Flexible protein–ligand docking by global energy optimization in internal coordinates

The archaeal highly thermostable GH35 family β-galactosidase DaβGal has a unique seven domain protein fold

The most extensively studied β-d-galactosidases (EC3.2.1.23) belonging to four glycoside hydrolase (GH) families 1, 2, 35, and 42 are widely distributed among Bacteria, Archaea and Eukaryotes. Here, we report a novel GH35 family β-galactosidase from the hyperthermophilic Thermoprotei archaeon Desulfurococcus amylolyticus (DaβGal). Unlike fungal monomeric six-domain β-galactosidases, the DaβGal enzyme is a dimer; it has an extra jelly roll domain D7 and three composite domains (D4, D5, and D6) that are formed by the distantly located polypeptide chain regions. The enzyme possesses a high specificity for β-d-galactopyranosides, and its distinguishing feature is the ability to cleave pNP-β-d-fucopyranoside. DaβGal efficiently catalyzes the hydrolysis of lactose at high temperatures, remains stable and active at 65 °С, and retains activity at 95 °С with a half-life time value equal to 73 min. These properties make archaeal DaβGal a more attractive candidate for biotechnology than the widely used fungal β-galactosidases.

Direct Growth Control of Antibiotic-Resistant Bacteria Using Visible-Light-Responsive Novel Photoswitchable Antibiotics

In addition to the discovery of new (modified) potent antibiotics to combat antibiotic resistance, there is a critical need to develop novel strategies that would restrict their off-target effects and unnecessary exposure to bacteria in our body and environment. We report a set of new photoswitchable arylazopyrazole-modified norfloxacin antibiotics that present a high degree of bidirectional photoisomerization, impressive fatigue resistance and reasonably high cis half-lives. The irradiated isomers of most compounds were found to exhibit nearly equal or higher antibacterial activity than norfloxacin against Gram-positive bacteria. Notably, against norfloxacin-resistant S. aureus bacteria, the visible-light-responsive p-SMe-substituted derivative showed remarkably high antimicrobial potency (MIC of 0.25 μg/mL) in the irradiated state, while the potency was reduced by 24-fold in case of its non-irradiated state. The activity was estimated to be retained for more than 7 hours. This is the first report to demonstrate direct photochemical control of the growth of antibiotic-resistant bacteria and to show the highest activity difference between irradiated and non-irradiated states of a photoswitchable antibiotic. Additionally, both isomers were found to be non-harmful to human cells. Molecular modellings were performed to identify the underlying reason behind the high-affinity binding of the irradiated isomer to topoisomerase IV enzyme.

Docking for Molecules That Bind in a Symmetric Stack with SymDOCK

Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of great current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures, the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein's symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligand's docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural-network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study, SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.

Docking for molecules that bind in a symmetric stack with SymDOCK

Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of much current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein's symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligand's docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed, and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.

Pharmacological and Physicochemical Properties Optimization for Dual-Target Dopamine D3 (D3R) and μ-Opioid (MOR) Receptor Ligands as Potentially Safer Analgesics

A new generation of dual-target μ opioid receptor (MOR) agonist/dopamine D3 receptor (D3R) antagonist/partial agonists with optimized physicochemical properties was designed and synthesized. Combining in vitro cell-based on-target/off-target affinity screening, in silico computer-aided drug design, and BRET functional assays, we identified new structural scaffolds that achieved high affinity and agonist/antagonist potencies for MOR and D3R, respectively, improving the dopamine receptor subtype selectivity (e.g., D3R over D2R) and significantly enhancing central nervous system multiparameter optimization scores for predicted blood-brain barrier permeability. We identified the substituted trans-(2S,4R)-pyrrolidine and trans-phenylcyclopropyl amine as key dopaminergic moieties and tethered these to different opioid scaffolds, derived from the MOR agonists TRV130 (3) or loperamide (6). The lead compounds 46, 84, 114, and 121 have the potential of producing analgesic effects through MOR partial agonism with reduced opioid-misuse liability via D3R antagonism. Moreover, the peripherally limited derivatives could have therapeutic indications for inflammation and neuropathic pain.

Nucleoside Analogs and Perylene Derivatives Modulate Phase Separation of SARS-CoV-2 N Protein and Genomic RNA In Vitro

The life cycle of severe acute respiratory syndrome coronavirus 2 includes several steps that are supposedly mediated by liquid-liquid phase separation (LLPS) of the viral nucleocapsid protein (N) and genomic RNA. To facilitate the rational design of LLPS-targeting therapeutics, we modeled N-RNA biomolecular condensates in vitro and analyzed their sensitivity to several small-molecule antivirals. The model condensates were obtained and visualized under physiological conditions using an optimized RNA sequence enriched with N-binding motifs. The antivirals were selected based on their presumed ability to compete with RNA for specific N sites or interfere with non-specific pi-pi/cation-pi interactions. The set of antivirals included fleximers, 5'-norcarbocyclic nucleoside analogs, and perylene-harboring nucleoside analogs as well as non-nucleoside amphiphilic and hydrophobic perylene derivatives. Most of these antivirals enhanced the formation of N-RNA condensates. Hydrophobic perylene derivatives and 5'-norcarbocyclic derivatives caused up to 50-fold and 15-fold enhancement, respectively. Molecular modeling data argue that hydrophobic compounds do not hamper specific N-RNA interactions and may promote non-specific ones. These findings shed light on the determinants of potent small-molecule modulators of viral LLPS.

