Identification and Validation of a Potent Dual Inhibitor of the P. falciparum M1 and M17 Aminopeptidases Using Virtual Screening

Chemoproteomics validates selective targeting of Plasmodium M1 alanyl aminopeptidase as an antimalarial strategy

New antimalarial drug candidates that act via novel mechanisms are urgently needed to combat malaria drug resistance. Here, we describe the multi-omic chemical validation of Plasmodium M1 alanyl metalloaminopeptidase as an attractive drug target using the selective inhibitor, MIPS2673. MIPS2673 demonstrated potent inhibition of recombinant Plasmodium falciparum (PfA-M1) and Plasmodium vivax (PvA-M1) M1 metalloaminopeptidases, with selectivity over other Plasmodium and human aminopeptidases, and displayed excellent in vitro antimalarial activity with no significant host cytotoxicity. Orthogonal label-free chemoproteomic methods based on thermal stability and limited proteolysis of whole parasite lysates revealed that MIPS2673 solely targets PfA-M1 in parasites, with limited proteolysis also enabling estimation of the binding site on PfA-M1 to within ~5 Å of that determined by X-ray crystallography. Finally, functional investigation by untargeted metabolomics demonstrated that MIPS2673 inhibits the key role of PfA-M1 in haemoglobin digestion. Combined, our unbiased multi-omic target deconvolution methods confirmed the on-target activity of MIPS2673, and validated selective inhibition of M1 alanyl metalloaminopeptidase as a promising antimalarial strategy.

Chemoproteomics validates selective targeting of Plasmodium M1 alanyl aminopeptidase as an antimalarial strategy

New antimalarial drug candidates that act via novel mechanisms are urgently needed to combat malaria drug resistance. Here, we describe the multi-omic chemical validation of Plasmodium M1 alanyl metalloaminopeptidase as an attractive drug target using the selective inhibitor, MIPS2673. MIPS2673 demonstrated potent inhibition of recombinant Plasmodium falciparum ( Pf A-M1) and Plasmodium vivax ( Pv A-M1) M1 metalloaminopeptidases, with selectivity over other Plasmodium and human aminopeptidases, and displayed excellent in vitro antimalarial activity with no significant host cytotoxicity. Orthogonal label-free chemoproteomic methods based on thermal stability and limited proteolysis of whole parasite lysates revealed that MIPS2673 solely targets Pf A-M1 in parasites, with limited proteolysis also enabling estimation of the binding site on Pf A-M1 to within ~5 Å of that determined by X-ray crystallography. Finally, functional investigation by untargeted metabolomics demonstrated that MIPS2673 inhibits the key role of Pf A-M1 in haemoglobin digestion. Combined, our unbiased multi-omic target deconvolution methods confirmed the on-target activity of MIPS2673, and validated selective inhibition of M1 alanyl metalloaminopeptidase as a promising antimalarial strategy.

Antimalarial drug discovery: progress and approaches

Recent antimalarial drug discovery has been a race to produce new medicines that overcome emerging drug resistance, whilst considering safety and improving dosing convenience. Discovery efforts have yielded a variety of new molecules, many with novel modes of action, and the most advanced are in late-stage clinical development. These discoveries have led to a deeper understanding of how antimalarial drugs act, the identification of a new generation of drug targets, and multiple structure-based chemistry initiatives. The limited pool of funding means it is vital to prioritize new drug candidates. They should exhibit high potency, a low propensity for resistance, a pharmacokinetic profile that favours infrequent dosing, low cost, preclinical results that demonstrate safety and tolerability in women and infants, and preferably the ability to block Plasmodium transmission to Anopheles mosquito vectors. In this Review, we describe the approaches that have been successful, progress in preclinical and clinical development, and existing challenges. We illustrate how antimalarial drug discovery can serve as a model for drug discovery in diseases of poverty.

