scholarly journals DNA-mediated engineering of multicomponent enzyme crystals

2015 ◽  
Vol 112 (15) ◽  
pp. 4564-4569 ◽  
Author(s):  
Jeffrey D. Brodin ◽  
Evelyn Auyeung ◽  
Chad A. Mirkin
Keyword(s):  
Gold Nanoparticles ◽  
Protein Interactions ◽  
Building Blocks ◽  
Inorganic Nanoparticles ◽  
Protein Protein Interactions ◽  
Dna Interactions ◽  
Interparticle Interactions ◽  
Crystalline Materials ◽  
Catalytically Active ◽  
Surface Chemistries

The ability to predictably control the coassembly of multiple nanoscale building blocks, especially those with disparate chemical and physical properties such as biomolecules and inorganic nanoparticles, has far-reaching implications in catalysis, sensing, and photonics, but a generalizable strategy for engineering specific contacts between these particles is an outstanding challenge. This is especially true in the case of proteins, where the types of possible interparticle interactions are numerous, diverse, and complex. Herein, we explore the concept of trading protein–protein interactions for DNA–DNA interactions to direct the assembly of two nucleic-acid–functionalized proteins with distinct surface chemistries into six unique lattices composed of catalytically active proteins, or of a combination of proteins and DNA-modified gold nanoparticles. The programmable nature of DNA–DNA interactions used in this strategy allows us to control the lattice symmetries and unit cell constants, as well as the compositions and habit, of the resulting crystals. This study provides a potentially generalizable strategy for constructing a unique class of materials that take advantage of the diverse morphologies, surface chemistries, and functionalities of proteins for assembling functional crystalline materials.

Distance Controlled and Electrically Driven Photoluminescence Quench From Quantum Dot-Au Complexes

2010 ◽  
Vol 1257 ◽  
Author(s):  
Zhitao Kang ◽  
Jie Xu ◽  
Dinal Andreasen ◽  
Brent Karl Wagner
Keyword(s):  
Gold Nanoparticles ◽  
Protein Interactions ◽  
Near Infrared ◽  
Incident Light ◽  
Gold Surface ◽  
Electric Signal ◽  
Protein Protein Interactions ◽  
Quenching Effect ◽  
Quenching Efficiency ◽  
Pl Quenching

AbstractQuantum Dots (QDs) bound to gold nanoparticles have shown photoluminescence (PL) quenching dependent on distance between the two particles. The incident light from the QD couples to plasmon excitation of the metal when the frequencies of the light and the surface plasmon resonance (SPR) coincide, leading to a reduction in emitted PL in the system. The quenching effect of gold nanoparticles on QDs was used to study protein-protein interactions with the potential for drug screening applications. CdTe and CdHgTe QDs with emission wavelengths from 500˜900nm were synthesized and gold nanospheres and nanorods with controlled absorption in the visible and near-infrared (NIR) wavelength regions were prepared. The PL quenching of QD-Protein-Protein-Au complexes was studied as a function of Au concentration, QD size and protein type. A quenching efficiency of up to 90% was observed. The QD-Au complexes were also studied for electric potential sensing. The surface of the QDs was negatively charged due to thiol ligands capping. By applying a positive potential on the gold or gold nanoparticle attached substrate, the local electric field between the substrate and the statically charged QDs would pull the QDs closer to the gold surface and quench the QD PL. PL quenching of QD with Au was studied as a function of electric signal and QD type. In this methodology, electric signals were effectively converted to optical signals.

scholarly journals A Multiplexed Bacterial Two-Hybrid for Rapid Characterization of Protein-Protein Interactions and Iterative Protein Design

2020 ◽  
Author(s):  
W. Clifford Boldridge ◽  
Ajasja Ljubetič ◽  
Hwangbeom Kim ◽  
Nathan Lubock ◽  
Dániel Szilágyi ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Coiled Coil ◽  
Building Blocks ◽  
Coiled Coils ◽  
Next Generation ◽  
Protein Protein Interactions ◽  
Library Size ◽  
Large Sets ◽  
Synthetic Cell ◽  
Two Hybrid

