Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerism

Stereoisomers have the same molecular formula and the same atom connectivity and their existence can be related to the presence of different three-dimensional arrangements. Stereoisomerism is of great importance in many different fields since the molecular properties and biological effects of the stereoisomers are often significantly different. Most drugs for example, are often composed of a single stereoisomer of a compound, and while one of them may have therapeutic effects on the body, another may be toxic. A challenging task is the automatic detection of stereoisomers using line input specifications such as SMILES or InChI since it requires information about group theory (to distinguish stereoisomers using mathematical information about its symmetry), topology and geometry of the molecule. There are several software packages that include modules to handle stereochemistry, especially the ones to name a chemical structure and/or view, edit and generate chemical structure diagrams. However, there is a lack of software capable of automatically analyzing a molecule represented as a graph and generate a classification of the type of isomerism present in a given atom or bond. Considering the importance of stereoisomerism when comparing chemical structures, this report describes a computer program for analyzing and processing steric information contained in a chemical structure represented as a molecular graph and providing as output a binary classification of the isomer type based on the recommended conventions. Due to the complexity of the underlying issue, specification of stereochemical information is currently limited to explicit stereochemistry and to the two most common types of stereochemistry caused by asymmetry around carbon atoms: chiral atom and double bond. A Webtool to automatically identify and classify stereochemistry is available at http://nams.lasige.di.fc.ul.pt/tools.ph

Interpretable correlation descriptors for quantitative structure-activity relationships

<p>Abstract</p> <p>Background</p> <p>The topological maximum cross correlation (TMACC) descriptors are alignment-independent 2D descriptors for the derivation of QSARs. TMACC descriptors are generated using atomic properties determined by molecular topology. Previous validation (<it>J Chem Inf Model </it>2007, <b>47</b>: 626-634) of the TMACC descriptor suggests it is competitive with the current state of the art.</p> <p>Results</p> <p>Here, we illustrate the interpretability of the TMACC descriptors, through the analysis of the QSARs of inhibitors of angiotensin converting enzyme (ACE) and dihydrofolate reductase (DHFR). In the case of the ACE inhibitors, the TMACC interpretation shows features specific to C-domain inhibition, which have not been explicitly identified in previous QSAR studies.</p> <p>Conclusions</p> <p>The TMACC interpretation can provide new insight into the structure-activity relationships studied. Freely available, open source software for generating the TMACC descriptors can be downloaded from <url>http://comp.chem.nottingham.ac.uk</url>.</p

Electronic Structures of LNA Phosphorothioate Oligonucleotides

Important oligonucleotides in anti-sense research have been investigated in silico and experimentally. This involves quantum mechanical (QM) calculations and chromatography experiments on locked nucleic acid (LNA) phosphorothioate (PS) oligonucleotides. iso-potential electrostatic surfaces are essential in this study and have been calculated from the wave functions derived from the QM calculations that provide binding information and other properties of these molecules. The QM calculations give details of the electronic structures in terms of e.g., energy and bonding, which make them distinguish or differentiate between the individual PS diastereoisomers determined by the position of sulfur atoms. Rules are derived from the electronic calculations of these molecules and include the effects of the phosphorothioate chirality and formation of electrostatic potential surfaces. Physical and electrochemical descriptors of the PS oligonucleotides are compared to the experiments in which chiral states on these molecules can be distinguished. The calculations demonstrate that electronic structure, electrostatic potential, and topology are highly sensitive to single PS configuration changes and can give a lead to understanding the activity of the molecules. Keywords: LNA phosphorothioate, DNA/LNA oligonucleotide, diastereoisomers, Hartree-Fock calculations, iso-potential surface, anion chromatogram

Empirical Potential Function for Simplified Protein Models: Combining Contact and Local Sequence-Structure Descriptors

An effective potential function is critical for protein structure prediction and folding simulation. Simplified protein models such as those requiring only $C_\alpha$ or backbone atoms are attractive because they enable efficient search of the conformational space. We show residue specific reduced discrete state models can represent the backbone conformations of proteins with small RMSD values. However, no potential functions exist that are designed for such simplified protein models. In this study, we develop optimal potential functions by combining contact interaction descriptors and local sequence-structure descriptors. The form of the potential function is a weighted linear sum of all descriptors, and the optimal weight coefficients are obtained through optimization using both native and decoy structures. The performance of the potential function in test of discriminating native protein structures from decoys is evaluated using several benchmark decoy sets. Our potential function requiring only backbone atoms or $C_\alpha$ atoms have comparable or better performance than several residue-based potential functions that require additional coordinates of side chain centers or coordinates of all side chain atoms. By reducing the residue alphabets down to size 5 for local structure-sequence relationship, the performance of the potential function can be further improved. Our results also suggest that local sequence-structure correlation may play important role in reducing the entropic cost of protein folding.Comment: 20 pages, 5 figures, 4 tables. In press, Protein

