QSAR Studies and Structure Property/Activity Relationships Applied in Pyrazine Derivatives as Antiproliferative Agents Against the BGC823

Electronic structures, the effect of the substitution, structure physicochemical property/activity relationships and drug-likeness applied in pyrazine derivatives, have been studied at ab initio (HF, MP2) and B3LYP/DFT (density functional theory) levels. In the paper, the calculated values, i.e., NBO (natural bond orbitals) charges, bond lengths, dipole moments, electron affinities, heats of formation and quantitative structure-activity relationships (QSAR) properties are presented. For the QSAR studies, we used multiple linear regression (MLR) and artificial neural network (ANN) tatistical modeling. The results show a high correlation between experimental and predicted activity values, indicating the validation and the good quality of the derived QSAR models. In addition, statistical analysis reveals that the ANN technique with (9-4-1) architecture is more significant than the MLR model. The virtual screening based on the molecular similarity method and applicability domain of QSAR allowed the discovery of novel anti-proliferative activity candidates with improved activity.

ANÁLISE CONFORMACIONAL DE COMPOSTOS DE BIGINELLI COM ATIVIDADE ANTINEOPLÁSICA

Dihydropyrimidinones, such as monastrol and analogues, are heterocycles with known antineoplastic activity. Conformational analysis represents an important preliminary step in structure-activity correlation studies. Herein we describe the conformational analysis of monastrol and analogues by AM1 semiempirical and ab initio HF/6-31G* calculations. Four equilibrium geometries were found (s-cis/ap, s-cis/sp, strans/ap and s-trans/sp), and the important internal rotations were those of the ab-unsaturated carbonyl system and of the aryl group connected to the heterocycle

Molecular Modeling of An Analog Of Curcumin Compounds Pentagamavunon-0 (PGV-0) And Pentagamavunon-1 (PGV-1) Through Computational Chemistry Methods Ab-Initio HF/4-31G

Breast cancer is the second largest number of cancer cases in Indonesia, after cervical cancer. The growth of these cancer cells can be prevented with compounds Pentagamavunon-0 (PGV-0) and Pentagamavunon-1 (PGV-1). This compound is an analog of curcumin compounds that have anti breast cancer activity. Modeling the structure of compound PGV-0 and PGV-1 through computational chemistry methods Ab-initio HF/4-31G could be used to predict the geometry and structure elucidation spectra associated with pharmacological activity such as anticancer compounds theoretically.This research involves modeling the structures and spectra prediction calculation compounds PGV-0 and PGV-1 by computational chemistry methods Ab-initio HF/4-31G, using Gaussian03W. The result using Ab-initio HF/4-31G method then compared with data from experimental geometry and the results of calculations with AM1.The results showed that computational chemistry methods Ab-initio HF/4-31G calculations give better results for modeling the structure compared semiempirik method AM1.