistance to extraction during dehydration of tissue sections. Covalent bonds involve shared electrons; they are very strong and essentially irreversible under conditions encountered during staining. Polar covalent bonds within dye molecules generate partial atomic charges that create the potential for hydrogen bonding. This is measured by the hydrogen bonding parameter (h), the number of groups bearing charges within the ranges ?0.15 to ?0.50 eV or +0.15 to +0.30 eV. The potential for ionic bonding is indicated by net charge (Z), while the strength of such bonds is a function of charge site geometry on both bonding partners. Charge delocalization owing to conjugation, electron influencing groups, and resonance creates soft charge sites in which the ionic charge is spread over a large volume. Poorly delocalized charges or point charges are hard (small in volume). Firm bonds result from hard-hard or soft-soft pairs. Hard-soft combinations are weak, readily displaced in competitive interactions, and disrupted by solvents. Coordinate bonds with certain metals are involved with mordant staining and metal chelation dyes. Three different van der Waals attractions comprise the remainder of bonding types, all involving dipoles: Keesom (dipole-dipole) forces, Debye (dipole-induced dipole) forces and London (induced dipole-induced dipole) forces. Potentials for engaging in any of these is quantified by measures of polarity (dipole moment, d), polarizability (crudely with π atoms describing the size of the conjugated system, or more directly with α), hydrophobicity (with the octanol-water partition coefficient, log P or the more convenient Hydrophobic Index, HI), and the number of halogen atoms (X). By using molecular modeling software, quantitative measures of bonding potential (bonding parameters) have been determined for over 400 dyes.     

Evo-devo and the search for homology (“sameness”) in biological systems

Developmental biology and evolutionary studies have merged into evolutionary developmental biology (“evo-devo”). This synthesis already influenced and still continues to change the conceptual framework of structural biology. One of the cornerstones of structural biology is the concept of homology. But the search for homology (“sameness”) of biological structures depends on our favourite perspectives (axioms, paradigms). Five levels of homology (“sameness”) can be identified in the literature, although they overlap to some degree: (i) serial homology (homonomy) within modular organisms, (ii) historical homology (synapomorphy), which is taken as the only acceptable homology by many biologists, (iii) underlying homology (i.e., parallelism) in closely related taxa, (iv) deep evolutionary homology due to the “same” master genes in distantly related phyla, and (v) molecular homology exclusively at gene level. The following essay gives emphasis on the heuristic advantages of seemingly opposing perspectives in structural biology, with examples mainly from comparative plant morphology. The organization of the plant body in the majority of angiosperms led to the recognition of the classical root–shoot model. In some lineages bauplan rules were transcended during evolution and development. This resulted in morphological misfits such as the Podostemaceae, peculiar eudicots adapted to submerged river rocks. Their transformed “roots” and “shoots” fit only to a limited degree into the classical model which is based on either–or thinking. It has to be widened into a continuum model by taking over elements of fuzzy logic and fractal geometry to accommodate for lineages such as the Podostemaceae.     

PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

Background

The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND) seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND.

Results

Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days.

Conclusions

Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.     

A “lookup table” schema for synthetic biological patterning

A schema is proposed by which the three-dimensional structure and temporal development of a biological organism might be encoded and implemented via a genetic “lookup table”. In the schema, diffusive morphogen gradients and/or the global concentration of a quickly diffusing signal index sets of kinase genes having promoters with logarithmically diminished affinity for the signal. Specificity of indexing is enhanced via concomitant expression of phosphatases undoing phosphorylation by “neighboring” kinases of greater affinity. Combinations of thus-selected kinases in turn jointly activate, via multiple phosphorylation, a particular enzyme from a virtual, multi-dimensional array thereof, at locations and times specified within the “lookup table”. In principle, such a scheme could be employed to specify arbitrary gross anatomy, surface pigmentation, and/or developmental sequencing, extending the burgeoning toolset of the nascent field of synthetic morphology. A model of two-dimensional surface coloration using this scheme is specified, and LabVIEW software for its exploration is described and made available.     

Climate change effects on behavioral and physiological ecology of predator–prey interactions: Implications for conservation biological control

Habitat management under the auspices of conservation biological control is a widely used approach to foster conditions that ensure a diversity of predator species can persist spatially and temporally within agricultural landscapes in order to control their prey (pest) species. However, an emerging new factor, global climate change, has the potential to disrupt existing conservation biological control programs. Climate change may alter abiotic conditions such as temperature, precipitation, humidity and wind that in turn could alter the life-cycle timing of predator and prey species and the behavioral nature and strength of their interactions. Anticipating how climate change will affect predator and prey communities represents an important research challenge. We present a conceptual framework—the habitat domain concept—that is useful for understanding contingencies in the nature of predator diversity effects on prey based on predator and prey spatial movement in their habitat. We illustrate how this framework can be used to forecast whether biological control by predators will become more effective or become disrupted due to changing climate. We discuss how changes in predator–prey interactions are contingent on the tolerances of predators and prey species to changing abiotic conditions as determined by the degree of local adaptation and phenotypic plasticity exhibited by species populations. We conclude by discussing research approaches that are needed to help adjust conservation biological control management to deal with a climate future.     

