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Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to spread globally, with more than 172 million confirmed cases and 3.57 million deaths. Cyclic sulfonamide derivative was identified as a successful compound and showed anti-SARS-CoV-2 activity. In this study, the structure and activity relationships of 35 cyclic sulfonamide compound inhibitors were investigated by using three-dimensional quantitative structure-activity relationship (3D-QSAR) and holographic quantitative structure-activity relationship (HQSAR).Two models with good statistical parameters and reliable predictive ability were obtained from the same training set, including Topomer CoMFA (q2= 0.623,r2= 0.938,rpred2= 0.893) model and HQSAR (q2= 0.704,r2= 0.958,rpred2=0.779) model, the established models not only have good stability, but also show good external prediction ability for the test set. The contour and color code maps of the models provide a lot of useful information for determining the structural requirements affecting the activity; this information paved the way for the design of four novel cyclic sulfonamide compounds, and predicted their pIC50 values. We explore the interaction between the newly designed molecule and SARS-CoV-2 3CLpro by molecular docking. The docking results showed that GLU166, GLN192, ALA194, and VAL186 may be the potential active residues of the SARS-CoV-2 inhibitor evaluated in this study. Finally, the oral bioavailability and toxicity of the newly designed cyclic sulfonamide compounds were evaluated and the results showed that the four newly designed cyclic sulfonamide compounds have major ADMET properties and can be used as reliable inhibitors against COVID-19. These results may provide useful insights for the design of effective SARS-CoV-2 inhibitors., Graphical abstract Image, graphical abstract

Serine/threonine protein kinase B (PknB) is essential to Mycobacterium tuberculosis (M. tuberculosis) cell division and metabolism and a potential anti-tuberculosis drug target. Here we apply Hologram Quantitative Structure Activity Relationship (HQSAR) and three-dimensional QSAR (Comparative Molecular Similarity Indices Analysis (CoMSIA)) methods to investigate structural requirements for PknB inhibition by a series of previously described quinazoline derivatives. PknB binding of quinazolines was evaluated by molecular dynamics (MD) simulations of the catalytic domain and binding energies calculated by Molecular Mechanics/Poisson Boltzmann Surface Area (MM-PBSA) and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) methods. Evaluation of a training set against experimental data showed both HQSAR and CoMSIA models to reliably predict quinazoline binding to PknB, and identified the quinazoline core and overall hydrophobicity as the major contributors to affinity. Calculated binding energies also agreed with experiment, and MD simulations identified hydrogen bonds to Glu93 and Val95, and hydrophobic interactions with Gly18, Phe19, Gly20, Val25, Thr99 and Met155, as crucial to PknB binding. Based on these results, additional quinazolines were designed and evaluated in silico, with HQSAR and CoMSIA models identifying sixteen compounds, with predicted PknB binding superior to the template, whose activity spectra and physicochemical, pharmacokinetic, and anti-M. tuberculosis properties were assessed. Compound, D060, bearing additional ortho- and meta-methyl groups on its R2 substituent, was superior to template regarding PknB inhibition and % caseum fraction unbound, and equivalent in other aspects, although predictions identified hepatotoxicity as a likely issue with the quinazoline series. These data provide a structural basis for rational design of quinazoline derivatives with more potent PknB inhibitory activity as candidate anti-tuberculosis agents.

Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CLpro inhibitory property were taken into consideration for building different internally and externally validated linear (SW-MLR and GA-MLR), non-linear (ANN and SVM) QSAR, and HQSAR models to identify important structural and physicochemical characters required for SARS-CoV-2 3CLpro inhibition. Importantly, 2-oxopyrrolidinyl methyl and benzylester functions, and methylene (hydroxy) sulphonic acid warhead group, were crucial for retaining higher SARS-CoV-2 3CLpro inhibition. These GA-MLR and HQSAR models were also applied to predict some already repurposed drugs. As per the GA-MLR model, curcumin, ribavirin, saquinavir, sepimostat, and remdesivir were found to be the potent ones, whereas according to the HQSAR model, lurasidone, saquinavir, lopinavir, elbasvir, and paritaprevir were the highly effective SARS-CoV-2 3CLpro inhibitors. The binding modes of those repurposed drugs were also justified by the molecular docking, molecular dynamics (MD) simulation, and binding energy calculations conducted by several groups of researchers. This current work, therefore, may be able to find out important structural parameters to accelerate the COVID-19 drug discovery processes in the future., Graphical Abstract Graphical Abstract Image, graphical abstract.

CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico FAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Outra Agência Aproximadamente três bilhões de pessoas vivem em regiões com risco de infecção por Dengue virus (DENV), Zika virus (ZIKV) e Yellow fever virus (YFV). Além dos casos graves de dengue, Zika exibe complicações como síndromes congênitas em fetos. Ademais, surtos de febre amarela ocorreram no Brasil em 2017, mesmo havendo vacina contra este vírus. Até o momento não há fármacos antivirais aprovados para o tratamento dessas doenças, ressaltando a necessidade de estratégias para se obter novas moléculas com atividade antiviral. Portanto, o objetivo deste trabalho foi avaliar, empregando estratégias in silico e in vitro, a atividade antiviral de substâncias em DENV, ZIKV e YFV, tendo como alvo a protease viral (NS3PRO). Estruturas tridimensionais de compostos peptideomiméticos inibidores de protease de DENV-3 foram empregadas para a geração de modelos da relação quantitativa entre a estrutura química e a atividade biológica por holograma (HQSAR) e de acoplamento molecular (docking). Paralelamente, foram preditos sítios de ligação e hotspots de ligação das proteases alvo (PDB: 3U1I e 5YOF) utilizando programas FTSite, FTMap e AutoGrid. Esses resultados foram utilizados na construção de um modelo farmacofórico para triagem virtual. Propriedades físico-químicas, presença de fragmentos estruturais e características de interações com o alvo molecular (farmacóforo) foram delimitadas na triagem. Foi realizada dinâmica molecular dos hits virtuais, bem como predições de toxicidade e atividade biológica, selecionando oito substâncias para aquisição. A validação da atividade biológica foi corroborada empregando o teste colorimétrico de brometo de 3-(4,5-dimetiltiazol-2-il)-2,5-difeniltetrazólio (MTT), determinando as concentrações citotóxicas (CC50), concentrações efetivas (CE50) e índices de seletividade (IS). A atividade antiviral também foi avaliada por ensaios de placas de lise, efeito de pré-tratamento e de atividade virucida das substâncias. Inicialmente, modelos de HQSAR foram construídos e validados, sendo um modelo ótimo (q2 = 0.675 e r2 = 0.873) selecionado utilizando mapas de contribuição dos fragmentos moleculares. Na estrutura da protease foi delimitada a tríade catalítica, ligantes, sítios e subsítios, sendo utilizados na construção de um modelo farmacofórico baseado no mapeamento, interpretação do modelo de HQSAR e interações observadas em estudos prévios de docking. Uma triagem virtual de aproximadamente 7.600.000 compostos foi conduzida em diversas etapas (farmacóforo, docking e dinâmica molecular), identificando oito potenciais inibidores da protease de DENV-3 (dois fármacos e seis moléculas sintéticas sob investigação). Na dinâmica molecular foram observadas interações estáveis no sítio alvo, complementadas por predições de atividade (5/8) e toxicidade favoráveis (8/8). Dentre as substâncias, uma foi ativa em ZIKV (CE50 = 11,86 ± 0,43 μM; IS = 1,42), quatro em YFV (CE50 = 4,79 ± 0,17 a 24,15 ± 1,15 μM; IS = 1,97 a 3,74), duas em DENV-2 (CE50 = 4,21 ± 0,14 e 9,51 ± 0,12 μM; IS = 2,26 e 3,16) e uma em DENV-3 (CE50 = 37,51 ± 0,8 μM; IS = 2,85). Nos ensaios de placa, as substâncias 136 e 128 reduziram cerca de 1 a 1,5 log10 do título viral (UFP/mL) de ZIKV, YFV e DENV-2. As substâncias 136 e 140 também reduziram cerca de 1 log10 do título viral de YFV nos ensaios de pré-tratamento. Posteriormente, ensaios de inibição enzimática serão realizados para confirmação do alvo planejado neste trabalho. Approximately three billion people live in regions at risk of infection by the dengue virus (DENV), Zika virus (ZIKV) and yellow fever virus (YFV). In addition to severe cases of dengue, Zika presents complications such as congenital syndromes in fetuses. Yellow fever outbreaks also happened in Brazil in 2017, even with a vaccine available against it. Currently, there are no licensed antivirals for the treatment of these diseases, emphasizing the need for strategies to obtain new bioactive molecules with antiviral activity. The objective of this work was to evaluate, through in vitro and in silico strategies, the antiviral activity of substances against DENV, ZIKV and YFV, targeting the viral protease (NS3PRO). Three-dimensional structures of peptidomimetic compounds inhibiting DENV-3 protease were used to generate models of the quantitative relationship between chemical structure and biological activity by holograms (HQSAR) and molecular docking. Binding sites and hotspots of protein structures (PDB: 3U1I and 5YOF) were detected using the FTSite, FTMap and AutoGrid programs. These results were used to the construction of a pharmacophoric model for virtual screening. Physical and chemical properties, presence molecular fragments and interactions with the molecular target (pharmacophore) were defined in the screening. Eight compounds were selected after molecular dynamics, as well as predictions of toxicity and biological activity. Biological activity was confirmed by the colorimetric assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), in order to obtain the cytotoxic (CC50) and effective (EC50) concentrations, as well as selectivity indixes (SI). The antiviral activity was also evaluated by plaque reduction, pre-treatment and virucide activity assays. Initially, HQSAR models were built and validated, with an optimal model (q2 = 0.675 and r2 = 0.873) selected using chemical contribution maps of molecular fragments. The catalytic triad, ligands and biding sites pointed at the structures were used to build a pharmacophoric model based on mapping, interpretation of the HQSAR model and interactions observed in previous fitting studies. A virtual screening of approximately 7,600,000 compounds was conducted in several stages (pharmacophore, docking and molecular dynamics), identifying eight potential inhibitors to the DENV-3 protease (two drugs and six synthetic molecules under investigation). Molecular dynamics simulations showed stable interactions at the target sites, and were complemented by favorable biological activity (5/8) and toxicity (8/8) predictions. Among the substances, one was active against ZIKV (EC50 = 11.86 ± 0.43 μM; IS = 1.42), four against YFV (EC50 = 4.79 ± 0.17 to 24.15 ± 1.15 μM; IS = 1.97 to 3.74), two against DENV- 2 (EC50 = 4.21 ± 0.14 and 9.51 ± 0.12 μM; 2.26 and 3.16) and one against DENV-3 (EC50 = 37.51 ± 0.8 μM; IS = 2.85). In plaque reduction assays, substances 136 and 128 reduced about 1.0 to 1.5 log10 of the viral titer (PFU/mL) of ZIKV, YFV and DENV-2. Substances 136 and 140 also reduced about 1.0 log10 of YFV titer in pre-treatment assays. As a perspective, enzyme inhibition assays will be carried out in order to confirm the molecular target predicted in this work.