The Search for Antibacterial Inhibitors Targeting Cell Division Protein FtsZ at Its Nucleotide and Allosteric Binding Sites

The global spread of bacterial antimicrobial resistance is associated to millions of deaths from bacterial infections per year, many of which were previously treatable. This, combined with slow antibiotic deployment, has created an urgent need for developing new antibiotics. A still clinically unexploited mode of action consists in suppressing bacterial cell division. FtsZ, an assembling GTPase, is the key protein organizing division in most bacteria and an attractive target for antibiotic discovery. Nevertheless, developing effective antibacterial inhibitors targeting FtsZ has proven challenging. Here we review our decade-long multidisciplinary research on small molecule inhibitors of bacterial division, in the context of global efforts to discover FtsZ-targeting antibiotics. We focus on methods to characterize synthetic inhibitors that either replace bound GTP from the FtsZ nucleotide binding pocket conserved across diverse bacteria or selectively bind into the allosteric site at the interdomain cleft of FtsZ from Bacillus subtilis and the pathogen Staphylococcus aureus. These approaches include phenotype screening combined with fluorescence polarization screens for ligands binding into each site, followed by detailed cytological profiling, and biochemical and structural studies. The results are analyzed to design an optimized workflow to identify effective FtsZ inhibitors, and new approaches for the discovery of FtsZ-targeting antibiotics are discussed.

Computational methods to assist in the discovery of pharmacological chaperones for rare diseases

Pharmacological chaperones are chemical compounds able to bind proteins and stabilize them against denaturation and following degradation. Some pharmacological chaperones have been approved, or are under investigation, for the treatment of rare inborn errors of metabolism, caused by genetic mutations that often can destabilize the structure of the wild-type proteins expressed by that gene. Given that, for rare diseases, there is a general lack of pharmacological treatments, many expectations are poured out on this type of compounds. However, their discovery is not straightforward. In this review, we would like to focus on the computational methods that can assist and accelerate the search for these compounds, showing also examples in which these methods were successfully applied for the discovery of promising molecules belonging to this new category of pharmacologically active compounds.

Broad-spectrum cyclic boronate β-lactamase inhibitors featuring an intramolecular prodrug for oral bioavailability

Early efforts to broaden the spectrum and potency of cyclic boronic acid β-lactamase inhibitor vaborbactam included a series of 7-membered ring boronates. Exploration of stereoisomers and incorporation of heteroatoms allowed identification of the all-carbon cyclic boronate with substituents trans as the preferred core structure, showing inhibition of Class A and C enzymes. Crystal structures of one analog bound to important β-lactamase enzymes were obtained. When isolated under acidic conditions, these compounds spontaneously formed a neutral cyclic anhydride (intramolecular prodrug) which was shown to have much-improved oral bioavailability (52-69%) compared to the ring-opened carboxylate salt (9%).

New Evidence on a Distinction between Aβ40 and Aβ42 Amyloids: Thioflavin T Binding Modes, Clustering Tendency, Degradation Resistance, and Cross-Seeding

The relative abundance of two main Abeta-peptide types with different lengths, Aβ40 and Aβ42, determines the severity of the Alzheimer’s disease progression. However, the factors responsible for different behavior patterns of these peptides in the amyloidogenesis process remain unknown. In this comprehensive study, new evidence on Aβ40 and Aβ42 amyloid polymorphism was obtained using a wide range of experimental approaches, including custom-designed approaches. We have for the first time determined the number of modes of thioflavin T (ThT) binding to Aβ40 and Aβ42 fibrils and their binding parameters using a specially developed approach based on the use of equilibrium microdialysis, which makes it possible to distinguish between the concentration of the injected dye and the concentration of dye bound to fibrils. The binding sites of one of these modes located at the junction of adjacent fibrillar filaments were predicted by molecular modeling techniques. We assumed that the sites of the additional mode of ThT-Aβ42 amyloid binding observed experimentally (which are not found in the case of Aβ40 fibrils) are localized in amyloid clots, and the number of these sites could be used for estimation of the level of fiber clustering. We have shown the high tendency of Aβ42 fibers to form large clots compared to Aβ40 fibrils. It is probable that this largely determines the high resistance of Aβ42 amyloids to destabilizing effects (denaturants, ionic detergents, ultrasonication) and their explicit cytotoxic effect, which we have shown. Remarkably, cross-seeding of Aβ40 fibrillogenesis using the preformed Aβ42 fibrils changes the morphology and increases the stability and cytotoxicity of Aβ40 fibrils. The differences in the tendency to cluster and resistance to external factors of Aβ40 and Aβ42 fibrils revealed here may be related to the distinct role they play in the deposition of amyloids and, therefore, differences in pathogenicity in Alzheimer’s disease.

