A esquistossomose é uma das principais causas de morbidade em países Tropicais e Subtropicais, gerando graves consequências socioeconômicas. Atualmente, os fármacos disponíveis para o tratamento da desta doença são praziquantel e oxamniquina, porém relatos de baixa susceptibilidade do parasita a esses medicamentos sugerem a necessidade de novas estratégias terapêuticas para o tratamento da doença. Todavia, existe pouco interesse da indústria farmacêutica no desenvolvimento de fármacos contra doenças tropicais e negligenciadas, entre as quais se encontra a esquistossomose. Devido a estes fatores, o presente trabalho teve por objetivo geral utilizar ferramentas computacionais para identificar inibidores da SmDHFR candidatos a novos fármacos. Avaliou-se as características exclusivas para a proteína de S. mansoni por meio de uma análise das sequências FASTA em comparação com a DHFR de outros organismos. A fim de garantir a ação seletiva dessas moléculas frente a enzima do parasita, os campos moleculares de interação seletivos para SmDHFR foram calculados e empregados na construção do modelo farmacofórico, o qual foi utilizado na triagem virtual de inibidores de SmDHFR. Os estudos computacionais realizados nos permitiram a seleção de 20 moléculas com uma boa complementariedade com o modelo farmacofórico gerado e com potencial para serem inibidores de SmDHFR. / Schistosomiasis is one of morbidity\'s main causes in tropical and subtropical countries, which leads to serious socioeconomic consequences. Praziquantel and oxamniquina are the drugs currently available for treating this disease, but reports points that the parasite has been resistant to both drugs, which suggests the need for new therapeutic strategies for the treatment of this disease. However, there is little interest in the pharmaceutical industry in developing drugs against neglected tropical diseases, including schistosomiasis. Due to these factors, the present work has the general objective to use computational tools to identify SmDHFR inhibitors which could be good candidates for developing new drugs. Evaluation of the exclusive characteristics of the S. mansoni protein were performed by FASTA sequence analyses in comparison to DHFR from other organisms. In order to guarantee the selective action of these molecules against the parasite enzyme, the molecular interaction fields selective for SmDHFR were calculated and used in the construction of the pharmacophoric model, which was further used in the virtual screening of SmDHFR inhibitors. Computational studies were performed and those led us to 20 molecules with a good complementarity with the pharmacophoric model that was previously generated and with potential to be SmDHFR inhibitors.

A esquistossomose é uma das principais causas de morbidade em países Tropicais e Subtropicais, gerando graves consequências socioeconômicas. Atualmente, os fármacos disponíveis para o tratamento da desta doença são praziquantel e oxamniquina, porém relatos de baixa susceptibilidade do parasita a esses medicamentos sugerem a necessidade de novas estratégias terapêuticas para o tratamento da doença. Todavia, existe pouco interesse da indústria farmacêutica no desenvolvimento de fármacos contra doenças tropicais e negligenciadas, entre as quais se encontra a esquistossomose. Devido a estes fatores, o presente trabalho teve por objetivo geral utilizar ferramentas computacionais para identificar inibidores da SmDHFR candidatos a novos fármacos. Avaliou-se as características exclusivas para a proteína de S. mansoni por meio de uma análise das sequências FASTA em comparação com a DHFR de outros organismos. A fim de garantir a ação seletiva dessas moléculas frente a enzima do parasita, os campos moleculares de interação seletivos para SmDHFR foram calculados e empregados na construção do modelo farmacofórico, o qual foi utilizado na triagem virtual de inibidores de SmDHFR. Os estudos computacionais realizados nos permitiram a seleção de 20 moléculas com uma boa complementariedade com o modelo farmacofórico gerado e com potencial para serem inibidores de SmDHFR. / Schistosomiasis is one of morbidity\'s main causes in tropical and subtropical countries, which leads to serious socioeconomic consequences. Praziquantel and oxamniquina are the drugs currently available for treating this disease, but reports points that the parasite has been resistant to both drugs, which suggests the need for new therapeutic strategies for the treatment of this disease. However, there is little interest in the pharmaceutical industry in developing drugs against neglected tropical diseases, including schistosomiasis. Due to these factors, the present work has the general objective to use computational tools to identify SmDHFR inhibitors which could be good candidates for developing new drugs. Evaluation of the exclusive characteristics of the S. mansoni protein were performed by FASTA sequence analyses in comparison to DHFR from other organisms. In order to guarantee the selective action of these molecules against the parasite enzyme, the molecular interaction fields selective for SmDHFR were calculated and used in the construction of the pharmacophoric model, which was further used in the virtual screening of SmDHFR inhibitors. Computational studies were performed and those led us to 20 molecules with a good complementarity with the pharmacophoric model that was previously generated and with potential to be SmDHFR inhibitors.

