Drug Discovery Platform Research Articles

MolProphet: A One-Stop, General Purpose, and AI-Based Platform for the Early Stages of Drug Discovery.

Artificial intelligence (AI) is an effective tool to accelerate drug discovery and cut costs in discovery processes. Many successful AI applications are reported in the early stages of small molecule drug discovery. However, most of those applications require a deep understanding of software and hardware, and focus on a single field that implies data normalization and transfer between those applications is still a challenge for normal users. It usually limits the application of AI in drug discovery. Here, based on a series of robust models, we formed a one-stop, general purpose, and AI-based drug discovery platform, MolProphet, to provide complete functionalities in the early stages of small molecule drug discovery, including AI-based target pocket prediction, hit discovery and lead optimization, and compound targeting, as well as abundant analyzing tools to check the results. MolProphet is an accessible and user-friendly web-based platform that is fully designed according to the practices in the drug discovery industry. The molecule screened, generated, or optimized by the MolProphet is purchasable and synthesizable at low cost but with good drug-likeness. More than 400 users from industry and academia have used MolProphet in their work. We hope this platform can provide a powerful solution to assist each normal researcher in drug design and related research areas. It is available for everyone at https://www.molprophet.com/.

Abstract 6918: Ba/F3-BCR-ABL engineering cell line panel, a useful platform for novel drug discovery

Abstract In the past few years, with the great success of Imatinib, the first kinase inhibitor, Imatinib rapidly became the first-line treatment for CML (Chronic myelogenous leukemia) carrying the BCR-ABL mutation. It opened a new chapter in targeted cancer treatment. Despite the increase in overall survival allowed by imatinib, the onset of drug resistance led scientists to investigate imatinib's fine structural mechanism of action to develop new and more effective compounds against mutated forms of Bcr-Abl. 7 BCR-ABL inhibitors have been approved, they are Imatinib, Dasatinib, Nilotinib, Bosutinib, Ponatinib, Olverembatinib, and Asciminib. However, acquired resistance has been a major challenge in the treatment of CML, and some patients still experience disease progression or even death due to drug resistance. BCR-ABL kinase domain mutations are one of the important mechanisms of acquired resistance, with the T315I mutation being the most common type of drug resistance mutation, accounting for approximately 25% of drug-resistant CML cases. Patients with T315I mutations in CML are resistant to all current first- and second-generation BCR-ABL inhibitors. Asciminib is designed as an allosteric inhibitor combined with an ATP-competitive TKI agent, which may hinder the development of mutation-driven acquired resistance or restore efficacy against highly resistant BCR-ABL mutants. Our group has generated 38 Ba/F3-BCR-ABL engineering cell lines as useful models for novel drug discovery in vitro and in vivo, including wild-type BCR-ABL and inhibitors leading drug resistance mutations, such as T315I, E255, Y253, F317, F359. V299, G250, A337T, V468F, and double mutations. Each cell was validated by cell sequencing and cell efficacy verification using approved BCR-ABL inhibitors. The Ba/F3-BCR-ABL engineering cell line panel can be useful for developing and evaluating next-generation BCR-ABL inhibitors and exploring newly acquired resistance mutations in BCR-ABL. Citation Format: Guoqian Wang, Yao Peng, Yu Wang, Yao Tang, Jingxiao Xu, Jinying Ning, Feng Hao. Ba/F3-BCR-ABL engineering cell line panel, a useful platform for novel drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6918.

Abstract 6917: Ba/F3 AKT engineering cell lines, a useful platform for novel drug discovery

Abstract AKT, also known as phosphoinositide 3-kinase (PI3K), plays a key role in various signaling cascades involved in cell growth and division, apoptosis inhibition, and angiogenesis. For AKT, which is at the central node of the PI3K/AKT/mTOR signaling pathway, the loss of PTEN, mutation, or amplification of AKT/PIK3CA can lead to the overactivation of the AKT signaling pathway, resulting in the occurrence and development of tumors. Recent studies have also found that AKT activation is associated with drug resistance in tumor therapy. Therefore, AKT has become a hot target for tumor therapy. The AKT family consists of three highly homologous isoforms, AKT1 (PKBα), AKT2 (PKBβ), and AKT3 (PKBγ), with more than 85% homology in their kinase regions. E17K is the most common and well-characterized activating mutation, accounting for approximately 15% of all AKT mutations. Rare mutations mainly include L52R, Q79K, and D323H. The failures of AKT inhibitors LY2780301 and Bayer's BAY1125976 demonstrate the significant challenges and complexities in developing inhibitors of the AKT pathway. Currently, the most advanced AKT inhibitor globally is AstraZeneca's capivasertib, which is primarily indicated for HR+ breast cancer and triple-negative breast cancer. Our group has generated 21 Ba/F3-AKT engineering cell lines, as useful models for novel drug discovery in vitro and in vivo, almost all clinically significant mutations were included, such as common mutations AKT1/2-E17K as well as rare mutations L52R, Q79K, D323H, and others. The Ba/F3-AKT engineering cell lines can be useful for developing and evaluating next-generation AKT inhibitors and exploring newly acquired resistance mutations in AKT. Citation Format: Guoqian Wang, Yao Tang, Jingxiao Xu, Yao Peng, Yu Wang, Jingying Ning, Feng Hao. Ba/F3 AKT engineering cell lines, a useful platform for novel drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6917.

