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drug discovery

Deep Learning-driven research for drug discovery: Tackling Malaria

February 24, 2020 - 13:50 -- Open Access
Author(s): 
Neves BJ, Braga RC, Alves VM, Lima MNN, Cassiano GC, Muratov EN, Costa FTM, Andrade CH
Reference: 
PLoS Comput Biol 16(2): e1007025

Malaria is an infectious disease that affects over 216 million people worldwide, killing over 445,000 patients annually. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new drug candidates is a major global health priority. Aiming to make the drug discovery processes faster and less expensive, we developed binary and continuous Quantitative Structure-Activity Relationships (QSAR) models implementing deep learning for predicting antiplasmodial activity and cytotoxicity of untested compounds.

NOT Open Access | Current progress in antimalarial pharmacotherapy and multi-target drug discovery

January 14, 2020 - 12:04 -- NOT Open Access
Author(s): 
Tibon NS, Ng CH, Cheong SL
Reference: 
European Journal of Medicinal Chemistry, Volume 188, 15 February 2020, 111983

Discovery and development of antimalarial drugs have long been dominated by single-target therapy. Continuous effort has been made to explore and identify different targets in malaria parasite crucial for the malaria treatment. The single-target drug therapy was initially successful, but it was later supplanted by combination therapy with multiple drugs to overcome drug resistance.

An in vitro toolbox to accelerate anti-malarial drug discovery and development

January 6, 2020 - 16:26 -- Open Access
Author(s): 
Susan A. Charman, Alice Andreu, Nada Abla, et al.
Reference: 
Malaria Journal 2020 19:1, 2 January 2020

Modelling and simulation are being increasingly utilized to support the discovery and development of new anti-malarial drugs. These approaches require reliable in vitro data for physicochemical properties, permeability, binding, intrinsic clearance and cytochrome P450 inhibition. This work was conducted to generate an in vitro data toolbox using standardized methods for a set of 45 anti-malarial drugs and to assess changes in physicochemical properties in relation to changing target product and candidate profiles.

A systematic review on anti-malarial drug discovery and antiplasmodial potential of green synthesis mediated metal nanoparticles: overview, challenges and future perspectives

October 7, 2019 - 15:31 -- Open Access
Author(s): 
Loick P. Kojom Foko, Francois Eya’ane Meva, Carole E. Eboumbou Moukoko, Agnes A. Ntoumba, Marie I. Ngaha Njila, Philippe Belle Ebanda Kedi, Lawrence Ayong and Leopold G. Lehman
Reference: 
Malaria Journal 2019 18:337, 3 October 2019

The recent emergence in Southeast Asia of artemisinin resistance poses major threats to malaria control and elimination globally. Green nanotechnologies can constitute interesting tools for discovering anti-malarial medicines. This systematic review focused on the green synthesis of metal nanoparticles as potential source of new antiplasmodial drugs.

Medical Condition: 
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