Ligand Binding Modes Research Articles

Field-evolved resistance to neonicotinoids in the mosquito, Anopheles gambiae, is associated with mutations of nicotinic acetylcholine receptor subunits combined with cytochrome P450-mediated detoxification

New insecticides prequalified for malaria control interventions include modulators of nicotinic acetylcholine receptors that act selectively on different subunits leading to variable sensitivity among arthropods. This study aimed to investigate the molecular mechanisms underlying contrasting susceptibility to neonicotinoids observed in wild populations of two mosquito sibling species. Bioassays and a synergist test with piperonyl butoxide revealed that the sister taxa, Anopheles gambiae and An. coluzzii, from Yaounde, Cameroon, both have the potential to develop resistance to acetamiprid through cytochrome P450-mediated detoxification. However, contrary to An. coluzzii, An. gambiae populations are evolving cross-resistance to several active ingredients facilitated by mutations of nicotinic acetylcholine receptors (nAChRs). We sequenced coding regions on the β1 and α6 nAChR subunits where variants associated with resistance to neonicotinoids or to spinosyns have been found in agricultural pests and detected no mutation in An. coluzzii. By contrast, six nucleotide substitutions including an amino acid change in one of the loops that modulate ligand binding and affect sensitivity were present in the resistant species, An. gambiae. Allele frequency distributions were consistent with the spread of beneficial mutations that likely reduce the affinity of An. gambiae nAChRs for synthetic modulators. Our findings provide critical information for the application and resistance management of nAChR modulators in malaria prevention.

From [2Mn2S] Diamond Cores to Butterfly Rhombs: Transformations That Highlight Alternating Peptide Binding Sites.

Thiocarboxamide chelates are known to assemble [2Mn2S] diamond core complexes via μ-S bridges that connect two MnI(CO)3 fragments. These can exist as syn- and anti-isomers and interconvert via 16-electron, monomeric intermediates. Herein, we demonstrate that reduction of such Mn2 derivatives leads to a loss of one thiocarboxamide ligand and a switch of ligand binding mode from an O- to N-donor of the amide group, yielding a dianionic butterfly rhomb with a short Mn0-Mn0 distance, 2.52 Å. Structural and chemical analyses suggest that reduction of the Mn(I) centers is dependent on the protonation state of the amide-H, as total deprotonation followed by reduction does not result in the reduction of the Mn2 core. Partial deprotonation followed by reduction suggests a pathway that involves monomeric Mn(CO)3(S-O) and Mn(CO)3(S-N) intermediates. Ligand modifications to tertiary amides that remove the possibility of amide-H reduction led to complexes that preserve the [2Mn2S] diamond core during chemical reduction. Further comparison with the tethered system, linking the Mn(CO)3(S-O) sites together, suggests that dimer dissociation is necessary for the overall reductive transformation. These results highlight organomanganese carbonyl chemistry to establish illustrations of peptide fragment binding modes in the uptake of low-valent metal carbonyls related to binuclear active sites of biocatalysts.

Biased activation of the vasopressin V2 receptor probed by molecular dynamics simulations, NMR and pharmacological studies

G protein-coupled receptors (GPCRs) control critical cell signaling. Their response to extracellular stimuli involves conformational changes to convey signals to intracellular effectors, among which the most important are G proteins and β-arrestins (βArrs). Biased activation of one pathway is a field of intense research in GPCR pharmacology. Combining NMR, site-directed mutagenesis, molecular pharmacology, and molecular dynamics (MD) simulations, we studied the conformational diversity of the vasopressin V2 receptor (V2R) bound to different types of ligands: the antagonist Tolvaptan, the endogenous unbiased agonist arginine-vasopressin, and MCF14, a partial Gs protein-biased agonist. A double-labeling NMR scheme was developed to study the receptor conformational changes and ligand binding: V2R was subjected to lysine 13CH3 methylation for complementary NMR studies, whereas the agonists were tagged with a paramagnetic probe. Paramagnetic relaxation enhancements and site-directed mutagenesis validated the ligand binding modes in the MD simulations. We found that the bias for the Gs protein over the βArr pathway involves interactions between the conserved NPxxY motif in the transmembrane helix 7 (TM7) and TM3, compacting helix 8 (H8) toward TM1 and likely inhibiting βArr signaling. A similar mechanism was elicited for the pathogenic mutation I130N, which constitutively activates the Gs proteins without concomitant βArr recruitment. The findings suggest common patterns of biased signaling in class A GPCRs, as well as a rationale for the design of G protein-biased V2R agonists.

