Finding a better path to drug selectivity

Discovery and optimization of isoliquiritigenin as a death-associated protein kinase 1 inhibitor

Death-associated protein kinase 1 (DAPK1) is a phosphotransferase in the serine/threonine kinase family. Inhibiting DAPK1 is expected to be beneficial in treating Alzheimer's disease and protecting neuronal cells during cerebral ischemia. In this study, we demonstrated that the natural chalcone isoliquiritigenin inhibits DAPK1 in an ATP-competitive manner, and we synthesized halogen derivatives to amplify the inhibitory effect. Among the compounds tested, the chlorine, bromine, and iodine derivatives exhibited high DAPK1 inhibitory activity and binding affinity. Crystal structure analysis revealed that this improvement is attributable to the halogen atoms fitting well into the hydrophobic pocket formed by I77, L93, and I160. In particular, the chlorine derivative showed a significant enthalpic contribution to the interaction with DAPK1, suggesting its potential as a primary compound for new DAPK1 inhibitors.

3-O-Methyltolcapone and Its Lipophilic Analogues Are Potent Inhibitors of Transthyretin Amyloidogenesis with High Permeability and Low Toxicity

Transthyretin (TTR) is an amyloidogenic homotetramer involved in the transport of thyroxine in blood and cerebrospinal fluid. To date, more than 130 TTR point mutations are known to destabilise the TTR tetramer, leading to its extracellular pathological aggregation accumulating in several organs, such as heart, peripheral and autonomic nerves, and leptomeninges. Tolcapone is an FDA-approved drug for Parkinson's disease that has been repurposed as a TTR stabiliser. We characterised 3-O-methyltolcapone and two newly synthesized lipophilic analogues, which are expected to be protected from the metabolic glucuronidation that is responsible for the lability of tolcapone in the organism. Immunoblotting assays indicated the high degree of TTR stabilisation, coupled with binding selectivity towards TTR in diluted plasma of 3-O-methyltolcapone and its lipophilic analogues. Furthermore, in vitro toxicity data showed their several-fold improved neuronal and hepatic safety compared to tolcapone. Calorimetric and structural data showed that both T4 binding sites of TTR are occupied by 3-O-methyltolcapone and its lipophilic analogs, consistent with an effective TTR tetramer stabilisation. Moreover, in vitro permeability studies showed that the three compounds can effectively cross the blood-brain barrier, which is a prerequisite for the inhibition of TTR amyloidogenesis in the cerebrospinal fluid. Our data demonstrate the relevance of 3-O-methyltolcapone and its lipophilic analogs as potent inhibitors of TTR amyloidogenesis.

Fast fragment and compound screening pipeline at the Swiss Light Source

Crystallography-based fragment screening is a highly effective technique employed in structure-based drug discovery to expand the range of lead development opportunities. It allows screening and sorting of weakly binding, low molecular mass fragments, which can be developed into larger high-affinity lead compounds. Technical improvements at synchrotron beamlines, design of innovative libraries mapping chemical space efficiently, effective soaking methods and enhanced data analysis have enabled the implementation of high-throughput fragment screening pipelines at multiple synchrotron facilities. This widened access to CBFS beyond the pharma industry has allowed academic users to rapidly screen large quantities of fragment-soaked protein crystals. The positive outcome of a CBFS campaign is a set of structures that present the three-dimensional arrangement of fragment-protein complexes in detail, thereby providing information on the location and the mode of interaction of bound fragments. Through this review, we provide users with a comprehensive guide that sets clear expectations before embarking on a crystallography-based fragment screening campaign. We present a list of essential pre-requirements that must be assessed, including the suitability of your current crystal system for a fragment screening campaign. Furthermore, we extensively discuss the available methodological options, addressing their limitations and providing strategies to overcome them. Additionally, we provide a brief perspective on how to proceed once hits are obtained. Notably, we emphasize the solutions we have implemented for instrumentation and software development within our Fast Fragment and Compound Screening pipeline. We also highlight third-party software options that can be utilized for rapid refinement and hit assessment.

Characterization of the molecular interactions between resveratrol derivatives and death-associated protein kinase 1

Death-associated protein kinase 1 (DAPK1), a Ca2+/calmodulin-regulated serine/threonine kinase, regulates cell apoptosis and autophagy and has been implicated in the pathogenesis of Alzheimer's disease (AD). Targeting DAPK1 may be a promising approach for treating AD. In our previous study, we found that a natural polyphenol, resveratrol (1), is a moderate DAPK1 inhibitor. In the present study, we investigated the interactions between natural and synthetic derivatives of 1 and DAPK1. Binding assays including intrinsic fluorescence quenching, protein thermal shift and isothermal titration calorimetry indicated that oxyresveratrol (3), a hydroxylated derivative, and pinostilbene (5), a methoxylated derivative, bind to DAPK1 with comparable affinity to 1. The enzymatic assay showed that 3 more effectively inhibits the intrinsic ATPase activity of DAPK1 compared with 1. Crystallographic analysis revealed that the binding modes of the methoxylated derivatives were different from those of 1 and 3, resulting in a unique interaction. Our results suggest that 3 may be helpful in treating AD and provide a clue for the development of promising DAPK1 inhibitors.

Today's drug discovery and the shadow of the rule of 5

INTRODUCTION

The rule of 5 developed by Lipinski et al., a landmark and prescient piece of scholarship, focused the minds of drug hunters by systematically characterizing the physical make-up of drug molecules for the first time, noting many sub-optimal compounds identified by high-throughput screening practices. Its profound influence on thinking and practices, whilst providing benefit, perhaps etched the guidelines too strongly in the minds of some drug hunters who applied the bounds too literally without understanding the implications of the underlying statistics.

