AIMC Topic: Plasmodium falciparum

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Bayesian models trained with HTS data for predicting β-haematin inhibition and in vitro antimalarial activity.

Bioorganic & medicinal chemistry
A large quantity of high throughput screening (HTS) data for antimalarial activity has become available in recent years. This includes both phenotypic and target-based activity. Realising the maximum value of these data remains a challenge. In this r...

Identification of therapeutics against PfPK6 protein of Plasmodium falciparum: Structure and Deep Learning approach.

Experimental parasitology
The Plasmodium falciparum Protein Kinase 6 (PfPK6) is a serine/threonine protein kinase categorized under the CMGC group, displaying both cyclin-dependent kinases (CDKs) and mitogen-activated protein kinases (MAPKs) activity. Previous research has in...

Increasing a microscope's effective field of view via overlapped imaging and machine learning.

Optics express
This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis. Automatic detection, classification and counting of various morpholog...

Antiplasmodial activity of some phenolic compounds from Cameroonians Allanblackia.

African health sciences
BACKGROUND: Plasmodium falciparum, one of the causative agents of malaria, has high adaptability through mutation and is resistant to many types of anti-malarial drugs. This study presents an in vitro assessment of the antiplasmodial activity of some...

Role of moving average analysis for development of multi-target (Q)SAR models.

Mini reviews in medicinal chemistry
In modern drug discovery era, multi target- quantitative structure activity relationship [mt- (Q)SAR] approaches have emerged as novel and powerful alternatives in the field of in-silico drug design so as to facilitate the discovery of new chemical e...