Identifying patient subgroups in MASLD and MASH-associated fibrosis: molecular profiles and implications for drug development.

The incidence of MASLD and MASH-associated fibrosis is rapidly increasing worldwide. Drug therapy is hampered by large patient variability and partial representation of human MASH fibrosis in preclinical models. Here, we investigated the mechanisms underlying patient heterogeneity using a discovery dataset and validated in distinct human transcriptomic datasets, to improve patient stratification and translation into subgroup specific patterns. Patient stratification was performed using weighted gene co-expression network analysis (WGCNA) in a large public transcriptomic discovery dataset (n = 216). Differential expression analysis was performed using DESeq2 to obtain differentially expressed genes (DEGs). Ingenuity Pathway analysis was used for functional annotation. The discovery dataset showed relevant fibrosis-related mechanisms representative of disease heterogeneity. Biological complexity embedded in genes signature was used to stratify discovery dataset into six subgroups of various sizes. Of note, subgroup-specific DEGs show differences in directionality in canonical pathways (e.g. Collagen biosynthesis, cytokine signaling) across subgroups. Finally, a multiclass classification model was trained and validated in two datasets. In summary, our work shows a potential alternative for patient population stratification based on heterogeneity in MASLD-MASH mechanisms. Future research is warranted to further characterize patient subgroups and identify protein targets for virtual screening and/or in vitro validation in preclinical models.

The Effect of Cancer-Associated Mutations on Ligand Binding and Receptor Function - A Case for the 5-HT2C Receptor.

The serotonin 5-HT2C receptor is a G protein-coupled receptor (GPCR) mainly expressed in the central nervous system. Besides regulating mood, appetite, and reproductive behavior, it has been identified as a potential target for cancer treatment. In this study, we aimed to investigate the effects of cancer patient-derived 5-HT2C receptor mutations on ligand binding and receptor functionality. By filtering the sequencing data from the Genomic Data Commons data portal (GDC), we selected 12 mutations from multiple cancer types. We found that the affinity of the endogenous agonist serotonin (5-HT) and inverse agonist mesulergine were both drastically decreased by mutations L209HECL2 and F328S6.52, which are located in the orthosteric binding pocket. In the calcium-flux assay, the potency of 5-HT was decreased at F328S6.52, while a trend of increased efficacy was observed. In contrast, 5-HT displayed higher affinity at E306K6.30 and E306A6.30, while a trend of decreased efficacy was observed. These two mutations may disrupt the conserved ionic interaction between E6.30 and R3.50, and thus increase the constitutive activity of the receptor. The inhibitory potency of mesulergine was increased at E306A6.30 but not E306K6.30. Lastly, P365H7.50 decreased the expression level of the receptor by more than ten-fold, which prevented further functional analyses. This study shows that cancer-associated mutations of 5-HT2C receptor have diverse effects on ligand binding and function. Such mutations may affect serotonin-mediated signaling in tumor cells as well as treatment strategies targeting this receptor.

AlphaFold Meets De Novo Drug Design: Leveraging Structural Protein Information in Multitarget Molecular Generative Models.

Recent advancements in deep learning and generative models have significantly expanded the applications of virtual screening for drug-like compounds. Here, we introduce a multitarget transformer model, PCMol, that leverages the latent protein embeddings derived from AlphaFold2 as a means of conditioning a de novo generative model on different targets. Incorporating rich protein representations allows the model to capture their structural relationships, enabling the chemical space interpolation of active compounds and target-side generalization to new proteins based on embedding similarities. In this work, we benchmark against other existing target-conditioned transformer models to illustrate the validity of using AlphaFold protein representations over raw amino acid sequences. We show that low-dimensional projections of these protein embeddings cluster appropriately based on target families and that model performance declines when these representations are intentionally corrupted. We also show that the PCMol model generates diverse, potentially active molecules for a wide array of proteins, including those with sparse ligand bioactivity data. The generated compounds display higher similarity known active ligands of held-out targets and have comparable molecular docking scores while maintaining novelty. Additionally, we demonstrate the important role of data augmentation in bolstering the performance of generative models in low-data regimes. Software package and AlphaFold protein embeddings are freely available at https://github.com/CDDLeiden/PCMol.