AREAS COVERED

This opinion is based on recent key developments that take thinking, measurements, and standards beyond those first set out, particularly the influences of molecular weight and the understanding, measurement, and calculation of lipophilicity.

EXPERT OPINION

Techniques and technologies for physicochemical estimations set new standards. It is timely to celebrate the significance and influence of the rule of 5, whilst taking thinking to new levels with better characterizations. The shadow of the rule of 5 may be long, but it is not dark, as new measurements, predictions and principles emerge as guiding lights in the design and prioritization of higher-quality molecules redefining the meaning of beyond the rule of 5.

New Insights on the Activity and Selectivity of MAO-B Inhibitors through In Silico Methods

To facilitate the identification of novel MAO-B inhibitors, we elaborated a consolidated computational approach, including a pharmacophoric atom-based 3D quantitative structure-activity relationship (QSAR) model, activity cliffs, fingerprint, and molecular docking analysis on a dataset of 126 molecules. An AAHR.2 hypothesis with two hydrogen bond acceptors (A), one hydrophobic (H), and one aromatic ring (R) supplied a statistically significant 3D QSAR model reflected by the parameters: R² = 0.900 (training set); Q² = 0.774 and Pearson's R = 0.884 (test set), stability s = 0.736. Hydrophobic and electron-withdrawing fields portrayed the relationships between structural characteristics and inhibitory activity. The quinolin-2-one scaffold has a key role in selectivity towards MAO-B with an AUC of 0.962, as retrieved by ECFP4 analysis. Two activity cliffs showing meaningful potency variation in the MAO-B chemical space were observed. The docking study revealed interactions with crucial residues TYR:435, TYR:326, CYS:172, and GLN:206 responsible for MAO-B activity. Molecular docking is in consensus with and complementary to pharmacophoric 3D QSAR, ECFP4, and MM-GBSA analysis. The computational scenario provided here will assist chemists in quickly designing and predicting new potent and selective candidates as MAO-B inhibitors for MAO-B-driven diseases. This approach can also be used to identify MAO-B inhibitors from other libraries or screen top molecules for other targets involved in suitable diseases.

Biophysical Approaches for the Characterization of Protein-Metabolite Interactions

With an estimate of hundred thousands of protein molecules per cell and the number of metabolites several orders of magnitude higher, protein-metabolite interactions are omnipresent. In vitro analyses are one of the main pillars on the way to establish a solid understanding of how these interactions contribute to maintaining cellular homeostasis. A repertoire of biophysical techniques is available by which protein-metabolite interactions can be quantitatively characterized in terms of affinity, specificity, and kinetics in a broad variety of solution environments. Several of those provide information on local or global conformational changes of the protein partner in response to ligand binding. This review chapter gives an overview of the state-of-the-art biophysical toolbox for the study of protein-metabolite interactions. It briefly introduces basic principles, highlights recent examples from the literature, and pinpoints promising future directions.

Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization

Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying "magic bullets" amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand-target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural-energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.

Tailored Parameterization of the LIE Method for Calculating the Binding Free Energy of Vps34-Inhibitor Complexes

Vps34 is the only isoform of the PI3K family in fungi, making this protein an attractive target to develop new treatments against pathogenic fungi. The high structural similarity between the active sites of the human and fungal Vps34 makes repurposing of human Vps34 inhibitors an appealing strategy. Nonetheless, while some of the cross-reactive inhibitors might have the potential to treat fungal infections, a safer approach to prevent undesired side effects would be to identify molecules that specifically inhibit the fungal Vps34. This study presents the parameterization of four LIE models for estimating the binding free energy of Vps34-inhibitor complexes. Two models are parameterized using a multiparametric linear regression leaving one or more free parameters, while the other two are based on the LIE-D model. All of the models show good predictive capacity (R ² > 0.7, r > 0.85) and a low mean absolute error (MAE < 0.71 kcal/mol). The current study highlights the advantages of LIE-D-derived models when predicting the weight of the different contributions to the binding free energy. It is expected that this study will provide researchers with a valuable tool to identify new Vps34 inhibitors for relevant applications such as cancer treatment and the development of new antimicrobial agents.

A chalcone derivative suppresses TSLP induction in mice and human keratinocytes through binding to BET family proteins

Although treatments for allergic diseases have improved, side effects and treatment resistance remain as challenges. New therapeutic drugs for allergic diseases are urgently required. Thymic stromal lymphopoietin (TSLP) is a cytokine target for prevention and treatment of allergic diseases. Since TSLP is produced from epithelial cells in allergic diseases, TSLP inhibitors may be new anti-allergic drugs. We previously identified a new inhibitor of TSLP production, named 16D10. However, its target of action remained unclarified. In this study, we found proteins binding to 16D10 from 24,000 human protein arrays by AlphaScreen-based high-throughput screening and identified bromodomain and extra-terminal (BET) family proteins as targets. We also clarified the detailed mode of interaction between 16D10 and a BET family protein using X-ray crystallography. Furthermore, we confirmed that inhibitors of BET family proteins suppressed TSLP induction and IL-33 and IL-36γ expression in both mouse and human keratinocyte cell lines. Taken together, our findings suggest that BET family proteins are involved in the suppression of TSLP production by 16D10. These proteins can contribute to the pathology of atopic dermatitis via TSLP regulation in keratinocytes and have potential as therapeutic targets in allergic diseases.