Empirical modelling using dummy atoms (EMUDA): an alternative approach for studying “auxetic” structures

Auxetics (materials or structures) are systems with a negative Poisson's ratio, a property that arises from the way various geometric features in the structure (or internal structure in the case of materials) deform when subjected to uniaxial loads. Such systems are normally studied by examining the behaviour of idealised representations of structures, which deform in a controlled fashion (e.g. deforming solely through hinging or stretching). Methods used for the analysis typically involve construction of real physical macro-models and/or derivation of analytical expressions for the mechanical properties. This paper proposes an alternative method for analysing such structures whereby idealised “hinging” or “stretching” structures are constructed within a molecular modelling environment using dummy atoms and examined using standard molecular mechanics techniques. We will show that this methodology of “empirical modelling using dummy atoms” (EMUDA) successfully reproduces the known properties of 2D conventional and auxetic hexagonal honeycombs hence confirming the suitability of this technique for studying auxetic structures.     

An examination of Nubian and Egyptian biological distances: Support for biological diffusion or in situ development?

Many authors have speculated on Nubian biological evolution. Because of the contact Nubians had with other peoples, migration and/or invasion (biological diffusion) were originally thought to be the biological mechanism for skeletal changes in Nubians. Later, a new hypothesis was put forth, the in situ hypothesis. The new hypothesis postulated that Nubians evolved in situ, without much genetic influence from foreign populations. This study examined 12 Egyptian and Nubian groups in an effort to explore the relationship between the two populations and to test the in situ hypothesis. Data from nine cranial nonmetric traits were assessed for an estimate of biological distance, using Mahalanobis D² with a tetrachoric matrix. The distance scores were then input into principal coordinates analysis (PCO) to depict the relationships between the two populations. PCO detected 60% of the variation in the first two principal coordinates. A plot of the distance scores revealed only one cluster; the Nubian and Egyptian groups clustered together. The grouping of the Nubians and Egyptians indicates there may have been some sort of gene flow between these groups of Nubians and Egyptians. However, common adaptation to similar environments may also be responsible for this pattern. Although the predominant results in this study appear to support the biological diffusion hypothesis, the in situ hypothesis was not completely negated.     

Complete separation of urinary metabolites of xylene in HPLC/DAD using β-cyclodextrin: Application for biological monitoring

To determine the biomarkers of exposure to xylene, urinary 2-, 3- and 4-methyl-hippuric acids, a new HPLC/DAD analytical method has been developed, which uses β-cyclodextrin as an additive for elution; its complexing abilities are exploited to achieve complete chromatographic separation of the three isomers. The mobile phase was a 3% aqueous solution of β-cyclodextrin, pH 3, and methanol, 80:20, in isocratic conditions, with a flow rate of 1 mL/min. To optimize quantitative analysis three wavelengths were employed for detection: λ = 198 nm, λ = 200 nm, and λ = 202 nm. SPE was applied for the extraction from urine samples of analytes. Validation parameters show recoveries always above 82%; LOD was set at 1 μg/mL with an LOQ of 3 μg/mL. The linear dynamic range (from 4 to 100 μg/mL) showed excellent correspondence. This method is rapid and inexpensive and can be applied to several samples simultaneously using a manifold for SPE extraction. The analytes were separated completely and could be fully quantified. The method was used for the analysis of urine samples from 54 workers exposed to xylene in hospital laboratories and showed a good applicability while allowing quantification even at low doses.     

Derivation of 13C chemical shift surfaces for the anomeric carbons of oligosaccharides and glycopeptides using ab initio methodology

The dependence between the anomeric carbon chemical shift and the glycosidic bond , dihedral angles in oligosaccharide and glycopeptide model compounds was studied by Gauge-Including Atomic Orbital (GIAO) ab initio calculations. Complete chemical shift surfaces versus and for d-Glcp-d-Glcp disaccharides with (11), (12), (13), and (14) linkages in both - and -configurations were computed using a 3-21G basis set, and scaled to reference results from calculations at the 6-311G^** level of theory. Similar surfaces were obtained for GlcNAcThr and GlcNAcSer model glycopeptides in - and -configurations, using in this case different conformations for the peptide moiety. The results obtained for both families of model compounds are discussed. We also present the determination of empirical formulas of the form ¹³C=f(,) obtained by fitting the raw ab initio data to trigonometric series expansions suitable for use in molecular mechanics and dynamics simulations. Our investigations are consistent with experimental observations and earlier calculations performed on smaller glycosidic bond models, and show the applicability of chemical shift surfaces in the study of the conformational behavior of oligosaccharides and glycopeptides.