FitDock: protein-ligand docking by template fitting

Protein-ligand docking is an essential method in computer-aided drug design and structural bioinformatics. It can be used to identify active compounds and reveal molecular mechanisms of biological processes. A successful docking usually requires thorough conformation sampling and scoring, which are computationally expensive and difficult. Recent studies demonstrated that it can be beneficial to docking with the guidance of existing similar co-crystal structures. In this work, we developed a protein-ligand docking method, named FitDock, which fits initial conformation to the given template using a hierarchical multi-feature alignment approach, subsequently explores the possible conformations and finally outputs refined docking poses. In our comprehensive benchmark tests, FitDock showed 40%-60% improvement in terms of docking success rate and an order of magnitude faster over popular docking methods, if template structures exist (> 0.5 ligand similarity). FitDock has been implemented in a user-friendly program, which could serve as a convenient tool for drug design and molecular mechanism exploration. It is now freely available for academic users at http://cao.labshare.cn/fitdock/.

Docking Ligands into Flexible and Solvated Macromolecules. 8. Forming New Bonds─Challenges and Opportunities

Over the years, structure-based design programs and specifically docking small molecules to proteins have become prominent in drug discovery. However, many of these computational tools have been developed to primarily dock enzyme inhibitors (and ligands to other protein classes) relying heavily on hydrogen bonds and electrostatic and hydrophobic interactions. In reality, many drug targets either feature metal ions, can be targeted covalently, or are simply not even proteins (e.g., nucleic acids). Herein, we describe several new features that we have implemented into Fitted to broaden its applicability to a wide range of covalent enzyme inhibitors and to metalloenzymes, where metal coordination is essential for drug binding. This updated version of our docking program was tested for its ability to predict the correct binding mode of drug-sized molecules in a large variety of proteins. We also report new datasets that were essential to demonstrate areas of success and those where additional efforts are required. This resource could be used by other program developers to assess their own software.

Chiral Cyclic Aliphatic Linkers as Building Blocks for Selective Dopamine D2 or D3 Receptor Agonists

Linkers are emerging as a key component in regulating the pharmacology of bitopic ligands directed toward G-protein coupled receptors (GPCRs). In this study, the role of regio- and stereochemistry in cyclic aliphatic linkers tethering well-characterized primary and secondary pharmacophores targeting dopamine D2 and D3 receptor subtypes (D2R and D3R, respectively) is described. We introduce several potent and selective D2R (rel-trans-16b; D2R Ki = 4.58 nM) and D3R (rel-cis-14a; D3R Ki = 5.72 nM) agonists while modulating subtype selectivity in a stereospecific fashion, transferring D2R selectivity toward D3R via inversion of the stereochemistry around these cyclic aliphatic linkers [e.g., (-)-(1S,2R)-43 and (+)-(1R,2S)-42]. Pharmacological observations were supported with extensive molecular docking studies. Thus, not only is it an innovative approach to modulate the pharmacology of dopaminergic ligands described, but a new class of optically active cyclic linkers are also introduced, which can be used to expand the bitopic drug design approach toward other GPCRs.

Structural insights on ligand recognition at the human leukotriene B4 receptor 1

The leukotriene B4 receptor 1 (BLT1) regulates the recruitment and chemotaxis of different cell types and plays a role in the pathophysiology of infectious, allergic, metabolic, and tumorigenic human diseases. Here we present a crystal structure of human BLT1 (hBLT1) in complex with a selective antagonist MK-D-046, developed for the treatment of type 2 diabetes and other inflammatory conditions. Comprehensive analysis of the structure and structure-activity relationship data, reinforced by site-directed mutagenesis and docking studies, reveals molecular determinants of ligand binding and selectivity toward different BLT receptor subtypes and across species. The structure helps to identify a putative membrane-buried ligand access channel as well as potential receptor binding modes of endogenous agonists. These structural insights of hBLT1 enrich our understanding of its ligand recognition and open up future avenues in structure-based drug design.

Novel Dual-Target μ-Opioid Receptor and Dopamine D3 Receptor Ligands as Potential Nonaddictive Pharmacotherapeutics for Pain Management

The need for safer pain-management therapies with decreased abuse liability inspired a novel drug design that retains μ-opioid receptor (MOR)-mediated analgesia, while minimizing addictive liability. We recently demonstrated that targeting the dopamine D₃ receptor (D₃R) with highly selective antagonists/partial agonists can reduce opioid self-administration and reinstatement to drug seeking in rodent models without diminishing antinociceptive effects. The identification of the D₃R as a target for the treatment of opioid use disorders prompted the idea of generating a class of ligands presenting bitopic or bivalent structures, allowing the dual-target binding of the MOR and D₃R. Structure-activity relationship studies using computationally aided drug design and in vitro binding assays led to the identification of potent dual-target leads (23, 28, and 40), based on different structural templates and scaffolds, with moderate (sub-micromolar) to high (low nanomolar/sub-nanomolar) binding affinities. Bioluminescence resonance energy transfer-based functional studies revealed MOR agonist-D₃R antagonist/partial agonist efficacies that suggest potential for maintaining analgesia with reduced opioid-abuse liability.