Abstract 6768: Matched XPDX™derivative models as a platform for continuity across preclinical drug development

Abstract Drug discovery is a reductive process in which druglike entities are carried through increasingly complex assay formats to tease out the compounds best suited for human studies. In vivo efficacy remains the benchmark for successful preclinical drug development. Cell-based models are a mainstay in early stages but translatability of different models across platforms remains a challenge. In oncology, patient-derived xenografts (PDX) are the gold standard for animal studies because they recapitulate key features of human tumors including the cellular heterogeneity, growth patterns, and drug response of the original patient tumor. Ex vivo, PDX derivatives have the potential to harness these same traits thereby extending the utility of PDX models to earlier stages of preclinical drug development. The KIYA-Predict™ platform is a clinically validated tool for the assessment of ex vivo drug responses across a broad range of drug classes that when applied to XPDX models shows good correlation to in vivo drug responses and excellent intra-sample reproducibility over time. Working with the well-characterized XenoSTART™ XPDX model repository, Kiyatec has derived 2D cell lines and organotypic 3D-expansion cultures to complement the ex vivo predictive value of our KIYA-PREDICT™ XPDX drug response profiling (DRP) platform. The development of syngeneic models applicable to simpler, high-throughput library screening (2D formats) and lower-throughput more complex mechanistic studies (3D organotypic models) could alleviate the burden and pitfalls of extrapolating data across unrelated models. Matched sets of 2D cell lines (2D-XPDX™) and 3D organotypic (XPDXO™) cultures were established from single cell suspensions of digested, mouse-cell depleted XPDX™ tissue samples. Drug response profiling of the XPDX™ in their various ex vivo culture formats showed relative similarities across platforms. Genomic profiling of the derivates confirmed shared tissue origin and retention of genomic and phenotypic signatures to varying degrees across models. Mechanistic evaluation of 3D organotypic culture demonstrated that disease-relevant biomarkers and processes are maintained. Together these results demonstrate the feasibility of this novel drug discovery platform that avoids ambiguity imparted by discordant models. Citation Format: Melissa Millard, Aaron Carlson, Danielle Y. Nadeau, Kimberly J. Burgess, Alyssa Simonson, Armando Diaz, Michael Wick, Teresa DesRochers. Matched XPDX™derivative models as a platform for continuity across preclinical drug development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6768.

Abstract 6025: Discovery of novel macrocyclic peptide radioligands for tumor therapy by mRNA display

Abstract Radioligand therapeutics (RLT) aim to selectively deliver radioisotopes to cancer tissues to eradicate tumor cells while limiting the damage to surrounding tissues. They are composed of a tumor-targeting ligand and a radioactive payload. The therapeutic potential of RLT strongly depends on their biostability and residence time in tumor and healthy tissue after injection. Macrocyclic peptides are effective tumor-targeting ligands because their size and molecular characteristics confer optimal pharmacologic properties that can be fine-tuned during the development process. mRNA display is a powerful platform for macrocyclic peptide drug discovery that identifies high affinity peptide ligands through in vitro selection. Here, we describe the selection and initial characterization of macrocyclic peptides discovered by mRNA display that bind to the extracellular domain of a tumor target. Enrichment of the library for peptides that bound to the recombinant target protein was observed after four rounds of selection with no further enrichment in round five. The library of round 5 was sequenced by Illumina sequencing and the top 1,000 sequences (highest counts) were used to perform cluster analysis. We tested the top sequences of 43 different clusters in in vitro translation binding assays to validate the selection output and identify sequences for hit confirmation. Most of the sequences tested showed clear binding to the target protein and only a few peptides showed binding to a closely related protein from the same protein family. No non-specific binding of the discovered peptides to an irrelevant protein was observed showing the high specificity of the generated library. From this confirmatory selection data, we chose a subset of peptides for chemical synthesis. Binding affinity measurements were determined by surface plasmon resonance (SPR) and cellular binding of selected candidates to target-positive and -negative tumor cells was analyzed by flow cytometry. From this hit confirmation data, in vitro internalization and in vitro anti-tumor efficacy of radiolabeled peptide candidates for RLT are assessed. Our data highlights the potential of mRNA display platforms for fast and efficient discovery of highly specific macrocyclic peptides with optimal binding properties suitable for RLT. Citation Format: Anika Jaekel, Kathryn Sherry, Prachi Desai, David Fox, Tang Guo-Qing, Manuel Sturzbecher-Hoehne, Dennis Mewis, Kaori Noridomi, Liam Rayman, Ping Ye. Discovery of novel macrocyclic peptide radioligands for tumor therapy by mRNA display [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6025.

