Unraveling Activation-Related Rearrangements and Intrinsic Divergence from Ligand-Specific Conformational Changes of the Dopamine D3 and D2 Receptors.

Effective rational drug discovery hinges on understanding the functional states of the target protein and distinguishing it from homologues. However, for the G protein coupled receptors, both activation-related conformational changes (ACCs) and intrinsic divergence among receptors can be misled or obscured by ligand-specific conformational changes (LCCs). Here, we unraveled ACCs and intrinsic divergence from LCCs of the dopamine D3 and D2 receptors (D3R and D2R), by analyzing their experimentally determined structures and the molecular dynamics (MD) simulation results of the receptors bound with various ligands. In addition to the ACCs common to other aminergic receptors, we revealed unique ACCs for these two receptors, including the extracellular portion of TM5 (TM5e) and TM6e shifting away from TM2e and TM3e, with a subtle rotation of TM5e. In identifying intrinsic divergence, we found more outward tilting of TM6e in the D2R compared to the D3R in both the experimental structures and simulations bound with ligands in different scaffolds. However, this difference was drastically reduced in the simulations bound with nonselective agonist quinpirole, suggesting a misleading effect of LCCs. Further, in the quinpirole-bound simulations, TM1 showed a greater disparity between these receptors, indicating that LCCs may also obscure intrinsic divergence. Importantly, our MD simulations revealed divergence in the dynamics of these receptors. Specifically, the D2R exhibited heightened flexibility compared to the D3R in the extracellular loops and TMs 5e, 6e, and 7e, associated with its greater ligand binding site plasticity. Our results lay the groundwork for crafting ligands specifically targeting the D2R and D3R with more precise pharmacological profiles.

Open posterior approach versus endoscopic approach for thoracic ligamentum flavum ossification: a systematic review and meta-analysis.

BACKGROUND: Thoracic ossification of the ligamentum flavum (TOLF), a rare condition more prevalent in East Asia, is managed through open and endoscopic surgical approaches. Determining the superior surgical option remains unclear. This study assesses the safety and clinical outcomes associated with these approaches in TOLF patients. METHODS: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic literature search up to August 5, 2023, across PubMed, Scopus, EMBASE, Web of Science, Cochrane, and ClinicalTrials.gov. We included randomized controlled trials and cohort studies reporting complication rates, mJOA (modified Japanese Orthopedic Association) scores, JOA scores, VAS (Visual Analog Scale) scores, or hospitalization duration for both open and endoscopic surgeries in TOLF patients. RESULTS: We analyzed 37 studies encompassing 1,646 TOLF patients using a random-effects model. Our findings revealed a significant difference in complication rates (overall complication rates: 0.12; 95% CI: 0.07, 0.19; p < 0.01; I2: 69%; quality of evidence: moderate), with lower complication rates in the endoscopy group. However, no significant differences were observed in JOA scores (overall JOA: 8.35; 95% CI: 7.16, 9.54; p = 0.12; I2: 99%; quality of evidence: very low), VAS scores (overall VAS: 1.31; 95% CI: 1.03, 1.59; p = 0.35; I2: 91%; quality of evidence: very low), or hospitalization duration (hospital stay: 10.83 days; 95% CI: 6.86, 14.80; p = 0.35; I2: 91%; quality of evidence: very low) between the open and endoscopic groups. CONCLUSIONS: This meta-analysis reports lower complication rates and improved postoperative mJOA scores for endoscopic surgery in TOLF patients compared to open surgery. It represents the first comprehensive evaluation of clinical outcomes and safety of different surgical approaches for TOLF patients. Further randomized controlled trials are essential to validate these findings.

Disentangling autoproteolytic cleavage from tethered agonist-dependent activation of the adhesion receptor ADGRL3.

