Development of a novel inducer of protein–protein interactions based on aplyronine A

2018 ◽  
Vol 54 (68) ◽  
pp. 9537-9540 ◽  
Author(s):  
Takayuki Ohyoshi ◽  
Atsuhiro Takano ◽  
Mayu Namiki ◽  
Tomotaka Ogura ◽  
Yuto Miyazaki ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Biological Activities ◽  
Side Chain ◽  
Protein Protein Interactions ◽  
Swinholide A ◽  
Aplyronine A

An aplyronine A–swinholide A hybrid, consisting of the macrolactone part of aplyronine A and the side chain part of swinholide A, was designed, synthesized, and evaluated for biological activities.

The C29–C34 parts of antitumor macrolide aplyronine A serve as versatile actin-affinity tags

2021 ◽  
Author(s):  
Didik Huswo Utomo ◽  
Akari Fujieda ◽  
Kentaro Tanaka ◽  
Momoko Takahashi ◽  
Kentaro Futaki ◽  
...  
Keyword(s):  
Natural Products ◽  
Drug Development ◽  
Anticancer Drug ◽  
Protein Interactions ◽  
Side Chain ◽  
Protein Protein Interactions ◽  
Affinity Tags ◽  
Promising Strategy ◽  
Anticancer Drug Development ◽  
Aplyronine A

Anticancer drug development inspired by natural products based on protein–protein interactions (PPI) is a promising strategy. We developed structurally-simplified C29–C34 side-chain analogs of aplyronine A (ApA), an antitumor marine macrolide....

scholarly journals Distinct p53 acetylation cassettes differentially influence gene-expression patterns and cell fate

2006 ◽  
Vol 173 (4) ◽  
pp. 533-544 ◽  
Author(s):  
Chad D. Knights ◽  
Jason Catania ◽  
Simone Di Giovanni ◽  
Selen Muratoglu ◽  
Ricardo Perez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Fate ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Biological Activities ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
P53 Gene ◽  
Protein Protein Interactions

The activity of the p53 gene product is regulated by a plethora of posttranslational modifications. An open question is whether such posttranslational changes act redundantly or dependently upon one another. We show that a functional interference between specific acetylated and phosphorylated residues of p53 influences cell fate. Acetylation of lysine 320 (K320) prevents phosphorylation of crucial serines in the NH2-terminal region of p53; only allows activation of genes containing high-affinity p53 binding sites, such as p21/WAF; and promotes cell survival after DNA damage. In contrast, acetylation of K373 leads to hyperphosphorylation of p53 NH2-terminal residues and enhances the interaction with promoters for which p53 possesses low DNA binding affinity, such as those contained in proapoptotic genes, leading to cell death. Further, acetylation of each of these two lysine clusters differentially regulates the interaction of p53 with coactivators and corepressors and produces distinct gene-expression profiles. By analogy with the “histone code” hypothesis, we propose that the multiple biological activities of p53 are orchestrated and deciphered by different “p53 cassettes,” each containing combination patterns of posttranslational modifications and protein–protein interactions.

scholarly journals Side-Chain Conformational Preferences Govern Protein–Protein Interactions

2016 ◽  
Vol 138 (33) ◽  
pp. 10386-10389 ◽  
Author(s):  
Andrew M. Watkins ◽  
Richard Bonneau ◽  
Paramjit S. Arora
Keyword(s):  
Protein Interactions ◽  
Side Chain ◽  
Protein Protein Interactions ◽  
Conformational Preferences

scholarly journals Membrane-Mediated Protein-Protein Interactions of Cholesterol Side-Chain Cleavage Cytochrome P450 with its Associated Electron Transport Proteins

ChemPlusChem ◽  
2016 ◽  
Vol 81 (9) ◽  
pp. 995-1002 ◽  
Author(s):  
Clemens Kubeil ◽  
Joyee Chun In Yeung ◽  
Robert C. Tuckey ◽  
Raymond J. Rodgers ◽  
Lisandra L. Martin
Keyword(s):  
Cytochrome P450 ◽  
Electron Transport ◽  
Protein Interactions ◽  
Transport Proteins ◽  
Side Chain ◽  
Protein Protein Interactions ◽  
Side Chain Cleavage ◽  
Chain Cleavage ◽  
Electron Transport Proteins

scholarly journals Evolutionary couplings detect side-chain interactions

2018 ◽  
Author(s):  
Adam J. Hockenberry ◽  
Claus O. Wilke
Keyword(s):  
Protein Interactions ◽  
De Novo ◽  
Protein Structures ◽  
Side Chain ◽  
Protein Protein Interactions ◽  
Sequence Alignments ◽  
Practical Applications ◽  
Residue Contacts ◽  
Coupling Algorithms ◽  
Evolutionary Coupling