Stereochemical optimization of N,2-substituted cycloalkylamines as norepinephrine reuptake inhibitors.

The norepinephrine transporter (NET), encoded by the SLC6A2 gene, is one of three key monoamine neurotransmitter transporters. Inhibition of NET-mediated reuptake of norepinephrine by monoamine reuptake inhibitors has been the main therapeutic strategy to treat disorders such as depression, ADHD and Parkinson's disease. Nevertheless, lack of efficacy as well as risk of adverse effects are still common for these treatments underscoring the necessity to improve drug discovery efforts for this target. In this study, we developed new inhibitors based on 4-((2-(3,4-dichlorophenyl)cyclopentyl)amino)butan-1-ol (8), a potent NET inhibitor, which emerged from earlier virtual screening efforts using a predictive proteochemometric model. Hence, we optimized the N,2-substituted cycloalkylamine scaffold in three regions to design twenty new derivatives. To establish structure-activity relationships for these NET inhibitors, all novel compounds were tested utilizing an impedance-based 'transporter activity through receptor activation' assay. Moreover, all stereoisomers of the most potent compound (27) were synthesized and evaluated for their inhibitory potencies. Initial screening indicated that modifications in the cyclopentylamine moiety and phenyl substitutions decreased NET inhibition compared to 8, emphasizing the importance of the five-membered ring, secondary amine and dichloro-substitution pattern in NET binding. Substituting the original butylalcohol at the R 2 position with a rigid cyclohexanol yielded lead compound 27, with potency similar to reference inhibitor nisoxetine. Pharmacological characterization of all eight stereoisomers of 27 revealed varying inhibitory potencies, favoring a trans-orientation of the N,2-substituted cyclopentyl moiety. Molecular docking highlighted key interactions and the impact of a hydrophilic region in the binding pocket. This study presents a novel set of moderate to highly potent NET inhibitors, elucidating the influence of molecular orientation in the NET binding pocket and offering valuable insights into drug discovery efforts for monoamine transport-related treatments.

CC chemokine receptor 2 is allosterically modulated by sodium ions and amiloride derivatives through a distinct sodium ion binding site.

CC chemokine receptor 2 and CCL2 are highly involved in cancer growth and metastasis, and immune escape. Raised sodium ion concentrations in solid tumours have also been correlated to metastasis and immune modulation. Sodium ions can modulate class A G protein-coupled receptors through the sodium ion binding site characterized by a highly conserved aspartic acid residue (D2.50), also present in CCR2. Hence, we further explored this binding site in CCR2 by radioligand binding studies and mutagenesis. Modulation of three distinctly binding radioligands by sodium ions and amiloride derivates was investigated. Sodium ions were observed to be relatively weak modulators of antagonist binding, but substantially increased 125I-CCL2 dissociation from CCR2. 6-Substituted Hexamethylene Amiloride (HMA) modulated all tested radioligands. Induced-fit docking of HMA in the presumed sodium ion binding site of CCR2 confirmed its binding site. Finally, investigation of (cancer-associated) mutations in the sodium ion binding site showed a markedly decreased expression compared to wild type. Only two mutants, G123A3.35 and G127K3.39, were able to be bound by [3H]INCB3344 and [3H]CCR2-RA-[R]. Thus, mutagenesis showed that the sodium ion binding site residues, which are distinct from other class A GPCRs and related to chemokine receptor evolution, are crucial for receptor integrity. Moreover, the tested mutations appeared to have no effect on modulation observed by HMA or a minor effect on sodium chloride modulation on the tested radioligands. All in all, these results invite further exploration of the CCR2 sodium ion binding site in (cancer) biology, and potentially as a third druggable binding site.

'Folfirinox' chemotherapy combined with contact x-ray brachytherapy 50kVp and 'CAP50' chemoradiotherapy aiming at organ preservation for selected intermediate distal-middle cT2-T3 rectal cancers: A feasibility study.

