Network-based methods for predicting essential genes or proteins: a survey

2019 ◽  
Vol 21 (2) ◽  
pp. 566-583 ◽  
Author(s):  
Xingyi Li ◽  
Wenkai Li ◽  
Min Zeng ◽  
Ruiqing Zheng ◽  
Min Li
Keyword(s):  
Drug Targets ◽  
Rapid Development ◽  
Essential Genes ◽  
Biological Information ◽  
Future Research ◽  
Dynamic Features ◽  
Laboratory Methods ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks ◽  
Topological Characteristics

Abstract Genes that are thought to be critical for the survival of organisms or cells are called essential genes. The prediction of essential genes and their products (essential proteins) is of great value in exploring the mechanism of complex diseases, the study of the minimal required genome for living cells and the development of new drug targets. As laboratory methods are often complicated, costly and time-consuming, a great many of computational methods have been proposed to identify essential genes/proteins from the perspective of the network level with the in-depth understanding of network biology and the rapid development of biotechnologies. Through analyzing the topological characteristics of essential genes/proteins in protein–protein interaction networks (PINs), integrating biological information and considering the dynamic features of PINs, network-based methods have been proved to be effective in the identification of essential genes/proteins. In this paper, we survey the advanced methods for network-based prediction of essential genes/proteins and present the challenges and directions for future research.

Network Controllability Analysis of Three Multiple-myeloma Patient Genetic Mutation Datasets

2020 ◽  
Author(s):  
Jose Angel Sanchez Martin ◽  
Ion Petre
Keyword(s):  
Drug Targets ◽  
Genetic Mutation ◽  
Directed Network ◽  
Initial State ◽  
Final State ◽  
Multiple Myeloma Patient ◽  
Protein Protein Interaction ◽  
Arbitrary Initial State ◽  
Protein Protein Interaction Networks ◽  
Network Controllability

Network controllability focuses on the concept of driving the dynamical system associated to a directed network of interactions from an arbitrary initial state to an arbitrary final state, through a well-chosen set of input functions applied in a minimal number of so-called input nodes. In earlier studies we and other groups demonstrated the potential of applying this concept in medicine. A directed network of interactions may be built around the main known drivers of the disease being studied, and then analysed to identify combinations of drug targets controlling survivability-essential genes in the network. This paper takes the next step and focuses on patient data. We demonstrate that comprehensive protein-protein interaction networks can be built around patient genetic data, and that network controllability can be used to identify possible personalised drug combinations. We discuss the algorithmic methods that can be used to construct and analyse these networks.

scholarly journals OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine

2019 ◽  
Author(s):  
Andrés López-Cortés ◽  
César Paz-y-Miño ◽  
Santiago Guerrero ◽  
Alejandro Cabrera-Andrade ◽  
Stephen J. Barigye ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Precision Medicine ◽  
Genetic Alterations ◽  
Essential Genes ◽  
Hallmarks Of Cancer ◽  
Panoramic View ◽  
Protein Protein Interaction ◽  
Consensus Strategy ◽  
Protein Protein Interaction Networks ◽  
Pan Cancer

SUMMARYBreast cancer (BC) is a heterogeneous disease where each OncoOmics approach needs to be fully understood as a part of a complex network. Therefore, the main objective of this study was to analyze genetic alterations, signaling pathways, protein-protein interaction networks, protein expression, dependency maps and enrichment maps in 230 previously prioritized genes by the Consensus Strategy, the Pan-Cancer Atlas, the Pharmacogenomics Knowledgebase and the Cancer Genome Interpreter, in order to reveal essential genes to accelerate the development of precision medicine in BC. The OncoOmics essential genes were rationally filtered to 144, 48 (33%) of which were hallmarks of cancer and 20 (14%) were significant in at least three OncoOmics approaches: RAC1, AKT1 CCND1, PIK3CA, ERBB2, CDH1, MAPK14, TP53, MAPK1, SRC, RAC3, PLCG1, GRB2, MED1, TOP2A, GATA3, BCL2, CTNNB1, EGFR and CDK2. According to the Open Targets Platform, there are 111 drugs that are currently being analyzed in 3151 clinical trials in 39 genes. Lastly, there are more than 800 clinical annotations associated with 94 genes in BC pharmacogenomics.

Network Controllability Analysis of Three Multiple-myeloma Patient Genetic Mutation Datasets

2020 ◽  
Vol 175 (1-4) ◽  
pp. 281-299 ◽  
Author(s):  
Jose Angel Sanchez Martin ◽  
Ion Petre
Keyword(s):  
Drug Targets ◽  
Genetic Mutation ◽  
Directed Network ◽  
Initial State ◽  
Final State ◽  
Multiple Myeloma Patient ◽  
Protein Protein Interaction ◽  
Arbitrary Initial State ◽  
Protein Protein Interaction Networks ◽  
Network Controllability

Network controllability focuses on the concept of driving the dynamical system associated to a directed network of interactions from an arbitrary initial state to an arbitrary final state, through a well-chosen set of input functions applied in a minimal number of so-called input nodes. In earlier studies we and other groups demonstrated the potential of applying this concept in medicine. A directed network of interactions may be built around the main known drivers of the disease being studied, and then analysed to identify combinations of drug targets controlling survivability-essential genes in the network. This paper takes the next step and focuses on patient data. We demonstrate that comprehensive protein-protein interaction networks can be built around patient genetic data, and that network controllability can be used to identify possible personalised drug combinations. We discuss the algorithmic methods that can be used to construct and analyse these networks.

