AIMC Topic: Protein Binding

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Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach.

Scientific reports
The bacterial cell division protein FtsZ, a crucial GTPase, plays a vital role in the formation of the contractile Z-ring, which is essential for bacterial cytokinesis. Consequently, inhibiting FtsZ could prevent the formation of proto-filaments and ...

Encoding and decoding selectivity and promiscuity in the human chemokine-GPCR interaction network.

Cell
In humans, selective and promiscuous interactions between 46 secreted chemokine ligands and 23 cell surface chemokine receptors of the G-protein-coupled receptor (GPCR) family form a complex network to coordinate cell migration. While chemokines and ...

Recognition of Specific PIP2-subtype Composition Triggers the Allosteric Control Mechanism for Selective Membrane Targeting of Cargo Loading and Release Functions of the Intracellular Sterol Transporter StarD4.

Journal of molecular biology
We present a comprehensive, quantitative model of the allosteric molecular mechanisms of selective cholesterol (CHL) uptake and delivery by the StarD4 protein - an intracellular cholesterol trafficking protein that facilitates the crucial non-vesicul...

In silico design of ankyrin repeat proteins that bind to the insulin-like growth factor type 1 receptor.

Journal of molecular graphics & modelling
Ankyrins are proteins widely distributed in nature that mediate protein‒protein interactions. Owing to their outstanding stability and ability to recognize targets, ankyrins have been used as therapeutic and diagnostic tools in several diseases, incl...

A comprehensive review of computational methods for Protein-DNA binding site prediction.

Analytical biochemistry
Accurately identifying protein-DNA binding sites is essential for understanding the molecular mechanisms underlying biological processes, which in turn facilitates advancements in drug discovery and design. While biochemical experiments provide the m...

QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials.

Journal of chemical information and modeling
Accurate prediction of protein-ligand binding affinities is crucial in drug discovery, particularly during hit-to-lead and lead optimization phases, however, limitations in ligand force fields continue to impact prediction accuracy. In this work, we ...

Edge-enhanced interaction graph network for protein-ligand binding affinity prediction.

PloS one
Protein-ligand interactions are crucial in drug discovery. Accurately predicting protein-ligand binding affinity is essential for screening potential drugs. Graph neural networks have proven highly effective in modeling spatial relationships and thre...

Persistent Directed Flag Laplacian (PDFL)-Based Machine Learning for Protein-Ligand Binding Affinity Prediction.

Journal of chemical theory and computation
Directionality in molecular and biomolecular networks plays an important role in the accurate representation of the complex, dynamic, and asymmetrical nature of interactions present in protein-ligand binding, signal transduction, and biological pathw...

Integrating deep learning and molecular dynamics simulations for FXR antagonist discovery.

Molecular diversity
Farnesoid X receptor (FXR) is a key regulator of bile acid, lipid, and glucose homeostasis, making it a promising target for treating metabolic diseases. FXR antagonists have shown therapeutic potential in cholestasis, metabolic disorders, and certai...