Physical biology最新文献_第4页

Structure of the space of folding protein sequences defined by large language models. 由大型语言模型定义的折叠蛋白质序列空间结构。

IF 2 4区生物学

Physical biology Pub Date : 2024-01-31 DOI: 10.1088/1478-3975/ad205c

A Zambon, R Zecchina, G Tiana

{"title":"Structure of the space of folding protein sequences defined by large language models.","authors":"A Zambon, R Zecchina, G Tiana","doi":"10.1088/1478-3975/ad205c","DOIUrl":"10.1088/1478-3975/ad205c","url":null,"abstract":"Proteins populate a manifold in the high-dimensional sequence space whose geometrical structure guides their natural evolution. Leveraging recently-developed structure prediction tools based on transformer models, we first examine the protein sequence landscape as defined by an effective energy that is a proxy of sequence foldability. This landscape shares characteristics with optimization challenges encountered in machine learning and constraint satisfaction problems. Our analysis reveals that natural proteins predominantly reside in wide, flat minima within this energy landscape. To investigate further, we employ statistical mechanics algorithms specifically designed to explore regions with high local entropy in relatively flat landscapes. Our findings indicate that these specialized algorithms can identify valleys with higher entropy compared to those found using traditional methods such as Monte Carlo Markov Chains. In a proof-of-concept case, we find that these highly entropic minima exhibit significant similarities to natural sequences, especially in critical key sites and local entropy. Additionally, evaluations through Molecular Dynamics suggests that the stability of these sequences closely resembles that of natural proteins. Our tool combines advancements in machine learning and statistical physics, providing new insights into the exploration of sequence landscapes where wide, flat minima coexist alongside a majority of narrower minima.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139491534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fitness effects of a demography-dispersal trade-off in expandingSaccharomyces cerevisiaemats. 在不断扩大的酿酒酵母垫中，种群数量-散布权衡对体能的影响。

IF 2 4区生物学

Physical biology Pub Date : 2024-01-22 DOI: 10.1088/1478-3975/ad1ccd

Rebekah Hall, Akila Bandara, Daniel A Charlebois

{"title":"Fitness effects of a demography-dispersal trade-off in expandingSaccharomyces cerevisiaemats.","authors":"Rebekah Hall, Akila Bandara, Daniel A Charlebois","doi":"10.1088/1478-3975/ad1ccd","DOIUrl":"10.1088/1478-3975/ad1ccd","url":null,"abstract":"Fungi expand in space and time to form complex multicellular communities. The mechanisms by which they do so can vary dramatically and determine the life-history and dispersal traits of expanding populations. These traits influence deterministic and stochastic components of evolution, resulting in complex eco-evolutionary dynamics during colony expansion. We perform experiments on budding yeast strains genetically engineered to display rough-surface and smooth-surface phenotypes in colony-like structures called 'mats'. Previously, it was shown that the rough-surface strain has a competitive advantage over the smooth-surface strain when grown on semi-solid media. We experimentally observe the emergence and expansion of segments with a distinct smooth-surface phenotype during rough-surface mat development. We propose a trade-off between dispersal and local carrying capacity to explain the relative fitness of these two phenotypes. Using a modified stepping-stone model, we demonstrate that this trade-off gives the high-dispersing, rough-surface phenotype a competitive advantage from standing variation, but that it inhibits this phenotype's ability to invade a resident smooth-surface population via mutation. However, the trade-off improves the ability of the smooth-surface phenotype to invade in rough-surface mats, replicating the frequent emergence of smooth-surface segments in experiments. Together, these computational and experimental findings advance our understanding of the complex eco-evolutionary dynamics of fungal mat expansion.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139404099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A thermodynamical model of non-deterministic computation in cortical neural networks 皮层神经网络非确定性计算的热力学模型