Investigation of New Inhibitors of UDP-N-Acetylglucosamine Enolpyruvyl Transferase (MurA) by Virtual Screening with Antibacterial Assessment

BACKGROUND

Considering the interesting role in the peptidoglycan biosynthesis pathway, the enzyme UDP-N-acetylglucosamine enolpyruvyl transferase is an attractive target to develop new antibacterial agents. It catalyzes the first key step of this pathway and its inhibition leads to bacterial cell death. Fosfomycin is known as the natural inhibitor of MurA.

OBJECTIVE

The study aimed to introduce new inhibitors of MurA by virtual screening of different chemical compounds libraries, and test the best scored "virtual hits" against three pathogenic bacteria: Escherichia coli, Bacillus subtilis and Staphylococcus aureus.

METHODS

A virtual screening of the structural analogues of fosfomycin downloaded from the Pub- Chem database was performed. Moreover, French National Chemical Library and ZINC database were also utilized to identify new structures different from fosfomycin. FlexX was the software used for this study. The antibacterial testing was divided into two methods: disk diffusion and broth dilution.

RESULTS

A set of virtual hits was found to have better energy score than that of fosfomycin, seven of them were tested in vitro. In addition, the disk diffusion method explored four compounds that exhibited antibacterial activity: CID-21680357 (fosfomycin analogue), AB-00005001, ZINC04658565, and ZINC901335. The testing was continued by broth dilution method for both compounds CID-21680357 and ZINC901335 to determine their minimum inhibitory concentrations, and ZINC901335 had the best value with 457μg/ml against Staphylococcus aureus.

CONCLUSION

Four compounds were found and proven in silico and in vitro to have antibacterial activity, namely CID-21680357, AB-00005001, ZINC04658565, and ZINC901335.

Withanolides from dietary tomatillo suppress HT1080 cancer cell growth by targeting mutant IDH1

Isocitrate dehydrogenase (IDH) is one key rate-limiting enzyme in the tricarboxylic acid cycle, which is related to various cancers. Tomatillo (Physalis ixocarpa), a special tomato, is widely consumed as nutritious vegetable in Mexico, USA, etc. As a rich source for withanolides, the fruits of P. ixocarpa were investigated, leading to the isolation of 11 type-A withanolides including 4 new ones (1 is an artificial withanolide). All these withanolides were evaluated for their inhibition on mutant IDH1 enzyme activity. Among them, physalin F (11) exhibited potent enzyme inhibitory activity and binding affinity with mutant IDH1. It inhibits the proliferation of HT1080 cells by selectively inhibiting the activity of mutant IDH1. Since Ixocarpalactone A, another major type-B withanolide in this plant, could act on another energy metabolism target PHGDH, the presence of different types of withanolides in tomatillo and their synergistic effect could make it a potential antitumor functional food or drug.

Ambroxol increases glucocerebrosidase (GCase) activity and restores GCase translocation in primary patient-derived macrophages in Gaucher disease and Parkinsonism

Mutations in the glucocerebrosidase gene (GBA) encoding the lysosomal enzyme glucocerebrosidase (GCase) cause Gaucher disease (GD) and are the most commonly known genetic risk factor for Parkinson disease (PD). Ambroxol is one of the most effective pharmacological chaperones of GCase. Fourteen GD patients, six PD patients with mutations in the GBA gene (GBA-PD), and thirty controls were enrolled. GCase activity and hexosylsphingosine (HexSph) concentration were measured in dried blood and macrophage spots using liquid chromatography coupled with tandem mass spectrometry. The effect of ambroxol on GCase translocation to lysosomes was assessed using confocal microscopy. The results showed that ambroxol treatment significantly increased GCase activity in cultured macrophages derived from patient blood monocytic cell (PBMC) of GD (by 3.3-fold) and GBA-PD patients (by 3.5-fold) compared to untreated cells (p < 0.0001 and p < 0.0001, respectively) four days after cultivation. Ambroxol treatment significantly reduced HexSph concentration in GD (by 2.1-fold) and GBA-PD patients (by 1.6-fold) (p < 0.0001 and p < 0.0001, respectively). GD macrophage treatment resulted in increased GCase level and increased enzyme colocalization with the lysosomal marker LAMP2. The possible binding modes of ambroxol to mutant GCase carrying N370S amino acid substitution at pH 4.7 were examined using molecular docking and molecular dynamics simulations. The ambroxol position characterized by minimal binding free energy was observed in close vicinity to the residue, at position 370. Taken together, these data showed that PBMC-derived macrophages could be used for assessing ambroxol therapy response for GD patients and also for GBA-PD patients.