Rapid altitude displacement induce zebrafish appearing acute high altitude illness symptoms

Rapid ascent to high-altitude areas above 2500 m often leads to acute high altitude illness (AHAI), posing significant health risks. Current models for AHAI research are limited in their ability to accurately simulate the high-altitude environment for drug screening. Addressing this gap, a novel static self-assembled water vacuum transparent chamber was developed to induce AHAI in zebrafish. This study identified 6000 m for 2 h as the optimal condition for AHAI induction in zebrafish. Under these conditions, notable behavioral changes including slow movement, abnormal exploration behavior and static behavior in the Novel tank test. Furthermore, this model demonstrated changes in oxidative stress-related markers included increased levels of malondialdehyde, decreased levels of glutathione, decreased activities of superoxide dismutase and catalase, and increased levels of inflammatory markers IL-6, IL-1β and TNF-α, and inflammatory cell infiltration and mild edema in the gill tissue, mirroring the clinical pathophysiology observed in AHAI patients. This innovative zebrafish model not only offers a more accurate representation of the high-altitude environment but also provides a high-throughput platform for AHAI drug discovery and pathogenesis research.

Abstract 5609: A WRN screening cascade to facilitate novel drug discovery

Abstract Human RecQ deconjugating enzyme WRN is involved in DNA replication, DNA repair, recombination, transcription and telomere stabilization[1]. It plays a key role in nucleic acid metabolism as well. WRN defects lead to premature aging, type II diabetes, osteoporosis, atherosclerosis and cancer[2]. Hence it is of great interest of both pharmaceutical and academic field to develop the WRN inhibitors. Here we constructed an integrated experimental cascade, which contains both in vitro and in vivo assays, to conduct the high throughput hit-to-lead compound screen. WRN proteins of different length have been successfully purified and utilized to develop multiple biochemical assays such as unwinding assay and ATPase assay. We have also validated different cellular assays, including proliferation and immunofluorescence, to assess the cytotoxicity and the influence of downstream biomarkers of WRN inhibitors. A WRN knock-out cell line has been generated to better appreciate the inhibition mechanism. In addition, we have generated a WRN-HiBiT knock-in cell line to evaluate WRN degraders or target-compound interactions. Lastly, multiple CDX models utilizing different MSI or MSS cell lines have been validated to help determine the efficacy of WRN inhibitors thus shed light on the drug indications. Together our WRN screening cascade can provide comprehensive compound evaluation across in vitro and in vivo platforms, thus serve as an efficient screening platform for new drug discovery. [1] Kitano K. Structural mechanisms of human RecQ helicases WRN and BLM. Front Genet. 2014 Oct 29;5:366. [2]Hussain M, Krishnamurthy S, Patel J, Kim E, Baptiste BA, Croteau DL, Bohr VA. Skin Abnormalities in Disorders with DNA Repair Defects, Premature Aging, and Mitochondrial Dysfunction. J Invest Dermatol. 2021 Apr;141(4S):968-975. Citation Format: Aicheng Wang, Kejun Mao, Tao Li, Lizhao Guan, Yuhong Chen, Haiting Dai, Xian Wu, Jiabao Lv, Xu Wang, Cong Huang, Tiejun Bing. A WRN screening cascade to facilitate novel drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5609.

Abstract 3092: MICRO-TAG: A novel fluorescence-based real-time cellular target engagement platform for drug discovery

Abstract Success of drug discovery programs can be amplified by adopting emerging technologies that can interrogate drug targets within their physiological context. Cell target engagement (CTE) presents a combined biological & biophysical method, which provides quantitative evaluation of target-drug interaction within the native environment of the cell. The currently available luminescence-based CTE methods are limited to measurement of end-point signal and poor resolution, thereby limiting their mechanistic and stoichiometric insight. We have developed MICRO-TAG, a novel fluorescence-based CTE platform, which relies on complementation of split-RNAse A. It enables interrogation of target engagement without interfering with folding, localization and function of target proteins - all within the physiological milieu of the cell. Uniquely, this new platform allows for quantitation and monitoring of CTE in real- time in the cell. It enables extraction of important parameters from target-drug interaction: target thermal profile and temperature of aggregation (Tagg), time required to reach equilibrium (teq), apparent association rate (Kon) and physiologically relevant drug:target binding affinity (KD). We provide data demonstrating potential and utility of MICRO-TAG platform on drug targets, such as KRAS, MTH1, EGFR, and UBE2N. The platform demonstrates relevance for discovery of novel drug candidates targeting challenging drug targets such as transcription factors. This highly scalable and quantitative novel method for assessing drug-target interaction within cells can enhance drug discovery programs, and offers potential to rapidly identify clinically relevant hit compounds for challenging drug targets. Citation Format: Ivan Babic, Nikolas Bryan, Claire Cunningham, Avery Sampson, Daniel Starczynowski, Elmar Nurmemmedov. MICRO-TAG: A novel fluorescence-based real-time cellular target engagement platform for drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3092.

