The influence of lead discovery strategies on the properties of drug candidates

Advancing mitochondrial therapeutics: Synthesis and pharmacological evaluation of pyrazole-based inhibitors targeting the mitochondrial pyruvate carrier

Inhibition of mitochondrial pyruvate transport via the mitochondrial pyruvate carrier (MPC) has shown beneficial effects in treating metabolic diseases, certain cancers, various forms of neurodegeneration, and hair loss. These benefits arise either from the direct inhibition of mitochondrial pyruvate metabolism or from the metabolic rewiring when pyruvate entry is inhibited. However, current MPC inhibitors are either nonspecific or possess poor pharmacokinetic properties. To address this, approximately 50 pyrazole-based MPC inhibitors were synthesized to explore the structure-activity relationship for MPC inhibition, evaluated through inhibition of mitochondrial pyruvate respiration. These inhibitors were designed with increased steric hindrance around electron-deficient double bonds, allowing for refined structural modifications that reduce their potential to act as Michael acceptors. Additionally, the new MPC inhibitors directly inhibited stellate cell activation, indicating their potential as therapeutic candidates for metabolic dysfunction-associated steatohepatitis (MASH). Unlike the thiazolidinedione class of MPC inhibitors, these compounds did not activate the nuclear receptor PPARγ. Molecular modeling was conducted to explore interactions between these novel inhibitors and the MPC complex. We have identified the chemical determinants critical for MPC inhibition and successfully developed novel inhibitors that are potent, specific and possess excellent physicochemical properties, high solubility, and outstanding metabolic stability in human liver microsomes.

Synthesis and structure-affinity relationships of spirocyclic σ1 receptor ligands with tetrahydropyran scaffold

The σ1 receptor plays a key role in the regulation of various processes in the human body; it is involved in the development of neurodegenerative and neuropsychiatric diseases and is overexpressed in several human tumors rendering it an important target for potential drug candidates. In this project, spirocyclic σ1 receptor ligands with different substituents in 4- and 9-position were synthesized and investigated for their σ1 receptor affinity and selectivity over related targets. The σ1 affinity of the ligands was correlated with their lipophilicity (logD7.4 value) giving insight into their lipophilic ligand efficiency (LLE). The (pyridin-3-yl)methyl derivative 5i showed a promising balance of high σ1 affinity (Ki(σ1) = 3.9 nM) and selectivity (>250-fold) as well as high LLE of 5.8. 5i has a high plasma protein binding (89 %) and promising metabolic stability in the presence of mouse liver microsomes and NADPH (83 % intact after 90 min). Increasing the size of the piperidine ring of the spirocyclic ligands 5 to an azepane ring led to considerably increased σ1 affinity (Ki(5a) = 1.2 nM, Ki(23a) = 0.42 nM) and selectivity over σ2 receptors (5a: 45-fold, 23a: 150-fold).

Selective [3 + 2] C-H/C-H Alkyne Annulation via Dual (Distal) C(β, δ)-H Bond Activation Relay: A Novel Therapeutic Quinazolone-Tethered Benzofulvenes for Oral Cancer

In contrast to proximal C-H bond activations, distal C-H bond activation is fundamentally more challenging and requires distinctly specialized directing partners or techniques. In this context, we report an unprecedented dual (distal) β-C(benzylic)-H and δ-C(aryl)-H bond activation relay protocol for the chemo-, regio-, and stereoselective construction of heterocycle-tethered benzofulvenes via [3 + 2] CH/CH-alkyne annulation under palladium catalysis. The protocol overrides the more favorable [4 + 2] CH/NH annulation and does not follow the vinylic C-H bond activation pathway. Mechanistic studies provide insight into the favored cyclopalladation of key intermediates (resulting from β-C(benzylic)-H bond cleavage) through relay δ-C(aryl)-H cleavage (vs N-H cleavage) prior to reductive elimination, which is the key to desired annulation. The synthesized new chemical entities (NCEs) constitute a novel scaffold with favorable anticancer activity against oral squamous cell carcinoma (OSCC). Detailed biomolecular studies, including RNA-sequencing and analysis, indicate that these compounds (4e and 4w) arrest the cell cycle at the S-phase and target multiple cancer hallmarks, such as the activation of apoptotic pathways and impairment of mitochondrial activity simultaneously, suggesting their chemotherapeutic potential for oral cancer by addressing the complexity and adaptability of cancer cells in chorus.

Deep Lead Optimization: Leveraging Generative AI for Structural Modification

The integration of deep learning-based molecular generation models into drug discovery has garnered significant attention for its potential to expedite the development process. Central to this is lead optimization, a critical phase where existing molecules are refined into viable drug candidates. As various methods for deep lead optimization continue to emerge, it is essential to classify these approaches more clearly. We categorize lead optimization methods into two main types: goal-directed and structure-directed. Our focus is on structure-directed optimization, which, while highly relevant to practical applications, is less explored compared to goal-directed methods. Through a systematic review of conventional computational approaches, we identify four tasks specific to structure-directed optimization: fragment replacement, linker design, scaffold hopping, and side-chain decoration. We discuss the motivations, training data construction, and current developments for each of these tasks. Additionally, we use classical optimization taxonomy to classify both goal-directed and structure-directed methods, highlighting their challenges and future development prospects. Finally, we propose a reference protocol for experimental chemists to effectively utilize Generative AI (GenAI)-based tools in structural modification tasks, bridging the gap between methodological advancements and practical applications.

Molecular hybridization assisted multi-technique approach for designing USP21 inhibitors to halt catalytic triad-mediated nucleophilic attack and suppress pancreatic ductal adenocarcinoma progression: A molecular dynamics study

AIMS

Pancreatic cancer, the 12th-most common cancer, globally, is highly challenging to treat due to its complex epigenetic, metabolic, and genomic characteristics. In pancreatic ductal adenocarcinoma, USP21 acts as an oncogene by stabilizing the long isoform of Transcription Factor 7, thereby activating the Wnt signaling pathway. This study aims to inhibit activation of this pathway through computer-aided drug discovery. Accordingly, four libraries of compounds were designed to target the USP21's catalytic domain (Cys221, His518, Asp534), responsible for its deubiquitinating activity.

MAIN METHODS

Utilizing an array of computer-aided drug design methodologies, such as molecular docking, virtual screening, principal component analysis, molecular dynamics simulation, and dynamic cross-correlation matrix, the structural and functional characteristics of the USP21-inhibitor complex were examined. Following the evaluation of the binding affinities, 20 potential ligands were selected, and the best ligand was subjected to additional molecular dynamics simulation study.

KEY FINDINGS

The results indicated that the ligand-bound USP21 exhibited reduced structural fluctuations compared to the unbound form, as evident from RMSD, RMSF, Rg, and SASA graphs. ADMET analysis of the top ligand showed promising pharmacokinetic and pharmacodynamic profiles, good bioavailability, and low toxicity. The stable conformations of the proposed drug when bound to their target cavities indicate a robust binding affinity of -9.3 kcal/mol. The drug exhibits an elevated pKi value of 6.82, a noteworthy pIC50 value of 5.972, and a pKd value of 6.023 proving its high affinity and inhibitory potential towards the target.

SIGNIFICANCE

In-vitro testing of the top compound (MOLHYB-0436) could lead to its use as a potential treatment for pancreatic cancer.

Ag-Catalyzed Domino Decarboxylative Alkylation/Dearomative Annulation: Entry to Fused-Pyrido[4,3-b]Indolones

Here we report the development of unprecedented silver-catalyzed intramolecular annulations of N-acrolyl-2-(3-indolyl) benzimidazoles with alkyl carboxylic acids to construct complex fused-pentacyclic alkaloid scaffolds. Divergent reactivities are noticed with altered groups at C2-indole of the substrate. The reaction proceeds through decarboxylative alkylation, followed by dearomative annulation in a domino manner with excellent diastereoselectivity. Owing to the reactivity of the tert-OH group, these aza-enriched scaffolds can be further functionalized.

