Peptide backbone folding induced by the C(alpha)-tetrasubstituted cyclic alpha-amino acids 4-amino-1,2-dithiolane-4-carboxylic acid (Adt) and 1-aminocyclopentane-1-carboxylic acid (Ac5c). A joint computational and experimental study

The conformational study of a new group of synthetic peptides containing 4-amino-1,2-dithiolane-4-carboxylic acid (Adt), a cysteine-related achiral residue, has been carried out through a joint application of computational and experimental methodologies. Molecular Dynamics simulations clearly suggest the tendency of this molecule to adopt a gamma-turn conformation in vacuum and help in analyzing the complex and crucial conformational behaviour of the dithiolane ring which appears to preferentially adopt a C(S)-like structure. Electronic structure calculations carried out in solution using the Density Functional Theory also indicate the preservation of the gamma-like folding in apolar solvents and the helix-like one in more polar solvents. A comparison with the achiral 1-aminocycloalkane-1-carboxylic acid (Ac5c) has been carried out using the same computational tools. NMR and IR data on dipeptide derivatives containing the Adt or Ac5c residue show that in chloroform solution all the models prefer a gamma-turn structure, centered at the cyclic residue, stabilized by an intramolecular H-bond, whereas in a more polar solvent, i.e. dimethyl sulfoxide, this folding is not maintained. The experimental conformational studies, extended to N-Boc protected tripeptides, clearly indicate the remarkable tendency of both the five-membered C(alpha)-tetrasubstituted cyclic amino acids Adt and Ac5c to induce the gamma-turn structure also in models able to adopt the beta-bend conformation.     

Group contributions to the thermodynamic properties of non-ionic organic solutes in dilute aqueous solution

The thermodynamic properties G _h ^o,H _h ^o, and C _p,h ^oassociated with the transfer of non-ionic organic compounds from gas to dilute aqueous solution and the limiting partial molar properties C _p ^o ,2 and V₂ ² of these compounds in water are described through a simple scheme of group contributions. A distinction is made between groups made only of carbon and hydrogen, and functional groups i.e. groups containing at least one atom different from carbon and hydrogen. Each group is assigned a contribution, for each property, through a least squares procedure which utilizes only molecules containing at most one functional group. Finally, for compounds containing more than one functional group, correction parameters are evaluated as the differences between the experimental values and those calculated by means of the group contributions. The different behavior of hydrophilic compared with hydrophobic groups is discussed for the various properties. A rationale for the correction parameters, i.e. for the effects of the interactions among hydrophilic groups on the thermodynamic properties, is attempted.     

Volumetric Properties of Binary Mixtures of Isomeric Butanols and C8 Solvents at 298.15 K

Excess molar volumes, V _m ^E, over the whole composition range for binary mixtures of 1-butanol, 2-butanol, and 2-methyl-2-propanol + 1-octanol, or 2-octanol, or di-n-butyl ether, or n-hexylacetate were determined at 298.15 K from density measurements carried out with a vibrating-tube densimeter. Small V _m ^E values, both positive and negative, are displayed by mixtures containing 1- or 2-octanol, whereas positive and larger values are always found for mixtures containing dibutyl ether and hexylacetate. These results can be justified in terms of H-bonding interactions and/or steric hindrance due to the branched alkyl chains. Partial molar volumes at infinite dilution of the isomeric butanols in the C8 compounds were also calculated from the apparent molar volumes in dilute solution. The solute-solvent interactions and the effects of the local organisation of the solvent around the butanol molecules were discussed using the void and cavity volumes as different estimates of the intrinsic volume of the molecules. The volumetric behavior of butanols seems to be determined by the solute-solvent interactions rather than packaging effects.     

Reducing the computational cost of NMR crystallography of organic powders at natural isotopic abundance with the help of 13C-13C dipolar couplings

Structure determination of functional organic compounds remains a formidable challenge when the sample exists as a powder. Nuclear magnetic resonance crystallography approaches based on the comparison of experimental and Density Functional Theory (DFT)-computed ¹H chemical shifts have already demonstrated great potential for structure determination of organic powders, but limitations still persist. In this study, we discuss the possibility of using ¹³C-¹³C dipolar couplings quantified on powdered theophylline at natural isotopic abundance with the help of dynamic nuclear polarization, to realize a DFT-free, rapid screening of a pool of structures predicted by ab initio random structure search. We show that although ¹³C-¹³C dipolar couplings can identify structures possessing long range structural motifs and unit cell parameters close to those of the true structure, it must be complemented with other data to recover information about the presence and the chemical nature of the supramolecular interactions.     

Chemometric Tools to Point Out Benchmarks and Chromophores in Pigments through Spectroscopic Data Analyses

Spectral preprocessing data and chemometric tools are analytical methods widely applied in several scientific contexts i.e., in archaeometric applications. A systematic classification of natural powdered pigments of organic and inorganic nature through Principal Component Analysis with a multi-instruments spectroscopic study is presented here. The methodology allows the access to elementary and molecular unique benchmarks to guide and speed up the identification of an unknown pigment and its recipe. This study is conducted on a set of 48 powdered pigments and tested on a real-case sample from the wall painting in S. Maria Delle Palate di Tusa (Messina, Italy). Four spectroscopic techniques (X-ray Fluorescence, Raman, Attenuated Total Reflectance and Total Reflectance Infrared Spectroscopies) and six different spectrometers are tested to evaluate the impact of different setups. The novelty of the work is to use a systematic approach on this initial dataset using the entire spectroscopic energy range without any windows selection to solve problems linked with the manipulation of large analytes/materials to find an indistinct property of one or more spectral bands opening new frontiers in the dataset spectroscopic analyses.     

