Abstract

Compounds in bodily fluids and biological tissues that interact with medications are identified as drug targets. Discovering new targets for drugs is an essential aspect of the drug development process and is vital for producing innovative treatments in areas such as precision medicine and cancer therapy. Traditional in vitro or in vivo target-finding techniques slow down the speed of drug discovery due to the labor or time-intensive nature of the process. The advancement of discovery techniques and the implementation of various cutting-edge technologies have led to a significant improvement in the effectiveness of drug discovery, resulting in shorter cycle times and lower costs. This study encompasses novel methods for drug target identification, such as computer-assisted techniques, drug affinity response target stability, multi-omics analysis, gene editing, and nonsense-mediated m-RNA degradation.

Keywords

Introduction

Drug targets are biomolecules in the body that come into direct contact with a drug to create an interaction. The discovery of drug targets is crucial in the development of new drugs for cancer therapy and precision medicine (An and Yu 2021; Koivisto et al., 2022). Most drugs exert their effects by interacting with target molecules in vivo. The effectiveness of a drug largely depends on its target (Hwang et al., 2021). Therefore, the search for new drug targets has become the focus of intense competition in innovative drug research today. A good target should be safe, effective, clinically and commercially viable, and druggable (Gashaw et al., 2011; Zhao et al., 2023b). The ideal drug target should have the following characteristics: first, the drug target should be closely related to the target disease and its regulatory mechanism should be an important factor in the disease; second, it has one or more sites where it can bind to other structural substances; third, the drug target should be modifiable so that the drug can modulate it when needed to achieve a therapeutic effect; and third, the physiological effects arising from the structure of the substance need to play an essential role in a complex regulatory process. Finally, there may be endogenous small molecules or exogenous ligands that bind to them, ligands that have pharmacological effects and are known to be (Gashaw et al., 2011)

II. Emergence of new drug target discovery methods

Target discovery methods can be divided into two categories according to their focus on drug-centred target discovery and disease-centered target discovery. Of these,drug-centred target discovery focuses on identifying the molecular targets of existing drugs and characterizing the mechanisms of drug-target interactions.Disease centered target discovery focuses on the back translation of pathological phenotypes to animal and in-vitro models aiming to identify the biological molecules that are responsible for these phenotypes using genetic manipulation of these models. In the following section, we provide a categorical overview of different target discovery approaches, including DARTS, network and machine learning-based approaches, gene editing, NMD, and multi-omics, from the the perspective of both drug-centered and disease-centered target discovery.

II. 1 Drug-centred target discovery methods

 A. Drug affinity responsive target stability (DARTS) Under physiological conditions, proteins are in dynamic equilibrium. When a specific ligand (e.g., a drug) binds, a thermodynamically more stable state results due to hydrophobic, hydrogen bonding, or electrostatic interactions formed between the

B. Network-based and machine learning-based methods for predicting drug

targets

Target prediction based on network and machine learning methods has been essential for drug target interaction (DTI) prediction (Jung et al., 2022). DTI prediction problems can be divided into four categories: (i) known drugs and known targets; (ii) known drugs and new target candidates; (iii) new drugs and known targets; and (iv) new drugs and new target candidates. While the ultimate goal of network-based and machine-learning approaches is the interactive prediction of new drugs and target candidates, most approaches in the literature are limited to the first three categories (Bagherian et al., 2021).

3. Multiomics approach for drug target discovery Multiomics research explores the interactions between genes, proteins, metabolites, and other substances in an organism. This approach has now become one of the most important strategies in the drug target discovery process. The development of many multiomics technologies (e.g., proteomics, genomics, metabolomics, transcriptomics, and phenomics (Figure 1E)) has opened up more possibilities to search for biomarkers that are highly relevant to diseases to aid in the early diagnosis, treatment, and prognosis of diseases, as well as for discovering potential drug targets (Li et al., 2021; Zhang et al., 2021a). This section describes the multiomics techniques involved in the drug target discovery process. Proteomics: Proteins are the primary target type of most drugs, with 50% of pharmaceuticals targeting proteins. Therefore, proteomics is vital in drug target discovery. As early as 1998, Müllner et al. suggested that proteomics is one of the most potent techniques for drug target discovery (Müllner et al., 1998). Proteomics involves studying three aspects of proteins, namely, their expression levels, modifications, and interactions.

       
           
       
Fig.1

The application of multi-omics approaches provides valuable insights into disease mechanisms and potential drug targets, but multiple challenges are also present in the actual drug target discovery process: the interpretation of large-scale multiomics data is one of the major challenges to overcome. This process requires the use of sophisticated bioinformatics tools to extract meaningful biological information from large data sets (Jeong and Yoon 2023). Second, the disease process changes over time. multi-omic data at a single time point may not fully capture dynamic changes at the molecular level, leading researchers to have an incomplete understanding of disease progression and potential targets (Huang et al., 2011). Furthermore, although multi-omic data can reveal disease-associated molecular changes, the corresponding functional annotation of these molecular changes is challenging (Rauthan et al., 2023). Despite these limitations, multi-omics methods have not been copyedited and formatted. The final version may differ from this version.

