Abdellah Jarid

Support vector machines: development of QSAR models for predicting anti-HIV-1 activity of TIBO derivatives.

The tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepinone (TIBO) derivatives, as non-nucleoside reverse transcriptase inhibitors, acquire a significant place in the treatment of the infections by the HIV. In the present paper, the support vector machines (SVM) are used to develop quantitative relationships between the anti-HIV activity and four molecular descriptors of 82 TIBO derivatives. The results obtained by SVM give good statistical results compared to those given by multiple linear regressions and artificial neural networks. The contribution of each descriptor to structure-activity relationships was evaluated. It indicates the importance of the hydrophobic parameter. The proposed method can be successfully used to predict the anti-HIV of TIBO derivatives with only four molecular descriptors which can be calculated directly from molecular structure alone.

Substituent effect on ammonia–borane donor–acceptor complexes: a G2(MP2) molecular orbital study

Abstract H3BNHnMe3−n and Me3−nHnBNH3 (n=0–3) donor–acceptor complexes have been studied using the G2(MP2) method. Predicted equilibrium structures and dissociation energies have been correlated to the degree of substitution on the donor and the acceptor separately. It is found that successive methyl substitutions on boron reduce the dissociation energies of the complexes, contrary to the successive substitutions on nitrogen. The NBO partitioning scheme suggests that there is no correlation between the charge transfer and the dissociation energies. These results are interpreted in terms of the changes in the HOMO−LUMO gap, the type of acceptor and donor involved, and distortion of the acceptor and donor moieties.

Quantitative structure-activity relationship studies of TIBO derivatives using support vector machines

A quantitative structure-activity relationship (QSAR) study is suggested for the prediction of anti-HIV activity of tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepinone (TIBO) derivatives. The model was produced by using the support vector machine (SVM) technique to develop quantitative relationships between the anti-HIV activity and ten molecular descriptors of 89 TIBO derivatives. The performance and predictive capability of the SVM method were investigated and compared with other techniques such as artificial neural networks and multiple linear regression. The results obtained indicate that the SVM model with the kernel radial basis function can be successfully used to predict the anti-HIV activity of TIBO derivatives with only ten molecular descriptors that can be calculated directly from only molecular structure. The contribution of each descriptor to the structure-activity relationships was evaluated. Hydrophobicity of the molecule was thus found to take the most relevant part in the molecular description.

Comparative G2(MP2) molecular orbital study of [H3AlX(CH3)2]− (X=N, P, and As) and H3AlY(CH3)2 (Y=O, S, and Se) donor–acceptor complexes

[H3AlX(CH3)2]− (X=N, P, and As) and H3AlY(CH3)2 (Y=O, S, and Se) donor–acceptor complexes have been studied using G2(MP2) level of theory. The coordination mode, the structural and the methyl substitution effects upon complexation are analyzed. The interaction of the alane with the donor ligand is stronger in the anionic complexes than in the neutral ones and the methylated complexes are more stable than the hydrogenated ones. The coordination is ensured by tow interactions having a reverse character: interaction between a′ symmetry fragment molecular orbital (stabilizing) and interaction between a″ symmetry occupied molecular orbital (destabilizing) of the two fragments. A linear correlation has been established and discussed between the energetic and the structural effects upon methylation. The NBO partitioning scheme suggests that there is no correlation between the charge transfer and the G2(MP2) complexation energy.

Computational study of chemo- and stereoselectivity of α-cis, α-trans and α′-trans-himachalene epoxidation by MCPBA

Abstract Chemo- and steroselectivity studies of α- cis -himachalene, α- trans -himachalene and α′- trans -himachalene MCPBA epoxidation have been computed at the AM1 level of theory. The chemoselectivity is controlled by frontier molecular orbitals while the stereoselectivity is kinetically controlled. In agreement with experimental investigations, the monoepoxidation process occurs on the most substituted double bond. It is stereoselective for α- cis -himachalene and α- trans -himachalene but not for α′- trans -himachalene. Diepoxidation happens independently of monoepoxidation and is not stereoselective. We also notice that monoepoxidation is less asynchronous than diepoxidation.

