Journal of Medicinal Chemistry

Protein Kinase Novel 3 (PKN3) understudied kinase with a diverse array of biological functions that are yet to be fully defined. Here, we report the design and development of a novel advanced functional chemical tool inhibitor for PKN3. A pyridyl imidazole series has been synthesized and evaluated against PKN3 in vitro and in cells. These efforts led to the discovery of 6e (URS03-06), a submicromolar cell active functional inhibitor with a narrow kinome spectrum, to enable the elucidation and interrogation of PKN3 cellular biology.

Modulating autophagy has emerged as a potential strategy for treating age-related diseases. However, commonly used pharmacological approaches to induce autophagy, particularly inhibition of mechanistic target of rapamycin complex 1 (mTORC1), can be associated with adverse effects, including immunosuppression and insulin resistance. This has prompted interest in autophagy modulators that act without directly inhibiting mTORC1. 2,5-Diketopiperazines (DKPs) are bioactive cyclic dipeptide scaffolds with diverse biological activities. However, systematic evaluation of their structure-activity relationships has been hindered by racemization during conventional chemical synthesis, leaving the contribution of stereochemistry to autophagy regulation poorly understood. Here, we used a stereoselective one-pot chemoenzymatic synthesis based on the adenylation domain of tyrocidine synthetase A to generate a DKP library with defined stereochemistry. Phenotypic screening in Caco-2 cells stably expressing the GFP-LC3-RFP autophagic flux probe identified four DKPs that increased autophagic flux: c(DW-DP), c(DW-LP), c(DF-DP), and c(DM-LP). Structure-activity analysis revealed stereochemistry-dependent effects associated with amino acid side-chain properties: D-configured residues were favored among DKPs containing aromatic amino acids or methionine, whereas L-configured residues were favored among those containing branched-chain amino acids. Substitution of the proline residue further altered activity, with glycine substitution tending to increase autophagic flux in some DKP scaffolds. Importantly, the active DKPs did not detectably reduce the phosphorylation of the mTORC1 downstream targets p70 S6K and 4EBP1, indicating that their autophagy-inducing effects do not require detectable suppression of canonical mTORC1 signaling. These findings establish stereochemically defined DKPs as candidate scaffolds for the development of autophagy inducers that act through mechanisms distinct from direct mTORC1 inhibition.

Cereblon (CRBN) is widely used in targeted protein degradation, but its ligand space has remained dominated by a narrow set of cyclic imide chemotypes. Here, we show that the accessible CRBN ligand space extends substantially beyond this canonical space. A high-throughput screen of > 40,000 compounds, followed by orthogonal biophysical validation, X-ray crystallography and SAR analyses, identified several chemically distinct ligand classes. These include linear acetyl-based motifs, a phthalide-derived scaffold, steroidal compounds, and a range of bicyclic ligands. They engage CRBN through distinct recognition modes, several of which deviate from the canonical hydrogen-bonding pattern. Steroidal scaffolds were particularly notable: cortisone binds the human CRBN thalidomide-binding domain with an affinity comparable to thalidomide, with its A-ring occupying the tri-tryptophan pocket in a glutarimide-like orientation despite lacking the canonical imide NH donor. SAR within this series showed substantial tolerance for chemical modification and scaffold simplification, raising the possibility that endogenous steroidal metabolites may contribute to the physiological ligand landscape of CRBN. Bicyclic lactams additionally provided synthetically accessible scaffolds with tunable affinity and promising sites for linker attachment. Across the identified ligand classes, none of the tested representatives induced detectable degradation of canonical CRBN neosubstrates, and several showed largely clean proteomic profiles. Together, these findings broaden the chemical, mechanistic and potential physiological landscape of CRBN recognition and provide diverse starting points for alternative, potentially neosubstrate-sparing CRBN recruiters.

Deubiquitinase-targeting chimeras (DUBTACs) have emerged as a promising strategy for targeted protein stabilization, but their broader application remains limited by the scarcity of ligandable deubiquitinase recruiters. Here, we report a previously unexplored four-membered-ring OTUB1 recruiter chemotype. Through systematic structure-activity relationship studies, we identified compound 21 (MS2159) as a potent and selective covalent OTUB1 ligand. Biochemical and intact protein mass spectrometric analyses demonstrated that MS2159 selectively engages the non-catalytic C23 residue of OTUB1, shows minimal reactivity toward other tested proteins, and preserves OTUB1 deubiquitinase activity. Conjugation of MS2159 with the CFTR ligand lumacaftor yielded compound 25 (MS2134), which effectively stabilized {Delta}F508-CFTR. Collectively, these findings establish a new OTUB1 recruiter scaffold, expand the ligandable chemical space of OTUB1, and provide additional opportunities for developing next-generation DUBTACs.

