scholarly journals Use Chou’s 5-Step Rule to Classify Protein Modification Sites with Neural Network

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Chuandong Song ◽  
Bin Yang
Keyword(s):  
Neural Network ◽  
Drug Discovery ◽  
Disease Prevention ◽  
Protein Modification ◽  
Biological Activities ◽  
Post Translational Modification ◽  
Feature Description ◽  
Experimental Approaches ◽  
Auc Value ◽  
Better Than

Lysine malonylation is a novel-type protein post-translational modification and plays essential roles in many biological activities. Having a good knowledge of malonylation sites can provide guidance in many issues, including disease prevention and drug discovery and other related fields. There are several experimental approaches to identify modification sites in the field of biology. However, these methods seem to be expensive. In this study, we proposed malNet, which employed neural network and utilized several novel and effective feature description methods. It was pointed that ANN’s performance is better than other models. Furthermore, we trained the classifiers according to an original crossvalidation method named Split to Equal validation (SEV). The results achieved AUC value of 0.6684, accuracy of 54.93%, and MCC of 0.1045, which showed great improvement than before.

scholarly journals CirBiTree: Citrullination Site Inference Based on a Fuzzy Neural Network and Flexible Neural Tree

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Chuandong Song ◽  
Haifeng Wang
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Classification Model ◽  
Peptide Sequence ◽  
Sequence Information ◽  
Post Translational Modification ◽  
Fuzzy Neural ◽  
Human Complex ◽  
Better Than

Emerging evidence demonstrates that post-translational modification plays an important role in several human complex diseases. Nevertheless, considering the inherent high cost and time consumption of classical and typical in vitro experiments, an increasing attention has been paid to the development of efficient and available computational tools to identify the potential modification sites in the level of protein. In this work, we propose a machine learning-based model called CirBiTree for identification the potential citrullination sites. More specifically, we initially utilize the biprofile Bayesian to extract peptide sequence information. Then, a flexible neural tree and fuzzy neural network are employed as the classification model. Finally, the most available length of identified peptides has been selected in this model. To evaluate the performance of the proposed methods, some state-of-the-art methods have been employed for comparison. The experimental results demonstrate that the proposed method is better than other methods. CirBiTree can achieve 83.07% in sn%, 80.50% in sp, 0.8201 in F1, and 0.6359 in MCC, respectively.

scholarly journals Apolipoprotein E binds to and reduces serum levels of DNA-mimicking, pyrrolated proteins

2019 ◽  
Vol 294 (28) ◽  
pp. 11035-11045 ◽  
Author(s):  
Sayumi Hirose ◽  
Yusuke Hioki ◽  
Hiroaki Miyashita ◽  
Naoya Hirade ◽  
Jun Yoshitake ◽  
...  
Keyword(s):  
Apolipoprotein E ◽  
Protein Modification ◽  
Serum Proteins ◽  
Lipoprotein Metabolism ◽  
Serum Levels ◽  
Post Translational Modification ◽  
Naturally Occurring ◽  
Biochemical Assays ◽  
Lysine Residues ◽  
Better Than

Lysine N-pyrrolation, converting lysine residues to Nϵ-pyrrole-l-lysine, is a recently discovered post-translational modification. This naturally occurring reaction confers electrochemical properties onto proteins that potentially produce an electrical mimic to DNA and result in specificity toward DNA-binding molecules such as anti-DNA autoantibodies. The discovery of this unique covalent protein modification provides a rationale for establishing the molecular mechanism and broad functional significance of the formation and regulation of Nϵ-pyrrole-l-lysine–containing proteins. In this study, we used microbeads coupled to pyrrolated or nonpyrrolated protein to screen for binding activities of human serum-resident nonimmunoglobin proteins to the pyrrolated proteins. This screen identified apolipoprotein E (apoE) as a protein that innately binds the DNA-mimicking proteins in serum. Using an array of biochemical assays, we observed that the pyrrolated proteins bind to the N-terminal domain of apoE and that oligomeric apoE binds these proteins better than does monomeric apoE. Employing surface plasmon resonance and confocal microscopy, we further observed that apoE deficiency leads to significant accumulation of pyrrolated serum albumin and is associated with an enhanced immune response. These results, along with the observation that apoE facilitates the binding of pyrrolated proteins to cells, suggest that apoE may contribute to the clearance of pyrrolated serum proteins. Our findings uncover apoE as a binding target of pyrrolated proteins, providing a key link connecting covalent protein modification, lipoprotein metabolism, and innate immunity.

