Physicochemical Property Determinants of Oral Absorption for PROTAC Protein Degraders

Journal of Medicinal Chemistry, Journal Year: 2023, Volume and Issue: 66(12), P. 8281 - 8287

Published: June 6, 2023

Heterobifunctional PROTAC degraders are gaining attention as a differentiated therapeutic modality with the potential for oral dosing in clinic. Belonging to beyond Rule of Five domain physicochemical property space, we have sought understand determinants absorption this class molecules rapid development novel agents. We collected large data set from that been dosed orally and intravenously rats estimate fraction absorbed dosing. Through estimation, effects differential hepatic clearance normalized, allowing better assessment absorption. demonstrate less permissive than mice. The properties then evaluated once compounds rank-ordered by absorbed. derive suggested design constraints on associated higher probability being

Language: Английский

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Rule of five violations among the FDA-approved small molecule protein kinase inhibitors

Pharmacological Research, Journal Year: 2023, Volume and Issue: 191, P. 106774 - 106774

Published: April 17, 2023

Because genetic alterations including mutations, overexpression, translocations, and dysregulation of protein kinases are involved in the pathogenesis many illnesses, this enzyme family is target drug discovery programs pharmaceutical industry. Overall, US FDA has approved 74 small molecule kinase inhibitors, nearly all which orally effective. Of drugs, thirty-nine block receptor protein-tyrosine kinases, nineteen nonreceptor twelve directed against protein-serine/threonine four dual specificity kinases. The data indicate that 65 these medicinals for management neoplasms (51 solid tumors such as breast, colon, lung cancers, eight nonsolid leukemia, six both types tumors). Nine FDA-approved inhibitors form covalent bonds with their enzymes they accordingly classified TCIs (targeted inhibitors). Medicinal chemists have examined physicochemical properties drugs Lipinski's rule five (Ro5) a computational procedure used to estimate solubility, membrane permeability, pharmacological effectiveness drug-discovery setting. It relies on parameters molecular weight, number hydrogen bond donors acceptors, Log partition coefficient. Other important descriptors include lipophilic efficiency, polar surface area, rotatable aromatic rings. We tabulated other inhibitors. 30 fail comply five.

Language: Английский

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Structural and Physicochemical Features of Oral PROTACs

Journal of Medicinal Chemistry, Journal Year: 2024, Volume and Issue: 67(15), P. 13106 - 13116

Published: July 30, 2024

Achieving oral bioavailability with Proteolysis Targeting Chimeras (PROTACs) is a key challenge. Here, we report the in vivo pharmacokinetic properties mouse, rat, and dog of four clinical PROTACs compare an internally derived data set. We use NMR to determine 3D molecular conformations structural preorganization free solution, introduce new experimental descriptors, solvent-exposed H-bond donors (eHBD), acceptors (eHBA). derive upper limit eHBD ≤ 2 for apolar environments show greater tolerance other (eHBA, polarity, lipophilicity, weight) than Rule-of-5 compliant drugs. Within set structurally related PROTACs, that examples > have much lower those 2. summarize our findings as "Rule-of-oral-PROTACs" order assist medicinal chemists achieve this challenging space.

Language: Английский

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Contextualising the developability risk of antibodies with lambda light chains using enhanced therapeutic antibody profiling

Communications Biology, Journal Year: 2024, Volume and Issue: 7(1)

Published: Jan. 8, 2024

Abstract Antibodies with lambda light chains ( λ -antibodies) are generally considered to be less developable than those kappa κ -antibodies). Though this hypothesis has not been formally established, it led substantial systematic biases in drug discovery pipelines and thus contributed dominance amongst clinical-stage therapeutics. However, the identification of increasing numbers epitopes preferentially engaged by -antibodies shows there is a functional cost neglecting consider them as potential lead candidates. Here, we update our Therapeutic Antibody Profiler (TAP) tool use latest data machine learning-based structure prediction, apply evaluate developability risk profiles for based on their surface physicochemical properties. We find that while human average have higher issues -antibodies, sizeable proportion assigned lower-risk TAP should represent more tractable candidates therapeutic development. Through comparative analysis low- high-risk populations, highlight opportunities strategic design suggests would enrich -antibodies. Overall, provide context differing - enabling rational approach incorporate diversity into initial pool immunotherapeutic

Language: Английский

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Hydrophobic deep eutectic solvent (HDES) as oil phase in lipid-based drug formulations

International Journal of Pharmaceutics, Journal Year: 2024, Volume and Issue: 661, P. 124418 - 124418

