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1. Tracking live-cell single-molecule dynamics enables measurements of heterochromatin-associated protein–protein interactions

   https://doi.org/10.1093/nar/gkae692  

   Chen, Ziyuan; Seman, Melissa; Fyodorova, Yekaterina; Farhat, Ali; Ames, Amanda; Levashkevich, Alexander; Biswas, Saikat; Huang, Fengting; Freddolino, Lydia; Biteen, Julie S.; et al (August 2024, Nucleic Acids Research)

   Abstract Visualizing and measuring molecular-scale interactions in living cells represents a major challenge, but recent advances in single-molecule super-resolution microscopy are bringing us closer to achieving this goal. Single-molecule super-resolution microscopy enables high-resolution and sensitive imaging of the positions and movement of molecules in living cells. HP1 proteins are important regulators of gene expression because they selectively bind and recognize H3K9 methylated (H3K9me) histones to form heterochromatin-associated protein complexes that silence gene expression, but several important mechanistic details of this process remain unexplored. Here, we extended live-cell single-molecule tracking studies in fission yeast to determine how HP1 proteins interact with their binding partners in the nucleus. We measured how genetic perturbations that affect H3K9me alter the diffusive properties of HP1 proteins and their binding partners, and we inferred their most likely interaction sites. Our results demonstrate that H3K9 methylation spatially restricts HP1 proteins and their interactors, thereby promoting ternary complex formation on chromatin while simultaneously suppressing off-chromatin binding. As opposed to being an inert platform to direct HP1 binding, our studies propose a novel function for H3K9me in promoting ternary complex formation by enhancing the specificity and stimulating the assembly of HP1–protein complexes in living cells. 

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2. Photoinduced reconfiguration to control the protein-binding affinity of azobenzene-cyclized peptides

   https://doi.org/10.1039/D0TB01189D  

   Day, Kevin; Schneible, John D; Young, Ashlyn T; Pozdin, Vladimir A.; Gaffney, Lewis; Prodromou, Raphael; Freytes, Donald; Daniele, Michael; Menegatti, Stefano (January 2020, Journal of Materials Chemistry B)

   The impact of next-generation biorecognition elements (ligands) will be determined by the ability to remotely control their binding activity for a target biomolecule in complex environments. Compared to conventional mechanisms for regulating binding affinity (pH, ionic strength, or chaotropic agents), light provides higher accuracy and rapidity, and is particularly suited for labile targets. In this study, we demonstrate a general method to develop azobenzene-cyclized peptide ligands with light-controlled affinity for target proteins. Light triggers a cis/trans isomerization of the azobenzene, which results in a major structural rearrangement of the cyclic peptide from a non-binding to a binding configuration. Critical to this goal are the abiliy to achieve efficient photo-isomerization under low light dosage and the temporal stability of both cis and trans isomers. We demonstrated our method by designing photo-switchable peptides targeting vascular cell adhesion marker 1 (VCAM1), a cell marker implicated in stem cell function. Starting from a known VCAM1-binding linear peptide, an ensemble of azobenzene-cyclized variants with selective light-controlled binding were identified by combining in silico design with experimental characterization via spectroscopy and surface plasmon resonance. Variant cycloAZOB[G-VHAKQHRN-K] featured rapid, light-controlled binding of VCAM1 (KD,Trans/KD,Cis ~ 130). Biotin-cycloAZOB[G-VHAKQHRN-K] was utilized to label brain microvascular endothelial cells (BMECs), showing co-localization with anti-VCAM1 antibodies in cis configuration and negligible binding in trans configuration. 

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3. A generalized Flory-Stockmayer kinetic theory of connectivity percolation and rigidity percolation of cytoskeletal networks

   https://doi.org/10.1371/journal.pcbi.1010105  

   Bueno, Carlos; Liman, James; Schafer, Nicholas P.; Cheung, Margaret S.; Wolynes, Peter G. (May 2022, PLOS Computational Biology)

   Gov, Nir (Ed.)