Abstract 4151: Development of a cancer-activated biologic imaging platform for early lung cancer diagnosis

Abstract Current modalities, such as LDCT and fluorodeoxyglucose positron emission tomography (FDG PET), for early lung cancer imaging, rely upon proxies resulting in poor specificity and/or sensitivity. They are also unreliable for discriminating benign versus malignant lesions resulting in the requirement of longitudinal analyses euphemistically called “watchful waiting”. Lung biopsies are marred by significant false negative rates and pose complications of collapsed lungs or bleeding in up to 22% of procedures and death rates up to 1%. To overcome these obstacles, Earli is developing a non-invasive, highly specific cancer-activated imaging platform that usurps dysregulated gene expression within malignancies to force only cancer cells to produce a synthetic biomarker that can be localized using PET imaging. EARLI-204 is a lipid nanoparticle that contains a DNA nanoplasmid comprised of a cancer-activated promoter driving selective expression of a functionally inactivated somatostatin receptor 2 (SSTR2fi) gene. Abrogation of internalization and signal transduction allows the safe use of SSTR2fi as an ectopically expressed PET reporter gene (PRG). Following administration, EARLI-204 transfects tumor and normal cells but transcriptional activation only within cancer cells results in selective cell-surface expression of SSTR2fi that can be imaged with FDA-approved SSTR2 PET tracers. H1299 human lung cancer cells engineered to express SSTR2 (H1299-SSTR2) revealed a discernable PET signal with as little as 31,000 engineered cells. Mixed cell titration studies using subcutaneous (SQ) tumors with H1299-SSTR2 and non-expressing H1299-wt cells suggest tumors with between 0.1% and 1% H1299-SSTR2 cells had a significant PET signal, compared to tumors with 100% H1299-wt. This result sets a benchmark transfection of ~1% to achieve a PET signal. Intratumoral (IT) dose titration of EARLI-204 revealed that 5 ug of EARLI-204 generates a significant PET signal. Consistent with the H1299-SSTR2 studies, IHC shows ~1% of tumor cells express the PRG at a 5 ug IT dose level. Furthermore, we measured 70 copies of EARLI-204 DNA per cell resulting in 22,629 SSTR2 mRNA copies/25 ng at a 5 ug IT dose level. IV dosing of EARLI-204 in SQ and intralung tumor models results in cancer-activated expression of SSTR2fi in both SQ and small (<4 mm) lung tumors with significantly increased (p < 0.05) PET signal. For lung tumors, analyses showed 1 copy of EARLI-204 DNA/cell resulting in 780 SSTR2 mRNA copies/25 ng. The results demonstrate an effective molecular imaging platform for drug discovery ranging from in vivo screening to building PK-PD-efficacy relationships and enabling human dose projection for the Earli PET localization drug. The benchmarks and findings established with this preclinical imaging pipeline are currently being evaluated in large animals such as dogs and pigs, and will be translated to humans in planned clinical trials. Citation Format: Mohammed Goryawala, Hung-Yu Henry Lee, Ling Tong, Trupti Patil, Alex Harwig, Chloe Xia, Suthara Ramachandran, Dariusz Wodziak, Dean Felsher, Tim Sproul, David Suhy. Development of a cancer-activated biologic imaging platform for early lung cancer diagnosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4151.

Abstract 7149: Discovery of a novel USP1 inhibitor: Targeted therapy for BRCA-mutated and PARPi-resistant cancers

Abstract Harnessing synthetic lethality offers an innovative approach to targeted cancer treatment. USP1, a specific deubiquitinating enzyme, has gained attention as a potential synthetic lethality target for BRCA-mutated cancers. At AIGEN Sciences, Inc., we've integrated the advanced capabilities of our human-in-the-loop (HITL) AI drug discovery platform, AIGEN ChemTailor. This cutting-edge platform thrives on continuous learning enhanced by expert feedback, refining our approach to drug discovery. Using AIGEN ChemTailor, we synthesized a specific USP1 inhibitor. Its inhibitory capabilities were validated through the Ubiquitin-rhodamine 110 assay. Notably, our inhibitor presented remarkable anti-proliferative effects on BRCA1 mutant cells (MDA-MB-436) while showing no activity against BRCA wild-type cells (HCC1954), highlighting its specificity. The efficacy of our inhibitor was enhanced when combined with PARP inhibitors, such as olaparib or AZD5305, especially in UWB1.289 cells. Impressively, the USP1 inhibitor also effectively targeted PARPi-resistant cell lines, including A2780-ola, UWB1.289-nir, HCC38-ola, MDA-MB-468-ola, U251MG-ola, and OVCAR8-ola. Clonogenic assays with MDA-MB-436 and MCF-10A emphasized our inhibitor's selectivity towards BRCA mutant phenotypes. Subsequent studies demonstrated the compound's mechanism: inducing replication stress by impairing of DNA synthesis and activating DNA damage pathways via ATR signaling. Preclinical mouse studies highlighted favorable pharmacokinetics and involved the assessment of anti-tumor effects in animal models. In summation, our USP1 inhibitor, developed using AIGEN ChemTailor and advanced molecular modeling techniques, stands out as a potent therapeutic against BRCA-mutated cancers and PARP inhibitor-resistant strains. Citation Format: Jihye Kim, Sunkyu Kim, Sejeong Park, Sanghoon Lee, Kiwoong Yoo, Ho-Jeong Lee, Jaewoo Kang, Kwang-Ok Lee. Discovery of a novel USP1 inhibitor: Targeted therapy for BRCA-mutated and PARPi-resistant cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7149.