Adhesion G protein-coupled receptor latrophilin 3 (ADGRL3), a cell adhesion molecule highly expressed in the central nervous system, acts in synapse formation through trans interactions with its ligands. It is largely unknown if these interactions serve a purely adhesive function or can modulate G protein signaling. To assess how different structural elements of ADGRL3 (e.g., the adhesive domains, autoproteolytic cleavage site, or tethered agonist (TA)) impact receptor function, we require constructs that disrupt specific receptor features without impacting others. While we showed previously that mutating conserved Phe and Met residues in the TA of ADGRL3-C-terminal fragment (CTF), a CTF truncated to the G protein-coupled receptor proteolysis site, abolishes receptor-mediated G protein activation, we now find that autoproteolytic cleavage is disrupted in the full-length version of this construct. To identify a construct that disrupts TA-dependent activity without impacting proteolysis, we explored other mutations in the TA. We found that mutating the sixth and seventh residues of the TA, Leu and Met, to Ala impaired activity in a serum response element activity assay for both full-length and CTF constructs. We confirmed this activity loss results from impaired G protein coupling using an assay that acutely exposes the TA through controlled proteolysis. The ADGRL3 mutant expresses normally at the cell surface, and immunoblotting shows that it undergoes normal autoproteolysis. Thus, we found a construct that disrupts tethered agonism while retaining autoproteolytic cleavage, providing a tool to disentangle these functions in vivo. Our approach and specific findings are likely to be broadly applicable to other adhesion receptors.

A Novel "Activation Switch" Motif Common to All Aminergic Receptors.

Aminergic receptors are G protein-coupled receptors (GPCRs) that transduce signals from small endogenous biogenic amines to regulate intracellular signaling pathways. Agonist binding in the ligand binding pocket on the extracellular side opens and prepares a cavity on the intracellular face of the receptors to interact with and activate G proteins and ß-arrestins. Here, by reviewing and analyzing all available aminergic receptor structures, we seek to identify activation-related conformational changes that are independent of the specific scaffold of the bound agonist, which we define as "activation conformational changes" (ACCs). While some common intracellular ACCs have been well-documented, identifying common extracellular ACCs, including those in the ligand binding pocket, is complicated by local adjustments to different ligand scaffolds. Our analysis shows no common ACCs at the extracellular ends of the transmembrane helices. Furthermore, the restricted access to the ligand binding pocket identified previously in some receptors is not universal. Notably, the Trp6.48 toggle switch and the Pro5.50-Ile3.40-Phe6.44 (PIF) motif at the bottom of the ligand binding pocket have previously been proposed to mediate the conformational consequences of ligand binding to the intracellular side of the receptors. Our analysis shows that common ACCs in the ligand binding pocket are associated with the PIF motif and nearby residues, including Trp6.48, but fails to support a shared rotamer toggle associated with activation. However, we identify two common rearrangements between the extracellular and middle subsegments, and propose a novel "activation switch" motif common to all aminergic receptors. This motif includes the middle subsegments of transmembrane helices 3, 5, and 6 and integrates both the PIF motif and Trp6.48.

Toward Reducing hERG Affinities for DAT Inhibitors with a Combined Machine Learning and Molecular Modeling Approach.

Psychostimulant drugs, such as cocaine, inhibit dopamine reuptake via blockading the dopamine transporter (DAT), which is the primary mechanism underpinning their abuse. Atypical DAT inhibitors are dissimilar to cocaine and can block cocaine- or methamphetamine-induced behaviors, supporting their development as part of a treatment regimen for psychostimulant use disorders. When developing these atypical DAT inhibitors as medications, it is necessary to avoid off-target binding that can produce unwanted side effects or toxicities. In particular, the blockade of a potassium channel, human ether-a-go-go (hERG), can lead to potentially lethal ventricular tachycardia. In this study, we established a counter screening platform for DAT and against hERG binding by combining machine learning-based quantitative structure-activity relationship (QSAR) modeling, experimental validation, and molecular modeling and simulations. Our results show that the available data are adequate to establish robust QSAR models, as validated by chemical synthesis and pharmacological evaluation of a validation set of DAT inhibitors. Furthermore, the QSAR models based on subsets of the data according to experimental approaches used have predictive power as well, which opens the door to target specific functional states of a protein. Complementarily, our molecular modeling and simulations identified the structural elements responsible for a pair of DAT inhibitors having opposite binding affinity trends at DAT and hERG, which can be leveraged for rational optimization of lead atypical DAT inhibitors with desired pharmacological properties.