Mono-palmitoyl-N-alkylurea ligands as specific activators of human Toll-like receptor 2/6 heterodimer.

Ligands for Toll-like-receptor 2 (TLR2) have demonstrated significant potential as immune-stimulating components in synthetic vaccines. Activation of TLR2 relies on the formation of dimeric complexes with either TLR1 or TLR6 and the nature of these dimers can impact therapeutic outcomes. The lipopeptide-based TLR2 ligands Pam3CysSK4 and Pam2CysSK4 have been extensively studied, and their recognition by different TLR-receptor heterodimers, TLR2/TLR1 and TLR2/TLR6, respectively, has been established. However, the high lipophilicity of these ligands, containing multiple palmitoyl residues, can result in solubility issues when used as vaccine adjuvants. To address this, we previously synthesized a less lipophilic ligand containing a single palmitoyl chain called mini-UPam, which effectively stimulates human moDC maturation. We here probe the receptor-dimer specificity of several mini-Upam derivatives and reveal that these mini-UPam are hTLR2/TLR6 selective ligands and that the introduction of longer urea alkyl chains does not shift the binding specificity to hTLR2/TLR1 heterodimers, in contrast to their Pam2CysSK4 and Pam3CysSK4 counterparts, pointing to a different binding mode of the UPam ligands.

Structural basis of μ-opioid receptor targeting by a nanobody antagonist

The μ-opioid receptor (μOR), a prototypical G protein-coupled receptor (GPCR), is the target of opioid analgesics such as morphine and fentanyl. Due to the severe side effects of current opioid drugs, there is considerable interest in developing novel modulators of μOR function. Most GPCR ligands today are small molecules, however biologics, including antibodies and nanobodies, represent alternative therapeutics with clear advantages such as affinity and target selectivity. Here, we describe the nanobody NbE, which selectively binds to the μOR and acts as an antagonist. We functionally characterize NbE as an extracellular and genetically encoded μOR ligand and uncover the molecular basis for μOR antagonism by determining the cryo-EM structure of the NbE-μOR complex. NbE displays a unique ligand binding mode and achieves μOR selectivity by interactions with the orthosteric pocket and extracellular receptor loops. Based on a β-hairpin loop formed by NbE that deeply protrudes into the μOR, we design linear and cyclic peptide analogs that recapitulate NbE’s antagonism. The work illustrates the potential of nanobodies to uniquely engage with GPCRs and describes lower molecular weight μOR ligands that can serve as a basis for therapeutic developments.

Screening the effective components of Lysionotus pauciflorus Maxim. on the treatment of LPS induced acute lung injury mice by integrated UHPLC-Q-TOF-MS/MS and network pharmacology