GPU-Accelerated Flexible Molecular Docking

Virtual screening is a key enabler of computational drug discovery and requires accurate and efficient structure-based molecular docking. In this work, we develop algorithms and software building blocks for molecular docking that can take advantage of graphics processing units (GPUs). Specifically, we focus on MedusaDock, a flexible protein-small molecule docking approach and platform. We accelerate the performance of the coarse docking phase of MedusaDock, as this step constitutes nearly 70% of total running time in typical use-cases. We perform a comprehensive evaluation of the quality and performance with single-GPU and multi-GPU acceleration using a data set of 3875 protein-ligand complexes. The algorithmic ideas, data structure design choices, and performance optimization techniques shed light on GPU acceleration of other structure-based molecular docking software tools.

P3DOCK: a protein-RNA docking webserver based on template-based and template-free docking

MOTIVATION

The main function of protein-RNA interaction is to regulate the expression of genes. Therefore, studying protein-RNA interactions is of great significance. The information of three-dimensional (3D) structures reveals that atomic interactions are particularly important. The calculation method for modeling a 3D structure of a complex mainly includes two strategies: free docking and template-based docking. These two methods are complementary in protein-protein docking. Therefore, integrating these two methods may improve the prediction accuracy.

RESULTS

In this article, we compare the difference between the free docking and the template-based algorithm. Then we show the complementarity of these two methods. Based on the analysis of the calculation results, the transition point is confirmed and used to integrate two docking algorithms to develop P3DOCK. P3DOCK holds the advantages of both algorithms. The results of the three docking benchmarks show that P3DOCK is better than those two non-hybrid docking algorithms. The success rate of P3DOCK is also higher (3-20%) than state-of-the-art hybrid and non-hybrid methods. Finally, the hierarchical clustering algorithm is utilized to cluster the P3DOCK's decoys. The clustering algorithm improves the success rate of P3DOCK. For ease of use, we provide a P3DOCK webserver, which can be accessed at www.rnabinding.com/P3DOCK/P3DOCK.html. An integrated protein-RNA docking benchmark can be downloaded from http://rnabinding.com/P3DOCK/benchmark.html.

AVAILABILITY AND IMPLEMENTATION

www.rnabinding.com/P3DOCK/P3DOCK.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Preparation of Biphenyl-Conjugated Bromotyrosine for Inhibition of PD-1/PD-L1 Immune Checkpoint Interactions

Cancer immunotherapy has been revolutionized by the development of monoclonal antibodies (mAbs) that inhibit interactions between immune checkpoint molecules, such as programmed cell-death 1 (PD-1), and its ligand PD-L1. However, mAb-based drugs have some drawbacks, including poor tumor penetration and high production costs, which could potentially be overcome by small molecule drugs. BMS-8, one of the potent small molecule drugs, induces homodimerization of PD-L1, thereby inhibiting its binding to PD-1. Our assay system revealed that BMS-8 inhibited the PD-1/PD-L1 interaction with IC₅₀ of 7.2 μM. To improve the IC₅₀ value, we designed and synthesized a small molecule based on the molecular structure of BMS-8 by in silico simulation. As a result, we successfully prepared a biphenyl-conjugated bromotyrosine (X) with IC₅₀ of 1.5 μM, which was about five times improved from BMS-8. We further prepared amino acid conjugates of X (amino-X), to elucidate a correlation between the docking modes of the amino-Xs and IC₅₀ values. The results suggested that the displacement of amino-Xs from the BMS-8 in the pocket of PD-L1 homodimer correlated with IC₅₀ values. This observation provides us a further insight how to derivatize X for better inhibitory effect.

Druggable exosites of the human kino-pocketome

Small molecules binding at any of the multiple regulatory sites on the molecular surface of a protein kinase may stabilize or disrupt the corresponding interaction, leading to consequent modulation of the kinase cellular activity. As such, each of these sites represents a potential drug target. Even targeting sites outside the immediate ATP site, the so-called exosites, may cause desirable biological effects through an allosteric mechanism. Targeting exosites can alleviate adverse effects and toxicity that is common when ATP-site compounds bind promiscuously to many other types of kinases. In this study we have identified, catalogued, and annotated all potentially druggable exosites on the protein kinase domains within the existing structural human kinome. We then priority-ranked these exosites by those most amenable to drug design. In order to identify pockets that are either consistent across the kinome, or unique and specific to a particular structure, we have also implemented a normalized representation of all pockets, and displayed these graphically. Finally, we have built a database and designed a web-based interface for users interested in accessing the 3-dimensional representations of these pockets. We envision this information will assist drug discovery efforts searching for untargeted binding pockets in the human kinome.