Mycobacterium tuberculosis DNA gyrase subunit B (GyrB) has been identified as a promising target for rational drug design against fluoroquinolone drug-resistant tuberculosis. In this study, we attempted to identify the key structural feature for highly potent GyrB inhibitors through 2D-QSAR using HQSAR, 3D-QSAR using CoMSIA and molecular dynamics (MD) simulations approaches on a series of thiazole urea core derivatives. The best HQSAR and CoMSIA models based on IC50 and MIC displayed the structural basis required for good activity against both GyrB enzyme and mycobacterial cell. MD simulations and binding free energy analysis using MM-GBSA and waterswap calculations revealed that the urea core of inhibitors has the strongest interaction with Asp79 via hydrogen bond interactions. In addition, cation-pi interaction and hydrophobic interactions of the R2 substituent with Arg82 and Arg141 help to enhance the binding affinity in the GyrB ATPase binding site. Thus, the present study provides crucial structural features and a structural concept for rational design of novel DNA gyrase inhibitors with improved biological activities against both enzyme and mycobacterial cell, and with good pharmacokinetic properties and drug safety profiles.

Based on the experimental data of octanol-water partition coefficients (Kow, represents bioaccumulation) for 13 polychlorinated biphenyl (PCB) congeners, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to establish 3D-QSAR models, combined with the hologram quantitative structure–activity relationship (HQSAR), the substitution sites (mono-substituted and bis-substituted) and substituent groups (electron-withdrawing hydrophobic groups) that significantly affect the octanol-water partition coefficients values of PCBs were identified, a total of 63 monosubstituted and bis-substituted were identified. Compared with using 3D-QSAR model alone, the coupling of 3D-QSAR and HQSAR models greatly increased the number of newly designed bis-substituted molecules, and the logKow reduction in newly designed bis-substituted molecules was larger than that of monosubstituted molecules. This was established to predict the Kow values of 196 additional PCBs and carry out a modification of target molecular PCB-207 to lower its Kow (biological enrichment) significantly, simultaneously maintaining the flame retardancy and insulativity after calculation by using Gaussian09. Simultaneously, molecular docking could further screen out three more environmental friendly low biological enrichment newly designed PCB-207 molecules (5-methyl-PCB-207, 5-amino-PCB-207, and 4-amino-5-ethyl-PCB-207).

Orientadora: Profa. Dra. Káthia Maria Honório Dissertação (mestrado) - Universidade Federal do ABC. Programa de Pós-Graduação em Ciência e Tecnologia/Química, Santo André, 2018. O desenvolvimento de um novo fármaco a partir de um alvo biológico é um processo que pode ser consideravelmente demorado e de alto custo. Entretanto, o uso de técnicas computacionais, conhecidas como estratégias in silico, busca tornar esse processo mais eficiente a partir de estudos teóricos entre as possíveis interações de protótipos farmacêuticos com os bio-receptores. Neste estudo, foram utilizadas técnicas computacionais baseadas na estrutura do receptor e dos ligantes a fim de avaliar as interações entre um conjunto de ligantes bioativos e os receptores da classe PPARd (que controlam o metabolismo de carboidratos e lipídios e a sensibilidade dos tecidos à insulina). O distúrbio desse metabolismo pode levar a doenças como a diabetes mellitus tipo 2 (DMT2) ou a síndrome metabólica (SM). Dentre as técnicas computacionais utilizadas, foi realizada a construção de modelos de QSAR 2D (HQSAR) e 3D (CoMFA) com valores significativos de validação interna (HQSAR: q²=0,683 e r²=0,905; CoMFA: q²=0,856 e r²=0,956) e externa (HQSAR: r²teste=0,848 e r²m=0,748; CoMFA: r²teste=0,852 e r²m=0,719). Os modelos foram testados quanto a sua capacidade preditiva e apresentaram valores em concordância com os obtidos experimentalmente (resíduos

