The Therapeutic Target Database: an Internet resource for the primary targets of approved,clinical trial and experimental drugs

Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets. A challenge in drug discovery is to decide which targets to pursue from an increasing pool of potential targets, given the fact that few innovative targets have made it to the approval list each year. Knowledge of existing drug targets (both approved and within clinical trials) is highly useful for facilitating target discovery, selection, exploration and tool development. The Therapeutic Target Database (TTD) has been developed and updated to provide information on 358 successful targets, 251 clinical trial targets and 1254 research targets in addition to 1511 approved drugs, 1118 clinical trials drugs and 2331 experimental drugs linked to their primary targets (3257 drugs with available structure data). This review briefly describes the TTD database and illustrates how its data can be explored for facilitating target and drug searches, the study of the mechanism of multi-target drugs and the development of in silico target discovery tools.     

The role of emerging genomics and proteomics technologies in cancer drug target discovery

Cancer drugs have traditionally been identified in screens designed to produce broad biological end points such as cell death. A serious undesired outcome of drugs discovered in these screens is that the mechanism of drug action is unknown and such drugs often have adverse side effects. Designing cancer drugs that act on specific targets offer the advantage that the mechanism of drug action can be understood and accurately monitored in clinical trials leading to development of better drugs. The pharmacological industry has recently shifted to a target directed drug discovery model. However, until recently potential cancer drug targets comprised of only a small fraction of the human genome. The human genome project and high-throughput structural and functional genomics have dramatically increased the number of cancer drug targets. Deciphering cancer drug targets requires the understanding of biochemical pathways that are affected in the cancer genome. It has been suggested that utilization of Single-nucleotide polymorphisms (SNPs) will aid in identifying individuals at high risk of developing certain cancers, and will also help in development of tailored medication or identify genetic profiles of specific drug action and toxicity. Achieving successful new cancer drug development schemes will require a merger of research disciplines that include pharmacology, genomics, comparative genomics, functional genomics, proteomics and bioinformatics. In this review the significance and challenges of these rapidly evolving technologies in cancer drug target discovery are discussed.     

Herpes simplex viruses in antiviral drug discovery

Since the 1950's, herpes simplex viruses (HSV) have played prominent roles in the development of antivirals. The first efficacious antivirals, as well as the first safe for systemic use, were developed against HSV. It was only in 1995 when the first antiviral against a target not validated first with HSV was approved for clinical use (sequinavir). The early successes of targeting HSV DNA replication were most influential in developing the concept that antiviral drugs must target viral proteins. Such concept has ensured the safety of current antiviral drugs, which all target viral proteins. Current antivirals have proven to have no major negative effects on non-infected cells or treated patients. Because of their success widespread and use, however, these drugs have been found to have some limitations. Perhaps the clinically most important one is their ability to promptly select for drug-resistant viral strains. Owing to such limitations, cellular proteins are now considered as valid targets for novel antiviral drugs. The discovery that pharmacological CDK inhibitors (PCIs) inhibit HSV replication through novel mechanisms played a major role in this new appreciation of cellular proteins as potential targets for antivirals. This appreciation is reflected in the scheduling of PCIs to enter clinical trials as antivirals (against HIV). Herein, we will review the roles of HSV as model viruses in the discovery and development of antiviral drugs. The major focus will be on the recent discovery on the activities of PCIs against HSV and other viruses.     

Progress and problems in the exploration of therapeutic targets

Drugs exert their therapeutic effect by binding and regulating the activity of a particular protein or nucleic acid target. A large number of targets have been explored for drug discovery. Continuous effort has been directed at the search for new targets and more-extensive exploration of existing targets. Knowledge of these targets facilitates the understanding of molecular mechanisms of drugs and the effort required for drug discovery and target searches. Areas of progress, current focuses of research and development and the difficulties in target exploration are reviewed. The characteristics of the currently explored targets and their correlation to the level of difficulty for target exploration are analyzed. From these characteristics, simple rules can be derived for estimating the difficulty level of target exploration. The feasibility of predicting druggable proteins by using simple rules and sequence-derived physicochemical properties is also discussed.     