scholarly journals Drug Target Protein-Protein Interaction Networks: A Systematic Perspective

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yanghe Feng ◽  
Qi Wang ◽  
Tengjiao Wang
Keyword(s):  
Protein Interactions ◽  
Drug Target ◽  
Drug Targets ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Ppi Network ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Topological Features ◽  
Protein Protein Interaction Networks

The identification and validation of drug targets are crucial in biomedical research and many studies have been conducted on analyzing drug target features for getting a better understanding on principles of their mechanisms. But most of them are based on either strong biological hypotheses or the chemical and physical properties of those targets separately. In this paper, we investigated three main ways to understand the functional biomolecules based on the topological features of drug targets. There are no significant differences between targets and common proteins in the protein-protein interactions network, indicating the drug targets are neither hub proteins which are dominant nor the bridge proteins. According to some special topological structures of the drug targets, there are significant differences between known targets and other proteins. Furthermore, the drug targets mainly belong to three typical communities based on their modularity. These topological features are helpful to understand how the drug targets work in the PPI network. Particularly, it is an alternative way to predict potential targets or extract nontargets to test a new drug target efficiently and economically. By this way, a drug target’s homologue set containing 102 potential target proteins is predicted in the paper.

scholarly journals AligNet: Alignment of Protein-Protein Interaction Networks

2019 ◽  
Author(s):  
R. Alberich ◽  
A. Alcalá ◽  
M. Llabrés ◽  
F. Rosselló ◽  
G. Valiente
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Biological Information ◽  
Global Alignment ◽  
Alignment Algorithm ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks

AbstractOne of the most difficult problems difficult problem in systems biology is to discover protein-protein interactions as well as their associated functions. The analysis and alignment of protein-protein interaction networks (PPIN), which are the standard model to describe protein-protein interactions, has become a key ingredient to obtain functional orthologs as well as evolutionary conserved pathways and protein complexes. Several methods have been proposed to solve the PPIN alignment problem, aimed to match conserved subnetworks or functionally related proteins. However, the right balance between considering network topology and biological information is one of the most difficult and key points in any PPIN alignment algorithm which, unfortunately, remains unsolved. Therefore, in this work, we propose AligNet, a new method and software tool for the pairwise global alignment of PPIN that produces biologically meaningful alignments and more efficient computations than state-of-the-art methods and tools, by achieving a good balance between structural matching and protein function conservation as well as reasonable running times.

Mycobacterial DNA Replication as a Target for Antituberculosis Drug Discovery

2017 ◽  
Vol 17 (19) ◽  
pp. 2129-2142 ◽  
Author(s):  
Renata Płocinska ◽  
Malgorzata Korycka-Machala ◽  
Przemyslaw Plocinski ◽  
Jaroslaw Dziadek
Keyword(s):  
Drug Resistance ◽  
Dna Replication ◽  
Drug Targets ◽  
Rapid Development ◽  
New Drugs ◽  
Drug Resistant ◽  
Antituberculosis Drug ◽  
Nucleotide Synthesis ◽  
Antituberculosis Therapy ◽  
Optimal Drug

Background: Mycobacterium tuberculosis (M. tuberculosis), the causative agent of tuberculosis, is a leading infectious disease organism, causing millions of deaths each year. This serious pathogen has been greatly spread worldwide and recent years have observed an increase in the number of multi-drug resistant and totally drug resistant M. tuberculosis strains (WHO report, 2014). The danger of tuberculosis becoming an incurable disease has emphasized the need for the discovery of a new generation of antimicrobial agents. The development of novel alternative medical strategies, new drugs and the search for optimal drug targets are top priority areas of tuberculosis research. Factors: Key characteristics of mycobacteria include: slow growth, the ability to transform into a metabolically silent - latent state, intrinsic drug resistance and the relatively rapid development of acquired drug resistance. These factors make finding an ideal antituberculosis drug enormously challenging, even if it is designed to treat drug sensitive tuberculosis strains. A vast majority of canonical antibiotics including antituberculosis agents target bacterial cell wall biosynthesis or DNA/RNA processing. Novel therapeutic approaches are being tested to target mycobacterial cell division, twocomponent regulatory factors, lipid synthesis and the transition between the latent and actively growing states. Discussion and Conclusion: This review discusses the choice of cellular targets for an antituberculosis therapy, describes putative drug targets evaluated in the recent literature and summarizes potential candidates under clinical and pre-clinical development. We focus on the key cellular process of DNA replication, as a prominent target for future antituberculosis therapy. We describe two main pathways: the biosynthesis of nucleic acids precursors – the nucleotides, and the synthesis of DNA molecules. We summarize data regarding replication associated proteins that are critical for nucleotide synthesis, initiation, unwinding and elongation of the DNA during the replication process. They are pivotal processes required for successful multiplication of the bacterial cells and hence they are extensively investigated for the development of antituberculosis drugs. Finally, we summarize the most potent inhibitors of DNA synthesis and provide an up to date report on their status in the clinical trials.

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