Drug discovery by targeting the protein-protein interactions involved in autophagy

Autophagy is a cellular process in which proteins and organelles are engulfed in autophagosomal vesicles and transported to the lysosome/vacuole for degradation. Protein-protein interactions (PPIs) play a crucial role at many stages of autophagy, which present formidable but attainable targets for autophagy regulation. Moreover, selective regulation of PPIs tends to have a lower risk in causing undesired off-target effects in the context of a complicated biological network. Thus, small-molecule regulators, including peptides and peptidomimetics, targeting the critical PPIs involved in autophagy provide a new opportunity for innovative drug discovery. This article provides general background knowledge of the critical PPIs involved in autophagy and reviews a range of successful attempts on discovering regulators targeting those PPIs. Successful strategies and existing limitations in this field are also discussed.

Small molecules targeting protein-protein interactions for cancer therapy

Protein-protein interactions (PPIs) are fundamental to many biological processes that play an important role in the occurrence and development of a variety of diseases. Targeting the interaction between tumour-related proteins with emerging small molecule drugs has become an attractive approach for treatment of human diseases, especially tumours. Encouragingly, selective PPI-based therapeutic agents have been rapidly advancing over the past decade, providing promising perspectives for novel therapies for patients with cancer. In this review we comprehensively clarify the discovery and development of small molecule modulators of PPIs from multiple aspects, focusing on PPIs in disease, drug design and discovery strategies, structure-activity relationships, inherent dilemmas, and future directions.

Exploring the association between de novo mutations and non-syndromic cleft lip with or without palate based on whole exome sequencing of case-parent trios / 北京大学学报(医学版)

OBJECTIVE@#To explore the association between de novo mutations (DNM) and non-syndromic cleft lip with or without palate (NSCL/P) using case-parent trio design.@*METHODS@#Whole-exome sequencing was conducted for twenty-two NSCL/P trios and Genome Analysis ToolKit (GATK) was used to identify DNM by comparing the alleles of the cases and their parents. Information of predictable functions was annotated to the locus with SnpEff. Enrichment analysis for DNM was conducted to test the difference between the actual number and the expected number of DNM, and to explore whether there were genes with more DNM than expected. NSCL/P-related genes indicated by previous studies with solid evidence were selected by literature reviewing. Protein-protein interactions analysis was conducted among the genes with protein-altering DNM and NSCL/P-related genes. R package "denovolyzeR" was used for the enrichment analysis (Bonferroni correction: P=0.05/n, n is the number of genes in the whole genome range). Protein-protein interactions among genes with DNM and genes with solid evidence on the risk factors of NSCL/P were predicted depending on the information provided by STRING database.@*RESULTS@#A total of 339 908 SNPs were qualified for the subsequent analysis after quality control. The number of high confident DNM identified by GATK was 345. Among those DNM, forty-four DNM were missense mutations, one DNM was nonsense mutation, two DNM were splicing site mutations, twenty DNM were synonymous mutations and others were located in intron or intergenic regions. The results of enrichment analysis showed that the number of protein-altering DNM on the exome regions was larger than expected (P < 0.05), and five genes (KRTCAP2, HMCN2, ANKRD36C, ADGRL2 and DIPK2A) had more DNM than expected (P < 0.05/(2×19 618)). Protein-protein interaction analysis was conducted among forty-six genes with protein-altering DNM and thirteen genes associated with NSCL/P selected by literature reviewing. Six pairs of interactions occurred between the genes with DNM and known NSCL/P-related genes. The score measuring the confidence level of the predicted interaction between RGPD4 and SUMO1 was 0.868, which was higher than the scores for other pairs of genes.@*CONCLUSION@#Our study provided novel insights into the development of NSCL/P and demonstrated that functional analyses of genes carrying DNM were warranted to understand the genetic architecture of complex diseases.

