Computer-Aided Design and Synthesis of Nonpeptidic Plasmepsin II and IV Inhibitors

Plasmepsin Inhibitors in Antimalarial Drug Discovery: Medicinal Chemistry and Target Validation (2000 to Present)

Plasmepsins represent novel antimalarial drug targets. However, plasmepsin-based antimalarial drug discovery efforts in the past 2 decades have generally suffered some drawbacks including lack of translatability of target inhibition to potent parasite inhibition in vitro and in vivo as well as poor selectivity over the related human aspartic proteases. Most studies reported in this period have over-relied on the use of hemoglobinase plasmepsins I-IV (particularly I and II) as targets for the new inhibitors even though these are known to be nonessential at the asexual stage of parasite development. Therefore, future antimalarial drug discovery efforts seeking to identify plasmepsin inhibitors should focus on incorporating non-hemoglobinase plasmepsins such as V, IX, and X in their screening in order to maximize chances of success. Additionally, there is need to go beyond just target enzymatic activity profiling to establishing cellular activity, physicochemical as well as drug metabolism and pharmacokinetics properties and finally in vivo proof-of-concept while ensuring selectivity over related human host proteases.

Indexing Natural Products for their Antifungal Activity by Filters-based Approach: Disclosure of Discriminative Properties

Methods:

A set of 240 FDA-approved antifungal drugs, which represent the active domain, and a set of 2,892 natural products, which represent the inactive domain, were used to construct predictive models and to index natural products for their antifungal bioactivity. The area under the curve for the produced predictive model was 0.89. When applying it to a database that is composed of active/inactive chemicals, we succeeded to detect 42% of the actives (antifungal drugs) in the top one percent of the screened chemicals, compared with one-percent when using a random model.

Results and Conclusion:

Eight natural products, which were highly scored as likely antifungal drugs, are disclosed. Searching PubMed showed only one molecule (Flindersine) out of the eight that have been tested was reported as an antifungal. The other seven phytochemicals await evaluation for their antifungal bioactivity in a wet laboratory.</P>

Ring-opening formal hetero-[5+2] cycloaddition of 1-tosyl-2,3-dihydro-1H-pyrroles with terminal alkynes: entry to 1-tosyl-2,3-dihydro 2,3-dihydro-1H-azepines

Lewis acid-catalyzed formal hetero-[5+2] cycloaddition of 2,3-dihydro-1H-pyrroles with alkynes through C(sp²)–N bond cleavage toward 2,3-dihydro-1H-azepines is described.

Protein surface roughness accounts for binding free energy of Plasmepsin II-ligand complexes

The calculation of absolute binding affinities for protein-inhibitor complexes remains as one of the main challenges in computational structure-based ligand design. The present work explored the calculations of surface fractal dimension (as a measure of surface roughness) and the relationship with experimental binding free energies of Plasmepsin II complexes. Plasmepsin II is an attractive target for novel therapeutic compounds to treat malaria. However, the structural flexibility of this enzyme is a drawback when searching for specific inhibitors. Concerning that, we performed separate explicitly solvated molecular dynamics simulations using the available high-resolution crystal structures of different Plasmepsin II complexes. Molecular dynamics simulations allowed a better approximation to systems dynamics and, therefore, a more reliable estimation of surface roughness. This constitutes a novel approximation in order to obtain more realistic values of fractal dimension, because previous works considered only x-ray structures. Binding site fractal dimension was calculated considering the ensemble of structures generated at different simulation times. A linear relationship between binding site fractal dimension and experimental binding free energies of the complexes was observed within 20 ns. Previous studies of the subject did not uncover this relationship. Regression model, coined FD model, was built to estimate binding free energies from binding site fractal dimension values. Leave-one-out cross-validation showed that our model reproduced accurately the absolute binding free energies for our training set (R²  = 0.76; <|error|> =0.55 kcal/mol; SD_error  = 0.19 kcal/mol). The fact that such a simple model may be applied raises some questions that are addressed in the article.