IF 2 4区生物学

Physical biology Pub Date : 2023-12-11 DOI: 10.1088/1478-3975/ad0f2d

Elizabeth A Stoll

{"title":"A thermodynamical model of non-deterministic computation in cortical neural networks","authors":"Elizabeth A Stoll","doi":"10.1088/1478-3975/ad0f2d","DOIUrl":"https://doi.org/10.1088/1478-3975/ad0f2d","url":null,"abstract":"Neuronal populations in the cerebral cortex engage in probabilistic coding, effectively encoding the state of the surrounding environment with high accuracy and extraordinary energy efficiency. A new approach models the inherently probabilistic nature of cortical neuron signaling outcomes as a thermodynamic process of non-deterministic computation. A mean field approach is used, with the trial Hamiltonian maximizing available free energy and minimizing the net quantity of entropy, compared with a reference Hamiltonian. Thermodynamic quantities are always conserved during the computation; free energy must be expended to produce information, and free energy is released during information compression, as correlations are identified between the encoding system and its surrounding environment. Due to the relationship between the Gibbs free energy equation and the Nernst equation, any increase in free energy is paired with a local decrease in membrane potential. As a result, this process of thermodynamic computation adjusts the likelihood of each neuron firing an action potential. This model shows that non-deterministic signaling outcomes can be achieved by noisy cortical neurons, through an energy-efficient computational process that involves optimally redistributing a Hamiltonian over some time evolution. Calculations demonstrate that the energy efficiency of the human brain is consistent with this model of non-deterministic computation, with net entropy production far too low to retain the assumptions of a classical system.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"12 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138692326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An exploration of the binding prediction of anatoxin-a and atropine to acetylcholinesterase enzyme using multi-level computer simulations. 利用多层次计算机模拟探索阿那托毒素a和阿托品与乙酰胆碱酯酶的结合预测。

IF 2 4区生物学

Physical biology Pub Date : 2023-11-23 DOI: 10.1088/1478-3975/ad0caa

Showkat Ahmad Mir, Jamoliddin Razzokov, Vishwajeet Mukherjee, Iswar Baitharu, Binata Nayak

{"title":"An exploration of the binding prediction of anatoxin-a and atropine to acetylcholinesterase enzyme using multi-level computer simulations.","authors":"Showkat Ahmad Mir, Jamoliddin Razzokov, Vishwajeet Mukherjee, Iswar Baitharu, Binata Nayak","doi":"10.1088/1478-3975/ad0caa","DOIUrl":"10.1088/1478-3975/ad0caa","url":null,"abstract":"Acetylcholinesterase (AChE) is crucial for the breakdown of acetylcholine to acetate and choline, while the inhibition of AChE by anatoxin-a (ATX-a) results in severe health complications. This study explores the structural characteristics of ATX-a and its interactions with AChE, comparing to the reference molecule atropine for binding mechanisms. Molecular docking simulations reveal strong binding affinity of both ATX-a and atropine to AChE, interacting effectively with specific amino acids in the binding site as potential inhibitors. Quantitative assessment using the MM-PBSA method demonstrates a significantly negative binding free energy of −81.659 kJ mol−1 for ATX-a, indicating robust binding, while atropine exhibits a stronger binding affinity with a free energy of −127.565 kJ mol−1. Umbrella sampling calculates the ΔG bind values to evaluate binding free energies, showing a favorable ΔG bind of −36.432 kJ mol−1 for ATX-a and a slightly lower value of −30.12 kJ mol−1 for atropine. This study reveals the dual functionality of ATX-a, acting as both a nicotinic acetylcholine receptor agonist and an AChE inhibitor. Remarkably, stable complexes form between ATX-a and atropine with AChE at its active site, exhibiting remarkable binding free energies. These findings provide valuable insights into the potential use of ATX-a and atropine as promising candidates for modulating AChE activity.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"107592072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Calcium regulates cortex contraction inPhysarum polycephalum. 钙调节多头绒泡菌皮层收缩。