Patterns of amino acid covariation in large protein sequence alignments can inform the prediction of de novo protein structures, binding interfaces, and mutational effects. While algorithms that detect these so-called evolutionary couplings between residues have proven useful for practical applications, less is known about how and why these methods perform so well, and what insights into biological processes can be gained from their application. Evolutionary coupling algorithms are commonly benchmarked by comparison to true structural contacts derived from solved protein structures. However, the methods used to determine true structural contacts are not standardized and different definitions of structural contacts may have important consequences for interpreting the results from evolutionary coupling analyses and understanding their overall utility. Here, we show that evolutionary coupling analyses are significantly more likely to identify structural contacts between side-chain atoms than between backbone atoms. We use both simulations and empirical analyses to highlight that purely backbone-based definitions of true residue–residue contacts (i.e., based on the distance between Cα atoms) may underestimate the accuracy of evolutionary coupling algorithms by as much as 40% and that a commonly used reference point (Cβ atoms) underestimates the accuracy by 10–15%. These findings show that co-evolutionary outcomes differ according to which atoms participate in residue–residue interactions and suggest that accounting for different interaction types may lead to further improvements to contact-prediction methods.Significance StatementEvolutionary couplings between residues within a protein can provide valuable information about protein structures, protein-protein interactions, and the mutability of individual residues. However, the mechanistic factors that determine whether two residues will co-evolve remains unknown. We show that structural proximity by itself is not sufficient for co-evolution to occur between residues. Rather, evolutionary couplings between residues are specifically governed by interactions between side-chain atoms. By contrast, intramolecular contacts between atoms in the protein backbone display only a weak signature of evolutionary coupling. These findings highlight that different types of stabilizing contacts exist within protein structures and that these types have a differential impact on the evolution of protein structures that should be considered in co-evolutionary applications.

scholarly journals Protein Interaction Z Score Assessment (PIZSA): an empirical scoring scheme for evaluation of protein–protein interactions

2019 ◽  
Vol 47 (W1) ◽  
pp. W331-W337 ◽  
Author(s):  
Ankit A Roy ◽  
Abhilesh S Dhawanjewar ◽  
Parichit Sharma ◽  
Gulzar Singh ◽  
M S Madhusudhan
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Three Dimensional ◽  
Optimal Number ◽  
Dimensional Structure ◽  
Side Chain ◽  
Interface Residue ◽  
Z Score ◽  
Protein Protein Interactions ◽  
Residue Contacts

Abstract Our web server, PIZSA (http://cospi.iiserpune.ac.in/pizsa), assesses the likelihood of protein–protein interactions by assigning a Z Score computed from interface residue contacts. Our score takes into account the optimal number of atoms that mediate the interaction between pairs of residues and whether these contacts emanate from the main chain or side chain. We tested the score on 174 native interactions for which 100 decoys each were constructed using ZDOCK. The native structure scored better than any of the decoys in 146 cases and was able to rank within the 95th percentile in 162 cases. This easily outperforms a competing method, CIPS. We also benchmarked our scoring scheme on 15 targets from the CAPRI dataset and found that our method had results comparable to that of CIPS. Further, our method is able to analyse higher order protein complexes without the need to explicitly identify chains as receptors or ligands. The PIZSA server is easy to use and could be used to score any input three-dimensional structure and provide a residue pair-wise break up of the results. Attractively, our server offers a platform for users to upload their own potentials and could serve as an ideal testing ground for this class of scoring schemes.

scholarly journals Protein-Protein Interactions Prediction Based on Graph Energy and Protein Sequence Information

Molecules ◽  
2020 ◽  
Vol 25 (8) ◽  
pp. 1841 ◽  
Author(s):  
Da Xu ◽  
Hanxiao Xu ◽  
Yusen Zhang ◽  
Wei Chen ◽  
Rui Gao
Keyword(s):  
Amino Acids ◽  
Feature Extraction ◽  
Protein Interactions ◽  
Biological Activities ◽  
Practical Significance ◽  
Sequence Information ◽  
Data Sets ◽  
Protein Protein Interactions ◽  
Ppi Networks ◽  
Graph Energy

Identification of protein-protein interactions (PPIs) plays an essential role in the understanding of protein functions and cellular biological activities. However, the traditional experiment-based methods are time-consuming and laborious. Therefore, developing new reliable computational approaches has great practical significance for the identification of PPIs. In this paper, a novel prediction method is proposed for predicting PPIs using graph energy, named PPI-GE. Particularly, in the process of feature extraction, we designed two new feature extraction methods, the physicochemical graph energy based on the ionization equilibrium constant and isoelectric point and the contact graph energy based on the contact information of amino acids. The dipeptide composition method was used for order information of amino acids. After multi-information fusion, principal component analysis (PCA) was implemented for eliminating noise and a robust weighted sparse representation-based classification (WSRC) classifier was applied for sample classification. The prediction accuracies based on the five-fold cross-validation of the human, Helicobacter pylori (H. pylori), and yeast data sets were 99.49%, 97.15%, and 99.56%, respectively. In addition, in five independent data sets and two significant PPI networks, the comparative experimental results also demonstrate that PPI-GE obtained better performance than the compared methods.