Abstract 3324: Discovery of a novel SOS1 inhibitor, AIG01012, targeting pan-KRAS mutant cancers

Abstract Targeting the SOS1-KRAS interaction represents a pivotal strategy in mitigating aberrant KRAS signaling, which is implicated in numerous malignancies. At AIGEN Sciences, Inc., we have harnessed an advanced human-in-the-loop (HITL) AI-based drug discovery platform (AIGEN ChemTailor). This innovative platform allows online learning through expert feedback, optimizing our drug development endeavors. We designed a potent SOS1 inhibitor, AIG01012 using AIGEN ChemTailor in combination with fragment-based drug discovery (FBDD) and molecular modeling techniques. We conceived numerous compounds and shortlisted the leading candidates for extensive testing after meticulous computer simulations. AIG01012 manifested substantial inhibitory effects against several KRAS mutant interactions with SOS1, specifically SOS1-KRAS WT, SOS1-KRAS G12C, SOS1-KRAS G12D, SOS1-KRAS G12V, and SOS1-KRAS G13D. However, its inhibitory capacity did not extend to the SOS2-KRAS G12C interaction. AIG01012 demonstrated remarkable inhibitory effects in 3D cell proliferation assays across various cell lines, including H358, MIA-PaCa2, SW837, AsPC-1, A427, SW620, Capan-2, A549, DLD-1, MKN-1, and H1666. Moreover, AIG01012 showed synergistic antiproliferative effects when combined with approved drugs such as sotorasib (for lung cancer with KRAS mutations), trametinib (a MEK inhibitor), and Osimertinib (targets specific EGFR mutations) in either H358 or PC-9 cell lines. Mouse studies further confirmed its favorable pharmacological properties, and its efficacy was evaluated in subsequent mouse tumor model. In summary, utilizing our human-in-the-loop (HITL) AI platform, AIGEN ChemTailor, we have efficiently derived AIG01012 as a potent SOS1 inhibitor that targets a wide range of KRAS interactions. With its notable in vitro and in vivo outcomes, AIG01012 is set for further exploration and prospective clinical trials as a significant contender in KRAS-targeted cancer treatments. Citation Format: Jihye Kim, Sejeong Park, Sunkyu Kim, Sanghoon Lee, Kiwoong Yoo, Ho-Jeong Lee, Jaewoo Kang, Kwang-Ok Lee. Discovery of a novel SOS1 inhibitor, AIG01012, targeting pan-KRAS mutant cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3324.

Abstract 2067: QUANTROseq, a transcriptomic based drug discovery platform using time-resolved gene expression profiling: Identification of inhibitors and degraders of transcription factors and cell signaling regulators

Abstract Integrative analyses of CRISPR/Cas9 screening datasets from different sources revealed - besides known oncogenes - a series of transcriptional master regulators as most prominent context-specific dependencies in cancer that remained largely inaccessible to conventional drug discovery approaches. New chemical entities (NCEs) that specifically interfere with a transcription factor (TF) at any level should induce and be detectable based on selective effects on their primary biochemical activity - i.e., the transcriptional activation of specific target genes. However, the definition of direct targets of a TF and, more generally, the unbiased detection of direct transcriptional effects has remained challenging due to the limited time resolution of conventional techniques for gene perturbation and transcriptional profiling. To overcome this limitation, QUANTRO Therapeutics relies on SLAMseq technology that, by metabolic labeling de novo-synthesized RNA immediately after intervention and conserving the information for later readout, provides unprecedent time-resolution in transcriptomic analysis. Aiming to target previously undruggable targets, we set out to first build definitive knowledge around their direct effect on transcription, inducing their quick protein degradation through the auxin-inducible degron (AID) technology followed by immediate transcriptional readout though SLAMseq -before any secondary, confounding effect could appear in the cell. The targets´ mRNA fingerprints produced are then used as a reference and cross-compared with existing and new chemical entities to: (i) benchmark the real mode of action of existing drugs; (ii) identify new drug candidates that specifically interfere with disease-causing transcriptional programs in cancer; (iii) interrogate the efficiency, selectivity, and potency of drug candidates during Hit-validation and Hit-to-Lead activities. Proof of concept data demonstrated that time-resolved transcriptional profiling can reveal drugs´ mode of action with unprecedent precision and sensitivity, when drugs act on Targets that have a direct effect on transcriptional regulation - such as TFs and signaling pathways. Building on this knowledge, QUANTRO Therapeutics unleashed the unique potential of mRNA fingerprinting technology for HTS-compatible drug discovery by (1) establishing scalable and automated workflows for metabolic RNA labeling, treatment of cells, and RNA extraction; (2) developing algorithms for combinatorial mRNA fingerprint-readout that allow for the simultaneous assessment of TF signatures by multiplexed targeted RNA sequencing (QUANTROseq), thus transforming the precision and scope of cell-based compound screens. Citation Format: Arianna Sabò, Nina Fasching Griesmayr, Tobias Neumann, Raphael Manzenreither, Maja Ivankovic, Rodrigo Pacheco Valamatos Costa, Sarah Rieser, Sara Scinicariello, Petr Triska, Anna Stingeder, Astrid Gruss, Ryan Cubero, Olga Frank, Ivica Sowemimo, Paul Kirchgatterer, Adriana Cantoran, Stefan Ameres, Johannes Zuber, Michael Bauer. QUANTROseq, a transcriptomic based drug discovery platform using time-resolved gene expression profiling: Identification of inhibitors and degraders of transcription factors and cell signaling regulators [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2067.

