scholarly journals A convex optimization approach for identification of human tissue-specific interactomes

2016 ◽  
Author(s):  
Shahin Mohammadi ◽  
Ananth Grama
Keyword(s):  
Human Tissue ◽  
Drug Targets ◽  
Protein Complexes ◽  
Disease Genes ◽  
Optimization Approach ◽  
Cell Type Specificity ◽  
Tissue Specific ◽  
Parkinson’S Diseases ◽  
Coordinated Expression ◽  
Validation Tests

AbstractMotivation:Analysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell-type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/ selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes.Results:We present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (ESEA, GO Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state of the art techniques. Finally, using case studies of Alzheimer’s and Parkinson’s diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets.Availability:http://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html

scholarly journals Walking on a Tissue-Specific Disease-Protein-Complex Heterogeneous Network for the Discovery of Disease-Related Protein Complexes

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Thibault Jacquemin ◽  
Rui Jiang
Keyword(s):  
Protein Complex ◽  
Heterogeneous Network ◽  
High Performance ◽  
Protein Complexes ◽  
Specific Protein ◽  
Disease Genes ◽  
Computational Systems Biology ◽  
Related Protein ◽  
Tissue Specific ◽  
Disease Protein

Besides the pinpointing of individual disease-related genes, associating protein complexes to human inherited diseases is also of great importance, because a biological function usually arises from the cooperative behaviour of multiple proteins in a protein complex. Moreover, knowledge about disease-related protein complexes could also enhance the inference of disease genes and pathogenic genetic variants. Here, we have designed a computational systems biology approach to systematically analyse potential relationships between diseases and protein complexes. First, we construct a heterogeneous network which is composed of a disease-disease similarity layer, a tissue-specific protein-protein interaction layer, and a protein complex membership layer. Then, we propose a random walk model on this disease-protein-complex network for identifying protein complexes that are related to a query disease. With a series of leave-one-out cross-validation experiments, we show that our method not only possesses high performance but also demonstrates robustness regarding the parameters and the network structure. We further predict a landscape of associations between human diseases and protein complexes. This landscape can be used to facilitate the inference of disease genes, thereby benefiting studies on pathology of diseases.

scholarly journals Tissue-specific genes as an underutilized resource in drug discovery

2018 ◽  
Author(s):  
Maria Ryaboshapkina ◽  
Mårten Hammar
Keyword(s):  
Drug Targets ◽  
Tissue Specificity ◽  
Drug Research ◽  
Phase 1 ◽  
Evolutionary Conservation ◽  
Disease Genes ◽  
Mendelian Disease ◽  
Tissue Specific ◽  
Protein Interactome ◽  
The Relationship

ABSTRACTTissue-specific genes are believed to be good drug targets due to improved safety. Here we show that this intuitive notion is not reflected in phase 1 and 2 clinical trials, despite the historic success of tissue-specific targets and their 2.3-fold overrepresentation among targets of marketed non-oncology drugs. We compare properties of tissue-specific genes and drug targets. We show that tissue-specificity of the target may also be related to efficacy of the drug. The relationship may be indirect (enrichment in Mendelian disease genes) or direct (elevated ability to spread perturbations in human protein-protein interactome for tissue-specifically produced enzymes and secreted proteins). Reduced evolutionary conservation of tissue-specific genes may represent a bottleneck for drug projects, prompting development of novel models with smaller evolutionary gap to humans. We highlight numerous open opportunities to use tissue-specific genes in drug research and hope that the current study will facilitate discovery efforts.

A Survey on Computational Methods for Essential Proteins and Genes Prediction

2019 ◽  
Vol 14 (3) ◽  
pp. 211-225 ◽  
Author(s):  
Ming Fang ◽  
Xiujuan Lei ◽  
Ling Guo
Keyword(s):  
Computational Methods ◽  
Drug Targets ◽  
Disease Genes ◽  
Essential Proteins ◽  
Experimental Identification ◽  
Cellular Life ◽  
Different Types ◽  
The Stability ◽  
Human Disease Genes ◽  
Biology Research