AbstractMyriad biological functions require protein-protein interactions (PPIs), and engineered PPIs are crucial for applications ranging from drug design to synthetic cell circuits. Understanding and engineering specificity in PPIs is particularly challenging as subtle sequence changes can drastically alter specificity. Coiled-coils are small protein domains that have long served as a simple model for studying the sequence-determinants of specificity and have been used as modular building blocks to build large protein nanostructures and synthetic circuits. Despite their simple rules and long-time use, building large sets of well-behaved orthogonal pairs that can be used together is still challenging because predictions are often inaccurate, and, as the library size increases, it becomes difficult to test predictions at scale. To address these problems, we first developed a method called the Next-Generation Bacterial Two-Hybrid (NGB2H), which combines gene synthesis, a bacterial two-hybrid assay, and a high-throughput next-generation sequencing readout, allowing rapid exploration of interactions of programmed protein libraries in a quantitative and scalable way. After validating the NGB2H system on previously characterized libraries, we designed, built, and tested large sets of orthogonal synthetic coiled-coils. In an iterative set of experiments, we assayed more than 8,000 PPIs, used the dataset to train a novel linear model-based coiled-coil scoring algorithm, and then characterized nearly 18,000 interactions to identify the largest set of orthogonal PPIs to date with twenty-two on-target interactions.

scholarly journals Amalgamation of 3D structure and sequence information for protein–protein interaction prediction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Kanchan Jha ◽  
Sriparna Saha
Keyword(s):  
Amino Acids ◽  
Deep Learning ◽  
Protein Interactions ◽  
3D Structure ◽  
Protein Sequences ◽  
Building Blocks ◽  
New Drugs ◽  
Sequence Information ◽  
Protein Protein Interactions ◽  
Structure Information

Abstract Protein is the primary building block of living organisms. It interacts with other proteins and is then involved in various biological processes. Protein–protein interactions (PPIs) help in predicting and hence help in understanding the functionality of the proteins, causes and growth of diseases, and designing new drugs. However, there is a vast gap between the available protein sequences and the identification of protein–protein interactions. To bridge this gap, researchers proposed several computational methods to reveal the interactions between proteins. These methods merely depend on sequence-based information of proteins. With the advancement of technology, different types of information related to proteins are available such as 3D structure information. Nowadays, deep learning techniques are adopted successfully in various domains, including bioinformatics. So, current work focuses on the utilization of different modalities, such as 3D structures and sequence-based information of proteins, and deep learning algorithms to predict PPIs. The proposed approach is divided into several phases. We first get several illustrations of proteins using their 3D coordinates information, and three attributes, such as hydropathy index, isoelectric point, and charge of amino acids. Amino acids are the building blocks of proteins. A pre-trained ResNet50 model, a subclass of a convolutional neural network, is utilized to extract features from these representations of proteins. Autocovariance and conjoint triad are two widely used sequence-based methods to encode proteins, which are used here as another modality of protein sequences. A stacked autoencoder is utilized to get the compact form of sequence-based information. Finally, the features obtained from different modalities are concatenated in pairs and fed into the classifier to predict labels for protein pairs. We have experimented on the human PPIs dataset and Saccharomyces cerevisiae PPIs dataset and compared our results with the state-of-the-art deep-learning-based classifiers. The results achieved by the proposed method are superior to those obtained by the existing methods. Extensive experimentations on different datasets indicate that our approach to learning and combining features from two different modalities is useful in PPI prediction.

scholarly journals Occurrence of the d-Proline Chemotype in Enzyme Inhibitors

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 558 ◽  
Author(s):  
Elena Lenci ◽  
Andrea Trabocchi
Keyword(s):  
Amino Acids ◽  
Protein Interactions ◽  
Medicinal Chemistry ◽  
Enzyme Inhibitors ◽  
Proteolytic Enzymes ◽  
Building Blocks ◽  
Protein Protein Interactions ◽  
Conformationally Constrained ◽  
Biological Outcomes ◽  
Insight Into

Natural and nonnatural amino acids represent important building blocks for the development of peptidomimetic scaffolds, especially for targeting proteolytic enzymes and for addressing protein–protein interactions. Among all the different amino acids derivatives, proline is particularly relevant in chemical biology and medicinal chemistry due to its secondary structure’s inducing and stabilizing properties. Also, the pyrrolidine ring is a conformationally constrained template that can direct appendages into specific clefts of the enzyme binding site. Thus, many papers have appeared in the literature focusing on the use of proline and its derivatives as scaffolds for medicinal chemistry applications. In this review paper, an insight into the different biological outcomes of d-proline and l-proline in enzyme inhibitors is presented, especially when associated with matrix metalloprotease and metallo-β-lactamase enzymes.