Efficient Entropy-Driven Inhibition of Dipeptidyl Peptidase III by Hydroxyethylene Transition-State Peptidomimetics

Dipeptidyl peptidase III (DPP3) is a ubiquitously expressed Zn‐dependent protease, which plays an important role in regulating endogenous peptide hormones, such as enkephalins or angiotensins. In previous biophysical studies, it could be shown that substrate binding is driven by a large entropic contribution due to the release of water molecules from the closing binding cleft. Here, the design, synthesis and biophysical characterization of peptidomimetic inhibitors is reported, using for the first time an hydroxyethylene transition‐state mimetic for a metalloprotease. Efficient routes for the synthesis of both stereoisomers of the pseudopeptide core were developed, which allowed the synthesis of peptidomimetic inhibitors mimicking the VVYPW‐motif of tynorphin. The best inhibitors inhibit DPP3 in the low μM range. Biophysical characterization by means of ITC measurement and X‐ray crystallography confirm the unusual entropy‐driven mode of binding. Stability assays demonstrated the desired stability of these inhibitors, which efficiently inhibited DPP3 in mouse brain homogenate.

VirtualFlow Ants-Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization

The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.

The shaping of a molecular linguist: How a career studying DNA energetics revealed the language of molecular communication

My personal and professional journeys have been far from predictable based on my early childhood. Owing to a range of serendipitous influences, I miraculously transitioned from a rebellious, apathetic teenage street urchin who did poorly in school to a highly motivated, disciplined, and ambitious academic honors student. I was the proverbial “late bloomer.” Ultimately, I earned my PhD in biophysical chemistry at Yale, followed by a postdoc fellowship at Berkeley. These two meccas of thermodynamics, coupled with my deep fascination with biology, instilled in me a passion to pursue an academic career focused on mapping the energy landscapes of biological systems. I viewed differential energetics as the language of molecular communication that would dictate and control biological structures, as well as modulate the modes of action associated with biological functions. I wanted to be a “molecular linguist.” For the next 50 years, my group and I used a combination of spectroscopic and calorimetric techniques to characterize the energy profiles of the polymorphic conformational space of DNA molecules, their differential ligand-binding properties, and the energy landscapes associated with mutagenic DNA damage recognition, repair, and replication. As elaborated below, the resultant energy databases have enabled the development of quantitative molecular biology through the rational design of primers, probes, and arrays for diagnostic, therapeutic, and molecular-profiling protocols, which collectively have contributed to a myriad of biomedical assays. Such profiling is further justified by yielding unique energy-based insights that complement and expand elegant, structure-based understandings of biological processes.

In Vitro, In Vivo and In Silico Effectiveness of LASSBio-1386, an N-Acyl Hydrazone Derivative Phosphodiesterase-4 Inhibitor, Against Leishmania amazonensis

Leishmaniasis are group of neglected diseases with worldwide distribution that affect about 12 million people. The current treatment is limited and may cause severe adverse effects, and thus, the search for new drugs more effective and less toxic is relevant. We have previously investigated the immunomodulatory effects of LASSBio-1386, an N-acylhydrazone derivative. Here we investigated the in vitro and in vivo activity of LASSBio-1386 against L. amazonensis. LASSBio-1386 inhibited the proliferation of promastigotes of L. amazonensis (EC₅₀ = 2.4 ± 0.48 µM), while presenting low cytotoxicity to macrophages (CC₅₀ = 74.1 ± 2.9 µM). In vitro incubation with LASSBio-1386 reduced the percentage of Leishmania-infected macrophages and the number of intracellular parasites (EC₅₀ = 9.42 ± 0.64 µM). Also, in vivo treatment of BALB/c mice infected with L. amazonensis resulted in a decrease of lesion size, parasitic load and caused histopathological alterations, when compared to vehicle-treated control. Moreover, LASSBio-1386 caused ultrastructural changes, arrested cell cycle in G0/G1 phase and did not alter the membrane mitochondrial potential of L. amazonensis. Aiming to its possible molecular interactions, we performed docking and molecular dynamics studies on Leishmania phosphodiesterase B1 (PDB code: 2R8Q) and LASSBio-1386. The computational analyses suggest that LASSBio-1386 acts against Leishmania through the modulation of leishmanial PDE activity. In conclusion, our results indicate that LASSBio-1386 is a promising candidate for the development of new leishmaniasis treatment.

The role of NMR in leveraging dynamics and entropy in drug design

Nuclear magnetic resonance (NMR) spectroscopy has contributed to structure-based drug development (SBDD) in a unique way compared to the other biophysical methods. The potency of a ligand binding to a protein is dictated by the binding free energy, which is an intricate interplay between entropy and enthalpy. In addition to providing the atomic resolution structural information, NMR can help to identify protein-ligand interactions that potentially contribute to the enthalpic component of the free energy. NMR can also illuminate dynamic aspects of the interaction, which correspond to the entropic term of the free energy. The ability of NMR to access both terms in the free energy equation stems from the suite of experiments developed to shed light on various aspects that contribute to both entropy and enthalpy, deepening our understanding of the biological function of macromolecules and assisting to target them in physiological conditions. Here we provide a brief account of the contribution of NMR to SBDD, highlighting hallmark examples and discussing the challenges that demand further method development. In the era of integrated biology, the unique ability of NMR to directly ascertain structural and dynamical aspects of macromolecule and monitor changes in these properties upon engaging a ligand can be combined with computational and other structural and biophysical methods to provide a more complete picture of the energetics of drug engagement with the target. Such efforts can be used to engineer better drugs.

