ChemMedChem

Excessive osteoclast activity contributes to pathological bone loss in osteoporosis, rheumatoid arthritis, and osteolytic malignancies. The effects of small catechol derivatives on receptor activator of nuclear factor-{kappa}B ligand (RANKL)-induced osteoclastogenesis remain poorly understood. This study investigated the effects of 4-methylcatechol (4-MC) on RANKL-induced NF-{kappa}B activation and osteoclast differentiation. 4-MC reduced RANKL-induced NF-{kappa}B luciferase activity in HEK-293T/RANK cells. 4-MC also suppressed RANKL-induced TRAP activity in RAW264.7 cells in a concentration-dependent manner and reduced the number of TRAP-positive multinucleated osteoclasts, without affecting cell viability. Molecular docking predicted non-covalent binding of 4-MC within the ATP-binding hinge region of IKK{beta} (PDB: 4KIK), forming a close polar contact with Glu97, predicted hydrogen bonds with Cys99, and a hydrophobic contact with Ile165, within the pocket occupied by the co-crystallized inhibitor K252a. Covalent docking predicted that the oxidized quinone form of 4-MC engages Cys179 in the IKK{beta} activation loop. Quantum chemical calculations confirmed a markedly higher electrophilicity index for the oxidized quinone than for the parent catechol, supporting this mechanism. In silico ADMET profiling indicated favorable drug-likeness and safety. These findings identify IKK{beta} as a plausible molecular target of 4-MC through both non-covalent and covalent mechanisms. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/741661v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@35a0d3org.highwire.dtl.DTLVardef@d19458org.highwire.dtl.DTLVardef@1623fadorg.highwire.dtl.DTLVardef@1429e8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

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

The folate receptor (FR) is overexpressed in a range of human tumours including ovarian cancer cells. We propose that the overexpression of the FR on the surface of ovarian tumour cells could be exploited for the selective delivery of a DNA damage response inhibitor (DDRi) in the form of an intact folate drug conjugate (FDC). This approach would improve the therapeutic index of the parent DDRi facilitating combination studies of the DDRi-based FDC with DNA damaging chemotherapy. FR-mediated cellular uptake of the proposed folate drug conjugates is requisite for FDC selective delivery into tumours. In this study, we synthesised a series of olaparib-based folate conjugates that maintained the biochemical PARP1 inhibition associated with olaparib and showed binding affinity for the folate receptor. Significantly, we identified compounds 10b and 11 that selectively enter FR overexpressing tumour cells via folate receptor-mediated endocytosis in their intact form and engage with their target as demonstrated by the potent inhibition of PARylation (KB cells, PARylation IC50 = 5.7 and 3.9 nM; respectively).

