ABSTRACT
The emergence and spread of Plasmodium falciparum resistance to first-line antimalarials creates an imperative to identify and develop potent preclinical candidates with distinct modes of action. Here, we report the identification of MMV688533, an acylguanidine that was developed following a whole-cell screen with compounds known to hit high-value targets in human cells. MMV688533 displays fast parasite clearance in vitro and is not cross-resistant with known antimalarials. In a P. falciparum NSG mouse model, MMV688533 displays a long-lasting pharmacokinetic profile and excellent safety. Selection studies reveal a low propensity for resistance, with modest loss of potency mediated by point mutations in PfACG1 and PfEHD. These proteins are implicated in intracellular trafficking, lipid utilization, and endocytosis, suggesting interference with these pathways as a potential mode of action. This preclinical candidate may offer the potential for a single low-dose cure for malaria.
Subject(s)
Antimalarials , Malaria, Falciparum , Malaria , Parasites , Animals , Antimalarials/pharmacology , Antimalarials/therapeutic use , Endocytosis , Malaria/drug therapy , Malaria, Falciparum/drug therapy , Plasmodium falciparumABSTRACT
Inhibition of protein kinase activity is a focus of intense drug discovery efforts in several therapeutic areas. Major challenges facing the field include understanding of the factors determining the selectivity of kinase inhibitors and the development of compounds with the desired selectivity profile. Here, we report the analysis of sequence variability among high and low affinity targets of eight different small molecule kinase inhibitors (BIRB796, Tarceva, NU6102, Gleevec, SB203580, balanol, H89, PP1). It is observed that all high affinity targets of each inhibitor are found among a relatively small number of kinases, which have similar residues at the specific positions important for binding. The findings are highly statistically significant, and allow one to exclude the majority of kinases in a genome from a list of likely targets for an inhibitor. The findings have implications for the design of novel inhibitors with a desired selectivity profile (e.g. targeted at multiple kinases), the discovery of new targets for kinase inhibitor drugs, comparative analysis of different in vivo models, and the design of "a-la-carte" chemical libraries tailored for individual kinases.
Subject(s)
Amino Acids/metabolism , Protein Kinase Inhibitors/pharmacology , Protein Kinases/metabolism , Thermodynamics , Amino Acid Sequence , Amino Acids/genetics , Benzamides , Binding Sites/drug effects , Binding Sites/genetics , Humans , Imatinib Mesylate , Ligands , Molecular Sequence Data , Piperazines/chemistry , Piperazines/pharmacology , Protein Binding/drug effects , Protein Binding/genetics , Protein Kinase Inhibitors/chemistry , Protein Kinases/chemistry , Protein Kinases/genetics , Pyrazoles/chemistry , Pyrazoles/pharmacology , Pyrimidines/chemistry , Pyrimidines/pharmacology , Sequence Alignment , Static ElectricityABSTRACT
The major hurdle to overcome in the development of 3D-QSAR models using steric, electrostatic, or lipophilic "fields" is related to both conformation selection and subsequent suitable overlay (alignment) of compounds. Therefore, it is of some interest to provide a conformationally sensitive lipophilicity descriptor that is alignment-independent. In this chapter we describe the derivation and parametrization of a new descriptor called 3D-LogP and demonstrate both its conformational sensitivity and its effectiveness in QSAR analysis. The 3D-LogP descriptor provides such a representation in the form of a rapidly computable description of the local lipophilicity at points on a user-defined molecular surface.