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Atomic Force Microscopy of Biomembranes
Published in Qiu-Xing Jiang, New Techniques for Studying Biomembranes, 2020
Yi Ruan, Lorena Redondo-Morata, Simon Scheuring
Membrane proteins and lipids are the main component of biological membranes. The characterization of the supramolecular organization and dynamics of membrane proteins is crucial for the understanding of the structure and function of biomembranes. AFM is now a unique tool for the investigation of membrane proteins at single molecule level resolution in a native-like environment. Combining all the advantages of AFM with a high temporal resolution in the millisecond range. HS-AFM allows both real-space and real-time visualization of the protein dynamics, providing an excellent platform to establish structure–function relationships and to determine biophysical parameters of single molecules previously inaccessible by other techniques.
Enzyme Kinetics and Drugs as Enzyme Inhibitors
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2019
Allosteric regulation (or control) means the influence of an effector molecule on an enzyme and plays a role in cell signaling (long-range allosteric effects); it binds at a site other than the enzyme’s active site, the allosteric site. This is often accompanied by conformational changes involving protein dynamics. Effector molecules either cause positive allosteric modulation (allosteric activation) or negative allosteric modulation (allosteric inhibition) and are in a broader sense of importance for conformational perturbations on cellular functions and disease states; in other words the allosteric change in one protein may affect the behavior of other proteins downstream. Non-competitive inhibition always means allosteric inhibition but not all allosteric inhibitors act non-competitive. For models explaining the allosteric effect see Monod et al. (1965; concerted model) and Koshland et al. (1966, sequential model).
Some Underlying Physical Principles
Published in Clive R. Bagshaw, Biomolecular Kinetics, 2017
More detailed analysis can be carried out starting with a crystal structure of a protein and subjecting it to analysis through molecular dynamics. This is a powerful method to examine protein motions, in which vibrations and rotations of individual atoms are modeled in time using Newton’s laws of motion [71,101,102]. These motions are coupled, giving rise to a complex problem that can be solved only by numerical integration or Monte Carlo simulations. Typically, the time interval taken between each step in the calculation is about 10−15 s. Simulations of protein dynamics are, in effect, single molecule experiments and can be repeated to find the most likely pathway. Needless to say, the process is computer intensive, and it is difficult to get beyond a time scale of microseconds without approximations. Super computers have achieved simulations of the folding of small proteins up to the millisecond time scale [103]. Atoms can be grouped to reduce computational time, resulting in lower resolution course-grained models [104–106]. On the other hand, to model enzyme-catalyzed reactions, hybrid quantum mechanical/molecular mechanics (QM/MM) calculations are used [102,107]. Here, the active site and substrates are modeled in detail, while the remainder of the protein is treated using classical force fields. This is an area of rapid development but continues to require experimental kinetic data to benchmark progress.
Rebellion of the deregulated regulators: What is the clinical relevance of studying intrinsically disordered proteins?
Published in Expert Review of Proteomics, 2022
The situation has changed at the end of the last century, when the crucial importance of protein dynamics and structural flexibility in the form of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) was recognized (reviewed by Turoverov et al. [8]). It is now accepted that different parts of a protein molecule can be (dis)ordered to different degree. This inherent spatiotemporal heterogeneity defines protein multifunctionality that can be described by a general ‘protein structure-function continuum’ model, where a protein molecule represents a dynamic conformational ensemble of multiple different forms characterized by a broad spectrum of structural features and different functional potentials [9]. Furthermore, a recent discovery of numerous membrane-less organelles (MLOs), which are abundantly present in the living cells, have multiple crucial functions, and play important roles in the spatio-temporal organization of the intracellular space, highlights a new crucial role of many IDPs/IDRs that can undergo liquid-liquid phase separation (LLPS) and thereby control the biogenesis of these phase separated liquid droplets or biomolecular condensates [8,10].
Anti-trypanosomatid structure-based drug design – lessons learned from targeting the folate pathway
Published in Expert Opinion on Drug Discovery, 2022
Joanna Panecka-Hofman, Ina Poehner, Rebecca C. Wade
The aforementioned lack of structural data on the potential trypanosomatid targets could be partly addressed by tapping the significant advances in predictive power of new protein structure prediction methods, such as AlphaFold [115] and RoseTTAfold [116]. Predicting trypanosomal and leishmanial targets by such approaches has to overcome the poor sequence sampling in databases for these species, and thus the low quality of multiple sequence alignments, but first solutions are appearing, such as the resource made available by Wheeler [117]. Another important question is the suitability of the such predicted structures for SBDD [118,119]. Currently, these methods display problems in capturing pocket conformations, protein-ligand complexes, and protein dynamics, e.g. cannot generate an ensemble of active/inactive states for the enzyme [119].
The clinical potential of prm-PASEF mass spectrometry
Published in Expert Review of Proteomics, 2021
The rise of proteomics as a powerful method for analyzing peptides and proteins revolutionized protein biochemistry by allowing the rapid identification and quantification of proteins. Additionally, it moved proteomics to the center stage of omics techniques. Today, proteomics techniques enable capturing the entire complexity of protein dynamics, which occurs after translating genetic information into proteins. This includes protein synthesis and destruction or regulation by a layer of post-translational modifications, which allow rapid changes of activity without the need for synthesis or degradation. Current studies show that only a subset of the dynamic proteome is directly linked to the abundance of the corresponding transcripts [1–3], underlining the importance of proteomics for the characterization of cellular processes.