Journal of Biological Physics最新文献

{"title":"Impact of Conformational Substates and Energy Landscapes on Understanding Hemoglobin Kinetics and Function","authors":"William A. Eaton","doi":"10.1007/s10867-021-09588-3","DOIUrl":"10.1007/s10867-021-09588-3","url":null,"abstract":"<div><p>Hans Frauenfelder’s discovery of conformational substates in studies of myoglobin carbon monoxide geminate rebinding kinetics at cryogenic temperatures (Austin RH, Beeson KW, Eisenstein L, Frauenfelder H, &amp; Gunsalus IC (1975) Dynamics of Ligand Binding to Myoglobin. <i>Biochemistry</i> 14(24):5355–5373) followed by his introduction of energy landscape theory with Peter Wolynes (Frauenfelder H, Sligar SG, &amp; Wolynes PG (1991) The Energy Landscapes and Motions of Proteins. <i>Science</i> 254(5038):1598–1603) marked the beginning of a new era in the physics and physical chemistry of proteins. Their work played a major role in demonstrating the power and importance of dynamics and of Kramers reaction rate theory for understanding protein function. The biggest impact of energy landscape theory has been in the protein folding field, which is well-known and has been documented in numerous articles and reviews, including a recent one of my own (Eaton WA (2021) Modern Kinetics and Mechanism of Protein Folding: a Retrospective. <i>J. Phys. Chem. B.</i> 125(14):3452–3467). Here I will describe the much less well-known impact of their modern view of proteins on both experimental and theoretical studies of hemoglobin kinetics and function. I will first describe how Frauenfelder’s experiments motivated and influenced my own research on myoglobin, which were key ingredients to my work on understanding hemoglobin.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 4","pages":"337 - 353"},"PeriodicalIF":1.8,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09588-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"4473489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning the local landscape of protein structures with convolutional neural networks","authors":"Anastasiya V. Kulikova,&nbsp;Daniel J. Diaz,&nbsp;James M. Loy,&nbsp;Andrew D. Ellington,&nbsp;Claus O. Wilke","doi":"10.1007/s10867-021-09593-6","DOIUrl":"10.1007/s10867-021-09593-6","url":null,"abstract":"<div><p>One fundamental problem of protein biochemistry is to predict protein structure from amino acid sequence. The inverse problem, predicting either entire sequences or individual mutations that are consistent with a given protein structure, has received much less attention even though it has important applications in both protein engineering and evolutionary biology. Here, we ask whether 3D convolutional neural networks (3D CNNs) can learn the local fitness landscape of protein structure to reliably predict either the wild-type amino acid or the consensus in a multiple sequence alignment from the local structural context surrounding site of interest. We find that the network can predict wild type with good accuracy, and that network confidence is a reliable measure of whether a given prediction is likely going to be correct or not. Predictions of consensus are less accurate and are primarily driven by whether or not the consensus matches the wild type. Our work suggests that high-confidence mis-predictions of the wild type may identify sites that are primed for mutation and likely targets for protein engineering.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 4","pages":"435 - 454"},"PeriodicalIF":1.8,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09593-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"4402480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive landscapes hidden beneath biological cellular automata","authors":"Lars Koopmans,&nbsp;Hyun Youk","doi":"10.1007/s10867-021-09592-7","DOIUrl":"10.1007/s10867-021-09592-7","url":null,"abstract":"<div><p>To celebrate Hans Frauenfelder’s achievements, we examine energy(-like) “landscapes” for complex living systems. Energy landscapes summarize all possible dynamics of some physical systems. Energy(-like) landscapes can explain some biomolecular processes, including gene expression and, as Frauenfelder showed, protein folding. But energy-like landscapes and existing frameworks like statistical mechanics seem impractical for describing many living systems. Difficulties stem from living systems being high dimensional, nonlinear, and governed by many, tightly coupled constituents that are noisy. The predominant modeling approach is devising differential equations that are tailored to each living system. This ad hoc approach faces the notorious “parameter problem”: models have numerous nonlinear, mathematical functions with unknown parameter values, even for describing just a few intracellular processes. One cannot