PURPOSE: The standard treatment of T2-T3 rectal adenocarcinoma is radical proctectomy by total mesorectal excision often combined with some neoadjuvant treatment. To reduce morbidity of this surgery, organ preservation strategy using various combination of radiotherapy, chemotherapy and local excision is gaining interest. Some randomized trials have proven the feasibility of such approaches. The OPERA trial demonstrated, for T2 T3<5cm diameter low-middle rectum, that a contact X-ray brachytherapy boost of 90Gy in three fractions over 4 weeks was able to achieve a planned organ preservation in 81% of patients at 3years with 97% success for tumour smaller than 3cm treated with contact X-ray brachytherapy boost first. To try to expand organ preservation to larger tumours we set up a feasibility trial in T2-T3 tumours using total neoadjuvant treatment and a contact X-ray brachytherapy boost. MATERIAL AND METHOD: The trial was approved by the institutional review board of Nice. Inclusion criteria were operable patients, 75years or less, adenocarcinoma of the low-middle rectum staged T2c-T3N0 larger than 3.5cm and less than 6cm in diameter or T2-T3N1 less than 6cm in diameter. Treatment started in all cases with neoadjuvant chemotherapy associating 5-fluoro-uracile, irinotecan and oxaliplatin ('folfirinox' regimen, four to six cycles). In case of good tumour response after four cycles, a contact X-ray brachytherapy boost (delivering 90Gy in three fractions) was given followed by chemoradiotherapy (external beam radiotherapy delivering 50Gy, with concurrent capecitabine). After six cycles if only a partial response (tumour still larger than 3cm) was seen, chemoradiotherapy was given and contact X-ray brachytherapy boost was delivered after that. At the end of this total neoadjuvant treatment a watch and wait strategy was decided in case of clinical complete response or radical proctectomy by total mesorectal excision for partial response. RESULTS: Between July 2019 and October 2022, 14 patients were included; median age was 66years (range: 51-77years), there were nine male and five female, two T2 N1 tumours, seven T3N0, and five T3N1, all were M0. Median tumour diameter was 40mm (range: 11-50mm); three tumours had a circumferential extension greater than 50%. Seven patients received four folfirinox cycles and seven had six cycles. Contact X-ray brachytherapy boost was given during folfirinox chemotherapy before chemoradiotherapy in 11 patients (and after in three). The tolerance was good, with no grade 4-5 toxicity. The main grade 3 early toxicity was in relation with the folfirinox regimen. A clinical complete response was seen in 12 patients at the end of the total neoadjuvant treatment (85%). All these patients are alive and have preserved their rectum with a mean follow-up time of 17.8months (range: 6-48months) and a good bowel function (low anterior rectal resection syndrome score below 30). The main contact X-ray brachytherapy boost toxicity was radiation ulceration in three patients that usually healed within 6 months, sometimes necessitating hyperbaric oxygen. CONCLUSION: The preliminary results of this feasibility study show that early tolerance of these intensive total neoadjuvant treatment is compatible with an acceptable toxicity. The high rate of organ preservation in this intermediate group of T2-T3 tumours is encouraging and is a good argument to start the next randomized TRESOR trial that will aim at achieving a 65% of 3-year survival with organ preservation in this intermediate tumour group.

Exploring novel dilazep derivatives as hENT1 inhibitors and potentially covalent molecular tools.

The human equilibrative nucleoside transporter 1 (SLC29A1, hENT1) is a solute carrier that modulates the passive transport of nucleosides and nucleobases, such as adenosine. This nucleoside regulates various physiological processes, such as vasodilation and -constriction, neurotransmission and immune defense. Marketed drugs such as dilazep and dipyridamole have proven useful in cardiovascular afflictions, but the application of hENT1 inhibitors can be beneficial in a number of other diseases. In this study, 39 derivatives of dilazep's close analogue ST7092 were designed, synthesized and subsequently assessed using [3H]NBTI displacement assays and molecular docking. Different substitution patterns of the trimethoxy benzoates of ST7092 reduced interactions within the binding pocket, resulting in diminished hENT1 affinity. Conversely, [3H]NBTI displacement by potentially covalent compounds 14b, 14c, and 14d resulted in high affinities (Ki values between 1.1 and 17.5 nM) for the transporter, primarily by the ability of accommodating the inhibitors in various ways in the binding pocket. However, any indication of covalent binding with amino acid residue C439 remained absent, conceivably as a result of decreased nucleophilic residue reactivity. In conclusion, this research introduces novel dilazep derivatives that are active as hENT1 inhibitors, along with the first high affinity dilazep derivatives equipped with an electrophilic warhead. These findings will aid the rational and structure-based development of novel hENT1 inhibitors and pharmacological tools to study hENT1's function, binding mechanisms, and its relevance in (patho)physiological conditions.