Dynamic conformational flexibility and molecular interactions of intrinsically disordered proteins

In order to improve crop plants in terms of their yield, drought resistance, pest resistance, nutritional value, etc.,modern agriculture has relied upon plant genetic engineering. Since the advent of recombinant DNA technology, several tools have been used for genetic transformations in plants such as Agrobacterium tumefaciens,virus-mediated gene transfer, direct gene transfer systems such as electroporation, particle gun, microinjectionand chemical methods. All these traditional methods lack specificity and the transgenes are integrated atrandom sites in the plant DNA. Recently novel techniques for gene targeting have evolved such as engineerednucleases such as Zinc Finger Nucleases, Transcription Activator like effector nucleases, Clustered regularinterspaced short palindromic repeats. Other advances include improvement in tools for delivery of geneediting components which include carrier proteins, and carbon nanotubes. The present review focuses on thelatest techniques for target specific gene delivery in plants, their expression and future directions in plantbiotechnology

Mining Polo-Box domain of Polo-like kinase 1 as a new therapeutic target for cancer / 生物工程学报

Polo-like kinase 1 (Plk1) is widely regarded as one of the most promising targets for cancer therapy due to its essential role in cell division and tumor cell survival. At present, most Plk1 inhibitors have been developed based on kinase domain, some of which are in clinical trial. However, inhibitors targeting kinase domain face off-target effect and drug resistance owing to the conserved nature and the frequent mutations in the ATP-binding pocket. In addition to a highly conserved kinase domain, Plk1 also contains a unique Polo-Box domain (PBD), which is essential for Plk1's subcellular localization and mitotic functions. Inhibitors targeting Plk1 PBD show stronger selectivity and less drug resistance for cancer therapy. Therefore, Plk1 PBD is an attractive target for the development of anti-cancer agents. In this review, we will summarize the up-to date drug discovery for targeting Plk1 PBD, including the molecular structure and cellular functions of Plk1 PBD. Small-molecule inhibitors targeting Plk1 PBD not only provide an opportunity to specifically inhibit Plk1 activity for cancer treatment, but also unveil novel biological basis regarding the molecular recognition of Plk1 and its substrates.

Comparative Analysis of Some Proteins Encoded by Genes Significantly Related to Diabetes

Aims: The study was performed with the aim of understanding the role of protein structures encoded by a few of those genes which show the most significant alterations in their expression under normal versus diabetic conditions. Study Design: The study involved identifying a few relevant genes and analysis of various components of their protein structures. Methodology: Nine genes were shortlisted based on the extensive search of available secondary data. The structures of proteins encoded by them were generated using standard online tools. Comparative models of each of them were also generated in reference to the gene PPARγ due to its high significance in both diabetes as well as obesity, one of its predominant contributing factors. Results: Our studies indicate that the protein structures have domains which can interact with each other as well as other signaling molecules and thereby contribute towards the transfer of information across the cells. Moreover, some of these proteins show significant overlap with the protein encoded by the gene PPARγ, indicating probable interactions between them. Conclusion: These preliminary observations are indicative of probable protein-protein interactions which may contribute towards disease pathology. Further studies on interactions between these domains of various proteins may throw light on this aspect. Since diabetes incidences are increasing exponentially across the world, further detailed analysis of the individual components of the protein structures may help in obtaining a better understanding of the molecular mechanisms that are involved in this disease. This study substantiates those findings which have reported the importance of genetics in diabetes.