Effects of recommendations on message quality and community formation in online conversations.

As asynchronous online discussions gain a broader usage due to the COVID-19 epidemic, the need for understanding of students' ideas from unstructured textual data becomes more pressing. In this experimental study, we examine the effects of recommendations on message quality and community formation from voluminous online discussions. Drawing on literature from group cognition, knowledge building discourse, and learning analytics, we calculate message quasi-quality index (QQI) scores based on message lexical complexity and topic-related keyword usage by participants in explaining their ideas. Furthermore, we examine the empirical evidence on the relationship between QQI scores and participants' interactions. Finally, we visualize network structures via sociograms and hierarchically cluster participants to identify subgroups. Our analysis of 281 messages finds that recommendations helped participants to write more messages that compared alternative viewpoints and refined preliminary ideas with higher QQI scores. Results also show that recommendations cultivated a sense of collective agency to increase the opportunity for creativity and reduce the likelihood that peripheral participants will be dissatisfied and fail to identify with a community. Theoretical contributions and practical implications are discussed.

Develop a High-Throughput Screening Method to Identify C-P4H1 (Collagen Prolyl 4-Hydroxylase 1) Inhibitors from FDA-Approved Chemicals.

Collagen prolyl 4-hydroxylase 1 (C-P4H1) is an α-ketoglutarate (α-KG)-dependent dioxygenase that catalyzes 4-hydroxylation of proline on collagen. C-P4H1-induced prolyl hydroxylation is required for proper collagen deposition and cancer metastasis. Therefore, targeting C-P4H1 is considered a potential therapeutic strategy for collagen-related cancer progression and metastasis. However, no C-P4H1 inhibitors are available for clinical testing, and the high content assay is currently not available for C-P4H1 inhibitor screening. In the present study, we developed a high-throughput screening assay by quantifying succinate, a byproduct of C-P4H-catalyzed hydroxylation. C-P4H1 is the major isoform of collagen prolyl 4-hydroxylases (CP4Hs) that contributes the majority prolyl 4-hydroxylase activity. Using C-P4H1 tetramer purified from the eukaryotic expression system, we showed that the Succinate-GloTM Hydroxylase assay was more sensitive for measuring C-P4H1 activity compared with the hydroxyproline colorimetric assay. Next, we performed high-throughput screening with the FDA-approved drug library and identified several new C-P4H1 inhibitors, including Silodosin and Ticlopidine. Silodosin and Ticlopidine inhibited C-P4H1 activity in a dose-dependent manner and suppressed collagen secretion and tumor invasion in 3D tissue culture. These C-P4H1 inhibitors provide new agents to test clinical potential of targeting C-P4H1 in suppressing cancer progression and metastasis.

Efficacy of independence sampling in replica exchange simulations of ordered and disordered proteins.

Recasting temperature replica exchange (T-RE) as a special case of Gibbs sampling has led to a simple and efficient scheme for enhanced mixing (Chodera and Shirts, J. Chem. Phys., 2011, 135, 194110). To critically examine if T-RE with independence sampling (T-REis) improves conformational sampling, we performed T-RE and T-REis simulations of ordered and disordered proteins using coarse-grained and atomistic models. The results demonstrate that T-REis effectively increase the replica mobility in temperatures space with minimal computational overhead, especially for folded proteins. However, enhanced mixing does not translate well into improved conformational sampling. The convergences of thermodynamic properties interested are similar, with slight improvements for T-REis of ordered systems. The study re-affirms the efficiency of T-RE does not appear to be limited by temperature diffusion, but by the inherent rates of spontaneous large-scale conformational re-arrangements. Due to its simplicity and efficacy of enhanced mixing, T-REis is expected to be more effective when incorporated with various Hamiltonian-RE protocols. © 2017 Wiley Periodicals, Inc.