N-Acyl-N-Alkyl Sulfonamide Probes for Ligand-Directed Covalent Labeling of GPCRs: The Adenosine A2B Receptor as Case Study.

Small molecular tool compounds play an essential role in the study of G protein-coupled receptors (GPCRs). However, tool compounds most often occupy the orthosteric binding site, hampering the study of GPCRs upon ligand binding. To overcome this problem, ligand-directed labeling techniques have been developed that leave a reporter group covalently bound to the GPCR, while allowing subsequent orthosteric ligands to bind. In this work, we applied such a labeling strategy to the adenosine A2B receptor (A2BAR). We have synthetically implemented the recently reported N-acyl-N-alkyl sulfonamide (NASA) warhead into a previously developed ligand and show that the binding of the A2BAR is not restricted by NASA incorporation. Furthermore, we have investigated ligand-directed labeling of the A2BAR using SDS-PAGE, flow cytometric, and mass spectrometry techniques. We have found one of the synthesized probes to specifically label the A2BAR, although detection was hindered by nonspecific protein labeling most likely due to the intrinsic reactivity of the NASA warhead. Altogether, this work aids the future development of ligand-directed probes for the detection of GPCRs.

Laparoscopic Versus Open Hemihepatectomy: The ORANGE II PLUS Multicenter Randomized Controlled Trial.

PURPOSE: To compare outcomes after laparoscopic versus open major liver resection (hemihepatectomy) mainly for primary or metastatic cancer. The primary outcome measure was time to functional recovery. Secondary outcomes included morbidity, quality of life (QoL), and for those with cancer, resection margin status and time to adjuvant systemic therapy. PATIENTS AND METHODS: This was a multicenter, randomized controlled, patient-blinded, superiority trial on adult patients undergoing hemihepatectomy. Patients were recruited from 16 hospitals in Europe between November 2013 and December 2018. RESULTS: Of the 352 randomly assigned patients, 332 patients (94.3%) underwent surgery (laparoscopic, n = 166 and open, n = 166) and comprised the analysis population. The median time to functional recovery was 4 days (IQR, 3-5; range, 1-30) for laparoscopic hemihepatectomy versus 5 days (IQR, 4-6; range, 1-33) for open hemihepatectomy (difference, -17.5% [96% CI, -25.6 to -8.4]; P < .001). There was no difference in major complications (laparoscopic 24/166 [14.5%] v open 28/166 [16.9%]; odds ratio [OR], 0.84; P = .58). Regarding QoL, both global health status (difference, 3.2 points; P < .001) and body image (difference, 0.9 points; P < .001) scored significantly higher in the laparoscopic group. For the 281 (84.6%) patients with cancer, R0 resection margin status was similar (laparoscopic 106 [77.9%] v open 122 patients [84.1%], OR, 0.60; P = .14) with a shorter time to adjuvant systemic therapy in the laparoscopic group (46.5 days v 62.8 days, hazard ratio, 2.20; P = .009). CONCLUSION: Among patients undergoing hemihepatectomy, the laparoscopic approach resulted in a shorter time to functional recovery compared with open surgery. In addition, it was associated with a better QoL, and in patients with cancer, a shorter time to adjuvant systemic therapy with no adverse impact on cancer outcomes observed.

Computational Characterization of Membrane Proteins as Anticancer Targets: Current Challenges and Opportunities.

