Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein–ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein–ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models—the “lock-and-key”, “induced fit”, and “conformational selection”—are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein–ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed.

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Insights into Protein-Ligand Interactions: Mechanisms, Models, and Methods

The aim of this book volume is to explain the importance of Markov state models to molecular simulation, how they work, and how they can be applied to a range of problems.The Markov state model (MSM) approach aims to address two key challenges of molecular simulation:1) How to reach long timescales using short simulations of detailed molecular models.2) How to systematically gain insight from the resulting sea of data.MSMs do this by providing a compact representation of the vast conformational space available to biomolecules by decomposing it into states sets of rapidly interconverting conformations and the rates of transitioning between states. This kinetic definition allows one to[...]

An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation

Molecular dynamics simulations.

Studies of structure and dynamics of proteins using site-directed spin labelling rely on explicit modelling of spin label conformations. The large computational effort associated with such modelling with molecular dynamics (MD) simulations can be avoided by a rotamer library approach based on a coarse-grained representation of the conformational space of the spin label. We show here that libraries of about 200 rotamers, obtained by iterative projection of a long MD trajectory of the free spin label onto a set of canonical dihedral angles, provide a representation of the underlying trajectory adequate for EPR distance measurements. Rotamer analysis was performed on selected X-ray structures of spin labelled T4 lysozyme mutants to characterize the spin label rotamer ensemble on a single protein site. Furthermore, predictions based on the rotamer library approach are shown to be in nearly quantitative agreement with electron paramagnetic resonance (EPR) distance data on the Na+/H+ antiporter NhaA and on the light-harvesting complex LHCII whose structures are known from independent cryo electron microscopy and X-ray studies, respectively. Suggestions for the selection of labelling sites in proteins are given, limitations of the approach discussed, and requirements for further development are outlined.

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Rotamer libraries of spin labelled cysteines for protein studies

Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein–ligand applications. We summarise the main topics and recent computational and methodological advances in protein–ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.

Receptor–ligand molecular docking

https://www.cell.com/biophysj/pdf/S0006-3495(06)71978-6.pdf

A Structure-Based Simulation Approach for Electron Paramagnetic Resonance Spectra Using Molecular and Stochastic Dynamics Simulations

Importance of the field: Current computational docking methods are often effective in predicting accurate drug-binding geometries in cases of relatively rigid target structures. However, binding of drug-like ligands to protein receptor molecules frequently involves or even requires conformational adaptation. Realistic prediction of ligand–receptor binding geometries and complex stability needs in many cases an appropriate inclusion of conformational changes, not only for the ligand, but also for the receptor molecule.Areas covered in this review: Recent approaches to efficiently account for target receptor flexibility during docking simulations are reviewed.What the reader will gain: The reader will gain insights into methods to efficiently treat protein side-chain flexibility and approaches for continuous adaptation of backbone conformations in pre-calculated essential or soft collective degrees of freedom. In addition, molecular dynamics or Monte Carlo based methods providing simultaneous inclusion of r...

Tackling the challenges posed by target flexibility in drug design.

Molecular dynamics simulation and EPR spectroscopy of nitroxide side chains in bacteriorhodopsin

Group B Streptococcus pili are covalently linked structures assembled via a sortase-catalyzed transpeptidation mechanism involving specific residues and motifs. A sequence element containing a conserved glutamic acid, called the E-box, has been described to be involved in pilus formation. Although it is known that the glutamic acid is involved in stabilizing the internal isopeptide bonds, its role in pilus assembly still needs to be investigated. Using site-specific mutagenesis and complementation studies of knockout strains, we found that the E-box glutamic residue of the backbone and the major ancillary proteins is essential for pilus protein polymerization. NMR analysis revealed that the mutation of this residue seriously affected the folding of the protein. By contrast, the mutation of the lysine involved in the same isopeptide bond did not engender a structural destabilization, and the native fold was preserved. Moreover, molecular dynamics simulations on the E-box-containing domain of the backbone protein showed that the E-box glutamic acid is necessary to maintain the appropriate dryness of the domain core and that its mutation favors an unfolded state. The data provide the first direct evidence that the E-box has an additional and key role in maintaining the correct protein fold independently of isopeptide bond formation.

/pdf/new-insights-into-the-role-of-the-glutamic-acid-of-the-e-box-2gm5cu3ib3.pdf

Christian Beier

Papers

A Structure-Based Simulation Approach for Electron Paramagnetic Resonance Spectra Using Molecular and Stochastic Dynamics Simulations

Tackling the challenges posed by target flexibility in drug design.

Molecular dynamics simulation and EPR spectroscopy of nitroxide side chains in bacteriorhodopsin

New insights into the role of the glutamic acid of the E-box motif in group B Streptococcus pilus 2a assembly