Pharmacological modulation of septins restores calcium homeostasis and is neuroprotective in models of Alzheimer's disease.

Abnormal calcium signaling is a central pathological component of Alzheimer's disease (AD). Here, we describe the identification of a class of compounds called ReS19-T, which are able to restore calcium homeostasis in cell-based models of tau pathology. Aberrant tau accumulation leads to uncontrolled activation of store-operated calcium channels (SOCCs) by remodeling septin filaments at the cell cortex. Binding of ReS19-T to septins restores filament assembly in the disease state and restrains calcium entry through SOCCs. In amyloid-ß and tau-driven mouse models of disease, ReS19-T agents restored synaptic plasticity, normalized brain network activity, and attenuated the development of both amyloid-ß and tau pathology. Our findings identify the septin cytoskeleton as a potential therapeutic target for the development of disease-modifying AD treatments.

Molecule auto-correction to facilitate molecular design.

Ensuring that computationally designed molecules are chemically reasonable is at best cumbersome. We present a molecule correction algorithm that morphs invalid molecular graphs into structurally related valid analogs. The algorithm is implemented as a tree search, guided by a set of policies to minimize its cost. We showcase how the algorithm can be applied to molecular design, either as a post-processing step or as an integral part of molecule generators.

Preventing lipophilic aggregation in cosolvent molecular dynamics simulations with hydrophobic probes using Plumed Automatic Restraining Tool (PART).

Cosolvent molecular dynamics (MD) simulations are molecular dynamics simulations used to identify preferable locations of small organic fragments on a protein target. Most cosolvent molecular dynamics workflows make use of only water-soluble fragments, as hydrophobic fragments would cause lipophilic aggregation. To date the two approaches that allow usage of hydrophobic cosolvent molecules are to use a low (0.2 M) concentration of hydrophobic probes, with the disadvantage of a lower sampling speed, or to use force field modifications, with the disadvantage of a difficult and inflexible setup procedure. Here we present a third alternative, that does not suffer from low sampling speed nor from cumbersome preparation procedures. We have built an easy-to-use open source command line tool PART (Plumed Automatic Restraining Tool) to generate a PLUMED file handling all intermolecular restraints to prevent lipophilic aggregation. We have compared restrained and unrestrained cosolvent MD simulations, showing that restraints are necessary to prevent lipophilic aggregation at hydrophobic probe concentrations of 0.5 M. Furthermore, we benchmarked PART generated restraints on a test set of four proteins (Factor-Xa, HIV protease, P38 MAP kinase and RNase A), showing that cosolvent MD with PART generated restraints qualitatively reproduces binding features of cocrystallised ligands.

Biophysical characterization of the Plasmodium falciparum circumsporozoite protein's N-terminal domain.

The circumsporozoite protein (CSP) is the main surface antigen of the Plasmodium sporozoite (SPZ) and forms the basis of the currently only licensed anti-malarial vaccine (RTS,S/AS01). CSP uniformly coats the SPZ and plays a pivotal role in its immunobiology, in both the insect and the vertebrate hosts. Although CSP's N-terminal domain (CSPN ) has been reported to play an important role in multiple CSP functions, a thorough biophysical and structural characterization of CSPN is currently lacking. Here, we present an alternative method for the recombinant production and purification of CSPN from Plasmodium falciparum (PfCSPN ), which provides pure, high-quality protein preparations with high yields. Through an interdisciplinary approach combining in-solution experimental methods and in silico analyses, we provide strong evidence that PfCSPN is an intrinsically disordered region displaying some degree of compaction.

Highly Selective Inhibitors of Dipeptidyl Peptidase 9 (DPP9) Derived from the Clinically Used DPP4-Inhibitor Vildagliptin.