Identification of inhibitors of the transmembrane protease FlaK of Methanococcus maripaludis

GxGD‐type intramembrane cleaving proteases (I‐CLiPs) form a family of proteolytic enzymes that feature an aspartate‐based catalytic mechanism. Yet, they structurally and functionally largely differ from the classical pepsin‐like aspartic proteases. Among them are the archaeal enzyme FlaK, processing its substrate FlaB2 during the formation of flagella and γ‐secretase, which is centrally involved in the etiology of the neurodegenerative Alzheimer's disease. We developed an optimized activity assay for FlaK and based on screening of a small in‐house library and chemical synthesis, we identified compound 9 as the first inhibitor of this enzyme. Our results show that this intramembrane protease differs from classical pepsin‐like aspartic proteases and give insights into the substrate recognition of this enzyme. By providing the needed tools to further study the enzymatic cycle of FlaK, our results also enable further studies towards a functional understanding of other GxGD‐type I‐CLiPs.

Fragment-Based Discovery of 2-Aminoquinazolin-4(3H)-ones As Novel Class Nonpeptidomimetic Inhibitors of the Plasmepsins I, II, and IV

2-Aminoquinazolin-4(3H)-ones were identified as a novel class of malaria digestive vacuole plasmepsin inhibitors by using NMR-based fragment screening against Plm II. Initial fragment hit optimization led to a submicromolar inhibitor, which was cocrystallized with Plm II to produce an X-ray structure of the complex. The structure showed that 2-aminoquinazolin-4(3H)-ones bind to the open flap conformation of the enzyme and provided clues to target the flap pocket. Further improvement in potency was achieved via introduction of hydrophobic substituents occupying the flap pocket. Most of the 2-aminoquinazolin-4(3H)-one based inhibitors show a similar activity against digestive Plms I, II, and IV and >10-fold selectivity versus CatD, although varying the flap pocket substituent led to one Plm IV selective inhibitor. In cell-based assays, the compounds show growth inhibition of Plasmodium falciparum 3D7 with IC50 ∼ 1 μM. Together, these results suggest 2-aminoquinazolin-4(3H)-ones as perspective leads for future development of an antimalarial agent.

Privileged Structures Meet Human T-Cell Leukemia Virus-1 (HTLV-1): C2-Symmetric 3,4-Disubstituted Pyrrolidines as Nonpeptidic HTLV-1 Protease Inhibitors

3,4-disubstituted pyrrolidines originally designed to inhibit the closely related HIV-1 protease were evaluated as privileged structures against HTLV-1 protease (HTLV-1 PR). The most potent inhibitor of this series exhibits two-digit nanomolar affinity and represents, to the best of our knowledge, the most potent nonpeptidic inhibitor of HTLV-1 PR described so far. The X-ray structures of two representatives bound to HTLV-1 PR were determined, and the structural basis of their affinity is discussed.

Fighting malaria: structure-guided discovery of nonpeptidomimetic plasmepsin inhibitors

Plasmepsins (Plms) are aspartic proteases involved in the degradation of human hemoglobin by Plasmodium falciparum. Given that the parasite needs the resulting amino acid building blocks for its growth and development, plasmepsins are an important antimalarial drug target. Over the past decade, tremendous progress has been achieved in the development of inhibitors of plasmepsin using two strategies: structure-based drug design (SBDD) and structure-based virtual screening (SBVS). Herein, we review the inhibitors of Plms I-IV developed by SBDD or SBVS with a particular focus on obtaining selectivity versus the human Asp proteases cathepsins and renin and activity in cell-based assays. By use of SBDD, the flap pocket of Plm II has been discovered and constitutes a convenient handle to obtain selectivity. In SBVS, activity against Plms I-IV and selectivity versus cathepsins are not always taken into account. A combination of SBVS, SBDD, and molecular dynamics simulations opens up opportunities for future design cycles.

Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.

Computational methods in drug discovery

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

The aminopeptidase inhibitor CHR-2863 is an orally bioavailable inhibitor of murine malaria

Malaria remains a significant risk in many areas of the world, with resistance to the current antimalarial pharmacopeia an ever-increasing problem. The M1 alanine aminopeptidase (PfM1AAP) and M17 leucine aminopeptidase (PfM17LAP) are believed to play a role in the terminal stages of digestion of host hemoglobin and thereby generate a pool of free amino acids that are essential for parasite growth and development. Here, we show that an orally bioavailable aminopeptidase inhibitor, CHR-2863, is efficacious against murine malaria.