Designing dual inhibitors against potential drug targets of Plasmodium falciparum -M17 Leucyl Aminopeptidase and Plasmepsins

Malaria is one of the major diseases of concern worldwide, especially in the African regions. According to a recent WHO report, 95% of deaths that occur due to malaria are in the African regions. Resistance to present antimalarial drugs is increasing rapidly and becoming a problem of concern. M17 Leucyl Aminopeptidase (PfM17LAP) and vacuolar Plasmepsins (PfPM) are two important enzymes involved in the haemoglobin degradation pathway of Plasmodium falciparum. PfM17LAP regulates the release of amino acids and PfPM mediates the conversion of haemoglobin proteins to oligopeptides. These enzymes thus play an essential role in the survival of malaria parasites inside the human body. In the present study, we used in-silico molecular docking, simulation and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) studies to find potential dual inhibitors of PfPM and PfM17LAP using the ChEMBL antimalarial library. Absorption, distribution, metabolism, excretion and toxicity (ADMET) profiling of the top ten ranked molecules was done using the BIOVIA Discovery Studio. The present investigation revealed that the compound CHEMBL426945 is stable in the binding site of both PfPM and PfM17LAP. In this study, we have reported novel dual-inhibitors that may act better than the present antimalarial drugs.Communicated by Ramaswamy H. Sarma.

Amino Acid Transporters as Disease Modifiers and Drug Targets

Amino acids perform a variety of functions in cells and organisms, particularly in the synthesis of proteins, as energy metabolites, neurotransmitters, and precursors for many other molecules. Amino acid transport plays a key role in all these functions. Inhibition of amino acid transport is pursued as a therapeutic strategy in several areas, such as diabetes and related metabolic disorders, neurological disorders, cancer, and stem cell biology. The role of amino acid transporters in these disorders and processes is well established, but the implementation of amino acid transporters as drug targets is still in its infancy. This is at least in part due to the underdeveloped pharmacology of this group of membrane proteins. Recent advances in structural biology, membrane protein expression, and inhibitor screening methodology will see an increased number of improved and selective inhibitors of amino acid transporters that can serve as tool compounds for further studies.

Computer-Assisted Selective Optimization of Side-Activities-from Cinalukast to a PPARα Modulator

Automated computational analogue design and scoring can speed up hit-to-lead optimization and appears particularly promising in selective optimization of side-activities (SOSA) where possible analogue diversity is confined. Probing this concept, we employed the cysteinyl leukotriene receptor 1 (CysLT₁ R) antagonist cinalukast as lead for which we discovered peroxisome proliferator-activated receptor α (PPARα) modulatory activity. We automatically generated a virtual library of close analogues and classified these roughly 8000 compounds for PPARα agonism and CysLT₁ R antagonism using automated affinity scoring and machine learning. A computationally preferred analogue for SOSA was synthesized, and in vitro characterization indeed revealed a marked activity shift toward enhanced PPARα activation and diminished CysLT₁ R antagonism. Thereby, this prospective application study highlights the potential of automating SOSA.

In-silico screening of small molecule inhibitors against Lactate Dehydrogenase (LDH) of Cryptosporidium parvum

Cryptosporidium parvum is a protozoan parasite which causes waterborne diseases known as Cryptosporidiosis. It is an acute enteric diarrheal disease being severe in the case of immunocompromised individuals and children. C. parvum mainly depends on the glycolysis process for energy production and LDH (Lactate Dehydrogenase) is a key controller of this process. In this study from different in-silico approaches such as structure-based, ligand-based and de novo drug design; a total of 40 compounds were selected for docking studies against LDH. The study reported a compound CHEMBL1784973 from Pathogen Box as the best inhibitor in terms of docking score and pharmacophoric features. Furthermore, the binding mode of the best-reported inhibitor was validated through molecular dynamics simulation for a time interval of 70 ns in water environment. The findings resulted in the stable conformation of the inhibitor in the active site of the protein. This study will be helpful for experimental validation.

