Multitalented actors inside and outside the cell: recent discoveries add to the number of moonlighting proteins

2019 ◽  
Vol 47 (6) ◽  
pp. 1941-1948 ◽  
Author(s):  
Constance J. Jeffery
Keyword(s):  
Molecular Mechanisms ◽  
Food Crops ◽  
Bacterial Strains ◽  
Cellular Processes ◽  
Biochemical Pathways ◽  
The Past ◽  
Single Polypeptide Chain ◽  
New Antibiotics ◽  
Moonlighting Proteins ◽  
Single Polypeptide

During the past few decades, it's become clear that many enzymes evolved not only to act as specific, finely tuned and carefully regulated catalysts, but also to perform a second, completely different function in the cell. In general, these moonlighting proteins have a single polypeptide chain that performs two or more distinct and physiologically relevant biochemical or biophysical functions. This mini-review describes examples of moonlighting proteins that have been found within the past few years, including some that play key roles in human and animal diseases and in the regulation of biochemical pathways in food crops. Several belong to two of the most common subclasses of moonlighting proteins: trigger enzymes and intracellular/surface moonlighting proteins, but a few represent less often observed combinations of functions. These examples also help illustrate some of the current methods used for identifying proteins with multiple functions. In general, a greater understanding about the functions and molecular mechanisms of moonlighting proteins, their roles in the regulation of cellular processes, and their involvement in health and disease could aid in many areas including developing new antibiotics, predicting the functions of the millions of proteins being identified through genome sequencing projects, designing novel proteins, using biological circuitry analysis to construct bacterial strains that are better producers of materials for industrial use, and developing methods to tweak biochemical pathways for increasing yields of food crops.

An introduction to protein moonlighting

2014 ◽  
Vol 42 (6) ◽  
pp. 1679-1683 ◽  
Author(s):  
Constance J. Jeffery
Keyword(s):  
Transcription Factors ◽  
Protein Sequence ◽  
Polypeptide Chain ◽  
Biochemical Pathways ◽  
Single Polypeptide Chain ◽  
Potential Benefits ◽  
Moonlighting Proteins ◽  
Structure Databases ◽  
Single Polypeptide ◽  
And Function

Moonlighting proteins comprise a class of multifunctional proteins in which a single polypeptide chain performs multiple physiologically relevant biochemical or biophysical functions. Almost 300 proteins have been found to moonlight. The known examples of moonlighting proteins include diverse types of proteins, including receptors, enzymes, transcription factors, adhesins and scaffolds, and different combinations of functions are observed. Moonlighting proteins are expressed throughout the evolutionary tree and function in many different biochemical pathways. Some moonlighting proteins can perform both functions simultaneously, but for others, the protein's function changes in response to changes in the environment. The diverse examples of moonlighting proteins already identified, and the potential benefits moonlighting proteins might provide to the organism, such as through coordinating cellular activities, suggest that many more moonlighting proteins are likely to be found. Continuing studies of the structures and functions of moonlighting proteins will aid in predicting the functions of proteins identified through genome sequencing projects, in interpreting results from proteomics experiments, in understanding how different biochemical pathways interact in systems biology, in annotating protein sequence and structure databases, in studies of protein evolution and in the design of proteins with novel functions.

scholarly journals The Functions of ZIP8, ZIP14, and ZnT10 in the Regulation of Systemic Manganese Homeostasis

2020 ◽  
Vol 21 (9) ◽  
pp. 3304
Author(s):  
James W.W. Winslow ◽  
Kirsten H. Limesand ◽  
Ningning Zhao
Keyword(s):  
Antioxidant Defense ◽  
Molecular Mechanisms ◽  
Cell Function ◽  
Immune Cell ◽  
The Body ◽  
Metal Transporters ◽  
Cellular Processes ◽  
The Past ◽  
Genes Encoding ◽  
Essential Nutrient