Dipeptidyl peptidase 9 (DPP9) is a proline-selective serine protease that plays a key role in NLRP1- and CARD8-mediated inflammatory cell death (pyroptosis). No selective inhibitors have hitherto been reported for the enzyme: all published molecules have grossly comparable affinities for DPP8 and 9 because of the highly similar architecture of these enzymes' active sites. Selective DPP9 inhibitors would be highly instrumental to address unanswered research questions on the enzyme's role in pyroptosis, and they could also be investigated as therapeutics for acute myeloid leukemias. Compounds presented in this manuscript (42 and 47) combine low nanomolar DPP9 affinities with unprecedented DPP9-to-DPP8 selectivity indices up to 175 and selectivity indices >1000 toward all other proline-selective proteases. To rationalize experimentally obtained data, a molecular dynamics study was performed. We also provide in vivo pharmacokinetics data for compound 42.

A molecule perturbation software library and its application to study the effects of molecular design constraints.

Computational molecular design can yield chemically unreasonable compounds when performed carelessly. A popular strategy to mitigate this risk is mimicking reference chemistry. This is commonly achieved by restricting the way in which molecules are constructed or modified. While it is well established that such an approach helps in designing chemically appealing molecules, concerns about these restrictions impacting chemical space exploration negatively linger. In this work we present a software library for constrained graph-based molecule manipulation and showcase its functionality by developing a molecule generator. Said generator designs molecules mimicking reference chemical features of differing granularity. We find that restricting molecular construction lightly, beyond the usual positive effects on drug-likeness and synthesizability of designed molecules, provides guidance to optimization algorithms navigating chemical space. Nonetheless, restricting molecular construction excessively can indeed hinder effective chemical space exploration.

From PERK to RIPK1: Design, synthesis and evaluation of novel potent and selective necroptosis inhibitors.

Receptor-Interacting serine/threonine-Protein Kinase 1 (RIPK1) emerged as an important driver of inflammation and, consequently, inflammatory pathologies. The enzymatic activity of RIPK1 is known to indirectly promote inflammation by triggering cell death, in the form of apoptosis, necroptosis and pyroptosis. Small molecule Receptor-Interacting serine/threonine-Protein Kinase 1 inhibitors have therefore recently entered clinical trials for the treatment of a subset of inflammatory pathologies. We previously identified GSK2656157 (GSK'157), a supposedly specific inhibitor of protein kinase R (PKR)-like ER kinase (PERK), as a much more potent type II Receptor-Interacting serine/threonine-Protein Kinase 1 inhibitor. We now performed further structural optimisation on the GSK'157 scaffold in order to develop a novel class of more selective Receptor-Interacting serine/threonine-Protein Kinase 1 inhibitors. Based on a structure-activity relationship (SAR) reported in the literature, we anticipated that introducing a substituent on the para-position of the pyridinyl ring would decrease the interaction with PERK. Herein, we report a series of novel GSK'157 analogues with different para-substituents with increased selectivity for Receptor-Interacting serine/threonine-Protein Kinase 1. The optimisation led to UAMC-3861 as the best compound of this series in terms of activity and selectivity for Receptor-Interacting serine/threonine-Protein Kinase 1 over PERK. The most selective compounds were screened in vitro for their ability to inhibit RIPK1-dependent apoptosis and necroptosis. With this work, we successfully synthesised a novel series of potent and selective type II Receptor-Interacting serine/threonine-Protein Kinase 1 inhibitors based on the GSK'157 scaffold.

Vildagliptin-Derived Dipeptidyl Peptidase 9 (DPP9) Inhibitors: Identification of a DPP8/9-Specific Lead.

Vildagliptin is a marketed DPP4 inhibitor, used in the management of type 2 diabetes. The molecule also has notable DPP8/9 affinity, with some preference for DPP9. Therefore, we aimed to use vildagliptin as a starting point for selective DPP8/9 inhibitors, and to engineer out the parent compound's DPP4-affinity. In addition, we wanted to identify substructures in the obtained molecules that allow their further optimization into inhibitors with maximal DPP9 selectivity. Various 2S-cyanopyrrolidines and isoindoline were investigated as P1 residues of vildagliptin analogs. The obtained set was expanded with derivatives bearing O-substituted, N-(3-hydroxyadamantyl)glycine moieties at the P2 position. In this way, representatives were discovered with DPP8/9 potencies comparable to the parent molecule, but with overall selectivity towards DPP4, DPP2, FAP, and PREP. Furthermore, the most promising molecules in this series have a 4- to 7-fold preference for DPP9 over DPP8. Finally, a molecular dynamics study was carried out to maximize our insight into experimental selectivity data.