Decoys Selection in Benchmarking Datasets: Overview and Perspectives

Virtual Screening (VS) is designed to prospectively help identifying potential hits, i.e., compounds capable of interacting with a given target and potentially modulate its activity, out of large compound collections. Among the variety of methodologies, it is crucial to select the protocol that is the most adapted to the query/target system under study and that yields the most reliable output. To this aim, the performance of VS methods is commonly evaluated and compared by computing their ability to retrieve active compounds in benchmarking datasets. The benchmarking datasets contain a subset of known active compounds together with a subset of decoys, i.e., assumed non-active molecules. The composition of both the active and the decoy compounds subsets is critical to limit the biases in the evaluation of the VS methods. In this review, we focus on the selection of decoy compounds that has considerably changed over the years, from randomly selected compounds to highly customized or experimentally validated negative compounds. We first outline the evolution of decoys selection in benchmarking databases as well as current benchmarking databases that tend to minimize the introduction of biases, and secondly, we propose recommendations for the selection and the design of benchmarking datasets.

Selective inhibition of PfA-M1, over PfA-M17, by an amino-benzosuberone derivative blocks malaria parasites development in vitro and in vivo

Background

Plasmodium falciparum M1 family aminopeptidase is currently considered as a promising target for anti-malarial chemotherapy. Several series of inhibitors developed by various research groups display IC50/Ki values down to nM range on native PfA-M1 or recombinant forms and block the parasite development in culture at µM to sub-µM concentrations. A handful of these inhibitors has been tested on murine models of malaria and has shown anti plasmodial in vivo activity. However, most of these inhibitors do also target the other neutral malarial aminopeptidase, PfA-M17, often with lower Ki values, which questions the relative involvement and importance of each enzyme in the parasite biology.

Results

An amino-benzosuberone derivative from a previously published collection of chemicals targeting specifically the M1-aminopeptidases has been identified; it is highly potent on PfA-M1 (Ki = 50 nM) and devoid of inhibitory activity on PfA-M17 (no inhibition up to 100 µM). This amino-benzosuberone derivative (T5) inhibits, in the µM range, the in vitro growth of two P. falciparum strains, 3D7 and FcB1, respectively chloroquino-sensitive and resistant. Evaluated in vivo, on the murine non-lethal model of malaria Plasmodium chabaudi chabaudi, this amino-benzosuberone derivative was able to reduce the parasite burden by 44 and 40% in a typical 4-day Peters assay at a daily dose of 12 and 24 mg/kg by intraperitoneal route of administration.

Conclusions

The evaluation of a highly selective inhibitor of PfA-M1, over PfA-M17, active on Plasmodium parasites in vitro and in vivo, highlights the relevance of PfA-M1 in the biological development of the parasite as well as in the list of promising anti-malarial targets to be considered in combination with current or future anti-malarial drugs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-017-2032-4) contains supplementary material, which is available to authorized users.

In silico screening of novel inhibitors of M17 Leucine Amino Peptidase (LAP) of Plasmodium vivax as therapeutic candidate

M17 LAP (Leucine Amino Peptidase) plays an important role in the hydrolysis of amino acids essential for growth and development of Plasmodium vivax (Pv), the pathogen causing malaria. In this paper a homology model of PvLAP was generated using MODELLER v9.15. From different in-silico methods such as structure based, ligand based and de novo drug designing a total of 90 compounds were selected for docking studies. A final list of 10 compounds was prepared. The study reported the identification of 2-[(3-azaniumyl-2-hydroxy-4-phenylbutanoyl) amino]-4-methylpentanoate as the best inhibitor in terms of docking score and pharmacophoric features. The reliability of the binding mode of the inhibitor is confirmed by molecular dynamics (MD) simulation study with GROMACS software for a simulation time of 20ns in water environment. Finally, in silico ADMET analysis of the inhibitors using MedChem Designer v3 evaluated the drug likeness of the best hits to be considered for industrial pharmaceutical research.

Docking Screens for Novel Ligands Conferring New Biology

It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking's greatest impact over the next few years.