Published: July 2, 2024

There is increasing pharmaceutical interest in deep eutectic solvents not only as a green alternative to organic drug manufacturing, but also liquid formulation for delivery. The present work introduces hydrophobic solvent (HDES) the field of lipid-based formulations (LBF). Phase behavior mixture with 2:1 M ratio decanoic- dodecanoic acid was studied experimentally and described by thermodynamic modelling. Venetoclax selected model atomistic molecular dynamics simulations mixtures. As result, valuable insights were gained into interaction networks between different components. Moreover, HDES showed greatly enhanced solubilization compared conventional glyceride-based vehicles, aqueous dispersion limited. Hence surfactants their ability improve addition Tween 80 resulted lowest droplet sizes high vitro release. In conclusion, combination surfactant(s) provides novel LBF potential. However, components must be finely balanced keep integrity solubilizing HDES, while enabling sufficient

Language: Английский

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Return to Flatland

Nature Reviews Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 31, 2025

Language: Английский

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Extracting medicinal chemistry intuition via preference machine learning

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Oct. 31, 2023

The lead optimization process in drug discovery campaigns is an arduous endeavour where the input of many medicinal chemists weighed order to reach a desired molecular property profile. Building expertise successfully drive such projects collaboratively very time-consuming that typically spans years within chemist's career. In this work we aim replicate by applying artificial intelligence learning-to-rank techniques on feedback was obtained from 35 at Novartis over course several months. We exemplify usefulness learned proxies routine tasks as compound prioritization, motif rationalization, and biased de novo design. Annotated response data provided, developed models code made available through permissive open-source license.

Language: Английский

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Compound Absorption in Polymer Devices Impairs the Translatability of Preclinical Safety Assessments

Advanced Healthcare Materials, Journal Year: 2023, Volume and Issue: 13(11)

Published: Dec. 6, 2023

Organotypic and microphysiological systems (MPS) that can emulate the molecular phenotype function of human tissues, such as liver, are increasingly used in preclinical drug development. However, despite their improved predictivity, development success rates have remained low with most compounds failing clinical phases promising data. Here, it is tested whether absorption small molecules to polymers commonly for MPS fabrication impact pharmacological toxicological assessments contribute high failure rates. To this end, identical devices fabricated from eight different prototypic physicochemical properties analyzed. It found overall primarily driven by compound hydrophobicity number rotatable bonds. differ >1000-fold between polydimethyl siloxane (PDMS) being absorptive, whereas polytetrafluoroethylene (PTFE) thiol-ene epoxy (TEE) absorbed least. Strikingly, organotypic primary liver cultures successfully flagged hydrophobic hepatotoxins lowly absorbing TEE at therapeutically relevant concentrations, isogenic PDMS resistant, resulting false negative safety signals. Combined, these results guide selection materials facilitate assays translatability.

Language: Английский

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Impact of Applicability Domains to Generative Artificial Intelligence

ACS Omega, Journal Year: 2023, Volume and Issue: 8(25), P. 23148 - 23167

Published: June 12, 2023

Molecular generative artificial intelligence is drawing significant attention in the drug design community, with several experimentally validated proof of concepts already published. Nevertheless, models are known for sometimes generating unrealistic, unstable, unsynthesizable, or uninteresting structures. This calls methods to constrain those algorithms generate structures drug-like portions chemical space. While concept applicability domains predictive well studied, its counterpart not yet well-defined. In this work, we empirically examine various possibilities and propose suited models. Using both public internal data sets, use novel that predicted be actives by a corresponding quantitative structure-activity relationships model while constraining stay within given domain. Our work looks at domain definitions, combining criteria, such as structural similarity training set, physicochemical properties, unwanted substructures, estimate drug-likeness. We assess generated from qualitative points view find definitions have strong influence on drug-likeness molecules. An extensive analysis our results allows us identify best molecules anticipate will help foster adoption an industrial context.

Language: Английский

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Identifying Substructures That Facilitate Compounds to Penetrate the Blood–Brain Barrier via Passive Transport Using Machine Learning Explainer Models

ACS Chemical Neuroscience, Journal Year: 2024, Volume and Issue: 15(11), P. 2144 - 2159

Published: May 9, 2024

The local interpretable model-agnostic explanation (LIME) method was used to interpret two machine learning models of compounds penetrating the blood–brain barrier. classification models, Random Forest, ExtraTrees, and Deep Residual Network, were trained validated using barrier penetration dataset, which shows penetrability in LIME able create explanations for such penetrability, highlighting most important substructures molecules that affect drug simple intuitive outputs prove applicability this explainable model interpreting permeability across terms molecular features. filtered with a weight equal or greater than 0.1 obtain only relevant explanations. results showed several structures are penetration. In general, it found some nitrogenous more likely permeate application these structural may help pharmaceutical industry potential synthesis research groups synthesize active rationally.

Language: Английский

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