AI Medical Compendium Topic:
Drug Design

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Cenderitide: structural requirements for the creation of a novel dual particulate guanylyl cyclase receptor agonist with renal-enhancing in vivo and ex vivo actions.

European heart journal. Cardiovascular pharmacotherapy
AIMS: Cenderitide is a novel dual natriuretic peptide (NP) receptor chimeric peptide activator, which targets the particulate guanylyl cyclase B (pGC-B) receptor and pGC-A unlike native NPs. Cenderitide was engineered to retain the anti-fibrotic prop...

A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction.

BioMed research international
Blood-brain barrier (BBB) is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM) is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM ...

Summarizing and visualizing structural changes during the evolution of biomedical ontologies using a Diff Abstraction Network.

Journal of biomedical informatics
Biomedical ontologies are a critical component in biomedical research and practice. As an ontology evolves, its structure and content change in response to additions, deletions and updates. When editing a biomedical ontology, small local updates may ...

Fully-automated synthesis of 16β-(18)F-fluoro-5α-dihydrotestosterone (FDHT) on the ELIXYS radiosynthesizer.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Noninvasive in vivo imaging of androgen receptor (AR) levels with positron emission tomography (PET) is becoming the primary tool in prostate cancer detection and staging. Of the potential (18)F-labeled PET tracers, (18)F-FDHT has clinically shown to...

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

BMC bioinformatics
BACKGROUND: Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when boun...

A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach.

Journal of computer-aided molecular design
The assessment of binding affinity between ligands and the target proteins plays an essential role in drug discovery and design process. As an alternative to widely used scoring approaches, machine learning methods have also been proposed for fast pr...

Applying machine learning techniques for ADME-Tox prediction: a review.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: Pharmacokinetics involves the study of absorption, distribution, metabolism, excretion and toxicity of xenobiotics (ADME-Tox). In this sense, the ADME-Tox profile of a bioactive compound can impact its efficacy and safety. Moreover, eff...

AI-Driven Design and Development of Nontoxic DYRK1A Inhibitors.

Journal of medicinal chemistry
Dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) is implicated in several human diseases, including DYRK1A syndrome, cancer, and neurodegenerative disorders such as Alzheimer's disease, making it a relevant therapeutic target. I...

Susana Vázquez Torres: the power of computational protein design.

Bulletin of the World Health Organization
Susana Vázquez Torres talks to Ana Lesher Treviño about AI-guided protein design for antivenoms and her aim to improve access to lifesaving treatments in low-resource settings.

Self-awareness of retrosynthesis via chemically inspired contrastive learning for reinforced molecule generation.

Briefings in bioinformatics
The recent progress of deep generative models in modeling complex real-world data distributions has enabled the generation of novel compounds with potential therapeutic applications for various diseases. However, most studies fail to optimize the pro...