measure many intracellular parameters or can only measure them as snapshots in time. Another modeling approach uses cellular automata to represent living systems as discrete dynamical systems with binary variables. Quantitative (Hamiltonian-based) rules can dictate cellular automata (e.g., Cellular Potts Model). But numerous biological features, in current practice, are qualitatively described rather than quantitatively (e.g., gene is (highly) expressed or not (highly) expressed). Cellular automata governed by verbal rules are useful representations for living systems and can mitigate the parameter problem. However, they can yield complex dynamics that are difficult to understand because the automata-governing rules are not quantitative and much of the existing mathematical tools and theorems apply to continuous but not discrete dynamical systems. Recent studies found ways to overcome this challenge. These studies either discovered or suggest an existence of predictive “landscapes” whose shapes are described by Lyapunov functions and yield “equations of motion” for a “pseudo-particle.” The pseudo-particle represents the entire cellular lattice and moves on the landscape, thereby giving a low-dimensional representation of the cellular automata dynamics. We outline this promising modeling strategy.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 4","pages":"355 - 369"},"PeriodicalIF":1.8,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09592-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"4227684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"It doesn’t always pay to be fit: success landscapes","authors":"Trung V. Phan,&nbsp;Gao Wang,&nbsp;Tuan K. Do,&nbsp;Ioannis G. Kevrekidis,&nbsp;Sarah Amend,&nbsp;Emma Hammarlund,&nbsp;Ken Pienta,&nbsp;Joel Brown,&nbsp;Liyu Liu,&nbsp;Robert H. Austin","doi":"10.1007/s10867-021-09589-2","DOIUrl":"10.1007/s10867-021-09589-2","url":null,"abstract":"<div><p>Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors. Although our analysis is purely theoretical, we believe the results have possibly strong connections to how we might treat diseases such as cancer in the future with a deeper understanding of the interplay between resource degradation, mutation, and uncontrolled cell growth.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 4","pages":"387 - 400"},"PeriodicalIF":1.8,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09589-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"5100311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the energy landscape of a SAM-I riboswitch","authors":"Christoph Manz,&nbsp;Andrei Yu Kobitski,&nbsp;Ayan Samanta,&nbsp;Karin Nienhaus,&nbsp;Andres Jäschke,&nbsp;Gerd Ulrich Nienhaus","doi":"10.1007/s10867-021-09584-7","DOIUrl":"10.1007/s10867-021-09584-7","url":null,"abstract":"<div><p>SAM-I riboswitches regulate gene expression through transcription termination upon binding a <i>S</i>-adenosyl-L-methionine (SAM) ligand. In previous work, we characterized the conformational energy landscape of the full-length <i>Bacillus subtilis yitJ</i> SAM-I riboswitch as a function of Mg²⁺ and SAM ligand concentrations. Here, we have extended this work with measurements on a structurally similar ligand, <i>S</i>-adenosyl-<span>l</span>-homocysteine (SAH), which has, however, a much lower binding affinity. Using single-molecule Förster resonance energy transfer (smFRET) microscopy and hidden Markov modeling (HMM) analysis, we identified major conformations and determined their fractional populations and dynamics. At high Mg²⁺ concentration, FRET analysis yielded four distinct conformations, which we assigned to two terminator and two antiterminator states. In the same solvent, but with SAM added at saturating concentrations, four states persisted, although their populations, lifetimes and interconversion dynamics changed. In the presence of SAH instead of SAM, HMM revealed again four well-populated states and, in addition, a weakly populated ‘hub’ state that appears to mediate conformational transitions between three of the other states. Our data show pronounced and specific effects of the SAM and SAH ligands on the RNA conformational energy landscape. Interestingly, both SAM and SAH shifted the fractional populations toward terminator folds, but only gradually, so the effect cannot explain the switching action. Instead, we propose that the noticeably accelerated dynamics of interconversion between terminator and antiterminator states upon SAM binding may be essential for control of transcription.