   Actin networks are essential for living cells to move, reproduce, and sense their environments. The dynamic and rheological behavior of actin networks is modulated by actin-binding proteins such as α-actinin, Arp2/3, and myosin. There is experimental evidence that actin-binding proteins modulate the cooperation of myosin motors by connecting the actin network. In this work, we present an analytical mean field model, using the Flory-Stockmayer theory of gelation, to understand how different actin-binding proteins change the connectivity of the actin filaments as the networks are formed. We follow the kinetics of the networks and estimate the concentrations of actin-binding proteins that are needed to reach connectivity percolation as well as to reach rigidity percolation. We find that Arp2/3 increases the actomyosin connectivity in the network in a non-monotonic way. We also describe how changing the connectivity of actomyosin networks modulates the ability of motors to exert forces, leading to three possible phases of the networks with distinctive dynamical characteristics: a sol phase, a gel phase, and an active phase. Thus, changes in the concentration and activity of actin-binding proteins in cells lead to a phase transition of the actin network, allowing the cells to perform active contraction and change their rheological properties. 

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4. Construction of gateway-compatible baculovirus expression vectors for high-throughput protein expression and in vivo microcrystal screening

   https://doi.org/10.1038/s41598-020-70163-2  

   Tang, Yanyang; Saul, Justin; Nagaratnam, Nirupa; Martin-Garcia, Jose M.; Fromme, Petra; Qiu, Ji; LaBaer, Joshua (August 2020, Scientific Reports)

   Abstract Baculovirus mediated-insect cell expression systems have been widely used for producing heterogeneous proteins. However, to date, there is still the lack of an easy-to-manipulate system that enables the high-throughput protein characterization in insect cells by taking advantage of large existing Gateway clone libraries. To resolve this limitation, we have constructed a suite of Gateway-compatible pIEx-derived baculovirus expression vectors that allow the rapid and cost-effective construction of expression clones for mass parallel protein expression in insect cells. This vector collection also supports the attachment of a variety of fusion tags to target proteins to meet the needs for different research applications. We first demonstrated the utility of these vectors for protein expression and purification using a set of 40 target proteins of various sizes, cellular localizations and host organisms. We then established a scalable pipeline coupled with the SONICC and TEM techniques to screen for microcrystal formation within living insect cells. Using this pipeline, we successfully identified microcrystals for ~ 16% of the tested protein set, which can be potentially used for structure elucidation by X-ray crystallography. In summary, we have established a versatile pipeline enabling parallel gene cloning, protein expression and purification, and in vivo microcrystal screening for structural studies. 

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5. Binding peptide generation for MHC Class I proteins with deep reinforcement learning

   https://doi.org/10.1093/bioinformatics/btad055  

   Chen, Ziqi; Zhang, Baoyi; Guo, Hongyu; Emani, Prashant; Clancy, Trevor; Jiang, Chongming; Gerstein, Mark; Ning, Xia; Cheng, Chao; Min, Martin Renqiang; et al (January 2023, Bioinformatics)

   Abstract MotivationMHC Class I protein plays an important role in immunotherapy by presenting immunogenic peptides to anti-tumor immune cells. The repertoires of peptides for various MHC Class I proteins are distinct, which can be reflected by their diverse binding motifs. To characterize binding motifs for MHC Class I proteins, in vitro experiments have been conducted to screen peptides with high binding affinities to hundreds of given MHC Class I proteins. However, considering tens of thousands of known MHC Class I proteins, conducting in vitro experiments for extensive MHC proteins is infeasible, and thus a more efficient and scalable way to characterize binding motifs is needed. ResultsWe presented a de novo generation framework, coined PepPPO, to characterize binding motif for any given MHC Class I proteins via generating repertoires of peptides presented by them. PepPPO leverages a reinforcement learning agent with a mutation policy to mutate random input peptides into positive presented ones. Using PepPPO, we characterized binding motifs for around 10 000 known human MHC Class I proteins with and without experimental data. These computed motifs demonstrated high similarities with those derived from experimental data. In addition, we found that the motifs could be used for the rapid screening of neoantigens at a much lower time cost than previous deep-learning methods. Availability and implementationThe software can be found in https://github.com/minrq/pMHC. Supplementary informationSupplementary data are available at Bioinformatics online. 

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