Optimization of the GBMV2 implicit solvent force field for accurate simulation of protein conformational equilibria.

Accurate treatment of solvent environment is critical for reliable simulations of protein conformational equilibria. Implicit treatment of solvation, such as using the generalized Born (GB) class of models arguably provides an optimal balance between computational efficiency and physical accuracy. Yet, GB models are frequently plagued by a tendency to generate overly compact structures. The physical origins of this drawback are relatively well understood, and the key to a balanced implicit solvent protein force field is careful optimization of physical parameters to achieve a sufficient level of cancellation of errors. The latter has been hampered by the difficulty of generating converged conformational ensembles of non-trivial model proteins using the popular replica exchange sampling technique. Here, we leverage improved sampling efficiency of a newly developed multi-scale enhanced sampling technique to re-optimize the generalized-Born with molecular volume (GBMV2) implicit solvent model with the CHARMM36 protein force field. Recursive optimization of key GBMV2 parameters (such as input radii) and protein torsion profiles (via the CMAP torsion cross terms) has led to a more balanced GBMV2 protein force field that recapitulates the structures and stabilities of both helical and ß-hairpin model peptides. Importantly, this force field appears to be free of the over-compaction bias, and can generate structural ensembles of several intrinsically disordered proteins of various lengths that seem highly consistent with available experimental data. © 2017 Wiley Periodicals, Inc.

Origins of specificity and affinity in antibody-protein interactions.

Natural antibodies are frequently elicited to recognize diverse protein surfaces, where the sequence features of the epitopes are frequently indistinguishable from those of nonepitope protein surfaces. It is not clearly understood how the paratopes are able to recognize sequence-wise featureless epitopes and how a natural antibody repertoire with limited variants can recognize seemingly unlimited protein antigens foreign to the host immune system. In this work, computational methods were used to predict the functional paratopes with the 3D antibody variable domain structure as input. The predicted functional paratopes were reasonably validated by the hot spot residues known from experimental alanine scanning measurements. The functional paratope (hot spot) predictions on a set of 111 antibody-antigen complex structures indicate that aromatic, mostly tyrosyl, side chains constitute the major part of the predicted functional paratopes, with short-chain hydrophilic residues forming the minor portion of the predicted functional paratopes. These aromatic side chains interact mostly with the epitope main chain atoms and side-chain carbons. The functional paratopes are surrounded by favorable polar atomistic contacts in the structural paratope-epitope interfaces; more that 80% these polar contacts are electrostatically favorable and about 40% of these polar contacts form direct hydrogen bonds across the interfaces. These results indicate that a limited repertoire of antibodies bearing paratopes with diverse structural contours enriched with aromatic side chains among short-chain hydrophilic residues can recognize all sorts of protein surfaces, because the determinants for antibody recognition are common physicochemical features ubiquitously distributed over all protein surfaces.

Multiscale enhanced sampling of intrinsically disordered protein conformations.

In a recently developed multiscale enhanced sampling (MSES) technique, topology-based coarse-grained (CG) models are coupled to atomistic force fields to enhance the sampling of atomistic protein conformations. Here, the MSES protocol is refined by designing more sophisticated Hamiltonian/temperature replica exchange schemes that involve additional parameters in the MSES coupling restraint potential, to more carefully control how conformations are coupled between the atomistic and CG models. A specific focus is to derive an optimal MSES protocol for simulating conformational ensembles of intrinsically disordered proteins (IDPs). The efficacy of the refined protocols, referred to as MSES-soft asymptote (SA), was evaluated using two model peptides with various levels of residual helicities. The results show that MSES-SA generates more reversible helix-coil transitions and leads to improved convergence on various ensemble conformational properties. This study further suggests that more detailed CG models are likely necessary for more effective sampling of local conformational transition of IDPs. © 2015 Wiley Periodicals, Inc.

The Structural Basis of the Activity Cliff in Modafinil-Based Dopamine Transporter Inhibitors.