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 4","pages":"371 - 386"},"PeriodicalIF":1.8,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09584-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"5436279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A bioconvection model for viscoelastic nanofluid confined by tapered asymmetric channel: implicit finite difference simulations","authors":"A. Abbasi,&nbsp;Akbar Zaman,&nbsp;Searatul Arooj,&nbsp;M. Ijaz Khan,&nbsp;Sami Ullah Khan,&nbsp;Waseh Farooq,&nbsp;Taseer Muhammad","doi":"10.1007/s10867-021-09585-6","DOIUrl":"10.1007/s10867-021-09585-6","url":null,"abstract":"<div><p>As part of the growing evolution in nanotechnology and thermal sciences, nanoparticles are considered as an alternative solution for the energy depletion due to their ultra-high thermal effectives. Nanofluids reflect inclusive and broad-spectrum significances in engineering, industrial and bio-engineering like power plants, energy source, air conditioning systems, surface coatings, evaporators, power consumptions, nano-medicine, cancer treatment, etc. The present study describes the bio-convective peristaltic flow of a third-grade nanofluid in a tapered asymmetric channel. Basic conservation laws of mass, momentum, energy, and concentration as well as the microorganism diffusion equation are utilized to model the problem. The simplified form of the modeled expressions is accounted with long wavelength assumptions. For solving the resulting coupled and nonlinear equations, a well-known numerical method implicit finite difference scheme has been utilized. The graphical results describe the velocity, temperature and concentration profiles, and the density of motile microorganisms at the nanoscale. Furthermore, microorganism concentration lines are analyzed.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 4","pages":"499 - 520"},"PeriodicalIF":1.8,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09585-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"4638702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mean-field theory of the interaction of the magnesium ion with biopolymers: the case of lysozyme","authors":"Theo Odijk","doi":"10.1007/s10867-021-09587-4","DOIUrl":"10.1007/s10867-021-09587-4","url":null,"abstract":"<div><p>A statistical theory is presented of the magnesium ion interacting with lysozyme under conditions where the latter is positively charged. Temporarily assuming magnesium is not noncovalently bound to the protein, I solve the nonlinear Poisson–Boltzmann equation accurately and uniformly in a perturbative fashion. The resulting expression for the effective charge, which is larger than nominal owing to overshooting, is subtle and cannot be asymptotically expanded at high ionic strengths that are practical. An adhesive potential taken from earlier work together with the assumption of possibly bound magnesium is then fitted to be in accord with measurements of the second virial coefficient by Tessier et al. The resulting numbers of bound magnesium ions as a function of MgBr<span>(_2)</span> concentration are entirely reasonable compared with densitometry measurements.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 4","pages":"521 - 528"},"PeriodicalIF":1.8,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09587-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"5135177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heat transfer analysis for EMHD peristalsis of ionic-nanofluids via curved channel with Joule dissipation and Hall effects","authors":"Saba,&nbsp;Fahad Munir Abbasi,&nbsp;Sabir Ali Shehzad","doi":"10.1007/s10867-021-09582-9","DOIUrl":"10.1007/s10867-021-09582-9","url":null,"abstract":"<div><p>The objective of this research is to study the combined influences of applied electric and magnetic fields on the two-phase peristaltic motion of nanofluid through a curved channel. A two-phase model of a nanofluid, Maxwell’s model of thermal conductivity [1], and no-slip velocity and thermal boundary conditions have been used in this study. Hall effects, Joule heating (due to magnetic and electric fields), and viscous heating aspects are under consideration. Governing equations for the present flow configuration have been modeled and simplified by enforcing the lubrication scheme. Debye-Huckel approximation is used to obtain the analytical solution of the electric potential function (Poisson-Boltzmann equation). Resulting expressions are solved numerically through the NDSolve command in Mathematica and plotted in order to understand the effects of different dimensionless parameters on the temperature, stress, heat transmission rate, and fluid’s velocity. Graphical results demonstrated that the thermal transmission rate is augmented by increasing the Hartmann number, Brinkman number, and Debye-Huckel parameter while decreases for zeta potential ratio, Joule dissipation parameter, and electro-osmotic velocity. A decrease in axial velocity is noted near the lower wall for higher values of <span>({m}^{ast})</span>.