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Current Opinion in Structural Biology Dec 2020Time-resolved serial femtosecond crystallography (tr-SFX) methods exploit slurries of crystalline samples that range in size from hundreds of nanometers to a few tens of... (Review)
Review
Time-resolved serial femtosecond crystallography (tr-SFX) methods exploit slurries of crystalline samples that range in size from hundreds of nanometers to a few tens of micrometers, at near-physiological temperature and pressure, to generate atomic resolution models and probe authentic function with the same experiment. 'Dynamic structural biology' is often used to encompass the research philosophy and techniques. Reaction cycles for tr-SFX studies are initiated by photons or ligand addition/mixing strategies, wherein the latter are potentially generalizable across enzymology. Thus, dynamic structural biology often creates stop-motion molecular movies of macromolecular function. In metal-dependent systems, complementary spectroscopic information can also be collected from the same samples and X-ray pulses, which provides even more detailed mechanistic insights. These types of experimental data also complement quantum mechanical and classical dynamics numerical calculations. Correlated structural-functional results will yield more detailed mechanistic insights and will likely translate into better drugs and treatments impacting human health, and better catalysis for clean energy and agriculture.
Topics: Bacteria; Biophysics; Macromolecular Substances; Proteins
PubMed: 33049498
DOI: 10.1016/j.sbi.2020.08.011 -
Protein Science : a Publication of the... Jul 2021
Topics: Biomolecular Condensates; Biophysics
PubMed: 34085339
DOI: 10.1002/pro.4135 -
Protein Science : a Publication of the... Aug 2001
Topics: Biophysics; Dipeptides; History, 20th Century; India; Models, Chemical; Models, Molecular; Molecular Conformation; Protein Conformation
PubMed: 11468367
DOI: 10.1002/pro.101691 -
Current Opinion in Structural Biology Dec 2021Accurate predictions from models based on physical principles are the ultimate metric of our biophysical understanding. Although there has been stunning progress... (Review)
Review
Accurate predictions from models based on physical principles are the ultimate metric of our biophysical understanding. Although there has been stunning progress toward structure prediction, quantitative prediction of enzyme function has remained challenging. Realizing this goal will require large numbers of quantitative measurements of rate and binding constants and the use of these ground-truth data sets to guide the development and testing of these quantitative models. Ground truth data more closely linked to the underlying physical forces are also desired. Here, we describe technological advances that enable both types of ground truth measurements. These advances allow classic models to be tested, provide novel mechanistic insights, and place us on the path toward a predictive understanding of enzyme structure and function.
Topics: Biophysical Phenomena; Biophysics; Genomics
PubMed: 34592682
DOI: 10.1016/j.sbi.2021.07.010 -
Annual Review of Biophysics May 2021Biophysics experiments performed at single-molecule resolution provide exceptional insight into the structural details and dynamic behavior of biological systems.... (Review)
Review
Biophysics experiments performed at single-molecule resolution provide exceptional insight into the structural details and dynamic behavior of biological systems. However, extracting this information from the corresponding experimental data unequivocally requires applying a biophysical model. In this review, we discuss how to use probability theory to apply these models to single-molecule data. Many current single-molecule data analysis methods apply parts of probability theory, sometimes unknowingly, and thus miss out on the full set of benefits provided by this self-consistent framework. The full application of probability theory involves a process called Bayesian inference that fully accounts for the uncertainties inherent to single-molecule experiments. Additionally, using Bayesian inference provides a scientifically rigorous method of incorporating information from multiple experiments into a single analysis and finding the best biophysical model for an experiment without the risk of overfitting the data. These benefits make the Bayesian approach ideal for analyzing any type of single-molecule experiment.
Topics: Bayes Theorem; Biophysics; Humans; Single Molecule Imaging
PubMed: 33534607
DOI: 10.1146/annurev-biophys-082120-103921 -
European Biophysics Journal : EBJ May 2018Manfred Eigen turned 90 on May 9th, 2017. He celebrated with a small group of colleagues and friends on behalf of the many inspired by him over his lifetime-whether... (Review)
Review
Manfred Eigen turned 90 on May 9th, 2017. He celebrated with a small group of colleagues and friends on behalf of the many inspired by him over his lifetime-whether scientists, artists, or philosophers. A small group of friends, because many-who by their breakthroughs have changed the face of science in different research areas-have already died. But it was a special day, devoted to the many genius facets of Manfred Eigen's oeuvre, and a day to highlight the way in which he continues to exude a great, vital and unbroken passion for science as well as an insatiable curiosity beyond his own scientific interests. He continues to dismiss arguments such as, that scientific problems cannot be solved because of a current lack of appropriate tools, or because of the persuasion of the community that certain things are immeasurable. He has lived up to and accepted only the highest scientific standards with his fundamental contributions in widely differing research fields, for which he has received numerous prizes and honorary doctorates, including the Nobel Prize for Chemistry in 1967. Some of his outstanding contributions to science and technology are honored in the following chapters. Here, we will report some characteristic traits of Manfred Eigen, and his personal development. We highlight his visionary foresight regarding how multidisciplinary science should combine to study the complex processes of life and its evolution in establishing an institute that applied biological, chemical, and physical methods, and how his vision became sustained reality.