IF 2 4区生物学

Physical biology Pub Date : 2023-11-17 DOI: 10.1088/1478-3975/ad0a9a

Bjoern Kscheschinski, Mirna Kramar, Karen Alim

{"title":"Calcium regulates cortex contraction inPhysarum polycephalum.","authors":"Bjoern Kscheschinski, Mirna Kramar, Karen Alim","doi":"10.1088/1478-3975/ad0a9a","DOIUrl":"10.1088/1478-3975/ad0a9a","url":null,"abstract":"The tubular network-forming slime moldPhysarum polycephalumis able to maintain long-scale contraction patterns driven by an actomyosin cortex. The resulting shuttle streaming in the network is crucial for the organism to respond to external stimuli and reorganize its body mass giving rise to complex behaviors. However, the chemical basis of the self-organized flow pattern is not fully understood. Here, we present ratiometric measurements of free intracellular calcium in simple morphologies ofPhysarumnetworks. The spatiotemporal patterns of the free calcium concentration reveal a nearly anti-correlated relation to the tube radius, suggesting that calcium is indeed a key regulator of the actomyosin activity. We compare the experimentally observed phase relation between the radius and the calcium concentration to the predictions of a theoretical model including calcium as an inhibitor. Numerical simulations of the model suggest that calcium indeed inhibits the contractions inPhysarum, although a quantitative difference to the experimentally measured phase relation remains. Unraveling the mechanism underlying the contraction patterns is a key step in gaining further insight into the principles ofPhysarum's complex behavior.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"21 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136398857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-throughput design of cultured tissue moulds using a biophysical model: optimising cell alignment. 使用生物物理模型对培养的组织模具进行高通量设计：优化细胞排列。

IF 2 4区生物学

Physical biology Pub Date : 2023-10-30 DOI: 10.1088/1478-3975/ad0276

James P Hague, Allison E Andrews, Hugh Dickinson

{"title":"High-throughput design of cultured tissue moulds using a biophysical model: optimising cell alignment.","authors":"James P Hague, Allison E Andrews, Hugh Dickinson","doi":"10.1088/1478-3975/ad0276","DOIUrl":"https://doi.org/10.1088/1478-3975/ad0276","url":null,"abstract":"The technique presented here identifies tethered mould designs, optimised for growing cultured tissue with very highly-aligned cells. It is based on a microscopic biophysical model for polarised cellular hydrogels. There is an unmet need for tools to assist mould and scaffold designs for the growth of cultured tissues with bespoke cell organisations, that can be used in applications such as regenerative medicine, drug screening and cultured meat. High-throughput biophysical calculations were made for a wide variety of computer-generated moulds, with cell-matrix interactions and tissue-scale forces simulated using a contractile network dipole orientation model. Elongated moulds with central broadening and one of the following tethering strategies are found to lead to highly-aligned cells: (1) tethers placed within the bilateral protrusions resulting from an indentation on the short edge, to guide alignment (2) tethers placed within a single vertex to shrink the available space for misalignment. As such, proof-of-concept has been shown for mould and tethered scaffold design based on a recently developed biophysical model. The approach is applicable to a broad range of cell types that align in tissues and is extensible for 3D scaffolds.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"20 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71413619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Rapid prediction of lab-grown tissue properties using deep learning. 使用深度学习快速预测实验室培养的组织特性。

IF 2 4区生物学

Physical biology Pub Date : 2023-10-19 DOI: 10.1088/1478-3975/ad0019

Allison Andrews, Hugh Dickinson, James Peter Hague

{"title":"Rapid prediction of lab-grown tissue properties using deep learning.","authors":"Allison Andrews, Hugh Dickinson, James Peter Hague","doi":"10.1088/1478-3975/ad0019","DOIUrl":"10.1088/1478-3975/ad0019","url":null,"abstract":"The interactions between cells and the extracellular matrix are vital for the self-organisation of tissues. In this paper we present proof-of-concept to use machine learning tools to predict the role of this mechanobiology in the self-organisation of cell-laden hydrogels grown in tethered moulds. We develop a process for the automated generation of mould designs with and without key symmetries. We create a large training set withN = 6400 cases by running detailed biophysical simulations of cell-matrix interactions using the contractile network dipole orientation model for the self-organisation of cellular hydrogels within these moulds. These are used to train an implementation of thepix2pixdeep learning model, with an additional 100 cases that were unseen in the training of the neural network for review and testing of the trained model. Comparison between the predictions of the machine learning technique and the reserved predictions from the biophysical algorithm show that the machine learning algorithm makes excellent predictions. The machine learning algorithm is significantly faster than the biophysical method, opening the possibility of very high throughput rational design of moulds for pharmaceutical testing, regenerative medicine and fundamental studies of biology. Future extensions for scaffolds and 3D bioprinting will open additional applications.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41176979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Calcium storage in multivesicular endo-lysosome. 钙在多泡内溶酶体中的储存。