As an essential nutrient, manganese is required for the regulation of numerous cellular processes, including cell growth, neuronal health, immune cell function, and antioxidant defense. However, excess manganese in the body is toxic and produces symptoms of neurological and behavioral defects, clinically known as manganism. Therefore, manganese balance needs to be tightly controlled. In the past eight years, mutations of genes encoding metal transporters ZIP8 (SLC39A8), ZIP14 (SLC39A14), and ZnT10 (SLC30A10) have been identified to cause dysregulated manganese homeostasis in humans, highlighting the critical roles of these genes in manganese metabolism. This review focuses on the most recent advances in the understanding of physiological functions of these three identified manganese transporters and summarizes the molecular mechanisms underlying how the loss of functions in these genes leads to impaired manganese homeostasis and human diseases.

scholarly journals Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods

2020 ◽  
Author(s):  
Farshid Shirafkan ◽  
Sajjad Gharaghani ◽  
Karim Rahimian ◽  
Reza Sajedi ◽  
Javad Zahiri
Keyword(s):  
Cross Validation ◽  
Classification Methods ◽  
Drug Target Discovery ◽  
Feature Vectors ◽  
Single Polypeptide Chain ◽  
Protein Functions ◽  
Moonlighting Proteins ◽  
Decision Tree Method ◽  
Single Polypeptide ◽  
Fold Cross Validation

Abstract Background: Moonlighting proteins (MPs) are a subclass of multifunctional proteins in which more than one independent or usually distinct function occurs in a single polypeptide chain. Identification of unknown cellular processes, understanding novel protein mechanisms, improving the prediction of protein functions, and gaining information about protein evolution are the main reasons to study MPs. They also play an important role in disease pathways and drug-target discovery. Since detecting MPs experimentally is quite a challenge, most of them were detected randomly. Therefore, introducing an appropriate computational approach seems to be rational. Results: In this study, we would like to represent a competent model for detecting moonlighting and non-moonlighting proteins by extracted features from protein sequences. Then, we will represent a scheme for detecting outlier proteins. To do so, 15 distinct feature vectors were used to study each one's effect on detecting MPs. Furthermore, 8 different classification methods were assessed to find the best performance. To detect outliers, each one of the classifications was implemented 100 times by 10 fold cross-validation on feature vectors, then proteins which miss classified 80 times or more, were grouped. This process was applied to every single feature vector and in the end, the intersection of these groups was determined as the outlier proteins. The results of 10 fold cross-validation on a dataset of 351 samples (containing 215 moonlighting and 136 non-moonlighting proteins) show that the decision tree method on all feature vectors has the highest performance among all methods in this research and also in other available methods. Besides, the study of outliers shows that 57 of 351 proteins in the dataset could be an appropriate candidate for the outlier. Among the outlier proteins, there are non-moonlighting proteins (such as P69797) that have been misclassified by 8 different classification methods with 16 different feature types. Because these moonlighting proteins have been obtained by computational methods, the results of this study could reduce the likelihood of hypothesizing that, these proteins are non-moonlighting. Conclusions: Moonlighting proteins are difficult to identify by experiments. Our method enables identification of novel moonlighting proteins using distinct feature vectors. It also indicates that a number of non-moonlight proteins are likely to be moonlight.

scholarly journals The “Stressful” Life of Cell Adhesion Molecules: On the Mechanosensitivity of Integrin Adhesome

2018 ◽  
Vol 140 (2) ◽  
Author(s):  
Hengameh Shams ◽  
Brenton D. Hoffman ◽  
Mohammad R. K. Mofrad
Keyword(s):  
Molecular Mechanisms ◽  
Current Knowledge ◽  
Mechanical Energy ◽  
Focal Adhesions ◽  
Local Stress ◽  
Local Composition ◽  
Functional Changes ◽  
Cellular Processes ◽  
Biochemical Pathways ◽  
Mechanochemical Signaling