Ethnopharmacological relevanceAcute lung injury (ALI) is an inflammatory reaction produced through various injury-causing factors acting on the lungs in a direct or indirect way, with a high morbidity and mortality rate. A review of clinical experience has revealed that Lysionotus pauciflorus Maxim (LP) has a significant therapeutic effect on ALI. However, the comprehensive effective components of LP are uncertain, and the mechanisms, especially the potential therapeutic target for anti-ALI, are still unknown. Aims of the studyIn vitro and in vivo validation of the pharmacodynamics of LP in the treatment of ALI and exploration of its potential mechanism of action based on network pharmacology, molecular docking and experimental validation. Materials and methodsUltra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) was employed to identify the ingredients of LP extracts. The potential bioactive ingredients, key targets and signalling pathways were identified by network pharmacology, based on the results of the mass spectrometry analysis. Subsequently, molecular docking was performed on the screened core components and key targets to calculate their molecular binding energies and binding potentials, and to explore the mutual binding modes of small-molecule ligands and large-molecule proteins. Finally, lipopolysaccharide (LPS)-induced RAW264.7 cell model and ALI mice model were used to validate the therapeutic effects and potential mechanism of LP extract towards ALI. ResultsFrom the mass spectrometry results of LP extracts, a total of 89 chemical components were identified, including 46 phenylethanol glycosides, 26 flavonoids, 9 organic acids and their derivatives and 8 other compounds. And furthermore 39 core active components were screened by network pharmacology. The top 10 core components (4 phenylethanol glycosides, 6 flavonoids) have been screened in the composition -target-disease network, and 37 core targets related to LP efficacy were obtained by fitting PPI network analysis. 10 signalling pathways and their targets associated with LP treatment of ALI were obtained by GO/KEGG analysis, indicating that LP could regulate TLR4 and NF-κB signalling pathways through 4 key targets, namely NFKB1, RELA, TLR4 and TNF. The results of the molecular docking procedure indicated a strong affinity, with the binding energies between each component and the target site being less than −6 kcal/mol. The binding modes included Hydrogen Bonds, Pi-Pi interaction, Hydrophobic Interactions, Salt Bridges, Pi-cation interactions. These observations were subsequently validated in vitro and in vivo experiments. The outcomes of in vitro and in vivo experiments demonstrated that LP was effective in reducing the infiltration of inflammatory bacteria in lung tissues and attenuated the expression of pro-inflammatory cytokines in LPS-stimulated mice bronchoalveolar lavage fluid (BALF) and RAW264.7 cells. Furthermore, LP inhibited the expression and phosphorylation of TLR4 protein and NF-κB protein, thus playing a role in the prevention of ALI. ConclusionsIn this study, mass spectrometry analysis was combined with biomolecular networks to initially elucidate the potential of LP to treat ALI by modulating the TLR4/NF-κB pathway. This offers a definitive experimental basis for the development of new LP drugs.

Structural insights into the human P2X1 receptor and ligand interactions.

The P2X1 receptor is a trimeric ligand-gated ion channel that plays an important role in urogenital and immune functions, offering the potential for new drug treatments. However, progress in this area has been hindered by limited structural information and a lack of well-characterised tool compounds. In this study, we employ cryogenic electron microscopy (cryo-EM) to elucidate the structures of the P2X1 receptor in an ATP-bound desensitised state and an NF449-bound closed state. NF449, a potent P2X1 receptor antagonist, engages the receptor distinctively, while ATP, the endogenous ligand, binds in a manner consistent with other P2X receptors. To explore the molecular basis of receptor inhibition, activation, and ligand interactions, key residues involved in ligand and metal ion binding were mutated. Radioligand binding assays with [3H]-α,β-methylene ATP and intracellular calcium ion influx assays were used to evaluate the effects of these mutations. These experiments validate key ligand-receptor interactions and identify conserved and non-conserved residues critical for ligand binding or receptor modulation. This research expands our understanding of the P2X1 receptor structure at a molecular level and opens new avenues for in silico drug design targeting the P2X1 receptor.

The Potential of Molecular Docking for Predictive Toxicology.

Molecular modeling techniques are widely used in medicinal chemistry for the study of biological targets, the rational design of new drugs, or the investigation of their mechanism of action.They are also applied in toxicology to identify chemical potential harmful effects.Molecular docking is a computational technique to predict the ligand binding mode and evaluate the interaction energy with a biological target.This chapter describes a computational workflow to predict possible endocrine disruptors on peroxisome proliferator-activated receptor alpha (PPARα), a nuclear receptor involved in glucose and lipid metabolism. The analyzed compounds are food contact chemicals, natural or synthetic substances intentionally added to food or released from the package or during production or technological processes.

Absolute Binding Free Energies with OneOPES.