Modafinil analogs with either a sulfoxide or sulfide moiety have improved binding affinities at the human dopamine transporter (hDAT) compared to modafinil, with lead sulfoxide-substituted analogs showing characteristics of atypical inhibition (e.g., JJC8-091). Interestingly, the only distinction between sulfoxide and sulfide substitution is the presence of one additional oxygen atom. To elucidate why such a subtle difference in ligand structure can result in different typical or atypical profiles, we investigated two pairs of analogs. Our quantum mechanical calculations revealed a more negatively charged distribution of the electrostatic potential surface of the sulfoxide substitution. Using molecular dynamics simulations, we demonstrated that sulfoxide-substituted modafinil analogs have a propensity to attract more water into the binding pocket. They also exhibited a tendency to dissociate from Asp79 and form a new interaction with Asp421, consequently promoting an inward-facing conformation of hDAT. In contrast, sulfide-substituted analogs did not display these effects. These findings elucidate the structural basis of the activity cliff observed with modafinil analogs and also enhance our understanding of the functionally relevant conformational spectrum of hDAT.

Unlocking the Potential of High-Quality Dopamine Transporter Pharmacological Data: Advancing Robust Machine Learning-Based QSAR Modeling.

The dopamine transporter (DAT) plays a critical role in the central nervous system and has been implicated in numerous psychiatric disorders. The ligand-based approaches are instrumental to decipher the structure-activity relationship (SAR) of DAT ligands, especially the quantitative SAR (QSAR) modeling. By gathering and analyzing data from literature and databases, we systematically assemble a diverse range of ligands binding to DAT, aiming to discern the general features of DAT ligands and uncover the chemical space for potential novel DAT ligand scaffolds. The aggregation of DAT pharmacological activity data, particularly from databases like ChEMBL, provides a foundation for constructing robust QSAR models. The compilation and meticulous filtering of these data, establishing high-quality training datasets with specific divisions of pharmacological assays and data types, along with the application of QSAR modeling, prove to be a promising strategy for navigating the pertinent chemical space. Through a systematic comparison of DAT QSAR models using training datasets from various ChEMBL releases, we underscore the positive impact of enhanced data set quality and increased data set size on the predictive power of DAT QSAR models.

Series of (([1,1'-Biphenyl]-2-yl)methyl)sulfinylalkyl Alicyclic Amines as Novel and High Affinity Atypical Dopamine Transporter Inhibitors with Reduced hERG Activity.

Currently, there are no FDA-approved medications for the treatment of psychostimulant use disorders (PSUD). We have previously discovered "atypical" dopamine transporter (DAT) inhibitors that do not display psychostimulant-like behaviors and may be useful as medications to treat PSUD. Lead candidates (e.g., JJC8-091, 1) have shown promising in vivo profiles in rodents; however, reducing hERG (human ether-à-go-go-related gene) activity, a predictor of cardiotoxicity, has remained a challenge. Herein, a series of 30 (([1,1'-biphenyl]-2-yl)methyl)sulfinylalkyl alicyclic amines was synthesized and evaluated for DAT and serotonin transporter (SERT) binding affinities. A subset of analogues was tested for hERG activity, and the IC50 values were compared to those predicted by our hERG QSAR models, which showed robust predictive power. Multiparameter optimization scores (MPO > 3) indicated central nervous system (CNS) penetrability. Finally, comparison of affinities in human DAT and its Y156F and Y335A mutants suggested that several compounds prefer an inward facing conformation indicating an atypical DAT inhibitor profile.

Modifications to 1-(4-(2-Bis(4-fluorophenyl)methyl)sulfinyl)alkyl Alicyclic Amines That Improve Metabolic Stability and Retain an Atypical DAT Inhibitor Profile.

