Bestatin is a non-competitive inhibitor of porcine M1 family glutamyl aminopeptidase: Insights for selective inhibitor design

Glutamyl aminopeptidase (APA) is an M1 family membrane-bound ectoenzyme that is a target for the development of antihypertensive and anticancer agents. Bestatin is a natural product described as a classical inhibitor of metallo-aminopeptidases. Although the IC50 value of bestatin vs human APA has been reported, the mechanism of inhibition is unknown. In the present contribution, we demonstrated that bestatin is a non-competitive (α>1) inhibitor of porcine APA (pAPA), with a Ki value of 31.59 µM (α=3.7). A model of the bestatin-pAPA complex predicted that bestatin binds to pAPA similarly to porcine aminopeptidase N (pAPN). The interaction involved catalytic and chelating residues conserved in the M1 family. Additionally, a salt bridge with R877 and a hydrogen bond interaction with T346, both key residues for APA specificity for N-terminal acidic residues were identified. These residues and E213, which forms a hydrogen bond interaction with bestatin, are not conserved in human and porcine APN. The extension of the in silico analysis to amastatin and bestatin analogs probestin, and phebestin, which are APA inhibitors, indicated that they may interact with the same residues. The results indicate that bestatin analogues currently reported to inhibit APN are dual inhibitors of APA and APN and that some APA residues could be targeted to improve inhibitor selectivity

Identification and Validation of Compounds Targeting Leishmania major Leucyl-Aminopeptidase M17

Leishmaniasis is a neglected tropical disease; there is currently no vaccine and treatment is reliant upon a handful of drugs suffering from multiple issues including toxicity and resistance. There is a critical need for development of new fit-for-purpose therapeutics, with reduced toxicity and targeting new mechanisms to overcome resistance. One enzyme meriting investigation as a potential drug target in Leishmania is M17 leucyl-aminopeptidase (LAP). Here, we aimed to chemically validate LAP as a drug target in L. major through identification of potent and selective inhibitors. Using RapidFire mass spectrometry, the compounds DDD00057570 and DDD00097924 were identified as selective inhibitors of recombinant Leishmania major LAP activity. Both compounds inhibited in vitro growth of L. major and L. donovani intracellular amastigotes, and overexpression of LmLAP in L. major led to reduced susceptibility to DDD00057570 and DDD00097924, suggesting that these compounds specifically target LmLAP. Thermal proteome profiling revealed that these inhibitors thermally stabilized two M17 LAPs, indicating that these compounds selectively bind to enzymes of this class. Additionally, the selectivity of the inhibitors to act on LmLAP and not against the human ortholog was demonstrated, despite the high sequence similarities LAPs of this family share. Collectively, these data confirm LmLAP as a promising therapeutic target for Leishmania spp. that can be selectively inhibited by drug-like small molecules.</p

Discovery of potent and selective inhibitors of the Escherichia coli M1-aminopeptidase via multicomponent solid-phase synthesis of tetrazole-peptidomimetics

The Escherichia coli neutral M1-aminopeptidase (ePepN) is a novel target identified for the development of antimicrobials. Here we describe a solid-phase multicomponent approach which enabled the discovery of potent ePepN inhibitors. The on-resin protocol, developed in the frame of the Distributed Drug Discovery (D3) program, comprises the implementation of parallel Ugi-azide four-component reactions with resin-bound amino acids, thus leading to the rapid preparation of a focused library of tetrazole-peptidomimetics (TPMs) suitable for biological screening. By dose-response studies, three compounds were identified as potent and selective ePepN inhibitors, as little inhibitory effect was exhibited for the porcine ortholog aminopeptidase. The study allowed for the identification of the key structural features required for a high ePepN inhibitory activity. The most potent and selective inhibitor (TPM 11) showed a non-competitive inhibition profile of ePepN. We predicted that both diastereomers of compound TPM 11 bind to a site distinct from that occupied by the substrate. Theoretical models suggested that TPM 11 has an alternative inhibition mechanism that doesn't involve Zn coordination. On the other hand, the activity landscape analysis provided a rationale for our findings. Of note, compound TMP 2 showed in vitro antibacterial activity against Escherichia coli. Furthermore, none of the three identified inhibitors is a potent haemolytic agent, and only two compounds showed moderate cytotoxic activity toward the murine myeloma P3X63Ag cells. These results point to promising compounds for the future development of rationally designed TPMs as antibacterial agents

AMDock: a versatile graphical tool for assisting molecular docking with Autodock Vina and Autodock4

