Three-dimensional Structure Of Molecule Research Articles

Two QSAR models for predicting the toxicity of chemicals towards Tetrahymena pyriformis based on topological-norm descriptors and spatial-norm descriptors

ABSTRACT Quantitative structure-activity relationship (QSAR) is important for safe, rapid and effective risk assessment of chemicals. In this study, two QSAR models were established with 1230 chemicals to predict toxicity towards Tetrahymena pyriformis using multiple linear regression (MLR) method. The topological(T)-QSAR model was developed by using topological-norm descriptors generated from the topological structure, and the spatial(S)-QSAR model were built with spatial-norm descriptors obtained from the three-dimensional structure of molecules and topological-norm descriptors. The r 2 training and r 2 test are 0.8304 and 0.8338 for the T-QSAR model, and 0.8485 and 0.8585 for the S-QSAR model, which means that T-QSAR model and S-QSAR model can be used to predict toxicity quickly and accurately. In addition, we also conducted validation on the developed models. Satisfying validation results and statistical parameters demonstrated that QSAR models based on the topological-norm descriptors and spatial-norm descriptors proposed in this paper could be further utilized to estimate the toxicity of chemicals towards Tetrahymena pyriformis.

Molecular Model and Its Simplification in Teaching Stereoisomerism at Undergraduate Level

The role of molecular models in teaching chemistry is well-known. It is widely used in explaining the shape of molecules. Several authors have reported the difficulty in teaching stereochemistry/chirality. Some researchers have pleaded that the students face difficulty in solving stereochemistry problems because of poor visualization of three-dimensional structure of molecules. The present paper describes herewith the use of simple and inexpensive ball-stick molecular models in teaching stereoisomerism (conformation, configuration, and chirality in allenes) of organic molecules at undergraduate introductory organic chemistry course. It specially describes the use of simplified molecular models in determining the configuration (R or S) of the molecule.

One novel calix[4]arene based QCM sensor for sensitive, selective and high performance-sensing of formaldehyde at room temperature

This work designs the synthesis of a novel amino morpholine schiff base functionalized calix[4]arene cage (SCC), its deposition onto Quartz Crystal Microbalance (QCM) crystal surface, and usage for the selective detecting of formaldehyde (HCHO). The SCC modified QCM sensor has been characterized by contact angle measurements and microscopy images. Initial experiments revealed that the frequency response decreased significantly which means that there was a good interaction between the SCC molecules and HCHO. The proposed sensor exhibited a linear response towards HCHO in different concentrations ranging from 1.85 to 9.25 ppm, having the high sensitivity (S) and low limit of detection (LOD) being 18.324 Hz/ppm and 0.67 ppm, respectively. Furthermore, the adsorption behavior and mechanism of HCHO onto the QCM sensor were investigated for this sensing system and the adsorption data exhibited a good correlation with the Freundlich and Langmuir-Freundlich adsorption models in terms of the regression coefficient. The QCM sensor showed outstanding selective performance to HCHO among %97 RH and some a number of interfering volatile organic compounds (VOCs) such as chloroform, dichloromethane, acetone, n-hexane, methanol, xylene, and ammonia. Thus, real-time, sensitive, selective and effective recognition of HCHO by the sensor can be explained some adsorption mechanisms such as size-fit concept, three-dimensional structures of molecules and interaction between moieties of the sensible film layer and analyte molecules such as hydrogen bonding interactions.

Pyrimidine Derivatives: QSAR Studies of Larvicidal Activity against Aedes aegypti

The present study investigated the activity of pyrimidine derivatives against Aedes aegypti. Two compounds, 3c and 3d showed excellent larvicide activity. Additionally, quantitative structure-activity relationship (QSAR) models were built using multiple-linear regression and partial least squares with descriptors generated from Dragon and VolSurf+ software, respectively. The best model is obtained with multiple linear regression (MLR), leading to a robust model. Moreover, the QSAR model is validated by means of some internal validation techniques in order to check its reliability, quality and robustness for predicting the larvicidal activity against A. aegypti. The models confirmed that the three-dimensional structure of molecules, steric properties, hydrophobic polar surface area, log partition (logP) and a simple pattern of substituent groups as methyl, methoxy, and succinimide in the pyrimidine derivatives are responsible for the larvicidal activity of the pyrimidine derivatives. Even more, the activity decreases by an electron-withdrawing group in R1 and increases when it is replaced by an aromatic ring activator group. These findings will aid in further studies of new pyrimidine derivatives active against Aedes aegypti.