The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four QSAR models were successfully established by CoMSIA, CoMFA, topomer CoMFA and HQSAR approaches with respective characteristic values q2 = 0.567, R2 = 0.968, ONC = 5; q2 = 0.547, R2 = 0.980, ONC = 7; q2 = 0.559, R2 = 0.921, ONC = 7 and q2 = 0.527, R2 = 0.921, ONC = 6. The predictive ability of CoMSIA with r2 = 0.991 is the best one compared with the other three approaches, such as CoMFA (r2 = 0.787), topomer CoMFA (r2 = 0.819) and HQSAR (r2 = 0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities.

This study presents the bioreduction of six β-ketoesters by whole cells of Kluyveromyces marxianus and molecular investigation of a series of 13 β-ketoesters by hologram quantitative structure-activity relationship (HQSAR) in order to relate with conversion and enantiomeric excess of β-stereogenic-hydroxyesters obtained by the same methodology. Four of these were obtained as (R)-configuration and two (S)-configuration, among them four compounds exhibited >99% enantiomeric excess. The β-ketoesters series LUMO maps showed that the β-carbon of the ketoester scaffold are exposed to undergo nucleophilic attack, suggesting a more favorable β-carbon side to enzymatic reduction based on adopted molecular conformation at the reaction moment. The HQSAR method was performed on the β-ketoesters derivatives separating them into those provided predominantly (R)- or (S)-β-hydroxyesters. The HQSAR models for both (R)- and (S)-configuration showed high predictive capacity. The HQSAR contribution maps suggest the importance of β-ketoesters scaffold as well as the substituents attached therein to asymmetric reduction, showing a possible influence of the ester group carbonyl position on the molecular conformation in the enzyme catalytic site, exposing a β-carbon side to the bioconversion to (S)- and (R)-enantiomers.

A malária é uma doença endêmica grave, causada por parasitos do gênero Plasmodium, que afeta grande parte da população, em especial nas áreas tropicais e subtropicais. Atualmente, o tratamento farmacológico faz uso de artemisinina ou de seus derivados associado a um segundo fármaco antimalárico. A escassez de novos tratamentos assim como a disseminação da resistência do parasito aos fármacos atualmente disponíveis, torna urgente a busca e descoberta de novos alvos e novos fármacos antimaláricos. A enzima deoxiuridina trifosfatase (dUTPase) de Plasmodium falciparum desempenha um papel importante na manutenção do equilíbrio entre 2’-desoxiuridina 5’-trifosfato (dUTP) e 2’-deoxitimina 5’-trifosfato (dTTP), a fim de evitar a incorporação errônea de uracila na fita do DNA. Dessa forma, a enzima dUTPase é um alvo potencial para o desenvolvimento de novos fármacos, e já foi validada para os organismos Escherichia coli, Saccharomyces cerevisiae e Mycobacterium smegmatis. Este trabalho teve como objetivo a realização de estudos quantitativos de relação entre estrutura e atividade (QSAR) para uma série de nucleosídeos β-ramificados inibidores da PfdUTPase, com a finalidade de se gerar modelos robustos e preditivos para predizer a atividade de compostos não testados e que possam auxiliar na elucidação dos requisitos estruturais importantes para a afinidade desta classe de compostos. Para isso, realizou-se a análise de holograma QSAR (HQSAR), análise comparativa de campos moleculares (CoMFA) e a análise comparativa dos índices de similaridade molecular (CoMSIA). Para os estudos de CoMFA e CoMSIA, foram testados dois métodos de cálculo de cargas parciais, o método empírico Gasteiger-Huckel e o método semi-empírico AM1-BCC. Foram também testadas três estratégias de alinhamento estrutural baseadas no ligante: máxima subestrutura comum, baseada na sobreposição de volumes moleculares, e em função da similaridade morfológica; e uma estratégia baseada nas coordenadas 3D do complexo enzima-inibidor (docking molecular). Os modelos de QSAR gerados apresentaram boa robustez e preditividade externa, demostrando bom poder de correlação e predição da afinidade. Os mapas de contribuição de HQSAR e os mapas de contorno do CoMFA e CoMSIA indicaram a importância de determinados grupos para a afinidade, como por exemplo, a importância da presença de ao menos dois anéis tritila que contribuem tanto estericamente como hidrofobicamente para interação com o sítio hidrofóbico da enzima do parasito, inexistente na enzima de humanos. O planejamento de fármacos baseado nas informações obtidas do QSAR 2D e 3D, gerou 121 moléculas agrupadas em 18 clusters. Dois hits com potência aproximada a um dos compostos mais ativos da série se destacaram por apresentar propriedades físico-químicas apropriadas. Malaria is a serious endemic disease caused by parasites of the genus Plasmodium, which affects much of the population, especially in tropical and subtropical areas. Currently, drug therapy makes use of artemisinin or its derivatives associated with a second anti-malarial drug. The shortage of new treatments as well as the spread of parasite resistance to drugs currently available, makes urgent the search and discovery of new targets and new antimalarial drugs. The enzyme deoxyuridine triphosphatase (dUTPase) of Plasmodium falciparum plays an important role in maintaining balance between 2'-deoxyuridine 5'-triphosphate (dUTP) and 2'- deoxitimina 5'-triphosphate (dTTP) in order to avoid the erroneous incorporation uracil on the DNA tape. Thus, the enzyme dUTPase is a potential target for the development of new drugs, and has been validated for the organisms Escherichia coli, Saccharomyces cerevisiae and Mycobacterium smegmatis. This study aimed to carry out quantitative studies of the relationship between structure and activity (QSAR) to a series of β-branched nucleoside inhibitors PfdUTPase, in order to generate robust and predictive models to predict compounds activity untested and that may help to elucidate the important structural requirements for the affinity of this class of compounds. For this, there was the hologram QSAR analysis (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). For studies of CoMFA and CoMSIA were tested two methods of calculation of partial charges, the empirical method Gasteiger-Huckel and the semi-empirical method AM1-BCC. Were also tested three structural alignment strategies based on the binder: maximum common substructure, based on the overlap of molecular volumes, and on the basis of morphological similarities; and a strategy based on the 3D coordinates of the enzymeinhibitor complex (molecular docking). The QSAR models generated showed good robustness and external predictability, showing good power correlation and prediction of affinity. The HQSAR contribution maps and contour maps of the CoMFA and CoMSIA indicated the importance of certain groups for affinity, such as the importance of the presence of at least two of trityl rings that contribute both sterically as hydrophobically to interact with the hydrophobic site of the parasite enzyme, non-existent in the human enzyme. The drug design based on information obtained from 2D and 3D QSAR, generated 121 molecules grouped into 18 clusters. Two hits with approximate power to one of the most active compounds of the series stood out by presenting appropriate physicochemical properties.