scholarly journals Internetwork connectivity of molecular networks across species of life

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tarun Mahajan ◽  
Roy D. Dar
Keyword(s):  
Molecular Interactions ◽  
Protein Interactions ◽  
Transcriptional Regulatory Network ◽  
Building Blocks ◽  
Hierarchical Organization ◽  
Molecular Networks ◽  
Protein Protein Interactions ◽  
Interacting Protein ◽  
Protein Protein Interaction ◽  
Eukaryotic Species

AbstractMolecular interactions are studied as independent networks in systems biology. However, molecular networks do not exist independently of each other. In a network of networks approach (called multiplex), we study the joint organization of transcriptional regulatory network (TRN) and protein–protein interaction (PPI) network. We find that TRN and PPI are non-randomly coupled across five different eukaryotic species. Gene degrees in TRN (number of downstream genes) are positively correlated with protein degrees in PPI (number of interacting protein partners). Gene–gene and protein–protein interactions in TRN and PPI, respectively, also non-randomly overlap. These design principles are conserved across the five eukaryotic species. Robustness of the TRN–PPI multiplex is dependent on this coupling. Functionally important genes and proteins, such as essential, disease-related and those interacting with pathogen proteins, are preferentially situated in important parts of the human multiplex with highly overlapping interactions. We unveil the multiplex architecture of TRN and PPI. Multiplex architecture may thus define a general framework for studying molecular networks. This approach may uncover the building blocks of the hierarchical organization of molecular interactions.

Self-Assembled 3D Free-Standing Superlattice of Gold Nanoparticles Driven by Interfacial Instability of Emulsion Droplets

2021 ◽  
Author(s):  
Xuejie Liu ◽  
Xuan Yue ◽  
Nan Yan ◽  
Wei Jiang
Keyword(s):  
Gold Nanoparticles ◽  
Three Dimensional ◽  
Building Blocks ◽  
Inorganic Nanoparticles ◽  
Interfacial Instability ◽  
Free Standing ◽  
Emulsion Droplets ◽  
Self Assembled

Three-dimensional (3D) superlattice materials self-assembled from functional inorganic nanoparticles (NPs) have attracted extensive attention due to the unique properties of the building blocks and additional intriguing collective properties derived from...

Protein-Directed Self-Assembly of Gold Nanoparticles

2005 ◽  
Vol 901 ◽  
Author(s):  
Alexey Vertegel ◽  
Wen Shang ◽  
Jonathan Dordick ◽  
Richard Siegel
Keyword(s):  
Gold Nanoparticles ◽  
Protein Interactions ◽  
Self Assembly ◽  
Low Ph ◽  
Molar Ratio ◽  
Protein Protein Interactions ◽  
Controlled Assembly ◽  
Antigen Complex

AbstractWe have employed protein-protein interactions for controlled assembly of gold nanoparticles. Stoichiometric 1:1 protein:nanoparticle conjugates were prepared for proteins known to strongly interact with each other and these interactions were used to self-assemble nanoparticles. Mixing equivalent amounts of the antigen-nanoparticle and antibody-nanoparticle conjugates resulted in the formation of nanoparticle dimers with a yield of about 60%. Trimers (yield ∼30%) can be obtained by mixing 2:1 antigen-nanoparticle with 1:1 antibody-nanoparticle conjugates in a molar ratio of 1:2. The structures are destroyed at low pH when the antibody-antigen complex dissociates.

scholarly journals Converting histidine-induced 3D protein arrays in crystals into their 3D analogues in solution by metal coordination cross-linking

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Xiaoyi Tan ◽  
Hai Chen ◽  
Chunkai Gu ◽  
Jiachen Zang ◽  
Tuo Zhang ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Structural Information ◽  
Building Blocks ◽  
Metal Coordination ◽  
Protein Protein Interactions ◽  
Protonation State ◽  
Physiological Conditions ◽  
Simple Cubic ◽  
Stacking Pattern ◽  
Crystal Structural