Synaptic vesicle glycoprotein 2C (SV2C) is a vesicular protein enriched in dopaminergic neurons of the basal ganglia that modulates dopamine storage and release, and its disruption is implicated in Parkinsons disease (PD). Despite strong genetic and pathological links to PD, there are no selective small-molecule probes for SV2C. Here, we describe an AI-enhanced virtual screening (VS) and experimental campaign that identified multiple novel chemotypes with low-micromolar affinity and marked selectivity for SV2C over SV2A and SV2B, starting from a large, general-purpose commercial library. Because no full-length high-resolution SV2C structure was available, we built a homology model using SV2A cryo-EM structures as templates and characterized its conformational landscape by molecular dynamics (MD) and Gaussian accelerated MD (GaMD) simulations in apo form and in complex with known SV2 ligands (plosaracetam, levetiracetam, brivaracetam, and padsevonil). A convolutional neural network-based scoring function (CNN VS), retrospectively validated on a manually curated 39-ligand SV2A benchmark (r = 0.72 vs experimental pIC50), was then applied in a multi-stage funnel to 5.96 million Mcule in-stock compounds, which were sequentially filtered to 3.19 million CNS-relevant molecules before docking and rescoring. From 94 VS-prioritized candidates, 71 compounds were experimentally profiled in an orthogonal primary assay cascade combining a thermal shift assay (TSA) with a [3H]-padsevonil scintillation proximity assay (SPA), followed by Ki determination and isoform selectivity profiling for key hits. This campaign yielded 22 active molecules (31% hit rate) that naturally segregated into two categories: compounds that showed primary site competition, and compounds that did not show primary site competition with [3H]-padsevonil. A subset of competitor compounds also showed thermostabilization activity. Among these, compounds 36 and 56 emerged as particularly attractive leads, with Ki values of 24.6 {micro}M and 3.25 {micro}M at SV2C, respectively, and >10-fold selectivity versus SV2A; compound 56 also maintained[~] 12-fold selectivity relative to SV2B. A complementary subset of SV2C-selective hits behaved as padsevonil-site competitors, providing a lead set that will serve as a template for functional characterization and future drug development for conditions that affect dopaminergic signaling. Docking analysis suggests a common binding mode anchored by conserved tryptophan residues in the SV2 pocket, a prediction independently confirmed by an unpublished SV2A- plosaracetam cryo-EM structure showing 0.76 [A] binding-site C RMSD relative to the SV2C model and complete conservation of the tryptophan cage. Subtle differences in the luminal domain and transmembrane region point to the structural determinants underlying isoform selectivity. Collectively, these results demonstrate that an AI-driven VS pipeline, tightly integrated with medium-throughput biophysical assays, can deliver selective SV2C binders from a general chemical library on a structurally under-characterized membrane target. The identified hits provide multiple starting points for hit-to-lead optimization and tools for probing SV2C biology and its role in PD.

Gabapentin (GBP) and pregabalin (PGB) are widely used gabapentinoids. Previously, we have demonstrated, for the first time, that GBP and PGB modulate the nociceptive response to noxious heat in C. elegans at an optimal concentration. In the current study, we use C. elegans and paired thermal nociception assays with direct internal drug concentration measurements to characterize the pharmacokinetic (PK)/pharmacodynamic (PD) relationship of both compounds. Neither drug altered baseline mobility or quadrant preference, confirming that behavioral effects reflected genuine antinociceptive action. Both GBP and PGB produced dose- and time-dependent reductions in thermal avoidance, with 500 uM exposures generating a biphasic, V-shaped time course in which suppression of thermal sensitivity deepened before partially reversing. This partial reversal occurred later with PGB than with GBP. Internal concentrations confirmed dose-dependent absorption and retention for both drugs, yet at 500 uM, internal drug levels remained elevated through 360 min even as behavioral avoidance recovered, indicating that the recovery limb reflects active counter-regulation rather than passive clearance, consistent with previously reported transcriptional and proteomic signatures. Exposure-response profiles were notably flat, suggesting a saturable pharmacodynamic ceiling. Molecular modeling revealed conserved electronic pharmacophores supporting shared alpha-2-delta engagement, alongside shape-descriptor differences that may contribute to divergent absorption kinetics. These findings position C. elegans as a valuable model for dissecting gabapentinoid PK/PD relationships. Beyond mechanistic insight, these findings support the continued investigation of C. elegans as a screening platform whose validation could help address the 3R (Replacement, Reduction, Refinement) principles guiding animal research.

