Literature DB >> 22352913

A review of QSAR studies to discover new drug-like compounds actives against leishmaniasis and trypanosomiasis.

Juan Alberto Castillo-Garit1, Concepción Abad, J Enrique Rodríguez-Borges, Yovani Marrero-Ponce, Francisco Torrens.   

Abstract

The neglected tropical diseases (NTDs) affect more than one billion people (one-sixth of the world's population) and occur primarily in undeveloped countries in sub-Saharan Africa, Asia, and Latin America. Available drugs for these diseases are decades old and present an important number of limitations, especially high toxicity and, more recently, the emergence of drug resistance. In the last decade several Quantitative Structure-Activity Relationship (QSAR) studies have been developed in order to identify new organic compounds with activity against the parasites responsible for these diseases, which are reviewed in this paper. The topics summarized in this work are: 1) QSAR studies to identify new organic compounds actives against Chaga's disease; 2) Development of QSAR studies to discover new antileishmanial drusg; 3) Computational studies to identify new drug-like compounds against human African trypanosomiasis. Each topic include the general characteristics, epidemiology and chemotherapy of the disease as well as the main QSAR approaches to discovery/identification of new actives compounds for the corresponding neglected disease. The last section is devoted to a new approach know as multi-target QSAR models developed for antiparasitic drugs specifically those actives against trypanosomatid parasites. At present, as a result of these QSAR studies several promising compounds, active against these parasites, are been indentify. However, more efforts will be required in the future to develop more selective (specific) useful drugs.

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Year:  2012        PMID: 22352913     DOI: 10.2174/156802612800166756

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  6 in total

1.  Probing the opportunities for designing anthelmintic leads by sub-structural topology-based QSAR modelling.

Authors:  Prabodh Ranjan; Mohd Athar; Prakash Chandra Jha; Kari Vijaya Krishna
Journal:  Mol Divers       Date:  2018-04-02       Impact factor: 2.943

2.  Ranking-Oriented Quantitative Structure-Activity Relationship Modeling Combined with Assay-Wise Data Integration.

Authors:  Katsuhisa Matsumoto; Tomoyuki Miyao; Kimito Funatsu
Journal:  ACS Omega       Date:  2021-04-28

Review 3.  Nanostructured delivery systems with improved leishmanicidal activity: a critical review.

Authors:  Natascia Bruni; Barbara Stella; Leonardo Giraudo; Carlo Della Pepa; Daniela Gastaldi; Franco Dosio
Journal:  Int J Nanomedicine       Date:  2017-07-26

4.  Antiprotozoal Nitazoxanide Derivatives: Synthesis, Bioassays and QSAR Study Combined with Docking for Mechanistic Insight.

Authors:  Thomas Scior; Jorge Lozano-Aponte; Subhash Ajmani; Eduardo Hernández-Montero; Fabiola Chávez-Silva; Emanuel Hernández-Núñez; Rosa Moo-Puc; Andres Fraguela-Collar; Gabriel Navarrete-Vázquez
Journal:  Curr Comput Aided Drug Des       Date:  2015       Impact factor: 1.606

Review 5.  Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases.

Authors:  David A Winkler
Journal:  Front Chem       Date:  2021-03-15       Impact factor: 5.221

6.  Antioxidant Activity of Pharmaceuticals: Predictive QSAR Modeling for Potential Therapeutic Strategy.

Authors:  Mario-Livio Jeličić; Jelena Kovačić; Matija Cvetnić; Ana Mornar; Daniela Amidžić Klarić
Journal:  Pharmaceuticals (Basel)       Date:  2022-06-24
  6 in total

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