Research & Reviews: A Journal of Drug Design & Discovery

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The main aim in drug discovery is to design different ligands those work on specific drug targets. However, various effective drugs work through the modulation of many proteins than single target. Advancement in system biology are establishing a phenotypic strength and a network structure, which suggests that, the excellent selective compounds may be performed less than desired clinical efficacy in comparison to multi-target drugs. In this new appreciation of the role of polypharmacology, there are important implications for dealing with two main sources of attrition in efficacy and toxicity of drug development. Integrating network biology and polypharmacology promotes existing opportunities for drug targets. However, in order to get benefit in the poly pharmacological rational design, various challenges are there to be faced in the need for the new methods. Here in these fields, the need for establishment of the next model in the pursuit of advanced medicine: Network Pharmacology. 

Keywords: Receptor proteins, modulation, drug discovery, drug targets, polypharmacology

Cite this Article

 

Trilochan Satapathy, Ashish Kumar Netam, Jhakeshwar Prasad. Modulation of Receptor Proteins: A Recent Paradigm in Drug Discovery and Target. Research & Reviews: A Journal of Drug Design & Discovery. 2018; 5(1): 14–24p.

 

Modulation of Receptor Proteins: A Recent Paradigm in Drug Discovery and Target

 

Trilochan Satapathy, Ashish Kumar Netam*, Jhakeshwar Prasad

Department of Pharmacology, Columbia Institute of Pharmacy, Raipur, Chhattisgarh, India

 

Abstract

The main aim in drug discovery is to design different ligands those work on specific drug targets. However, various effective drugs work through the modulation of many proteins than single target. Advancement in system biology are establishing a phenotypic strength and a network structure, which suggests that, the excellent selective compounds may be performed less than desired clinical efficacy in comparison to multi-target drugs. In this new appreciation of the role of polypharmacology, there are important implications for dealing with two main sources of attrition in efficacy and toxicity of drug development. Integrating network biology and polypharmacology promotes existing opportunities for drug targets. However, in order to get benefit in the poly pharmacological rational design, various challenges are there to be faced in the need for the new methods. Here in these fields, the need for establishment of the next model in the pursuit of advanced medicine: Network Pharmacology. 

Keywords: Receptor proteins, modulation, drug discovery, drug targets, polypharmacology

 

*Author for Correspondence E-mail: [email protected]

 

 

INTRODUCTION

Over the past twenty years, there has been a significant decrease in the rate of translation of new drug candidates into effective clinical therapeutic agents, the successful cases of drug design have been going up significantly [1].The term pharmacology is the branch of science deals with complete study on drugs, including its pharmacokinetic and pharmacodynamic properties etc where as in a broad sense, drug can be any substance from natural, synthetic, semi-synthetic or marine sources those are used to modify or explore the physiological conditions or pathological states and are used for the benefit of the recipient. The various branches of pharmacology include behavioral pharmacology, general pharmacology, clinical pharmacology, neuro-pharmacology, psychopharmacology, Autacoids pharmacology, environmental pharmacology, biochemical and molecular pharmacology, cardiovascular pharmacology, gastrointestinal pharmacology, respiratory tract pharmacology etc.

 

Network pharmacology is the combination of chemical biology and network science which is very recent approach to drug discovery and also differs from conventional drug discovery approaches, which is generally based on highly specific targeting of a single protein. It possess a potential to provide new treatments for multiple disorders where conventional approaches do not able to deliver satisfactory therapies [2]. It involves the application of network pharmacological analysis to determine the set of proteins most critical in any disease and then chemical biology to identify molecules capable of targeting that set of proteins. The main cause was strongly attributed to the ideology for drug design in traditional pharmacology based on the view of a drug - a target - a disease [3]. Many reasons have been argued for such decline of productivity in pharmaceutical research [4].

 

The aim of the recent approach to focus on more effective drugs that can be result from selective ligands to focus the selective target that may in turn regulate the signal transduction to exert the appropriate response. In the other way the specificity of the ligand towards its target may lead to reduction of undesirable effects [5]. It has been evidenced from the recent research that, many effective drugs may act on multiple targets rather than the specific target a condition called as polypharmacology [6]. When a ligand approaches a multiple site, it believed that the drug molecule exerts safety and enhancement of therapeutic efficacy. In this present era this new technique is called as network Pharmacology [7]. Network pharmacology is considered as an emerging tool in developing the relationship between the drug action and disease susceptibility gene [8]. Regular attempts have been made by researchers for repurposing accessible drug entity for different beneficial indications. Integration of systems biology and network pharmacology can be enhance the search for drug targets and will be helpful in designing new drugs, which focus multiple biological targets. Network pharmacology paved the way for novel therapeutic options as well as helps to improve safety and efficacy of existing medications [9].