The human immune system excels at generating highly effective antibodies through natural selection and somatic hypermutation, but adapting these antibodies for therapeutic use, referred to as "antibody medicine-likeness", requires careful consideration of biochemical and physiological properties. Traditional redesign methods are often slow and limited in scope. In this study, we introduce a machine learning-based approach to evolve new anti-PD-1 antibodies within a chemically informed latent space using a conditional kernel-elastic autoencoder (CKEA) between nivolumab and pembrolizumab, both of which bind the FG-loop "hotspot" of PD-1 in the most distantly related orientations, differing by 174{degrees}. This generative framework is designed to preserve favorable therapeutic features while exploring variants with different potency, ultimately for improved potency. To evaluate structural and functional viability, we performed molecular dynamics (MD) simulations of the generated antibody - PD-1 complexes and described their MD properties. These simulations reveal detailed free-energy landscapes and identify stable binding conformations, providing a strong basis for experimental validation. To validate our designs, we expressed and experimentally tested the antibodies for binding affinity to PD-1. Upon expression and purification, three out of six designed antibodies exhibited some binding to PD-1, whose properties could likely be improved using other computational saturation mutagenesis or laboratory evolution. Our results demonstrate the potential of artificial intelligence (AI)-guided interpolation methods to generate novel, high-affinity antibodies with therapeutic promise, offering a powerful strategy for next-generation antibody development. SYNOPSIS TOCCombination of MD simulations with machine learning algorithms could revolutionize the antibody-breeding sciences to lead to new antibody discovery that is compatible with or better than naturally occurring antibodies. Topics of Content (TOC)Fingerprints of R86 finger of PD-1 are recognized by our designed P2N_2 anti-PD-1 antibody according to our MD simulations O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC="FIGDIR/small/742579v1_ufig1.gif" ALT="Figure 1000"> View larger version (49K): org.highwire.dtl.DTLVardef@1bbeb5eorg.highwire.dtl.DTLVardef@599658org.highwire.dtl.DTLVardef@19d8c69org.highwire.dtl.DTLVardef@6d5f0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Antibiotics with new mechanisms are highly pursued to address the threat of infections caused by drug-resistant Gram-negative bacteria. Targeting MsbA, a key protein of the lipopolysaccharide biosynthesis pathway, represents a promising strategy to discover new classes of antibiotics. However, currently available MsbA-targeted molecules either lack sufficient potency or have unfavorable properties, necessitating expansion of chemical space. In this study, we chose the most promising cerastecin Cpd 4 as the template, and used two Artificial Intelligence (AI)-based tools, i.e. Link-INVENT and AutoMolDesigner for molecular design, performed chemical derivatization and antibacterial activity evaluation, which led to the discovery of Y-11 (MIC for A. baumannii: 0.5 g/mL). Encouragingly, Y-11 showed equivalent potency to Cpd4 for carbapenem-resistant A. baumannii, and less cytotoxicity and hemolysis as well as lower spontaneous resistance frequency. In vivo efficacy study demonstrated that Y-11 could effectively reduce bacterial loads in the mice infected by A. baumannii. The following mechanism study including molecular dynamics simulation, biochemical assay, and transmission electron microscope (TEM) analysis suggested that Y-11 inhibited the transport of lipooligosaccharide and impaired the formation of outer membrane, probably by competitively binding to the substrate binding site of MsbA and modulating ATPase activity. Taken together, we have discovered a MsbA-targeted small molecule Y-11 via AI-driven drug design, which provides a foundation for future antibiotic development.

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.

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.

Macrocyclic peptides are an attractive therapeutic modality capable of engaging challenging protein targets while retaining many favourable drug-like properties. Their high-affinity binding also provides an ideal framework for proximity-driven covalent inhibition through incorporation of latent electrophiles. Phage display enables the high-throughput screening of billion-member macrocyclic peptide libraries; however, existing libraries rely predominantly on cysteine-mediated cyclisation, restricting the range of macrocyclic topologies available for ligand discovery. Here, we report a mild and efficient cyclisation strategy based on a bromomethyl picolinaldehyde (BMP) linker that reacts with a cysteine side chain and the peptide N-terminus to generate a previously unexplored macrocyclic topology incorporating neighbouring pyridine and imidazolidinone rings. The chemistry is compatible with phage display and enabled screening of BMP-cyclised peptide libraries against plasma kallikrein, yielding a potent macrocyclic inhibitor. The BMP-cyclised peptide displayed substantially greater potency than analogous peptides cyclised through either a disulfide bond or the widely used linker 1,4-bis(bromomethyl)benzene (DBMB). Furthermore, comparison with an equivalent DBMB-cyclised library demonstrated that BMP-mediated cyclisation enabled access to binding motifs not identified by conventional cysteine-to-cysteine cyclisation. Finally, positional sulfur(VI) fluoride exchange (SuFEx) electrophile scanning converted the BMP-derived hit into a selective covalent macrocyclic activity-based probe capable of labelling plasma kallikrein in human plasma. Together, these findings establish BMP-mediated cyclisation as a versatile strategy for expanding the topological diversity of phage-displayed macrocycles and accelerating the discovery of both reversible and covalent macrocyclic peptide ligands.