Genomic and Phenotypic Characterization of Experimentally Selected Resistant Leishmania donovani Reveals a Role for Dynamin-1-Like Protein in the Mechanism of Resistance to a Novel Antileishmanial Compound.

The implementation of prospective drug resistance (DR) studies in the research-and-development (R&D) pipeline is a common practice for many infectious diseases but not for neglected tropical diseases (NTDs). Here, we explored and demonstrated the importance of this approach using as paradigms Leishmania donovani, the etiological agent of visceral leishmaniasis (VL), and TCMDC-143345, a promising compound of the GlaxoSmithKline (GSK) "Leishbox" to treat VL. We experimentally selected resistance to TCMDC-143345 in vitro and characterized resistant parasites at the genomic and phenotypic levels. We found that it took more time to develop resistance to TCMDC-143345 than to other drugs in clinical use and that there was no cross-resistance to these drugs, suggesting a new and unique mechanism. By whole-genome sequencing, we found two mutations in the gene encoding the L. donovani dynamin-1-like protein (LdoDLP1) that were fixed at the highest drug pressure. Through phylogenetic analysis, we identified LdoDLP1 as a family member of the dynamin-related proteins, a group of proteins that impacts the shapes of biological membranes by mediating fusion and fission events, with a putative role in mitochondrial fission. We found that L. donovani lines genetically engineered to harbor the two identified LdoDLP1 mutations were resistant to TCMDC-143345 and displayed altered mitochondrial properties. By homology modeling, we showed how the two LdoDLP1 mutations may influence protein structure and function. Taken together, our data reveal a clear involvement of LdoDLP1 in the adaptation/reduced susceptibility of L. donovani to TCMDC-143345. IMPORTANCE Humans and their pathogens are continuously locked in a molecular arms race during which the eventual emergence of pathogen drug resistance (DR) seems inevitable. For neglected tropical diseases (NTDs), DR is generally studied retrospectively once it has already been established in clinical settings. We previously recommended to keep one step ahead in the host-pathogen arms race and implement prospective DR studies in the R&D pipeline, a common practice for many infectious diseases but not for NTDs. Here, using Leishmania donovani, the etiological agent of visceral leishmaniasis (VL), and TCMDC-143345, a promising compound of the GSK Leishbox to treat VL, as paradigms, we experimentally selected resistance to the compound and proceeded to genomic and phenotypic characterization of DR parasites. The results gathered in the present study suggest a new DR mechanism involving the L. donovani dynamin-1-like protein (LdoDLP1) and demonstrate the practical relevance of prospective DR studies.

LEADD: Lamarckian evolutionary algorithm for de novo drug design.

Given an objective function that predicts key properties of a molecule, goal-directed de novo molecular design is a useful tool to identify molecules that maximize or minimize said objective function. Nonetheless, a common drawback of these methods is that they tend to design synthetically unfeasible molecules. In this paper we describe a Lamarckian evolutionary algorithm for de novo drug design (LEADD). LEADD attempts to strike a balance between optimization power, synthetic accessibility of designed molecules and computational efficiency. To increase the likelihood of designing synthetically accessible molecules, LEADD represents molecules as graphs of molecular fragments, and limits the bonds that can be formed between them through knowledge-based pairwise atom type compatibility rules. A reference library of drug-like molecules is used to extract fragments, fragment preferences and compatibility rules. A novel set of genetic operators that enforce these rules in a computationally efficient manner is presented. To sample chemical space more efficiently we also explore a Lamarckian evolutionary mechanism that adapts the reproductive behavior of molecules. LEADD has been compared to both standard virtual screening and a comparable evolutionary algorithm using a standardized benchmark suite and was shown to be able to identify fitter molecules more efficiently. Moreover, the designed molecules are predicted to be easier to synthesize than those designed by other evolutionary algorithms.

Assessment of the Fragment Docking Program SEED.