Cancer remains a leading cause of mortality worldwide and calls for novel therapeutic targets. Membrane proteins are key players in various cancer types but present unique challenges compared to soluble proteins. The advent of computational drug discovery tools offers a promising approach to address these challenges, allowing for the prioritization of "wet-lab" experiments. In this review, we explore the applications of computational approaches in membrane protein oncological characterization, particularly focusing on three prominent membrane protein families: receptor tyrosine kinases (RTKs), G protein-coupled receptors (GPCRs), and solute carrier proteins (SLCs). We chose these families due to their varying levels of understanding and research data availability, which leads to distinct challenges and opportunities for computational analysis. We discuss the utilization of multi-omics data, machine learning, and structure-based methods to investigate aberrant protein functionalities associated with cancer progression within each family. Moreover, we highlight the importance of considering the broader cellular context and, in particular, cross-talk between proteins. Despite existing challenges, computational tools hold promise in dissecting membrane protein dysregulation in cancer. With advancing computational capabilities and data resources, these tools are poised to play a pivotal role in identifying and prioritizing membrane proteins as personalized anticancer targets.

Still in Search for an EAAT Activator: GT949 Does Not Activate EAAT2, nor EAAT3 in Impedance and Radioligand Uptake Assays.

Excitatory amino acid transporters (EAATs) are important regulators of amino acid transport and in particular glutamate. Recently, more interest has arisen in these transporters in the context of neurodegenerative diseases. This calls for ways to modulate these targets to drive glutamate transport, EAAT2 and EAAT3 in particular. Several inhibitors (competitive and noncompetitive) exist to block glutamate transport; however, activators remain scarce. Recently, GT949 was proposed as a selective activator of EAAT2, as tested in a radioligand uptake assay. In the presented research, we aimed to validate the use of GT949 to activate EAAT2-driven glutamate transport by applying an innovative, impedance-based, whole-cell assay (xCELLigence). A broad range of GT949 concentrations in a variety of cellular environments were tested in this assay. As expected, no activation of EAAT3 could be detected. Yet, surprisingly, no biological activation of GT949 on EAAT2 could be observed in this assay either. To validate whether the impedance-based assay was not suited to pick up increased glutamate uptake or if the compound might not induce activation in this setup, we performed radioligand uptake assays. Two setups were utilized; a novel method compared to previously published research, and in a reproducible fashion copying the methods used in the existing literature. Nonetheless, activation of neither EAAT2 nor EAAT3 could be observed in these assays. Furthermore, no evidence of GT949 binding or stabilization of purified EAAT2 could be observed in a thermal shift assay. To conclude, based on experimental evidence in the present study GT949 requires specific assay conditions, which are difficult to reproduce, and the compound cannot simply be classified as an activator of EAAT2 based on the presented evidence. Hence, further research is required to develop the tools needed to identify new EAAT modulators and use their potential as a therapeutic target.

Cluster Randomized Trials with a Pretest and Posttest: Equivalence of Three-, Two- and One-Level Analyses, and Sample Size Calculation.

In a cluster randomized trial clusters of persons, for instance, schools or health centers, are assigned to treatments, and all persons in the same cluster get the same treatment. Although less powerful than individual randomization, cluster randomization is a good alternative if individual randomization is impossible or leads to severe treatment contamination (carry-over). Focusing on cluster randomized trials with a pretest and post-test of a quantitative outcome, this paper shows the equivalence of four methods of analysis: a three-level mixed (multilevel) regression for repeated measures with as levels cluster, person, and time, and allowing for unstructured between-cluster and within-cluster covariance matrices; a two-level mixed regression with as levels cluster and person, using change from baseline as outcome; a two-level mixed regression with as levels cluster and time, using cluster means as data; a one-level analysis of cluster means of change from baseline. Subsequently, similar equivalences are shown between a constrained mixed model and methods using the pretest as covariate. All methods are also compared on a cluster randomized trial on mental health in children. From these equivalences follows a simple method to calculate the sample size for a cluster randomized trial with baseline measurement, which is demonstrated step-by-step.

Molecular insights into disease-associated glutamate transporter (EAAT1 / SLC1A3) variants using in silico and in vitro approaches.