Dual specificity tyrosine-phosphorylation-regulated kinase-1A (DYRK1A) is an enzyme directly involved in Alzheimer’s disease, since its increased expression leads to β-amyloidosis, Tau protein aggregation, and subsequent formation of neurofibrillary tangles. Hologram quantitative structure-activity relationship (HQSAR, 2D fragment-based) models were developed for a series of 6-arylquinazolin-4-amine inhibitors (36 training, 10 test) of DYRK1A. The best HQSAR model (q2 = 0.757, SEcv = 0.493, R2 = 0.937, SE = 0.251, R2pred = 0.659) presents high goodness-of-fit (R2 &gt, 0.9), as well as high internal (q2 &gt, 0.7) and external (R2pred &gt, 0.5) predictive power. The fragments that increase and decrease the biological activity values were addressed using the colored atomic contribution maps provided by the method. The HQSAR contribution map of the best model is an important tool to understand the activity profiles of new derivatives and may provide information for further design of novel DYRK1A inhibitors.

A esquistossomose é uma doença tropical negligenciada (DTN) que afeta grande número de indivíduos, principalmente em áreas tropicais. Esta doença é causada por vermes platelmintos do gênero Schistosoma, que possuem como hospedeiros intermediários os caramujos do gênero Biomphalaria. O fármaco mais utilizado no tratamento atualmente é o praziquantel, que devido à grande disseminação do seu uso, traz preocupações quanto ao desenvolvimento de resistência. A enzima tioredoxina glutationa redutase de Schistosoma mansoni (SmTGR) desempenha um papel importante na detoxificação de espécies reativas de oxigênio (ROS), permitindo a sobrevivência dos parasitos por muito tempo na circulação sanguínea, protegendo-os do sistema imune do hospedeiro. A dependência do parasito de um único sistema para detoxificação de ROS, torna a SmTGR um alvo promissor no desenvolvimento de novos fármacos esquistossomicidas. Frente à necessidade de se desenvolver novos fármacos contra esquistossomose, foram realizados estudos quantitativos da relação entre estrutura e atividade (QSAR) para uma série de oxadiazóis-2-óxidos reportados na literatura como inibidores de SmTGR. Foi realizada análise de holograma-QSAR (HQSAR), que é um método de QSAR bidimensional (QSAR-2D). Além disso, foram utilizadas a análise comparativa de campos moleculares (CoMFA) e a análise comparativa dos índices de similaridade molecular (CoMSIA), que são métodos de QSAR tridimensional (QSAR-3D). Nos métodos de QSAR-3D foram utilizados dois métodos de cálculo de cargas parciais: o método empírico Gasteiger-Hückel e o semi-empírico AM1-BCC. Foram também testadas duas estratégias de alinhamento, uma baseada na sobreposição de volumes moleculares e outra baseada em uma função de similaridade morfológica. Os modelos de QSAR gerados demonstraram boa robustez e preditividade externa e foram usados para predição da atividade biológica de novos compostos inibidores de SmTGR. Os mapas de contribuição e de contorno obtidos forneceram informações estruturais importantes a respeito dos oxadizóis-2-óxidos, que foram utilizadas no planejamento de novos inibidores da SmTGR. Schistosomiasis is a neglected tropical disease (NTD) that affects many individuals, mainly in tropical areas. This disease is caused by blood flukes of the genus Schistosoma, which have the snails of the genus Biomphalaria as their intermediate hosts. The most used drug in schistosomiasis treatment is praziquantel, which because of its widespread use, brings concerns about the development of resistance. The enzyme Thioredoxin Glutathione Reductase of Schistosoma