Rho guanosine triphosphatases (GTPases) are molecular-switches implicated in neurodegenerative diseases, yet targeting them through competitive inhibition remains a challenge due to their high affinity for guanine nucleotides. Guanine nucleotide exchange factors (GEFs) catalyse GDP-to-GTP nucleotide exchange to activate GTPases, providing an alternative opportunity for GTPase modulation. Herein, we describe a complex-targeted strategy to inhibit nucleotide exchange with covalent molecular glues that engage the Kalirin-Rac1 GEF-GTPase complex at the nucleotide binding site are sequester the GEF Kalirin. Fragment hits were identified through XChem and in silico screening, and a fragment merging approach resulted in the generation of covalent inhibitors RS-009 and MC-278. Multiple analyses demonstrate our compounds inhibit nucleotide exchange both through competition with the nucleotides and by stabilising a ternary inhibitor-Rac1-Kalirin complex, thereby trapping Kalirin in a non-productive state and reducing GEF turnover. Biochemical selectivity screening and cellular activity-based protein profiling (ABPP) show that selectivity can be achieved across distinct GEF-GTPase complexes, which may result in improved spatiotemporal control over targeting the GTPase alone. This work provides evidence for targeting GTPase signalling via stabilization of the GEF-GTPase complex in a unique covalent molecular glue mechanism and provides the basis of a chemical probe or therapeutic.

Arylamino alcohols constitute an established class of antimalarial agents. While this class is best known for its potent antiplasmodial activity, selected members, most notably mefloquine, have also been reported to exhibit antibacterial activity. Structurally related 3-hydroxypropanamidines were developed as highly potent antimalarial agents. Here, we explored the antibacterial activity of three 3-hydroxypropanamidines (4 (BLK278), 5 (BLK280), and 6 (TKK088)) against clinically relevant Gram-positive and Gram-negative bacteria and investigated their cytotoxicity, in vitro pharmacokinetic properties, and proteome-based bacterial response to treatment. We observed good antibacterial activity against Staphylococcus aureus, with 6 (TKK088) displaying the highest activity against multidrug-resistant MRSA and VISA strains. 5 (BLK280) demonstrated the greatest spectrum of activity acting also against clinically relevant Gram-negative strains of Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, Klebsiella aerogenes, and Shigella sonnei. In cytotoxicity assays with HUVEC and HAOSMC cells, 4 (BLK278) and the previously reported 7 (TKK129) showed the most favourable overall profiles among the investigated 3-hydroxypropanamidines. The selectivity indices for S. aureus were below 2.5 with clear cell-type-dependent differences for all compounds including mefloquine, suggesting that improving antibacterial selectivity is an important objective for further optimization. In vitro pharmacokinetics showed high plasma protein binding and good human microsomal and plasma stability for all three 3-hydroxypropanamidines. Gel-based proteomic responses revealed a strong impact on the bacterial cell envelope. The observed acute proteomic responses reflect pleiotropic effects and are consistent with earlier reports implicating F0F1-ATPase as a potential molecular target of mefloquine in Streptococcus pneumoniae.

The classical estrogen receptor (ER) is a steroid hormone receptor known for its role in both health and disease. ER, like its counterpart ER{beta}, acts as a receptor for its endogenous ligand 17{beta}-estradiol (E2) and is capable of binding a diverse set of natural and synthetic small molecules. Several screening campaigns have identified various ER ligands, based on the oxabicyclo[3.3.1]-nonene scaffold, that act as ER agonists. One such campaign extensively characterized an oxabicyclic ER agonist, termed AB-1. Herein, we report the synthesis of a series of analogs based on the scaffold of AB-1 (herein termed 1), focusing on the enhancement of their binding to ER and functional potencies in ER mediated assays. We identify a new substituted compound 9 that achieves subnanomolar potencies for ER binding (IC50= 0.45 nM) and ER dependent transcription (EC50= 0.37 nM) and proliferation (EC50= 0.03 nM), with potencies approaching those of E2. The high potency of 9 provides a promising scaffold for the potential development of new ER-targeted therapeutics.

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.