 

AIM AND SCOPE

Network Pharmacology is a disciplinary science based on pharmacology, network biology, system biology, bioinformatics, computational science, and other related scientific topics. In particular, it is a network based science, like other new proposed science [10]. The purpose of network pharmacology is to understand network interactions between living organisms and drugs that affect normal or unusual biochemical function. It tries to take advantage of the medicinal mechanism of drug action in the biological network and helps in finding the goal of the drug and improving the efficacy of the drug[11].The scope of the network pharmacology is covered, but there is no limit; theories, algorithms, models and software of network pharmacology, network construction and interactions prediction, theories and methods on dynamics, optimization and control of pharmacological networks, network analysis of pharmacological networks, including flow (flux) balance analysis, topological analysis, network stability, etc, various pharmacological networks and interactions, factors that affect drug metabolism; (vii) network approach for searching targets and discovering medicines (including medicinal plants, etc); (viii) big data analytics of network pharmacology, etc[12].

 

NETWORK PHARMACOLOGY

Network Pharmacology is a unique approach to drug discovery and is the drug target network and biological network which involves the application of network analysis to establish the set of proteins in any disease or disorder and then chemical biology to recognize molecules capable of targeting that set of proteins. It has been potential to provide new treatments for complex diseases where conventional approaches have unsuccessful to deliver satisfactory therapies. It has emerged which attempts to understand drug actions and interactions with multiple targets. It uses computational power to scientifically catalogue the molecular interactions of a drug molecule in a living cell organism [13] (Figure 1). It appears as an important contrivance in understanding the underlying complex relationships between botanical formula and the whole body. It also attempts to discover new drug leads compound and targets and to repurpose existing drug molecules for different therapeutic conditions by allowing an impartial investigation of potential target spaces [14]. Knowledge about traditional systems of medicine play a vital role in the process of new drug discovery as well as formulation development. Integration of systems biology and network pharmacology may be possible to develop the drug molecules for next generation. Network pharmacology analysis not only opens up the door for new therapeutic options, but it also aims to improve the safety and effectiveness of existing medications [15].

 

POLYPHARMACOLOGY

A schematic workflow of network-based polypharmacology in drug discovery, network-based models enable the addition of molecular and medicinal profiles of drugs and processes in their cellular targets and phenotypes of various diseases [16]. Polypharmacology targets the biological systems consisting of cellular and molecular organization along with their molecular interaction and various signaling. The increasing availability of phenotypic profiling of the drug reaction has opened a promising possibility for a better understanding of the mechanism of action and resistance mechanism at a casual level [17]. Generally, these integrated data is incorporated into mathematical models to assume the potentially therapeutic effectiveness (Figure 2). Hence, computational methods are efficient for evaluation of target combinations [18] (Figure 3).

 

Fig. 1: Structural representation of Network Pharmacology.

 

 

Fig. 2: Structural representation of Polypharmacology.

 

Fig. 3: Diagrammatic representation of network polypharmacology for drug discovery.

 

 

CURRENT TECHNOLOGIES AND PROGRESS

Polypharmacology studies are significant in drug discovery and development. Though, the extensive coverage of all targets by experimental methods is still an industry-wide challenge. Apparently, the most experienced approach would be to use the -omics (proteomics, cheminformatics, and others) technologies. During the post genomic era various molecular data are generated which support to polypharmacological research. Many molecular databases originated from the public and private system made available and constantly helping to increase the size and number. These combinations help to integrate diverse information of molecular signaling pathways, binding study, adverse drug reaction as well as drug targets [19].

 

NETWORK BIOLOGY

A group of two scientists named Barabasi and Otlvai in the year 2004, First coined the term network biology. It includes theories, innovations, and applications of biological networks; Dynamics, optimization and control of biological networks; algorithms and programs of network analysis; ecological networks, and natural equilibrium; co-evolution, co-extinction, bio-diversity conservation; these are the different types of biological networks such as metabolic networks, protein-protein interaction networks, biochemical reaction networks, gene networks, transcriptional regulatory networks, cell cycle networks, phylogenetic networks, network motifs; physiological networks; network regulation of metabolic processes, human diseases and ecological systems; social networks, and epidemiological networks, etc [20]. In recent years, the theory and methodology of network biology have been establishing. Network biology involved in protein-protein interaction and various metabolic pathways. In the recent era of life science, the major role expected by network biology is remodeling, analysis and important functions etc. It significance of genetic networks is also evidence through the quickly increase in publications regarding network-related topics and the rising number of investigations dealing with that particular area [21]. 