Solving the Competitive Binding Equilibria between Many Ligands: Application to High-Throughput Screening and Affinity Optimization

Modern small-molecule drug discovery relies on the selective targeting of biological macromolecules by low-molecular weight compounds. Therefore, the binding affinities of candidate drugs to their targets are key for pharmacological activity and clinical use. For drug discovery methods where multiple drug candidates can simultaneously bind to the same target, a competition is established, and the resulting equilibrium depends on the dissociation constants and concentration of all the species present. Such coupling between all equilibrium-governing parameters complicates analysis and development of improved mixture-based, high-throughput drug discovery techniques. In this work, we present an iterative computational algorithm to solve coupled equilibria between an arbitrary number of ligands and a biomolecular target that is efficient and robust. The algorithm does not require the estimation of initial values to rapidly converge to the solution of interest. We explored binding equilibria under ligand/receptor conditions used in mixture-based library screening by affinity selection-mass spectrometry (AS-MS). Our studies support a facile method for affinity-ranking hits. The ranking method involves varying the receptor-to-ligand concentration ratio in a pool of candidate ligands in two sequential AS-MS analyses. The ranking is based on the relative change in bound ligand concentration. The method proposed does not require a known reference ligand and produces a ranking that is insensitive to variations in the concentration of individual compounds, thereby enabling the use of unpurified compounds generated by mixture-based combinatorial synthesis techniques.

[Synthetic Studies on Developments for Bioactive New Leads of Oligovalent Symmetrical Molecules]

Interactions between carbohydrate-containing glycoproteins, proteoglycans, and glycolipids on the cell surface are important biological stages for the processes of bacterial or viral infection and tumor metastasis. Moreover, supramolecular interaction by macromolecules with two-fold (C₂) or three-fold (C₃) geometry is one of the common interactions in many important biological responses. To develop new multivalent symmetrical bioactive compounds or leads, we designed and synthesized several new molecules with these geometries and evaluated their bioactivities in an attempt to find new types of bioactive leads that may interfere with the sugar recognition process. We evaluated bioactivities including antibacterial, antiviral, and anticancer activities of targeted molecules in vitro using biological assay systems. Among the synthesized target derivatives examined, some bivalent symmetrical derivatives showed high levels of bioactivities. In this review, the author describes the results of synthesis of oligovalent symmetrical target compounds and some interesting guiding results of evaluation of their biological activities and structure-activity relationships.

Design, Optimization, and Study of Small Molecules That Target Tau Pre-mRNA and Affect Splicing

Approximately 95% of human genes are alternatively spliced, and aberrant splicing events can cause disease. One pre-mRNA that is alternatively spliced and linked to neurodegenerative diseases is tau (microtubule-associated protein tau), which can cause frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17) and can contribute to Alzheimer's disease. Here, we describe the design of structure-specific lead small molecules that directly target tau pre-mRNA from sequence. This was followed by hit expansion and analogue synthesis to further improve upon these initial lead molecules. The emergent compounds were assessed for functional activity in a battery of assays, including binding assays and an assay that mimics molecular recognition of tau pre-mRNA by a U1 small nuclear ribonucleoprotein (snRNP) splicing factor. Compounds that emerged from these studies had enhanced potency and selectivity for the target RNA relative to the initial hits, while also having significantly improved drug-like properties. The compounds are shown to directly target tau pre-mRNA in cells, via chemical cross-linking and isolation by pull-down target profiling, and to rescue disease-relevant splicing of tau pre-mRNA in a variety of cellular systems, including primary neurons. More broadly, this study shows that lead, structure-specific compounds can be designed from sequence and then further optimized for their physicochemical properties while at the same time enhancing their activity.

Comprehensive investigation of selectivity landscape of glycogen synthase kinase-3 inhibitors

Interaction signatures of drug candidates are characteristic to off-target (neutral) and antitarget (negative) effects, inferring reduced efficiency, side-effects and high attrition rate. Today's retroactive scaled-down virtual screening (VS) experiments relying on benchmarking datasets are extensively involved to assess ligand enrichment in the real-world problem. In recent years, unbiased benchmarking sets turned into a tremendous need to assist virtual screening methodologies for emerging drug targets. To date, the benchmarking datasets are quite limited, whereas glycogen synthase kinase-3 (GSK-3) is not included into directories of benchmarking datasets such as DUD-e, MUV, etc. Herein we introduced our in-house algorithm to build an unbiased benchmarking dataset, including highly selective, moderately selective and nonselective inhibitors for a significant therapeutic target - GSK-3, suitable for both ligand-based and structure-based VS approaches. These datasets are unbiased in terms of physico-chemical properties and topological descriptors, as resulted from mean(ROC-AUC) leave-one-out cross-validation (LOO CV). and additional 2 D similarity search. Moreover, we investigated the gradual selectivity dataset by application of multiple 2 D similarity coefficients and distances, 3 D similarity and docking. Besides the resulted links between the enrichment of selective GSK-3 inhibitors and their chemical structures, a database of compounds and their 3 D similarity signatures including cut-off thresholds for enhanced selectivity was generated. 2 D similarity space analysis revealed that selectivity problem cannot be evaluated appropriately with 2 D similarity searching alone. The current analysis provided useful, comprehensive insights, which may facilitate the knowledge-based identification of novel selective GSK-3 inhibitors.Communicated by Ramaswamy H. Sarma.