TICA: Transcriptional Interaction and Coregulation Analyzer / 基因组蛋白质组与生物信息学报·英文版

Transcriptional regulation is critical to cellular processes of all organisms. Regulatory mechanisms often involve more than one transcription factor (TF) from different families, binding together and attaching to the DNA as a single complex. However, only a fraction of the regulatory partners of each TF is currently known. In this paper, we present the Transcriptional Interaction and Coregulation Analyzer (TICA), a novel methodology for predicting heterotypic physical interaction of TFs. TICA employs a data-driven approach to infer interaction phenomena from chromatin immunoprecipitation and sequencing (ChIP-seq) data. Its prediction rules are based on the distribution of minimal distance couples of paired binding sites belonging to different TFs which are located closest to each other in promoter regions. Notably, TICA uses only binding site information from input ChIP-seq experiments, bypassing the need to do motif calling on sequencing data. We present our method and test it on ENCODE ChIP-seq datasets, using three cell lines as reference including HepG2, GM12878, and K562. TICA positive predictions on ENCODE ChIP-seq data are strongly enriched when compared to protein complex (CORUM) and functional interaction (BioGRID) databases. We also compare TICA against both motif/ChIP-seq based methods for physical TF-TF interaction prediction and published literature. Based on our results, TICA offers significant specificity (average 0.902) while maintaining a good recall (average 0.284) with respect to CORUM, providing a novel technique for fast analysis of regulatory effect in cell lines. Furthermore, predictions by TICA are complementary to other methods for TF-TF interaction prediction (in particular, TACO and CENTDIST). Thus, combined application of these prediction tools results in much improved sensitivity in detecting TF-TF interactions compared to TICA alone (sensitivity of 0.526 when combining TICA with TACO and 0.585 when combining with CENTDIST) with little compromise in specificity (specificity 0.760 when combining with TACO and 0.643 with CENTDIST). TICA is publicly available at http://geco.deib.polimi.it/tica/.

Arrestins: structural disorder creates rich functionality

Arrestins are soluble relatively small 44-46 kDa proteins that specifically bind hundreds of active phosphorylated GPCRs and dozens of non-receptor partners. There are binding partners that demonstrate preference for each of the known arrestin conformations: free, receptor-bound, and microtubule-bound. Recent evidence suggests that conformational flexibility in every functional state is the defining characteristic of arrestins. Flexibility, or plasticity, of proteins is often described as structural disorder, in contrast to the fixed conformational order observed in high-resolution crystal structures. However, protein-protein interactions often involve highly flexible elements that can assume many distinct conformations upon binding to different partners. Existing evidence suggests that arrestins are no exception to this rule: their flexibility is necessary for functional versatility. The data on arrestins and many other multi-functional proteins indicate that in many cases, "order" might be artificially imposed by highly non-physiological crystallization conditions and/or crystal packing forces. In contrast, conformational flexibility (and its extreme case, intrinsic disorder) is a more natural state of proteins, representing true biological order that underlies their physiologically relevant functions.

Conformation-locked nucleation strategies ofα-helical peptides / 国际药学研究杂志

Protein-protein interactions(PPI)with large and shallow interfaces are generally undruggable targets. Many PPI in-volved in vital biological processes are mediated by helixes,therefore PPI can be easily targeted by helical epitope mimics. However, the application of peptide was limited by its conformational flexibility and low stability until the significant work was done by Arora ,et al who applied nucleation and crosslinking strategies to lock peptides in helical conformation. The conformation-locked strategies helps to improve peptide stability,cell permeability,and afterwards target intracellular PPI. At present,the conformation-locked strategies of peptides have achieved great development,and have become a hot spot in peptide research field. In this paper,the recent develop-ment,centering nucleation strategies,applications and bright prospects of helical conformation-locked peptides,are reviewed in order to provide theoretical basis for drug design based on PPI.

Identification of a novel target for cancer and anti-fibrotic therapy / 中国药理学与毒理学杂志

Gene transcription mechanisms are critical control points for cell function and differentiation as well as disease pathology. It has remained difficult to target gene transcription mechanisms with small molecule drugs due in part to the role of protein-protein interactions in transcription complexes. RhoA/C- GTPase regulation of the serum responsive transcription factor complex involving serum response factor (SRF) and myocardin-related transcription factor (MRTF) plays a key role in cancer and fibrotic mechanisms. In an attempt to disrupt this critical gene transcription mechanism, we undertook a high-throughput ″pathway screen″ using an SRE-Luciferase reporter which was activated by transient transfection of HEK293 cells with Ga13, an up- stream activator of RhoA and RhoC. The Rho/MRTF inhibitor tool compound CCG-1423 was identified in this screen. It and analogs such as CCG-203971 have been used extensively to disrupt myofibroblast activation and tissue fibrosis as well as melanoma cell migration and metastasis. In the present study, we have used immobilized compounds and mass spectroscopy to identify the molecular target of the CCG-203971 series of anti-fibrotic and anti-meta?static agents. It is a poorly studied intranuclear protein that participates in gene transcription regulation by NF-κB and MRTF/SRF mechanisms. This dual mechanism rationalizes the strong efficacy of CCG-203971 and related compounds as anti-fibrotic and anti-metastatic agents. The identification of a molecular target also greatly facilitates future compound development through structure- based drug discovery and target biology evaluation.