mansoni (SmTGR) has an important function in reactive oxygen species (ROS) detoxification, allowing the survival of parasites for a very long time in blood stream, protecting them against the host immune system. The dependence of the parasite on a single system for ROS detoxification, makes the SmTGR a promissing target in the development of new schistosomicidal drugs. Facing the need for development of new drugs against schistosomiasis, quantitative structure activity relationships (QSAR) studies were carried out for a series of oxadiazoles-2-oxides reported in literature as SmTGR inhibitors. Hologram-QSAR (HQSAR) analysis, a two-dimensional QSAR method (2D-QSAR), was performed. Furthermore comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA), that are three-dimensional QSAR (3D-QSAR), were also carried out. In 3D-QSAR methods, two partial charge calculation methods were used: the empirical method Gasteiger-Hückel and the semiempirical method AM1-BCC. Two alignment strategies were also tested, one based on molecular volume superposition and the other based on a morphological similarity function. The QSAR models generated showed great robustness and external predictivity and can be used to predict the biological activity of new compounds inhibitors of SmTGR. The contribution and contour maps showed important structural information about oxadiazoles-2-oxides that was used for the design of new SmTGR inhibitors.

Over the last decades fungal infections have become an increasing health problem, especially for immunocompromised patients. Unfortunately, the gold standard prophylactic therapy for such ailment is based on azole derivatives, which are fungistatic rather than fungicidal against C. neoformans and cause hepatotoxicity. Aiming at circumvent these problems, non-azole CYP51 inhibitors were designed. Herein a comprehensive structure-activity relationships study was carried out for a dataset of 110 molecules by means of hologram- and descriptor-based QSAR studies. The best descriptor-based QSAR model (r² = 0.92, q² = 0.90, 6 LVs and r²pred =0.86) suggests that resonance effects (ESpm08r) play a major role for antifungal activity. The hologram-based QSAR (r² = 0.87, q² = 0.81, 6 LVs and r²pred = 0.84) supports this hypothesis and hints at steric properties that should also contribute to non-azole inhibitors potency. The insights provided by the integrated analysis of QSAR models, along with their good predictive power prove their usefulness to future drug design efforts. Durante as últimas décadas as infecções fúngicas têm se tornado um crescente problema de saúde, especialmente para pacientes imunocomprometidos. Infelizmente, o padrão-ouro de terapia profilática para tal doença é baseada em derivados azólicos, que são mais fungistáticos do que fungicidas contra C. neoformans e causam hepatotoxicidade. Objetivando contornar estes problemas, inibidores não-azólicos de CYP51 foram planejados. Aqui, um abrangente estudo de relação estrutura-atividade foi executado para uma série de 110 moléculas através de um estudo de QSAR baseado em hologramas e descritores moleculares. O melhor modelo de QSAR baseado em descritores (r² = 0,92, q² = 0,90, 6 LVs e r²pred =0,86) sugere que o efeito de ressonância (ESpm08r) desempenha um papel principal para a atividade antifúngica. O modelo de QSAR baseado em hologramas (r² = 0,87, q² = 0,81, 6 LVs e r²pred = 0,84) sustenta esta hipótese. Estas percepções obtidas pelas análises integradas dos modelos de QSAR, juntamente com o bom poder preditivo comprovam sua utilidade para futuros esforços em planejamento de fármacos.