Abstract Histidine (His) residues represent versatile motifs for designing protein-protein interactions because the protonation state of the imidazole group of His is the only moiety in protein to be significantly pH dependent under physiological conditions. Here we show that, by the designed His motifs nearby the C4 axes, ferritin nanocages arrange in crystals with a simple cubic stacking pattern. The X-ray crystal structures obtained at pH 4.0, 7.0, and 9.0 in conjunction with thermostability analyses reveal the strength of the π–π interactions between two adjacent protein nanocages can be fine-tuned by pH. By using the crystal structural information as a guide, we constructed 3D protein frameworks in solution by a combination of the relatively weak His–His interaction and Ni2+-participated metal coordination with Glu residues from two adjacent protein nanocages. These findings open up a new way of organizing protein building blocks into 3D protein crystalline frameworks.

scholarly journals Identification of a New Vertebrate Nucleoporin, Nup188, with the Use of a Novel Organelle Trap Assay

2000 ◽  
Vol 11 (10) ◽  
pp. 3381-3396 ◽  
Author(s):  
Brian R. Miller ◽  
Maureen Powers ◽  
Minkyu Park ◽  
Wolfgang Fischer ◽  
Douglass J. Forbes
Keyword(s):  
Protein Interactions ◽  
Building Blocks ◽  
Nuclear Pore ◽  
Annulate Lamellae ◽  
Protein Protein Interactions ◽  
Gene Encoding ◽  
Step Potential ◽  
Trap Assay ◽  
Novel Protein

The study of the nuclear pore in vertebrates would benefit from a strategy to directly identify new nucleoporins and interactions between those nucleoporins. We have developed a novel two-step “organelle trap” assay involving affinity selection and in vitro pore assembly. In the first step, soluble proteins derived from Xenopusegg extracts are applied to a column containing a ligand of interest. The bound proteins are then tagged by biotinylation and eluted. In the second step, potential nucleoporins are selected for by virtue of their ability to assemble into annulate lamellae, a cytoplasmic mimic of nuclear pores. The incorporated proteins are then recognized by their biotin tag. Here we use the lectin wheat germ agglutinin (WGA) as ligand; WGA inhibits nuclear transport and has been shown to directly bind three known nucleoporins from Xenopus extract, Nup62, Nup98, and Nup214, all of which containN-acetylglucosamine residues. Under reduced-stringency conditions, three additional proteins bind to WGA–Sepharose and are revealed by the organelle trap assay. We identified all three as partner nucleoporins. Two were discovered to be XenopusNup93 and Nup205. The third is a novel vertebrate nucleoporin, Nup188. This new vertebrate protein, Xenopus Nup188, exists in a complex with xNup93 and xNup205. The Nup93-Nup188-Nup205 complex does not bind directly to WGA but binds indirectly via theN-acetylglucosamine–modified nucleoporins. A gene encoding human Nup188 was also identified. The discovery of vertebrate Nup188, related to a yeast nucleoporin, and its novel protein–protein interactions illustrates the power of the two-step organelle trap assay and identifies new building blocks for constructing the nuclear pore.

scholarly journals Synthetic Protein Circuits and Devices Based on Reversible Protein-Protein Interactions: An Overview

Life ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1171
Author(s):  
Stefano Rosa ◽  
Chiara Bertaso ◽  
Paolo Pesaresi ◽  
Simona Masiero ◽  
Andrea Tagliani
Keyword(s):  
Protein Interactions ◽  
De Novo ◽  
Cell Metabolism ◽  
Building Blocks ◽  
New Drugs ◽  
Cell Physiology ◽  
Protein Protein Interactions ◽  
Genetic Circuits ◽  
Cellular Targets ◽  
Synthetic Protein

Protein-protein interactions (PPIs) contribute to regulate many aspects of cell physiology and metabolism. Protein domains involved in PPIs are important building blocks for engineering genetic circuits through synthetic biology. These domains can be obtained from known proteins and rationally engineered to produce orthogonal scaffolds, or computationally designed de novo thanks to recent advances in structural biology and molecular dynamics prediction. Such circuits based on PPIs (or protein circuits) appear of particular interest, as they can directly affect transcriptional outputs, as well as induce behavioral/adaptational changes in cell metabolism, without the need for further protein synthesis. This last example was highlighted in recent works to enable the production of fast-responding circuits which can be exploited for biosensing and diagnostics. Notably, PPIs can also be engineered to develop new drugs able to bind specific intra- and extra-cellular targets. In this review, we summarize recent findings in the field of protein circuit design, with particular focus on the use of peptides as scaffolds to engineer these circuits.

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