Water-mediated ionic interactions in protein structures.

It is well known that water molecules play an indispensable role in the structure and function of biological macromolecules. The water-mediated ionic interactions between the charged residues provide stability and plasticity and in turn address the function of the protein structures. Thus, this study specifically addresses the number of possible water-mediated ionic interactions, their occurrence, distribution and nature found in 90% non-redundant protein chains. Further, it provides a statistical report of different charged residue pairs that are mediated by surface or buried water molecules to form the interactions. Also, it discusses its contributions in stabilizing various secondary structural elements of the protein. Thus, the present study shows the ubiquitous nature of the interactions that imparts plasticity and flexibility to a protein molecule.

Microarray Data Analysis of Perturbed Pathways in Breast Cancer Tissues

Due to the polygenic nature of cancer, it is believed that breast cancer is caused by the perturbation of multiple genes and their complex interactions, which contribute to the wide aspects of disease phenotypes. A systems biology approach for the identification of subnetworks of interconnected genes as functional modules is required to understand the complex nature of diseases such as breast cancer. In this study, we apply a 3-step strategy for the interpretation of microarray data, focusing on identifying significantly perturbed metabolic pathways rather than analyzing a large amount of overexpressed and underexpressed individual genes. The selected pathways are considered to be dysregulated functional modules that putatively contribute to the progression of disease. The subnetwork of protein-protein interactions for these dysregulated pathways are constructed for further detailed analysis. We evaluated the method by analyzing microarray datasets of breast cancer tissues; i.e., normal and invasive breast cancer tissues. Using the strategy of microarray analysis, we selected several significantly perturbed pathways that are implicated in the regulation of progression of breast cancers, including the extracellular matrix-receptor interaction pathway and the focal adhesion pathway. Moreover, these selected pathways include several known breast cancer-related genes. It is concluded from this study that the present strategy is capable of selecting interesting perturbed pathways that putatively play a role in the progression of breast cancer and provides an improved interpretability of networks of protein-protein interactions.

The Birth,Development and Applications of Domain-Domain Interaction Databases / 生物化学与生物物理进展

Domains are evolutionarily conserved sequence units and they are structural and functional building blocks of proteins.Interaction between two proteins typically involves binding between specific domains, and identifying interacting domain pairs is an important step towards thoroughly understanding protein function and evolution, constructing protein-protein interaction(PPI) networks, and analyzing pathway at the domain level.A number of interacting and/or functionally linked domain pairs have been identified and the information was organized and hosted in many domain-domain interactions(DDI) databases with the help of further mining experimental data and computational predictions from various input data.First, the 8 computational predicting methods used to acquire DDI data will be introduced.Then the introduction of DDI public databases, including 3DID, iPfam, InterDom, DIMA and DOMINE will be given.And finally, some examples are described about applications of DDI in computational predicting interacting protein pairs, assessment of the reliability for PPI, protein domain annotation, and in pathway study.

Protein-protein interactions and their network analysis in bioinformatics / 上海第二医科大学学报

The ultimate goal of post-genome research is to understand a complete set of proteins in a living organism for their expression pattern and biological function,which is called proteomics.One of the major challenges in proteome research is to study the protein-protein interactions,and the emerging bioinformatics approaches present us tremendous advantages when dealing with protein interaction networking and data analysis.Useful bioinformatics tools include protein-protein interaction network mapping,topology of the network,structure of the module and comparison of the network.The technology advancement in this field brings further understandings to the structure and function of cells at the proteome level,which may eventually lead to the discovery of new drug targets and design methods.This paper attempts to review the current researches on protein-protein interaction with an emphasis on bioinformatics intervention,and also summarizes some widely used methods for network analysis.