Targeting PilA in Acinetobacter baumannii: A Computational Approach for Anti-Virulent Compound Discovery

Acinetobacter baumannii (A. baumannii) has emerged as a critical global pathogen due to its ability to acquire resistance traits. This bacterium exhibits two distinct forms of motility: twitching, mediated by type IV pili (T4P), and surface-associated motility, independent of appendages. T4P is crucial in various bacterial species, facilitating twitching motility, biofilm formation, and host-cell adhesion. The synthesis of T4P is a common feature among Gram-negative pathogens, particularly A. baumannii, suggesting that PilA could be a viable target for biofilm-related treatments. This study aims to develop drug molecules to mitigate A. baumannii virulence by targeting PilA. Using Schrodinger software, we screened 60,766 compounds from the CMNPD, ChemDiv, and Enamine antibacterial databases through high-throughput virtual screening. The top two compounds from each database, identified through extra precision (XP) mode, were subjected to further studies. Among the six compounds identified (CMNPD18469, CMNPD20698, Z2377302405, Z2378175729, N039-0021, and N098-0051), docking scores ranged from - 5.0 to - 7.5 kcal/mol. Subsequently, we conducted 300 ns molecular dynamics simulations and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis of the PilA-ligand complexes. Analysis of the simulation trajectories indicated structural stability and consistent behavior of the PilA-ligand complexes in a dynamic environment. Notably, the PilA-N098-0051 complex exhibited enhanced stability and robust binding interactions, underscoring its potential as a therapeutic agent. These findings suggest that the identified compounds, particularly N098-0051, hold promise as potent molecules targeting PilA, necessitating further validation through in vitro and in vivo studies.

Balancing Molecular Size, Activity, Permeability, and Other Properties: Drug Candidates in the Context of Their Chemical Structure Optimization

Chemical structure optimization is a vital part of early drug discovery projects. Starting with compounds that show activity on the target of interest, the chemical structures are subsequently optimized toward a development candidate (DC) molecule with the best chances of clinical success. However, the DCs in the context of such optimization programs, as well as detailed characterization of major limiting factors, have not been investigated in detail so far. Here, we report an analysis of the historical DC molecules at Novartis since 2005 in the context of their optimization projects. Mapping the DCs into their respective chemical optimization series, we find that these tend to be synthesized rather early in a substantial number of cases. Further analysis of structural properties, ADMET, and potency-related readouts revealed that DC compounds tend to be generally significantly smaller, more permeable, and have higher ligand efficiency than other compounds sent to in vivo PK studies, which we also show for compounds from the same chemical series. Although this might seem obvious to most practitioners in medicinal chemistry, for all of these properties, we could show that they tend to evolve in an undesired direction during structure optimization. This highlights the difficulty of successfully translating our knowledge to medicinal chemistry optimizations.

Step Forward Cross Validation for Bioactivity Prediction: Out of Distribution Validation in Drug Discovery

Recent advances in machine learning methods for materials science have significantly enhanced accurate predictions of the properties of novel materials. Here, we explore whether these advances can be adapted to drug discovery by addressing the problem of prospective validation - the assessment of the performance of a method on out-of-distribution data. First, we tested whether k-fold n-step forward cross-validation could improve the accuracy of out-of-distribution small molecule bioactivity predictions. We found that it is more helpful than conventional random split cross-validation in describing the accuracy of a model in real-world drug discovery settings. We also analyzed discovery yield and novelty error, finding that these two metrics provide an understanding of the applicability domain of models and an assessment of their ability to predict molecules with desirable bioactivity compared to other small molecules. Based on these results, we recommend incorporating a k-fold n-step forward cross-validation and these metrics when building state-of-the-art models for bioactivity prediction in drug discovery.

Drug solubilization in dog intestinal fluids with and without administration of lipid-based formulations

The use of animal experiments can be minimized with computational models capable of reflecting the simulated environments. One such environment is intestinal fluid and the colloids formed in it. In this study we used molecular dynamics simulations to investigate solubilization patterns for three model drugs (carvedilol, felodipine and probucol) in dog intestinal fluid, a lipid-based formulation, and a mixture of both. We observed morphological transformations that lipids undergo due to the digestion process in the intestinal environment. Further, we evaluated the effect of bile salt concentration and observed the importance of interindividual variability. We applied two methods of estimating solubility enhancement based on the simulated data, of which one was in good qualitative agreement with the experimentally observed solubility enhancement. In addition to the computational simulations, we also measured solubility in i) aspirated dog intestinal fluid samples and ii) simulated canine intestinal fluid in the fasted state, and found there was no statistical difference between the two. Hence, a simplified dissolution medium suitable for in vitro studies provided physiologically relevant data for the systems explored. The computational protocol used in this study, coupled with in vitro studies using simulated intestinal fluids, can serve as a useful prescreening tool in the process of drug delivery strategies development.

Drug Crystal Precipitation in Biorelevant Bicarbonate Buffer: A Well-Controlled Comparative Study with Phosphate Buffer

The purpose of the present study was to clarify whether the precipitation profile of a drug in bicarbonate buffer (BCB) may differ from that in phosphate buffer (PPB) by a well-controlled comparative study. The precipitation profiles of structurally diverse poorly soluble drugs in BCB and PPB were evaluated by a pH-shift precipitation test or a solvent-shift precipitation test (seven weak acid drugs (pKa: 4.2 to 7.5), six weak base drugs (pKa: 4.8 to 8.4), one unionizable drug, and one zwitterionic drug). To focus on crystal precipitation processes, each ionizable drug was first completely dissolved in an HCl (pH 3.0) or NaOH (pH 11.0) aqueous solution (450 mL, 50 rpm, 37 °C). A 10-fold concentrated buffer solution (50 mL) was then added to shift the pH value to 6.5 to initiate precipitation (final volume: 500 mL, buffer capacity (β): 4.4 mM/ΔpH (BCB: 10 mM or PPB: 8 mM), ionic strength (I): 0.14 M (adjusted by NaCl)). The pH, β, and I values were set to be relevant to the physiology of the small intestine. For an unionizable drug, a solvent-shift method was used (1/100 dilution). To maintain the pH value of BCB, a floating lid was used to avoid the loss of CO2. The floating lid was applied also to PPB to precisely align the experimental conditions between BCB and PPB. The solid form of the precipitants was identified by powder X-ray diffraction and differential scanning microscopy. The precipitation of weak acids (pKa ≤ 5.1) and weak bases (pKa ≥ 7.3) was found to be slower in BCB than in PPB. In contrast, the precipitation profiles in BCB and PPB were similar for less ionizable or nonionizable drugs at pH 6.5. The final pH values of the bulk phase were pH 6.5 ± 0.1 after the precipitation tests in all cases. All precipitates were in their respective free forms. The precipitation of ionizable weak acids and bases was slower in BCB than in PPB. The surface pH of precipitating particles may have differed between BCB and PPB due to the slow hydration process of CO2 specific to BCB. Since BCB is a physiological buffer in the small intestine, it should be considered as an option for precipitation studies of ionizable weak acids and bases.

Generative design of compounds with desired potency from target protein sequences using a multimodal biochemical language model

Deep learning models adapted from natural language processing offer new opportunities for the prediction of active compounds via machine translation of sequential molecular data representations. For example, chemical language models are often derived for compound string transformation. Moreover, given the principal versatility of language models for translating different types of textual representations, off-the-beaten-path design tasks might be explored. In this work, we have investigated generative design of active compounds with desired potency from target sequence embeddings, representing a rather provoking prediction task. Therefore, a dual-component conditional language model was designed for learning from multimodal data. It comprised a protein language model component for generating target sequence embeddings and a conditional transformer for predicting new active compounds with desired potency. To this end, the designated "biochemical" language model was trained to learn mappings of combined protein sequence and compound potency value embeddings to corresponding compounds, fine-tuned on individual activity classes not encountered during model derivation, and evaluated on compound test sets that were structurally distinct from training sets. The biochemical language model correctly reproduced known compounds with different potency for all activity classes, providing proof-of-concept for the approach. Furthermore, the conditional model consistently reproduced larger numbers of known compounds as well as more potent compounds than an unconditional model, revealing a substantial effect of potency conditioning. The biochemical language model also generated structurally diverse candidate compounds departing from both fine-tuning and test compounds. Overall, generative compound design based on potency value-conditioned target sequence embeddings yielded promising results, rendering the approach attractive for further exploration and practical applications. SCIENTIFIC CONTRIBUTION: The approach introduced herein combines protein language model and chemical language model components, representing an advanced architecture, and is the first methodology for predicting compounds with desired potency from conditioned protein sequence data.