Nucleotide-induced folding of cell division protein FtsZ from Staphylococcus aureus

The essential bacterial division protein FtsZ uses GTP binding and hydrolysis to assemble into dynamic filaments that treadmill around the Z-ring, guiding septal wall synthesis and cell division. FtsZ is a structural homolog of tubulin and a target for discovering new antibiotics. Here, using FtsZ from the pathogen S. aureus (SaFtsZ), we reveal that, prior to assembly, FtsZ monomers require nucleotide binding for folding; this is possibly relevant to other mesophilic FtsZs. Apo-SaFtsZ is essentially unfolded, as assessed by nuclear magnetic resonance and circular dichroism. Binding of GTP (≥ 1 mm) dramatically shifts the equilibrium toward the active folded protein. Supportingly, SaFtsZ refolded with GDP crystallizes in a native structure. Apo-SaFtsZ also folds with 3.4 m glycerol, enabling high-affinity GTP binding (K_D 20 nm determined by isothermal titration calorimetry) similar to thermophilic stable FtsZ. Other stabilizing agents that enhance nucleotide binding include ethylene glycol, trimethylamine N-oxide, and several bacterial osmolytes. High salt stabilizes SaFtsZ without bound nucleotide in an inactive twisted conformation. We identified a cavity behind the SaFtsZ-GDP nucleotide-binding pocket that harbors different small compounds, which is available for extended nucleotide-replacing inhibitors. Furthermore, we devised a competition assay to detect any inhibitors that overlap the nucleotide site of SaFtsZ, or Escherichia coli FtsZ, employing osmolyte-stabilized apo-FtsZs and the specific fluorescence anisotropy change in mant-GTP upon dissociation from the protein. This robust assay provides a basis to screening for high-affinity GTP-replacing ligands, which combined with structural studies and phenotypic profiling should facilitate development of a next generation of FtsZ-targeting antibacterial inhibitors.

Computational approaches for drug discovery against trypanosomatid-caused diseases

During three decades, only about 20 new drugs have been developed for malaria, tuberculosis and all neglected tropical diseases (NTDs). This critical situation was reached because NTDs represent only 10% of health research investments; however, they comprise about 90% of the global disease burden. Computational simulations applied in virtual screening (VS) strategies are very efficient tools to identify pharmacologically active compounds or new indications for drugs already administered for other diseases. One of the advantages of this approach is the low time-consuming and low-budget first stage, which filters for testing experimentally a group of candidate compounds with high chances of binding to the target and present trypanocidal activity. In this work, we review the most common VS strategies that have been used for the identification of new drugs with special emphasis on those applied to trypanosomiasis and leishmaniasis. Computational simulations based on the selected protein targets or their ligands are explained, including the method selection criteria, examples of successful VS campaigns applied to NTDs, a list of validated molecular targets for drug development and repositioned drugs for trypanosomatid-caused diseases. Thereby, here we present the state-of-the-art of VS and drug repurposing to conclude pointing out the future perspectives in the field.

Surprising Non-Additivity of Methyl Groups in Drug-Kinase Interaction

Drug optimization is guided by biophysical methods with increasing popularity. In the context of lead structure modifications, the introduction of methyl groups is a simple but potentially powerful approach. Hence, it is crucial to systematically investigate the influence of ligand methylation on biophysical characteristics such as thermodynamics. Here, we investigate the influence of ligand methylation in different positions and combinations on the drug-kinase interaction. Binding modes and complex structures were analyzed using protein crystallography. Thermodynamic signatures were measured via isothermal titration calorimetry (ITC). An extensive computational analysis supported the understanding of the underlying mechanisms. We found that not only position but also stereochemistry of the methyl group has an influence on binding potency as well as the thermodynamic signature of ligand binding to the protein. Strikingly, the combination of single methyl groups does not lead to additive effects. In our case, the merger of two methyl groups in one ligand leads to an entirely new alternative ligand binding mode in the protein ligand complex. Moreover, the combination of the two methyl groups also resulted in a nonadditive thermodynamic profile of ligand binding. Molecular dynamics (MD) simulations revealed distinguished characteristic motions of the ligands in solution explaining the pronounced thermodynamic changes. The unexpected drastic change in protein ligand interaction highlights the importance of crystallographic control even for minor modifications such as the introduction of a methyl group. For an in-depth understanding of ligand binding behavior, MD simulations have shown to be a powerful tool.

Advances in preclinical approaches to Chagas disease drug discovery

Introduction: Chagas disease affects 8-10 million people worldwide, mainly in Latin America. The current therapy for Chagas disease is limited to nifurtimox and benznidazole, which are effective in treating only the acute phase of the disease but with severe side effects. Therefore, there is an unmet need for new drugs and for the exploration of innovative approaches which may lead to the discovery of new effective and safe drugs for its treatment. Areas covered: The authors report and discuss recent approaches including structure-based design that have led to the discovery of new promising small molecule candidates for Chagas disease which affect prime targets that intervene in the sterol pathway of T. cruzi. Other trypanosome targets, phenotypic screening, the use of artificial intelligence and the challenges with Chagas disease drug discovery are also discussed. Expert opinion: The application of recent scientific innovations to the field of Chagas disease have led to the discovery of new promising drug candidates for Chagas disease. Phenotypic screening brought new hits and opportunities for drug discovery. Artificial intelligence also has the potential to accelerate drug discovery in Chagas disease and further research into this is warranted.