SIGNAL TRANSDUCTION AND GENE REGULATORY NETWORKS

Cellular and molecular signals are initiated by the messengers which is responsible to transmit signals between the cells for cellular communication. The messengers may be endogenous ligands such as hormones, neurotransmitters etc. or any exogenous substances which causes activation or deactivation of cellular response depending upon their type. [22].A signal transduction pathway is a directed network of chemical reactions resulted from attachment of ligand with its specific site of respective receptors. A signaling cascade is a progression where signal transduction involves an increasing number of molecules in the steps from the stimulus to the response [23] (Figure 4). Gene regulation is a wide word the synthesis of proteins at the transcription step for cellular control. Which can also response of a cell to an internal stimulus. Often one gene is regulated by another gene via the corresponding protein (called transcription factor), thus gene regulation is coordinated in a gene regulatory network. They network directs the level of expression for each gene in the cell by controlling whether and how often that gene will be transcribed into RNA. Analogous to signaling cascades in signal transduction networks a gene can activate more genes in turn and an initial stimulus can trigger the expression of large sets of genes. As mentioned above we study signal transduction and gene regulation together [24] sketches both processes with signal transduction going from an external signal through several steps to the activation of a gene as one possible response and gene regulation going from a gene via a protein to another gene (Figure 5).
 

Fig. 4: Role of endogenous hormones in signal transduction and genetic network.

 

Fig. 5: Diagrammatic representation of networking in gene regulation.

 

BIOLOGICAL NETWORKS ARE SIMILAR IN STRUCTURE TO OTHER COMPLEX NETWORKS

As per the above discussion the experimental techniques which leads to the collections of ‘interactions’ between a variety of bimolecular have few, if any, quantitative labels on them, a high error rate and, in most cases, little cellular context. They provide an overview of the worldwide structure or topology of these imperative cellular networks [25]. In recent era, many similar structural features have been reported for biological networks, specifically metabolism. Metabolic networks represent the entire picture which is available of any molecular network at least for several model organisms and as a result it is an ideal subject for the study of large-scale network properties [26]. In these networks, nodes represent metabolites, and the edges between nodes are directed and represent enzymatic reactions that utilize one of the nodes as a substrate and produce the other as a product. By Barabasi and co-workers the pragmatic studies of metabolism in 43 organisms and co-workers which [27] proved that the several features in this organism are common [28].

 

