Ligand binding by macromolecules represents a core event of broad relevance to a range of systems, including catalytic systems alongside noncatalytic systems such as nucleic acid binding by transcription factors or extracellular ligand binding by proteins involved in signaling pathways. The scope of this primer is constrained to introduce only foundational models without significant discussion of more advanced topics such as allosteric or linkage effects. Linkage occurs when the binding of a ligand is influenced by the binding of another molecule of the same ligand (homotropic linkage), the binding of a different ligand (heterotropic linkage), physical variables such as temperature or pressure (physical linkage), or changes in macromolecular assembly state (polysteric linkage). Taking this into account, the foundational themes presented in this primer can be used to describe any macromolecule–ligand interaction either by direct use of the models and techniques described here or by applying them to develop more advanced models to explain additional complexities such as those allosteric or linkage effects just mentioned. The target audience of this primer is the senior undergraduate or junior graduate student who lacks a foundation in ligand-binding thermodynamics. As such, we have focused primarily on foundational thermodynamic treatments and presented only general discussions of relevant experimental designs. Readers of this primer will learn how to build a working understanding of common factors that promote energetic favorability for ligand binding; develop a functional toolbox to understand ligand binding from the perspective of collecting, plotting, and interpreting ligand-binding data; enhance proficiency in deriving thermodynamic mechanisms for ligand binding; and become comfortable in interpreting binding data reported in the literature and independently expanding knowledge beyond the scope introduced in this primer.

This practical reference for medicinal and pharmaceutical chemists combines the theoretical background with modern methods as well as applications from recent lead finding and optimization projects. Divided into two parts on the thermodynamics and kinetics of drug-receptor interaction, the text provides the conceptual and methodological basis for characterizing binding mechanisms for drugs and other bioactive molecules. It covers all currently used methods, from experimental approaches, such as ITC or SPR, right up to the latest computational methods. Case studies of real-life lead or drug development projects are also included so readers can apply the methods learned to their own projects. Finally, the benefits of a thorough binding mode analysis for any drug development project are summarized in an outlook chapter written by the editors.

Free energy constitutes the most important thermodynamic quantity to understand how chemical species recognize each other, associate or react. Examples of problems in which knowledge of the underlying free energy behaviour is required, include conformational equilibria and molecular association, partitioning between immiscible liquids, receptor-drug interaction, protein-protein and protein-DNA association, and protein stability. This volume sets out to present a coherent and comprehensive account of the concepts that underlie different approaches devised for the determination of free energies. The reader will gain the necessary insight into the theoretical and computational foundations of the subject and will be presented with relevant applications from molecular-level modelling and simulations of chemical and biological systems. Both formally accurate and approximate methods are covered using both classical and quantum mechanical descriptions. A central theme of the book is that the wide variety of free energy calculation techniques available today can be understood as different implementations of a few basic principles. The book is aimed at a broad readership of graduate students and researchers having a background in chemistry, physics, engineering and physical biology.