Small-Scale Panel Comprising Diverse Gene Family Targets To Evaluate Compound Promiscuity

Despite the recent advances in the life sciences and the remarkable investment in drug discovery research, the success rate of small-molecule drug development remains low. Safety is the second most influential factor of drug attrition in clinical studies; thus, the selection of compounds with fewer toxicity concerns is crucial to increase the success rate of drug discovery. Compounds that promiscuously bind to multiple targets are likely to cause unexpected pharmacological activity that may lead to adverse effects. Therefore, avoiding such compounds during early research stages would contribute to identifying compounds with a higher chance of success in the clinic. To evaluate the interaction profile against a wide variety of targets, we constructed a small-scale promiscuity panel (PP) consisting of eight targets (ROCK1, PDE4D2, GR, PPARγ, 5-HT_2B, adenosine A₃, M1, and GABA_A) that were selected from diverse gene families. The validity of this panel was confirmed by comparison with the promiscuity index evaluated from larger-scale panels. Analysis of data from the PP revealed that both lipophilicity and basicity are likely to increase promiscuity, while the molecular weight does not significantly contribute. Additionally, the promiscuity assessed using our PP correlated with the occurrence of both in vitro cytotoxicity and in vivo toxicity, suggesting that the PP is useful to identify compounds with fewer toxicity concerns. In summary, this small-scale and cost-effective PP can contribute to the identification of safer compounds that would lead to a reduction in drug attrition due to safety issues.

Tinkering with Binding Polynomials in Isothermal Titration Calorimetry

Isothermal titration calorimetry (ITC) has become the preferred experimental technique for characterizing intermolecular interactions between biological molecules. Among the several advantages, the use of natural non-labeled molecules and the determination of the complete thermodynamic profile for the interaction in solution remain as the primary features that have promoted ITC to the forefront of experimental biophysics. The experimental design in ITC may range from studying a simple direct binary macromolecule-ligand interaction to studying the homotropic or heterotropic cooperative effect between ligands when interacting with a given macromolecule. The theory of the binding polynomial has proven to be an appropriate unifying framework for handling the complexities that can be encountered when studying macromolecule-ligand interactions, though it has been deemed troublesome. The goal of this chapter is to provide a quite simple and widely available set of training experiments aimed at mastering the formalism of the binding polynomial applied to isothermal titration calorimetry.

FragLites-Minimal, Halogenated Fragments Displaying Pharmacophore Doublets. An Efficient Approach to Druggability Assessment and Hit Generation

Identifying ligand binding sites on proteins is a critical step in target-based drug discovery. Current approaches to this require resource-intensive screening of large libraries of lead-like or fragment molecules. Here, we describe an efficient and effective experimental approach to mapping interaction sites using a set of halogenated compounds expressing paired hydrogen-bonding motifs, termed FragLites. The FragLites identify productive drug-like interactions, which are identified sensitively and unambiguously by X-ray crystallography, exploiting the anomalous scattering of the halogen substituent. This mapping of protein interaction surfaces provides an assessment of druggability and can identify efficient start points for the de novo design of hit molecules incorporating the interacting motifs. The approach is illustrated by mapping cyclin-dependent kinase 2, which successfully identifies orthosteric and allosteric sites. The hits were rapidly elaborated to develop efficient lead-like molecules. Hence, the approach provides a new method of identifying ligand sites, assessing tractability and discovering new leads.

Discovery and Genetic Validation of Chemotherapeutic Targets for Chagas' Disease

There is an urgent need to develop new treatments for Chagas' disease. To identify drug targets, it is important to understand the basic biology of Trypanosoma cruzi, in particular with respect to the biological pathways or proteins that are essential for its survival within the host. This review provides a streamlined approach for identifying drug targets using freely available chemogenetic databases and outlines the relevant characteristics of an ideal chemotherapeutic target. Among those are their essentiality, druggability, availability of structural information, and selectivity. At the moment only 16 genes have been found as essential by gene disruption in T. cruzi. At the TDR Targets database, a chemogenomics resource for neglected diseases, information about published structures for these genes was only found for three of these genes, and annotation of validated inhibitors was found in two. These inhibitors have activity against the parasitic stages present in the host. We then analyzed three of the pathways that are considered promising in the search for new targets: (1) Ergosterol biosynthesis, (2) Resistance to oxidative stress, (3) Synthesis of surface glycoconjugates. We have annotated all the genes that participate in them, identified those that are considered as druggable, and incorporated evidence from either Trypanosoma brucei, and Leishmania spp. that supports the hypothesis that these pathways are essential for T. cruzi survival.

Present drug-likeness filters in medicinal chemistry during the hit and lead optimization process: how far can they be simplified?

During the past decade, decreasing the attrition rate of drug development candidates reaching the market has become one of the major challenges in pharmaceutical research and drug development (R&D). To facilitate the decision-making process, and to increase the probability of rapidly finding and developing high-quality compounds, a variety of multiparametric guidelines, also known as rules and ligand efficiency (LE) metrics, have been developed. However, what are the 'best' descriptors and how far can we simplify these drug-likeness prediction tools in terms of the numerous, complex properties that they relate to?

New ferrocene-based 2-thio-imidazol-4-ones and their copper complexes. Synthesis and cytotoxicity

Characterization and cytotoxicity of ferrocene-based imidazolones and their copper complexes.

Structural and Functional View of Polypharmacology

Protein domains mediate drug-protein interactions and this principle can guide the design of multi-target drugs i.e. polypharmacology. In this study, we associate multi-target drugs with CATH functional families through the overrepresentation of targets of those drugs in CATH functional families. Thus, we identify CATH functional families that are currently enriched in drugs (druggable CATH functional families) and we use the network properties of these druggable protein families to analyse their association with drug side effects. Analysis of selected druggable CATH functional families, enriched in drug targets, show that relatives exhibit highly conserved drug binding sites. Furthermore, relatives within druggable CATH functional families occupy central positions in a human protein functional network, cluster together forming network neighbourhoods and are less likely to be within proteins associated with drug side effects. Our results demonstrate that CATH functional families can be used to identify drug-target interactions, opening a new research direction in target identification.