The fragment docking program solvation energy for exhaustive docking (SEED) is evaluated on 15 different protein targets, with a focus on enrichment and the hit rate. It is shown that SEED allows for consistent computational enrichment of fragment libraries, independent of the effective hit rate. Depending on the actual target protein, true positive rates ranging up to 27% are observed at a cutoff value corresponding to the experimental hit rate. The impact of variations in docking protocols and energy filters is discussed in detail. Remaining issues, limitations, and use cases of SEED are also discussed. Our results show that fragment library selection or enhancement for a particular target is likely to benefit from docking with SEED, suggesting that SEED is a useful resource for fragment screening campaigns. A workflow is presented for the use of the program in virtual screening, including filtering and postprocessing to optimize hit rates.

A Computational and Modeling Study of the Reaction Mechanism of Staphylococcus aureus Monoglycosyltransferase Reveals New Insights on the GT51 Family of Enzymes.

Bacterial glycosyltransferases of the GT51 family are key enzymes in bacterial cell wall synthesis. Inhibiting cell wall synthesis is a very effective approach for development of antibiotics, as this can lead to either bacteriostatic or bactericidal effects. Even though the existence of this family has been known for over 50 years, only one potent inhibitor exists, which is an analog of the lipid IV product and derived from a natural product. Drug development focused on bacterial transglycosylase has been hampered due to little being know about its structure and reaction mechanism. In this study, Staphylococcus aureus monoglycosyltransferase was investigated at an atomistic level using computational methods. Classical molecular dynamics simulations were used to reveal information about the large-scale dynamics of the enzyme-substrate complex and the importance of magnesium in structure and function of the protein, while mixed mode quantum mechanics/molecular mechanics calculations unveiled a novel hypothesis for the reaction mechanism. From these results, we present a new model for the binding mode of lipid II and the reaction mechanism of the GT51 glycosyltransferases. A metal-bound hydroxide catalyzed reaction mechanism yields an estimated free energy barrier of 16.1 ± 1.0 kcal/mol, which is in line with experimental values. The importance of divalent cations is also further discussed. These findings could significantly aid targeted drug design, particularly the efficient development of transition state analogues as potential inhibitors for the GT51 glycosyltransferases.

Novel Small Molecule-Derived, Highly Selective Substrates for Fibroblast Activation Protein (FAP).

Fibroblast activation protein (FAP) is a proline-selective serine protease. It is hardly expressed in healthy adult tissue but upregulated in tissue remodeling sites associated with several diseases including epithelial cancer types, atherosclerosis, arthritis and fibrosis. Ongoing research aims at clinical implementation of FAP as a biomarker for these diseases. Several immunochemical methods that quantify FAP expression have been reported. An alternative/complementary approach focuses on quantification of FAP's enzymatic activity. Developing an activity-based assay for FAP has nonetheless proven challenging because of selectivity issues with respect to prolyl oligopeptidase (PREP). Here, we present substrate-type FAP probes that are structurally derived from a FAP-inhibitor (UAMC1110) that we published earlier. Both cleavage efficiency and FAP-selectivity of the best compounds in the series equal or surpass the most advanced peptide-based FAP substrates reported to date. Finally, proof-of-concept is provided that 4-aminonaphthol containing probes can spatially localize FAP activity in biological samples.

Efforts towards an On-Target Version of the Groebke-Blackburn-Bienaymé (GBB) Reaction for Discovery of Druglike Urokinase (uPA) Inhibitors.

Target-guided synthesis (TGS) has emerged as a promising strategy in drug discovery. Although reported examples of TGS generally involve two-component reactions, there is a strong case for developing target-guided versions of three-component reactions (3CRs) because of their potential to deliver highly diversified druglike molecules. To this end, the Groebke-Blackburn-Bienaymé reaction was selected as a model 3CR. We recently reported a series of druglike urokinase inhibitors, and these serve as reference compounds in the present study. Due to the limited number of literature reports on target-guided 3CRs, multiple experimental parameters were optimized here. Most challenging was the formation of imine intermediates under near-physiological conditions. This aspect was addressed by exploring chemical imine stabilization strategies. Notably, imines are also crucial intermediates of other 3CRs. Such systematic studies are strongly required for further development of the TGS domain but are largely absent in the literature. Hence, this work is intended as a reference for future multicomponent-based TGS studies.