Synthesis and Anti-Trypanosoma cruzi Activity of 3-Cyanopyridine Derivatives

Chagas disease (CD) is a parasitic neglected tropical disease (NTD) caused by the protozoan Trypanosoma cruzi that affects 6 million people worldwide, often resulting in financial burden, morbidity, and mortality in endemic regions. Given a lack of highly efficient and safe treatments, new, affordable, and fit-for-purpose drugs for CD are urgently needed. In this work, we present a hit-to-lead campaign for novel cyanopyridine analogues as antichagasic agents. In a phenotypic screening against intracellular T. cruzi, hits 1 and 2 were identified and displayed promising potency combined with balanced physicochemical properties. As part of the Lead Optimization Latin America consortium, a set of 40 compounds was designed, synthesized, and tested against T. cruzi intracellular amastigotes and relevant human cell lines. The structural modifications were focused on three positions: cyanopyridine core, linker, and right-hand side. The ADME properties of selected compounds, lipophilicity, kinetic solubility, permeability, and liver microsomal stability, were evaluated. Compounds 1-9 displayed good potency (EC50T. cruzi amastigote <1 μM), and most compounds did not present significant cytotoxicity (CC50 MRC-5 = 32-64 μM). Despite the good balance between potency and selectivity, the antiparasitic activity of the series appeared to be driven by lipophilicity, making the progression of the series unfeasible due to poor ADME properties and potential promiscuity issues.

Dissolution Mechanisms of Amorphous Solid Dispersions: Application of Ternary Phase Diagrams To Explain Release Behavior

The use of amorphous solid dispersions (ASDs) in commercial drug products has increased in recent years due to the large number of poorly soluble drugs in the pharmaceutical pipeline. However, the release behavior of ASDs is complex and remains not well understood. Often, the drug release from ASDs is rapid and complete at lower drug loadings (DLs) but becomes slow and incomplete at higher DLs. The DL where release becomes hindered is termed the limit of congruency (LoC). Currently, there are no approaches to predict the LoC. However, recent findings show that one potential cause leading to the LoC is a change in phase morphology after water-induced phase separation at the ASD/solution interface. In this study, the phase behavior of ASDs in contact with aqueous solutions was described thermodynamically by constructing experimental and computational ternary phase diagrams, and these were used to predict morphology changes and ultimately the LoC. Experimental ternary phase diagrams were obtained by equilibrating ASD/water mixtures over time. Computational ternary phase diagrams were obtained by Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT). The morphology of the hydrophobic phase was studied with fluorescence confocal microscopy. It was demonstrated that critical point (plait point) composition approximately corresponded to the ASD DL, where the hydrophobic phase, formed during phase separation, became interconnected and hindered ASD release. This work provides mechanistic insights into the ASD release behavior and highlights the potential of in silico ASD design using phase diagrams.

Analysing the effect caused by increasing the molecular volume in M1-AChR receptor agonists and antagonists: a structural and computational study

M1 muscarinic acetylcholine receptor (M1-AChR), a member of the G protein-coupled receptors (GPCR) family, plays a crucial role in learning and memory, making it an important drug target for Alzheimer's disease (AD) and schizophrenia. M1-AChR activation and deactivation have shown modifying effects in AD and PD preclinical models, respectively. However, understanding the pharmacology associated with M1-AChR activation or deactivation is complex, because of the low selectivity among muscarinic subtypes, hampering their therapeutic applications. In this regard, we constructed two quantitative structure-activity relationship (QSAR) models, one for M1-AChR agonists (total and partial), and the other for the antagonists. The binding mode of 59 structurally different compounds, including agonists and antagonists with experimental binding affinity values (pKi), were analyzed employing computational molecular docking over different structures of M1-AChR. Furthermore, we considered the interaction energy (Einter), the number of rotatable bonds (NRB), and lipophilicity (ilogP) for the construction of the QSAR model for agonists (R2 = 89.64, QLMO2 = 78, and Qext2 = 79.1). For the QSAR model of antagonists (R2 = 88.44, QLMO2 = 82, and Qext2 = 78.1) we considered the Einter, the fraction of sp3 carbons fCsp3, and lipophilicity (MlogP). Our results suggest that the ligand volume is a determinant to establish its biological activity (agonist or antagonist), causing changes in binding energy, and determining the affinity for M1-AChR.

Challenging the anticolorectal cancer capacity of quinoxaline-based scaffold via triazole ligation unveiled new efficient dual VEGFR-2/MAO-B inhibitors

Monoamine oxidases (MAOs) and vascular endothelial growth factor receptor-2 (VEGFR-2) are promoters of colorectal cancer (CRC) and central signaling nodes in epithelial-mesenchymal transition (EMT) induced by activating hypoxia-inducible factors (HIFs). Herein, a novel series of rationally designed triazole-tethered quinoxalines were synthesized and evaluated against HCT-116 CRC cells. The tailored scaffolds combine the pharmacophoric themes of both VEGFR-2 inhibitors and MAO inhibitors. All the synthesized derivatives were screened utilizing the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay for their possible cytotoxic effects on normal human colonocytes, then evaluated for their anticancer activities against HCT-116 cells overexpressing MAOs. The hit derivatives 11 and 14 exhibited IC50 = 18.04 and 7.850 µM, respectively, against HCT-116cells within their EC100 doses on normal human colonocytes. Wound healing assay revealed their efficient CRC antimetastatic activities recording HCT-116 cell migration inhibition exceeding 75 %. In vitro enzymatic assays demonstrated that both 11 and 14 efficiently inhibited VEGFR-2 (IC50 = 88.79 and 9.910 nM), MAO-A (IC50 = 0.763 and 629.1 nM) and MAO-B (IC50 = 0.488 and 209.6 nM) with observed MAO-B over MAO-A selectivity (SI = 1.546 and 3.001), respectively. Enzyme kinetics studies were performed for both compounds to identify their mode of MAO-B inhibition. Furthermore, qRT-PCR analysis showed that the hits efficiently downregulated HIF-1α in HCT-116cells by 3.420 and 16.96 folds relative to untreated cells. Docking studies simulated their possible binding modes within the active sites of VEGFR-2 and MAO-B to highlight their essential structural determinants of activities. Finally, they recorded in silico drug-like absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles as well as ligand efficiency metrics.

Electrophilic MiniFrags Revealed Unprecedented Binding Sites for Covalent HDAC8 Inhibitors

Screening of ultra-low-molecular weight ligands (MiniFrags) successfully identified viable chemical starting points for a variety of drug targets. Here we report the electrophilic analogues of MiniFrags that allow the mapping of potential binding sites for covalent inhibitors by biochemical screening and mass spectrometry. Small electrophilic heterocycles and their N-quaternized analogues were first characterized in the glutathione assay to analyze their electrophilic reactivity. Next, the library was used for systematic mapping of potential covalent binding sites available in human histone deacetylase 8 (HDAC8). The covalent labeling of HDAC8 cysteines has been proven by tandem mass spectrometry measurements, and the observations were explained by mutating HDAC8 cysteines. As a result, screening of electrophilic MiniFrags identified three potential binding sites suitable for the development of allosteric covalent HDAC8 inhibitors. One of the hit fragments was merged with a known HDAC8 inhibitor fragment using different linkers, and the linker length was optimized to result in a lead-like covalent inhibitor.

Discovery of tetrazolo-pyridazine-based small molecules as inhibitors of MACC1-driven cancer metastasis

Metastasis is directly linked to poor prognosis of cancer patients and warrants search for effective anti-metastatic drugs. MACC1 is a causal key molecule for metastasis. High MACC1 expression is prognostic for metastasis and poor survival. Here, we developed novel small molecule inhibitors targeting MACC1 expression to impede metastasis formation. We performed a human MACC1 promoter-driven luciferase reporter-based high-throughput screen (HTS; 118.500 compound library) to identify MACC1 transcriptional inhibitors. HTS revealed 1,2,3,4-tetrazolo[1,5-b]pyridazine-based compounds as efficient transcriptional inhibitors of MACC1 expression, able to decrease MACC1-induced cancer cell motility in vitro. Structure-activity relationships identified the essential inhibitory core structure. Best candidates were evaluated for metastasis inhibition in xenografted mouse models demonstrating metastasis restriction. ADMET showed high drug-likeness of these new candidates for cancer therapy. The NFκB pathway was identified as one mode of action targeted by these compounds. Taken together, 1,2,3,4-tetrazolo[1,5-b]pyridazine-based compounds are effective MACC1 inhibitors and pose promising candidates for anti-metastatic therapies particularly for patients with MACC1-overexpressing cancers, that are at high risk to develop metastases. Although further preclinical and clinical development is necessary, these compounds represent important building blocks for an individualized anti-metastatic therapy for solid cancers.