Atypical dopamine transporter (DAT) inhibitors have shown therapeutic potential in the preclinical models of psychostimulant use disorders (PSUD). In rats, 1-(4-(2-((bis(4-fluorophenyl)methyl)sulfinyl)ethyl)-piperazin-1-yl)-propan-2-ol (JJC8-091, 3b) was effective in reducing the reinforcing effects of both cocaine and methamphetamine but did not exhibit psychostimulant behaviors itself. Improvements in DAT affinity and metabolic stability were desirable for discovering pipeline drug candidates. Thus, a series of 1-(4-(2-bis(4-fluorophenyl)methyl)sulfinyl)alkyl alicyclic amines were synthesized and evaluated for binding affinities at DAT and the serotonin transporter (SERT). Replacement of the piperazine with either a homopiperazine or a piperidine ring system was well tolerated at DAT (Ki range = 3-382 nM). However, only the piperidine analogues (20a-d) showed improved metabolic stability in rat liver microsomes as compared to the previously reported analogues. Compounds 12b and 20a appeared to retain an atypical DAT inhibitor profile, based on negligible locomotor activity in mice and molecular modeling that predicts binding to an inward-facing conformation of DAT.

Unraveling activation-related rearrangements and intrinsic divergence from ligand-induced conformational changes of the dopamine D3 and D2 receptors.

Effective rational drug discovery targeting a specific protein hinges on understanding their functional states and distinguishing it from homologs. However, for the G protein coupled receptors, both the activation-related conformational changes (ACCs) and the intrinsic divergence among receptors can be misled or obscured by ligand-induced conformational changes (LCCs). Here, we unraveled ACCs and intrinsic divergence from LCCs of the dopamine D3 and D2 receptors (D3R and D2R), by analyzing their experimentally determined structures and the molecular dynamics simulation results of the receptors bound with different ligands. In addition to the ACCs common to other aminergic receptors, we revealed unique ACCs for these two receptors including TM5e and TM6e shifting away from TM2e and TM3e, with a subtle rotation of TM5e. In identifying intrinsic divergence, we found pronounced outward tilting of TM6e in the D2R compared to the D3R in both experimental structures and simulations with ligands in different scaffolds. This tilting was drastically reduced in the simulations of the receptors bound with nonselective full agonist quinpirole, suggesting a misleading impact of LCCs. Further, in the quinpirole-bound simulations, TM1 showed a greater disparity between these receptors, indicating that LCCs may obscure intrinsic divergence. In addition, our analysis showed that the impact of the nonconserved TM1 propagated to conserved Trp7.40 and Glu2.65, both are ligand binding residues. We also found that the D2R exhibited heightened flexibility compared to the D3R in the extracellular portions of TMs 5, 6, and 7, potentially associated with its greater ligand binding site plasticity. Our results lay the groundwork for crafting ligands specifically targeting D2R or D3R with more precise pharmacological profiles.

Identification and Characterization of ML321: A Novel and Highly Selective D2 Dopamine Receptor Antagonist with Efficacy in Animal Models That Predict Atypical Antipsychotic Activity.

We have developed and characterized a novel D2R antagonist with exceptional GPCR selectivity - ML321. In functional profiling screens of 168 different GPCRs, ML321 showed little activity beyond potent inhibition of the D2R and to a lesser extent the D3R, demonstrating excellent receptor selectivity. The D2R selectivity of ML321 may be related to the fact that, unlike other monoaminergic ligands, ML321 lacks a positively charged amine group and adopts a unique binding pose within the orthosteric binding site of the D2R. PET imaging studies in non-human primates demonstrated that ML321 penetrates the CNS and occupies the D2R in a dose-dependent manner. Behavioral paradigms in rats demonstrate that ML321 can selectively antagonize a D2R-mediated response (hypothermia) while not affecting a D3R-mediated response (yawning) using the same dose of drug, thus indicating exceptional in vivo selectivity. We also investigated the effects of ML321 in animal models that are predictive of antipsychotic efficacy in humans. We found that ML321 attenuates both amphetamine- and phencyclidine-induced locomotor activity and restored pre-pulse inhibition (PPI) of acoustic startle in a dose-dependent manner. Surprisingly, using doses that were maximally effective in both the locomotor and PPI studies, ML321 was relatively ineffective in promoting catalepsy. Kinetic studies revealed that ML321 exhibits slow-on and fast-off receptor binding rates, similar to those observed with atypical antipsychotics with reduced extrapyramidal side effects. Taken together, these observations suggest that ML321, or a derivative thereof, may exhibit ″atypical″ antipsychotic activity in humans with significantly fewer side effects than observed with the currently FDA-approved D2R antagonists.