Background: Essential proteins play important roles in the survival or reproduction of an organism and support the stability of the system. Essential proteins are the minimum set of proteins absolutely required to maintain a living cell. The identification of essential proteins is a very important topic not only for a better comprehension of the minimal requirements for cellular life, but also for a more efficient discovery of the human disease genes and drug targets. Traditionally, as the experimental identification of essential proteins is complex, it usually requires great time and expense. With the cumulation of high-throughput experimental data, many computational methods that make useful complements to experimental methods have been proposed to identify essential proteins. In addition, the ability to rapidly and precisely identify essential proteins is of great significance for discovering disease genes and drug design, and has great potential for applications in basic and synthetic biology research. Objective: The aim of this paper is to provide a review on the identification of essential proteins and genes focusing on the current developments of different types of computational methods, point out some progress and limitations of existing methods, and the challenges and directions for further research are discussed.

scholarly journals Understanding multicellular function and disease with human tissue-specific networks

2015 ◽  
Vol 47 (6) ◽  
pp. 569-576 ◽  
Author(s):  
Casey S Greene ◽  
Arjun Krishnan ◽  
Aaron K Wong ◽  
Emanuela Ricciotti ◽  
Rene A Zelaya ◽  
...  
Keyword(s):  
Human Tissue ◽  
Tissue Specific

scholarly journals Tissue-Specific Transcriptional Targeting of a Replication-Competent Retroviral Vector

2002 ◽  
Vol 76 (24) ◽  
pp. 12783-12791 ◽  
Author(s):  
Christopher R. Logg ◽  
Aki Logg ◽  
Robert J. Matusik ◽  
Bernard H. Bochner ◽  
Noriyuki Kasahara
Keyword(s):  
Tumor Cells ◽  
Viral Vectors ◽  
High Efficiency ◽  
Leukemia Virus ◽  
Transduction Efficiency ◽  
Promoter Strength ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Tissue Specific

ABSTRACT The inability of replication-defective viral vectors to efficiently transduce tumor cells in vivo has prevented the successful application of such vectors in gene therapy of cancer. To address the need for more efficient gene delivery systems, we have developed replication-competent retroviral (RCR) vectors based on murine leukemia virus (MLV). We have previously shown that such vectors are capable of transducing solid tumors in vivo with very high efficiency. While the natural requirement of MLV infection for cell division imparts a certain degree of specificity for tumor cells, additional means for confining RCR vector replication to tumor cells are desirable. Here, we investigated the parameters critical for successful tissue-specific transcriptional control of RCR vector replication by replacing various lengths of the MLV enhancer/promoter with sequences derived either from the highly prostate-specific probasin (PB) promoter or from a more potent synthetic variant of the PB promoter. We assessed the transcriptional specificity of the resulting hybrid long terminal repeats (LTRs) and the cell type specificity and efficiency of replication of vectors containing these LTRs. Incorporation of PB promoter sequences effectively restricted transcription from the LTR to prostate-derived cells and imparted prostate-specific RCR vector replication but required the stronger synthetic promoter and retention of native MLV sequences in the vicinity of the TATA box for optimal replicative efficiency and specificity. Our results have thus identified promoter strength and positioning within the LTR as important determinants for achieving both high transduction efficiency and strict cell type specificity in transcriptionally targeted RCR vectors.

scholarly journals Are GPCRs Still a Source of New Targets?

2013 ◽  
Vol 18 (9) ◽  
pp. 947-966 ◽  
Author(s):  
Stephen L. Garland
Keyword(s):  
Drug Targets ◽  
Protein Complexes ◽  
X Ray Crystallography ◽  
Peptide Family ◽  
Wide Range ◽  
The Family ◽  
Receptor Pharmacology ◽  
Technical Advances ◽  
Allosteric Mechanisms ◽  
G Protein Coupled

G-protein–coupled receptors (GPCRs) still offer enormous scope for new therapeutic targets. Currently marketed agents are dominated by those with activity at aminergic receptors and yet they account for only ~10% of the family. Progress up until now with other subfamilies, notably orphans, Family A/peptide, Family A/lipid, Family B, Family C, and Family F, has been, at best, patchy. This may be attributable to the heterogeneous nature of GPCRs, their endogenous ligands, and consequently their binding sites. Our appreciation of receptor similarity has arguably been too simplistic, and screening collections have not necessarily been well suited to identifying leads in new areas. Despite the relative shortage of high-quality tool molecules in a number of cases, there is an emerging, and increasingly substantial, body of evidence associating many as yet “undrugged” receptors with a very wide range of diseases. Significant advances in our understanding of receptor pharmacology and technical advances in screening, protein X-ray crystallography, and ligand design methods are paving the way for new successes in the area. Exploitation of allosteric mechanisms; alternative signaling pathways such as G12/13, Gβγ, and β-arrestin; the discovery of “biased” ligands; and the emergence of GPCR-protein complexes as potential drug targets offer scope for new and much improved drugs.