HMGB1–Carbenoxolone Interactions: Dynamics Insights from Combined Nuclear Magnetic Resonance and Molecular Dynamics

The interplay of protein dynamics and molecular recognition is of fundamental importance in biological processes. Atomic‐resolution insights into these phenomena may provide new opportunities for drug discovery. Herein, we have combined NMR relaxation experiments and residual dipolar coupling (RDC) measurements with molecular dynamics (MD) simulations to study the effects of the anti‐inflammatory drug carbenoxolone (CBNX) on the conformational properties and on the internal dynamics of a subdomain (box A) of high‐mobility group B protein (HMGB1). ¹⁵N relaxation data show that CBNX binding enhances the fast pico‐ to nanosecond motions of a loop and partially removes the internal motional anisotropy of the first two helices of box A. Dipolar wave analysis of amide RDC data shows that ligand binding induces helical distortions. In parallel, increased mobility of the loop upon ligand binding is highlighted by the essential dynamics analysis (EDA) of MD simulations. Moreover, simulations detect two possible orientations for CBNX, which induces two possible conformations of helix H3, one being similar to the free form and the second one causing a partial helical distortion. Finally, we introduce a new approach for the analysis of the internal coordination of protein residues that is consistent with experimental data and allows us to pinpoint which substructures of box A are dynamically affected by CBNX. The observations reported here may be useful for understanding the role of protein dynamics in binding at atomic resolution.     

Predicting physical-chemical properties of compounds from molecular structures by recursive neural networks

In this paper, we report on the potential of a recently developed neural network for structures applied to the prediction of physical chemical properties of compounds. The proposed recursive neural network (RecNN) model is able to directly take as input a structured representation of the molecule and to model a direct and adaptive relationship between the molecular structure and target property. Therefore, it combines in a learning system the flexibility and general advantages of a neural network model with the representational power of a structured domain. As a result, a completely new approach to quantitative structure-activity relationship/quantitative structure-property relationship (QSPR/QSAR) analysis is obtained. An original representation of the molecular structures has been developed accounting for both the occurrence of specific atoms/groups and the topological relationships among them. Gibbs free energy of solvation in water, Delta(solv)G degrees , has been chosen as a benchmark for the model. The different approaches proposed in the literature for the prediction of this property have been reconsidered from a general perspective. The advantages of RecNN as a suitable tool for the automatization of fundamental parts of the QSPR/QSAR analysis have been highlighted. The RecNN model has been applied to the analysis of the Delta(solv)G degrees in water of 138 monofunctional acyclic organic compounds and tested on an external data set of 33 compounds. As a result of the statistical analysis, we obtained, for the predictive accuracy estimated on the test set, correlation coefficient R = 0.9985, standard deviation S = 0.68 kJ mol(-1), and mean absolute error MAE = 0.46 kJ mol(-1). The inherent ability of RecNN to abstract chemical knowledge through the adaptive learning process has been investigated by principal components analysis of the internal representations computed by the network. It has been found that the model recognizes the chemical compounds on the basis of a nontrivial combination of their chemical structure and target property.     

Characterization of the Phytochemical Profiles and Biological Activities of Ajuga chamaepitys subsp. chia var. chia and Ajuga bombycina by High-Performance Liquid Chromatography–Electrospray Ionization–Tandem Mass Spectrometry (HPLC–ESI–MSn)

This study investigates into the pharmacological potential of three solvent extracts (ethyl acetate, methanol, and water) of two Ajuga species (Ajuga chamaepitys subsp. chia var. chia and Ajuga bombycina) based on their antioxidant activity and enzyme inhibitory effects along with establishing the phytochemical profile. Spectrophotometric and high-performance liquid chromatography–electrospray ionization–tandem mass spectrometry (HPLC–ESI–MSⁿ) were used to determine the total and individual phytocompounds, respectively. Antioxidant potential was assessed using different assays such as DPPH, ABTS, CUPRAC, FRAP, phosphomolybdenum, and metal chelation. Enzyme inhibitory effects were studied against acetylcholinesterase, butyrylcholinesterase, tyrosinase, α-amylase, and α-glucosidase. The aqueous extract of both plants showed better ABTS scavenging, FRAP, and metal chelating activities. The methanol extracts displayed the highest tyrosinase inhibitory and antioxidant activity in the phosphomolybdenum assay while the ethyl acetate extracts of both plants showed better butyrylcholinesterase (BChE), α-amylase, and α-glucosidase inhibition. The total phenolic content was highest in the aqueous extract of A. chamaepitys while the methanolic extract of A. bombycina showed the highest flavonoid content. Identification by HPLC–ESI–MSⁿ revealed the presence of some individual compounds including phenolic acids, flavonoids, iridoid glycosides, phenylethanoid glycosides, and other compounds. To conclude, both A. chamaepitys and A. bombycina can be considered as rich sources of phytocompounds to manage chronic diseases.     

Force probing of protein crystals: An atomic force microscopy study

The atomic force microscope (AFM) was used for measuring force-distance curves on horse spleen ferritin crystals in liquid environment. In the region of the approach curve which corresponds to tip-surface contact, discrete jumps were recorded, as predicted by molecular dynamics simulations in the case of low tip-sample interaction. The observed jumps can be related to the removal of individual molecules from the surface by the AFM tip. A simple steric model, which takes into account tip and ferritin molecule size, can explain the displacements observed with excellent agreement. The elemental force jump resulting from the approach curves is a direct measure of the force required to remove a single molecule from the crystal face. We discuss the conditions under which the cantilever potential energy difference along the elemental force step provides the energy of extraction of a single molecule. The estimate of the intermolecular binding energy turns out to be in good agreement with the value calculated independently from the surface free energy of ferritin crystals. Received 10 February 2000 and Received in final form 4 May 2000