Linked drug-drug conjugates based on triterpene and phenol structures. Rational synthesis, molecular properties, toxicity and bioactivity prediction

Die Therapielandschaft des metastasierten Urothelkarzinoms hat sich seit der Zulassung der ersten Immun-Checkpoint-Inhibitoren verändert. Die neuen Therapien sind deutlich effektiver, allerdings erreichen die Responseraten der neuen Therapien nur bis zu etwa 30 %, beklagte Prof. Matthew Milowsky, Chapel Hill/USA, auf einer Oral Abstract Session auf dem ASCO-GU. In San Francisco gaben erste Vorträge und Poster bereits einen Einblick, wovon diejenigen Patienten profitieren könnten, die auf die etablierten Chemotherapien und die neuen Immuntherapien nicht ansprechen. Manche Onkologen sprechen bereits von der „Post-Checkpoint-Ära”. Als Kandidaten werden vor allem Antikörper-Wirkstoff-Konjugate (antibody-drug conjugates; ADC) gehandelt – und zwar nicht nur zur Therapie des metastasierten Blasenkarzinoms.

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A Thorough Theoretical Exploration of Intriguing Characteristics of Cyclo[18]carbon: Geometry, Bonding Nature, Aromaticity, Weak Interaction, Reactivity, Excited States, Vibrations, Molecular Dynamics and Various Molecular Properties

10.26434/chemrxiv.11320130.v1 ◽

2019 ◽

Cited By ~ 2

Author(s):

Tian Lu ◽

Qinxue Chen ◽

Zeyu Liu

Keyword(s):

Molecular Dynamics ◽

Excited States ◽

Electronic Excitation ◽

Ring Structure ◽

Molecular Properties ◽

Molecular Vibration ◽

Full Characterization ◽

Long Time ◽

Almost All

Although cyclo[18]carbon has been theoretically and experimentally investigated since long time ago, only very recently it was prepared and directly observed by means of STM/AFM in condensed phase (Kaiser et al., Science, 365, 1299 (2019)). The unique ring structure and dual 18-center π delocalization feature bring a variety of unusual characteristics and properties to the cyclo[18]carbon, which are quite worth to be explored. In this work, we present an extremely comprehensive and detailed investigation on almost all aspects of the cyclo[18]carbon, including (1) Geometric characteristics (2) Bonding nature (3) Electron delocalization and aromaticity (4) Intermolecular interaction (5) Reactivity (6) Electronic excitation and UV/Vis spectrum (7) Molecular vibration and IR/Raman spectrum (8) Molecular dynamics (9) Response to external field (10) Electron ionization, affinity and accompanied process (11) Various molecular properties. We believe that our full characterization of the cyclo[18]carbon will greatly deepen researchers' understanding of this system, and thereby help them to utilize it in practice and design its various valuable derivatives.

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A Thorough Theoretical Exploration of Intriguing Characteristics of Cyclo[18]carbon: Geometry, Bonding Nature, Aromaticity, Weak Interaction, Reactivity, Excited States, Vibrations, Molecular Dynamics and Various Molecular Properties

10.26434/chemrxiv.11320130 ◽

2019 ◽

Cited By ~ 2

Author(s):

Tian Lu ◽

Qinxue Chen ◽

Zeyu Liu

Keyword(s):

Molecular Dynamics ◽

Excited States ◽

Electronic Excitation ◽

Ring Structure ◽

Molecular Properties ◽

Molecular Vibration ◽

Full Characterization ◽

Long Time ◽

Almost All

Although cyclo[18]carbon has been theoretically and experimentally investigated since long time ago, only very recently it was prepared and directly observed by means of STM/AFM in condensed phase (Kaiser et al., Science, 365, 1299 (2019)). The unique ring structure and dual 18-center π delocalization feature bring a variety of unusual characteristics and properties to the cyclo[18]carbon, which are quite worth to be explored. In this work, we present an extremely comprehensive and detailed investigation on almost all aspects of the cyclo[18]carbon, including (1) Geometric characteristics (2) Bonding nature (3) Electron delocalization and aromaticity (4) Intermolecular interaction (5) Reactivity (6) Electronic excitation and UV/Vis spectrum (7) Molecular vibration and IR/Raman spectrum (8) Molecular dynamics (9) Response to external field (10) Electron ionization, affinity and accompanied process (11) Various molecular properties. We believe that our full characterization of the cyclo[18]carbon will greatly deepen researchers' understanding of this system, and thereby help them to utilize it in practice and design its various valuable derivatives.

