Docking cholesterol to integral membrane proteins with Rosetta

Nuclear lipids in chromatin regulation: Biological roles, experimental approaches and existing challenges

Lipids are crucial for various cellular functions. Besides the storage of energy equivalents, these include forming membrane bilayers and serving as signaling molecules. While significant progress has been made in the comprehension of the molecular and cellular biology of lipids, their functions in the cell nucleus remain poorly understood. The main role of the eukaryotic cell nucleus is to provide an environment for the storage and regulation of chromatin which is a complex of DNA, histones, and associated proteins. Recent studies suggest that nuclear lipids play a role in chromatin regulation and epigenetics. Here, we discuss various experimental methods in lipid-chromatin research, including biophysical, structural, and cell biology approaches, pointing out their strengths and weaknesses. We take the view that nuclear lipids have a far more widespread impact on chromatin than is currently acknowledged. This gap in comprehension is mostly due to existing experimental challenges in the study of lipid-chromatin biology. Several new, interdisciplinary approaches are discussed that could aid in elucidating the roles of nuclear lipids in chromatin regulation and gene expression.

In Silico Tools to Score and Predict Cholesterol-Protein Interactions

Cholesterol is structurally distinct from other lipids, which confers it with singular roles in membrane organization and protein function. As a signaling molecule, cholesterol engages in discrete interactions with transmembrane, peripheral, and certain soluble proteins to control cellular responses. Accordingly, the cholesterol-protein interface is central to cholesterol-related diseases and is an essential consideration in drug design. However, cholesterol's hydrophobic, un-drug-like nature presents a unique challenge to traditional in silico analyses. In this Perspective, we survey a collection of tools designed to predict and evaluate cholesterol binding sites in proteins, including classical sequence motifs, molecular docking, template-based strategies, molecular dynamics simulations, and recent artificial intelligence approaches. We then comment on contemporary tools to evaluate ligand-protein interactions, their applicability to cholesterol, and the yet-untapped potential of cholesterol-protein interactions in human health and disease.

Targeting ion channels with ultra-large library screening for hit discovery

Ion channels play a crucial role in a variety of physiological and pathological processes, making them attractive targets for drug development in diseases such as diabetes, epilepsy, hypertension, cancer, and chronic pain. Despite the importance of ion channels in drug discovery, the vastness of chemical space and the complexity of ion channels pose significant challenges for identifying drug candidates. The use of in silico methods in drug discovery has dramatically reduced the time and cost of drug development and has the potential to revolutionize the field of medicine. Recent advances in computer hardware and software have enabled the screening of ultra-large compound libraries. Integration of different methods at various scales and dimensions is becoming an inevitable trend in drug development. In this review, we provide an overview of current state-of-the-art computational chemistry methodologies for ultra-large compound library screening and their application to ion channel drug discovery research. We discuss the advantages and limitations of various in silico techniques, including virtual screening, molecular mechanics/dynamics simulations, and machine learning-based approaches. We also highlight several successful applications of computational chemistry methodologies in ion channel drug discovery and provide insights into future directions and challenges in this field.