Effects of the binding of calcium ions on the structure and dynamics of the ΦX174 virus investigated using molecular dynamics.

It is known that the presence of calcium ions (Ca(2 + )) is necessary for the enterobacterial virus ΦX174 to inject its DNA into the host cell, and that some mutations in the major capsid proteins lead to better survivability at higher temperatures. Our goal in the current study is to determine the physical changes in both the wild-type and mutant virus due to the binding of Ca(2 + ). Thus, we performed molecular dynamics simulations of the ΦX174 major capsid protein complex with and without Ca(2 + ) bound. Our results show that binding of Ca(2 + ) leads to energetic and dynamical changes in the virus proteins. In particular, the results suggest that binding of Ca(2 + ) is energetically favorable and that the mutation leads to increased fluctuations of the protein complex (especially with the calcium ions bound to the complex), which may increase the rate of genome packaging and ejection for ΦX174.

Multiepitope Fusion Antigen: MEFA, an Epitope- and Structure-Based Vaccinology Platform for Multivalent Vaccine Development.

Vaccines are regarded as the most cost-effective countermeasure against infectious diseases. One challenge often affecting vaccine development is antigenic diversity or pathogen heterogeneity. Different strains produce immunologically heterogeneous virulence factors, therefore an effective vaccine needs to induce broad-spectrum host immunity to provide cross-protection. Recent advances in genomics and proteomics, particularly computational biology and structural biology, establishes structural vaccinology and highlights the feasibility of developing effective and precision vaccines. Here, we introduce the epitope- and structure-based vaccinology platform multiepitope-fusion-antigen (MEFA), and provide instructions to generate polyvalent MEFA immunogens for vaccine development. Conceptually, MEFA combines epitope vaccinology and structural vaccinology to enable a protein immunogen to present heterogeneous antigenic domains (epitopes) and to induce broadly protective immunity against different virulence factors, strains or diseases. Methodologically, the MEFA platform first identifies a safe, structurally stable and strongly immunogenic backbone protein and immunodominant (ideally neutralizing or protective) epitopes from heterogeneous strains or virulence factors of interest. Then, assisted with protein modeling and molecule dynamic simulation, MEFA integrates heterogeneous epitopes into a backbone protein via epitope substitution for a polyvalent MEFA protein and mimics epitope native antigenicity. Finally, the MEFA protein is examined for broad immunogenicity in animal immunization, and assessed for potential application for multivalent vaccine development in preclinical studies.

Structure Activity Relationships for a Series of Eticlopride-Based Dopamine D2/D3 Receptor Bitopic Ligands.

The crystal structure of the dopamine D3 receptor (D3R) in complex with eticlopride inspired the design of bitopic ligands that explored (1) N-alkylation of the eticlopride's pyrrolidine ring, (2) shifting of the position of the pyrrolidine nitrogen, (3) expansion of the pyrrolidine ring system, and (4) incorporation of O-alkylations at the 4-position. Structure activity relationships (SAR) revealed that moving the N- or expanding the pyrrolidine ring was detrimental to D2R/D3R binding affinities. Small pyrrolidine N-alkyl groups were poorly tolerated, but the addition of a linker and secondary pharmacophore (SP) improved affinities. Moreover, O-alkylated analogues showed higher binding affinities compared to analogously N-alkylated compounds, e.g., O-alkylated 33 (D3R, 0.436 nM and D2R, 1.77 nM) vs the N-alkylated 11 (D3R, 6.97 nM and D2R, 25.3 nM). All lead molecules were functional D2R/D3R antagonists. Molecular models confirmed that 4-position modifications would be well-tolerated for future D2R/D3R bioconjugate tools that require long linkers and or sterically bulky groups.