Drug target discovery methods and strategies are still a powerful tool in the drug target discovery process. The combination of multi-omics result prediction and later experimental verification can significantly improve the stability of drug target discovery, which is important in drug target discovery.

III. Applications in the discovery of drug targets for the treatment of human diseases

A. Practical application of drug-centred target discovery methods

The design and screening of novel drugs require the premise of known targets, which makes target screening a critical part of the drug development process. DARTS was first proposed by Lomenick et al. in 2009, and the method is now widely used for drug target discovery (Lomenick et al., 2009). In mammals, based on the application of DARTS, Shi et al. showed that 5-aza-2'-deoxycytidine could enhance antitumor immunity in colorectal peritoneal metastases by targeting ABC A9- mediated cholesterol accumulation in macrophages (Shi et al., 2022). Yu et al. found that dictamnine could target and inhibit c-Met activity and downregulate the PI3K/AKT/mTOR and MAPK signaling pathways to inhibit lung cancer cell proliferation (Yu et al., 2022). In addition, DARTS has been used to identify therapeutic target proteins for colorectal cancer (Derry et al., 2014), hepatocellular carcinoma (An et al., 2022), and osteosarcoma cell proliferation (Zhu et al., 2021)

2. Practical application of disease-centred target discovery methods

Gene editing technology is also one of the most essential tools for drug target discovery, the most important of which is the application of CRISPR/Cas9 library screening. There are three scenarios depending on the type of library chosen. (i) CRISPR KO libraries have been found in studies related to drug target discovery in many cancers, such as colorectal cancer (CAC) (Ringel et al., 2020), pancreatic ductal adenocarcinoma (PDAC) (Steinhart et al., 2017; Ubhi et al., 2024), esophageal squamous cell carcinoma (ESCC) (Xu et al., 2023), hepatocellular carcinoma (HCC) (Bao et al., 2021), B-cell acute lymphoblastic leukemia (B-ALL) (Ramos et al., 2023; Han et al., 2017), and breast cancer (BC) (Guarducci et al., 2024). (ii) The discovery of drug targets is also extensive based on the CRISPRi library. An efficient C-G to GC base editor was developed using CRISPRi screening, improving target accuracy (Koblan et al., 2021). One study identified NSD2 as a target for treating lung adenocarcinoma through CRISPR interference in mouse models (Sengupta et al., 2021). Vest et al. identified potential targets for treating neurodegenerative diseases, such as lysosomes, by screening for genome-wide CRISPRi targets (Vest et al.,)

       
           
       
Fig.2

What is the role of receptors in how drugs work?

Identification of the target.
Medications are ineffective or unsafe in clinical trials, leading to their failure. Therefore, identifying and validating a target is a crucial step in the development of a new drug. A target is a general term that can refer to various biological entities such as proteins, genes, and RNA. An effective target must be capable of being targeted by drugs, as well as meeting safety requirements and both clinical and commercial demands. A 'druggable' target can be reached by a potential drug molecule, whether it's a small molecule or larger biologicals. When binding occurs, it triggers a biological reaction that can be evaluated in both in vitro and in vivo settings. It is currently understood that specific target classes like G-protein-coupled receptors (GPCRs) are more suitable for small molecule drug discovery, while antibodies excel in inhibiting protein/protein interactions. Effective identification and validation of targets boost trust in the link between target and disease, enabling investigation into potential mechanism-based side effects of target modulation.
Analyzing the biomedical data that is currently accessible has resulted in a notable rise in target identification. Within this framework, data mining involves utilizing a bioinformatics strategy to not just identify, but also choose and prioritize potential disease targets (Yang et al., 2009). The accessible data originates from diverse sources such as publications and patent information, gene expression and proteomics data, transgenic phenotyping, and compound profiling data. Methods for identification also involve analyzing the levels of mRNA and proteins to establish if they are present in the disease and if they are linked to the worsening or advancement of the disease.

       
           
       
Validation of target

Once the target has been recognized, they must then be prosecuted to the fullest extent of the law. Validation methods vary from using in vitro tools and whole animal models to altering a specific target in patients with diseases. Though each method is valid on its own, utilizing multiple validations significantly boosts confidence in the outcome (Figure 3).

The identification and validation of targets is a process that serves multiple functions. IHC, immunohistochemistry technique.

Antisense technology involves using chemically modified oligonucleotides that resemble RNA and are specifically designed to complement a segment of target mRNA molecules (Henning and Beste, 2002). The antisense oligonucleotide binding to the target mRNA inhibits the translational machinery from binding, thus halting the production of the encoded protein. Researchers at Abbott Laboratories showcased the effectiveness of antisense technology by creating antisense probes for the rat P2X3 receptor. Administered via an intrathecal mini pump, phosphorothioate antisense P2X3 oligonucleonucleotides showed significant anti-hyperalgesic effects in the Complete Freund's Adjuvant model, indicating the clear involvement of this receptor in chronic inflammatory conditions and preventing toxicities linked to bolus injection. After the antisense oligonucleotides were no longer given, receptor function and pain responses came back. Unlike gene knockout, antisense oligonucleotide effects can be reversed, but the presence of antisense must be maintained for target protein inhibition. Nevertheless, the chemistry involved in synthesizing oligonucleotides has led to the production of molecules that have restricted bioavailability and significant toxicity, posing challenges for their in vivo application. This issue has been exacerbated by vague actions, issues with controlling these tools, and a limited range of options when choosing nucleotide probes (Henning and Beste, 2002)

