Barrier potentials,molecular structure,force filed calculations and quantum chemical studies of some bipyridine di-carboxylic acids using the experimental and theoretical using (DFT,IVP) approach

ABSTRACT

FT-IR and FT-Raman spectra of 2,2′-bipyridine-3,3′-dicarboxylic acid (B3DA), 2,2′-bipyridine-4,4′-dicarboxylic acid (B4DA) and 2,2′-bipyridine-5,5′-dicarboxylic acid (B5DA) were recorded and analysed. The quantum chemical calculations of the title compounds begin with barrier potentials at different rotation angles around the C–C′ and C–Cα bonds in order to arrive conformation of lowest energy using DFT employing B3LYP functional with 6-311++G(d,p) basis set. This confirmation was further optimised to get the global minimum geometry. The vibrational frequencies along with IR, Raman intensities were computed, the rms error between observed and calculated frequencies were 11.2 cm^?1, 10.2 cm^?1 and 12.2 cm^?1 for B3DA, B4DA, and B5DA. An 87-element modified valence force field is derived by solving the inverse vibrational problem using Wilson’s GF matrix method. This force field is refined using 163 observed fundamentals employing in overlay least-squares technique. The average error between computed and experimental frequencies was found as 12.85 cm^?1 using potential energy distribution (PED) and eigenvectors. By using the gauge-independent atomic orbital (GIAO) method calculate the ¹H and ¹³C NMR chemical shifts of the molecules and compared with experimental results. The first-order hyperpolarisability, HOMO and LUMO energies, molecular electrostatic potential (MESP) and natural orbital analysis (NBO) of titled compounds were evaluated using DFT.     

Structural elucidation,theoretical investigation,biological screening and molecular docking studies of metal(II) complexes of NN donor ligand derived from 4-(2-aminopyridin-3-methylene)aminobenzoic acid

Complexes of 4-(((2-aminopyridin-3-yl)methylene)amino)benzoic acid ligand with cobalt(II) (1), nickel(II) (2), copper(II) (3), zinc(II) (4) and palladium(II) (5) are synthesized and characterized by using different spectroscopic methods like, UV–Visible, infrared, ¹H, ¹³C NMR, molar conductance, ESR and elemental analysis. Quantum chemical computations were made using DFT (density functional theory), B3LYP functional and 6-31+?+G(d,p)/SDD basis set in order to determine optimized structure parameters, frontier molecular orbital parameters and NLO properties. Based on DFT and experimental evidence, the complexes ensured that the octahedral geometry have been proposed for complexes 1, 2 and 4, square planar for complexes 3 and 5. All the complexes showed only residual molar conductance values and hence they were considered as non-electrolytes in DMF. In addition, the anti-proliferative activity of the compounds was evaluated against different human cancer cell lines (IMR-32, MCF-7, COLO205, A549, HeLa and HEK 293) and cisplatin is used as a reference drug. Compounds 1 and 4 showed remarkable cytotoxicity in five cancer cell lines tested except MCF-7. Also, the compounds were examined for their in vitro antimicrobial and scavenging activities. The molecular docking results are well corroborated with the experimental anticancer activity results.

     

Predicting the distribution and ecological niche of unexploited snow crab (Chionoecetes opilio) populations in Alaskan waters: a first open-access ensemble model

Populations of the snow crab (Chionoecetes opilio) are widely distributed on high-latitude continental shelves of the North Pacific and North Atlantic, and represent a valuable resource in both the United States and Canada. In US waters, snow crabs are found throughout the Arctic and sub-Arctic seas surrounding Alaska, north of the Aleutian Islands, yet commercial harvest currently focuses on the more southerly population in the Bering Sea. Population dynamics are well-monitored in exploited areas, but few data exist for populations further north where climate trends in the Arctic appear to be affecting species' distributions and community structure on multiple trophic levels. Moreover, increased shipping traffic, as well as fisheries and petroleum resource development, may add additional pressures in northern portions of the range as seasonal ice cover continues to decline. In the face of these pressures, we examined the ecological niche and population distribution of snow crabs in Alaskan waters using a GIS-based spatial modeling approach. We present the first quantitative open-access model predictions of snow-crab distribution, abundance, and biomass in the Chukchi and Beaufort Seas. Multi-variate analysis of environmental drivers of species' distribution and community structure commonly rely on multiple linear regression methods. The spatial modeling approach employed here improves upon linear regression methods in allowing for exploration of nonlinear relationships and interactions between variables. Three machine-learning algorithms were used to evaluate relationships between snow-crab distribution and environmental parameters, including TreeNet, Random Forests, and MARS. An ensemble model was then generated by combining output from these three models to generate consensus predictions for presence-absence, abundance, and biomass of snow crabs. Each algorithm identified a suite of variables most important in predicting snow-crab distribution, including nutrient and chlorophyll-a concentrations in overlying waters, temperature, salinity, and annual sea-ice cover; this information may be used to develop and test hypotheses regarding the ecology of this species. This is the first such quantitative model for snow crabs, and all GIS-data layers compiled for this project are freely available from the authors, upon request, for public use and improvement.