Advancing algorithmic drug product development: Recommendations for machine learning approaches in drug formulation

Artificial intelligence is a rapidly expanding area of research, with the disruptive potential to transform traditional approaches in the pharmaceutical industry, from drug discovery and development to clinical practice. Machine learning, a subfield of artificial intelligence, has fundamentally transformed in silico modelling and has the capacity to streamline clinical translation. This paper reviews data-driven modelling methodologies with a focus on drug formulation development. Despite recent advances, there is limited modelling guidance specific to drug product development and a trend towards suboptimal modelling practices, resulting in models that may not give reliable predictions in practice. There is an overwhelming focus on benchtop experimental outcomes obtained for a specific modelling aim, leaving the capabilities of data scraping or the use of combined modelling approaches yet to be fully explored. Moreover, the preference for high accuracy can lead to a reliance on black box methods over interpretable models. This further limits the widespread adoption of machine learning as black boxes yield models that cannot be easily understood for the purposes of enhancing product performance. In this review, recommendations for conducting machine learning research for drug product development to ensure trustworthiness, transparency, and reliability of the models produced are presented. Finally, possible future directions on how research in this area might develop are discussed to aim for models that provide useful and robust guidance to formulators.

Corrected solid-state 13 C nuclear magnetic resonance peak assignment and side-group quantification of hydroxypropyl methylcellulose acetyl succinate pharmaceutical excipients

Hydroxypropyl methylcellulose acetyl succinate (HPMCAS) is widely used as a pharmaceutical excipient, making a detailed understanding of its tunable structure important for formulation design. Several recently reported peak assignments in the solid-state 13 C NMR spectrum of HPMCAS have been corrected here using peak integrals in quantitative spectra, spectral editing, empirical chemical-shift predictions based on solution NMR, and full spectrum simulation analogous to deconvolution. Unlike in cellulose, the strong peak at 84 ppm must be assigned to C2 and C3 methyl ethers, instead of regular C4 of cellulose. The proposed assignment of signals at <65 ppm to OCH sites, including C5 of cellulose, could not be confirmed. CH2 spectral editing showed two resolved OCH2 bands, a more intense one from O-CH2 ethers of C6 at >69 ppm and a smaller one from its esters and possibly residual CH2 -OH groups, near 63 ppm. The strong intensities of resolved signals of acetyl, succinoyl, and oxypropyl substituents indicated the substitution of >85% of the OH groups in HPMCAS. The side-group concentrations in three different grades of HPMCAS were quantified.

Diastereoselective synthesis and structure-affinity relationships of σ1 receptor ligands with spirocyclic scaffold

Spirocyclic scaffolds play an increasing role in drug discovery as they define a rigid three-dimensional space to increase specific interactions with protein binding sites. Herein, a spirocyclic center was introduced into the lead compound 1 to rigidify its flexible benzylaminoethyl side chain. The key step of the synthesis was the reaction of different α,β-unsaturated amides 6 and 13-16 with methyl acrylate in the presence of TBDMSOTf. DFT calculations explain the mechanism of this transformation as concerted Diels-Alder reaction (functionals B3LYP and TPSS) or double (aza)-Michael addition (functionals PBE and wB97X-D). After separation of the diastereomeric spirocyclic products 8 and 17-20, LiAlH4 reduction provided the spirocyclic hydroxymethyl piperidines 21a,b-25a,b showing low nanomolar σ1 affinity (Ki < 100 nM). trans-Configured ligands (a-series) showed higher or equal σ1 affinity and higher selectivity over σ2 receptors and GluN2B-NMDA receptors than their cis-configured analogs (b-series). The additional hydroxymethyl moiety brings the log D7.4 value in a promising range. The high σ1 affinity (Ki = 3.6 nM) and the low lipophilicity result in the highest lipophilic ligand efficiency for the dispiro compound 23a (LLE = 6.0). The spirocyclic compounds reported herein and in particular the dispiro compound 23a demonstrate that ligands containing a large number of sp3 C-atoms possess favorable pharmacological (σ1 receptor affinity, receptor selectivity) and physicochemical properties (log D7.4 value) resulting in promising LLE.

Efficient Ligand Discovery Using Sulfur(VI) Fluoride Reactive Fragments

Sulfur(VI) fluorides (SFs) have emerged as valuable electrophiles for the design of "beyond-cysteine" covalent inhibitors and offer potential for expansion of the liganded proteome. Since SFs target a broad range of nucleophilic amino acids, they deliver an approach for the covalent modification of proteins without requirement for a proximal cysteine residue. Further to this, libraries of reactive fragments present an innovative approach for the discovery of ligands and tools for proteins of interest by leveraging a breadth of mass spectrometry analytical approaches. Herein, we report a screening approach that exploits the unique properties of SFs for this purpose. Libraries of SF-containing reactive fragments were synthesized, and a direct-to-biology workflow was taken to efficiently identify hit compounds for CAII and BCL6. The most promising hits were further characterized to establish the site(s) of covalent modification, modification kinetics, and target engagement in cells. Crystallography was used to gain a detailed molecular understanding of how these reactive fragments bind to their target. It is anticipated that this screening protocol can be used for the accelerated discovery of "beyond-cysteine" covalent inhibitors.

Discovery, Structure-Activity Relationships, and In Vivo Activity of Dihydropyridone Agonists of the Bile Acid Receptor TGR5

A novel series of potent agonists of the bile acid receptor TGR5 bearing a dihydropyridone scaffold was developed from a high-throughput screen. Starting from a micromolar hit compound, we implemented an extensive structure-activity-relationship (SAR) study with the synthesis and biological evaluation of 83 analogues. The project culminated with the identification of the potent nanomolar TGR5 agonist 77A. We report the GLP-1 secretagogue effect of our lead compound ex vivo in mouse colonoids and in vivo. In addition, to identify specific features favorable for TGR5 activation, we generated and optimized a three-dimensional quantitative SAR model that contributed to our understanding of our activity profile and could guide further development of this dihydropyridone series.

Development of Long-Acting Dipeptidyl Peptidase-4 Inhibitors: Structural Evolution and Long-Acting Determinants

Considerable effort has been made to achieve less frequent dosing in the development of DPP-4 inhibitors. Enthusiasm for long-acting DPP-4 inhibitors is based on the promise that such agents with less frequent dosing regimens are associated with improved patient adherence, but the rational design of long-acting DPP-4 inhibitors remains a major challenge. In this Perspective, the development of long-acting DPP-4 inhibitors is comprehensively summarized to highlight the evolution of initial lead compounds on the path toward developing long-acting DPP-4 inhibitors over nearly three decades. The determinants for long duration of action are then examined, including the nature of the target, potency, binding kinetics, crystal structures, selectivity, and preclinical and clinical pharmacokinetic and pharmacodynamic profiles. More importantly, several possible approaches for the rational design of long-acting drugs are discussed. We hope that this information will facilitate the design and development of safer and more effective long-acting DPP-4 inhibitors and other oral drugs.

Thermal degradation of Affinisol HPMC: Optimum Processing Temperatures for Hot Melt Extrusion and 3D Printing

PURPOSE

Affinisol HPMC HME is a new popular form of hypromellose specifically designed for the hot melt extrusion and 3D printing of pharmaceutical products. However, reports of its thermal stability include only data obtained under inert N2 atmosphere, which is not consistent with the common pharmaceutical practice. Therefore, detailed investigation of its real-life thermal stability in air is paramount for identification of potential risks and limitations during its high-temperature processing.

METHODS

In this work, the Affinisol HPMC HME 15LV powder as well as extruded filaments will be investigated by means of thermogravimetry, differential scanning calorimetry and infrared spectroscopy with respect to its thermal stability.

RESULTS

The decomposition in N2 was proceeded in accordance with the literature data and manufacturer's specifications: onset at ~260°C at 0.5°C·min-1, single-step mass loss of 90-95%. However, in laboratory or industrial practice, high-temperature processing is performed in the air, where oxidation-induced degradation drastically changes. The thermogravimetric mass loss in air proceeded in three stages: ~ 5% mass loss with onset at 150°C, ~ 70% mass loss at 200°C, and ~ 15% mass loss at 380°C. Diffusion of O2 into the Affinisol material was identified as the rate-determining step.

