AIMC Topic: Small Molecule Libraries

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Enabling Open Machine Learning of Deoxyribonucleic Acid-Encoded Library Selections to Accelerate the Discovery of Small Molecule Protein Binders.

Journal of medicinal chemistry
Machine learning (ML) is increasingly used in DNA-encoded library (DEL) screening for ligand discovery, but its success depends on access to suitable data sets, which are often proprietary and costly. To overcome this, we present the first fully open...

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...

Rethinking Retrosynthesis: Curriculum Learning Reshapes Transformer-Based Small-Molecule Reaction Prediction.

Journal of chemical information and modeling
Retrosynthesis prediction remains a central challenge in computational chemistry, particularly when models must generalize to rare or structurally complex reactions. We present a curriculum learning (CL) framework that reshapes model training by syst...

Freedom Space 3.0: ML-Assisted Selection of Synthetically Accessible Small Molecules.

Journal of chemical information and modeling
Advances in machine learning (ML) have revolutionized the exploration of chemical space, enabling the creation of subsets tailored for specific applications. Herein, we describe the development of Chemspace Freedom Space 3.0, a chemical library of sy...

Enhancing accuracy of virtual kinase profiling via application of graph neural network to 3D pharmacophore ensembles.

Journal of computer-aided molecular design
Kinase profiling is an essential step in both hit identification and selectivity evaluation. Since in vitro testing of large chemical libraries is costly and time-consuming, a computational approach can be applied to narrow down the reasonable chemic...

Development and Validation of an Automated DNA-Encoded Library Screening Data Analysis Platform: PB-DEL Autoscreening Analysis (PB-DELASA).

Journal of chemical information and modeling
Tools available for analyzing next-generation sequencing (NGS) data produced from DNA-encoded library (DEL) screening campaigns are often constrained to customized methods developed internally by individual institutes, which usually generate data spe...

BIOPTIC B1 Ultra-High-Throughput Virtual Screening System Discovers LRRK2 Ligands in Vast Chemical Space.

Journal of chemical information and modeling
The rapid expansion of chemical space presents significant challenges in identifying novel ligands for drug targets. Here, we introduce BIOPTIC B1, an ultra-high-throughput ligand-based virtual screening system capable of rapidly evaluating multi-bil...

Practically Significant Method Comparison Protocols for Machine Learning in Small Molecule Drug Discovery.

Journal of chemical information and modeling
Machine Learning (ML) methods that relate molecular structure to properties are frequently proposed as in silico surrogates for expensive or time-consuming experiments. In small molecule drug discovery, such methods inform high-stakes decisions like ...

Advances and Challenges in Machine Learning for RNA-Small Molecule Interaction Modeling: Review.

Journal of chemical theory and computation
RNA plays a pivotal role in biological processes such as gene expression regulation and protein synthesis. Targeting RNA with small molecules offers a novel therapeutic strategy for various diseases by directly modulating these processes. However, th...

Machine Learning-Assisted Iterative Screening for Efficient Detection of Drug Discovery Starting Points.

Journal of medicinal chemistry
High-throughput screening (HTS) remains central to small molecule lead discovery, but increasing assay complexity challenges the screening of large compound libraries. While retrospective studies have assessed active-learning-guided screening, extens...