Trends in the exploration of therapeutic targets for the treatment of endocrine, metabolic and immune disorders

A number of therapeutic targets have been explored for developing drugs in the treatment of endocrine, metabolic and immune disorders. Continuous efforts and increasing interest have been directed at the search of new targets. Data from the therapeutic target database at http://bidd.nus.edu.sg/group/cjttd/ttd.asp, shows that there are 26, 24, and 22 targets of marketed drugs for the treatment of these three classes of diseases, respectively. The number of targets of investigational agents has reached 98, 124, and 72, respectively. An analysis of these targets, particularly those of recently approved drugs and patented investigational agents, provides useful hint about the general trends of target exploration, with current focus on drug discovery and the difficulties encountered in developing drugs against these targets. Multiple profiles of these targets have been analyzed to probe the sequence, structural, physicochemical and systems-related features contributing to the successful exploration of a target against these diseases.     

Trends in exploration of therapeutic targets

Lead discovery against a preselected therapeutic target is a key component in modern drug development. Continuous effort and increasing interest has been directed at the search for new targets, which has led to the identification of a growing number of them. Data from the therapeutic target database, at http://bidd.nus.edu.sg/group/cjttd/ttd.asp, show that, as of July 2004, the number of documented targets of marketed and investigational drugs has reached 1,174 distinct proteins (including subtypes) and 27 nucleic acids, 239 of which are targets of the marketed drugs. Analysis of these targets, particularly those of recently approved drugs and patented investigational agents, provide useful hints about general trends of target exploration and current focus in drug discovery for the treatment of high impact diseases needing effective or more treatment options.     

Contemporary medicinal chemistry strategies for the discovery and optimization of influenza inhibitors targeting vRNP constituent proteins

Influenza is an acute respiratory infectious disease caused by the influenza virus, affecting people globally and causing significant social and economic losses. Due to the inevitable limitations of vaccines and approved drugs, there is an urgent need to discover new anti-influenza drugs with different mechanisms. The viral ribonucleoprotein complex (vRNP) plays an essential role in the life cycle of influenza viruses, representing an attractive target for drug design. In recent years, the functional area of constituent proteins in vRNP are widely used as targets for drug discovery, especially the PA endonuclease active site, the RNA-binding site of PB1, the cap-binding site of PB2 and the nuclear export signal of NP protein. Encouragingly, the PA inhibitor baloxavir has been marketed in Japan and the United States, and several drug candidates have also entered clinical trials, such as favipiravir. This article reviews the compositions and functions of the influenza virus vRNP and the research progress on vRNP inhibitors, and discusses the representative drug discovery and optimization strategies pursued.     

药物发现过程中人工智能的应用研究进展

人工智能（AI）和机器学习不仅使药物发现和开发实现了质的飞跃,而且帮助药物开发进程进入现代化。机器学习和深度学习算法已应用于药物发现各个阶段,如先导化合物的筛选、多肽合成及小分子药物的发现、最佳给药剂量的确定、类药化合物的设计和药物不良反应的预测、蛋白质间相互作用的预测、虚拟筛选效率的提高、定量构效关系（QSAR）建模和药物重新定位、理化性质和药物靶标亲和力的预测、化合物的结合预测和体内安全性分析、多靶点配体药物分子的设计以及临床试验的设计。简要综述了AI算法和传统化学相结合以提高药物发现的效率以及AI在药物发现过程中的应用研究进展,以期为AI应用于药物发现提供一定参考。     