Topics: Biophysics; Chemistry, Physical; History, 20th Century; History, 21st Century; Interdisciplinary Communication; Kinetics
PubMed: 29230510
DOI: 10.1007/s00249-017-1266-y -
Current Medicinal Chemistry 2008The identification and characterization of potential pharmacological targets in neurology and psychiatry is a fundamental problem at the intersection between medicinal... (Review)
Review
The identification and characterization of potential pharmacological targets in neurology and psychiatry is a fundamental problem at the intersection between medicinal chemistry and the neurosciences. Exciting new techniques in proteomics and genomics have fostered rapid progress, opening numerous questions as to the functional consequences of ligand binding at the systems level. Psycho- and neuro-active drugs typically work in nerve cells by affecting one or more aspects of electrophysiological activity. Thus, an integrated understanding of neuropharmacological agents requires bridging the gap between their molecular mechanisms and the biophysical determinants of neuronal function. Computational neuroscience and bioinformatics can play a major role in this functional connection. Robust quantitative models exist describing all major active membrane properties under endogenous and exogenous chemical control. These include voltage-dependent ionic channels (sodium, potassium, calcium, etc.), synaptic receptor channels (e.g. glutamatergic, GABAergic, cholinergic), and G protein coupled signaling pathways (protein kinases, phosphatases, and other enzymatic cascades). This brief review of neuromolecular medicine from the computational perspective provides compelling examples of how simulations can elucidate, explain, and predict the effect of chemical agonists, antagonists, and modulators in the nervous system.
Topics: Animals; Biophysical Phenomena; Biophysics; Combinatorial Chemistry Techniques; Computer Simulation; Electrophysiology; Humans; Models, Neurological; Neuropharmacology
PubMed: 18855673
DOI: 10.2174/092986708785909094 -
Journal of Experimental Botany Jul 2019All scientific measurements are affected to some degree by both systematic and random errors. The quantification of these errors supports correct interpretation of data,... (Review)
Review
All scientific measurements are affected to some degree by both systematic and random errors. The quantification of these errors supports correct interpretation of data, thus supporting scientific progress. Absence of information regarding reliability and accuracy can slow scientific progress, and can lead to a reproducibility crisis. Here we consider both measurement theory and plant biomechanics literature. Drawing from measurement theory literature, we review techniques for assessing both the accuracy and uncertainty of a measurement process. In our survey of plant biomechanics literature, we found that direct assessment of measurement accuracy and uncertainty is not yet common. The advantages and disadvantages of efforts to quantify measurement accuracy and uncertainty are discussed. We conclude with recommended best practices for improving the scientific rigor in plant biomechanics through attention to the issues of measurement accuracy and uncertainty.
Topics: Biomechanical Phenomena; Biophysics; Plants; Uncertainty
PubMed: 31301144
DOI: 10.1093/jxb/erz279 -
Biochimica Et Biophysica Acta Jan 2014
Topics: Biophysics; Ligands; Membrane Proteins; Protein Binding; Protein Conformation
PubMed: 24206896
DOI: 10.1016/j.bbamem.2013.09.013 -
Journal of Orthopaedic Research :... Feb 2018Advances in mechanobiology have evolved through insights from multiple disciplines including structural engineering, biomechanics, vascular biology, and orthopaedics. In... (Review)
Review
Advances in mechanobiology have evolved through insights from multiple disciplines including structural engineering, biomechanics, vascular biology, and orthopaedics. In this paper, we reviewed the impact of key reports related to the study of applied loads on tissues and cells and the resulting signal transduction pathways. We addressed how technology has helped advance the burgeoning field of mechanobiology (over 33,600 publications from 1970 to 2016). We analyzed the impact of critical ideas and then determined how these concepts influenced the mechanobiology field by looking at the citation frequency of these reports as well as tracking how the overall number of citations within the field changed over time. These data allowed us to understand how a key publication, idea, or technology guided or enabled the field. Initial observations of how forces acted on bone and soft tissues stimulated the development of computational solutions defining how forces affect tissue modeling and remodeling. Enabling technologies, such as cell and tissue stretching, compression, and shear stress devices, allowed more researchers to explore how deformation and fluid flow affect cells. Observation of the cell as a tensegrity structure and advanced methods to study genetic regulation in cells further advanced knowledge of specific mechanisms of mechanotransduction. The future of the field will involve developing gene and drug therapies to simulate or augment beneficial load regimens in patients and in mechanically conditioning organs for implantation. Here, we addressed a history of the field, but we limited our discussions to advances in musculoskeletal mechanobiology, primarily in bone, tendon, and ligament tissues. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:605-619, 2018.
Topics: Animals; Biophysics; History, 19th Century; History, 20th Century; Humans; Mechanotransduction, Cellular
PubMed: 28817244
DOI: 10.1002/jor.23707