Histone deacetylases (HDACs) are pivotal epigenetic regulators that modulate diverse cellular pathways by removing acetyl groups from lysine residues on both histone and non-histone proteins. Histone deacetylase 11 (HDAC11), the sole member of class IV HDACs, exhibits both deacetylation and fatty acid deacylation activities. Accumulating evidence implicates HDAC11 as a key epigenetic regulator of fundamental cellular processes, including metabolism, immune responses, and tissue development. Dysregulation of HDAC11 activity has been associated with inflammatory diseases, metabolic disorders, neurodegenerative conditions, and cancer, highlighting its potential as a therapeutic target. Although several HDAC11-specific inhibitors have been identified, none have progressed to clinical development. In this study, we aimed to discover HDAC11-selective inhibitors by integrating in silico and in vitro validation approaches. Homology modelling of the HDAC11 structure was conducted, followed by model validation, structure-based virtual screening, molecular dynamics (MD) simulations, and binding free energy calculations. We identified and validated three lead compounds and their intermediates using biochemical and cell-based assays. Fluorescence-based and HPLC-based enzymatic assays demonstrated potent inhibition of both the deacetylase and deacylase activities of HDAC11, with Inhibitor 6 and Inhibitor 3 exhibiting the strongest effects among the six compounds tested. Further, a decrease in lipid accumulation, reduced stability of the HDAC11 substrate SHMT2, as determined by immunoblot analysis and decreased cell viability, as assessed by MTT assay, confirmed HDAC11 inhibition in cellular models. The study shows that new HDAC11 inhibitors significantly reduce the viability of breast cancer cells and induce apoptosis; inhibitor 6, in particular, showed high potency, similar to the reference compound SIS-17. Flow cytometry showed that treated MDA-MB-231 cells exhibited cell-cycle arrest and increased apoptosis, a finding further confirmed by Annexin V/PI staining. Molecular analysis showed that BAX increased while BCL2 decreased, indicating that apoptotic pathways were activated in novel compound-treated MDA-MB-231 cells. The results suggest that inhibiting HDAC11 is an effective way to induce cancer cell death and provide a basis for further assessment of these compounds as potential treatments for breast cancer. Collectively, this study identifies novel zinc-chelating HDAC11 inhibitors containing a nitro-sp2 group, providing promising candidates for further therapeutic development.

AlphaFold 3 (AF3) and Boltz-2 are state-of-the-art AI-based tools for biomolecular structure prediction, but whether their predictions provide useful guidance for lead optimization, SAR interpretation, and virtual screening remains insufficiently characterized. We benchmarked their performance using newly determined soluble epoxide hydrolase co-crystal structures and matched activity data together with a curated post-training-cutoff dataset spanning kinases, allosteric modulators, covalent systems, PROTACs, molecular glues, fragments, membrane proteins, RNA binders, and activity-cliff pairs. Both models recovered canonical orthosteric enzyme and kinase complexes, including key DFG/C conformational states, whereas allosteric, membrane-protein, and induced-proximity complexes remained challenging. Pharmacophore RMSD was often lower than overall ligand RMSD, indicating preservation of key recognition features despite imperfect whole-ligand alignment. AF3 minPAE correlated with pose accuracy, and very low minPAE values (<0.85 A) were strongly enriched for accurate poses. Model confidence scores were not associated with experimental activity, whereas Boltz-2 predicted affinity captured relative activity trends and distinguished the activity-cliff pair, although its performance varied across ligand series.