Conformational dynamics is often essential for a protein's function. For example, proteins are able to communicate the effect of binding at one site to a distal region of the molecule through changes in its conformational dynamics. This so called allosteric coupling fine tunes the sensitivity of ligand binding to changes in concentration. A conformational change between a "closed" (apo) and an "open" (holo) conformation upon ligation often produces this coupling between binding sites. Enhanced sensitivity between the unbound and bound ensembles leads to a sharper binding curve. There are two basic conceptual frameworks that guide our visualization about ligand binding mechanisms. First, a ligand can stabilize the unstable "open" state from a dynamic ensemble of conformations within the unbound basin. This binding mechanism is called conformational selection. Second, a ligand can weakly bind to the low-affinity "closed" state followed by a conformational transition to the "open" state. This is called induced fit binding.In this dissertation, I focus on molecular dynamics simulations to understand microscopic origins of ligand binding cooperativity. A minimal model of allosteric binding transitions must include ligand binding/unbinding events, while capturing the transition mechanism between two distinct meta-stable free energy basins. Due in part to computational timescales limitations, work in this dissertation describes large-scale conformational transitions through a simplified, coarse-grained model based on the energy basins defined by the open and closed conformations of the protein Calmodulin (CaM). CaM is a ubiquitous calcium-binding protein consisting of two structurally similar globular domains connected by a flexible linker. The two domains of CaM, N-terminal domain (nCaM) and C-terminal domain (cCaM) consists of two helix-loop-helix motifs (the EF-hands) connected by a flexible linker. Each domain of CaM consists of two binding loops and binds 2 calcium ions each. The intact domain binds up to 4 calcium ions. The simulations use a coupled molecular dynamics/monte carlo scheme where the protein dynamics is simulated explicitly, while ligand binding/unbinding are treated implicitly. This helps us characterize complementary thermodynamic and kinetic description of calcium binding mechanism to CaM.In the model, ligand binding/unbinding events coupled with a conformational change of the protein within the grand canonical ensemble. Here, ligand concentration is controlled through the chemical potential (μ). This allows us to use a simple thermodynamic model to analyze the simulated data and quantify binding cooperativity. Simulated binding titration curves are calculated through equilibrium simulations at different values of μ.First, I study domain opening transitions of isolated nCaM and cCaM in the absence of calcium. This work is motivated by results from a recent analytic variational model that predicts distinct domain opening transition mechanism for the domains of CaM. This is a surprising result because the domains have the same folded state topology. In the simulations, I find the two domains of CaM have distinct transition mechanism over a broad range of temperature, in harmony with the analytic predictions. In particular, the simulated transition mechanism of nCaM follows a two-state behavior, while domain opening in cCaM involves global unfolding and refolding of the tertiary structure. The unfolded intermediate also appears in the landscape of nCaM, but at a higher temperature than it appears in cCaM's energy landscape. This is consistent with nCaM's higher thermal stability. Under approximate physiological conditions, majority of the sampled transitions in cCaM involves unfolding and refolding during conformational change. Kinetically, the transient unfolding and refolding in cCaM significantly slows the domain opening and closing rates in cCaM.Second, I investigate the structural origins of binding affinity and allosteric cooperativity of binding 2 calcium-ions to each domain of CaM. In my work, I predict the order of binding strength of CaM's loops. I analyze simulated binding curves within the framework of the classic Monod-Wyman-Changeux (MWC) model of allostery to extract the binding free energies to the closed and open ensembles. The simulations predict that cCaM binds calcium with higher affinity and greater cooperativity than nCaM. Where it is possible to compare, these predictions are in good agreement with experimental results. The analysis of the simulations offers a rationale for why the two domains differ in cooperativity: the higher cooperativity of cCaM is due to larger difference in affinity of its binding loops.Third, I extend the work to investigate structural origins of binding cooperativity of 4 calcium-ions to intact CaM. I characterize the microscopic cooperativities of each ligation state and provide a kinetic description of the binding mechanism. Due to the heterogeneous nature of CaM's loops, as predicted in our simulations of isolated domains, I focus on investigating the influence of this heterogeneity on the kinetic flux of binding pathways as a function of concentration. The formalism developed for Network Models of protein folding kinetics, is used to evaluate the directed flux of all possible pathways between unligated and fully loaded CaM.

Machine learning methods such as neural networks, non-linear dimensionality reduction techniques, random forests and others meet in this research topic with biomolecular simulations. The authors of eight articles applied these methods to analyze simulation results, accelerate simulations or to make molecular mechanics force fields more accurate.

Proteins are the cell’s workers, their messengers and overseers. In these roles, proteins specifically bind small molecules, nucleic acid and other protein partners. Cellular systems are closely regulated and biologically significant changes in populations of particular protein complexes correspond to very small variations of their thermodynamics or kinetics of reaction. Interfering with the interactions of proteins is the dominant strategy in the development of new pharmaceuticals. Protein Ligand Interactions: Methods and Applications, Second Edition provides a complete introduction to common and emerging procedures for characterizing the interactions of individual proteins. From the initial discovery of natural substrates or potential drug leads, to the detailed quantitative understanding of the mechanism of interaction, all stages of the research process are covered with a focus on those techniques that are, or are anticipated to become, widely accessible and performable with mainstream commercial instrumentation. Written in the highly successful Methods in Molecular Biology series format, chapters contain introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and accessible, Protein Ligand Interactions: Methods and Applications, Second Edition serves as an ideal guide for researchers new to the field of biophysical characterization of protein interactions – whether they are beginning graduate students or experts in allied areas of molecular cell biology, microbiology, pharmacology, medicinal chemistry or structural biology.