The Hyperconjugation and the Trans Bent Structure of A =A (A =C, Si,..., Pb) Double Bond, from Dimetallene A 2 H 4 to Nanosystems

The trans-bent structure of the A =A (A of 14 th group elements) double bond neighbourhood is reinvestigated at a high level of theory. The hyperconjugation phenomenon is rationalised on going from C to Pb in dimetallene A 2R4 systems. This phenomenon also exhibits conjugated behaviour in larger systems having conjugated double bonds like congeners of polyenes, graphene, and fullerene. Behind this phenomenon is the electronic delocalisation from occupied orbitals σ, π and LP to virtual ones π*, σ* and LP* respectively. In this study we have meticulously analysed the geometrical and electronic structures by performing optimisation at high level of computation like B3LYP/6-311 + G(3df,2p) and B3LYP/LANL2DZ and electronic distribution NBO model.

Large gallanes and the PSEPT theory: a theoretical study of Ga n H n+2 clusters (n = 7–9)

AbstractDo alanes AlnHn+2 and gallanes GanHn+2 satisfy the polyhedral skeletal electron pair theory (PSEPT)? Taking into account previous work on this question, this paper provides a convincing answer and proposes the reformulation of the (n + 1) electron pairs rule of Wade and Mingos (W–M) for such systems. Following recent studies of tetra-, penta-, hexa-, hepta-, octa-, and nonaalanes as well as valence-isoelectronic/related gallanes, in this paper we present an analysis of the hydrides of aluminum and gallium AnHn+2 (A = Al, Ga and n = 7–9). The aim is still to examine the applicability of PSEPT, especially the W–M rule, to these clusters. Exploration of the total potential energy surfaces (PESs) of hepta-, octa-, and nonagallanes shows that the absolute minima have a nido-like polyhedron arrangement. Unlike the smaller GanHn+2 (n = 4, 5, 6), it seems that the size of the cluster largely dictates its preferred geometry. Although none of them have closed (totally triangular) cages, these clusters exhibit significant compactness, comparable to borane double anions, BnHn2−, which are the archetypes for the PSEPT theory. FigureGnHn+2 the structural deviation between (n + 1) electron pairs rule (PSEPT) prediction and energetical stability

Theoretical study of the stereochemistry of crotylmagnesium chloride's addition on a series of cyclic and acyclic enones

Abstract Semi-empirical methods AM1 and PM3 have been used to study the stereochemistry of the addition reaction of crotylmagnesium chloride on a series of cyclic and acyclic enones. The mechanism of this reaction has been studied by localizing the different possible transition states. The stereochemistry of the diastereoisomers obtained can be explained by comparison of the values of the energy of activation. We show in this paper that the major diastereoisomer for acyclic enones is formed via a boat-shaped transition state where the magnesium reacts with the trans conformation. Whereas for cyclic enones such as pulegone or methyl pulegone, a chair transition state where the magnesium adopts a cis conformation explains the final stereochemistry. Moreover, we demonstrate that the stereoselectivity depends of both steric and electronic factors.

Molecular modeling: Application of Support Vector Machines and Decision trees for anti-HIV activity prediction of organic compounds

Multivariate methods of pattern recognition, classification and discriminant analysis have been found most useful in many types of chemical and biological problems. Predicting the biological activity of molecules from their chemical structures is a principal problem in drug discovery. Pattern recognition has gained attention as methods covering this need. In the present study classification models for inhibiting Human Immunodeficiency Virus (HIV) activity, based on Support Vector Machines (SVM) and Decision trees (DT), are developed. The obtained results indicate that SVM and DT can be employed as a forceful tool for quantitative structure-activity relationship studies.

Pattern recognition: Application of Support Vector Machines, Artificial Neural Networks and Decision Trees for anti-HIV activity prediction of organic compounds

Predicting the biological activity of molecules from their chemical structures is a principal problem in drug discovery. Pattern recognition has gained attention as methods covering this need. In this study three classification models for anti-HIV activity, based on pattern recognition methods such as Support Vector Machines, Artificial Neural Networks and Decision Trees, are developed. All models give good results in learning and prediction phases. These results indicate that these models can be used as an alternative tool for classification problems in structure anti-HIV activity relationship.