Disulfide-rich peptides possess exceptional potency and selectivity but are often limited by the instability and synthetic challenges associated with native disulfide bonds. Here, we report the design, synthesis, pharmacological evaluation, and structural characterisation of triazole-based peptidomimetics of the -GI conotoxin, a selective antagonist of the muscle-type nicotinic acetylcholine receptor (nAChR). A series of 1,4- and 1,5-disubstituted triazole analogues were prepared entirely on resin using CuAAC and RuAAC chemistry to replace the native Cys3/13 disulfide bridge. Functional evaluation against human muscle nAChRs revealed that 1,5-triazole analogues retained low-nanomolar potency, with the lead mimetic exhibiting activity comparable to native -GI. Cryo-electron microscopy of the lead compound bound to the muscle-type nAChR provided the first structure of a disulfide-isostere peptidomimetic in complex with a membrane receptor. The structure demonstrates that the 1,5-triazole reproduces the native peptide fold with high fidelity while contributing receptor-facing interactions not available to the native disulfide bridge. Molecular dynamics simulations further revealed conserved hydration networks and similar conformational sampling between the native peptide and lead mimetic. Together, these findings establish triazoles as effective disulfide surrogates and provide a structural framework for the rational design of stabilised conotoxin therapeutics.

Background: Subtype-selectivity predictions are scored against measured selectivity and judged against an assumed noise ceiling. We asked what an 2-adrenergic benchmark rewards and which controls change its interpretation. Research design and methods: On a frozen benchmark of 586 paired 2A/2C compounds we evaluated Glide SP docking, CNN rescoring, ligand-only fingerprint models, receptor descriptors and pose contacts, with dopamine D3/D2 as comparator, applying five controls: a measured ceiling, a cluster-identity null, a nonselective reference, a same-receptor floor and a trivial-descriptor baseline. Results: Five descriptors from SMILES reached Spearman 0.645, 72% of the measured ceiling, against 0.071 for Glide SP and 0.188 for CNN rescoring; receptor properties and pose contacts reduced to size under control, while a non-size signal of 0.258 survived. Measured rather than propagated noise raised that ceiling from 0.704 to 0.897; cluster identity alone reached R2 0.499 on D3/D2 and none on 2; a nonselective reference received +1.43 to +4.79 kcal/mol where zero is expected; and a same-receptor floor reached 1.77-fold against 1.88-fold across subtypes. Conclusions: Such benchmarks reward molecular size first; a method must exceed 0.645 before its score indicates structural reasoning. The controls are inexpensive; conclusions rest on two receptor pairs, a three-pair floor and static structures.

Mycosporine-like amino acids (MAAs) are among nature's most effective sunscreen compounds, capable of converting harmful ultraviolet radiation into harmless heat, and are widely distributed in marine organisms such as red macroalgae. Although decades of research have led to numerous discoveries, the rate of new MAA identifications has declined. To address this, we considerably expanded our previously developed combinatorial MAA database, increasing the number of covered structures tenfold. Following a comprehensive literature search for plausible but undescribed building blocks, the database now incorporates an extensive set of proteinogenic and non-proteinogenic amino acids, as well as other marine organic osmolytes, in combination with all (currently) known MAA scaffolds. This expanded resource was integrated into our identification platform, which combines UHPLC-VWD-HRMS2 analysis, feature-based molecular networking, and bioinformatics-driven annotation. Application of this updated workflow enabled the isolation and structural elucidation of a novel MAA, mycosporine-cysteinolic acid, from the red marine macroalga Vertebrata lanosa. Altogether, this study provides a valuable extension of the bioinformatics-based MAA screening pipeline, enhancing the annotation and discovery of novel MAAs in natural matrices.