Cells have evolved into complex sensory machines that communicate with their microenvironment via mechanochemical signaling. Extracellular mechanical cues trigger complex biochemical pathways in the cell, which regulate various cellular processes. Integrin-mediated focal adhesions (FAs) are large multiprotein complexes, also known as the integrin adhesome, that link the extracellular matrix (ECM) to the actin cytoskeleton, and are part of powerful intracellular machinery orchestrating mechanotransduction pathways. As forces are transmitted across FAs, individual proteins undergo structural and functional changes that involve a conversion of chemical to mechanical energy. The local composition of early adhesions likely defines the regional stress levels and determines the type of newly recruited proteins, which in turn modify the local stress distribution. Various approaches have been used for detecting and exploring molecular mechanisms through which FAs are spatiotemporally regulated, however, many aspects are yet to be understood. Current knowledge on the molecular mechanisms of mechanosensitivity in adhesion proteins is discussed herein along with important questions yet to be addressed, are discussed.

scholarly journals MoonProt 3.0: an update of the moonlighting proteins database

2020 ◽  
Vol 49 (D1) ◽  
pp. D368-D372
Author(s):  
Chang Chen ◽  
Haipeng Liu ◽  
Shadi Zabad ◽  
Nina Rivera ◽  
Emily Rowin ◽  
...  
Keyword(s):  
Data Bank ◽  
Transmembrane Helices ◽  
Additional Information ◽  
Single Polypeptide Chain ◽  
Open Access Database ◽  
Moonlighting Proteins ◽  
Version 2.0 ◽  
Single Polypeptide ◽  
Scop Classification ◽  
Relationship Of

Abstract MoonProt 3.0 (http://moonlightingproteins.org) is an updated open-access database storing expert-curated annotations for moonlighting proteins. Moonlighting proteins have two or more physiologically relevant distinct biochemical or biophysical functions performed by a single polypeptide chain. Here, we describe an expansion in the database since our previous report in the Database Issue of Nucleic Acids Research in 2018. For this release, the number of proteins annotated has been expanded to over 500 proteins and dozens of protein annotations have been updated with additional information, including more structures in the Protein Data Bank, compared with version 2.0. The new entries include more examples from humans, plants and archaea, more proteins involved in disease and proteins with different combinations of functions. More kinds of information about the proteins and the species in which they have multiple functions has been added, including CATH and SCOP classification of structure, known and predicted disorder, predicted transmembrane helices, type of organism, relationship of the protein to disease, and relationship of organism to cause of disease.

scholarly journals Stacking Interactions mediate Recognition in Ribosome Inactivating Protein

2014 ◽  
Vol 70 (a1) ◽  
pp. C1654-C1654
Author(s):  
Punit Kaur ◽  
Shavait Yamini ◽  
Gajraj Kushwaha ◽  
Mau Sinha ◽  
Sujata Sharma ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Dominant Role ◽  
Structural Basis ◽  
Stacking Interactions ◽  
Aromatic Rings ◽  
Single Polypeptide Chain ◽  
Single Polypeptide ◽  
Covalently Linked ◽  
Polypeptide Chains

Ribosome Inactivating Proteins (RIPs) are capable of inhibiting protein synthesis by catalytically hydrolyzing at specific purine residues from the sarcin / ricin loop of large ribosomal RNA. There are two types of RIPs: type 1 - RIPs (RIP-1) are single polypeptide chain proteins while type 2 - RIPs contain two polypeptide chains which are covalently linked by a disulphide bond. Studies have indicated that stacking interactions play a dominant role in the ligand binding to RIPs. However, the structural basis of these interactions with RIPs as well as the nature of stack pairing and associated molecular mechanisms are not clearly understood. In order to examine the significance of these stacking interactions and the role of various aromatic residues involved, we have carried out the structural analysis of the complexes of RIP-1 from Momordica balsamina (MbRIP-1) and crystallized it with six different sugar molecules, ribose, fucose, glucose, fructose, maltose and lactose. The crystals belong to hexagonal space group H3 with approximate cell dimension of a = b = 130 Å, c = 40.5 Å. The r.m.s. deviation for the Calpha atoms in the complexed structures was found to be in the range of 0.5 Å to 0.9 Å. The aromatic rings of sugars are seen to be involved in stacking with aromatic rings of Tyr 70 and Tyr 111. The side chain torsion angles chi1 and chi2 of Tyr 70 in the complexes with ribose, fucose, glucose, fructose, maltose and lactose were found to be 64° / 161°, 166° / 86°, 6° / 172°, 70° / 167°, 64° / 161° and -75° / 178° respectively. The sugars are held firmly in the binding site of RIP-1 with the help of stacking interactions and hydrogen bonds. The results presented here have revealed the significance of aromatic stack pairing and delineated the stabilizing role of tyrosine residue in these interactions.