Anticancer mechanisms of Strobilanthes crispa Blume hexane extract on liver and breast cancer cell lines

Cancer is a major public health concern not only in developed countries, but also in developing countries. It is one of the leading causes of mortality worldwide. However, current treatments may cause severe side effects and harm. Therefore, recent research has been focused on identifying alternative therapeutic agents extracted from plant-based sources in order to develop novel treatment options for cancer. Strobilanthes crispa Blume is a plant native to countries including Madagascar and Indonesia. It has been used as an anti-diabetic, diuretic and laxative in traditional folk medicine. Furthermore, S. crispa has potential in treating cancer, as evidenced in previous studies. In the present study, the cytotoxic and apoptotic activities of S. crispa crude extracts were investigated in liver and breast cancer cell lines. Hexane, ethyl acetate, chloroform, methanol and water extracts prepared from the leaves, and stems of S. crispa were evaluated for their cytotoxicity on HepG-2 and MDA-MB-231 cells using an MTT assay. The anti-proliferative properties of stem hexane (SH) extract on both cell lines were analysed using cell doubling time determination and cell cycle analysis, while the apoptogenic properties was determined through the detection of caspase-8. Among the extracts tested, SH extract exhibited the lowest half maximal inhibitory concentrations in both the cell lines. The SH extract induced morphological changes in HepG-2 and MDA-MB-231 cells, and significantly delayed cell population doubling time. Furthermore, it altered cell cycle profile and significantly increased caspase-8 activity in HepG-2 cells, but not in MDA-MB-231 cells. In conclusion, the SH extract of S. crispa possesses potent anticancer properties and may be a suitable chemotherapeutic target.

Determination of the endothelin-1 recognition sites of endothelin receptor type A by the directed-degeneration method

G-protein coupled receptors (GPCRs) play indispensable physiological roles in cell proliferation, differentiation, and migration; therefore, identifying the mechanisms by which ligands bind to GPCRs is crucial for developing GPCR-targeting pharmaceutics and for understanding critical biological functions. Although some structural information is available regarding the interactions between GPCRs and their small molecule ligands, knowledge of how GPCRs interact with their corresponding macromolecule ligands, such as peptides and proteins, remains elusive. In this study, we have developed a novel strategy to investigate the precise ligand recognition mechanisms involved in the interaction of endothelin receptor type A (ET_A) with its ligand, endothelin-1 (ET-1); we call this method “directed degeneration” method. Through flow cytometric screening of a randomized ET_A library, statistical analysis of the identified sequences, and biochemical studies, the ligand interaction map was successfully obtained.

A Transcriptomic Survey of Ion Channel-Based Conotoxins in the Chinese Tubular Cone Snail (Conus betulinus)

Conotoxins in the venom of cone snails (Conus spp.) are a mixture of active peptides that work as blockers, agonists, antagonists, or inactivators of various ion channels. Recently we reported a high-throughput method to identify 215 conotoxin transcripts from the Chinese tubular cone snail, C. betulinus. Here, based on the previous datasets of four transcriptomes from three venom ducts and one venom bulb, we explored ion channel-based conotoxins and predicted their related ion channel receptors. Homologous analysis was also performed for the most abundant ion channel protein, voltage-gated potassium (Kv; with Kv1.1 as the representative), and the most studied ion channel receptor, nicotinic acetylcholine receptor (nAChR; with α2-nAChR as the representative), in different animals. Our transcriptomic survey demonstrated that ion channel-based conotoxins and related ion channel proteins/receptors transcribe differentially between the venom duct and the venom bulb. In addition, we observed that putative κ-conotoxins were the most common conotoxins with the highest transcription levels in the examined C. betulinus. Furthermore, Kv1.1 and α2-nAChR were conserved in their functional domains of deduced protein sequences, suggesting similar effects of conotoxins via the ion channels in various species, including human beings. In a word, our present work suggests a high-throughput way to develop conotoxins as potential drugs for treatment of ion channel-associated human diseases.

Structural mechanisms for α-conotoxin activity at the human α3β4 nicotinic acetylcholine receptor

Nicotinic acetylcholine receptors (nAChR) are therapeutic targets for a range of human diseases. α-Conotoxins are naturally occurring peptide antagonists of nAChRs that have been used as pharmacological probes and investigated as drug leads for nAChR related disorders. However, α-conotoxin interactions have been mostly characterised at the α7 and α3β2 nAChRs, with interactions at other subtypes poorly understood. This study provides novel structural insights into the molecular basis for α-conotoxin activity at α3β4 nAChR, a therapeutic target where subtype specific antagonists have potential to treat nicotine addiction and lung cancer. A co-crystal structure of α-conotoxin LsIA with Lymnaea stagnalis acetylcholine binding protein guided the design and functional characterisations of LsIA analogues that identified the minimum pharmacophore regulating α3β4 antagonism. Interactions of the LsIA R10F with β4 K57 and the conserved -NN- α-conotoxin motif with β4 I77 and I109 conferred α3β4 activity to the otherwise inactive LsIA. Using these structural insights, we designed LsIA analogues with α3β4 activity. This new understanding of the structural basis of protein-protein interactions between α-conotoxins and α3β4 may help rationally guide the development of α3β4 selective antagonists with therapeutic potential.