The dopamine D2 receptor is a principal target of antipsychotic and antiparkinsonian drugs, yet well-characterized fluorescent ligands for the D2 receptor remain scarce compared with its relative, the D3 receptor. Here we show that fluorescent ligands developed for the D3 subtype can be repurposed as tools for studying the D2 receptor pharmacology. Using a machine-learning-assisted, live-cell fluorescence microscopy assay, we screened twelve fluorescent probes and identified eight ligands that bound specifically to the D2 receptor at 10 nM. Four ligands exhibited classical saturable binding, yielding Kd in the nanomolar range, whereas the remaining probes displayed unsaturated, time-dependent binding profiles. Kinetic analyses revealed substantial differences in association and dissociation behavior, highlighting the importance of time-resolved measurements. Competition binding with dopamine and haloperidol yielded affinity estimates consistent with literature values. These results expand the toolkit of validated D2 receptor fluorescent probes and support cross-receptor repurposing as a strategy for fluorescent ligand development.

The de novo design of proteins that bind chemically complex small molecules has broad chemical and biological implications, but strategies typically rely on a small set of protein scaffolds and require extensive experimental screening. Here, we computationally designed proteins around a minimal aromatic {pi}-stacking motif to bind the anthracycline anticancer drug doxorubicin. Experimental characterization of twelve proteins revealed a {micro}M doxorubicin binder; two additional design cycles improved scaffold stability and binding affinity to yield an 85-residue protein that binds doxorubicin with a dissociation constant of 85 nM. An X-ray crystal structure of the protein-drug complex confirmed the accuracy of the designed {pi}-{pi} stacking interactions. The designed protein could act to protect cultured cells from doxorubicin-induced cytotoxicity. Unlike previous ligand-binding protein designs based on repeat proteins or naturally occurring folds, the designed protein adopts a previously unobserved 5-helix globular fold, indicating that a broader space of folded, functional proteins exists even for compact tertiary structures smaller than 100 residues. These results demonstrate that motif-guided generative protein design can discover compact de novo protein folds capable of high-affinity recognition of chemically complex small molecules.

Tunicamycins are potent inhibitors of dolichyl-phosphate N-acetylglucosamine phosphotransferase (DPAGT1) but are unsuitable for therapeutic development due to non-selective cytotoxicity, acid-labile glycosidic linkages, and poor physicochemical properties. Although prior structural modifications reduced the promiscuous toxicity of tunicamycins, the intrinsic 11'-{beta}-1''- trehalose-type glycosidic linkage remains chemically unstable, limiting biological durability. Here, we report a rationally engineered scaffold-stabilization strategy in which the acid-labile linkage is replaced with a chemically robust cyclitol framework, enabling the concise synthesis of chemically stable and water-soluble tunicamycin analogues in only 12 synthetic steps. From this platform, TM-Cy-TBPA (4) was identified as a lead DPAGT1 inhibitor that potently suppresses the proliferation of breast cancer cells by inducing G2-phase arrest followed by apoptosis, while exhibiting minimal cytotoxicity toward nontransformed cells. The compound shows improved solubility, and favorable pharmacokinetic exposure. These results establish tunicamycin cyclitol analogues as a structurally distinct class of selective DPAGT1-targeted anticancer agents and demonstrate that stabilization of the glycosidic linkage is an effective strategy for enhancing pharmacological selectivity, improving in vivo performance, and simplifying the synthetic route.

Viral RNA-cap MTases are attractive targets for antiviral drug development. We previously identified C7-substituted 7-deaza-SAH analogues as potent inhibitors of the mpox virus 2'-O-MTase VP39. Here, we used structure-guided design to develop branched C7-substituted analogues intended to engage multiple hydrophobic regions of the VP39 SAM-binding pocket. The synthesized compounds were characterized using biochemical and crystallographic approaches. Several analogues effectively inhibited VP39, with the most potent compound displaying an IC50 in the tens-of-nanomolar range. Crystal structures of VP39 in complex with STM1187 and STM1189 confirmed that the branched aromatic substituents extend towards hydrophobic regions adjacent to the SAM binding site. The precise ligand conformations were strongly influenced by linker geometry and the branching groups mode of attachment. STM1078 also inhibited DENV3 NS5 MTase with submicromolar potency, and the complexs structure revealed a conserved binding mode of the SAH-like core accompanied by conformational adaptability of the branched substituent. These results demonstrate how three-dimensional expansion from the 7-deaza position can generate potent inhibitors capable of binding structurally distinct viral MTases.