Uiaran de Oliveira Magalhães,1 Alessandra Mendonça Teles de Souza,1 Magaly Girão Albuquerque,2 Monique Araújo de Brito,3 Murilo Lamim Bello,1 Lucio Mendes Cabral,4 Carlos Rangel Rodrigues1 1Universidade Federal do Rio de Janeiro (UFRJ), Faculdade de Farmácia, Laboratório de Modelagem Molecular and QSAR (ModMolQSAR), Rio de Janeiro, RJ, Brazil; 2Universidade Federal do Rio de Janeiro (UFRJ), Instituto de Química, Laboratório de Modelagem Molecular (LabMMol), Rio de Janeiro, RJ, Brazil; 3Universidade Federal Fluminense (UFF), Faculdade de Farmácia, Laboratório de Química Medicinal Computacional (LabQMC), Niterói, RJ, Brazil; 4Universidade Federal do Rio de Janeiro (UFRJ), Faculdade de Farmácia, Laboratório de Tecnologia Farmacêutica Industrial (LabTIF), Rio de Janeiro, RJ, Brazil Abstract: Acquired immunodeficiency syndrome is a public health problem worldwide caused by the Human immunodeficiency virus (HIV). Treatment with antiretroviral drugs is the best option for viral suppression, reducing morbidity and mortality. However, viral resistance in HIV-1 therapy has been reported. HIV-1 integrase (IN) is an essential enzyme for effective viral replication and an attractive target for the development of new inhibitors. In the study reported here, two- and three-dimensional quantitative structure–activity relationship (2D/3D-QSAR) studies, applying hologram quantitative structure–activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) methods, respectively, were performed on a series of tricyclic phthalimide HIV-1 IN inhibitors. The best HQSAR model (q2 = 0.802, r2 = 0.972) was obtained using atoms, bonds, and connectivity as the fragment distinction, a fragment size of 2–5 atoms, hologram length of 61 bins, and six components. The best CoMFA model (q2 = 0.748, r2 = 0.974) was obtained with alignment of all atoms of the tricyclic phthalimide moiety (alignment II). The HQSAR contribution map identified that the carbonyl-hydroxy-aromatic nitrogen motif made a positive contribution to the activity of the compounds. Furthermore, CoMFA contour maps suggested that bulky groups in meta and para positions in the phenyl ring would increase the biological activity of this class. The conclusions of this work may lead to a better understanding of HIV-1 IN inhibition and contribute to the design of new and more potent derivatives. Keywords: 3D-QSAR, AIDS, CoMFA, HQSAR, 2D/3D-QSAR

Despite advances in the development of antifungal drugs, there has been an upsurge of cryptococosis infections that poorly respond to fluconazole (first choice drug). Hence, it is paramount to investigate the chemical properties of azole derivatives that are active against resistant C. neoformans. In order to achieve this goal, the susceptibility profile of a clinical isolate of resistant C. neoformans against 33 commercial azole derivatives was evaluated along with their potency (minimum inhibitory concentration, MIC). These data were employed to build SIMCA (soft independent modeling of class analogies) models that pinpoint the importance of electronic features (JGI10) to separate active from inactive compounds and hologram-QSAR models that have good fit but insufficient predictive power (HQSAR, r² = 0.85, q² = 0.35 and r²pred = 0.38). Conversely, 2D QSAR models built from topological descriptors improved the statistical quality (r² = 0.95, q² = 0.86, r²pred = 0.72) and highlight that charge distribution (GGI1) and topological electronegativity (GATS1e and MATS2e) should be modulated to overcome the C. neoformans resistance. Apesar dos avanços no desenvolvimento de antifúngicos, tem ocorrido um aumento de casos de criptococose que não respondem de forma adequada a fluconazol (fármaco de primeira escolha). Portanto, é de suma importância investigar as propriedades químicas de derivados azólicos que sejam ativos contra cepas de Cryptococcus neoformans resistentes a fluconazol. Visando alcançar esse objetivo, o perfil de suscetibilidade de um isolado clínico de C. neoformans resistente contra 33 derivados azólicos comerciais foi avaliado junto com as suas respectivas concentrações inibitórias mínimas (MIC). Esses dados foram utilizados para construir modelos SIMCA (modelagem independente flexível por analogias de classes) que destacam a importância de propriedades eletrônicas (JGI10) para separar as moléculas ativas das inativas e para construir modelos de holograma-QSAR que apresentam bom ajuste, mas capacidade preditiva baixa (HQSAR, r² = 0.85, q² = 0.35 e r²pred = 0.38). Por outro lado, modelos de QSAR 2D desenvolvidos a partir de descritores topológicos apresentaramm boa qualidade estatística (r² = 0.95, q² = 0.86, r²pred = 0.72) e destacam que a distribuição de cargas (GGI1) e a eletronegatividade topológica (GATS1e e MATS2e) devem ser modulados para contornar a resistência de C. neoformans.

