Partial inclusion of bis(1,10-phenanthroline)silver(I) salicylate in ß-cyclodextrin: Spectroscopic characterization, in vitro and in silico antimicrobial evaluation.

Silver complexes containing 1,10-phenanthroline as a coordinated ligand have been of great interest due to their antibacterial and antifungal pharmacological properties. In this paper, we describe the synthesis of a new partial inclusion complex of bis(1,10-phenanthroline)silver(I) salicylate in ß-cyclodextrin (ß-CD) which was synthesized with a good yield. The compounds were characterized by FTIR, 1H, 13C NMR including 1H-1H COSY, TGA/DSC, elemental analysis (CHN), and X-ray powder diffraction. The results suggest the presence of non-covalent interactions such as hydrogen bonds, van der Waals forces, and hydrophobic interactions in the formation of the partial inclusion compound between ß-CD and bis(1,10-phenanthroline)silver(I) salicylate [Ag(phen)2]salH. Additionally, an in silico prediction of 1,10-phenanthroline biological activities was carried out and the acquired data suggests several potential targets associated with the antimicrobial activity of this compound and its silver complex. Most predicted targets are related to antimicrobial virulence and resistance that are a serious threat to global public health. The inclusion compound showed a higher inhibiting growth of Candida albicans than the free complex [Ag(phen)2]salH indicating that the formation of the inclusion complex with ß-CD increases the bioavailability of the antimicrobial active species [Ag(phen)2]+ of the new silver(I) compound.

A comprehensive in silico analysis of the functional and structural impact of SNPs in the IGF1R gene.

Insulin-like growth factor 1 receptor (IGF1R) acts as a critical mediator of cell proliferation and survival. Many single nucleotide polymorphisms (SNPs) found in the IGF1R gene have been associated with various diseases, including both breast and prostate cancer. The genetics of these diseases could be better understood by knowing the functions of these SNPs. In this study, we performed a comprehensive analysis of the functional and structural impact of all known SNPs in this gene using publicly available computational prediction tools. Out of a total of 2412 SNPs in IGF1R retrieved from dbSNP, we found 32 nsSNPs, 58 sSNPs, 83 mRNA 3' UTR SNPs, and 2225 intronic SNPs. Among the nsSNPs, a total of six missense nsSNPs were found to be damaging by both a sequence homology-based tool (SIFT) and a structural homology-based method (PolyPhen), and one nonsense nsSNP was found. Further, we modeled mutant proteins and compared the total energy values with the native IGF1R protein, and showed that a mutation from arginine to cysteine at position 1216 (rs61740868) on the surface of the protein caused the greatest impact on stability. Also, the FASTSNP tool suggested that 31 sSNPs and 3 intronic SNPs might affect splicing regulation. Based on our investigation, we report potential candidate SNPs for future studies on IGF1R mutations.

Protein cutoff scanning: A comparative analysis of cutoff dependent and cutoff free methods for prospecting contacts in proteins.

In this study, we carried out a comparative analysis between two classical methodologies to prospect residue contacts in proteins: the traditional cutoff dependent (CD) approach and cutoff free Delaunay tessellation (DT). In addition, two alternative coarse-grained forms to represent residues were tested: using alpha carbon (CA) and side chain geometric center (GC). A database was built, comprising three top classes: all alpha, all beta, and alpha/beta. We found that the cutoff value at about 7.0 A emerges as an important distance parameter. Up to 7.0 A, CD and DT properties are unified, which implies that at this distance all contacts are complete and legitimate (not occluded). We also have shown that DT has an intrinsic missing edges problem when mapping the first layer of neighbors. In proteins, it may produce systematic errors affecting mainly the contact network in beta chains with CA. The almost-Delaunay (AD) approach has been proposed to solve this DT problem. We found that even AD may not be an advantageous solution. As a consequence, in the strict range up to 7.0 A, the CD approach revealed to be a simpler, more complete, and reliable technique than DT or AD. Finally, we have shown that coarse-grained residue representations may introduce bias in the analysis of neighbors in cutoffs up to 6.8 A, with CA favoring alpha proteins and GC favoring beta proteins. This provides an additional argument pointing to the value of 7.0 A as an important lower bound cutoff to be used in contact analysis of proteins.

The Application of DNA-Biosensors and Differential Scanning Calorimetry to the Study of the DNA-Binding Agent Berenil.

The in situ DNA-damaging capacity of berenil (1) has been investigated usingan electrochemical approach employing double stranded (ds) DNA-modified glassy carbonelectrode biosensors. Electrochemical voltammetric sensing of damage caused by 1 todsDNA was monitored by the appearance of peaks diagnostic of the oxidation of guanineand adenine. When 1 was incorporated directly onto the biosensor surface, DNA damagecould be observed at concentrations of additive as low as 10 µM. In contrast, when thedsDNA-modified biosensor was exposed to 1, in acetate buffer solution, the method wasmuch less sensitive and DNA damage could be detected only in the presence of 100 µMberenil. When mixed solutions of 1 and single stranded (ss) DNA, polyguanylic acid orpolyadenylic acid were submitted to voltammetric study, the oxidation signals of therespective bases decreased in a concentration-dependent manner and the major variation ofthe adenine current peak indicated preferential binding of 1 to adenine. The electrochemical results were in close agreement with those deriving from a differentialscanning calorimetric study of the DNA-berenil complex.

3D QSAR studies on binding affinities of coumarin natural products for glycosomal GAPDH of Trypanosoma cruzi.

Drug design strategies based on Comparative Molecular Field Analysis (CoMFA) have been used to predict the activity of new compounds. The major advantage of this approach is that it permits the analysis of a large number of quantitative descriptors and uses chemometric methods such as partial least squares (PLS) to correlate changes in bioactivity with changes in chemical structure. Because it is often difficult to rationalize all variables affecting the binding affinity of compounds using CoMFA solely, the program GRID was used to describe ligands in terms of their molecular interaction fields, MIFs. The program VolSurf that is able to compress the relevant information present in 3D maps into a few descriptors can treat these GRID fields. The binding affinities of a new set of compounds consisting of 13 coumarins, for one of which the three-dimensional ligand-enzyme bound structure is known, were studied. A final model based on the mentioned programs was independently validated by synthesizing and testing new coumarin derivatives. By relying on our knowledge of the real physical data (i.e., combining crystallographic and binding affinity results), it is also shown that ligand-based design agrees with structure-based design. The compound with the highest binding affinity was the coumarin chalepin, isolated from Rutaceae species, with an IC50 value of 55.5 microM towards the enzyme glyceraldehyde-3-phosphate dehydrogenase (gGAPDH) from glycosomes of the parasite Trypanosoma cruzi, the causative agent of Chagas' disease. The proposed models from GRID MIFs have revealed the importance of lipophilic interactions in modulating the inhibition, but without excluding the dependence on stereo-electronic properties as found from CoMFA fields.