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A Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Ligand-Target Predictions

10.26434/chemrxiv.11526132 ◽

2020 ◽

Author(s):

Lewis Mervin ◽

Avid M. Afzal ◽

Ola Engkvist ◽

Andreas Bender

Keyword(s):

Target Prediction ◽

Support Vector ◽

Machine Learning Method ◽

Learning Method ◽

Protein Target ◽

Bioactivity Prediction ◽

Vector Machines ◽

Scaling Methods ◽

Data Points ◽

Compound Target

In the context of bioactivity prediction, the question of how to calibrate a score produced by a machine learning method into reliable probability of binding to a protein target is not yet satisfactorily addressed. In this study, we compared the performance of three such methods, namely Platt Scaling, Isotonic Regression and Venn-ABERS in calibrating prediction scores for ligand-target prediction comprising the Naïve Bayes, Support Vector Machines and Random Forest algorithms with bioactivity data available at AstraZeneca (40 million data points (compound-target pairs) across 2112 targets). Performance was assessed using Stratified Shuffle Split (SSS) and Leave 20% of Scaffolds Out (L20SO) validation.

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Design, 22-step synthesis, and evaluation of highly potent D-ring modified and linker-equipped analogs of spongistatin 1

10.26434/chemrxiv.5773830.v1 ◽

2018 ◽

Author(s):

James Leighton ◽

Linda M. Suen ◽

Makeda A. Tekle-Smith ◽

Kevin S. Williamson ◽

Joshua R. Infantine ◽

...

Keyword(s):

Targeted Delivery ◽

Functional Group ◽

Human Cancer ◽

Natural Sources ◽

Spongistatin 1 ◽

Human Cancer Cell Lines ◽

Drug Conjugates ◽

Attractive Candidate ◽

Complex Fragment ◽

Antibody Drug

With an average GI50 value against the NCI panel of 60 human cancer cell lines of 0.12 nM, spongistatin 1 is among the most potent anti-proliferative agents ever discovered rendering it an attractive candidate for development as a payload for antibody-drug conjugates and other targeted delivery approaches. It is unavailable from natural sources and its size and complex stereostructure render chemical synthesis highly time- and resource-intensive, however, and its development requires more efficient and step-economical synthetic access. Using novel and uniquely enabling direct complex fragment coupling alkallyl- and crotylsilylation reactions, we have developed a 22-step synthesis of a rationally designed D-ring modified analog of spongistatin 1 that is equipotent with the natural product, and have used that synthesis to establish that the C(15) acetate may be replaced with a linker functional group-bearing ester with only minimal reductions in potency. <div> </div>

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Accurate and Transferable Multitask Prediction of Chemical Properties with an Atoms-in-Molecule Neural Network

10.26434/chemrxiv.7151435.v2 ◽

2018 ◽

Author(s):

Roman Zubatyuk ◽

Justin S. Smith ◽

Jerzy Leszczynski ◽

Olexandr Isayev

Keyword(s):

Neural Network ◽

Molecular System ◽

Computational Cost ◽

Chemical Properties ◽

The State ◽

Molecular Properties ◽

Training Data ◽

Dft Methods ◽

Benchmark Datasets ◽

Quantum Phenomena

Atomic and molecular properties could be evaluated from the fundamental Schrodinger’s equation and therefore represent different modalities of the same quantum phenomena. Here we present AIMNet, a modular and chemically inspired deep neural network potential. We used AIMNet with multitarget training to learn multiple modalities of the state of the atom in a molecular system. The resulting model shows on several benchmark datasets the state-of-the-art accuracy, comparable to the results of orders of magnitude more expensive DFT methods. It can simultaneously predict several atomic and molecular properties without an increase in computational cost. With AIMNet we show a new dimension of transferability: the ability to learn new targets utilizing multimodal information from previous training. The model can learn implicit solvation energy (like SMD) utilizing only a fraction of original training data, and archive MAD error of 1.1 kcal/mol compared to experimental solvation free energies in MNSol database.

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Thienopyrrolocarbazoles: New Building Blocks for Functional Organic Materials

10.26434/chemrxiv.7777343.v1 ◽

2019 ◽

Cited By ~ 1

Author(s):

Dorian Bader ◽

Johannes Fröhlich ◽

Paul Kautny

Keyword(s):

Building Block ◽

Organic Materials ◽

Building Blocks ◽

Molecular Properties ◽

The Family ◽

Facile Preparation

The facile preparation of three regioisomeric thienopyrrolocarbazoles applying a convenient C-H activation approach is presented. Derived from indolo[3,2,1-jk]carbazole, the incorporation of thiophene into the triarylamine framework significantly impacted the molecular properties of the parent scaffold. The developed thienopyrrolocarbazoles enrich the family of triarylamine donors and constitute a novel building block for functional organic materials.

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