The calculation of absolute binding free energies (ABFEs) for protein-ligand systems has long been a challenge. Recently, refined force fields and algorithms have improved the quality of the ABFE calculations. However, achieving the level of accuracy required to inform drug discovery efforts remains difficult. Here, we present a transferable enhanced sampling strategy to accurately calculate absolute binding free energies using OneOPES with simple geometric collective variables. We tested the strategy on two protein targets, BRD4 and Hsp90, complexed with a total of 17 chemically diverse ligands, including both molecular fragments and drug-like molecules. Our results show that OneOPES accurately predicts protein-ligand binding affinities with a mean unsigned error within 1 kcal mol-1 of experimentally determined free energies, without the need to tailor the collective variables to each system. Furthermore, our strategy effectively samples different ligand binding modes and consistently matches the experimentally determined structures regardless of the initial protein-ligand configuration. Our results suggest that the proposed OneOPES strategy can be used to inform lead optimization campaigns in drug discovery and to study protein-ligand binding and unbinding mechanisms.

Investigating the Antimicrobial Properties of Essential Oil Constituents and Their Mode of Action.

Essential oils (EOs) and plant extracts, rich in beneficial chemical compounds, have diverse applications in medicine, food, cosmetics, and agriculture. This study investigates the antibacterial activity of nine essential oil constituents (EOCs) against Escherichia coli, focusing on the effects of treatment pH and biosynthetic requirements. The impact of EOCs on bacterial inactivation in E. coli strains was examined using both nonselective and selective culture media. Computer-assisted drug design (CADD) methods were employed to identify critical binding sites and predict the main binding modes of ligands to proteins. The EOCs, including citral, α-terpinyl acetate, α-terpineol, and linalool, demonstrated significant bacterial inactivation, particularly under acidic conditions. This study revealed that EOCs have an effect on the presence of sublethal damage to both the cytoplasmic membrane and the outer membrane in Gram-negative bacteria. Adding penicillin G to the repair medium prevents the recovery of sublethal injuries in E. coli treated with α-terpinyl acetate, α-terpineol, linalool, and citral, indicating that peptidoglycan synthesis is essential for recovering from these injuries. However, penicillin G did not hinder the recovery process of most sublethally injured cells treated with the other assessed EOCs. Molecular docking studies revealed the favorable binding interactions of α-terpinyl acetate, α-terpineol, linalool, and citral with the β-lactamase enzyme Toho-1, indicating their potential as effective antibacterial agents. The findings suggest that EOCs could serve as viable alternatives to synthetic preservatives, offering new strategies for combating antibiotic-resistant bacteria.

The path to the G protein-coupled receptor structural landscape: Major milestones and future directions.

G protein-coupled receptors (GPCRs) play a crucial role in cell function by transducing signals from the extracellular environment to the inside of the cell. They mediate the effects of various stimuli, including hormones, neurotransmitters, ions, photons, food tastants and odorants, and are renowned drug targets. Advancements in structural biology techniques, including X-ray crystallography and cryo-electron microscopy (cryo-EM), have driven the elucidation of an increasing number of GPCR structures. These structures reveal novel features that shed light on receptor activation, dimerization and oligomerization, dichotomy between orthosteric and allosteric modulation, and the intricate interactions underlying signal transduction, providing insights into diverse ligand-binding modes and signalling pathways. However, a substantial portion of the GPCR repertoire and their activation states remain structurally unexplored. Future efforts should prioritize capturing the full structural diversity of GPCRs across multiple dimensions. To do so, the integration of structural biology with biophysical and computational techniques will be essential. We describe in this review the progress of nuclear magnetic resonance (NMR) to examine GPCR plasticity and conformational dynamics, of atomic force microscopy (AFM) to explore the spatial-temporal dynamics and kinetic aspects of GPCRs, and the recent breakthroughs in artificial intelligence for protein structure prediction to characterize the structures of the entire GPCRome. In summary, the journey through GPCR structural biology provided in this review illustrates how far we have come in decoding these essential proteins architecture and function. Looking ahead, integrating cutting-edge biophysics and computational tools offers a path to navigating the GPCR structural landscape, ultimately advancing GPCR-based applications.