ClpP Protease, a Promising Antimicrobial Target.

The caseinolytic protease proteolytic subunit (ClpP) is a serine protease playing an important role in proteostasis of eukaryotic organelles and prokaryotic cells. Alteration of ClpP function has been proved to affect the virulence and infectivity of a number of pathogens. Increased bacterial resistance to antibiotics has become a global problem and new classes of antibiotics with novel mechanisms of action are needed. In this regard, ClpP has emerged as an attractive and potentially viable option to tackle pathogen fitness without suffering cross-resistance to established antibiotic classes and, when not an essential target, without causing an evolutionary selection pressure. This opens a greater window of opportunity for the host immune system to clear the infection by itself or by co-administration with commonly prescribed antibiotics. A comprehensive overview of the function, regulation and structure of ClpP across the different organisms is given. Discussion about mechanism of action of this protease in bacterial pathogenesis and human diseases are outlined, focusing on the compounds developed in order to target the activation or inhibition of ClpP.

Molecular Dynamics Simulations of Membrane Proteins: An Overview.

Simulations of membrane proteins have been rising in popularity in the past decade. Advancements in technology and force fields made it possible to simulate behavior of membrane proteins. Membrane protein simulations can now be used as supporting evidence for experimental findings, for elucidating protein mechanisms, and validating protein crystal structures. Unrelated to experimental data, these simulations can also serve to investigate larger scale processes like protein sorting, protein-membrane interactions, and more. In this review, the history as well as the state-of-the-art methodologies in membrane protein simulations will be summarized. An emphasis will be put on how to set up the system and on the current models for the different components of the simulation system. An overview of the available tools for membrane protein simulation will be given, and current limitations and prospects will also be discussed.

Discovery of Novel, Drug-Like Ferroptosis Inhibitors with in Vivo Efficacy.

Ferroptosis is an iron-catalyzed, nonapoptotic form of regulated necrosis that results in oxidative lipid damage in cell membranes that can be inhibited by the radical-trapping antioxidant Ferrostatin-1 (Fer-1). Novel inhibitors derived from the Fer-1 scaffold inhibited ferroptosis potently but suffered from solubility issues. In this paper, we report the synthesis of a more stable and readily soluble series of Fer-1 analogues that potently inhibit ferroptosis. The most promising compounds (37, 38, and 39) showed an improved protection compared to Fer-1 against multiorgan injury in mice. No toxicity was observed in mice after daily injection of 39 (UAMC-3203) for 4 weeks. UAMC-3203 inserts rapidly in a phospholipid bilayer in silico, which aligns with the current understanding of the mechanism of action of these compounds. In conclusion, these analogues have superior properties compared to Fer-1, show in vivo efficacy, and represent novel lead compounds with therapeutic potential in relevant ferroptosis-driven disease models.

Author Correction: Virtual screening for inhibitors of the human TSLP:TSLPR interaction.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Spectrophores as one-dimensional descriptors calculated from three-dimensional atomic properties: applications ranging from scaffold hopping to multi-target virtual screening.

Spectrophores are novel descriptors that are calculated from the three-dimensional atomic properties of molecules. In our current implementation, the atomic properties that were used to calculate spectrophores include atomic partial charges, atomic lipophilicity indices, atomic shape deviations and atomic softness properties. This approach can easily be widened to also include additional atomic properties. Our novel methodology finds its roots in the experimental affinity fingerprinting technology developed in the 1990's by Terrapin Technologies. Here we have translated it into a purely virtual approach using artificial affinity cages and a simplified metric to calculate the interaction between these cages and the atomic properties. A typical spectrophore consists of a vector of 48 real numbers. This makes it highly suitable for the calculation of a wide range of similarity measures for use in virtual screening and for the investigation of quantitative structure-activity relationships in combination with advanced statistical approaches such as self-organizing maps, support vector machines and neural networks. In our present report we demonstrate the applicability of our novel methodology for scaffold hopping as well as virtual screening.