Abstract 6790: Breaking barriers: A high-throughput 3D drug discovery platform for ovarian cancer

Abstract Background: Ovarian Cancer (OVCA) is a formidable challenge in oncology and remains the most lethal gynecologic malignancy with many cases (~80%) diagnosed at a late stage with an equally high rate of recurrence. Yet, no established OVCA models exist that faithfully recapitulate the biological complexity of metastatic OVCA. This multidisciplinary team developed a new in vitro high-throughput model that maintains the characteristics of the patient’s tumor including resident immune cells. Key breakthroughs include long term (>21 day) culture of patient-derived microtumors, a functional and perfusable microgel medium (Liquid Like Solids - LLS™), microplates with controlled “pumpless” perfusion of culture media (Darcy Plates™), and integrated in situ imaging. Methods: We designed, fabricated, and validated a new 3D culture device in the standard SBS microplate format (Darcy Plate) that integrates in situ microscopy and perfusion through a bio-conjugated microgel bed (LLS). Patient tumors were collected during debulking surgery, micronized into 1 µl microtumors, suspended in LLS, and plated into the 48-well Darcy Plate. Viability and proliferation were assessed over 21 days in situ using a standard LIVE/DEAD™ kit and EDU staining, respectively. Epithelial OVCA cells and immune cells were identified with immunofluorescence microscopy. Results: Optimal media conditions (HPLM media with 10% FBS, 1% Pen/Strep, 2.5 mg L−1 Amphotericin B, 10 mM HEPES, 0.5 µM A83-01 -TGF-β inhibitor-, and ITS) and perfusion flow rates (100 µl/day per well) were identified that resulted in outstanding cell viability after 21 days (~100% - no detectable cell death using LIVE/DEAD™). PAX8 nuclear expression, a marker for epithelial metastatic OVCA, was retained. EDU staining confirmed cell proliferation and CD45 staining revealed retention of viable immune cells on and within the microtumor at 21 days. Drug testing to evaluate tumor response to chemotherapeutic agents, carboplatin, and emerging targeted therapies was performed by dosing the feed-wells at different concentrations and evaluating cell death through LIVE/DEAD imaging after 5 days of treatment. Conclusions: OVCA is a challenging disease with understudied biological complexity and extensive metastatic involvement. This study demonstrates that drug screening with 3D microtumors has important clinical implications and provides a unique opportunity to evaluate drug responses and personalized treatment strategies. These patient-derived microtumors retain crosstalk between diverse cell populations and the tumor microenvironment, which increases the likelihood of identifying effective therapies and drug candidates. This system retains patient-specific tumor heterogeneity and microenvironmental complexity of OVCA, offering a promising platform for drug screening, high-throughput assays, biomarker discovery, and ultimately improving treatment outcomes. Citation Format: Erin George, Diego I. Pedro, Alfonso Pepe, Angie M. Rivera, Ryan A. Smolchek, Jack E. Famiglietti, W. Gregory Sawyer. Breaking barriers: A high-throughput 3D drug discovery platform for ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6790.

Abstract 5940: JAB-30355: A highly potent, orally bioavailable p53-Y220C reactivator