Abstract AMDock (Assisted Molecular Docking) is a user-friendly graphical tool to assist in the docking of protein-ligand complexes using Autodock Vina and AutoDock4, including the option of using the Autodock4Zn force field for metalloproteins. AMDock integrates several external programs (Open Babel, PDB2PQR, AutoLigand, ADT scripts) to accurately prepare the input structure files and to optimally define the search space, offering several alternatives and different degrees of user supervision. For visualization of molecular structures, AMDock uses PyMOL, starting it automatically with several predefined visualization schemes to aid in setting up the box defining the search space and to visualize and analyze the docking results. One particularly useful feature implemented in AMDock is the off-target docking procedure that allows to conduct ligand selectivity studies easily. In summary, AMDock’s functional versatility makes it a very useful tool to conduct different docking studies, especially for beginners. The program is available, either for Windows or Linux, at https://github.com/Valdes-Tresanco-MS . Reviewers This article was reviewed by Alexander Krah and Thomas Gaillard

Identifying Potential Molecular Targets in Fungi Based on (Dis)Similarities in Binding Site Architecture with Proteins of the Human Pharmacolome

Invasive fungal infections represent a public health problem that worsens over the years with the increasing resistance to current antimycotic agents. Therefore, there is a compelling medical need of widening the antifungal drug repertoire, following different methods such as drug repositioning, identification and validation of new molecular targets and developing new inhibitors against these targets. In this work we developed a structure-based strategy for drug repositioning and new drug design, which can be applied to infectious fungi and other pathogens. Instead of applying the commonly accepted off-target criterion to discard fungal proteins with close homologues in humans, the core of our approach consists in identifying fungal proteins with active sites that are structurally similar, but preferably not identical to binding sites of proteins from the so-called “human pharmacolome”. Using structural information from thousands of human protein target-inhibitor complexes, we identified dozens of proteins in fungal species of the genera Histoplasma, Candida, Cryptococcus, Aspergillus and Fusarium, which might be exploited for drug repositioning and, more importantly, also for the design of new fungus-specific inhibitors. As a case study, we present the in vitro experiments performed with a set of selected inhibitors of the human mitogen-activated protein kinases 1/2 (MEK1/2), several of which showed a marked cytotoxic activity in different fungal species

Origin of the Phosphoprotein Phosphatase (PPP) sequence family in Bacteria: Critical ancestral sequence changes, radiation patterns and substrate binding features

Background: Phosphoprotein phosphatases (PPP) belong to the PPP Sequence family, which in turn belongs to the broader metallophosphoesterase (MPE) superfamily. The relationship between the PPP Sequence family and other members of the MPE superfamily remains unresolved, in particular what transitions took place in an ancestral MPE to ultimately produce the phosphoprotein specific phosphatases (PPPs). Methods: We use structural and sequence alignment data, phylogenetic tree analysis, sequence signature (Weblogo) analysis, in silico protein-peptide modeling data, and in silico mutagenesis to trace a likely route of evolution from MPEs to the PPP Sequence family. Hidden Markov Model (HMM) based iterative database search strategies were utilized to identify PPP Sequence Family members from numerous bacterial groups. Results: Using Mre11 as proxy for an ancestral nuclease-like MPE we trace a possible evolutionary route that alters a single active site substrate binding His-residue to yield a new substrate binding accessory, the “2-Arg-Clamp”. The 2-Arg-Clamp is not found in MPEs, but is present in all PPP Sequence family members, where the phosphomonesterase reaction predominates. Variation in position of the clamp arginines and a supplemental sequence loop likely provide substrate specificity for each PPP Sequence family group. Conclusions: Loss of a key substrate binding His-in MPEs opened the path to bind novel substrates and evolution of the 2-Arg-Clamp, a sequence change seen in both bacterial and eukaryotic phosphoprotein phosphatases.General significance: We establish a likely evolutionary route from nuclease-like MPE to PPP Sequence family enzymes, that includes the phosphoprotein phosphatases

AMDock: a versatile graphical tool for assisting molecular docking with Autodock Vina and Autodock4

AMDock (Assisted Molecular Docking) is a user-friendly graphical tool to assist in the docking of protein-ligand complexes using Autodock Vina and AutoDock4, including the option of using the Autodock4Zn force field for metalloproteins. AMDock integrates several external programs (Open Babel, PDB2PQR, AutoLigand, ADT scripts) to accurately prepare the input structure files and to optimally define the search space, offering several alternatives and different degrees of user supervision. For visualization of molecular structures, AMDock uses PyMOL, starting it automatically with several predefined visualization schemes to aid in setting up the box defining the search space and to visualize and analyze the docking results. One particularly useful feature implemented in AMDock is the off-target docking procedure that allows to conduct ligand selectivity studies easily. In summary, AMDock's functional versatility makes it a very useful tool to conduct different docking studies, especially for beginners. The program is available, either for Windows or Linux, at https://github.com/Valdes-Tresanco-MS . REVIEWERS: This article was reviewed by Alexander Krah and Thomas Gaillard