CONCLUSION

For extrusion temperatures ≥170°C, Affinisol exhibits a significant degree of degradation within the 5 min extruder retention time. Hot melt extrusion of pure Affinisol can be comfortably performed below this temperature. Utilization of plasticizers may be necessary for safe 3D printing.

Herbal concoction Unveiled: A computational analysis of phytochemicals' pharmacokinetic and toxicological profiles using novel approach methodologies (NAMs)

Herbal medications have an extensive history of use in treating various diseases, attributed to their perceived efficacy and safety. Traditional medicine practitioners and contemporary healthcare providers have shown particular interest in herbal syrups, especially for respiratory illnesses associated with the SARS-CoV-2 virus. However, the current understanding of the pharmacokinetic and toxicological properties of phytochemicals in these herbal mixtures is limited. This study presents a comprehensive computational analysis utilizing novel approach methodologies (NAMs) to investigate the pharmacokinetic and toxicological profiles of phytochemicals in herbal syrup, leveraging in-silico techniques and prediction tools such as PubChem, SwissADME, and Molsoft's database. Although molecular dynamics, docking, and broader system-wide analyses were not considered, future studies hold potential for further investigation in these areas. By combining drug-likeness with molecular simulation, researchers identify diverse phytochemicals suitable for complex medication development examining their pharmacokinetic-toxicological profiles in phytopharmaceutical syrup. The study focuses on herbal solutions for respiratory infections, with the goal of adding to the pool of all-natural treatments for such ailments. This research has the potential to revolutionize environmental and alternative medicine by leveraging in-silico models and innovative analytical techniques to identify novel phytochemicals with enhanced therapeutic benefits and explore network-based and systems biology approaches for a deeper understanding of their interactions with biological systems. Overall, our study offers valuable insights into the computational analysis of the pharmacokinetic and toxicological profiles of herbal concoction. This paves the way for advancements in environmental and alternative medicine. However, we acknowledge the need for future studies to address the aforementioned topics that were not adequately covered in this research.

Synthesis of Bleomycin-Inspired RNA Ligands Targeting the Biogenesis of Oncogenic miRNAs

Noncoding RNAs (ncRNAs) play pivotal roles in the regulation of gene expression and represent a promising target for the development of new therapeutic approaches. Among these ncRNAs, microRNAs (miRNAs or miRs) are involved in the regulation of gene expression, and their dysregulation has been linked to several diseases such as cancers. Indeed, oncogenic miRNAs are overexpressed in cancer cells, thus promoting tumorigenesis and maintenance of cancer stem cells that are resistant to chemotherapy and often responsible for therapeutic failure. Here, we describe the design and synthesis of new small-molecule RNA binders able to inhibit the biogenesis of oncogenic miRNAs and target efficiently cancer stem cells. Through the biochemical study of their interaction with the target and thanks to intracellular assays, we describe the structure-activity relationships for this new series of RNA ligands, and we identify compounds bearing a very promising antiproliferative activity against cancer stem cells.

Energy-based generative models for target-specific drug discovery

Drug targets are the main focus of drug discovery due to their key role in disease pathogenesis. Computational approaches are widely applied to drug development because of the increasing availability of biological molecular datasets. Popular generative approaches can create new drug molecules by learning the given molecule distributions. However, these approaches are mostly not for target-specific drug discovery. We developed an energy-based probabilistic model for computational target-specific drug discovery. Results show that our proposed TagMol can generate molecules with similar binding affinity scores as real molecules. GAT-based models showed faster and better learning relative to Graph Convolutional Network baseline models.

Insight into the mechanism behind oral bioavailability-enhancement by nanosuspensions through combined dissolution/permeation studies

As numerous new drug candidates are poorly water soluble, enabling formulations are needed to increase their bioavailability for oral administration. Nanoparticles are a conceptually simple, yet resource consuming strategy for increasing drug dissolution rate, as predicting in vivo oral absorption using in vitro dissolution remains difficult. The objective of this study was to obtain insight into nanoparticle characteristics and performance utilizing an in vitro combined dissolution/permeation setup. Two examples of poorly soluble drugs were examined (cinnarizine and fenofibrate). Nanosuspensions were produced by top-down wet bead milling using dual asymmetric centrifugation, obtaining particle diameters of approx. 300 nm. DSC and XRPD studies indicated that nanocrystals of both drugs were present with retained crystallinity, however with some disturbances. Equilibrium solubility studies showed no significant increase in drug solubility over the nanoparticles, as compared to the raw APIs. Combined dissolution/permeation experiments revealed significantly increased dissolution rates for both compounds compared to the raw APIs. However, there were substantial differences between the dissolution curves of the nanoparticles as fenofibrate exhibited supersaturation followed by precipitation, whereas cinnarizine did not exhibit any supersaturation, but instead a shift towards faster dissolution rate. Permeation rates were found significantly increased for both nanosuspensions when compared to the raw APIs, indicating a direct implication that formulation strategies are needed, be it stabilization of supersaturation by precipitation inhibition and/or dissolution rate enhancement. This study indicates that in vitro dissolution/permeation studies can be employed to better understand the oral absorption enhancement of nanocrystal formulations.

Repurposing 1,2,4-oxadiazoles as SARS-CoV-2 PLpro inhibitors and investigation of their possible viral entry blockade potential

Although vaccines are obviously mitigating the COVID-19 pandemic diffusion, efficient complementary antiviral agents are urgently needed to combat SARS-CoV-2. The viral papain-like protease (PLpro) is a promising therapeutic target being one of only two essential proteases crucial for viral replication. Nevertheless, it dysregulates the host immune sensing response. Here we report repositioning of the privileged 1,2,4-oxadiazole scaffold as promising SARS-CoV-2 PLpro inhibitor with potential viral entry inhibition profile. The design strategy relied on mimicking the general structural features of the lead benzamide PLpro inhibitor GRL0617 with isosteric replacement of its pharmacophoric amide backbone by 1,2,4-oxadiazole core. Inspired by the multitarget antiviral agents, the substitution pattern was rationalized to tune the scaffold's potency against other additional viral targets, especially the spike receptor binding domain (RBD) that is responsible for the viral invasion. The Adopted facial synthetic protocol allowed easy access to various rationally substituted derivatives. Among the evaluated series, the 2-[5-(pyridin-4-yl)-1,2,4-oxadiazol-3-yl]aniline (5) displayed the most balanced dual inhibitory potential against SARS-CoV-2 PLpro (IC50=7.197 μM) and spike protein RBD (IC50 = 8.673 μM), with acceptable ligand efficiency metrics, practical LogP (3.8) and safety profile on Wi-38 (CC50 = 51.78 μM) and LT-A549 (CC50 = 45.77 μM) lung cells. Docking simulations declared the possible structural determinants of activities and enriched the SAR data for further optimization studies.

Dockey: a modern integrated tool for large-scale molecular docking and virtual screening

Molecular docking is a structure-based and computer-aided drug design approach that plays a pivotal role in drug discovery and pharmaceutical research. AutoDock is the most widely used molecular docking tool for study of protein-ligand interactions and virtual screening. Although many tools have been developed to streamline and automate the AutoDock docking pipeline, some of them still use outdated graphical user interfaces and have not been updated for a long time. Meanwhile, some of them lack cross-platform compatibility and evaluation metrics for screening lead compound candidates. To overcome these limitations, we have developed Dockey, a flexible and intuitive graphical interface tool with seamless integration of several useful tools, which implements a complete docking pipeline covering molecular sanitization, molecular preparation, paralleled docking execution, interaction detection and conformation visualization. Specifically, Dockey can detect the non-covalent interactions between small molecules and proteins and perform cross-docking between multiple receptors and ligands. It has the capacity to automatically dock thousands of ligands to multiple receptors and analyze the corresponding docking results in parallel. All the generated data will be kept in a project file that can be shared between any systems and computers with the pre-installation of Dockey. We anticipate that these unique characteristics will make it attractive for researchers to conduct large-scale molecular docking without complicated operations, particularly for beginners. Dockey is implemented in Python and freely available at https://github.com/lmdu/dockey.