Field-evolved resistance to neonicotinoids in the mosquito, Anopheles gambiae, is associated with downregulation and mutations of nicotinic acetylcholine receptor subunits combined with cytochrome P450-mediated detoxification.

Neonicotinoid insecticides act selectively on their nicotinic receptor targets leading to variable sensitivity among arthropods. This study aimed to investigate the molecular mechanisms underlying contrasting susceptibility to neonicotinoids observed in wild populations of two mosquito sibling species. Bioassays and a synergism test revealed that the sister taxa, Anopheles gambiae and An. coluzzii, from Yaounde, Cameroon, rely on cytochrome P450s to detoxify neonicotinoids and develop resistance. However, contrary to An. coluzzii, An. gambiae populations are evolving stronger resistance to several active ingredients facilitated by mutations and reduced expression of nicotinic acetylcholine receptors. Six mutations were detected in coding sequences of the β1 and α6 subunits, including two substitutions in one of the loops that modulate ligand binding and sensitivity. Allele frequencies were strongly correlated with a susceptibility gradient between An. coluzzii and An. gambiae suggesting that the mutations may play a key role in sensitivity. Messenger RNA expression levels of the β1, α3, and α7 subunits decreased dramatically, on average by 23.27, 17.50, 15.80-fold, respectively, in wild An. gambiae populations compared to a susceptible insectary colony. By contrast, only the β2 and α9-1 subunits were moderately downregulated (5.28 and 2.67-fold change, respectively) in field-collected An. coluzzii adults relative to susceptible colonized mosquitoes. Our findings provide critical information for the application and resistance management of neonicotinoids in malaria prevention.

The Impact of Nanobodies on G Protein-Coupled Receptor Structural Biology and Their Potential as Therapeutic Agents.

The family of human G protein-coupled receptors (GPCRs) comprises about 800 different members, with about 35% of current pharmaceutical drugs targeting GPCRs. However, GPCR structural biology, necessary for structure-guided drug design, has lagged behind that of other membrane proteins, and it was not until the year 2000 when the first crystal structure of a GPCR (rhodopsin) was solved. Starting in 2007, the determination of additional GPCR structures was facilitated by protein engineering, new crystallization techniques, complexation with antibody fragments, and other strategies. More recently, the use of camelid heavy-chain-only antibody fragments (nanobodies) as crystallographic chaperones has revolutionized the field of GPCR structural biology, aiding in the determination of more than 340 GPCR structures to date. In most cases, the GPCR structures solved as complexes with nanobodies (Nbs) have revealed the binding mode of cognate or non-natural ligands; in a few cases, the same Nb has acted as an orthosteric or allosteric modulator of GPCR signaling. In this review, we summarize the multiple ingenious strategies that have been conceived and implemented in the last decade to capitalize on the discovery of nanobodies to study GPCRs from a structural perspective. SIGNIFICANCE STATEMENT: G protein-coupled receptors (GPCRs) are major pharmacological targets, and the determination of their structures at high resolution has been essential for structure-guided drug design and for insights about their functions. Single-domain antibodies (nanobodies) have greatly facilitated the structural determination of GPCRs by forming complexes directly with the receptors or indirectly through protein partners.

Diisobutyl-ammonium tri-phenyl(2-thiolato-acetato-κ2 O,S)stannate(IV).

Crystals of the title salt, (C8H20N)[Sn(C6H5)3(C2H2O2S)], comprise diisobutyl-ammonium cations and mercapto-acetato-tri-phenyl-stannate(IV) anions. The bidentate binding mode of the mercapto-acetate ligand gives rise to a five-coordinated, ionic tri-phenyl-tin complex with a distorted cis-trigonal-bipyramidal geometry around the tin atom. In the crystal, charge-assisted ammonium-N-H⋯O(carboxyl-ate) hydrogen-bonding connects two cations and two anions into a four-ion aggregate. Two positions were resolved for one of the phenyl rings with the major component having a site occupancy factor of 0.60 (3).

