High-Throughput Screening and Prediction Model Building for Novel Hemozoin Inhibitors Using Physicochemical Properties

2D-quantitative structure-activity relationships model using PLS method for anti-malarial activities of anti-haemozoin compounds

Background

Emergence of cross-resistance to current anti-malarial drugs has led to an urgent need for identification of potential compounds with novel modes of action and anti-malarial activity against the resistant strains. One of the most promising therapeutic targets of anti-malarial agents related to food vacuole of malaria parasite is haemozoin, a product formed by the parasite through haemoglobin degradation.

Methods

With this in mind, this study developed two-dimensional-quantitative structure–activity relationships (QSAR) models of a series of 21 haemozoin inhibitors to explore the useful physicochemical parameters of the active compounds for estimation of anti-malarial activities. The 2D-QSAR model with good statistical quality using partial least square method was generated after removing the outliers.

Results

Five two-dimensional descriptors of the training set were selected: atom count (a_ICM); adjacency and distance matrix descriptor (GCUT_SLOGP_2: the third GCUT descriptor using atomic contribution to logP); average total charge sum (h_pavgQ) in pKa prediction (pH = 7); a very low negative partial charge, including aromatic carbons which have a heteroatom-substitution in “ortho” position (PEOE_VSA-0) and molecular descriptor (rsynth: estimating the synthesizability of molecules as the fraction of heavy atoms that can be traced back to starting material fragments resulting from retrosynthetic rules), respectively. The model suggests that the anti-malarial activity of haemozoin inhibitors increases with molecules that have higher average total charge sum in pKa prediction (pH = 7). QSAR model also highlights that the descriptor using atomic contribution to logP or the distance matrix descriptor (GCUT_SLOGP_2), and structural component of the molecules, including topological descriptors does make for better anti-malarial activity.

Conclusions

The model is capable of predicting the anti-malarial activities of anti-haemozoin compounds. In addition, the selected molecular descriptors in this QSAR model are helpful in designing more efficient compounds against the P. falciparum 3D7A strain.

Oxidative and nitrosative stresses in cerebral malaria: can we target them to avoid a bad prognosis?

There is currently a global effort to reduce malaria morbidity and mortality. However, malaria still results in the deaths of thousands of people every year. Malaria is caused by Plasmodium spp., parasites transmitted through the bite of an infected female Anopheles mosquito. Treatment timing plays a decisive role in reducing mortality and sequelae associated with the severe forms of the disease such as cerebral malaria (CM). The available antimalarial therapy is considered effective but parasite resistance to these drugs has been observed in some countries. Antimalarial drugs act by increasing parasite lysis, especially through targeting oxidative stress pathways. Here we discuss the roles of reactive oxygen species and reactive nitrogen intermediates in CM as a result of host-parasite interactions. We also present evidence of the potential contribution of oxidative and nitrosative stress-based antimalarial drugs to disease treatment and control.

Lapatinib, Nilotinib and Lomitapide Inhibit Haemozoin Formation in Malaria Parasites

With the continued loss of antimalarials to resistance, drug repositioning may have a role in maximising efficiency and accelerating the discovery of new antimalarial drugs. Bayesian statistics was previously used as a tool to virtually screen USFDA approved drugs for predicted β-haematin (synthetic haemozoin) inhibition and in vitro antimalarial activity. Here, we report the experimental evaluation of nine of the highest ranked drugs, confirming the accuracy of the model by showing an overall 93% hit rate. Lapatinib, nilotinib, and lomitapide showed the best activity for inhibition of β-haematin formation and parasite growth and were found to inhibit haemozoin formation in the parasite, providing mechanistic insights into their mode of antimalarial action. We then screened the USFDA approved drugs for binding to the β-haematin crystal, applying a docking method in order to evaluate its performance. The docking method correctly identified imatinib, lapatinib, nilotinib, and lomitapide. Experimental evaluation of 22 of the highest ranked purchasable drugs showed a 24% hit rate. Lapatinib and nilotinib were chosen as templates for shape and electrostatic similarity screening for lead hopping using the in-stock ChemDiv compound catalogue. The actives were novel structures worthy of future investigation. This study presents a comparison of different in silico methods to identify new haemozoin-inhibiting chemotherapeutic alternatives for malaria that proved to be useful in different ways when taking into consideration their strengths and limitations.

Antimalarial Quinoline Drugs Inhibit β-Hematin and Increase Free Hemin Catalyzing Peroxidative Reactions and Inhibition of Cysteine Proteases

Malaria caused by Plasmodium affects millions people worldwide. Plasmodium consumes hemoglobin during its intraerythrocytic stage leaving toxic heme. Parasite detoxifies free heme through formation of hemozoin (β-hematin) pigment. Proteolysis of hemoglobin and formation of hemozoin are two main targets for antimalarial drugs. Quinoline antimarial drugs and analogs (β-carbolines or nitroindazoles) were studied as inhibitors of β-hematin formation. The most potent inhibitors were quinacrine, chloroquine, and amodiaquine followed by quinidine, mefloquine and quinine whereas 8-hydroxyquinoline and β-carbolines had no effect. Compounds that inhibited β-hematin increased free hemin that promoted peroxidative reactions as determined with TMB and ABTS substrates. Hemin-catalyzed peroxidative reactions were potentiated in presence of proteins (i.e. globin or BSA) while antioxidants and peroxidase inhibitors decreased peroxidation. Free hemin increased by chloroquine action promoted oxidative reactions resulting in inhibition of proteolysis by three cysteine proteases: papain, ficin and cathepsin B. Glutathione reversed inhibition of proteolysis. These results show that active quinolines inhibit hemozoin and increase free hemin which in presence of H2O2 that abounds in parasite digestive vacuole catalyzes peroxidative reactions and inhibition of cysteine proteases. This work suggests a link between the action of quinoline drugs with biochemical processes of peroxidation and inhibition of proteolysis.

Prediction Model for Antimalarial Activities of Hemozoin Inhibitors by Using Physicochemical Properties

The rapid spread of strains of malaria parasites that are resistant to several drugs has threatened global malaria control. Hence, the aim of this study was to predict the antimalarial activity of chemical compounds that possess anti-hemozoin-formation activity as a new means of antimalarial drug discovery. After the initial in vitro anti-hemozoin-formation high-throughput screening (HTS) of 9,600 compounds, a total of 224 hit compounds were identified as hemozoin inhibitors. These 224 compounds were tested for in vitro erythrocytic antimalarial activity at 10 μM by using chloroquine-mefloquine-sensitive Plasmodium falciparum strain 3D7A. Two independent experiments were conducted. The physicochemical properties of the active compounds were extracted from the ChemSpider and SciFinder databases. We analyzed the extracted data by using Bayesian model averaging (BMA). Our findings revealed that lower numbers of S atoms; lower distribution coefficient (log D) values at pH 3, 4, and 5; and higher predicted distribution coefficient (ACD log D) values at pH 7.4 had significant associations with antimalarial activity among compounds that possess anti-hemozoin-formation activity. The BMA model revealed an accuracy of 91.23%. We report new prediction models containing physicochemical properties that shed light on effective chemical groups for synthetic antimalarial compounds and help with in silico screening for novel antimalarial drugs.