Breast cancer (BC) is the second most common noncutaneous cancer and the second leading cause of cancer-related death in women. BC is classified into three primary subtypes, with triple-negative breast cancer (TNBC) having the poorest prognosis because it lacks specific targetable markers. Preclinical studies on TNBC indicated a common occurrence of diminished tumor-suppressor activity of PTEN, activating the PI3K/AKT/mTOR signaling pathway. Notably, published studies reveal that the WWP1 enzyme plays a pivotal role in driving PTEN degradation via ubiquitination, unveiling a promising therapeutic target for treating TNBC. In the search of new WWP1 inhibitors, we used artificial intelligence (AI)-driven computational strategies for de novo design of peptide-based WWP1 inhibitors and identified a hexapeptide, termed WI23-B, which demonstrated high nanomolar binding affinity to WWP1. In TR-FRET enzymatic assays, WI23-B inhibited WWP1 activity with an IC of approximately 11 {micro}M. In MCF7 and MDA-MB-231 breast cancer cell lines, WI23-B showed promising cytotoxic efficacy, particularly in combination with the PI3K inhibitor BYL719, also when it was loaded into nanocapsules. Collectively, these findings highlight WI23-B as a promising lead peptide with potent WWP1 inhibitory activity and synergistic antiproliferative effects when combined with PI3K inhibitors. While further structural optimization is required to enhance its potency and pharmacological properties, our results provide a strong foundation for the development of next-generation WWP1 inhibitors. Such agents have the potential to reshape therapeutic strategies for BC and TNBC by enabling more effective and less toxic treatment regimens, ultimately reducing the reliance on high-dose chemotherapy and minimizing adverse effects.

Small-molecule drug discovery relies on identifying compounds that modulate specific protein targets, a process often hindered by cellular complexity. Through phenotypic screening of a kinase-focused diazaquinazoline library, we serendipitously identified CEM198 as the first high-affinity ligand of tubulin-tyrosine ligase (TTL). Functional assays combining live-cell TTL inhibition, microtubule polymerization, cell cycle analysis, and proteomics revealed that CEM198 acts through a dual mechanism: directly binding to TTL and altering /{beta}-tubulin conformation. This interaction restricts -tubulin tyrosination and disrupts tubulin polymerization, leading to microtubule destabilization. The differential effects observed between SH-SY5Y and HEK293T cells indicate that effective TTL inhibition depends on both direct binding and structural modulation of the tubulin heterodimer. These findings introduce CEM198 as a chemical probe for investigating the tubulin tyrosination-detyrosination and demonstrate the potential of chemoproteomics to uncover novel modulators of microtubule dynamics.

BackgroundCannabis derivatives have been reported to possess antinociceptive properties. However, oral delivery is limited by poor bioavailability, stability, and reliability of effects. Previously, we reported an analgesic effect of the aqueous complex {Delta}9-tetrahydrocannabinol/2-hydroxypropyl-{beta}-cyclodextrin (THC/HP{beta}CD) after intracerebroventricular administration in male rats. MethodsHere, we investigated the analgesic effects of the THC/HP{beta}CD complex after oral administration (0.3 and 3 mg/kg) by the tail flick test after both acute and chronic administration (15 days) in female rats. Locomotor activity and anxiety-like behavior were also evaluated at the same experimental conditions. Moreover, dopamine and glutamate content in the periaqueductal gray (PAG), a key area for the antinociceptive action of THC, were also measured by HPLC. ResultsAfter acute administration, the antinociceptive effect of the complex was seen at 3 but not 0.3 mg/kg THC, with a maximum effect observed at 30 min (MPE 60%). Similar results were obtained after 15 days of treatment, although partially reduced (max MPE 20%). Reductions in locomotor activity with the dose of 3 mg/kg and a slight biphasic effect of the two doses on anxiety-like behavior were also observed. Finally, neurochemical analyses revealed that the dose of 3 mg/kg significantly increased dopamine and glutamate content in the PAG, an effect no longer present after 15 days of treatment. ConclusionsOur results highlight the antinociceptive efficacy of the THC/HP{beta}CD complex also after oral administration, notably higher than that previously seen with other carriers, although with some degree of tolerance after chronic administration. From a translational point of view, these results are relevant for the development of THC-based oral formulations with analgesic properties for the treatment of pain in humans. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC="FIGDIR/small/742765v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@fff791org.highwire.dtl.DTLVardef@d672f4org.highwire.dtl.DTLVardef@1150b3forg.highwire.dtl.DTLVardef@956403_HPS_FORMAT_FIGEXP M_FIG C_FIG