Multi-target dopamine D3 receptor modulators: Actionable knowledge for drug design from molecular dynamics and machine learning

Local changes in the structure of G-protein coupled receptors (GPCR) binders largely affect their pharmacological profile. While the sought efficacy can be empirically obtained by introducing local modifications, the underlining structural explanation can remain elusive. Here, molecular dynamics (MD) simulations of the eticlopride-bound inactive state of the Dopamine D3 Receptor (D3DR) have been clustered using a machine learning-based approach in the attempt to rationalize the efficacy change in four congeneric modulators. Accumulating extended MD trajectories of receptor-ligand complexes, we observed how the increase in ligand flexibility progressively destabilized the crystal structure of the inactivated receptor. To prospectively validate this model, a partial agonist was rationally designed based on structural insights and computational modeling, and eventually synthesized and tested. Results turned out to be in line with the predictions. This case study suggests that the investigation of ligand flexibility in the framework of extended MD simulations can assist and inform drug design strategies, highlighting its potential role as a powerful in silico counterpart to functional assays.

Structural consequences of BMPR2 kinase domain mutations causing pulmonary arterial hypertension

Bone morphogenetic proteins (BMPs) are secreted ligands of the transforming growth factor-β (TGF-β) family that control embryonic patterning, as well as tissue development and homeostasis. Loss of function mutations in the type II BMP receptor BMPR2 are the leading cause of pulmonary arterial hypertension (PAH), a rare disease of vascular occlusion that leads to high blood pressure in the pulmonary arteries. To understand the structural consequences of these mutations, we determined the crystal structure of the human wild-type BMPR2 kinase domain at 2.35 Å resolution. The structure revealed an active conformation of the catalytic domain that formed canonical interactions with the bound ligand Mg-ADP. Disease-associated missense mutations were mapped throughout the protein structure, but clustered predominantly in the larger kinase C-lobe. Modelling revealed that the mutations will destabilize the protein structure by varying extents consistent with their previously reported functional heterogeneity. The most severe mutations introduced steric clashes in the hydrophobic protein core, whereas those found on the protein surface were less destabilizing and potentially most favorable for therapeutic rescue strategies currently under clinical investigation.

Discovery of holoenzyme-disrupting chemicals as substrate-selective CK2 inhibitors

CK2 is a constitutively active protein kinase overexpressed in numerous malignancies. Interaction between CK2α and CK2β subunits is essential for substrate selectivity. The CK2α/CK2β interface has been previously targeted by peptides to achieve functional effects; however, no small molecules modulators were identified due to pocket flexibility and open shape. Here we generated numerous plausible conformations of the interface using the fumigation modeling protocol, and virtually screened a compound library to discover compound 1 that suppressed CK2α/CK2β interaction in vitro and inhibited CK2 in a substrate-selective manner. Orthogonal SPR, crystallography, and NMR experiments demonstrated that 4 and 6, improved analogs of 1, bind to CK2α as predicted. Both inhibitors alter CK2 activity in cells through inhibition of CK2 holoenzyme formation. Treatment with 6 suppressed MDA-MB231 triple negative breast cancer cell growth and induced apoptosis. Altogether, our findings exemplify an innovative computational-experimental approach and identify novel non-peptidic inhibitors of CK2 subunit interface disclosing substrate-selective functional effects.

Protein Phosphatase 1-Targeting Small-Molecule C31 Inhibits Ebola Virus Replication

Background

Ebola virus (EBOV) infection causes severe hemorrhagic fever. EBOV transcription is controlled by host protein phosphatase 1 (PP1), which dephosphorylates VP30 protein. We previously developed 1E7-03, a compound targeting a noncatalytic site of PP1 that induced VP30 phosphorylation and inhibited EBOV transcription. Here, we attempted to further improve 1E7-03, which was not stable in murine serum.

Results

High-throughput screening with EBOV-green fluorescent protein was conducted on 72 1E7-03 analogs and identified 6 best inhibitory and the least toxic compounds. A parallel in silico screening of compounds from the ZINC database by docking to PP1 identified the best-binding compound C31, which was also present among the top 6 compounds found in the viral screen. C31 showed the best EBOV inhibitory activity among the top 6 compounds and also inhibited EBOV minigenome. C31 bound to the PP1 C-terminal groove in vitro and increased VP30 phosphorylation in cultured cells. C31 demonstrated improved stability in mouse plasma and cell permeability, compared with 1E7-03. It was also detected for 24 hours after injection in mice.

Conclusion

C31 represents a novel PP1-targeting EBOV inhibitor with improved pharmacological properties that can be further evaluated for future antifiloviral therapy.