The European Federation for Medicinal Chemistry and Chemical Biology (EFMC) Best Practice Initiative: Hit Generation

Hit generation is a crucial step in drug discovery that will determine the speed and chance of success of identifying drug candidates. Many strategies are now available to identify chemical starting points, or hits, and each biological target warrants a tailored approach. In this set of best practices, we detail the essential approaches for target centric hit generation and the opportunities and challenges they come with. We then provide guidance on how to validate hits to ensure medicinal chemistry is only performed on compounds and scaffolds that engage the target of interest and have the desired mode of action. Finally, we discuss the design of integrated hit generation strategies that combine several approaches to maximize the chance of identifying high quality starting points to ensure a successful drug discovery campaign.

Worm Generator: A System for High-Throughput in Vivo Screening

Large-scale screening of molecules in organisms requires high-throughput and cost-effective evaluating tools during preclinical development. Here, a novel in vivo screening strategy combining hierarchically structured biohybrid triboelectric nanogenerators (HB-TENGs) arrays with computational bioinformatics analysis for high-throughput pharmacological evaluation using Caenorhabditis elegans is described. Unlike the traditional methods for behavioral monitoring of the animals, which are laborious and costly, HB-TENGs with micropillars are designed to efficiently convert animals' behaviors into friction deformation and result in a contact-separation motion between two triboelectric layers to generate electrical outputs. The triboelectric signals are recorded and extracted to various bioinformation for each screened compound. Moreover, the information-rich electrical readouts are successfully demonstrated to be sufficient to predict a drug's identity by multiple-Gaussian-kernels-based machine learning methods. This proposed strategy can be readily applied to various fields and is especially useful in in vivo explorations to accelerate the identification of novel therapeutics.

Microfluidic synthesis of multilayered lipid-polymer hybrid nanoparticles for the formulation of low solubility drugs

Hybrid phospholipid/block copolymer membranes where polymers and lipids are molecularly mixed or phase-separated into polymer-rich and lipid-rich domains are promising drug delivery materials. Harnessing the chemical diversity of polymers and the biocompatability of lipids is a compelling approach to design the next generation of drug carriers. Here, we report on the development of a microfluidics-based strategy analogous to produce lipid nanoparticles (LNPs) for the nanomanufacturing of multilayered hybrid nanoparticles (HNPs). Using X-ray scattering, Cryo-electron, and polarized microscopy we show that phosphatidylcholine (PC) and PBD-b-PEO (poly(butadiene-block-ethylene oxide)) hybrid membranes can be nanomanufactured by microfluidics into HNPs with dense and multilayered cores which are ideal carriers of low-solubility drugs of the Biopharmaceutical Classification System (BCS) II and IV such as antimalarial DSM265 and Paclitaxel, respectively.

In-vitro dynamic dissolution/bioconversion/permeation of fosamprenavir using a novel tool with an artificial biomimetic permeation barrier and microdialysis-sampling

Fosamprenavir is a phosphate ester prodrug that, upon dissolution, is cleaved to the poorly soluble yet readily absorbable parent drug amprenavir. In this study, a novel cell-free in vitro setup with quasi-continuous monitoring of the dynamic dissolution/bio-conversion/permeation of fosamprenavir was designed and tested. It consists of side-by-side diffusion cells, where the donor and acceptor compartments are separated by the biomimetic barrier PermeaPad®, and sampling from the donor compartment is accomplished via a microdialysis probe. Externally added bovine alkaline phosphatase induced bioconversion in the donor compartment. Microdialysis sampling allowed to follow the enzymatic conversion of fosamprenavir to amprenavir by the bovine alkaline phosphatase in an (almost) real-time manner eliminating the need to remove or inactivate the enzyme. Biomimetic conversion rates in the setup were established by adding appropriate amounts of the alkaline phosphatase. A substantial (6.5-fold) and persistent supersaturation of amprenavir was observed due to bioconversion at lower (500 µM) concentrations, resulting in a substantially increased flux across the biomimetic barrier, nicely reflecting the situation in vivo. At conditions with an almost 10-fold higher dose than the usual human dose, some replicates showed premature precipitation and collapse of supersaturation, while others did not. In conclusion, the proposed novel tool appears very promising in gaining an in-depth mechanistic understanding of the bioconversion/permeation interplay, including transient supersaturation of phosphate-ester prodrugs like fosamprenavir.

Prediction of Oral Drug Absorption in Rats from In Vitro Data

PURPOSE

In drug discovery, rats are widely used for pharmacological and toxicological studies. We previously reported that a mechanism-based oral absorption model, the gastrointestinal unified theoretical framework (GUT framework), can appropriately predict the fraction of a dose absorbed (Fa) in humans and dogs. However, there are large species differences between humans and rats. The purpose of the present study was to evaluate the predictability of the GUT framework for rat Fa.

METHOD

The Fa values of 20 model drugs (a total of 39 Fa data) were predicted in a bottom-up manner. Based on the literature survey, the bile acid concentration (C_bile) and the intestinal fluid volume were set to 15 mM and 4 mL/kg, respectively, five and two times higher than in humans. LogP, pK_a, molecular weight, intrinsic solubility, bile micelle partition coefficients, and Caco-2 permeability were used as input data.

RESULTS

The Fa values were appropriately predicted for highly soluble drugs (absolute average fold error (AAFE) = 1.65, 18 Fa data) and poorly soluble drugs (AAFE = 1.57, 21 Fa data). When the species difference in C_bile was ignored, Fa was over- and under-predicted for permeability and solubility limited cases, respectively. High C_bile in rats reduces the free fraction of drug molecules available for epithelial membrane permeation while increasing the solubility of poorly soluble drugs.

CONCLUSION

The Fa values in rats were appropriately predicted by the GUT framework. This result would be of great help for a better understanding of species differences and model-informed preclinical formulation development.

Novel rhodanine based inhibitors of aldose reductase of non-acidic nature with p-hydroxybenzylidene functional group

Aldose reductase, the first enzyme of the polyol pathway represents a key drug target in therapy of diabetic complications. In this study a series of six novel rhodanine based inhibitors of aldose reductase was designed, synthesized, and tested for their ability to inhibit aldose reductase and for selectivity relative to structurally related aldehyde reductase. Aldose reductase inhibitory activities of the compounds were characterized by the IC₅₀ values ranging from 2000 nM to 20 nM. The values of selectivity factors relative to aldehyde reductase were decreasing in the same array from 24 to 5. In silico docking into the inhibitor binding site of aldose reductase revealed a specific binding pattern of the compounds comprising interaction of the deprotonated 4-hydroxybenzylidene group with the anion-binding sub-pocket of aldose reductase, creating a strong H-bond and charge interactions. Predicted pH-distribution profiles of the novel compounds into octanol, supported by experimentally determined distribution ratios, favour drug uptake at the physiological pH, as a result of the presence of the low-acidic phenolic group, instead of the more acidic carboxymethyl functional group.

Discovery of a structurally novel, potent, and once-weekly free fatty acid receptor 1 agonist for the treatment of diabetes

Type 2 diabetes mellitus (T2DM) is a lifelong disease that requires long-term medication to control glucose levels, and thereby long-acting drug has been clinically needed for improving medical adherence. The free fatty acid receptor 1 (FFA1) was considered as a promising target for several diseases, such as T2DM, pain and fatty liver. However, no once-weekly FFA1 agonist has been reported until now. Herein, we report the successful discovery of ZLY50, the first once-weekly FFA1 agonist with a completely new chemotype, highly agonistic activity and selectivity on FFA1. Moreover, ZLY50 has enough brain exposure to activate FFA1 in brain, and it is the first orally available FFA1 agonist with analgesic activity. Notably, the long-term anti-diabetic and anti-fatty liver effects of ZLY50 (once-weekly) were better than those of HWL-088 (once-daily), a highly potent FFA1 agonist with far stronger glucose-lowering effect than Phase 3 clinical candidate TAK-875. Further mechanism studies suggested that ZLY50 alleviates fatty liver by regulating the expressions of genes related to lipid metabolism, mitochondrial function, and oxidative stress in liver.

