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 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.

Engineering an acetyllysine reader with photocrosslinking amino acid for interactome profiling

2021 ◽  
Author(s):  
Babu Sudhamalla ◽  
Anirban Roy ◽  
Soumen Barman ◽  
Jyotirmayee Padhan
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Protein Interactions ◽  
Unnatural Amino Acids ◽  
Protein Protein Interactions ◽  
Site Specific ◽  
Powerful Approach

The site-specific installation of light-activable crosslinker unnatural amino acids offers a powerful approach to trap transient protein-protein interactions both in vitro and in vivo. Herein, we engineer a bromodomain to...

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.

scholarly journals Getting into position: the catalytic mechanisms of protein ubiquitylation

2004 ◽  
Vol 379 (3) ◽  
pp. 513-525 ◽  
Author(s):  
Lori A. PASSMORE ◽  
David BARFORD
Keyword(s):  
Protein Interactions ◽  
Regulatory Elements ◽  
Substrate Selection ◽  
Protein Protein Interactions ◽  
Different Types ◽  
Catalytic Mechanisms ◽  
Cellular Pathways ◽  
Ubiquitin Conjugating Enzymes ◽  
Insight Into

The role of protein ubiquitylation in the control of diverse cellular pathways has recently gained widespread attention. Ubiquitylation not only directs the targeted destruction of tagged proteins by the 26 S proteasome, but it also modulates protein activities, protein–protein interactions and subcellular localization. An understanding of the components involved in protein ubiquitylation (E1s, E2s and E3s) is essential to understand how specificity and regulation are conferred upon these pathways. Much of what we know about the catalytic mechanisms of protein ubiquitylation comes from structural studies of the proteins involved in this process. Indeed, structures of ubiquitin-activating enzymes (E1s) and ubiquitin-conjugating enzymes (E2s) have provided insight into their mechanistic details. E3s (ubiquitin ligases) contain most of the substrate specificity and regulatory elements required for protein ubiquitylation. Although several E3 structures are available, the specific mechanistic role of E3s is still unclear. This review will discuss the different types of ubiquitin signals and how they are generated. Recent advances in the field of protein ubiquitylation will be examined, including the mechanisms of E1, E2 and E3. In particular, we discuss the complexity of molecular recognition required to impose selectivity on substrate selection and topology of poly-ubiquitin chains.

scholarly journals Positive and Negative Regulation of Poly(A) Nuclease

2004 ◽  
Vol 24 (12) ◽  
pp. 5521-5533 ◽  
Author(s):  
David A. Mangus ◽  
Matthew C. Evans ◽  
Nathan S. Agrin ◽  
Mandy Smith ◽  
Preetam Gongidi ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Protein Interactions ◽  
Binding Pocket ◽  
Negative Regulation ◽  
Single Amino Acid ◽  
Carboxy Terminus ◽  
Protein Protein Interactions ◽  
C Terminus

ABSTRACT PAN, a yeast poly(A) nuclease, plays an important nuclear role in the posttranscriptional maturation of mRNA poly(A) tails. The activity of this enzyme is dependent on its Pan2p and Pan3p subunits, as well as the presence of poly(A)-binding protein (Pab1p). We have identified and characterized the associated network of factors controlling the maturation of mRNA poly(A) tails in yeast and defined its relevant protein-protein interactions. Pan3p, a positive regulator of PAN activity, interacts with Pab1p, thus providing substrate specificity for this nuclease. Pab1p also regulates poly(A) tail trimming by interacting with Pbp1p, a factor that appears to negatively regulate PAN. Pan3p and Pbp1p both interact with themselves and with the C terminus of Pab1p. However, the domains required for Pan3p and Pbp1p binding on Pab1p are distinct. Single amino acid changes that disrupt Pan3p interaction with Pab1p have been identified and define a binding pocket in helices 2 and 3 of Pab1p's carboxy terminus. The importance of these amino acids for Pab1p-Pan3p interaction, and poly(A) tail regulation, is underscored by experiments demonstrating that strains harboring substitutions in these residues accumulate mRNAs with long poly(A) tails in vivo.

