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"631/154"
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Optimization of the 4-anilinoquin(az)oline scaffold as epidermal growth factor receptor (EGFR) inhibitors for chordoma utilizing a toxicology profiling assay platform
by
Asquith, Christopher R. M.
,
Bieberich, Andrew A.
,
Laitinen, Tuomo
in
631/154
,
631/154/309
,
631/154/309/2132
2022
The 4-anilinoquin(az)oline is a well-known kinase inhibitor scaffold incorporated in clinical inhibitors including gefitinib, erlotinib, afatinib, and lapatinib, all of which have previously demonstrated activity against chordoma cell lines in vitro. We screened a focused array of compounds based on the 4-anilinoquin(az)oline scaffold against both U-CH1 and the epidermal growth factor receptor (EGFR) inhibitor resistant U-CH2. To prioritize the hit compounds for further development, we screened the compound set in a multiparameter cell health toxicity assay. The de-risked compounds were then screened against a wider panel of patient derived cell lines and demonstrated low micromolar efficacy in cells. We also investigated the properties that gave rise to the toxophore markers, including the structural and electronic features, while optimizing for EGFR in-cell target engagement. These de-risked leads present a potential new therapeutic avenue for treatment of chordomas and new chemical tools and probe compound
45
(UNC-CA359) to interrogate EGFR mediated disease phenotypes.
Journal Article
Exploiting machine learning for end-to-end drug discovery and development
by
Zorn, Kimberley M
,
Russo, Daniel P
,
Puhl, Ana C
in
Artificial intelligence
,
Artificial neural networks
,
Bayesian analysis
2019
A variety of machine learning methods such as naive Bayesian, support vector machines and more recently deep neural networks are demonstrating their utility for drug discovery and development. These leverage the generally bigger datasets created from high-throughput screening data and allow prediction of bioactivities for targets and molecular properties with increased levels of accuracy. We have only just begun to exploit the potential of these techniques but they may already be fundamentally changing the research process for identifying new molecules and/or repurposing old drugs. The integrated application of such machine learning models for end-to-end (E2E) application is broadly relevant and has considerable implications for developing future therapies and their targeting.This Perspective describes the application of machine learning models in the design, synthesis and characterisation of molecules at different stages in the drug discovery and development process.
Journal Article
Correlation between hemolytic activity, cytotoxicity and systemic in vivo toxicity of synthetic antimicrobial peptides
2020
The use of non-standard toxicity models is a hurdle in the early development of antimicrobial peptides towards clinical applications. Herein we report an extensive in vitro and in vivo toxicity study of a library of 24 peptide-based antimicrobials with narrow spectrum activity towards veterinary pathogens. The haemolytic activity of the compounds was evaluated against four different species and the relative sensitivity against the compounds was highest for canine erythrocytes, intermediate for rat and human cells and lowest for bovine cells. Selected peptides were additionally evaluated against HeLa, HaCaT and HepG2 cells which showed increased stability towards the peptides. Therapeutic indexes of 50–500 suggest significant cellular selectivity in comparison to bacterial cells. Three peptides were administered to rats in intravenous acute dose toxicity studies up to 2–8 × MIC. None of the injected compounds induced any systemic toxic effects in vivo at the concentrations employed illustrating that the correlation between the different assays is not obvious. This work sheds light on the in vitro and in vivo toxicity of this class of promising compounds and provides insights into the relationship between the different toxicity models often employed in different manners to evaluate the toxicity of novel bioactive compounds in general.
Journal Article
Delivering on the promise of protein degraders
by
Brown, Matthew F
,
Bartlett, Derek W
,
O’Brien Laramy, Matthew N
in
Clinical trials
,
Design
,
Oral administration
2023
Over the past 3 years, the first bivalent protein degraders intentionally designed for targeted protein degradation (TPD) have advanced to clinical trials, with an initial focus on established targets. Most of these clinical candidates are designed for oral administration, and many discovery efforts appear to be similarly focused. As we look towards the future, we propose that an oral-centric discovery paradigm will overly constrain the chemical designs that are considered and limit the potential to drug novel targets. In this Perspective, we summarize the current state of the bivalent degrader modality and propose three categories of degrader designs, based on their likely route of administration and requirement for drug delivery technologies. We then describe a vision for how parenteral drug delivery, implemented early in research and supported by pharmacokinetic–pharmacodynamic modelling, can enable exploration of a broader drug design space, expand the scope of accessible targets and deliver on the promise of protein degraders as a therapeutic modality.Bivalent protein degraders such as proteolysis targeting chimeras (PROTACs) are entering clinical trials, with a current focus on oral administration. O’Brien Laramy et al. propose that implementing non-oral drug delivery technologies guided by pharmacokinetic–pharmacodynamic modelling could expand the chemical design space for degraders as well as the number of druggable targets.