       
           
       
CONCLUSION AND DISCUSSION

Target discovery for therapeutic drugs is the key to new drug development and a prerequisite for precision medicine. By advancing target discovery techniques, researchers can accelerate drug discovery, improve therapeutic outcomes, and move closer to the goal of precision medicine (Koivisto et al., 2022). At present, most experimental research related to target discovery uses a combination of multiple methods to discover and determine targets. Joint analysis of multiple methods and multiple data provides the possibility for a more comprehensive understanding of disease mechanisms (Li et al., 2022c; Wang et al., 2022a; Rodrigues and Bernardes 2020). For example, the continuous advancement and development of related technologies such as high-throughput sequencing, omics technology, and CRISPR-based library screening have greatly changed the form of drug target discovery (Liu et al., 2020; Kumar et al., 2024). In addition, the emergence of emerging drug target discovery strategie.

Drug repurposing: challenges and opportunities

Drug repurposing or repositioning aims to take a drug (approved or in advanced clinical stages or even a drug that has been withdrawn from the market, most of the time it involves small molecules but biologics like antibodies are also explored), thus a molecule that has undergone extensive safety and efficacy testing, and use it for an additional or unrelated indication (van den Berg et al., 2021; Roessler et al., 2021; Schipper et al., 2022). In some situations, even a withdrawn drug can be repurposed like thalidomide, originally intended as a sedative, and then used for treating a wide range of other conditions, including morning sickness in pregnant women. Thalidomide was then withdrawn due to causing birth defects but then was approved to treat leprosy (in 1998) and multiple myeloma (in 2006) (Begley et al., 2021). Drug repurposing approach can be very valuable in most cases including emergencies like a pandemic, for rare and neglected diseases [for which specific drug developments are in general missing in pharmaceutical companies (Scherman and Fetro, 2020; Roessler et al., 2021)]. This strategy is promoted as a cost- and time-effective approach for providing novel medicines. It is often claimed that repurposing drugs can be faster, more economical, less risky, and carry higher success rates as compared to traditional approaches, primarily because it is in theory possible to bypass early stages of development such as establishing drug safety. Other benefits that come with this approach include readily available products and manufacturing supply chains. Drug repurposing can be very profitable as in the case of fenfluramine (in 2022, the acquisition of Zogenix by UCB Pharma for about US$ 1.9 billion, https://www.ucb.com/stories-media/Press-Releases/article/UCB-Completes-Acquisition-of-Zogenix-Inc), a drug initially developed for weight loss, withdrawn and now used in several countries for the treatment of some forms of epilepsy (Odi et al., 2021). Yet, despite its advantages, drug repurposing suffers from several issues. One problem is that there are no possibilities for optimization of the therapeutic molecule without losing the repurposing potential because any small change in the structure of the therapeutic agent means a new full manufacturing process validation and preclinical safety development. Identifying an optimal dosage and formulation for the new disease indication can also be time-consuming and requires novel investigations while side effects can indeed arise due to the new indication or in some cases, doses need to be changed. Also, assessing the patent status of the drug to repurpose requires very specific skills. The molecules that are investigated for repurposing are either patented or off-patent, and in some cases, the intellectual property protection for the new indication may not be strong enough to engage in such a project. Overall, while drug repurposing is intuitively attractive as it offers shorter routes to the clinic, challenges throughout the entire process are usually substantial. Investigating molecular mechanisms behind repurposing can however be very valuable as it can help identify novel targets and as the repurposed drugs could be considered as starting points for the development of novel compounds (e.g., lenalidomide and pomalidomide are superior molecules derived from thalidomide) and as such emerge as a breakthrough innovation in a reduced amount of time and still reduced cost compared to starting from scratch. It could also be of interest to combine several approved drugs (in some cases with a newer drug) to increase effectiveness.
III. Applications in the discovery of drug targets for the treatment of human diseases

A. Practical application of drug-centred target discovery methods The design and screening of novel drugs require the premise of known targets, which makes target screening a critical part of the drug development process. DARTS was first proposed by Lomenick et al. in 2009, and the method is now widely used for drug target discovery (Lomenick et al., 2009). In mammals, based on the application of DARTS, Shi et al. showed that 5-aza-2'-deoxycytidine could enhance antitumor immunity in colorectal peritoneal metastases by targeting ABC A9- mediated cholesterol accumulation in macrophages (Shi et al., 2022). Yu et al. found that dictamnine could target and inhibit c-Met activity and downregulate the PI3K/AKT/mTOR and MAPK signaling pathways to inhibit lung cancer cell proliferation (Yu et al., 2022). In addition, DARTS has been used to identify therapeutic target proteins for colorectal cancer (Derry et al., 2014), hepatocellular carcinoma (An et al., 2022), and osteosarcoma cell proliferation (Zhu et al., 2021)

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