Studies of protein–ligand interactions by NMR

2003 ◽  
Vol 31 (5) ◽  
pp. 1006-1009 ◽  
Author(s):  
J. Clarkson ◽  
I.D. Campbell
Keyword(s):  
Chemical Shift ◽  
Structure Determination ◽  
Dissociation Constants ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Ligand Complex ◽  
Protein Ligand Interactions ◽  
Small Proteins ◽  
Ligand Interactions

Solution-state NMR has become an accepted method for studying the structure of small proteins in solution. This has resulted in over 3000 NMR-based co-ordinate sets being deposited in the Protein Databank. It is becoming increasingly apparent, however, that NMR is also a very powerful tool for accessing interactions between macromolecules and various ligands. These interactions can be assessed at a wide variety of levels, e.g. qualitative screening of libraries of pharmaceuticals and ‘chemical shift mapping’. Dissociation constants can sometimes be obtained in such cases. Another example would be the complete three-dimensional structure determination of a protein–ligand complex. Here we briefly describe a few of the principles involved and illustrate the method with recent examples.

scholarly journals Layer-wise relevance propagation of InteractionNet explains protein–ligand interactions at the atom level

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hyeoncheol Cho ◽  
Eok Kyun Lee ◽  
Insung S. Choi
Keyword(s):  
Dissociation Constants ◽  
Structural Information ◽  
Three Dimensional ◽  
Graph Representation ◽  
Ligand Complex ◽  
Covalent Bonds ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Atom Level ◽  
Graph Neural Networks

AbstractDevelopment of deep-learning models for intermolecular noncovalent (NC) interactions between proteins and ligands has great potential in the chemical and pharmaceutical tasks, including structure–activity relationship and drug design. It still remains an open question how to convert the three-dimensional, structural information of a protein–ligand complex into a graph representation in the graph neural networks (GNNs). It is also difficult to know whether a trained GNN model learns the NC interactions properly. Herein, we propose a GNN architecture that learns two distinct graphs—one for the intramolecular covalent bonds in a protein and a ligand, and the other for the intermolecular NC interactions between the protein and the ligand—separately by the corresponding covalent and NC convolutional layers. The graph separation has some advantages, such as independent evaluation on the contribution of each convolutional step to the prediction of dissociation constants, and facile analysis of graph-building strategies for the NC interactions. In addition to its prediction performance that is comparable to that of a state-of-the art model, the analysis with an explainability strategy of layer-wise relevance propagation shows that our model successfully predicts the important characteristics of the NC interactions, especially in the aspect of hydrogen bonding, in the chemical interpretation of protein–ligand binding.

scholarly journals High-resolution cryo-EM proteasome structures in drug development

2017 ◽  
Vol 73 (6) ◽  
pp. 522-533 ◽  
Author(s):  
Edward P. Morris ◽  
Paula C. A. da Fonseca
Keyword(s):  
Structure Determination ◽  
Protein Structures ◽  
Three Dimensional ◽  
Specific Inhibitor ◽  
Particle Analysis ◽  
20S Proteasome ◽  
Ligand Specificity ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Dimensional Reconstruction

With the recent advances in biological structural electron microscopy (EM), protein structures can now be obtained by cryo-EM and single-particle analysis at resolutions that used to be achievable only by crystallographic or NMR methods. We have explored their application to study protein–ligand interactions using the human 20S proteasome, a well established target for cancer therapy that is also being investigated as a target for an increasing range of other medical conditions. The map of a ligand-bound human 20S proteasome served as a proof of principle that cryo-EM is emerging as a realistic approach for more general structural studies of protein–ligand interactions, with the potential benefits of extending such studies to complexes that are unfavourable to other methods and allowing structure determination under conditions that are closer to physiological, preserving ligand specificity towards closely related binding sites. Subsequently, the cryo-EM structure of thePlasmodium falciparum20S proteasome, with a new prototype specific inhibitor bound, revealed the molecular basis for the ligand specificity towards the parasite complex, which provides a framework to guide the development of highly needed new-generation antimalarials. Here, the cryo-EM analysis of the ligand-bound human andP. falciparum20S proteasomes is reviewed, and a complete description of the methods used for structure determination is provided, including the strategy to overcome the bias orientation of the human 20S proteasome on electron-microscope grids and details of theicr3dsoftware used for three-dimensional reconstruction.

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