AIMC Topic: Central Nervous System Agents

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Breaking barriers: Medicinal chemistry strategies and advanced in-silico approaches for overcoming the BBB and enhancing CNS penetration.

European journal of medicinal chemistry
Delivering small molecules to the brain and central nervous system (CNS) is greatly hindered by the restrictive blood-brain barrier (BBB), which selectively permits essential molecules while excluding toxic molecules. This selective permeability feat...

CNSGT: Generative Transformer for De Novo Drug Design Targeting the Central Nervous System.

Journal of chemical information and modeling
The design of novel central nervous system (CNS) drugs presents formidable challenges due to the restrictive nature of the blood-brain barrier, which imposes stringent physicochemical requirements. Recent advances in deep learning, particularly Trans...

GCN-BBB: Deep Learning Blood-Brain Barrier (BBB) Permeability PharmacoAnalytics with Graph Convolutional Neural (GCN) Network.

The AAPS journal
The Blood-Brain Barrier (BBB) is a selective barrier between the Central Nervous System (CNS) and the peripheral system, regulating the distribution of molecules. BBB permeability has been crucial in CNS-targeting drug development, such as glioblasto...

Molecular Generation for CNS Drug Discovery and Design.

ACS chemical neuroscience
Computational drug design is a rapidly evolving field, especially the latest breakthroughs in generative artificial intelligence (GenAI) to create new compounds. However, the potential of GenAI to address the challenges in designing central nervous s...

Prediction of the Extent of Blood-Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model.

Pharmaceutical research
INTRODUCTION: The unbound brain-to-plasma partition coefficient (K) is an essential parameter for predicting central nervous system (CNS) drug disposition using physiologically-based pharmacokinetic (PBPK) modeling. K values for specific compounds ar...

A Practical Method for Predicting Compound Brain Concentration-Time Profiles: Combination of PK Modeling and Machine Learning.

Molecular pharmaceutics
Given the aging populations in advanced countries globally, many pharmaceutical companies have focused on developing central nervous system (CNS) drugs. However, due to the blood-brain barrier, drugs do not easily reach the target area in the brain. ...

A novel open-access artificial-intelligence-driven platform for CNS drug discovery utilizing adult zebrafish.

Journal of neuroscience methods
BACKGROUND: Although zebrafish are increasingly utilized in biomedicine for CNS disease modelling and drug discovery, this generates big data necessitating objective, precise and reproducible analyses. The artificial intelligence (AI) applications ha...

CNSMolGen: A Bidirectional Recurrent Neural Network-Based Generative Model for De Novo Central Nervous System Drug Design.

Journal of chemical information and modeling
Central nervous system (CNS) drugs have had a significant impact on treating a wide range of neurodegenerative and psychiatric disorders. In recent years, deep learning-based generative models have shown great potential for accelerating drug discover...

Machine Learning Exploration of the Relationship Between Drugs and the Blood-Brain Barrier: Guiding Molecular Modification.

Pharmaceutical research
OBJECTIVE: This study aimed to improve the efficiency of pharmacotherapy for CNS diseases by optimizing the ability of drug molecules to penetrate the Blood-Brain Barrier (BBB).

Leading consumption patterns of psychoactive substances in Colombia: A deep neural network-based clustering-oriented embedding approach.

PloS one
The number of health-related incidents caused using illegal and legal psychoactive substances (PAS) has dramatically increased over two decades worldwide. In Colombia, the use of illicit substances has increased up to 10.3%, while the consumption alc...