Natural Sesquiterpene Lactones in the Prevention and Treatment of Inflammatory Disorders and cancer: A Systematic Study of this Emerging Therapeutic Approach based on Chemical and Pharmacological Aspect

2020 ◽  
Vol 17 (9) ◽  
pp. 1102-1116
Author(s):  
Sudip Kumar Mandal ◽  
Utsab Debnath ◽  
Amresh Kumar ◽  
Sabu Thomas ◽  
Subhash Chandra Mandal ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Biological Activities ◽  
Sesquiterpene Lactones ◽  
Structural Diversity ◽  
Cancer Drug ◽  
Cancer Drug Discovery ◽  
Anti Cancer ◽  
Drug Discovery Program ◽  
Anti Inflammatory ◽  
Family Based

Background and Introduction: Sesquiterpene lactones are a class of secondary metabolite that contains sesquiterpenoids and lactone ring as pharmacophore moiety. A large group of bioactive secondary metabolites such as phytopharmaceuticals belong to this category. From the Asteraceae family-based medicinal plants, more than 5,000 sesquiterpene lactones have been reported so far. Sesquiterpene lactone-based pharmacophore moieties hold promise for broad-spectrum biological activities against cancer, inflammation, parasitic, bacterial, fungal, viral infection and other functional disorders. Moreover, these moiety based phytocompounds have been highlighted with a new dimension in the natural drug discovery program worldwide after the 2015 Medicine Nobel Prize achieved by the Artemisinin researchers. Objective: These bitter substances often contain an α, β-unsaturated-γ-lactone as a major structural backbone, which in recent studies has been explored to be associated with anti-tumor, cytotoxic, and anti-inflammatory action. Recently, the use of sesquiterpene lactones as phytomedicine has been increased. This study will review the prospect of sesquiterpene lactones against inflammation and cancer. Methods: Hence, we emphasized on the different features of this moiety by incorporating its structural diversity on biological activities to explore structure-activity relationships (SAR) against inflammation and cancer. Results: How the dual mode of action such as anti-inflammatory and anti-cancer has been exhibitedby these phytopharmaceuticals will be forecasted in this study. Furthermore, the correlation of anti-inflammatory and anti-cancer activity executed by the sesquiterpene lactones for fruitful phytotherapy will also be revealed in the present review in the milieu of pharmacophore activity relation and pharmacodynamics study as well. Conclusion: So, these metabolites are paramount in phytopharmacological aspects. The present discussion on the future prospect of this moiety based on the reported literature could be a guide for anti-inflammatory and anti-cancer drug discovery programs for the upcoming researchers.

Secondary Metabolites of Plant Origin containing Carbazole as Lead Molecule: A Review

2019 ◽  
Vol 05 ◽  
Author(s):  
Atul Sharma ◽  
Devender Pathak
Keyword(s):  
Drug Discovery ◽  
Heterocyclic Compounds ◽  
Biological Activities ◽  
Chemical Compounds ◽  
Lethal Effect ◽  
Chemical Diversity ◽  
Chemical Transformations ◽  
Pharmacological Effects ◽  
Structural Class ◽  
Biological Targets

Keeping this fact that study of a body is biology but life is all about chemicals and chemical transformations, many medicinal chemist start research in finding new and novel chemical compounds which having pharmacological activities. Most of those chemical compounds which are having active pharmacological effects are heterocyclic compounds. Heterocyclic compounds clutch a particular place among pharmaceutically active natural and synthetic compounds. The ability to serve both as biomimetics and reactive pharmacophores of heterocyclic nuclei is incredible and it has principally contributed to their unique value as traditional key elements of numerous drugs. These heterocyclic nuclei offer a huge area for new lead molecules for drug discovery and for generation of activity relationships with biological targets to enhance pharmacological effects. For these reasons, it is not surprising that this structural class has received special attention in drug discovery. The hydrogen bond acceptors and donors arranged in a manner of a semi-rigid skeleton in heterocyclic rings and therefore they can present a varied display of significant pharmacophores. Lead identification and optimization of drug target probable can be achieved by generation of chemical diversity produced by derivatization of heterocyclic pharmacophores with different groups or substituents. A tricyclic carbazole nucleus is an integral part of naturally occurring alkaloids and synthetic derivatives, possessing various potential biological activities such as anticancer, antimicrobial and antiviral. Binding mechanism of carbazole with target receptor as a molecule or fused molecule exhibits the potential lethal effect.

scholarly journals Diketopiperazine Gels: New Horizons from the Self-Assembly of Cyclic Dipeptides

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3376
Author(s):  
Marco Scarel ◽  
Silvia Marchesan
Keyword(s):  
Drug Discovery ◽  
Enzymatic Hydrolysis ◽  
Self Assembly ◽  
Biological Activities ◽  
Functional Materials ◽  
The Self ◽  
Cyclic Dipeptides ◽  
New Horizons ◽  
Concise Review