Abstract Background: As a key tumor suppressor, p53 precisely regulates cellular events such as cell cycle arrest, apoptosis, senescence, and DNA repair under physiological conditions. In 50-60% of human cancers, TP53 gene is mutated. The TP53 Y220C is a hotspot loss-of-function mutation occurring in around 1% of solid tumors. Application of p53-Y220C reactivator for restoration of p53 function represents a promising treatment strategy for patients with this mutation. Methods: The Induced Allosteric Drug Discovery Platform (IADDP), which integrates medicinal chemistry, biochemical and biophysical studies, and computational techniques, was applied for the development of JAB-30355. The proportion of p53-Y220C with wild-type protein-like structure after JAB-30355 treatment was determined by immunoprecipitation. Thermal shift assay was applied to assess the thermal stability of JAB-30355-reactivated p53-Y220C protein. DNA binding assay was developed to evaluate the in vitro DNA binding activity. p53-luciferase reporter system was developed to evaluate the cellular transcriptional activity. qPCR and Western blotting were performed to evaluate the transcriptional and translational levels of p53 downstream targets, respectively. CellTiter-Glo assay was performed to evaluate the inhibitory activity of JAB-30355 on the viability of tumor cell lines harboring wild-type or Y220C mutated TP53. In vivo PK-PD study was conducted to evaluate the relationship between JAB-30355 concentration and expression of p53 target genes. Multiple CDX and PDX mouse models harboring TP53 Y220C were used to evaluate the antitumor activity of JAB-30355. Results: Immunoprecipitation assay and thermal shift assay results demonstrated that JAB-30355 efficiently restored the wild-type p53-like structure and enhanced protein stability of p53-Y220C in a dose-dependent manner. In addition, JAB-30355 significantly enhanced the DNA binding activity of p53-Y220C and subsequently increased the expression of p53 target genes, such as CDKN1A, MDM2 and PUMA. JAB-30355 inhibited cell viability of multiple TP53 Y220C-mutated cancer cell lines with IC50s ranging from 0.2 to 0.7 μM, and exhibited good selectivity against TP53 wild-type cells. Overall, the in vitro data demonstrated that JAB-30355 is a potent and selective p53-Y220C reactivator. In vivo PK-PD study showed good correlation between JAB-30355 exposure and activation of p53 target genes. Furthermore, JAB-30355 exhibited dose-dependent anti-tumor activity, inducing tumor stasis or regression in multiple CDX and PDX models of ovarian cancer, pancreatic cancer, gastric cancer, and small cell lung cancer, with overall good tolerability. Conclusions: JAB-30355 is a highly potent, selective, and orally bioavailable p53-Y220C reactivator that will be tested in clinical space soon. Citation Format: Qian Zheng, Peng Wang, Chen Liang, Yao Li, Xin Sun, Amin Li, Wei Zhang, Wei Long, Yanping Wang. JAB-30355: A highly potent, orally bioavailable p53-Y220C reactivator [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5940.

Organotypic culture of human brain explants as a preclinical model for AI-driven antiviral studies

Viral neuroinfections represent a major health burden for which the development of antivirals is needed. Antiviral compounds that target the consequences of a brain infection (symptomatic treatment) rather than the cause (direct-acting antivirals) constitute a promising mitigation strategy that requires to be investigated in relevant models. However, physiological surrogates mimicking an adult human cortex are lacking, limiting our understanding of the mechanisms associated with viro-induced neurological disorders. Here, we optimized the Organotypic culture of Post-mortem Adult human cortical Brain explants (OPAB) as a preclinical platform for Artificial Intelligence (AI)-driven antiviral studies. OPAB shows robust viability over weeks, well-preserved 3D cytoarchitecture, viral permissiveness, and spontaneous local field potential (LFP). Using LFP as a surrogate for neurohealth, we developed a machine learning framework to predict with high confidence the infection status of OPAB. As a proof-of-concept, we showed that antiviral-treated OPAB could partially restore LFP-based electrical activity of infected OPAB in a donor-dependent manner. Together, we propose OPAB as a physiologically relevant and versatile model to study neuroinfections and beyond, providing a platform for preclinical drug discovery.

Ex-vivo drug screening of surgically resected glioma stem cells to replace murine avatars and provide personalise cancer therapy for glioblastoma patients

With diminishing returns and high clinical failure rates from traditional preclinical and animal-based drug discovery strategies, more emphasis is being placed on alternative drug discovery platforms. Ex vivo approaches represent a departure from both more traditional preclinical animal-based models and clinical-based strategies and aim to address intra-tumoural and inter-patient variability at an earlier stage of drug discovery. Additionally, these approaches could also offer precise treatment stratification for patients within a week of tumour resection in order to direct tailored therapy. One tumour group that could significantly benefit from such ex vivo approaches are high-grade gliomas, which exhibit extensive heterogeneity, cellular plasticity and therapy-resistant glioma stem cell (GSC) niches. Historic use of murine-based preclinical models for these tumours has largely failed to generate new therapies, resulting in relatively stagnant and unacceptable survival rates of around 12-15 months post-diagnosis over the last 50 years. The near universal use of DNA damaging chemoradiotherapy after surgical resection within standard-of-care (SoC) therapy regimens provides an opportunity to improve current treatments if we can identify efficient drug combinations in preclinical models that better reflect the complex inter-/intra-tumour heterogeneity, GSC plasticity and inherent DNA damage resistance mechanisms. We have therefore developed and optimised a high-throughput ex vivo drug screening platform; GliExP, which maintains GSC populations using immediately dissociated fresh surgical tissue. As a proof-of-concept for GliExP, we have optimised SoC therapy responses and screened 30+ small molecule therapeutics and preclinical compounds against tumours from 18 different patients, including multi-region spatial heterogeneity sampling from several individual tumours. Our data therefore provides a strong basis to build upon GliExP to incorporate combination-based oncology therapeutics in tandem with SoC therapies as an important preclinical alternative to murine models (reduction and replacement) to triage experimental therapeutics for clinical translation and deliver rapid identification of effective treatment strategies for individual gliomas.

Construction of an Enzymatically Controlled DNA Nanomachine for One-Step Imaging of Telomerase in Living Cells.