Glutamate is an essential excitatory neurotransmitter and an intermediate for energy metabolism. Depending on the tumor site, cancer cells have increased or decreased expression of excitatory amino acid transporter 1 or 2 (EAAT1/2, SLC1A3/2) to regulate glutamate uptake for the benefit of tumor growth. Thus, EAAT1/2 may be an attractive target for therapeutic intervention in oncology. Genetic variation of EAAT1 has been associated with rare cases of episodic ataxia, but the occurrence and functional contribution of EAAT1 mutants in other diseases, such as cancer, is poorly understood. Here, 105 unique somatic EAAT1 mutations were identified in cancer patients from the Genomic Data Commons dataset. Using EAAT1 crystal structures and in silico studies, eight mutations were selected based on their close proximity to the orthosteric or allosteric ligand binding sites and the predicted change in ligand binding affinity. In vitro functional assessment in a live-cell, impedance-based phenotypic assay demonstrated that these mutants differentially affect L-glutamate and L-aspartate transport, as well as the inhibitory potency of an orthosteric (TFB-TBOA) and allosteric (UCPH-101) inhibitor. Moreover, two episodic ataxia-related mutants displayed functional responses that were in line with literature, which confirmed the validity of our assay. Of note, ataxia-related mutant M128R displayed inhibitor-induced functional responses never described before. Finally, molecular dynamics (MD) simulations were performed to gain mechanistic insights into the observed functional effects. Taken together, the results in this work demonstrate 1) the suitability of the label-free phenotypic method to assess functional variation of EAAT1 mutants and 2) the opportunity and challenges of using in silico techniques to rationalize the in vitro phenotype of disease-relevant mutants.

Development of an Affinity-Based Probe to Profile Endogenous Human Adenosine A3 Receptor Expression.

The adenosine A3 receptor (A3AR) is a G protein-coupled receptor (GPCR) that exerts immunomodulatory effects in pathophysiological conditions such as inflammation and cancer. Thus far, studies toward the downstream effects of A3AR activation have yielded contradictory results, thereby motivating the need for further investigations. Various chemical and biological tools have been developed for this purpose, ranging from fluorescent ligands to antibodies. Nevertheless, these probes are limited by their reversible mode of binding, relatively large size, and often low specificity. Therefore, in this work, we have developed a clickable and covalent affinity-based probe (AfBP) to target the human A3AR. Herein, we show validation of the synthesized AfBP in radioligand displacement, SDS-PAGE, and confocal microscopy experiments as well as utilization of the AfBP for the detection of endogenous A3AR expression in flow cytometry experiments. Ultimately, this AfBP will aid future studies toward the expression and function of the A3AR in pathologies.

Collaborative SAR Modeling and Prospective In Vitro Validation of Oxidative Stress Activation in Human HepG2 Cells.

Oxidative stress is the consequence of an abnormal increase of reactive oxygen species (ROS). ROS are generated mainly during the metabolism in both normal and pathological conditions as well as from exposure to xenobiotics. Xenobiotics can, on the one hand, disrupt molecular machinery involved in redox processes and, on the other hand, reduce the effectiveness of the antioxidant activity. Such dysregulation may lead to oxidative damage when combined with oxidative stress overpassing the cell capacity to detoxify ROS. In this work, a green fluorescent protein (GFP)-tagged nuclear factor erythroid 2-related factor 2 (NRF2)-regulated sulfiredoxin reporter (Srxn1-GFP) was used to measure the antioxidant response of HepG2 cells to a large series of drug and drug-like compounds (2230 compounds). These compounds were then classified as positive or negative depending on cellular response and distributed among different modeling groups to establish structure-activity relationship (SAR) models. A selection of models was used to prospectively predict oxidative stress induced by a new set of compounds subsequently experimentally tested to validate the model predictions. Altogether, this exercise exemplifies the different challenges of developing SAR models of a phenotypic cellular readout, model combination, chemical space selection, and results interpretation.

3DDPDs: describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors.