Dissolution Mechanisms of Amorphous Solid Dispersions: Role of Drug Load and Molecular Interactions

High drug load amorphous solid dispersions (ASDs) have been a challenge to formulate partially because drug release is inhibited at high drug loads. The maximum drug load prior to inhibition of release has been termed the limit of congruency (LoC) and has been most widely studied for copovidone (PVPVA)-based ASDs. The terminology was derived from the observation that below LoC, the polymer controlled the kinetics and the drug and the polymer released congruently, while above LoC, the release rates diverged and were impaired. Recent studies show a correlation between the LoC value and drug-polymer interaction strength, where a lower LoC was observed for systems with stronger interactions. The aim of this study was to investigate the causality between drug-PVPVA interaction strength and LoC. Four chemical analogues with diverse abilities to interact with PVPVA were used as model drugs. The distribution of the polymer between the dilute aqueous phase and the insoluble nanoparticles containing drug was studied with solution nuclear magnetic resonance spectroscopy and traditional separation techniques to understand the thermodynamics of the systems in a dilute environment. Polymer diffusion to and from ASD particles suspended in aqueous solution was monitored for drug loads above the LoC to investigate the thermodynamic driving force for polymer release. The surface composition of ASD compacts before and after exposure to buffer was studied with Fourier transform infrared spectroscopy to capture potential kinetic barriers to release. It was found that ASD compacts with drug loads above the LoC formed an insoluble barrier on the surface that was in pseudo-equilibrium with the aqueous phase and prevented further release of drugs and polymers during dissolution. The insoluble barrier contained a substantial amount of the polymer for the strongly interacting drug-polymer systems. In contrast, a negligible amount was found for the weakly interacting systems. This observation provides an explanation for the ability of strongly interacting systems to form an insoluble barrier at lower drug loads. The study highlights the importance of thermodynamic and kinetic factors on the dissolution behavior of ASDs and provides a potential framework for maximizing the drug load in ASDs.

Molecular Dynamics Simulations of Self-Assembling Colloids in Fed-State Human Intestinal Fluids and Their Solubilization of Lipophilic Drugs

Bioavailability of oral drugs often depends on how soluble the active pharmaceutical ingredient is in the fluid present in the small intestine. For efficient drug discovery and development, computational tools are needed for estimating this drug solubility. In this paper, we examined human intestinal fluids collected in the fed state, with coarse-grained molecular dynamics simulations. The experimentally obtained concentrations in aspirated duodenal fluids from five healthy individuals were used in three simulation sets to evaluate the importance of the initial distribution of molecules and the presence of glycerides in the simulation box when simulating the colloidal environment of the human intestinal fluid. We observed self-assembly of colloidal structures of different types: prolate, elongated, and oblate micelles, and vesicles. Glycerides were important for the formation of vesicles, and their absence was shown to induce elongated micelles. We then simulated the impact of digestion and absorption on the different colloidal types. Finally, we looked at the solubilization of three model compounds of increasing lipophilicity (prednisolone, fenofibrate, and probucol) by calculating contact ratios of drug-colloid to drug-water. Our simulation results of colloidal interactions with APIs were in line with experimental solubilization data but showed a dissimilarity to solubility values when comparing fasted-/fed-state ratios between two of the APIs. This work shows that coarse-grained molecular dynamics simulation is a promising tool for investigation of the intestinal fluids, in terms of colloidal attributes and drug solubility.

Structure optimization of new tumor-selective Passerini α-acyloxy carboxamides as Caspase-3/7 activators

Selective elimination of tumors has always been the mainstay of oncology research. The on-going research underlying the cellular apoptotic mechanisms reveal caspases activation, especially the key effector caspase-3, as a personalized tumor-selective therapeutic strategy. Our continued research protocol has exploited new optimized Passerini α-acyloxy carboxamides as efficient apoptotic inducers via caspase-3/7 dependent mechanism with highly selective anticancer profiles. The adopted design rationale relied on excluding structural alerts of previous leads, while merging various pharmacophoric motifs of natural and synthetic caspase activators via optimized one-pot Passerini reaction conditions. The prepared compounds resulting from Passerini reaction were screened for their cytotoxic activities against colorectal Caco-2 and liver HepG-2 cancer cells compared to normal fibroblasts utilizing MTT assay. Notably, all compounds exhibited promising low-range submicromolar IC₅₀ against the studied cancer cell lines, with outstanding tumor selectivity (SI values up to 266). Hence, they were superior to 5-fluorouracil. Notably, 7a, 7g, and 7j conferred the highest potencies against Caco-2 and HepG-2 cells and were selected for further mechanistic studies. Caspas-3/7 activation assay of the hit compounds and flow cytometric analysis of the treated apoptotic cancer cells demonstrated their significant caspase activation potential (up to 4.2 folds) and apoptotic induction capacities (up to 58.7%). Further assessment of Bcl2 expression was performed being a physiological caspase-3 substrate. Herein, the three studied Passerini adducts were able to downregulate Bcl2 in the treated Caco-2 cells. Importantly, the mechanistic studies results of the three hits echoed their preliminary MTT antiproliferative potencies data highlighting their caspase-3 dependent apoptotic induction. Finally, the in silico predicted physicochemical and pharmacokinetic profiles, as well as ligand efficiency metrics were drug-like.

Predicting the Temperature Evolution during Nanomilling of Drug Suspensions via a Semi-Theoretical Lumped-Parameter Model

Although temperature can significantly affect the stability and degradation of drug nanosuspensions, temperature evolution during the production of drug nanoparticles via wet stirred media milling, also known as nanomilling, has not been studied extensively. This study aims to establish both descriptive and predictive capabilities of a semi-theoretical lumped parameter model (LPM) for temperature evolution. In the experiments, the mill was operated at various stirrer speeds, bead loadings, and bead sizes, while the temperature evolution at the mill outlet was recorded. The LPM was formulated and fitted to the experimental temperature profiles in the training runs, and its parameters, i.e., the apparent heat generation rate Q_gen and the apparent overall heat transfer coefficient times surface area UA, were estimated. For the test runs, these parameters were predicted as a function of the process parameters via a power law (PL) model and machine learning (ML) model. The LPM augmented with the PL and ML models was used to predict the temperature evolution in the test runs. The LPM predictions were also compared with those of an enthalpy balance model (EBM) developed recently. The LPM had a fitting capability with a root-mean-squared error (RMSE) lower than 0.9 °C, and a prediction capability, when augmented with the PL and ML models, with an RMSE lower than 4.1 and 2.1 °C, respectively. Overall, the LPM augmented with the PL model had both good descriptive and predictive capability, whereas the one with the ML model had a comparable predictive capability. Despite being simple, with two parameters and obviating the need for sophisticated numerical techniques for its solution, the semi-theoretical LPM generally predicts the temperature evolution similarly or slightly better than the EBM. Hence, this study has provided a validated, simple model for pharmaceutical engineers to simulate the temperature evolution during the nanomilling process, which will help to set proper process controls for thermally labile drugs.

25 Years of Small-Molecule Optimization at Novartis: A Retrospective Analysis of Chemical Series Evolution

In the drug development process, optimization of properties and biological activities of small molecules is an important task to obtain drug candidates with optimal efficacy when first applied in subsequent clinical studies. However, despite its importance, large-scale investigations of the optimization process in early drug discovery are lacking, likely due to the absence of historical records of different chemical series used in past projects. Here, we report a retrospective reconstruction of ∼3000 chemical series from the Novartis compound database, which allows us to characterize the general properties of chemical series as well as the time evolution of structural properties, ADMET properties, and target activities. Our data-driven approach allows us to substantiate common MedChem knowledge. We find that size, fraction of sp³-hybridized carbon atoms (F_sp³), and the density of stereocenters tend to increase during optimization, while the aromaticity of the compounds decreases. On the ADMET side, solubility tends to increase and permeability decreases, while safety-related properties tend to improve. Importantly, while ligand efficiency decreases due to molecular growth over time, target activities and lipophilic efficiency tend to improve. This emphasizes the heavy-atom count and log D as important parameters to monitor, especially as we further show that the decrease in permeability can be explained with the increase in molecular size. We highlight overlaps, shortcomings, and differences of the computationally reconstructed chemical series compared to the series used in recent internal drug discovery projects and investigate the relation to historical projects.