Sequence-Based Protein Design: A Review of Using Statistical Models to Characterize Coevolutionary Traits for Developing Hybrid Proteins as Genetic Sensors.

Statistical analyses of homologous protein sequences can identify amino acid residue positions that co-evolve to generate family members with different properties. Based on the hypothesis that the coevolution of residue positions is necessary for maintaining protein structure, coevolutionary traits revealed by statistical models provide insight into residue-residue interactions that are important for understanding protein mechanisms at the molecular level. With the rapid expansion of genome sequencing databases that facilitate statistical analyses, this sequence-based approach has been used to study a broad range of protein families. An emerging application of this approach is to design hybrid transcriptional regulators as modular genetic sensors for novel wiring between input signals and genetic elements to control outputs. Among many allosterically regulated regulator families, the members contain structurally conserved and functionally independent protein domains, including a DNA-binding module (DBM) for interacting with a specific genetic element and a ligand-binding module (LBM) for sensing an input signal. By hybridizing a DBM and an LBM from two different family members, a hybrid regulator can be created with a new combination of signal-detection and DNA-recognition properties not present in natural systems. In this review, we present recent advances in the development of hybrid regulators and their applications in cellular engineering, especially focusing on the use of statistical analyses for characterizing DBM-LBM interactions and hybrid regulator design. Based on these studies, we then discuss the current limitations and potential directions for enhancing the impact of this sequence-based design approach.

Exploring serial crystallography for drug discovery.

Structure-based drug design is highly dependent on the availability of structures of the protein of interest in complex with lead compounds. Ideally, this information can be used to guide the chemical optimization of a compound into a pharmaceutical drug candidate. A limitation of the main structural method used today - conventional X-ray crystallography - is that it only provides structural information about the protein complex in its frozen state. Serial crystallography is a relatively new approach that offers the possibility to study protein structures at room temperature (RT). Here, we explore the use of serial crystallography to determine the structures of the pharmaceutical target, soluble epoxide hydrolase. We introduce a new method to screen for optimal microcrystallization conditions suitable for use in serial crystallography and present a number of RT ligand-bound structures of our target protein. From a comparison between the RT structural data and previously published cryo-temperature structures, we describe an example of a temperature-dependent difference in the ligand-binding mode and observe that flexible loops are better resolved at RT. Finally, we discuss the current limitations and potential future advances of serial crystallography for use within pharmaceutical drug discovery.

Effect of molecular crowders on ligand binding kinetics with G-quadruplex DNA probed by fluorescence correlation spectroscopy

Guanine-rich single-stranded DNA folds into G-quadruplex DNA (GqDNA) structures, which play crucial roles in various biological processes. These structures are also promising targets for ligands, potentially inducing antitumor effects. While thermodynamic parameters of ligand/DNA interactions are well-studied, the kinetics of ligand interaction with GqDNA, particularly in cell-like crowded environments, remain less explored. In this study, we investigate the impact of molecular crowding agents (glucose, sucrose, and ficoll 70) at physiologically relevant concentrations (20% w/v) on the association and dissociation rates of the benzophenoxazine-core based ligand, cresyl violet (CV), with human telomeric antiparallel-GqDNA. We utilized fluorescence correlation spectroscopy (FCS) along with other techniques. Our findings reveal that crowding agents decrease the binding affinity of CV to GqDNA, with the most significant effect—a nearly three-fold decrease—observed with ficoll 70. FCS measurements indicate that this decrease is primarily due to a viscosity-induced slowdown of ligand association in the crowded environment. Interestingly, dissociation rates remain largely unaffected by smaller crowders, with only small effect observed in presence of ficoll 70 due to direct but weak interaction between the ligand and ficoll. These results along with previously reported data provide valuable insights into ligand/GqDNA interactions in cellular contexts, suggesting a conserved mechanism of saccharide crowder influence, regardless of variations in GqDNA structure and ligand binding mode. This underscores the importance of considering crowding effects in the design and development of GqDNA-targeted drugs for potential cancer treatment.