Proteochemometric (PCM) modelling is a powerful computational drug discovery tool used in bioactivity prediction of potential drug candidates relying on both chemical and protein information. In PCM features are computed to describe small molecules and proteins, which directly impact the quality of the predictive models. State-of-the-art protein descriptors, however, are calculated from the protein sequence and neglect the dynamic nature of proteins. This dynamic nature can be computationally simulated with molecular dynamics (MD). Here, novel 3D dynamic protein descriptors (3DDPDs) were designed to be applied in bioactivity prediction tasks with PCM models. As a test case, publicly available G protein-coupled receptor (GPCR) MD data from GPCRmd was used. GPCRs are membrane-bound proteins, which are activated by hormones and neurotransmitters, and constitute an important target family for drug discovery. GPCRs exist in different conformational states that allow the transmission of diverse signals and that can be modified by ligand interactions, among other factors. To translate the MD-encoded protein dynamics two types of 3DDPDs were considered: one-hot encoded residue-specific (rs) and embedding-like protein-specific (ps) 3DDPDs. The descriptors were developed by calculating distributions of trajectory coordinates and partial charges, applying dimensionality reduction, and subsequently condensing them into vectors per residue or protein, respectively. 3DDPDs were benchmarked on several PCM tasks against state-of-the-art non-dynamic protein descriptors. Our rs- and ps3DDPDs outperformed non-dynamic descriptors in regression tasks using a temporal split and showed comparable performance with a random split and in all classification tasks. Combinations of non-dynamic descriptors with 3DDPDs did not result in increased performance. Finally, the power of 3DDPDs to capture dynamic fluctuations in mutant GPCRs was explored. The results presented here show the potential of including protein dynamic information on machine learning tasks, specifically bioactivity prediction, and open opportunities for applications in drug discovery, including oncology.

Preclinical evaluation of EpCAM-binding designed ankyrin repeat proteins (DARPins) as targeting moieties for bimodal near-infrared fluorescence and photoacoustic imaging of cancer.

PURPOSE: Fluorescence-guided surgery (FGS) can play a key role in improving radical resection rates by assisting surgeons to gain adequate visualization of malignant tissue intraoperatively. Designed ankyrin repeat proteins (DARPins) possess optimal pharmacokinetic and other properties for in vivo imaging. This study aims to evaluate the preclinical potential of epithelial cell adhesion molecule (EpCAM)-binding DARPins as targeting moieties for near-infrared fluorescence (NIRF) and photoacoustic (PA) imaging of cancer. METHODS: EpCAM-binding DARPins Ac2, Ec4.1, and non-binding control DARPin Off7 were conjugated to IRDye 800CW and their binding efficacy was evaluated on EpCAM-positive HT-29 and EpCAM-negative COLO-320 human colon cancer cell lines. Thereafter, NIRF and PA imaging of all three conjugates were performed in HT-29_luc2 tumor-bearing mice. At 24 h post-injection, tumors and organs were resected and tracer biodistributions were analyzed. RESULTS: Ac2-800CW and Ec4.1-800CW specifically bound to HT-29 cells, but not to COLO-320 cells. Next, 6 nmol and 24 h were established as the optimal in vivo dose and imaging time point for both DARPin tracers. At 24 h post-injection, mean tumor-to-background ratios of 2.60 ± 0.3 and 3.1 ± 0.3 were observed for Ac2-800CW and Ec4.1-800CW, respectively, allowing clear tumor delineation using the clinical Artemis NIRF imager. Biodistribution analyses in non-neoplastic tissue solely showed high fluorescence signal in the liver and kidney, which reflects the clearance of the DARPin tracers. CONCLUSION: Our encouraging results show that EpCAM-binding DARPins are a promising class of targeting moieties for pan-carcinoma targeting, providing clear tumor delineation at 24 h post-injection. The work described provides the preclinical foundation for DARPin-based bimodal NIRF/PA imaging of cancer.

DrugEx: Deep Learning Models and Tools for Exploration of Drug-Like Chemical Space.

The discovery of novel molecules with desirable properties is a classic challenge in medicinal chemistry. With the recent advancements of machine learning, there has been a surge of de novo drug design tools. However, few resources exist that are user-friendly as well as easily customizable. In this application note, we present the new versatile open-source software package DrugEx for multiobjective reinforcement learning. This package contains the consolidated and redesigned scripts from the prior DrugEx papers including multiple generator architectures, a variety of scoring tools, and multiobjective optimization methods. It has a flexible application programming interface and can readily be used via the command line interface or the graphical user interface GenUI. The DrugEx package is publicly available at https://github.com/CDDLeiden/DrugEx.