Telomerase is a basic reverse transcriptase that maintains the telomere length in cells, and accurate and specific sensing of telomerase in living cells is critical for medical diagnostics and disease therapeutics. Herein, we demonstrate for the first time the construction of an enzymatically controlled DNA nanomachine with endogenous apurinic/apyrimidinic endonuclease 1 (APE1) as a driving force for one-step imaging of telomerase in living cells. The DNA nanomachine is designed by rational engineering of substrate probes and reporter probes embedded with an enzyme-activatable site (i.e., AP site) and their subsequent assembly on a gold nanoparticle (AuNP). Upon recognition and cleavage of the AP site in the substrate probe by APE1, the loop of the substrate probe unfolds, exposing telomeric primer (TP) with the 3'-OH end. Subsequently, the TP is elongated by telomerase at the 3'-OH end to generate a long telomeric product. The resultant telomeric product acts as a swing arm that can hybridize with a reporter probe to initiate the APE1-powered walking reaction, ultimately generating a significantly enhanced fluorescence signal. Notably, endogenous APE1 is used as the driving force of the DNA nanomachine, avoiding the introduction of exogenous auxiliary cofactors into the cellular microenvironment. Owing to the high kinetics and high amplification efficiency of the APE1-powered DNA nanomachine, this strategy enables one-step sensitive sensing of telomerase in vitro and in vivo. It can successfully discriminate telomerase activity between cancer cells and normal cells, screen telomerase inhibitors, and monitor the variations of telomerase activity in living cells, offering a prospective platform for molecular diagnostics and drug discovery.

“DompeKeys”: a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases

The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the field of cheminformatics and computer-aided drug design. Molecular fingerprints represent a widely employed class of descriptors; however, their generation process is time-consuming for large databases and is susceptible to bias. Therefore, descriptors able to accurately detect predefined structural fragments and devoid of lengthy generation procedures would be highly desirable. To meet additional needs, such descriptors should also be interpretable by medicinal chemists, and suitable for indexing databases with trillions of compounds. To this end, we developed—as integral part of EXSCALATE, Dompé’s end-to-end drug discovery platform—the DompeKeys (DK), a new substructure-based descriptor set, which encodes the chemical features that characterize compounds of pharmaceutical interest. DK represent an exhaustive collection of curated SMARTS strings, defining chemical features at different levels of complexity, from specific functional groups and structural patterns to simpler pharmacophoric points, corresponding to a network of hierarchically interconnected substructures. Because of their extended and hierarchical structure, DK can be used, with good performance, in different kinds of applications. In particular, we demonstrate how they are very well suited for effective mapping of chemical space, as well as substructure search and virtual screening. Notably, the incorporation of DK yields highly performing machine learning models for the prediction of both compounds’ activity and metabolic reaction occurrence. The protocol to generate the DK is freely available at https://dompekeys.exscalate.eu and is fully integrated with the Molecular Anatomy protocol for the generation and analysis of hierarchically interconnected molecular scaffolds and frameworks, thus providing a comprehensive and flexible tool for drug design applications.

BioPrint meets the AI age: development of artificial intelligence-based ADMET models for the drug-discovery platform SAFIRE.

Background: To prioritize compounds with a higher likelihood of success, artificial intelligence models can be used to predict absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of molecules quickly and efficiently. Methods: Models were trained with BioPrint database proprietary data along with public datasets to predict various ADMET end points for the SAFIRE platform. Results: SAFIRE models performed at or above 75% accuracy and 0.4 Matthew's correlation coefficient with validation sets. Training with both proprietary and public data improved model performance and expanded the chemical space on which the models were trained. The platform features scoring functionality to guide user decision-making. Conclusion: High-quality datasets along with chemical space considerations yielded ADMET models performing favorably with utility in the drug discovery process.

Induced Pluripotent Stem Cells in Drug Discovery and Neurodegenerative Disease Modelling.

Induced pluripotent stem cells (iPSCs) are derived from reprogrammed adult somatic cells. These adult cells are manipulated in vitro to express genes and factors essential for acquiring and maintaining embryonic stem cell (ESC) properties. This technology is widely applied in many fields, and much attention has been given to developing iPSC-based disease models to validate drug discovery platforms and study the pathophysiological molecular processes underlying disease onset. Especially in neurological diseases, there is a great need for iPSC-based technological research, as these cells can be obtained from each patient and carry the individual's bulk of genetic mutations and unique properties. Moreover, iPSCs can differentiate into multiple cell types. These are essential characteristics, since the study of neurological diseases is affected by the limited access to injury sites, the need for in vitro models composed of various cell types, the complexity of reproducing the brain's anatomy, the challenges of postmortem cell culture, and ethical issues. Neurodegenerative diseases strongly impact global health due to their high incidence, symptom severity, and lack of effective therapies. Recently, analyses using disease specific, iPSC-based models confirmed the efficacy of these models for testing multiple drugs. This review summarizes the advances in iPSC technology used in disease modelling and drug testing, with a primary focus on neurodegenerative diseases, including Parkinson's and Alzheimer's diseases.