Lívia B. Salum

Structure-Based Drug Design Strategies in Medicinal Chemistry

A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the development of high quality drug candidates. Structure-based drug design (SBDD) methods are becoming increasingly powerful, versatile and more widely used. This review summarizes current developments in structure-based virtual screening and receptor-based pharmacophores, highlighting achievements as well as challenges, along with the value of structure-based lead optimization, with emphasis on recent examples of successful applications for the identification of novel active compounds.

Fragment-based QSAR: perspectives in drug design

Drug design is a process driven by innovation and technological breakthroughs involving a combination of advanced experimental and computational methods. A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the optimization of leads into drug candidates. Quantitative structure–activity relationship (QSAR) methods are among the most important strategies that can be applied for the successful design of small molecule modulators having clinical utility. Hologram QSAR (HQSAR) is a modern 2D fragment-based QSAR method that employs specialized molecular fingerprints. HQSAR can be applied to large data sets of compounds, as well as traditional-size sets, being a versatile tool in drug design. The HQSAR approach has evolved from a classical use in the generation of standard QSAR models for data correlation and prediction into advanced drug design tools for virtual screening and pharmacokinetic property prediction. This paper provides a brief perspective on the evolution and current status of HQSAR, highlighting present challenges and new opportunities in drug design.

N4-Phenyl-substituted 2-acetylpyridine thiosemicarbazones: Cytotoxicity against human tumor cells, structure–activity relationship studies and investigation on the mechanism of action

N(4)-Phenyl 2-acetylpyridine thiosemicarbazone (H2Ac4Ph; N-(phenyl)-2-(1-(pyridin-2-yl)ethylidene)hydrazinecarbothioamide) and its N(4)-ortho-, -meta- and -para-fluorophenyl (H2Ac4oFPh, H2Ac4mFPh, H2Ac4pFPh), N(4)-ortho-, -meta- and -para-chlorophenyl (H2Ac4oClPh, H2Ac4mClPh, H2Ac4pClPh), N(4)-ortho-, -meta- and -para-iodophenyl (H2Ac4oIPh, H2Ac4mIPh, H2Ac4pIPh) and N(4)-ortho-, -meta- and -para-nitrophenyl (H2Ac4oNO(2)Ph, H2Ac4mNO(2)Ph, H2Ac4pNO(2)Ph) derivatives were assayed for their cytotoxicity against human malignant breast (MCF-7) and glioma (T98G and U87) cells. The compounds were highly cytotoxic against the three cell lineages (IC(50): MCF-7, 52-0.16 nM; T98G, 140-1.0 nM; U87, 160-1.4 nM). All tested thiosemicarbazones were more cytotoxic than etoposide and did not present any haemolytic activity at up to 10(-5)M. The compounds were able to induce programmed cell death. H2Ac4pClPh partially inhibited tubulin assembly at high concentrations and induced cellular microtubule disorganization.

Role of halogen bonds in thyroid hormone receptor selectivity: pharmacophore-based 3D-QSSR studies.

Most physiological effects of thyroid hormones are mediated by the two thyroid hormone receptor subtypes, TRalpha and TRbeta. Several pharmacological effects mediated by TRbeta might be beneficial in important medical conditions such as obesity, hypercholesterolemia and diabetes, and selective TRbeta activation may elicit these effects while maintaining an acceptable safety profile. To understand the molecular determinants of affinity and subtype selectivity of TR ligands, we have successfully employed a ligand- and structure-guided pharmacophore-based approach to obtain the molecular alignment of a large series of thyromimetics. Statistically reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models were obtained using the comparative molecular field analysis (CoMFA) method, and the visual analyses of the contour maps drew attention to a number of possible opportunities for the development of analogs with improved affinity and selectivity. Furthermore, the 3D-QSSR analysis allowed the identification of a novel and previously unmentioned halogen bond, bringing new insights to the mechanism of activity and selectivity of thyromimetics.

Pharmacophore-based 3D QSAR studies on a series of high affinity 5-HT1A receptor ligands

5-HT(1A) receptor antagonists have been employed to treat depression, but the lack of structural information on this receptor hampers the design of specific and selective ligands. In this study, we have performed CoMFA studies on a training set of arylpiperazines (high affinity 5-HT(1A) receptor ligands) and to produce an effective alignment of the data set, a pharmacophore model was produced using Galahad. A statistically significant model was obtained, indicating a good internal consistency and predictive ability for untested compounds. The information gathered from our receptor-independent pharmacophore hypothesis is in good agreement with results from independent studies using different approaches. Therefore, this work provides important insights on the chemical and structural basis involved in the molecular recognition of these compounds.