scholarly journals Structure/Function Analysis of the Vaccinia Virus F18 Phosphoprotein, an Abundant Core Component Required for Virion Maturation and Infectivity

2010 ◽  
Vol 84 (13) ◽  
pp. 6846-6860 ◽  
Author(s):  
Nadi T. Wickramasekera ◽  
Paula Traktman
Keyword(s):  
Amino Acids ◽  
Structure Function ◽  
Protein Interactions ◽  
Function Analysis ◽  
Aromatic Amino Acids ◽  
Protein Protein Interactions ◽  
Core Component ◽  
Virion Morphogenesis

ABSTRACT Poxvirus virions, whose outer membrane surrounds two lateral bodies and a core, contain at least 70 different proteins. The F18 phosphoprotein is one of the most abundant core components and is essential for the assembly of mature virions. We report here the results of a structure/function analysis in which the role of conserved cysteine residues, clusters of charged amino acids and clusters of hydrophobic/aromatic amino acids have been assessed. Taking advantage of a recombinant virus in which F18 expression is IPTG (isopropyl-β-d-thiogalactopyranoside) dependent, we developed a transient complementation assay to evaluate the ability of mutant alleles of F18 to support virion morphogenesis and/or to restore the production of infectious virus. We have also examined protein-protein interactions, comparing the ability of mutant and WT F18 proteins to interact with WT F18 and to interact with the viral A30 protein, another essential core component. We show that F18 associates with an A30-containing multiprotein complex in vivo in a manner that depends upon clusters of hydrophobic/aromatic residues in the N′ terminus of the F18 protein but that it is not required for the assembly of this complex. Finally, we confirmed that two PSSP motifs within F18 are the sites of phosphorylation by cellular proline-directed kinases in vitro and in vivo. Mutation of both of these phosphorylation sites has no apparent impact on virion morphogenesis but leads to the assembly of virions with significantly reduced infectivity.

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 MiRNA-Regulated Pathways for Hypertrophic Cardiomyopathy: Network-Based Approach to Insight into Pathogenesis

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 2016
Author(s):  
German Osmak ◽  
Natalia Baulina ◽  
Ivan Kiselev ◽  
Olga Favorova
Keyword(s):  
Hypertrophic Cardiomyopathy ◽  
Signaling Pathways ◽  
Protein Interactions ◽  
Target Gene ◽  
High Throughput Sequencing ◽  
Point Of View ◽  
Specific Gene ◽  
Protein Protein Interactions ◽  
Insight Into ◽  
Sarcomeric Genes

Hypertrophic cardiomyopathy (HCM) is the most common hereditary heart disease. The wide spread of high-throughput sequencing casts doubt on its monogenic nature, suggesting the presence of mechanisms of HCM development independent from mutations in sarcomeric genes. From this point of view, HCM may arise from the interactions of several HCM-associated genes, and from disturbance of regulation of their expression. We developed a bioinformatic workflow to study the involvement of signaling pathways in HCM development through analyzing data on human heart-specific gene expression, miRNA-target gene interactions, and protein–protein interactions, available in open databases. Genes regulated by a pool of miRNAs contributing to human cardiac hypertrophy, namely hsa-miR-1-3p, hsa-miR-19b-3p, hsa-miR-21-5p, hsa-miR-29a-3p, hsa-miR-93-5p, hsa-miR-133a-3p, hsa-miR-155-5p, hsa-miR-199a-3p, hsa-miR-221-3p, hsa-miR-222-3p, hsa-miR-451a, and hsa-miR-497-5p, were considered. As a result, we pinpointed a module of TGFβ-mediated SMAD signaling pathways, enriched by targets of the selected miRNAs, that may contribute to the cardiac remodeling in HCM. We suggest that the developed network-based approach could be useful in providing a more accurate glimpse on pathological processes in the disease pathogenesis.

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