New benzimidazole derivatives as antiplasmodial agents and plasmepsin inhibitors: synthesis and analysis of structure-activity relationships

The newly synthesized benzimidazole compounds were suggested to be inhibitors of Plasmodium falciparum plasmepsin II and human cathepsin D by virtual screening of an internal library of synthetic compounds. This was confirmed by enzyme inhibition studies that gave IC(50) values in the low micromolar range (2-48μM). Ligand docking studies with plasmepsin II predicted binding of benzimidazole compounds at the center of the extended substrate-binding cleft. According to the plausible mode of binding, the pyridine ring of benzimidazole compounds interacted with S1' subsite residues whereas the acetophenone moiety was in contact with S1-S3 subsites of plasmepsin II active center. The benzimidazole derivatives were evaluated for capacity to inhibit the growth of intraerythrocytic P. falciparum in culture. Four benzimidazole compounds inhibited parasite growth at ⩽3μM. The most active compound 10, 1-(4-phenylphenyl)-2[2-(pyridinyl-2-yl)-1,3-benzdiazol-1-yl]ethanone showed an IC(50) of 160nM. The substitution of a phenyl group and a chlorine atom at the para position of the acetophenone moiety were shown to be crucial for antiplasmodial activity.

Computational perspectives into plasmepsins structure-function relationship: implications to inhibitors design

The development of efficient and selective antimalariais remains a challenge for the pharmaceutical industry. The aspartic proteases plasmepsins, whose inhibition leads to parasite death, are classified as targets for the design of potent drugs. Combinatorial synthesis is currently being used to generate inhibitor libraries for these enzymes, and together with computational methodologies have been demonstrated capable for the selection of lead compounds. The high structural flexibility of plasmepsins, revealed by their X-ray structures and molecular dynamics simulations, made even more complicated the prediction of putative binding modes, and therefore, the use of common computational tools, like docking and free-energy calculations. In this review, we revised the computational strategies utilized so far, for the structure-function relationship studies concerning the plasmepsin family, with special focus on the recent advances in the improvement of the linear interaction estimation (LIE) method, which is one of the most successful methodologies in the evaluation of plasmepsin-inhibitor binding affinity.

Identification of plasmepsin inhibitors as selective anti-malarial agents using ligand based drug design

We describe the application of ligand based virtual screening technologies towards the discovery of novel plasmepsin (PM) inhibitors, a family of malarial parasitic aspartyl proteases. Pharmacophore queries were used to screen vendor libraries in search of active and selective compounds. The virtual hits were biologically assessed for activity and selectivity using whole cell Plasmodium falciparum parasites and on target in PM II, PM IV and the closely related human homologue, Cathepsin D assays. Here we report the virtual screening highlights, structures of the hits and their demonstrated biological activity.

Computational analysis of aspartic protease plasmepsin II complexed with EH58 inhibitor: a QM/MM MD study

Plasmepsin (PM) II is one of four enzymes in the food vacuole of Plasmodium falciparum. It has become an attractive target for combating malaria through research regarding its importance in the P. falciparum metabolism and life cycle, making it the target of choice for structure-based drug design. This paper reports the results of hybrid quantum mechanics / molecular mechanics (QM/MM) molecular dynamics (MD) simulations employed to study the details of the interactions established between PM II and N-(3-{(2-benzo[1, 3]dioxol-5-yl-ethyl)[3-(1-methyl-3-oxo-1,3-dihydro-isoindol-2-yl) propionyl]-amino}-1-benzyl-2-(hydroxyl-propyl)-4-benzyloxy-3,5dimethoxy-benzamide (EH58), a well-known potent inhibitor for this enzyme. Electrostatic binding free energy and energy terms decomposition have been computed for PM II complexed with the EH58 inhibitor. The results reveal that there is a strong interaction between Asp34, Val78, Ser79, Tyr192 and Asp214 residues and the EH58 inhibitor. In addition, we have computed the potential of the mean force (PMF) profile in order to assign the protonation state of the two catalytic aspartates in PM II-EH58 complex. The results indicate that the protonation of Asp214 favors a stable active site structure, which is consistent with our electrostatic binding free energy calculation and with previous published works.