Nilotinib, an approved leukemia drug, inhibits smoothened signaling in Hedgehog-dependent medulloblastoma

Dysregulation of the seven-transmembrane (7TM) receptor Smoothened (SMO) and other components of the Hedgehog (Hh) signaling pathway contributes to the development of cancers including basal cell carcinoma (BCC) and medulloblastoma (MB). However, SMO-specific antagonists produced mixed results in clinical trials, marked by limited efficacy and high rate of acquired resistance in tumors. Here we discovered that Nilotinib, an approved inhibitor of several kinases, possesses an anti-Hh activity, at clinically achievable concentrations, due to direct binding to SMO and inhibition of SMO signaling. Nilotinib was more efficacious than the SMO-specific antagonist Vismodegib in inhibiting growth of two Hh-dependent MB cell lines. It also reduced tumor growth in subcutaneous MB mouse xenograft model. These results indicate that in addition to its known activity against several tyrosine-kinase-mediated proliferative pathways, Nilotinib is a direct inhibitor of the Hh pathway. The newly discovered extension of Nilotinib's target profile holds promise for the treatment of Hh-dependent cancers.

ZYH005, a novel DNA intercalator, overcomes all-trans retinoic acid resistance in acute promyelocytic leukemia

Despite All-trans retinoic acid (ATRA) has transformed acute promyelocytic leukemia (APL) from the most fatal to the most curable hematological cancer, there remains a clinical challenge that many high-risk APL patients who fail to achieve a complete molecular remission or relapse and become resistant to ATRA. Herein, we report that 5-(4-methoxyphenethyl)-[1, 3] dioxolo [4, 5-j] phenanthridin-6(5H)-one (ZYH005) exhibits specific anticancer effects on APL and ATRA-resistant APL in vitro and vivo, while shows negligible cytotoxic effect on non-cancerous cell lines and peripheral blood mononuclear cells from healthy donors. Using single-molecule magnetic tweezers and molecule docking, we demonstrate that ZYH005 is a DNA intercalator. Further mechanistic studies show that ZYH005 triggers DNA damage, and caspase-dependent degradation of the PML-RARa fusion protein. As a result, APL and ATRA-resistant APL cells underwent apoptosis upon ZYH005 treatment and this apoptosis-inducing effect is even stronger than that of arsenic trioxide and anticancer agents including 5-fluorouracil, cisplatin and doxorubicin. Moreover, ZYH005 represses leukemia development in vivo and prolongs the survival of both APL and ATRA-resistant APL mice. To our knowledge, ZYH005 is the first synthetic phenanthridinone derivative, which functions as a DNA intercalator and can serve as a potential candidate drug for APL, particularly for ATRA-resistant APL.

Structural bioinformatics analysis of variants on GPCR function

G protein-coupled receptors (GPCRs) are key membrane-embedded receptor proteins, with critical roles in cellular signal transduction. In the era of precision medicine, understanding the role of natural variants on GPCR function is critical, especially from a pharmacogenomics viewpoint. Studies involved in mapping variants to GPCR structures are briefly reviewed here. The endocannabinoid system involving the central nervous system (CNS), the human cannabinoid receptor 1 (CB1), is an important drug target and its variability has implications for disease susceptibility and altered drug and pain response. We have carried out a computational study to map deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) to CB1. CB1 mutations were computationally evaluated from neutral to deleterious, and the top twelve deleterious mutations, with structural information, were found to be either close to the ligand binding region or the G-protein binding site. We have mapped these to the active and inactive CB1 X-ray crystallographic structures to correlate variants with available phenotypic information. We have also carried out molecular dynamics simulations to functionally characterize four selected mutants.

Benzothiazole-based cyanines as fluorescent "light-up" probes for duplex and quadruplex DNA

Analogs of benzothiazole orange (BO) with one, two or three methylbenzothiazolylmethylidene substituents in the 1-methylpyridinium ring were obtained from the respective picolinium, lutidinium or collidinium salts. Fluorescence parameters of the known and new dyes in complexes with various DNA structures, including G-quadruplexes (G4s) and i-motifs (IMs), were analyzed. All dyes efficiently distinguished G4s and ss-DNA. The bi- and tri-substituted derivatives had basically similar distributions of relative fluorescence intensities. The mono-substituted derivatives exhibited enhanced sensitivity to parallel G4s. All dyes were particularly sensitive to a G4 structure with an additional duplex module (the thrombin-binding aptamer TBA31), presumably due to a distinctive binding mode (interaction with the junction between the two modules). In particular, BO showed a strong (160-fold) enhancement in fluorescence quantum yield in complex with TBA31 compared to the free dye. The fluorescence quantum yields of the 2,4-bisubstituted derivative in complex with well-characterized G4s from oncogene promoters were in the range of 0.04-0.28, i.e. comparable to those of ThT. The mono/bi-substituted derivatives should be considered as possible light-up probes for G4 formation.

MedusaDock 2.0: Efficient and Accurate Protein-Ligand Docking With Constraints

Molecular docking is the key ingredient of virtual drug screening, a promising and cost-effective approach for finding new drugs. A critical limitation of this approach is the inadequate sampling efficiency of both ligand and/or receptor conformations for finding the lowest energy bound state. To circumvent this limitation, we develop a protein-ligand docking methodology capable of incorporating structural constraints, experimentally derived or theoretically predicted, to improve accuracy and efficiency. We develop a web server with a user-friendly online graphical interface as a platform for accurate and efficient protein-ligand molecule docking.