Introducción: La resistencia antimicrobiana es un problema alarmante en la salud pública mundial. A mediados del 2017, la Organización Mundial de la Salud (OMS) reportó una lista de las bacterias para la búsqueda de nuevos antibióticos, incluyendo sobre todo enterobacterias. En el Perú, hubo reporte de casos de Klebsiella pneumoniae resistente a antibióticos en diferentes regiones del país. Por lo tanto, existe una necesidad de encontrar nuevos sitios diana de acción farmacológica para enfrentar esta problemática sanitaria. Objetivo: Identificar las moléculas orgánicas con capacidad de inhibición de la enzima Glucosa 1-fosfato Timidilil Transferasa (RmlA) de K. pneumoniae resistente a antibióticos utilizando la técnica de acoplamiento molecular. Materiales y métodos: Se realizó un estudio in-silico, mediante programas para acoplamiento molecular por ordenador local. La semejanza de fármacos con el sustrato natural de la enzima fue dada con programas de similaridad de ligandos, se obtuvieron datos teóricos de las interacciones entre los fármacos seleccionados con el sitio activo de la enzima. Finalmente se analizó cada ligando en función de sus energías libres. Resultados: Se analizó computacionalmente 14100 unidades farmacológicas con posible interacción con la enzima RmlA de K. pneumoniae resistente a antibióticos, según las energías libres de interacción los valores enteros están entre 96 a 103 (kcal/mol), frente al valor de acoplamiento del sustrato-enzima de -222.357 (kcal/mol). Conclusiones: Se encontraron posibles fármacos inhibidores de la enzima RmlA de K. pneumonia, es necesario continuar con la valoración y estudio de estos fármacos en estudios laboratoriales para mejorar la propuesta de inhibición enzimática basada en este trabajo de investigación computacional. / Introduction: Antimicrobial resistance is an alarming problem in global public health. In mid-2017, the World Health Organization (WHO) reported a list of bacteria for the search for new antibiotics, including especially Enterobacteriaceae. In Peru, there were reports of cases of antibiotic-resistant Klebsiella pneumoniae in different regions of the country. Therefore, there is a need to find new target sites for pharmacological action to address this health problem. Objective: Identify organic molecules with the capacity to inhibit the enzyme Glucose 1-phosphate Thymidylyl Transferase (RmlA) of antibioticresistant K. pneumoniae using the molecular docking technique. Materials and methods: An in-silico study was carried out, using programa for molecular docking by local computer. The similarity of drugs with the natural substrate of the enzyme was given with ligand similarity programs, theoretical data were obtained on the interactions between the selected drugs with the active site of the enzyme. Finally, each ligand was analyzed based on its free energies. Results: 14100 pharmacological units with possible interaction with the RmlA enzyme of antibiotic-resistant K. pneumoniae were computationally analyzed. According to the interaction free energies, the integer values are between 96 to 103 (kcal/mol), compared to the coupling value of the substrate. enzyme of -222,357 (kcal/mol). Conclusions: Possible drugs that inhibit the RmlA enzyme of K. pneumonia were found; it is necessary to continue with the evaluation and study of these drugs in laboratory studies to improve the proposal for enzyme inhibition based on this computational research work.