Modeling Ligands into Maps Derived from Electron Cryomicroscopy.

Deciphering the protein-ligand interactions in a macromolecular complex is crucial for understanding the molecular mechanism, underlying biological processes, and drug development. In recent years, cryogenic sample electron microscopy (cryoEM) has emerged as a powerful technique to determine the structures of macromolecules and to investigate the mode of ligand binding at near-atomic resolution. Identifying and modeling non-protein molecules in cryoEM maps is often challenging due to anisotropic resolution across the molecule of interest and inherent noise in the data. In this article, the readers are introduced to various software and methods currently used for ligand identification, model building, and refinement of atomic coordinates using selected macromolecules. One of the simplest ways to identify the presence of a ligand, as illustrated with the enolase enzyme, is to subtract the two maps obtained with and without the ligand. The extra density of the ligand is likely to stand out in the difference map even at a higher threshold. There are instances, as shown in the case of metabotropic Glutamate receptor mGlu5, when such simple difference maps cannot be generated. The recently introduced method of deriving the Fo-Fc omit map can serve as a tool for validating and demonstrating the presence of the ligand. Finally, using the well-studied β-galactosidase as an example, the effect of resolution on modeling the ligands and solvent molecules in cryoEM maps is analyzed, and an outlook on how cryoEM can be used in drug discovery is presented.

Navigating the complexities of docking tools with nicotinic receptors and acetylcholine binding proteins in the realm of neonicotinoids

Molecular docking, pivotal in predicting small-molecule ligand binding modes, struggles with accurately identifying binding conformations and affinities. This is particularly true for neonicotinoids, insecticides whose impacts on ecosystems require precise molecular interaction modeling. This study scrutinizes the effectiveness of prominent docking software (Ledock, ADFR, Autodock Vina, CDOCKER) in simulating interactions of environmental chemicals, especially neonicotinoid-like molecules with nicotinic acetylcholine receptors (nAChRs) and acetylcholine binding proteins (AChBPs). We aimed to assess the accuracy and reliability of these tools in reproducing crystallographic data, focusing on semi-flexible and flexible docking approaches. Our analysis identified Ledock as the most accurate in semi-flexible docking, while Autodock Vina with Vinardo scoring function proved most reliable. However, no software consistently excelled in both accuracy and reliability. Additionally, our evaluation revealed that none of the tools could establish a clear correlation between docking scores and experimental dissociation constants (Kd) for neonicotinoid-like compounds. In contrast, a strong correlation was found with drug-like compounds, bringing to light a bias in considered software towards pharmaceuticals, thus limiting their applicability to environmental chemicals. The comparison between semi-flexible and flexible docking revealed that the increased computational complexity of the latter did not result in enhanced accuracy. In fact, the higher computational cost of flexible docking with its lack of enhanced predictive accuracy, rendered this approach useless for this class of compounds. Conclusively, our findings emphasize the need for continued development of docking methodologies, particularly for environmental chemicals. This study not only illuminates current software capabilities but also underscores the urgency for advancements in computational molecular docking as it is a relevant tool to environmental sciences.

Chemogenomics for NR1 nuclear hormone receptors

Nuclear receptors (NRs) regulate transcription in response to ligand binding and NR modulation allows pharmacological control of gene expression. Although some NRs are relevant as drug targets, the NR1 family, which comprises 19 NRs binding to hormones, vitamins, and lipid metabolites, has only been partially explored from a translational perspective. To enable systematic target identification and validation for this protein family in phenotypic settings, we present an NR1 chemogenomic (CG) compound set optimized for complementary activity/selectivity profiles and chemical diversity. Based on broad profiling of candidates for specificity, toxicity, and off-target liabilities, sixty-nine comprehensively annotated NR1 agonists, antagonists and inverse agonists covering all members of the NR1 family and meeting potency and selectivity standards are included in the final NR1 CG set. Proof-of-concept application of this set reveals effects of NR1 members in autophagy, neuroinflammation and cancer cell death, and confirms the suitability of the set for target identification and validation.