A tuberculose (TB) é uma doença infecto-contagiosa crônica com altas taxas epidemiológicas. O surgimento de cepas multi- e extensivamente resistentes aos fármacos utilizados bem como os efeitos adversos e a longa duração do tratamento tornam urgente o desenvolvimento de novas opções terapêuticas. A enzima timidina monofosfato quinase de Mycobacterium tuberculosis (TMPKmt) é essencial para a síntese de DNA e replicação celular. Além disso, esta enzima possui características estruturais únicas na família de TMPKs, sendo um alvo potencial para o planejamento racional de novos agentes anti-TB. O presente trabalho objetivou a aplicação de estratégias de planejamento de fármacos auxiliado por computador (CADD), utilizando um conjunto de 109 análogos de timidina inibidores de TMPKmt selecionados da literatura, buscando-se elucidar os requisitos estruturais relevantes à atividade biológica dessa classe de compostos e gerar modelos capazes de prever a atividade de compostos ainda não testados. Utilizou-se metodologias de QSAR-2D (HQSAR), QSAR-3D (CoMFA e CoMSIA), docking QM/MM e substituição bioisostérica de fragmentos para a proposição de novos inibidores da TMPKmt. Os modelos finais de HQSAR, CoMFA e CoMSIA possuem elevada consistência interna e externa, apresentando bom poder de correlação e predição da atividade biológica. Os mapas de contribuição de HQSAR e os mapas de contorno de CoMFA e CoMSIA forneceram informações importantes sobre características estruturais relacionadas à afinidade, tais como a presença de substituintes hidrofóbicos e pouco volumosos no anel timina favorecerem a atividade, assim como a presença de grupos volumosos e com alta densidade eletrônica, hidrofílicos e aceptores de ligação de hidrogênio no grupo sulfona do anel naftosutâmico. Utilizando-se as informações obtidas, planejou-se nove novos compostos como possíveis inibidores de TMPKmt, que apresentaram afinidade e propriedades físico-químicas otimizadas. Estudos de docking evidenciaram que os dois hits mais potentes apresentam interações no sítio ativo da TMPKmt capazes de desestabilizar o processo catalítico entre a enzima e o substrato natural, indicando que os compostos propostos são potenciais inibidores da TMPKmt. Tuberculosis (TB) is a chronic infectious and contagious disease with high epidemiological rates. The rise of multi- and extensively drug-resistant strains as well as the side effects and the long term treatment become urgent the development of novel therapy options. The enzyme thymidine monophosphate kinase of Mycobacterium tuberculosis (TMPKmt) is essential to DNA synthesis and cell replication. Moreover, this enzyme has unique structural characteristics among TMPKs family, emerging as a potential target to rational design of novel anti-TB agents. The present work had as objective the application of Computer Aided Drug-Design (CADD) strategies, using a set of 109 thymidine analogues inhibitors of TMPKmt selected from the literature, aiming to elucidate the structural features relevant to the biological activity of this set of compounds and generate models able to predict the activity of untested compounds. Methodologies of 2D-QSAR (HQSAR), 3-D-QSAR (CoMFA and CoMSIA), QM/MM docking and bioisosteric fragment replacement were performed for proposing new TMPKmt inhibitors. The final models of HQSAR, CoMFA and CoMSIA exhibit good internal and external consistency, presenting good correlation ability and prediction of biological activity. The HQSAR contribution maps and the contour maps of CoMFA and CoMSIA provided important information about structural features related to affinity, such as the favorable presence of hydrophobic and less bulky substituents on thymine ring and more bulky, electronegative, hydrophilic and hydrogen acceptors on sulfone of naphtosultam ring. Gathering the information provided, it was planned nine new compounds as potential TMPKmt inhibitors, which showed optimized affinity and physicochemical properties. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES

p. 962-972 Submitted by Suelen Reis (suziy.ellen@gmail.com) on 2014-05-15T13:12:49Z No. of bitstreams: 1 10.5935-0103-5053.20130122.pdf: 644229 bytes, checksum: 918cbc6eec05cca63351e93046d421a8 (MD5) Approved for entry into archive by Rodrigo Meirelles (rodrigomei@ufba.br) on 2014-10-10T15:09:31Z (GMT) No. of bitstreams: 1 10.5935-0103-5053.20130122.pdf: 644229 bytes, checksum: 918cbc6eec05cca63351e93046d421a8 (MD5) Made available in DSpace on 2014-10-10T15:09:31Z (GMT). No. of bitstreams: 1 10.5935-0103-5053.20130122.pdf: 644229 bytes, checksum: 918cbc6eec05cca63351e93046d421a8 (MD5) Previous issue date: 2013 Despite advances in the development of antifungal drugs,there has been an upsurge of cryptococosis infections that poorly respond to fluconazole (first choice drug). Hence,it is paramount to investigate the chemical properties of azole derivatives that are active against resistant C. neoformans. In order to achieve this goal,the susceptibility profile of a clinical isolate of resistant C. neoformans against 33 commercial azole derivatives was evaluated along with their potency (minimum inhibitory concentration,MIC). These data were employed to build SIMCA (soft independent modeling of class analogies) models that pinpoint the importance of electronic features (JGI10) to separate active from inactive compounds and hologram-QSAR models that have good fit but insufficient predictive power (HQSAR,r2 = 0.85, q2 = 0.35 and r 2 pred = 0.38). Conversely, 2D QSAR models built from topological descriptors improved the statistical quality (r2 = 0.95, q2 = 0.86, r2 pred = 0.72) and highlight that charge distribution (GGI1) and topological electronegativity (GATS1e and MATS2e) should be modulated to overcome the C. neoformans resistance.