Methods for combinatorial and parallel library design

Diversity has historically played a critical role in design of combinatorial libraries, screening sets and corporate collections for lead discovery. Large library design dominated the field in the 1990s with methods ranging anywhere from purely arbitrary through property based reagent selection to product based approaches. In recent years, however, there has been a downward trend in library size. This was due to increased information about the desirable targets gleaned from the genomics revolution and to the ever growing availability of target protein structures from crystallography and homology modeling. Creation of libraries directed toward families of receptors such as GPCRs, kinases, nuclear hormone receptors, proteases, etc., replaced the generation of libraries based primarily on diversity while single target focused library design has remained an important objective. Concurrently, computing grids and cpu clusters have facilitated the development of structure based tools that screen hundreds of thousands of molecules. Smaller "smarter" combinatorial and focused parallel libraries replaced those early un-focused large libraries in the twenty-first century drug design paradigm. While diversity still plays a role in lead discovery, the focus of current library design methods has shifted to receptor based methods, scaffold hopping/bio-isostere searching, and a much needed emphasis on synthetic feasibility. Methods such as "privileged substructures based design" and pharmacophore based design still are important methods for parallel and small combinatorial library design. This chapter discusses some of the possible design methods and presents examples where they are available.

Automated docking screens: a feasibility study

Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 A rmsd 50-60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 A rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org .

Design and discovery of plasmepsin II inhibitors using an automated workflow on large-scale grids

Novel and potent inhibitors of Plasmodium falciparum plasmepsin II were identified by post-processing the results of a docking screening with BEAR, a recently reported procedure for the refinement and rescoring of docked ligands in virtual screening. FRET substrate degradation assays performed on the 30 most promising compounds resulted in 26 inhibitors with IC(50) values ranging from 4.3 nM to 1.8 microM.Herein we report the discovery of novel and potent inhibitors of Plasmodium falciparum plasmepsin II using GRID computing infrastructures. These compounds were identified by post-processing the results of a large docking screen of commercially available compounds using an automated procedure based on molecular dynamics refinement and binding free-energy estimation using MM-PBSA and MM-GBSA. Among the best-scored compounds, four highly populated and promising chemical classes were identified: N-alkoxyamidines, guanidines, amides, and ureas and thioureas. Thirty hit compounds representative of each class were selected on the basis of their favourable binding free energies and molecular interactions with key active site residues. These were experimentally validated using an inhibition assay based on FRET substrate degradation. Remarkably, 26 of the 30 tested compounds proved to be active as plasmepsin II inhibitors, with IC(50) values ranging from 4.3 nM to 1.8 microM.

Plasmodium falciparum neutral aminopeptidases: new targets for anti-malarials

The neutral aminopeptidases M1 alanyl aminopeptidase (PfM1AAP) and M17 leucine aminopeptidase (PfM17LAP) of the human malaria parasite Plasmodium falciparum are targets for the development of novel anti-malarial drugs. Although the functions of these enzymes remain unknown, they are believed to act in the terminal stages of haemoglobin degradation, generating amino acids essential for parasite growth and development. Inhibitors of both enzymes are lethal to P. falciparum in culture and kill the murine malaria P. chabaudi in vivo. Recent biochemical, structural and functional studies provide the substrate specificity and mechanistic binding data needed to guide the development of more potent anti-malarial drugs. Together with biological studies, these data form the rationale for choosing PfM1AAP and PfM17LAP as targets for anti-malarial development.

Virtual screening to identify lead inhibitors for bacterial NAD synthetase (NADs)

Virtual screening was employed to identify new drug-like inhibitors of NAD synthetase (NADs) as antibacterial agents. Four databases of commercially available compounds were docked against three subsites of the NADs active site using FlexX in conjunction with CScore. Over 200 commercial compounds were purchased and evaluated in enzyme inhibition and antibacterial assays. 18 compounds inhibited NADs at or below 100 microM (7.6% hit rate), and two were selected for future SAR studies.