Identification of UQCRB as an oxymatrine recognizing protein using a T7 phage display screen

ETHNOPHARMACOLOGICAL RELEVANCE

Sophora flavescens Aiton (Radix Sophorae Flavescentis, Kushen) is used in traditional Chinese medicine to treat chronic hepatitis B (CHB), and has the ability to clear heat and dampness from the body. Oxymatrine is one of the major bioactive compounds extracted from Sophora flavescens Aiton and constitutes more than 90% of the oxymatrine injection commonly used for CHB treatment in clinics in China.

AIM OF THE STUDY

We aim to analyze the protein binding target of oxymatrine in treating CHB by screening a T7 phage display cDNA library of human CHB and examine the biochemistry of protein-ligand binding between oxymatrine and its ligands.

MATERIALS AND METHODS

A T7 phage cDNA library of human CHB was biopanned by affinity selection using oxymatrine as bait. The interaction of oxymatrine with its candidate binding protein was investigated by affinity assay, molecular docking, Isothermal Titration Calorimetry (ITC) and Surface Plasmon Resonance (SPR).

RESULTS

A library of potential oxymatrine binding peptides was generated. Ubiquinol-cytochrome c reductase binding protein (UQCRB) was one of the candidate binding proteins of oxymatrine. UQCRB-displaying T7 phage binding numbers in the oxymatrine group were significantly higher than that in the control group, biotin group, and matrine group (p<0.05 or p<0.01). Three-dimensional structure modeling of the UQCRB with oxymatrine showed that their binding interfaces matched and oxymatrine inserted into a deeper pocket of UQCRB, which mainly involved amino acid residues Tyr21, Arg33, Tyr83, Glu84, Asp86, Pro88, and Glu91. The binding affinity constant (Kb) from SPR was 4.2mM. The Kb from ITC experiment was 3.9mM and stoichiometry was fixed as 1, which fit very well with the result of SPR. The binding of oxymatrine to UQCRB was driven by strong enthalpy forces such as hydrogen bonds and polar interactions as the heat released was about 157kcal/mol and ΔG was less than zero.

CONCLUSIONS

In this study, using the T7 phage display system, we have identified UQCRB as a direct binding protein of oxymatrine. Furthermore, the specificity and molecular interaction of oxymatrine with UQCRB were also determined. The binding of UQCRB to oxymatrine suggests that UQCRB is a potential target of oxymatrine in treating CHB. These results provide new understanding into the mechanism of oxymatrine and insights into the strategy on the treatment of CHB.

Optimization and bioevaluation of Cdc37-derived peptides: An insight into Hsp90-Cdc37 protein-protein interaction modulators

Targeting Hsp90-Cdc37 protein-protein interaction (PPI) is becoming an alternative approach for future anti-cancer drug development. We previously reported the discovery of an eleven-residue peptide (Pep-1) with micromolar activity for the disruption of Hsp90-Cdc37 PPI. Efforts to improve upon the Pep-1 led to the discovery of more potent modulators for Hsp90-Cdc37 PPI. Through the analysis of peptides binding patterns, more peptides were designed for further verification which resulted in Pep-5, the shortest peptide targeting Hsp90-Cdc37, exerting the optimal structure and the most efficient binding mode. Subsequent MD simulation analysis also confirmed that Pep-5 could perform more stable binding ability and better ligand properties than Pep-1. Under the premise of retentive binding capacity, Pep-5 exhibited lower molecular weight and higher ligand efficiency with a K_d value of 5.99μM (Pep-1 K_d=6.90μM) in both direct binding determination and biological evaluation. The optimal and shortest Pep-5 might provide a breakthrough and a better model for the future design of small molecule inhibitors targeting Hsp90-Cdc37 PPI.

Enthalpy screen of drug candidates

The enthalpic and entropic contributions to the binding affinity of drug candidates have been acknowledged to be important determinants of the quality of a drug molecule. These quantities, usually summarized in the thermodynamic signature, provide a rapid assessment of the forces that drive the binding of a ligand. Having access to the thermodynamic signature in the early stages of the drug discovery process will provide critical information towards the selection of the best drug candidates for development. In this paper, the Enthalpy Screen technique is presented. The enthalpy screen allows fast and accurate determination of the binding enthalpy for hundreds of ligands. As such, it appears to be ideally suited to aid in the ranking of the hundreds of hits that are usually identified after standard high throughput screening.

Improved QM/MM Linear-Interaction Energy Model for Substrate Recognition in Zinc-Containing Metalloenzymes

One of the essential challenges in the description of receptor-drug interactions in the presence of various polyvalent cations (such as zinc, magnesium, or iron) is the accurate assessment of the electronic effects due to cofactor binding. The effects can range from partial electronic polarization of the proximal atoms in a receptor and bound substrate to long-range effects related to partial charge transfer and electronic delocalization effects between the cofactor and the drug. Here, we examine the role of the explicit account for electronic effects for a panel of small-molecule inhibitors binding to the zinc-aminopeptidase PfA-M1, an essential target for antimalarial drug development. Our study on PfA-M1:inhibitor interactions at the QM level reveals that the partial charge and proton transfer due to bound zinc ion are important mechanisms in the inhibitors' recognition and catalysis. The combination of classical MD simulations with a posteriori QM/MM corrections with novel DFTB parameters for the zinc cation and the linear-interaction energy (LIE) approach offers by far the most accurate estimates for the PfA-M1:inhibitor binding affinities, opening the door for future inhibitor design.