Chirality Measures of α-Amino Acids

Continuous symmetry and chirality measures: approximate algorithms for large molecular structures

Quantifying imperfect symmetry of molecules can help explore the sources, roles and extent of structural distortion. Based on the established methodology of continuous symmetry and chirality measures, we develop a set of three-dimensional molecular descriptors to estimate distortion of large structures. These three-dimensional geometrical descriptors quantify the gap between the desirable symmetry (or chirality) and the actual one. They are global parameters of the molecular geometry, intuitively defined, and have the ability to detect even minute structural changes of a given molecule across chemistry, including organic, inorganic, and biochemical systems. Application of these methods to large structures is challenging due to countless permutations that are involved in the symmetry operations and have to be accounted for. Our approach focuses on iteratively finding the approximate direction of the symmetry element in the three-dimensional space, and the relevant permutation. Major algorithmic improvements over previous versions are described, showing increased accuracy, reliability and structure preservation. The new algorithms are tested for three sets of molecular structures including pillar[5]arene complexes with Li+, C100 fullerenes, and large unit cells of metal organic frameworks. These developments complement our recent algorithms for calculating continuous symmetry and chirality measures for small molecules as well as protein homomers, and simplify the usage of the full set of measures for various research goals, in molecular modeling, QSAR and cheminformatics.

On Aromaticity of the Aromatic α-Amino Acids and Tuning of the NICS Indices to Find the Aromaticity Order

The NICS aromaticity indices of the rings in flexible phenylalanine (Phe), tryptophan (Trp), tyrosine (Tyr), and histidine (His) chiral molecules were analyzed. These molecules have several dozens of conformers, and their rings are slightly non-planar. Therefore, the population-averaged NICS_pav index was defined, and the NICS scans had to be performed with respect to planes found by the least-squares routine. A rule differentiating an obverse and a reverse ring face in aromatic amino acids was formulated. The NICS scan minima corresponding to the obverse and reverse face were unequal, which prompted us to use the term ring face aromaticity/ring face tropicity. It appeared that for Phe, Trp, Tyr, and His, the reverse face has always had higher ring face aromaticity/ring face tropicity than the obverse one. Despite the NICS modifications, uncertainty about the amino acid aromaticity order remained. This motivated us to use the integral INICS index newly proposed by Stanger as well. Then, the following sequence was obtained: Trp(phenyl) > Phe > Trp(pyrrole) > His > Tyr. The juxtaposition of the INICS indices of amino acids with that of some model rings revealed a fair transferability of the values. Finally, analysis of the substituent effect on INICS demonstrated that the aromaticity of Tyr is the lowest due to the strength of the OH group π-electron-donating effect able to perturb enough the ring charge distribution and its magnetic aromaticity. The NICS calculations were executed using the ARONICS program written within the project.

TorsiFlex: an automatic generator of torsional conformers. Application to the twenty proteinogenic amino acids

In this work, we introduce TorsiFlex, a user-friendly software written in Python 3 and designed to find all the torsional conformers of flexible acyclic molecules in an automatic fashion. For the mapping of the torsional potential energy surface, the algorithm implemented in TorsiFlex combines two searching strategies: preconditioned and stochastic. The former is a type of systematic search based on chemical knowledge and should be carried out before the stochastic (random) search. The algorithm applies several validation tests to accelerate the exploration of the torsional space. For instance, the optimized structures are stored and this information is used to prevent revisiting these points and their surroundings in future iterations. TorsiFlex operates with a dual-level strategy by which the initial search is carried out at an inexpensive electronic structure level of theory and the located conformers are reoptimized at a higher level. Additionally, the program takes advantage of conformational enantiomerism, when possible. As a case study, and in order to exemplify the effectiveness and capabilities of this program, we have employed TorsiFlex to locate the conformers of the twenty proteinogenic amino acids in their neutral canonical form. TorsiFlex has produced a number of conformers that roughly doubles the amount of the most complete work to date.

Endohedral isomerism in model achiral and chiral La@C58N2 systems

Endohedral structures with La⁰ or La³⁺ encapsulated in chiral (1,16)C₅₈N₂ or achiral (1,4)C₅₈N₂ diazafullerenes were studied at the B3LYP/G-31G*/SDD level. Two stable locations of La⁰ and La³⁺ are possible in each cage but only with La⁰@(1,16)C₅₈N₂ can the two isomers coexist. We found that an AIM determined hapticity of the endohedral species selectively differentiates the systems. We predict that there will always exist IR and Raman bands which allow for them to be identified in the presence of the parent cage. For the La⁰@(1,16) C₅₈N₂ molecules and the parent diazafullerene, the Raman spectra are likely to reveal a pre-resonance effect even at 785 nm and it seems possible to selectively excite only one isomer. The calculated electronic spectra suggested a chance to determine the less populated diazafullerene in the presence of the more populated one, be it chiral or achiral. For the chiral endohedral isomers, the calculated VCD spectra are quite dissimilar and the two endohedral isomers and the parent heterofullerene seem to be easily detected. Eventually, we defined the endohedral isomerism as follows: The endohedral isomerism is the phenomenon whereby an internal individuum captured in a cage can occupy more than one stable position without changing the cage connectivity.

Chiral Ramachandran Plots I: Glycine

Ramachandran plots (RPs) map the wealth of conformations of the polypeptide backbone and are widely used to characterize protein structures. A limitation of the RPs is that they are based solely on two dihedral angles for each amino acid residue and provide therefore only a partial picture of the conformational richness of the protein. Here we extend the structural RP analysis of proteins from a two-dimensional (2D) map to a three-dimensional map by adding the quantitative degree of chirality-the continuous chirality measure (CCM)-of the amino acid residue at each point in the RP. This measure encompasses all bond angles and bond lengths of an amino acid residue. We focus in this report on glycine (Gly) because, due to its flexibility, it occupies a large portion of the 2D map, thus allowing a detailed study of the chirality measure, and in order to evaluate the justification of classically labeling Gly as the only achiral amino acid. We have analyzed in detail 4366 Gly residues extracted from high resolution crystallographic data of 160 proteins. This analysis reveals not only that Gly is practically always conformationally chiral, but that upon comparing with the backbone of all amino acids, the quantitative chirality values of Gly are of similar magnitudes to those of the (chiral) amino acids. Structural trends and energetic considerations are discussed in detail. Generally we show that adding chirality to Ramachandran plots creates far more informative plots that highlight the sensitivity of the protein structure to minor conformational changes.

SCRAMBLE'N'GAMBLE: a tool for fast and facile generation of random data for statistical evaluation of QSAR models

A common practice in modern QSAR modelling is to derive models by variable selection methods working on large descriptor pools. As pointed out previously, this is intrinsically burdened with the risk of finding random correlations. Therefore it is desirable to perform tests showing the performance of models built on random data. In this contribution, we introduce a simple and freely available software tool SCRAMBLE’N’GAMBLE that is aimed at facilitating data preparation for y-randomization and pseudo-descriptors tests. Then, four close-to-real-world modelling situations are analysed. The tests indicate what the quality of obtained QSAR models is like in comparison to chance models derived from random data. The non-randomness is not the only requirement for a good QSAR model, however, it is a good practice to consider it together with internal statistical parameters and possible physical interpretations of a model.

On splitting of the NICS(1) magnetic aromaticity index

The NICS(1) magnetic aromaticity index is split into NICS(1) and NICS(−1) indices when the points 1 Å above and below the ring center are inequivalent by symmetry. The two indices characterize the aromaticity of the two ring faces rather than the ring itself.