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. Then, we applied the best models for a virtual screening of a large database of chemical compounds. The top computational predictions were evaluated experimentally against asexual blood stages of both sensitive and multi-drug-resistant Plasmodium falciparum strains. Among them, two compounds, LabMol-149 and LabMol-152, showed potent antiplasmodial activity at low nanomolar concentrations (EC₅₀ <500 nM) and low cytotoxicity in mammalian cells. Therefore, the computational approach employing deep learning developed here allowed us to discover two new families of potential next generation antimalarial agents, which are in compliance with the guidelines and criteria for antimalarial target candidates. Malaria is a serious infectious disease caused by parasites of the genus Plasmodium. The recommended treatment is a combination of antimalarial drugs. However, the rise of parasites resistant to the current antimalarial drugs means that new therapeutics are continually required. To meet this challenge, we developed and applied models using deep learning, a powerful artificial intelligence method, supported by experimental validation to identify new drug candidates against malaria. We used the developed computational models to prioritize novel, active, and nontoxic compounds from virtual chemical libraries for experimental evaluation. Then, the predicted antimalarial compounds were experimentally validated in assays on Plasmodium falciparum culture. This allowed us to discover two new potential antimalarial candidates. The use of computational approaches is an attractive route to expedite the discovery of new therapeutics, especially to infectious tropical diseases, as it can reduce time and development costs. Future directions include in vivo studies on animal models.

The circumsporozoite protein (CSP) of the Plasmodium vivax infective sporozoite is considered to be a major target for the development of recombinant malaria vaccines. The Duffy blood group molecule acts as the red blood cell receptor for P. vivax. We review the frequency of P. vivax CSP variants and report their association with the Duffy blood group genotypes from Brazilian Amazon patients carrying P. vivax malaria. Peripheral blood samples were collected from 155 P. vivax-infected individuals from five Brazilian malaria-endemic areas. The P. vivax CSP variants and the Duffy blood group genotypes were assessed using PCR/RFLP. In single infections, the VK210 variant was the commonest followed by the P. vivax-like variant. The typing of P. vivax indicated that the frequency of variants among the study areas was significantly different from one to another. This is the first detection of the VK247 and P. vivax-like variant in single infections in endemic areas of Brazil. Association of the CSP P. vivax variants with the heterozygous Duffy blood group system genotype was significant for VK210 single infection. These observations provide additional data on the Plasmodium-host interactions concerning the Duffy blood group and P. vivax capability of causing human malaria.

Malaria is a life-threatening infectious disease caused by parasites of the genus Plasmodium, affecting more than 200 million people worldwide every year and leading to about a half million deaths. Malaria parasites of humans have evolved resistance to all current antimalarial drugs, urging for the discovery of new effective compounds. Given that the inhibition of deoxyuridine triphosphatase of Plasmodium falciparum (PfdUTPase) induces wrong insertions in plasmodial DNA and consequently leading the parasite to death, this enzyme is considered an attractive antimalarial drug target. Using a combi-QSAR (quantitative structure-activity relationship) approach followed by virtual screening and in vitro experimental evaluation, we report herein the discovery of novel chemical scaffolds with in vitro potency against asexual blood stages of both P. falciparum multidrug-resistant and sensitive strains and against sporogonic development of P. berghei. We developed 2D- and 3D-QSAR models using a series of nucleosides reported in the literature as PfdUTPase inhibitors. The best models were combined in a consensus approach and used for virtual screening of the ChemBridge database, leading to the identification of five new virtual PfdUTPase inhibitors. Further in vitro testing on P. falciparum multidrug-resistant (W2) and sensitive (3D7) parasites showed that compounds LabMol-144 and LabMol-146 demonstrated fair activity against both strains and presented good selectivity versus mammalian cells. In addition, LabMol-144 showed good in vitro inhibition of P. berghei ookinete formation, demonstrating that hit-to-lead optimization based on this compound may also lead to new antimalarials with transmission blocking activity.

Plasmodium vivax circumsporozoite variants have been identified in several geographical areas. The real implication of the genetic variation in this region of the P. vivax genome has been questioned for a long time. Although previous studies have observed significant association between VK210 and the Duffy blood group, we present here that evidences of this variation are limited to the CSP central portion.