Fragment screening using biolayer interferometry reveals ligands targeting the SHP-motif binding site of the AAA+ ATPase p97

Biosensor techniques have become increasingly important for fragment-based drug discovery during the last years. The AAA+ ATPase p97 is an essential protein with key roles in protein homeostasis and a possible target for cancer chemotherapy. Currently available p97 inhibitors address its ATPase activity and globally impair p97-mediated processes. In contrast, inhibition of cofactor binding to the N-domain by a protein-protein-interaction inhibitor would enable the selective targeting of specific p97 functions. Here, we describe a biolayer interferometry-based fragment screen targeting the N-domain of p97 and demonstrate that a region known as SHP-motif binding site can be targeted with small molecules. Guided by molecular dynamics simulations, the binding sites of selected screening hits were postulated and experimentally validated using protein- and ligand-based NMR techniques, as well as X-ray crystallography, ultimately resulting in the first structure of a small molecule in complex with the N-domain of p97. The identified fragments provide insights into how this region could be targeted and present first chemical starting points for the development of a protein-protein interaction inhibitor preventing the binding of selected cofactors to p97.

Discovery of a pyrano[2,3-b]pyridine derivative YX-2102 as a cannabinoid receptor 2 agonist for alleviating lung fibrosis

BACKGROUND

Pharmacological modulation of cannabinoid 2 receptor (CB2R) is a promising therapeutic strategy for pulmonary fibrosis (PF). Thus, to develop CB2R selective ligands with new chemical space has attracted much research interests. This work aims to discover a novel CB2R agonist from an in-house library, and to evaluate its therapeutic effects on PF model, as well as to disclose the pharmacological mechanism.

METHODS

Virtual screening was used to identify the candidate ligand for CB2R from a newly established in-house library. Both in vivo experiments on PF rat model and in vitro experiments on cells were performed to investigate the therapeutic effects of the lead compound and underlying mechanism.

RESULTS

A "natural product-like" pyrano[2,3-b]pyridine derivative, YX-2102 was identified that bound to CB2R with high affinity. Intraperitoneal YX-2102 injections significantly ameliorated lung injury, inflammation and fibrosis in a rat model of PF induced by bleomycin (BLM). On one hand, YX-2102 inhibited inflammatory response at least partially through modulating macrophages polarization thereby exerting protective effects. Whereas, on the other hand, YX-2102 significantly upregulated CB2R expression in alveolar epithelial cells in vivo. Its pretreatment inhibited lung alveolar epithelial-to-mesenchymal transition (EMT) in vitro and PF model induced by transforming growth factor beta-1 (TGF-β1) via a CB2 receptor-dependent pathway. Further studies suggested that the Nrf2-Smad7 pathway might be involved in.

CONCLUSION

These findings suggest that CB2R is a potential target for PF treatment and YX-2102 is a promising CB2R agonist with new chemical space.

When interactions between bile salts and cyclodextrin cause a negative food effect: Dynamic dissolution/permeation studies with itraconazole (Sporanox®) and biomimetic media

The marketed oral solution of itraconazole (Sporanox®) contains 40% (259.2 mM) of 2-hydroxypropyl-β-cyclodextrin (HP-β-CD). The obvious role of HP-β-CD is to solubilize itraconazole and to overcome its poor aqueous solubility that restricts its absorption. In this study, we investigated the biorelevance of in vitro experiments by the influence of biomimetic media (containing bile salts and phospholipids) on the predicted itraconazole absorption from the commercial HP-β-CD-based Sporanox® solution. We performed phase-solubility studies of itraconazole and dynamic 2-step-dissolution/permeation studies using a biomimetic artificial barrier, Sporanox® solution, and fasted state simulated intestinal fluid (FaSSIF_V1). Both FaSSIF_V1 and HP-β-CD increased the apparent solubility of itraconazole when used individually. In combination, their solubility-enhancing effects were not additive probably due to the competition of bile salts with itraconazole for the hydrophobic cavity of HP-β-CD. Our combined dissolution/permeation experiments indicated the occurrence of a transient supersaturation from Sporanox® upon two-step dissolution. Through systematic variation of bile salt concentrations in the biomimetic media, it was observed that the extent and the duration of supersaturation depend on the concentrations of bile salts: supersaturation was rather stable in the absence of bile salts and phospholipids. The higher the bile salt concentration, the faster the collapse of the transient supersaturation occurred, an effect which is nicely mirrored by reduced in vitro permeation across the barrier. This is an indication of a negative food effect, which in fact correlates well with what earlier had been observed in clinical studies for Sporanox® solution. In essence, we could demonstrate that in vitro two-stage dissolution/permeation experiments using an artificial barrier and selected biomimetic media may predict the negative effects of the latter on cyclodextrin-based drug formulations like Sporanox® Oral Solution and, at the same time, provide a deeper mechanistic insight.

Carvedilol Precipitation Inhibition by the Incorporation of Polymeric Precipitation Inhibitors Using a Stable Amorphous Solid Dispersion Approach: Formulation, Characterization, and In Vitro In Vivo Evaluation

An amorphous solid dispersion (ASD) of carvedilol (CVL) was prepared via the solvent evaporation method, using cellulose derivatives as polymeric precipitation inhibitors (PPIs). The prepared ASDs existed in the amorphous phase, as revealed by X-ray powder diffraction (XRPD) and scanning electron microscopy (SEM). The Fourier-transform infrared spectroscopy (FT-IR) and differential scanning calorimetry (DSC) results confirmed the compatibility between CVL and the polymers used. The ASDs characteristics were evaluated, with no change in viscosity, a pH of 6.8, a polydispersity index of 0.169, a particle size of 423-450 nm, and a zeta potential of 3.80 mV. Crystal growth inhibition was assessed for 180 min via an infusion precipitation study in simulated intestinal fluid (SIF). The interactions between the drug and polymers were established in great detail, using nuclear magnetic resonance (NMR) spectroscopy, nuclear Overhauser effect spectroscopy (NOESY), and Raman spectroscopy studies. Dielectric analysis was employed to determine the drug-polymer interactions between ion pairs and to understand ion transport behavior. In vivo oral kinetics and irritation studies performed on Wistar rats have demonstrated promising biocompatibility, stability, and the enhanced bioavailability of CVL. Collectively, the stable ASDs of CVL were developed using cellulose polymers as PPIs that would inhibit drug precipitation in the gastrointestinal tract and would aid in achieving higher in vivo drug stability and bioavailability.

Identification of Small Molecules with Improved Potency against Orthopoxviruses from Vaccinia to Smallpox

The genus Orthopoxvirus contains several human pathogens, including vaccinia, monkeypox, cowpox, and variola virus, the causative agent of smallpox. Although there are a few effective vaccines, widespread prophylactic vaccination has ceased and is unlikely to resume, making therapeutics increasingly important to treat poxvirus disease. Here, we described efforts to improve the potency of the anti-poxvirus small molecule CMLDBU6128. This class of small molecules, referred to as pyridopyrimidinones (PDPMs), showed a wide range of biological activities. Through the synthesis and testing of several exploratory chemical libraries based on this molecule, we identified several compounds that had increased potency from the micromolar into the nanomolar range. Two compounds, designated (12) and (16), showed inhibitory concentrations of 326 nM and 101 nM, respectively, which was more than a 10-fold increase in potency to CMLDBU6128 with an inhibitory concentration of around 6 μM. We also expanded our investigation of the breadth of action of these molecules and showed that they can inhibit the replication of variola virus, a related orthopoxvirus. Together, these findings highlighted the promise of this new class of antipoxviral agents as broad-spectrum small molecules with significant potential to be developed as antiviral therapy. This would add a small molecule option for therapy of spreading diseases, including monkeypox and cowpox viruses, that would also be expected to have efficacy against smallpox.

Build-Couple-Transform: A Paradigm for Lead-like Library Synthesis with Scaffold Diversity

High-throughput screening provides one of the most common ways of finding hit compounds. Lead-like libraries, in particular, provide hits with compatible functional groups and vectors for structural elaboration and physical properties suitable for optimization. Library synthesis approaches can lead to a lack of chemical diversity because they employ parallel derivatization of common building blocks using single reaction types. We address this problem through a "build-couple-transform" paradigm for the generation of lead-like libraries with scaffold diversity. Nineteen transformations of a 4-oxo-2-butenamide scaffold template were optimized, including 1,4-cyclizations, 3,4-cyclizations, reductions, and 1,4-additions. A pool-transformation approach efficiently explored the scope of these transformations for nine different building blocks and synthesized a >170-member library with enhanced chemical space coverage and favorable drug-like properties. Screening revealed hits against CDK2. This work establishes the build-couple-transform concept for the synthesis of lead-like libraries and provides a differentiated approach to libraries with significantly enhanced scaffold diversity.