IF 2 4区生物学

Physical biology Pub Date : 2023-10-17 DOI: 10.1088/1478-3975/acfe6a

Cameron C Scott, Vaibhav Wasnik, Paula Nunes-Hassler, Nicolas Demaurex, Karsten Kruse, Jean Gruenberg

{"title":"Calcium storage in multivesicular endo-lysosome.","authors":"Cameron C Scott, Vaibhav Wasnik, Paula Nunes-Hassler, Nicolas Demaurex, Karsten Kruse, Jean Gruenberg","doi":"10.1088/1478-3975/acfe6a","DOIUrl":"10.1088/1478-3975/acfe6a","url":null,"abstract":"It is now established that endo-lysosomes, also referred to as late endosomes, serve as intracellular calcium store, in addition to the endoplasmic reticulum. While abundant calcium-binding proteins provide the latter compartment with its calcium storage capacity, essentially nothing is known about the mechanism responsible for calcium storage in endo-lysosomes. In this paper, we propose that the structural organization of endo-lysosomal membranes drives the calcium storage capacity of the compartment. Indeed, endo-lysosomes exhibit a characteristic multivesicular ultrastructure, with intralumenal membranes providing a large amount of additional bilayer surface. We used a theoretical approach to investigate the calcium storage capacity of endosomes, using known calcium binding affinities for bilayers and morphological data on endo-lysosome membrane organization. Finally, we tested our predictions experimentally after Sorting Nexin 3 depletion to decrease the intralumenal membrane content. We conclude that the major negatively-charge lipids and proteins of endo-lysosomes serve as calcium-binding molecules in the acidic calcium stores of mammalian cells, while the large surface area of intralumenal membranes provide the necessary storage capacity.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41131268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Seeking and sharing information in collective olfactory search. 在集体嗅觉搜索中寻求和共享信息。

IF 2 4区生物学

Physical biology Pub Date : 2023-10-09 DOI: 10.1088/1478-3975/acfd7a

Emanuele Panizon, Antonio Celani

引用次数: 0

Facilitating cell segmentation with the projection-enhancement network. 利用投影增强网络促进细胞分割。

IF 2 4区生物学

Physical biology Pub Date : 2023-10-09 DOI: 10.1088/1478-3975/acfe53

Christopher Z Eddy, Austin Naylor, Christian T Cunningham, Bo Sun

{"title":"Facilitating cell segmentation with the projection-enhancement network.","authors":"Christopher Z Eddy, Austin Naylor, Christian T Cunningham, Bo Sun","doi":"10.1088/1478-3975/acfe53","DOIUrl":"10.1088/1478-3975/acfe53","url":null,"abstract":"Contemporary approaches to instance segmentation in cell science use 2D or 3D convolutional networks depending on the experiment and data structures. However, limitations in microscopy systems or efforts to prevent phototoxicity commonly require recording sub-optimally sampled data that greatly reduces the utility of such 3D data, especially in crowded sample space with significant axial overlap between objects. In such regimes, 2D segmentations are both more reliable for cell morphology and easier to annotate. In this work, we propose the projection enhancement network (PEN), a novel convolutional module which processes the sub-sampled 3D data and produces a 2D RGB semantic compression, and is trained in conjunction with an instance segmentation network of choice to produce 2D segmentations. Our approach combines augmentation to increase cell density using a low-density cell image dataset to train PEN, and curated datasets to evaluate PEN. We show that with PEN, the learned semantic representation in CellPose encodes depth and greatly improves segmentation performance in comparison to maximum intensity projection images as input, but does not similarly aid segmentation in region-based networks like Mask-RCNN. Finally, we dissect the segmentation strength against cell density of PEN with CellPose on disseminated cells from side-by-side spheroids. We present PEN as a data-driven solution to form compressed representations of 3D data that improve 2D segmentations from instance segmentation networks.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"20 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10586931/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41156771","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}

引用次数: 0