AIMC Topic: Immunoconjugates

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Linker-GPT: design of Antibody-drug conjugates linkers with molecular generators and reinforcement learning.

Scientific reports
The stability and therapeutic efficacy of antibody-drug conjugates (ADCs) are critically determined by the chemical linkers that connect the antibody to the cytotoxic payload, which is a key factor influencing drug release, plasma stability, and off-...

The latest advances with natural products in drug discovery and opportunities for the future: a 2025 update.

Expert opinion on drug discovery
INTRODUCTION: The landscape of drug discovery is rapidly evolving, with natural products (NPs) playing a pivotal role in the development of novel therapeutics. Despite their historical significance, challenges persist in fully harnessing their potent...

Machine Learning for Predicting the Drug-to-Antibody Ratio (DAR) in the Synthesis of Antibody-Drug Conjugates (ADCs).

Journal of chemical information and modeling
The pharmaceutical industry faces challenges in developing efficient and cost-effective drug delivery systems. Among various applications, antibody-drug conjugates (ADCs) stand out by combining cytotoxic or bioactive agents with monoclonal antibodies...

A high hydrophobic moment arginine-rich peptide screened by a machine learning algorithm enhanced ADC antitumor activity.

Journal of peptide science : an official publication of the European Peptide Society
Cell-penetrating peptides (CPPs) with better biomolecule delivery properties will expand their clinical applications. Using the MLCPP2.0 machine algorithm, we screened multiple candidate sequences with potential cellular uptake ability from the nucle...

Quantifying drug tissue biodistribution by integrating high content screening with deep-learning analysis.

Scientific reports
Quantitatively determining in vivo achievable drug concentrations in targeted organs of animal models and subsequent target engagement confirmation is a challenge to drug discovery and translation due to lack of bioassay technologies that can discrim...

Electrochemiluminescent detection of cardiac troponin I by using soybean peroxidase labeled-antibody as signal amplifier.

Talanta
This work proposed an electrochemiluminescence (ECL) immunosensor for quantitative monitoring of cardiac troponin I (cTnI) in plasma with soybean peroxidase (SBP) labeled-antibody as signal amplifier. The ECL sandwich immunosensor was constructed by ...

Harnessing computational technologies to facilitate antibody-drug conjugate development.

Nature chemical biology
Antibody-drug conjugates (ADCs) represent a powerful therapeutic approach for the treatment of a range of cancers. They merge the toxicity of known chemical agents with the specificity of monoclonal antibodies, thereby maximizing efficacy while minim...

The Icarian flight of antibody-drug conjugates: target selection amidst complexity and tackling adverse impacts.

Protein & cell
Antibody-drug conjugates (ADCs) represent a promising class of targeted cancer therapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic payloads. Despite their therapeutic potential, the use of ADCs faces signi...

Molecular glue meets antibody: next-generation antibody-drug conjugates.

Trends in pharmacological sciences
Antibody-drug conjugates (ADCs) have revolutionized oncology by enabling the delivery of cytotoxic agents. However, persistent limitations in payload diversity and emerging drug-resistance mechanisms have spurred investigations into innovative payloa...

Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on the Chemical Structure.

International journal of molecular sciences
Antibody-drug conjugates (ADCs) are promising cancer therapeutics, but optimizing their cytotoxic payloads remains challenging. We present DumplingGNN, a novel hybrid Graph Neural Network architecture for predicting ADC payload activity and toxicity....