Journal Article
Non-specific interactions of antibody-oligonucleotide conjugates with living cells
2021
Antibody-Oligonucleotide Conjugates (AOCs) represent an emerging class of functionalized antibodies that have already been used in a wide variety of applications. While the impact of dye and drug conjugation on antibodies’ ability to bind their target has been extensively studied, little is known about the effect caused by the conjugation of hydrophilic and charged payloads such as oligonucleotides on the functions of an antibody. Previous observations of non-specific interactions of nucleic acids with untargeted cells prompted us to further investigate their impact on AOC binding abilities and cell selectivity. We synthesized a series of single- and double-stranded AOCs, as well as a human serum albumin-oligonucleotide conjugate, and studied their interactions with both targeted and non-targeted living cells using a time-resolved analysis of ligand binding assay. Our results indicate that conjugation of single strand oligonucleotides to proteins induce consistent non-specific interactions with cell surfaces while double strand oligonucleotides have little or no effect, depending on the preparation method.
Journal Article
The effect of fatty diacid acylation of human PYY3-36 on Y2 receptor potency and half-life in minipigs
2021
Peptides are notoriously known to display very short
in vivo
half-lives often measured in minutes which in many cases greatly reduces or eliminates sufficient
in vivo
efficacy. To obtain long half-lives allowing for up to once-weekly dosing regimen, fatty acid acylation (lipidation) have been used to non-covalently associate the peptide to serum albumin thus serving as a circulating depot. This approach is generally considered in the scientific and patent community as a standard approach to protract almost any given peptide. However, it is not trivial to prolong the half-life of peptides by lipidation and still maintain high potency and good formulation properties. Here we show that attaching a fatty acid to the obesity-drug relevant peptide PYY
3-36
is not sufficient for long pharmacokinetics (PK), since the position in the backbone, but also type of fatty acid and linker strongly influences PK and potency. Furthermore, understanding the proteolytic stability of the backbone is key to obtain long half-lives by lipidation, since backbone cleavage still occurs while associated to albumin. Having identified a PYY analogue with a sufficient half-life, we show that in combination with a GLP-1 analogue, liraglutide, additional weight loss can be achieved in the obese minipig model.
Journal Article
Apigeninidin-rich Sorghum bicolor (L. Moench) extracts suppress A549 cells proliferation and ameliorate toxicity of aflatoxin B1-mediated liver and kidney derangement in rats
2022
Sorghum bicolor
plant has a high abundance of 3-deoxyanthocyanins, flavonoids and other polyphenol compounds that have been shown to offer numerous health benefits. Epidemiological studies have linked increased intake of
S. bicolor
to reduced risk of certain cancer types, including lung adenocarcinoma.
S. bicolor
extracts have shown beneficial effects in managing hepatorenal injuries. This study investigated the cytotoxic potential of three apigeninidin-rich extracts of
S. bicolor
(SBE-05, SBE-06 and SBE-07) against selected cancer cell lines and their ameliorative effect on aflatoxin B
1
(AFB
1
)-mediated hepatorenal derangements in rats. We observed that, among the three potent extracts, SBE-06 more potently and selectively suppressed the growth of lung adenocarcinoma cell line (A549) (IC
50
= 6.5 μg/mL). SBE-06 suppressed the expression of STAT3 but increased the expression of caspase 3. In addition, SBE-05, SBE-06 and SBE-07 inhibited oxidative and nitrosative stress, inflammation, and apoptosis and preserved the histoarchitectural networks of the liver and kidney of rats treated with AFB
1
. These in vitro and in vivo studies indicate the potential of these cheap and readily accessible extracts for cancer therapy and as chemo-preventive agents in preventing aflatoxin-related health issues.