Comprehensive assessment of flexible-ligand docking algorithms: current effectiveness and challenges

Protein-ligand docking has been playing an important role in modern drug discovery. To model drug-target binding in real systems, a number of flexible-ligand docking algorithms with different sampling strategies and scoring methods have been subsequently developed over the past three decades, while rigid-ligand docking is still being used because of its compelling computational efficiency. Here, a comprehensive assessment has been conducted to investigate the effectiveness of flexible-ligand docking versus rigid-ligand docking for three representative docking algorithms (global optimization, incremental construction and multi-conformer docking) in virtual screening and pose prediction on the Directory of Useful Decoys. It was found that overall flexible-ligand docking did not achieve a statistically significant improvement in enrichments over rigid-ligand docking in virtual screening, but all docking programs significantly improved the success rates when considering ligand flexibility in pose prediction. The worse effectiveness of flexible-ligand docking in virtual screening than in pose prediction suggests that the challenges of current docking algorithms exist in ranking more than docking, although the use of flexible-ligand docking in virtual screening was justified by its better effectiveness for more flexible ligand in virtual screening. Challenges for scoring, including internal energy, charge polarization, entropy and flexibility, were investigated and discussed. An empirical way was also proposed to consider loss of ligand conformational entropy for virtual screening.

Protein-Protein Docking in Drug Design and Discovery

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

Structure-Based Discovery of a Selective KDM5A Inhibitor that Exhibits Anti-Cancer Activity via Inducing Cell Cycle Arrest and Senescence in Breast Cancer Cell Lines

Breast cancer is the one of the most frequent causes of female cancer mortality. KDM5A, a histone demethylase, can increase the proliferation, metastasis, and drug resistance of cancers, including breast cancer, and is thus an important therapeutic target. In the present work, we performed hierarchical virtual screening towards the KDM5A catalytic pocket from a chemical library containing 90,000 compounds. Using multiple biochemical methods, the cyclopenta[c]chromen derivative 1 was identified as the top candidate for KDM5A demethylase inhibitory activity. Compared with the well-known KDM5 inhibitor CPI-455 (18), 1 exhibited higher potency against KDM5A and much higher selectivity for KDM5A over both KDM4A and other KDM5 family members (KDM5B and KDM5C). Additionally, compound 1 repressed the proliferation of various KDM5A-overexpressing breast cancer cell lines. Mechanistically, 1 promoted accumulation of p16 and p27 by blocking KDM5A-mediated H3K4me3 demethylation, leading to cell cycle arrest and senescence. To date, compound 1 is the first cyclopenta[c]chromen-based KDM5A inhibitor reported, and may serve as a novel motif for developing more selective and efficacious pharmacological molecules targeting KDM5A. In addition, our research provides a possible anti-cancer mechanism of KDM5A inhibitors and highlights the feasibility and significance of KDM5A as a therapeutic target for KDM5A-overexpressing breast cancer.

Characterization and Thermal Denaturation Kinetic Analysis of Recombinant l-Amino Acid Ester Hydrolase from Stenotrophomonas maltophilia

Stenotrophomonas maltophilia HS1 exhibits l-amino acid ester hydrolase (SmAEH) activity, which can synthesize dipeptides such as Ile-Trp, Val-Gly, and Trp-His from the corresponding amino acid methyl esters and amino acids. The gene encoding SmAEH was cloned and expressed in Escherichia coli and was purified and characterized. SmAEH shared 77% sequence identity with a known amino acid ester hydrolase (AEH) from Xanthomonas citri, which belongs to a class of β-lactam antibiotic acylases. The thermal stability of SmAEH was evaluated using various mathematical models to assess its industrial potential. First-order kinetics provided the best description for the inactivation of the enzyme over a temperature range of 35-50 °C. Decimal reduction time ranged from 212.76 to 3.44 min, with a z value of 8.06 °C, and the deactivation energy was 204.1 kJ mol^-1.

Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

Structure-based virtual screening (VS) is a widely used approach that employs the knowledge of the three-dimensional structure of the target of interest in the design of new lead compounds from large-scale molecular docking experiments. Through the prediction of the binding mode and affinity of a small molecule within the binding site of the target of interest, it is possible to understand important properties related to the binding process. Empirical scoring functions are widely used for pose and affinity prediction. Although pose prediction is performed with satisfactory accuracy, the correct prediction of binding affinity is still a challenging task and crucial for the success of structure-based VS experiments. There are several efforts in distinct fronts to develop even more sophisticated and accurate models for filtering and ranking large libraries of compounds. This paper will cover some recent successful applications and methodological advances, including strategies to explore the ligand entropy and solvent effects, training with sophisticated machine-learning techniques, and the use of quantum mechanics. Particular emphasis will be given to the discussion of critical aspects and further directions for the development of more accurate empirical scoring functions.