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 4","pages":"455 - 476"},"PeriodicalIF":1.8,"publicationDate":"2021-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09582-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"5066748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the effects of magnetic levitation to simulate microgravity environment on the Arp2/3 complex pathway in macrophage","authors":"Sufang Wang,&nbsp;Nu Zhang,&nbsp;Jianglei Di,&nbsp;Wenjuan Zhao,&nbsp;Guolin Shi,&nbsp;Ruiheng Xie,&nbsp;Bohan Hu,&nbsp;Hui Yang","doi":"10.1007/s10867-021-09581-w","DOIUrl":"10.1007/s10867-021-09581-w","url":null,"abstract":"<div><p>With dwindling natural resources on earth, current and future generations will need to explore space to new planets that will require travel under no or varying gravity conditions. Hence, long-term space missions and anticipated impacts on human biology such as changes in immune function are of growing research interest. Here, we reported new findings on mechanisms of immune response to microgravity with a focus on macrophage as a cellular model. We employed a superconducting magnet to generate a simulated microgravity environment and evaluated the effects of simulated microgravity on RAW 264.7 mouse macrophage cell line in three time frames: 8, 24, and 48 h. As study endpoints, we measured cell viability, phagocytosis, and used next-generation sequencing to explore its changing mechanism. Macrophage cell viability and phagocytosis both showed a marked decrease under microgravity. The differentially expressed genes (DEG) were identified in two ways: (1) gravity-dependent DEG, compared μg samples and 1 g samples at each time point; (2) time-dependent DEG, compared time-point samples within the same gravitational field. Through transcriptome analysis and confirmed by molecular biological verification, our findings firstly suggest that microgravity might affect macrophage phagocytosis by targeting Arp2/3 complex involved cytoskeleton synthesis and causing macrophage immune dysfunction. Our findings contribute to an emerging body of scholarship on biological effects of space travel.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 3","pages":"323 - 335"},"PeriodicalIF":1.8,"publicationDate":"2021-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09581-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"4706108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In silico simulation of the effect of hypoxia on MCF-7 cell cycle kinetics under fractionated radiotherapy","authors":"Adrian S. Remigio","doi":"10.1007/s10867-021-09580-x","DOIUrl":"10.1007/s10867-021-09580-x","url":null,"abstract":"<div><p>The treatment outcome of a given fractionated radiotherapy scheme is affected by oxygen tension and cell cycle kinetics of the tumor population. Numerous experimental studies have supported the variability of radiosensitivity with cell cycle phase. Oxygen modulates the radiosensitivity through hypoxia-inducible factor (HIF) stabilization and oxygen fixation hypothesis (OFH) mechanism. In this study, an existing mathematical model describing cell cycle kinetics was modified to include the oxygen-dependent G1/S transition rate and radiation inactivation rate. The radiation inactivation rate used was derived from the linear-quadratic (LQ) model with dependence on oxygen enhancement ratio (OER), while the oxygen-dependent correction for the G1/S phase transition was obtained from numerically solving the ODE system of cyclin D-HIF dynamics at different oxygen tensions. The corresponding cell cycle phase fractions of aerated MCF-7 tumor population, and the resulting growth curve obtained from numerically solving the developed mathematical model were found to be comparable to experimental data. Two breast radiotherapy fractionation schemes were investigated using the mathematical model. Results show that hypoxia causes the tumor to be more predominated by the tumor subpopulation in the G1 phase and decrease the fractional contribution of the more radioresistant tumor cells in the S phase. However, the advantage provided by hypoxia in terms of cell cycle phase distribution is largely offset by the radioresistance developed through OFH. The delayed proliferation caused by severe hypoxia slightly improves the radiotherapy efficacy compared to that with mild hypoxia for a high overall treatment duration as demonstrated in the 40-Gy fractionation scheme.</p></div>","PeriodicalId":612,"journal":{"name":"Journal of Biological Physics","volume":"47 3","pages":"301 - 321"},"PeriodicalIF":1.8,"publicationDate":"2021-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10867-021-09580-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"4705151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}