scholarly journals Pathogen Moonlighting Proteins: From Ancestral Key Metabolic Enzymes to Virulence Factors

2021 ◽  
Vol 9 (6) ◽  
pp. 1300
Author(s):  
Luis Franco-Serrano ◽  
David Sánchez-Redondo ◽  
Araceli Nájar-García ◽  
Sergio Hernández ◽  
Isaac Amela ◽  
...  
Keyword(s):  
Primary Metabolism ◽  
Protein Targets ◽  
Pathogen Virulence ◽  
Single Polypeptide Chain ◽  
Moonlighting Proteins ◽  
Single Polypeptide ◽  
Main Ideas ◽  
Moonlighting Functions ◽  
Work First ◽  
Host Tissues

Moonlighting and multitasking proteins refer to proteins with two or more functions performed by a single polypeptide chain. An amazing example of the Gain of Function (GoF) phenomenon of these proteins is that 25% of the moonlighting functions of our Multitasking Proteins Database (MultitaskProtDB-II) are related to pathogen virulence activity. Moreover, they usually have a canonical function belonging to highly conserved ancestral key functions, and their moonlighting functions are often involved in inducing extracellular matrix (ECM) protein remodeling. There are three main questions in the context of moonlighting proteins in pathogen virulence: (A) Why are a high percentage of pathogen moonlighting proteins involved in virulence? (B) Why do most of the canonical functions of these moonlighting proteins belong to primary metabolism? Moreover, why are they common in many pathogen species? (C) How are these different protein sequences and structures able to bind the same set of host ECM protein targets, mainly plasminogen (PLG), and colonize host tissues? By means of an extensive bioinformatics analysis, we suggest answers and approaches to these questions. There are three main ideas derived from the work: first, moonlighting proteins are not good candidates for vaccines. Second, several motifs that might be important in the adhesion to the ECM were identified. Third, an overrepresentation of GO codes related with virulence in moonlighting proteins were seen.

scholarly journals Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Farshid Shirafkan ◽  
Sajjad Gharaghani ◽  
Karim Rahimian ◽  
Reza Hasan Sajedi ◽  
Javad Zahiri
Keyword(s):  
Cross Validation ◽  
Classification Methods ◽  
Drug Target Discovery ◽  
Feature Vectors ◽  
Single Polypeptide Chain ◽  
Protein Functions ◽  
Moonlighting Proteins ◽  
Tenfold Cross Validation ◽  
Single Polypeptide ◽  
Set Up

Abstract Background Moonlighting proteins (MPs) are a subclass of multifunctional proteins in which more than one independent or usually distinct function occurs in a single polypeptide chain. Identification of unknown cellular processes, understanding novel protein mechanisms, improving the prediction of protein functions, and gaining information about protein evolution are the main reasons to study MPs. They also play an important role in disease pathways and drug-target discovery. Since detecting MPs experimentally is quite a challenge, most of them are detected randomly. Therefore, introducing an appropriate computational approach to predict MPs seems reasonable. Results In this study, we introduced a competent model for detecting moonlighting and non-MPs through extracted features from protein sequences. We attempted to set up a well-judged scheme for detecting outlier proteins. Consequently, 37 distinct feature vectors were utilized to study each protein’s impact on detecting MPs. Furthermore, 8 different classification methods were assessed to find the best performance. To detect outliers, each one of the classifications was executed 100 times by tenfold cross-validation on feature vectors; proteins which misclassified 90 times or more were grouped. This process was applied to every single feature vector and eventually the intersection of these groups was determined as the outlier proteins. The results of tenfold cross-validation on a dataset of 351 samples (containing 215 moonlighting and 136 non-moonlighting proteins) reveal that the SVM method on all feature vectors has the highest performance among all methods in this study and other available methods. Besides, the study of outliers showed that 57 of 351 proteins in the dataset could be an appropriate candidate for the outlier. Among the outlier proteins, there were non-MPs (such as P69797) that have been misclassified in 8 different classification methods with 16 different feature vectors. Because these proteins have been obtained by computational methods, the results of this study could reduce the likelihood of hypothesizing whether these proteins are non-moonlighting at all. Conclusions MPs are difficult to be identified through experimentation. Using distinct feature vectors, our method enabled identification of novel moonlighting proteins. The study also pinpointed that a number of non-MPs are likely to be moonlighting.