4D- quantitative structure–activity relationship modeling: making a comeback

ABSTRACT Introduction: Predictive Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential methodology for rapidly assessing various properties of chemicals. The vast majority of these QSAR models utilize numerical descriptors derived from the two- and/or three-dimensional structures of molecules. However, the conformation-dependent characteristics of flexible molecules and their dynamic interactions with biological target(s) is/are not encoded by these descriptors, leading to limited prediction performances and reduced interpretability. 2D/3D QSAR models are successful for virtual screening, but typically suffer at lead optimization stages. That is why conformation-dependent 4D-QSAR modeling methods were developed two decades ago. However, these methods have always suffered from the associated computational cost. Recently, 4D-QSAR has been experiencing a significant come-back due to rapid advances in GPU-accelerated molecular dynamic simulations and modern machine learning techniques. Areas covered: Herein, the authors briefly review the literature regarding 4D-QSAR modeling and describe its modern workflow called MD-QSAR. Challenges and current limitations are also highlighted. Expert opinion: The development of hyper-predictive MD-QSAR models could represent a disruptive technology for analyzing, understanding, and optimizing dynamic protein-ligand interactions with countless applications for drug discovery and chemical toxicity assessment. Therefore, there has never been a better time and relevance for molecular modeling teams to engage in hyper-predictive MD-QSAR modeling.

Molecular Dynamics Study of Binding of Substrates Bearing Two Positively Charged Residues to Oligopeptidase B from Serratia proteamaculans

The behavior of the peptide substrates GlyArgArgGly and GlyLysArgGly, which contain arginine or lysine at the Р2 position, in the active site of oligopeptidase В from the gamma-proteobacterium Serratia proteamaculans was studied by molecular dynamics simulations. The nature of the residue at the Р2 position was shown not only to influence the position of this residue and its contacts with the amino-acid environment in the substrate-binding pocket but also to affect the conformational dynamics of the entire peptide. Only the residue at the Р1 position forms persistent contacts with the S1-substrate-binding site of the enzyme, whereas contacts of the residue at the Р2 position may vary depending on its nature. Molecular dynamics simulations are shown to complement and improve the knowledge extracted from X-ray diffraction studies that enable the determination of the three-dimensional structures of molecules in one of numerous alternative conformations.

Building Molecular Models Using Screw-On Bottle Caps

Chemical models can be built using screw-on bottle caps. Two identical caps can be joined together by thermal welding to form atoms, and the resulting atoms can be joined together by welding or by hot polymer glue to form molecules. The method is easy, can be applied at every level of chemical education, and gives access to an unlimited number of models at almost no cost. It inspires hands-on activity of pupils and can be used to show the dependence between the three-dimensional structure of molecules and their chemical, physical, and biological features.

MOQUAC, a new expression for the excess Gibbs energy based on molecular orientations

A new expression for the excess Gibbs energy based on molecular orientations is derived. In this expression, the effect of molecular orientation on a molecular interaction is explicitly taken into account. In this way the three-dimensional structure of molecules can be accounted for and effects like multiple contact points or steric hindrance can be considered. This is especially important for the modeling of components with more than one strongly interacting functional group, or for the modeling of isomers. The expression is based on a quasi-chemical approach and leads to a system of equations, for which a very efficient iterative solution method exists. In combination with a predictive model, which uses information from a quantum-chemical calculation and describes the interaction energy in dependence of the molecular orientation, a priori method for the prediction of thermophysical data of liquids is presented. A methodological comparison with the structure-interpolating group-contribution method UNIFAC and the surface segment based COSMO-RS model is given. The new model is compared to results from a lattice simulation and a first application to real systems is presented.

Synthesis and Biological Evaluation of New Bischromone Derivatives with Antiproliferative Activity

The synthesis of new bischromone derivatives (4a-c and 5a-c) as potential anticancer drugs is described. The difference in the reactivity between 4-oxo-4H-chromene-3-carboxylic acid 2 (or its methyl ester 3) and 4-oxo-4H-chromene-3-carbonyl chloride 1 with three different polyamines: 3,3'-diamino-N-methyldipropylamine (a), 1,4-bis(3-aminopropyl)piperazine (b), 4,9-dioxa-1,12-dodecanediamine (c) resulted in the formation of two different groups of products, compounds 4a-c and 5a-c, designed in agreement with the bisintercalators' structural requirements. The transformation of 4-oxo-4H-chromene-3-carboxylic acid into 2H-chromene-2,4(3H)-diones (5) was confirmed by the NMR and XRD experiments. Compounds 4a and 5a were evaluated in vitro in the highly aggressive melanoma cell line A375. An enhanced induction of apoptosis and cell cycle arrest clearly revealed that compound 5a was more potent than 4a. Compound 5a was also more active in diminishing the adhesive potential of melanoma cells. Current studies support the notion that small changes in the three-dimensional structure of molecules might have a substantial impact on their biological activity.