scholarly journals High-resolution structures of a heterochiral coiled coil

2015 ◽  
Vol 112 (43) ◽  
pp. 13144-13149 ◽  
Author(s):  
David E. Mortenson ◽  
Jay D. Steinkruger ◽  
Dale F. Kreitler ◽  
Dominic V. Perroni ◽  
Gregory P. Sorenson ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Structural Information ◽  
Coiled Coil ◽  
Coiled Coils ◽  
Side Chain ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Polypeptide Chains ◽  
Packing Interactions

Interactions between polypeptide chains containing amino acid residues with opposite absolute configurations have long been a source of interest and speculation, but there is very little structural information for such heterochiral associations. The need to address this lacuna has grown in recent years because of increasing interest in the use of peptides generated from d amino acids (d peptides) as specific ligands for natural proteins, e.g., to inhibit deleterious protein–protein interactions. Coiled–coil interactions, between or among α-helices, represent the most common tertiary and quaternary packing motif in proteins. Heterochiral coiled–coil interactions were predicted over 50 years ago by Crick, and limited experimental data obtained in solution suggest that such interactions can indeed occur. To address the dearth of atomic-level structural characterization of heterochiral helix pairings, we report two independent crystal structures that elucidate coiled-coil packing between l- and d-peptide helices. Both structures resulted from racemic crystallization of a peptide corresponding to the transmembrane segment of the influenza M2 protein. Networks of canonical knobs-into-holes side-chain packing interactions are observed at each helical interface. However, the underlying patterns for these heterochiral coiled coils seem to deviate from the heptad sequence repeat that is characteristic of most homochiral analogs, with an apparent preference for a hendecad repeat pattern.

α-Helix mimetics as inhibitors of protein–protein interactions

2008 ◽  
Vol 36 (6) ◽  
pp. 1414-1417 ◽  
Author(s):  
Ishu Saraogi ◽  
Andrew D. Hamilton
Keyword(s):  
Protein Interactions ◽  
First Generation ◽  
Side Chain ◽  
Protein Protein Interactions ◽  
Substitution Pattern ◽  
Pathological Conditions ◽  
Synthetic Accessibility ◽  
Helix Mimetics ◽  
Viable Approach ◽  
Α Helix

The inhibition of protein–protein interactions using small molecules is a viable approach for the treatment of a range of pathological conditions that result from a malfunctioning of these interactions. Our strategy for the design of such agents involves the mimicry of side-chain residues on one face of the α-helix; these residues frequently play a key role in mediating protein–protein interactions. The first-generation terphenyl scaffold, with a 3,2′,2″-substitution pattern, is able to successfully mimic key helix residues and disrupt therapeutically relevant interactions, including the Bcl-XL–Bak and the p53–hDM2 (human double minute 2) interactions that are implicated in cancer. The second- and third-generation scaffolds have resulted in greater synthetic accessibility and more drug-like character in these molecules.

scholarly journals Interactions between Hepatitis Delta Virus Proteins

2000 ◽  
Vol 74 (12) ◽  
pp. 5509-5515 ◽  
Author(s):  
Gloria Moraleda ◽  
Kate Dingle ◽  
Preetha Biswas ◽  
Jinhong Chang ◽  
Harmon Zuccola ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Hepatitis Delta Virus ◽  
Biological Activities ◽  
Dominant Negative ◽  
Genome Replication ◽  
Protein Protein Interactions ◽  
Particle Assembly ◽  
Hepatitis Delta ◽  
Delta Virus

ABSTRACT The 195- and 214-amino-acid (aa) forms of the delta protein (δAg-S and δAg-L, respectively) of hepatitis delta virus (HDV) differ only in the 19-aa C-terminal extension unique to δAg-L. δAg-S is needed for genome replication, while δAg-L is needed for particle assembly. These proteins share a region at aa 12 to 60, which mediates protein-protein interactions essential for HDV replication. H. Zuccola et al. (Structure 6:821–830, 1998) reported a crystal structure for a peptide spanning this region which demonstrates an antiparallel coiled-coil dimer interaction with the potential to form tetramers of dimers. Our studies tested whether predictions based on this structure could be extrapolated to conditions where the peptide was replaced by full-length δAg-S or δAg-L, and when the assays were not in vitro but in vivo. Nine amino acids that are conserved between several isolates of HDV and predicted to be important in multimerization were mutated to alanine on both δAg-S and δAg-L. We found that the predicted hierarchy of importance of these nine mutations correlated to a significant extent with the observed in vivo effects on the ability of these proteins to (i) support intrans the replication of the HDV genome when expressed on δAg-S and (ii) act as dominant-negative inhibitors of replication when expressed on δAg-L. We thus infer that these biological activities of δAg depend on ordered protein-protein interactions.

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