BRIDGE BETWEEN NETWORK BIOLOGY AND NETWORK PHARMACOLOGY

When molecules interact with living cells is term as scientific catalogue [29]. It is also essential to understand the mechanism by which how the molecules maintain the relations to establish the complex technology. This led to the advancement of network biology [30]. Various approaches for network biology development were initiated that adopted computational methods to develop understand the relationship between the phenotypes and genotypes [31].  A novel approach have been initiated for the construction of gene networks by integrating micro array analysis and literature mining. [32, 33].  The Literature Mining and Microarray Analysis (LMMA) biological network has been move toward to enables researchers to carryout modern along with appropriate literature on specialized biological network and to make sense of the appropriate large-scale microarray dataset. [34]. The consequence of accumulated-data integration was appreciated by pharmacologists, and they began to look away from the classic lock-and-key concept theory as a far more complicated picture of drug action became clear in the post genomic era. The global mapping of pharmacological space discovered promiscuity; the receptors are the specific in nature and them binding of a chemical to more than one target [35]. As there can be multiple keys for a single lock, correspondingly, a single key can vigorous into multiple locks. Similarly, a ligand might interact with many receptors or targets and a target may provide accommodation different types of ligands [36]. This is also referred to as “polypharmacology.” The basic concept of network biology was used to put together an online catalogue of human genes and genetic disorders to well know the industry trends, and the properties of drug targets, and to study how drug targets are related to disease-gene products [37]. Thus, when the first drug-target network was constructed, isolated were expected based on the existed one-drug/one-target/one disease approach. Rather, the authors observed a rich network of polypharmacology interactions among drugs and their specific targets [38]. The concept “follow-on” drugs that already targeted proteins were observed suggested a need to improve the single target single-drug paradigm, as a single-protein and single-function relations are limited to accurately describing the reality of cellular processes. The concept of polypharmacology possess the previous idea as an unwanted property that needs to be removed or reduced drugs acting on single-targets. As per the rules of network biology, concurrent modulations of multiple targets are required for modifying phenotypes. Development of appropriate methods to help polypharmacology can develop an advance efficacy and predict the undesired off-target effects [39]. They observed that network biology and polypharmacology can illuminate the understanding of drug action. He introduced the term “network pharmacology.” This distinctive new approach to drug discovery can enable the paradigm shift from highly specific magic bulletbased drug discovery to multi-targeted drug discovery [26]. Network Pharmacology holds the potential to provide new treatments for complex and complex complications, and can lead to therapeutic development, where under each disease type, it can be adapted to prepare ligands for each complex signal. It can be expanded in the future and can go further for customized and personalized therapeutics. The integration of network biology with polypharmacology can deal with two major sources in the discovery and development of the drugs and their efficacy and toxicity. This integration makes a promise of expanding the recent opportunity space for drug targets [40] This proposal for network pharmacology will prove as the next model in drug discovery. The secondary suggestion was the development of multi-component drug formulations. The change in metabolism, bioavailability, and pharmacokinetics of formulation as well as safety would be the major concerns of this approach. The third strategy was to design a single compound with selective polypharmacology. According to the researcher, the third method is advantageous, as it would ease the dosing studies. Also, the regulatory barriers for the single compound are fewer compared to a formulation [26]. A computational framework, based on the retrograde model, a computational structure that integrates human protein-protein interaction, the phenotype similarity of the disease, and has been proposed to Gene-phenotype associations to catch complex relationships between phenotypes and genotype. It was based on the assumption that phenotypic similar diseases are due to functionally related genes [41]. Correlating protein Interaction network and Phenotype network to predict disease genes helps to uncover known disease genes and predict novel susceptibility candidates. The next application of this present study is to predict a human disease that can be exploited gene related phenotype that will be clustered together in a molecular interaction network. In turn this will facilitate the discovery of disease genes and help to analyze the co-operativity among genes. [42]. Network pharmacology was also used to develop miRNAsbased biomarkers [43]. For this, a network of miRNAs and their targets was constructed and further refined to study the data for specific diseases. This process integrated with literature mining was useful to develop potent miRNA markers for diseases. Network Pharmacology was also used to develop a drug gene-diseasecomodule [44]. Initially, a drug-disease network was constructed by information gathered from databases followed by the integration of gene data. The gene closeness was studied by developing a mathematical model. This network inferred the association of multiple genes for most of the diseases and target sharing of drugs and diseases. These kinds of networks give insight into new drug-disease associations and their molecular connections.

CHALLENGES FOR POLYPHARMACOLOGY

Despite their apparent development, polypharmacological approaches have been attributed to many challenges. The main limitation is that we only understand the path/mechanism of many diseases at the molecular level partially. It is extremely difficult to get complete polypharmacological network without the whole data. On the other hand, understanding the convoluted associations is also a challenging task after the complex networks built [45]. Other methods also have been to face different issues. For example, the inverse docking approach suffers from many short comings, including the difficulty of addressing the goal flexibility and low performance of algorithms [46, 47]. In the matter of text mining, it is still very difficult to regularly update the adequate information provided by different and nonsynchronized databases [48].

 

APPLICATIONS OF NETWORK PHARMACOLOGY

Network pharmacology has received incentives as a novel model for the discovery of medicines. This approach is increasingly popular in silico data because of the efficiency of the cost and the relatively good assessment capacity (Table1). Thus, in network analysis, future prospects have been promised in relation to the process of exploration and development of various medical and applications. [49]

 

CONCLUSION

Network Pharmacology is a current approach to drug design and discovery which includes system biology, network pharmacology, analysis, connectivity, redundancy. It represents an extraordinary scope for exploring and expanding the traditional knowledge to find solutions for the current problems challenging the drug discovery industry. Network pharmacology offers a way of thinking about drug discovery that simultaneously embraces efforts to improve clinical efficacy and understand side effects and toxicity two of the most important reason for failure. Various studies have shown the power of network analysis in understanding biological systems. The biological reasoning is forced to consider multi-targeted strategies on single-targeted approaches, yet such strategies are a minority activity in the pharmaceutical industry.The reason for this is that it is a difficult task to optimize many activities in order to balance properties like medicines and to control unwanted off-task effects.

 

Table 1: Applications of Network Pharmacology [49].

Traditional

Medicine

·    Scientific proof for use of Ayurvedic medicine

·    Understanding the justification of traditional formulations

·    Understanding the mechanism of action of Ayurvedicmedicines

·    Safety and efficacy of Ayurvedic medicines

·    Possible substitutes for scarce botanicals

·    Network-based designing and prescribing of plantformulations

·    Analysis of multiple bioactive, studying synergistic action

·    Botanical biomarkers for quality control

Pharmacology

·    To develop new leads from natural products

·    Understanding the mechanism of action of drugs

·    Determining the promising side effects of drugs

·    Predicting new indications

·