2D QSAR studies on a series of bifonazole derivatives with antifungal activity

Abstract

Candida albicans (CA) é considerado como o principal patógeno oportunista em pacientes imunossuprimidos. A maior parte dos fármacos disponíveis para o tratamento de cepas resistentes são altamente tóxicos ou ineficazes. Uma forma de amenizar esse cenário seria através de modificações na estrutura de derivados de azóis que resultassem no aumento da potência e seletividade. Visando esclarecer quais propriedades químicas e estruturais são importantes para atividade antifúngica de derivados de azol, estudos de QSAR 2D clássico e holograma QSAR (HQSAR) foram realizados para um conjunto diverso de 52 derivados de bifonazol com atividade antifúngica. Os descritores topológicos utilizados nos estudos de QSAR 2D clássico originaram modelos com baixa consistência interna (r 2 = 0,38, q 2 = 0,27) e poder preditivo nulo (r 2 pred = −0,6). Por outro lado, a utilização de hologramas moleculares possibilitou a criação de modelos de HQSAR robustos (r 2 = 0,92, q 2 = 0,65) e com bom poder preditivo (r 2 pred = 0,79).Candida albicans (CA) has been identified as the major opportunistic pathogen in immunosuppressed patients. Most of currently available drugs are either highly toxic or becoming ineffective against resistant strains. An approach to overcome this burden relies on azole derivatives with increased potency and selectivity. Aiming at shedding some light on structural and chemical features that are important for the antifungal activity of azole derivatives, classical 2D QSAR and hologram QSAR (HQSAR) studies were performed for a diverse set of 52 bifonazole derivatives with antifungal activity. Topological descriptors, employed in Classical QSAR studies, resulted in models with low correlation (r 2 = 0.38, q 2 = 0.27) and lack of predictive power (r 2 pred = −0.6). On the other hand molecular holograms afforded HQSAR models with good correlation coefficients (r 2 = 0.92, q 2 = 0.65) and good predictive ability (r 2 pred = 0.79).

Descriptor-and fragment-based QSAR models for a series of Schistosoma mansoni purine nucleoside inhibitors

“…24,25 The synergy between descriptor-based and fragmentbased QSAR models has been a valuable approach to boost SAR studies, due to the complementary nature of these ligand-based drug design (LBDD) strategies. 26,27 Thus, our initial efforts focused on the development of QSAR models by means of topological descriptors that account for molecular size, shape and branching through graph theoretical invariants (using the DRAGON 5.5 software). Additional information regarding molecular charge and polarizability was also considered through the weighting of the descriptors.…”

Quantitative Structure-Activity Relationship Study of Ester-Based Ferulic Acid Derivatives Against Cervical Cancer Cell (Hela)

“…This consists of the similarities between molecules in a large database of existing molecules with known properties [16]. This technique has been used in various procedures for various applications such as anticancer [16][17], antibacterial [18], antifungus [19], and hormone controlling [20]. The result of the QSAR prediction model shows a high correlation with the experimental data [16,18].…”

Two-dimensional quantitative structure-activity relationship studies on bioactive ligands of peroxisome proliferator-activated receptor δ

“…With this in mind, the main objective of this study is to obtain 2D quantitative structure-activity relationships (QSAR) of a series of PPARd ligands by employing the hologram QSAR (HQSAR) method, which has been used successfully in several ligand-based studies and provided good statistical results. [12][13][14][15][16][17] It is interesting to notice that structure-and ligand-based approaches have become vital components of many modern drug design projects.…”