A New Euler's Formula for DNA Polyhedra

DNA polyhedra are cage-like architectures based on interlocked and interlinked DNA strands. We propose a formula which unites the basic features of these entangled structures. It is based on the transformation of the DNA polyhedral links into Seifert surfaces, which removes all knots. The numbers of components , of crossings , and of Seifert circles are related by a simple and elegant formula: . This formula connects the topological aspects of the DNA cage to the Euler characteristic of the underlying polyhedron. It implies that Seifert circles can be used as effective topological indices to describe polyhedral links. Our study demonstrates that, the new Euler's formula provides a theoretical framework for the stereo-chemistry of DNA polyhedra, which can characterize enzymatic transformations of DNA and be used to characterize and design novel cages with higher genus

Mathematical Analysis in Characterization of Carbon Nanotubes (CNTs) as possible Mosquito Repellents

Mosquitoes are a great threat to human health to date and are a subject of interdisciplinary research involving scientists from many areas. Recently much attention has been put to novel approaches to mosquito repellent products that involve the use of novel materials, such as carbon nanomaterials, where it is essential to determine their properties. This research discusses the full molecular characterization of carbon nanotubes (CNTs) produced by electrolysis in molten salts. Each CNT has its mathematical representation due to its hexagonal lattice structure. Multi-wall carbon nanotubes (MWCNTs) are considered. The focus is on determining their structural parameters: innermost and outermost diameters, chiral indices m and n, number of walls, and unit cell parameters. Corresponding frequency parts of Raman spectra of four experimentally produced CNTs are elaborated, and Python programming and Mathematica are employed for the most accurate (m,n) assignment. Determining the chirality of these samples enables the calculation of other structural properties, which are performed now, including their graph representation. The latter enables the evaluation of different distance-based topological indices (Wiener, Balaban, Sum-Balaban, Harary index, etc.) to predict some index-related properties of the molecules

The Eighth Central European Conference "Chemistry towards Biology": snapshot

The Eighth Central European Conference "Chemistry towards Biology" was held in Brno, Czech Republic, on 28 August – 1 September 2016The Eighth Central European Conference "Chemistry towards Biology" was held in Brno, Czech Republic, on 28 August-1 September 2016 to bring together experts in biology, chemistry and design of bioactive compounds; promote the exchange of scientific results, methods and ideas; and encourage cooperation between researchers from all over the world. The topics of the conference covered "Chemistry towards Biology", meaning that the event welcomed chemists working on biology-related problems, biologists using chemical methods, and students and other researchers of the respective areas that fall within the common scope of chemistry and biology. The authors of this manuscript are plenary speakers and other participants of the symposium and members of their research teams. The following summary highlights the major points/topics of the meeting

Characterizing human odorant signals: insights from insect semiochemistry and in silico modelling

Interactions relating to human chemical signalling, although widely acknowledged, are relatively poorly characterized chemically, except for human axillary odour. However, the extensive chemical ecology of insects, involving countless pheromone and other semiochemical identifications, may offer insights into overcoming problems of characterizing human-derived semiochemicals more widely. Current techniques for acquiring insect semiochemicals are discussed, particularly in relation to the need for samples to relate, as closely as possible, to the ecological situation in which they are naturally deployed. Analysis is facilitated by chromatography coupled to electrophysiological preparations from the olfactory organs of insects in vivo. This is not feasible with human olfaction, but there are now potential approaches using molecular genetically reconstructed olfactory preparations already in use with insect systems. There are specific insights of value for characterizing human semiochemicals from advanced studies on semiochemicals of haematophagous insects, which include those involving human hosts, in addition to wider studies on farm and companion animals. The characterization of the precise molecular properties recognized in olfaction could lead to new advances in analogue design and a range of novel semiochemicals for human benefit. There are insights from successful synthetic biology studies on insect semiochemicals using novel biosynthetic precursors. Already, wider opportunities in olfaction emerging from in silico studies, involving a range of theoretical and computational approaches to molecular design and understanding olfactory systems at the molecular level, are showing promise for studying human semiochemistry

Simplifying inverse material design problems for fixed lattices with alchemical chirality

Massive brute-force compute campaigns relying on demanding ab initio calculations routinely search for novel materials in chemical compound space, the vast virtual set of all conceivable stable combinations of elements and structural configurations which form matter. Here we demonstrate that 4-dimensional chirality, arising from anti-symmetry of alchemical perturbations, dissects that space and defines approximate ranks which effectively reduce its formal dimensionality, and enable us to break down its combinatorial scaling. The resulting distinct `alchemical' enantiomers must share the exact same electronic energy up to third order -- independent of respective covalent bond topology, and imposing relevant constraints on chemical bonding. Alchemical chirality deepens our understanding of chemical compound space and enables the `on-the-fly' establishment of new trends without empiricism for any materials with fixed lattices. We demonstrate its efficacy for three such cases: i) new formulas for estimating electronic energy contributions to chemical bonding; ii) analysis of the perturbed electron density of BN doped benzene; and iii) ranking stability estimates for BN doping in over 2,000 naphthalene and over 400 million picene derivatives