Gallium(III) complexes with 2-acetylpyridine-derived thiosemicarbazones: antimicrobial and cytotoxic effects and investigation on the interactions with tubulin

Complexes [Ga(2Ac4pFPh)2]NO3 (1), [Ga(2Ac4pClPh)2]NO3 (2), [Ga(2Ac4pIPh)2]NO3 (3), [Ga(2Ac4pNO2Ph)2]NO3·3H2O (4) and [Ga(2Ac4pT)2]NO3 (5) were obtained with 2-acetylpyridine N(4)-para-fluorophenyl-(H2Ac4pFPh), 2-acetylpyridine N(4)-para-chlorophenyl-(H2Ac4pClPh), 2-acetylpyridine N(4)-para-iodophenyl-(H2Ac4pIPh), 2-acetylpyridine N(4)-para-nitrophenyl-(H2Ac4pNO2Ph) and 2-acetylpyridine N(4)-para-tolyl-(H2Ac4pT) thiosemicarbazone. 1–5 presented antimicrobial and cytotoxic properties. Coordination to gallium(III) proved to be an effective strategy for activity improvement against Pseudomonas aeruginosa and Candida albicans. The complexes were highly cytotoxic against malignant glioblastoma and breast cancer cells at nanomolar concentrations. The compounds induced morphological changes characteristic of apoptotic death in tumor cells and showed no toxicity against erythrocytes. 2 partially inhibited tubulin assembly at high concentrations and induced cellular microtubule disorganization, but this does not appear to be the main mechanism of cytotoxic activity.

Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity.

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpha (hERalpha) and beta (hERbeta). Because the levels and relative proportion of hERalpha and hERbeta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hERalpha and hERbeta. Significant statistical coefficients were obtained (hERalpha, q(2) = 0.76; hERbeta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hERalpha and hERbeta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design of novel hER modulators with improved selectivity.

Three-Dimensional Quantitative Structure-Activity Relationships for a Large Series of Potent Antitubercular Agents

Abstract: Comparative molecular field analysis (CoMFA) studies were conducted on a series of 100 isoniazid derivatives as anti-tuberculosis agents using two receptor-independent structural data set alignment strategies: (1) rigid-body fit, and (2) pharmacophore-based. Significant cross-validated correlation coefficients were obtained (CoMFA(1), q2= 0,75 and CoMFA(2), q = 0.74), indicating the potential of the models for untested compounds. The models were then used to predict the inhibitory potency of 20 test set compounds that were not included in the training set, and the predicted values were in good agreement with the experimental results.

Structural and chemical basis for anticancer activity of a series of²-tubulin ligands: molecular modeling and 3D QSAR studies

An important approach to cancer therapy is the design of small molecule modulators that interfere with microtubule dynamics through their specific binding to the ²-subunit of tubulin. In the present work, comparative molecular field analysis (CoMFA) studies were conducted on a series of discodermolide analogs with antimitotic properties. Significant correlation coefficients were obtained (CoMFA(i), q2 =0.68, r2=0.94; CoMFA(ii), q2 = 0.63, r2= 0.91), indicating the good internal and external consistency of the models generated using two independent structural alignment strategies. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the 3D contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of discodermolide analogs, and should be useful for the design of new specific ²-tubulin modulators with potent anticancer activity.

Fragment-based QSAR strategies in drug design

Recently, fragment-based drug design has been established as a crucial strategy for hit identification and lead generation, which has strongly encouraged the development of approaches to specifically recognize and evaluate molecular fragments or structural scaffolds that preferentially interact with particular sites of important biological targets. In this context, fragment-based quantitative structure–activity relationship (FB-QSAR) has emerged as a versatile tool to explore the chemical and biological space of data sets of compounds. FB-QSAR approaches have evolved from a classical use in the generation of standard QSAR models into advanced drug design tools for database mining, pharmacokinetic property prediction and optimization of multiple parameters. This paper provides a brief perspective on the evolution and current status of FB-QSAR, highlighting new opportunities in drug design.