Journal Article
In vitro assessment and phase I randomized clinical trial of anfibatide a snake venom derived anti-thrombotic agent targeting human platelet GPIbα
2021
The interaction of platelet GPIbα with von Willebrand factor (VWF) is essential to initiate platelet adhesion and thrombosis, particularly under high shear stress conditions. However, no drug targeting GPIbα has been developed for clinical practice. Here we characterized anfibatide, a GPIbα antagonist purified from snake (
Deinagkistrodon acutus
) venom, and evaluated its interaction with GPIbα by surface plasmon resonance and in silico modeling. We demonstrated that anfibatide interferds with both VWF and thrombin binding, inhibited ristocetin/botrocetin- and low-dose thrombin-induced human platelet aggregation, and decreased thrombus volume and stability in blood flowing over collagen. In a single-center, randomized, and open-label phase I clinical trial, anfibatide was administered intravenously to 94 healthy volunteers either as a single dose bolus, or a bolus followed by a constant rate infusion of anfibatide for 24 h. Anfibatide inhibited VWF-mediated platelet aggregation without significantly altering bleeding time or coagulation. The inhibitory effects disappeared within 8 h after drug withdrawal. No thrombocytopenia or anti-anfibatide antibodies were detected, and no serious adverse events or allergic reactions were observed during the studies. Therefore, anfibatide was well-tolerated among healthy subjects. Interestingly, anfibatide exhibited pharmacologic effects in vivo at concentrations thousand-fold lower than in vitro, a phenomenon which deserves further investigation.
Trial registration:
Clinicaltrials.gov NCT01588132.
Journal Article
AI based natural inhibitor targeting RPS20 for colorectal cancer treatment using integrated computational approaches
2025
The increasing global incidence of cancer emphasizes the vital role of machine learning algorithms and artificial intelligence (AI) in identifying novel anticancer targets and developing new drugs. Computational approaches can significantly quicken research on complex disorders, enabling the discovery of effective treatments. This study explores anticancer targets by assessing the potential of naturally occurring compounds derived from various plants to cure colorectal cancer. Twenty compounds were sourced from PubChem, and the
RPS20
protein structure was obtained from AlphaFold, and mutation “V50S” was added. Validation of mutated
RPS20
protein was performed using the Ramachandran plot and ERRAT. Binding sites on the mutated
RPS20
protein were identified with DeepSite, followed by virtual screening to pinpoint the most promising natural lead drug candidate. Indirubin emerged as the lead drug candidate, fulfilling all ADMET criteria and exhibiting a good binding affinity. Further development included designing an AI-based drug using the WADDAICA server, which was validated through molecular docking, molecular dynamics (MD) simulation, and MMGBSA. The electronic properties of indirubin were studied using DFT calculations. The results show a moderate HOMO-LUMO gap, indicating its potential reactivity and the possible capability for biological target interactions. These findings indicate that indirubin could serve as a potent and effective cancer inhibitor, offering high efficacy with minimal side effects.
Journal Article
Applications of chemogenomic library screening in drug discovery
2017
Key Points
A chemogenomic library is a collection of well-defined pharmacological agents. A hit from such a set in a phenotypic screen suggests that the annotated target or targets of the probe molecules are involved in the phenotypic perturbation.
The creation and utility of a number of chemogenomic libraries have been described, by academia and industry, and some are commercially available.
Chemogenomic screening has the potential to expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications include drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.
Target identification from phenotypic screening can benefit from the integration of small-molecule chemogenomics with genetic approaches, such as RNA-mediated interference and CRISPR–Cas9.
Current limitations of chemogenomic screening include small-molecule polypharmacology, misannotation of biological activity and false-positive results (deriving from compound fluorescence or luciferase reporter binding) for example, although opportunities to overcome these issues, particularly through the incorporation of computational techniques, are emerging.
'Open innovation' and collaborative ventures across academia and industry are required to create and assemble the best pharmacological probes for chemogenomic libraries.
Chemogenomic screening is increasingly being applied to expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Here, Jones and Bunnage discuss the principles of the creation and use of chemogenomic libraries, highlighting key examples and their applications, including target identification, drug repositioning and predictive toxicology.
The allure of phenotypic screening, combined with the industry preference for target-based approaches, has prompted the development of innovative chemical biology technologies that facilitate the identification of new therapeutic targets for accelerated drug discovery. A chemogenomic library is a collection of selective small-molecule pharmacological agents, and a hit from such a set in a phenotypic screen suggests that the annotated target or targets of that pharmacological agent may be involved in perturbing the observable phenotype. In this Review, we describe opportunities for chemogenomic screening to considerably expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications are explored, including drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.
Journal Article