The Research of New Inhibitors of Bacterial Methionine Aminopeptidase by Structure Based Virtual Screening Approach of ZINC DATABASE and In Vitro Validation

2020 ◽  
Vol 16 (4) ◽  
pp. 389-401 ◽  
Author(s):  
Hanane Boucherit ◽  
Abdelouahab Chikhi ◽  
Abderrahmane Bensegueni ◽  
Amina Merzoug ◽  
Jean-Michel Bolla
Keyword(s):  
Virtual Screening ◽  
Bacterial Survival ◽  
Methionine Aminopeptidase ◽  
Bacterial Strains ◽  
Microdilution Method ◽  
Zinc Database ◽  
Promising Target ◽  
New Antibiotics ◽  
Potential Inhibitors

Background: The great emergence of multi-resistant bacterial strains and the low renewal of antibiotics molecules are leading human and veterinary medicine to certain therapeutic impasses. Therefore, there is an urgent need to find new therapeutic alternatives including new molecules in the current treatments of infectious diseases. Methionine aminopeptidase (MetAP) is a promising target for developing new antibiotics because it is essential for bacterial survival. Objective: To screen for potential MetAP inhibitors by in silico virtual screening of the ZINC database and evaluate the best potential lead molecules by in vitro studies. Methods: We have considered 200,000 compounds from the ZINC database for virtual screening with FlexX software to identify potential inhibitors against bacterial MetAP. Nine chemical compounds of the top hits predicted were purchased and evaluated in vitro. The antimicrobial activity of each inhibitor of MetAP was tested by the disc-diffusion assay against one Gram-positive (Staphylococcus aureus) and two Gram-negative (Escherichia coli & Pseudomonas aeruginosa) bacteria. Among the studied compounds, compounds ZINC04785369 and ZINC03307916 showed promising antibacterial activity. To further characterize their efficacy, the minimum inhibitory concentration was determined for each compound by the microdilution method which showed significant results. Results: These results suggest compounds ZINC04785369 and ZINC03307916 as promising molecules for developing MetAP inhibitors. Conclusion: Furthermore, they could therefore serve as lead molecules for further chemical modifications to obtain clinically useful antibacterial agents.

Novel Findings of Anti-cancer Property of Propofol

2018 ◽  
Vol 18 (2) ◽  
pp. 156-165 ◽  
Author(s):  
Jiaqiang Wang ◽  
Chien-shan Cheng ◽  
Yan Lu ◽  
Xiaowei Ding ◽  
Minmin Zhu ◽  
...  
Keyword(s):  
General Anesthesia ◽  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Intravenous Anesthetic ◽  
The Past ◽  
Anti Cancer ◽  
Underlying Mechanisms ◽  
Recent Attention

Background: Propofol, a widely used intravenous anesthetic agent, is traditionally applied for sedation and general anesthesia. Explanation: Recent attention has been drawn to explore the effect and mechanisms of propofol against cancer progression in vitro and in vivo. Specifically, the proliferation-inhibiting and apoptosis-inducing properties of propofol in cancer have been studied. However, the underlying mechanisms remain unclear. Conclusion: This review focused on the findings within the past ten years and aimed to provide a general overview of propofol's malignance-modulating properties and the potential molecular mechanisms.

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