A study of the quantitative relation between the radial distribution function and saturated vapor pressure curve in the series of n-alkanes on the basis of a modified linear dynamic model

A new approach to the determination of the quantitative relations between the structure and properties of molecules on the basis of a modified linear dynamic model is suggested. The dependence between the radial distribution function and saturated vapor pressure curve in the series of n-alkanes was studied. It was found that the suggested model could be used not only to reveal correlation dependences between the structure and activity of molecules but also to obtain information about the three-dimensional structure of molecules with the required properties.

One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties

Many chemoinformatics applications, including high-throughput virtual screening, benefit from being able to rapidly predict the physical, chemical, and biological properties of small molecules to screen large repositories and identify suitable candidates. When training sets are available, machine learning methods provide an effective alternative to ab initio methods for these predictions. Here, we leverage rich molecular representations including 1D SMILES strings, 2D graphs of bonds, and 3D coordinates to derive efficient machine learning kernels to address regression problems. We further expand the library of available spectral kernels for small molecules developed for classification problems to include 2.5D surface and 3D kernels using Delaunay tetrahedrization and other techniques from computational geometry, 3D pharmacophore kernels, and 3.5D or 4D kernels capable of taking into account multiple molecular configurations, such as conformers. The kernels are comprehensively tested using cross-validation and redundancy-reduction methods on regression problems using several available data sets to predict boiling points, melting points, aqueous solubility, octanol/water partition coefficients, and biological activity with state-of-the art results. When sufficient training data are available, 2D spectral kernels in general tend to yield the best and most robust results, better than state-of-the art. On data sets containing thousands of molecules, the kernels achieve a squared correlation coefficient of 0.91 for aqueous solubility prediction and 0.94 for octanol/water partition coefficient prediction. Averaging over conformations improves the performance of kernels based on the three-dimensional structure of molecules, especially on challenging data sets. Kernel predictors for aqueous solubility (kSOL), LogP (kLOGP), and melting point (kMELT) are available over the Web through: http://cdb.ics.uci.edu.

A protein-protein docking algorithm dependent on the type of complexes.

An efficient 'soft docking' algorithm is described to assist the prediction of protein-protein association using three-dimensional structures of molecules. The basic tools are the 'simplified protein' model and the docking algorithm of Wodak and Janin. The side chain flexibility of Arg, Lys, Asp, Glu and Met residues at the protein surface is taken into account. The complex type-dependent filtering technique on the basis of the geometric matching, hydrophobicity and electrostatic complementarity is used to select candidate binding modes. Subsequently, we calculate a scoring function which includes electrostatic and desolvation energy terms. In the 44 complexes tested including enzyme-inhibitor, antibody-antigen and other complexes, native-like structures were all found, of which 30 were ranked in the top 20. Thus, our soft docking algorithm has the potential to predict protein-protein recognition.

A database for cell signaling networks.

We developed a data and knowledge base for cellular signal transduction in human cells, to make this rapidly growing information available. The database includes all the biological properties of cellular signal transduction, including biological reactions that transfer cellular signals and molecular attributes characterized by sequences, structures, and functions. Since the database is based on the object-oriented technique, highly flexible methods of data definition and modification are necessary to handle this diverse and complex biological information. The database includes attractive graphical representations of signaling cascades and the three-dimensional structure of molecules. The database is a novel application of ACEDB, which was the database originally developed to store the C. elegans genome. The database can be accessed through the Internet at http://geo.nihs.go.jp/csndb.html.

Computer Techniques for Drug Design

Designing molecules has become more and more important in drug development. Computational methods for designing drugs rationally and efficiently are attracting much attention. Methods of Quantitative Structure-Activity Relationships (QSAR) represented by Hansch method seem to be excellent for lead optimization, but not for lead generation. As for lead generation, another computational method based on three-dimensional structures of molecules is expected to be useful. Theoretical calculations on stabilities, physical and chemical properties of molecules, and on molecular interactions with target macromolecules, can give useful informations which enable us to explain structure-activity relationships and to design new active structures. Computer graphics are indispensable tools for performing computer-aided durg design efficiently. We also describe about the basis and application of molecular dynamics calculation.

Determination of three-dimensional structures of molecules by gas chromatography on graphitized carbon black and on monolayers of planar molecules deposited on it

Determination of three-dimensional structures of molecules by gas chromatography on graphitized carbon black and on monolayers of planar molecules deposited on it