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Oligopeptidase B and B2: comparative modelling and virtual screening as searching tools for new antileishmanial compounds

Published online by Cambridge University Press:  29 December 2016

ANA CAROLINA R. SODERO*
Affiliation:
Laboratório de Modelagem Molecular e QSAR (MODMOLQSAR), Departamento de Fármacos e Medicamentos, Universidade Federal do Rio de Janeiro (UFRJ), Av. Carlos Chagas Filho, 373, 21941-599, Brazil
ANA CAROLINA G. O. DOS SANTOS
Affiliation:
Laboratório de Modelagem Molecular e QSAR (MODMOLQSAR), Departamento de Fármacos e Medicamentos, Universidade Federal do Rio de Janeiro (UFRJ), Av. Carlos Chagas Filho, 373, 21941-599, Brazil
JULIANA F. R. E MELLO
Affiliation:
Laboratório de Modelagem Molecular e QSAR (MODMOLQSAR), Departamento de Fármacos e Medicamentos, Universidade Federal do Rio de Janeiro (UFRJ), Av. Carlos Chagas Filho, 373, 21941-599, Brazil
JÉSSICA B. DE JESUS
Affiliation:
Laboratório de Modelagem Molecular e QSAR (MODMOLQSAR), Departamento de Fármacos e Medicamentos, Universidade Federal do Rio de Janeiro (UFRJ), Av. Carlos Chagas Filho, 373, 21941-599, Brazil
ALESSANDRA M. T. DE SOUZA
Affiliation:
Laboratório de Modelagem Molecular e QSAR (MODMOLQSAR), Departamento de Fármacos e Medicamentos, Universidade Federal do Rio de Janeiro (UFRJ), Av. Carlos Chagas Filho, 373, 21941-599, Brazil
MARIA ISABEL C. RODRIGUES
Affiliation:
Centro de Desenvolvimento Tecnológico em Saúde (CDTS)/Instituto Nacional de Ciência e Tecnologia de Inovação em Doenças de Populações Negligenciadas (INCT-IDPN), 21045-900 Rio de Janeiro, RJ, Brazil
SALVATORE G. DE SIMONE
Affiliation:
Centro de Desenvolvimento Tecnológico em Saúde (CDTS)/Instituto Nacional de Ciência e Tecnologia de Inovação em Doenças de Populações Negligenciadas (INCT-IDPN), 21045-900 Rio de Janeiro, RJ, Brazil
CARLOS R. RODRIGUES
Affiliation:
Laboratório de Modelagem Molecular e QSAR (MODMOLQSAR), Departamento de Fármacos e Medicamentos, Universidade Federal do Rio de Janeiro (UFRJ), Av. Carlos Chagas Filho, 373, 21941-599, Brazil
HERBERT L. DE MATOS GUEDES*
Affiliation:
Grupo de Imunologia e Vacinologia, Laboratório de Inflamação, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, 21941-902 Rio de Janeiro, RJ, Brazil Núcleo Multidisciplinar de Pesquisa UFRJ – Xerém em Biologia (NUMPEX-BIO), Polo Avançado de Xerém – Universidade Federal do Rio de Janeiro, 25245-390 Duque de Caxias, RJ, Brazil
*
*Corresponding authors: Laboratório de Modelagem Molecular e QSAR (MODMOLQSAR), Departamento de Fármacos e Medicamentos, Universidade Federal do Rio de Janeiro (UFRJ), Av. Carlos Chagas Filho, 373, 21941-599, Brazil. E-mail: [email protected] and Grupo de Imunologia e Vacinologia, Laboratório de Inflamação, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, 21941-902 Rio de Janeiro, RJ, Brazil. E-mail: [email protected]
*Corresponding authors: Laboratório de Modelagem Molecular e QSAR (MODMOLQSAR), Departamento de Fármacos e Medicamentos, Universidade Federal do Rio de Janeiro (UFRJ), Av. Carlos Chagas Filho, 373, 21941-599, Brazil. E-mail: [email protected] and Grupo de Imunologia e Vacinologia, Laboratório de Inflamação, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, 21941-902 Rio de Janeiro, RJ, Brazil. E-mail: [email protected]

Summary

Leishmaniasis are diseases caused by parasites of the genus Leishmania and transmitted to humans by the bite of infected insects of the subfamily Phlebotominae. Current drug therapy shows high toxicity and severe adverse effects. Recently, two oligopeptidases (OPBs) were identified in Leishmania amazonensis, namely oligopeptidase B (OPB) and oligopeptidase B2 (OPB2). These OPBs could be ideal targets, since both enzymes are expressed in all parasite lifecycle and were not identified in human. This work aimed to identify possible dual inhibitors of OPB and OPB2 from L. amazonensis. The three-dimensional structures of both enzymes were built by comparative modelling and used to perform a virtual screening of ZINC database by DOCK Blaster server. It is the first time that OPB models from L. amazonensis are used to virtual screening approach. Four hundred compounds were identified as possible inhibitors to each enzyme. The top scored compounds were submitted to refinement by AutoDock program. The best results suggest that compounds interact with important residues, as Tyr490, Glu612 and Arg655 (OPB numbers). The identified compounds showed better results than antipain and drugs currently used against leishmaniasis when ADMET in silico were performed. These compounds could be explored in order to find dual inhibitors of OPB and OPB2 from L. amazonensis.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2016 

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