The leukocyte-specific {beta}2-integrin receptor family exerts a wide range of functions: {beta}2-integrins are involved in leukocyte trafficking, where they mediate cell adhesion during inflammatory responses via binding to ICAM-1, ICAM-2, or JAM-C. Furthermore, they are essential for the recognition and phagocytosis of pathogens opsonized by complement. Accordingly, the {beta}2-integrin family is known to be involved in autoimmune and inflammatory diseases, such as systemic lupus erythematosus. Owing to their complex biology, involving multiple conformational transitions, different signaling pathways, and a broad spectrum of ligands, the development of {beta}2-integrin-targeted probes and therapeutics has remained challenging. We aimed to develop macrocyclic peptides, derived from phage display screening, which can be used to unravel ligand binding profiles of {beta}2-integrins with an emphasis on the I domain. The selection of suitable lead peptides, and the characterization of their interaction profiles with different I domains, was enabled by an established in-vitro assay platform. Various peptide sequences were enriched during several rounds of phage display against the I-domain of CR3, of which two peptides with particularly low micromolar binding affinity were further characterized. Both peptides showed direct binding to {beta}2-integrin I-domains and, in a competitive assay, dose-dependent inhibition of the I-domains interactions with their main ligands iC3b and ICAM-1, respectively. These ligand-interfering properties were confirmed in bead- and cell-based adhesion assays. The modulators developed here are expected to provide valuable insight into the (patho-)physiology of CR3 and the other members of the {beta}2-integrin family, as the two peptides were able to compete with different ligands. In the future, this may help to identify potential therapeutic approaches for autoimmune, inflammatory, and age-related diseases.

Mucopolysaccharidosis IIIC (Sanfilippo syndrome type C) is a rare lysosomal storage disorder caused by loss-of-function mutations in HGSNAT, which encodes an enzyme involved in heparan sulfate (HS) degradation, leading to impaired HS catabolism, lysosomal accumulation, and progressive neurodegeneration. Because enzyme replacement therapies have limited penetration across the blood-brain barrier, substrate-reduction therapy represents an alternative therapeutic strategy. Here, N-deacetylase/N-sulfotransferase 1 (NDST1), a key enzyme responsible for HS biosynthesis, was investigated as a potential substrate-reduction target. A structure-based computational pipeline was used to identify and evaluate inhibitors targeting the NDST1 sulfotransferase domain. Approximately 4.1 million drug-like compounds and FDA-approved drugs were screened by molecular docking, followed by pharmacokinetic filtering, molecular dynamics simulations, and MM/PBSA binding free energy calculations. In parallel, peptide binders targeting the same site were generated using diffusion-based protein design and evaluated using molecular dynamics and MM/GBSA analysis. Four chemically distinct small-molecule scaffolds and three peptide candidates were identified as stable binders to the NDST1 active site. The lead small-molecule candidate exhibited a predicted binding free energy of -13.36 {+/-} 5.87 kcal mol-1. These provide a focused set of candidates for further investigation and support the feasibility of targeting NDST1 as a substrate-reduction strategy for MPS IIIC.