It is essential to experimentally evaluate antiviral efficacy predicted by molecular docking and related in silico approaches, which this study achieves for three bisphosphonates (alendronate, minodronate, zoledronate) and treprostinil, identified as potential antiviral therapies in our previous work. These investigational compounds had no detectable cytotoxicity at concentrations up to 25M in Vero E6 cells but also failed to show any antiviral effect against the PQ.8.1 isolate of SARS-CoV-2, when compared to control drugs (ensitrelvir, nirmatrelvir, and remdesivir). It appears that for bisphosphonates, any protective effect is likely due to other virus- or host-mediated mechanisms of action. This study demonstrates the importance of iterating between theoretical hypotheses and experiments to elucidate underlying mechanisms at play.

Genetic variants throughout the multi-domain protein leucine-rich repeat kinase 2 (LRRK2) gene are the most common cause of autosomal dominant Parkinson's disease, and the most prevalent Parkinson's-associated LRRK2 variants enhance kinase activity. Hence, the kinase domain has been extensively targeted for therapeutic development. However, clinical progression of LRRK2 kinase inhibitors has been limited by on-target peripheral toxicities linked to strong kinase suppression, raising the question of whether targeting LRRK2 kinase activity through other means could offer a more tunable therapeutic window. LRRK2 is one of two proteins in the human proteome that possess a Roc-COR GTPase domain in tandem with a kinase domain, and the GTPase domain has been shown to intramolecularly regulate kinase output. Here, we ask whether the Roc-COR GTPase can be targeted as an alternative approach to downregulate kinase activity. We utilize a chemical genetic approach to sensitize LRRK2 to existing GTPase inhibitors and show that pharmacologically engaging the Roc-COR GTPase domain in cells decreases but does not fully inhibit LRRK2-mediated Rab10 T73 phosphorylation. This study lays the groundwork for future efforts directed at the development of pharmacological inhibitors for the LRRK2 GTPase, providing an alternative approach for therapies targeting LRRK2-driven Parkinson's disease.

CC10137 is a first-in-class peripherally restricted 2A-adrenergic receptor (2AAR) agonist with broad-spectrum analgesic efficacy and a favorable safety profile. Systematic exploration of the chemical space surrounding first-in-class leads is important for defining series boundaries and guiding continued optimization, but conventional analogue-by-analogue medicinal chemistry samples only a small fraction of the accessible structural space. Here, we used a scaffold-seeded enumeration strategy to expand the chemical space surrounding CC10137 from four SAR-informed seed compounds comprising CC10137 and three closely related structural variants. Application of predefined medicinal chemistry transformation rules in StarDrop generated a virtual library of 16,601,163 unique structures. Morgan fingerprint-based principal component analysis indicated that the library occupied a highly multidimensional structural space involving variation in scaffold substitution, peripheral functional groups, and side-chain composition. A retrospective comparison set of 43 compounds independently designed and experimentally characterized in the earlier CC10137 program represented only approximately 0.00026% of the 16.6-million-member library, yet all 43 were recovered as exact structural matches. Three compounds selected directly from the virtual library retained 2AAR binding affinity and agonist potency below 25 nM. Five representative compounds further showed significant anti-allodynic effects in the in vivo spared nerve injury model, with inhibition rates ranging from 39.3% to 55.7%. These findings support scaffold-seeded computational enumeration as a practical strategy for systematic chemical-space mapping around a first-in-class lead and for identifying additional pharmacologically active structural regions for further optimization.

Screening of the open-access CRESTdb small-molecule library identified the imidazothiazole carboxamide sCQG200 (1) as an initial hit, with activity against H37Rv and Erdman Mycobacterium tuberculosis strains in cholesterol-containing medium (MIC90= 6.88 uM and 4.48 uM, respectively) and against intracellular Mtb (EC50= 3.80 uM). sCQG200 retained activity against drug-resistant Mtb strains, including clinical MDR/XDR isolates. SAR optimization led to analogs 21 and 24 with substantially improved antimycobacterial potency. Mouse pharmacokinetic studies following oral and intravenous administration showed 62.1% and 29.5% oral bioavailability for 21 and 24, respectively. This structurally differentiated chemotype provides a promising starting point for further optimization as antitubercular agent.