Cyclodipeptides (CDPs) or 2,5-diketopiperazines (DKPs) can exert a variety of biological activities and display pronounced resistance against enzymatic hydrolysis as well as a propensity towards self-assembly into gels, relative to the linear-dipeptide counterparts. They have attracted great interest in a variety of fields spanning from functional materials to drug discovery. This concise review will analyze the latest advancements in their synthesis, self-assembly into gels, and their more innovative applications.

scholarly journals Ubiquitination, Biotech Startups, and the Future of TRIM Family Proteins: A TRIM-Endous Opportunity

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1015
Author(s):  
Utsa Bhaduri ◽  
Giuseppe Merla
Keyword(s):  
Drug Discovery ◽  
Protein Degradation ◽  
Ubiquitin Ligase ◽  
Genetic Disorders ◽  
E3 Ubiquitin Ligase ◽  
Ubiquitin Ligases ◽  
E3 Ubiquitin Ligases ◽  
Post Translational Modification ◽  
Disease Biology ◽  
The Future

Ubiquitination is a post-translational modification that has pivotal roles in protein degradation and diversified cellular processes, and for more than two decades it has been a subject of interest in the biotech or biopharmaceutical industry. Tripartite motif (TRIM) family proteins are known to have proven E3 ubiquitin ligase activities and are involved in a multitude of cellular and physiological events and pathophysiological conditions ranging from cancers to rare genetic disorders. Although in recent years many kinds of E3 ubiquitin ligases have emerged as the preferred choices of big pharma and biotech startups in the context of protein degradation and disease biology, from a surface overview it appears that TRIM E3 ubiquitin ligases are not very well recognized yet in the realm of drug discovery. This article will review some of the blockbuster scientific discoveries and technological innovations from the world of ubiquitination and E3 ubiquitin ligases that have impacted the biopharma community, from biotech colossuses to startups, and will attempt to evaluate the future of TRIM family proteins in the province of E3 ubiquitin ligase-based drug discovery.

scholarly journals STUDY OF A MA16-BASED VERTEX TRIGGER FOR THE CDF EXPERIMENT

1995 ◽  
Vol 06 (05) ◽  
pp. 681-692
Author(s):  
R. ODORICO
Keyword(s):  
Neural Network ◽  
Response Time ◽  
Impact Parameter ◽  
Electronic Components ◽  
The Neural Network ◽  
Viable Solution ◽  
Impact Parameters ◽  
Input Variables ◽  
Better Than

A Neural Network trigger for [Formula: see text] events based on the SVT microvertex processor of experiment CDF at Fermilab is presented. It exploits correlations among track impact parameters and azimuths calculated by the SVT from the SVX microvertex detector data. The neural trigger is meant for implementation on the systolic Siemens microprocessor MA16, which has already been used in a neural-network trigger for experiment WA92 at CERN. A suitable set of input variables is found, which allows a viable solution for the preprocessing task using standard electronic components. The response time of the neural-network stage of the trigger, including preprocessing, can be estimated ~10 μs. Its precise value depends on the quantitative specifications of the output signals of the SVT, which is still in development. The performance of the neural-network trigger is found to be significantly better than that of a conventional trigger exclusively based on impact parameter data.

Protocatechuic Acid and Human Disease Prevention: Biological Activities and Molecular Mechanisms

2012 ◽  
Vol 19 (18) ◽  
pp. 2901-2917 ◽  
Author(s):  
R. Masella ◽  
C. Santangelo ◽  
M. D’Archivio ◽  
G. LiVolti ◽  
C. Giovannini ◽  
...  
Keyword(s):  
Disease Prevention ◽  
Human Disease ◽  
Molecular Mechanisms ◽  
Protocatechuic Acid ◽  
Biological Activities

Artificial neural network-based seismic detector

1995 ◽  
Vol 85 (1) ◽  
pp. 308-319 ◽  
Author(s):  
Jin Wang ◽  
Ta-Liang Teng
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Input Data ◽  
Seismic Event ◽  
Signal To Noise Ratio ◽  
Type B ◽  
Earthquake Detection ◽  
Seismic Event Detection ◽  
Artificial Neural ◽  
Better Than

Abstract An artificial neural network-based pattern classification system is applied to seismic event detection. We have designed two types of Artificial Neural Detector (AND) for real-time earthquake detection. Type A artificial neural detector (AND-A) uses the recursive STA/LTA time series as input data, and type B (AND-B) uses moving window spectrograms as input data to detect earthquake signals. The two AND's are trained under supervised learning by using a set of seismic recordings, and then the trained AND's are applied to another set of recordings for testing. Results show that the accuracy of the artificial neural network-based seismic detectors is better than that of the conventional algorithms solely based on the STA/LTA threshold. This is especially true for signals with either low signal-to-noise ratio or spikelike noises.

Sign in / Sign up

Export Citation Format

Share Document