This book discusses how biological molecules exert their function and regulate biological processes, with a clear focus on how conformational dynamics of proteins are critical in this respect. In the last decade, the advancements in computational biology, nuclear magnetic resonance including paramagnetic relaxation enhancement, and fluorescence-based ensemble/single-molecule techniques have shown that biological molecules (proteins, DNAs and RNAs) fluctuate under equilibrium conditions. The conformational and energetic spaces that these fluctuations explore likely contain active conformations that are critical for their function. More interestingly, these fluctuations can respond actively to external cues, which introduces layers of tight regulation on the biological processes that they dictate. A growing number of studies have suggested that conformational dynamics of proteins govern their role in regulating biological functions, examples of this regulation can be found in signal transduction, molecular recognition, apoptosis, protein / ion / other molecules translocation and gene expression. On the experimental side, the technical advances have offered deep insights into the conformational motions of a number of proteins. These studies greatly enrich our knowledge of the interplay between structure and function. On the theoretical side, novel approaches and detailed computational simulations have provided powerful tools in the study of enzyme catalysis, protein / drug design, protein / ion / other molecule translocation and protein folding/aggregation, to name but a few. This work contains detailed information, not only on the conformational motions of biological systems, but also on the potential governing forces of conformational dynamics (transient interactions, chemical and physical origins, thermodynamic properties). New developments in computational simulations will greatly enhance our understanding of how these molecules function in various biological events.

"The biological functions of proteins are ultimately governed by the dynamical properties of their large conformational transitions rooted on multidimensional free energy landscapes. Straightforward molecular dynamics simulation provides a mechanistically detailed picture of conformational transitions, but is hampered by the long timescales of these processes, which are rare events compared to the molecular timescales. In order to overcome these difficulties, we present in this thesis a new method, path-metadynamics, for the study of rare events. Path-metadynamics aims to explore high dimensional free energy landscapes and determine local likely transition pathways. The formalism works within the framework of a history-dependent bias potential applied to a flexible path-variable. Control of the sampling of the orthogonal modes recovers the average path and the minimum free energy path as limiting cases. Simultaneously the bias potential estimates the free energy profile along the path. The method has trivial scaling with the number of order parameters and this makes it suitable for the study of complex transitions. We have applied path-metadynamics to investigate the partial unfolding of a relevant photoreceptor, the photoactive yellow protein, and the formation/dissociation mechanism of a coiled coil, the leucine zipper domain. Our results demonstrate that path-metadynamics enables the calculation of rate constants, the localization of transition states, and the mapping of the free energy along a transition path described on a high-dimensional space. The likely transition paths obtained provide unique molecular insight about the protein conformational changes investigated. This approach opens a new way for studying complex rare events transitions."--Samenvatting auteur.

The Latest Developments on the Role of Dynamics in Protein FunctionsComputational Approaches to Protein Dynamics: From Quantum to Coarse-Grained Methods presents modern biomolecular computational techniques that address protein flexibility/dynamics at all levels of theory. An international contingent of leading researchers in chemistry, physics, an

Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly, Volume 170 in the Progress in Molecular Biology and Translational Science series, provides the most topical, informative and exciting monographs available on a wide variety of research topics. The series includes in-depth knowledge on the molecular biological aspects of organismal physiology, with this release including chapters on Pairwise-Additive and Polarizable Atomistic Force Fields for Molecular Dynamics Simulations of Proteins, Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers, Enhanced sampling and free energy methods, and much more. Includes comprehensive coverage on molecular biology Presents ample use of tables, diagrams, schemata and color figures to enhance the reader's ability to rapidly grasp the information provided Contains contributions from renowned experts in the field

In order to execute their biological activities, most proteins fold into their unique, three-dimensional structure. The discovery of intrinsically disordered proteins (IDPs) about two decades ago, which are now widely found in eukaryotes, has since challenged the structure-function paradigm. IDPs, which in isolation exist as broad, non-random, conformational ensembles of interconverting states, are centrally involved in many biological processes. The key to their functioning is the ability to fold when bound to ligand partner(s), thus operating as morphing proteins. Despite booming interest in morphing behavior, investigating their structural transitions and mechanism remains extremely difficult because of their distinct characteristics. Previously, we observed a close connection between intrinsically partially disordered proteins (IPDPS) and gradual (un)folding transitions of downhill folders, leading to the hypothesis that many IPDPs work as a conformational rheostat. The scope of this dissertation is to investigate the biological and technological implications of gradual conformational transitions. We first demonstrate the design principles of protein-based scaffolds by utilizing gradual (un)folding coupled to binding for developing rheostatic conformational transducers using computational modeling and experiments. Our engineered transducers showcase>6 orders of magnitude change in analyte concentration (broadband sensitivity) and have practical advantages over extant ones, which conventionally operate as conformational switches. Next, inspired by the LEGO toy, we devised a novel modular approach to dissect the folding cooperativity and the energetic contributions of native interactions in defining the conformational ensemble and binding properties of IPDPs. Using an integrated strategy of computation and experiments, we perform an ensemble-based conformational analysis and find that the approach provides an exciting new tool for analyzing morphing transitions that should generally apply to any IPDP, thereby addressing a fundamental gap in the field. One particularly interesting IPDP is NCBD that binds to multiple structurally diverse ligand partners and recruits the basal transcription machinery. We then explore the concept of NCBD functioning as a conformational rheostat, which allows its promiscuous binding. Finally, using extensive all-atom Molecular Dynamics simulations of NCBD and its biological partners in their free and bound forms, we decipher the hidden conformational biases in the dynamics of the heterogeneous ensemble of NCBD, undergoing gradual morphing transitions hinting at a working conformational rheostat in transcription.