Search PubMed⌕ Search

PubMed · 15584863

Hitting multiple targets with multimeric ligands.

Abstract

Multimeric ligands consist of multiple monomeric ligands attached to a single backbone molecule, creating a multimer that can bind to multiple receptors or targets simultaneously. Numerous examples of multimeric binding exist within nature. Due to the multiple and simultaneous binding events, multimeric ligands bind with an increased affinity compared to their corresponding monomers. Multimeric ligands may provide opportunities in the field of drug discovery by providing enhanced selectivity and affinity of binding interactions, thus providing molecular-based targeted therapies. However, gaps in our knowledge currently exist regarding the quantitative measures for important design characteristics, such as flexibility, length and orientation of the inter-ligand linkers, receptor density and ligand sequence. In this review, multimeric ligand binding in two separate phases is examined. The prerecruitment phase describes the binding of one ligand of a multimer to its corresponding receptor, an event similar to monomeric ligand binding. This results in transient increases in the local concentration of the other ligands, leading to apparent cooperativity. The postrecruitment phase only occurs once all receptors have been aligned and bound by their corresponding ligand. This phase is analogous to DNA-DNA interactions in that the stability of the complex is derived from physical orientation. Multiple factors influence the kinetics and thermodynamics of multimeric binding, and these are discussed.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Heather L Handl, Josef Vagner, Haiyong Han, Eugene Mash, Victor J Hruby, Robert J Gillies. 2004. Hitting multiple targets with multimeric ligands.. https://doi.org/10.1517/14728222.8.6.565

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Deep generative neural network for accurate drug response imputation.

Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study, we develop a deep variational autoencoder (VAE) model to compress thousands of genes into latent vectors in a low-dimensional space. We then demonstrate that these encoded vectors could accurately impute drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. We apply rigorous quality assessment and validation, including assessing the impact of cell line lineage, cross-validation, cross-panel evaluation, and application in independent clinical data sets, to warrant the accuracy of the imputed drug response in both cell lines and cancer samples. Specifically, the expression-regulated component (EReX) of the observed drug response achieves high correlation across panels. Using the well-trained models, we impute drug response of The Cancer Genome Atlas data and investigate the features and signatures associated with the imputed drug response, including cell line origins, somatic mutations and tumor mutation burdens, tumor microenvironment, and confounding factors. In summary, our deep learning method and the results are useful for the study of signatures and markers of drug response.

Antineoplastic Agents↗

Favorable response of intraommaya topotecan for leptomeningeal metastasis of neuroblastoma after intravenous route failure.

A 3-year-old male, diagnosed with stage 4 neuroblastoma, developed recurrent leptomeningeal metastasis after multi-modality treatment including multi-agent chemotherapy, surgery, high dose chemotherapy plus stem cell rescue, cis-retinoic acid and intravenous (IV) topotecan. He then received intraommaya (IO) topotecan three times weekly (maximum dose; 0.4 mg). A complete response was achieved by a resolution of malignant cells in cerebrospinal fluid and resolution leptomeningeal enhancement by brain MRI. Treatment toxicities included low-grade fever and minimal headache. The duration of treatment response from IO topotecan was 18 weeks. The survival time from CNS recurrence in this patient was 13 months. We suggest IO topotecan be considered for neoplastic meningitis of tumors with known sensitivity to topotecan.

Antineoplastic Agents↗

Extracorporeal membrane oxygenation (ECMO) initiation without intubation in two children with mediastinal malignancy.

We report the cases of two children presenting with severe airway compromise secondary to a mediastinal malignancy managed with extracorporeal membrane oxygenation without intubation. Results are presented on the use of ECMO as a primary means of stabilizing a pediatric patient with a critical mediastinal mass, thus providing another management strategy for this difficult situation.

Antineoplastic Agents↗