Plant-derived small molecules possess highly diverse physicochemical properties, and the computational design of their protein recognition elements depends not only on the global structural quality of candidate backbones, but also on whether the local binding pocket, ligand-contact pattern, and predefined recognition conformation can be consistently retained after sequence design and structural back-prediction. To explore pocket-design strategies for different types of natural-product small molecules, this study selected capsaicin, (4R)-limonene, and quercetin as model ligands, representing a flexible amphipathic molecule, a compact hydrophobic monoterpene, and a rigid polyphenolic flavonoid scaffold, respectively, and covering the dimensions of pungent sensory flavor, volatile aroma, and flavonoid functional constituents. A ligand- physicochemical-property-guided computational design and multi-stage prioritization framework was established for candidate protein binders. The results showed that candidates with favorable initial global structural scores did not necessarily form reasonable local small-molecule binding pockets, indicating that evaluation of the local ligand environment is essential for candidate prioritization. After screening, 31 partial- pocket candidate backbones for capsaicin, 75 buried hydrophobic-pocket candidate backbones for (4R)-limonene, and 56 pocket-qualified candidate backbones for quercetin were obtained. Further sequence design and structural back-prediction analyses indicated that a subset of candidates could maintain the original pocket geometry and major ligand-contact patterns after sequence realization. Overall, these results suggest that the physicochemical properties of different plant-derived small molecules substantially influence the efficiency of de novo protein pocket formation, with compact hydrophobic ligands being more compatible with buried hydrophobic- pocket strategies, whereas flexible or multipolar ligands require a more refined balance between hydrophobic burial and polar exposure. This study provides a pre- experimental computational prioritization framework for natural-product small- molecule-recognizing proteins and offers candidate resources for subsequent protein expression, in vitro binding validation, active-constituent enrichment, and development of small-molecule biorecognition tools. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/743643v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@8fe6c2org.highwire.dtl.DTLVardef@176cef2org.highwire.dtl.DTLVardef@10c8201org.highwire.dtl.DTLVardef@2b28cf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Catalytic activity of 5'-3' exonuclease Phospholipase D3 (PLD3) is associated with immune signaling and neurodegeneration including Alzheimers disease. PLD3 undergoes multiple post-translational modifications and proteolytic cleavage to establish its catalytically active form. However, the proteases catalyzing the cleavage of PLD3 have remained unidentified. To study the proteolytic cleavage of PLD3, we have evaluated the small molecule covalent inhibitor E64d that blocks proteolysis catalyzed by cysteine cathepsins. To validate the selectivity of E64d, we have designed and synthetized an E64d propargyl analogue and carried out a detailed activity-based protein profiling to reveal a broad engagement of the compound with other protein targets including bleomycin hydrolase (BLMH), Kelch-like ECH-associated protein 1 (KEAP1), transcription elongation factor SPT5 (SUPT5H) and asparagine synthetase (ASNS). The specificity of the E64d-protein interactions was confirmed by biochemical assays and mass spectrometry-based site identifications. In neurons, treatment with E64d lead to about 50-fold PLD3 accumulation and dysregulation of its proteolytic cleavage, while there was only a minor overall change on the whole proteome level. Taken together, this study provides insights into previously unknown E64d selectivity and renders cysteine cathepsins responsible for PLD3 degradation in neurons. It highlights the importance of cysteine cathepsins activity in neuronal lysosomes for proper PLD3 processing and hence it suggests that their activation might be responsible for decreased PLD3 levels in neurons of patients with Alzheimers diseases. These findings are key for further elucidation of PLD3 function in neurodegenerative diseases.

Lead optimization, the systematic refinement of therapeutic compounds through iterative structural modification, faces a dual challenge in modern drug discovery: navigating astronomically vast molecular design spaces while balancing conflicting demands on potency, pharmacokinetics, and safety. We present MASCOT (Multi-Agent SearCh for molecular OpTimization), a role-specialized multi-agent framework for molecular optimization. Integrated with a chemically constrained graph-editing search, MASCOT coordinates three specialized agents: a trade-off agent that reprioritizes competing objectives, a strategy agent that adapts how molecular edits are proposed, and a reflection agent that distills lessons from previous decisions. Computational experiments showed that MASCOT achieved the best performance over competing methods on six benchmark settings. On the SARS-CoV-2 main protease task, its mean docking-score improvement was 3.6 times that of the strongest baseline. Applied to the clinically used anesthetic remimazolam (RM), MASCOT prioritized RM-1, which showed a shorter liver microsomal half-life, higher brain exposure, and a larger therapeutic index than RM. Subsequent derivative design yielded RM-7. Extensive animal studies established RM-7 as a rapid-recovery intravenous anesthetic candidate with greater potency, faster functional recovery, a wider safety margin, and preserved flumazenil reversibility. These results demonstrate that multi-agent coordination can link adaptive molecular search to medicinal chemistry and experimental pharmacology.

To combat refractory diseases, such as cancer, multitarget-directed ligands (MTDLs) have become an emerging area of research to exploit synthetic lethality (SL) relationships associated with drug resistance. Herein, we present the in silico design of MTDLs for the polypharmaceutical treatment of endometrial adenocarcinoma (EAC) and our discovery of a novel SL in EAC; PTEN loss of function (LOF) and the inhibition of CDK9. We used high-resolution x-ray crystallographic data to chemically engineer, LCI133, to inhibit CDK9, CDK4/6-and AURKA/B kinases. PTEN LOF in EAC results in augmented deregulated transcription and a massive increase in nascent RNA, a phenotype which encodes a high level of apoptotic sensitivity to LCI133 and CDK9 inhibitors. Treatment with LCI133 results in a rapid decline nose-dive in global nRNA, MYC nRNA levels and TS elongation (TE) in PTEN LOF EAC. PTEN LOF is necessary and sufficient to confer sensitivity of EAC cells to LCI133 and other CDK9 inhibitors.