scholarly journals Current Analytical Strategies in Studying Chromatin-Associated-Proteome (Chromatome)

Molecules ◽  
2021 ◽  
Vol 26 (21) ◽  
pp. 6694
Author(s):  
Niamat Khan ◽  
Sidra Shahid ◽  
Abdul R. Asif
Keyword(s):  
Drug Targets ◽  
Protein Complexes ◽  
Dynamic Structure ◽  
Associated Diseases ◽  
Specific Complex ◽  
Analytical Strategies ◽  
Associated Proteins ◽  
Therapeutic Molecules ◽  
Unique Nature ◽  
Mass Spectrometric Identification

Chromatin is a dynamic structure comprising of DNA and proteins. Its unique nature not only help to pack the DNA tightly within the cell but also is pivotal in regulating gene expression DNA replication. Furthermore it also protects the DNA from being damaged. Various proteins are involved in making a specific complex within a chromatin and the knowledge about these interacting partners is helpful to enhance our understanding about the pathophysiology of various chromatin associated diseases. Moreover, it could also help us to identify new drug targets and design more effective remedies. Due to the existence of chromatin in different forms under various physiological conditions it is hard to develop a single strategy to study chromatin associated proteins under all conditions. In our current review, we tried to provide an overview and comparative analysis of the strategies currently adopted to capture the DNA bounded protein complexes and their mass spectrometric identification and quantification. Precise information about the protein partners and their function in the DNA-protein complexes is crucial to design new and more effective therapeutic molecules against chromatin associated diseases.

scholarly journals A computational interactome and functional annotation for the human proteome

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
José Ignacio Garzón ◽  
Lei Deng ◽  
Diana Murray ◽  
Sagi Shapira ◽  
Donald Petrey ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Enrichment Analysis ◽  
Human Proteome ◽  
Gene Set Enrichment Analysis ◽  
Protein Protein Interactions ◽  
Functional Relationships ◽  
Structural Relationships ◽  
Human Proteins ◽  
Validation Tests

We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein’s function. We provide annotations for most human proteins, including many annotated as having unknown function.

scholarly journals On the scope and limitations of baker's yeast as a model organism for studying human tissue-specific pathways

2014 ◽  
Author(s):  
Shahin Mohammadi ◽  
Baharak Saberidokht ◽  
Shankar Subramaniam ◽  
Ananth Grama
Keyword(s):  
Drug Targets ◽  
Model Organism ◽  
Functional Space ◽  
Computational Method ◽  
Therapeutic Interventions ◽  
Human Tissues ◽  
Human Interactome ◽  
Tissue Specific ◽  
Complex Disorders ◽  
Human Genes

Budding yeast, S. cerevisiae, has been used extensively as a model organism for studying cellular processes in evolutionarily distant species, including humans. However, different human tissues, while inheriting a similar genetic code, exhibit distinct anatomical and physiological properties. Specific biochemical processes and associated biomolecules that differentiate various tissues are not completely understood, neither is the extent to which a unicellular organism, such as yeast, can be used to model these processes within each tissue. We propose a novel computational and statistical framework to systematically quantify the suitability of yeast as a model organism for different human tissues. We develop a computational method for dissecting the human interactome into tissue-specific cellular networks. Using these networks, we simultaneously partition the functional space of human genes, and their corresponding pathways, based on their conservation both across species and among different tissues. We study these sub-spaces in detail, and relate them to the overall similarity of each tissue with yeast. Many complex disorders are driven by a coupling of housekeeping (universally expressed in all tissues) and tissue-selective (expressed only in specific tissues) dysregulated pathways. We show that human-specific subsets of tissue-selective genes are significantly associated with the onset and development of a number of pathologies. Consequently, they provide excellent candidates as drug targets for therapeutic interventions. We also present a novel tool that can be used to assess the suitability of the yeast model for studying tissue-specific physiology and pathophysiology in humans.

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