Quantitative Systems Pharmacology for Rare Disease Drug Development

Though hundreds of drugs have been approved by the US Food and Drug Administration (FDA) for treating various rare diseases, most rare diseases still lack FDA-approved therapeutics. To identify the opportunities for developing therapies for these diseases, the challenges of demonstrating the efficacy and safety of a drug for treating a rare disease are highlighted herein. Quantitative systems pharmacology (QSP) has increasingly been used to inform drug development; our analysis of QSP submissions received by FDA showed that there were 121 submissions as of 2022, for informing rare disease drug development across development phases and therapeutic areas. Examples of published models for inborn errors of metabolism, non-malignant hematological disorders, and hematological malignancies were briefly reviewed to shed light on use of QSP in drug discovery and development for rare diseases. Advances in biomedical research and computational technologies can potentially enable QSP simulation of the natural history of a rare disease in the context of its clinical presentation and genetic heterogeneity. With this function, QSP may be used to conduct in-silico trials to overcome some of the challenges in rare disease drug development. QSP may play an increasingly important role in facilitating development of safe and effective drugs for treating rare diseases with unmet medical needs.     

<Emphasis Type="Italic">In-Silico</Emphasis> Approaches to Multi-target Drug Discovery

Multi-target drugs against selective multiple targets improve therapeutic efficacy, safety and resistance profiles by collective regulations of a primary therapeutic target together with compensatory elements and resistance activities. Efforts have been made to employ in-silico methods for facilitating the search and design of selective multi-target agents. These methods have shown promising potential in facilitating drug discovery directed at selective multiple targets.     

Recent developments in the medicinal chemistry of single boron atom-containing compounds

Various boron-containing drugs have been approved for clinical use over the past two decades, and more are currently in clinical trials. The increasing interest in boron-containing compounds is due to their unique binding properties to biological targets; for example, boron substitution can be used to modulate biological activity, pharmacokinetic properties, and drug resistance. In this perspective, we aim to comprehensively review the current status of boron compounds in drug discovery, focusing especially on progress from 2015 to December 2020. We classify these compounds into groups showing anticancer, antibacterial, antiviral, antiparasitic and other activities, and discuss the biological targets associated with each activity, as well as potential future developments.     

Target validation: linking target and chemical properties to desired product profile

The discovery of drugs is a lengthy, high-risk and expensive business taking at least 12 years and is estimated to cost upwards of US$800 million for each drug to be successfully approved for clinical use. Much of this cost is driven by the late phase clinical trials and therefore the ability to terminate early those projects destined to fail is paramount to prevent unwanted costs and wasted effort. Although neglected diseases drug discovery is driven more by unmet medical need rather than financial considerations, the need to minimise wasted money and resources is even more vital in this under-funded area. To ensure any drug discovery project is addressing the requirements of the patients and health care providers and delivering a benefit over existing therapies, the ideal attributes of a novel drug needs to be pre-defined by a set of criteria called a target product profile. Using a target product profile the drug discovery process, clinical study design, and compound characteristics can be defined all the way back through to the suitability or druggability of the intended biochemical target. Assessment and prioritisation of the most promising targets for entry into screening programmes is crucial for maximising chances of success.     

New therapeutic approaches targeted at the late stages of the HIV-1 replication cycle

Owing to the serious clinical consequences associated with acquisition of resistance to current antiretroviral drugs, discovery of new drug targets and development of novel anti-HIV-1 therapeutic agents have become a high research priority. The late stages of HIV-1 replication involve the processes of assembly, budding and maturation, and comprise several new potential therapeutic targets which have not (yet) been targeted by any of the antiretroviral drugs approved at present. The structural protein Gag plays a central role in these stages through its different regions and mature Gag proteins working in concert. In this article, we highlight a number of steps in the late stages of HIV-1 replication that represent promising targets for drug discovery. Recent progress in development of related inhibitors targeting at CA, zinc fingers of NC, p6-Tsg101 interaction, lipid rafts of plasma membrane, proteolytic cleavage sites in Gag and gp160 processing is also reviewed.     

Antimalarial drugs and their useful therapeutic lives: rational drug design lessons from pleiotropic action of quinolines and artemisinins

Efforts to develop an effective malarial vaccine are yet to be successful and thus chemotherapy remains the mainstay of malaria control strategy. Unfortunately, Plasmodium falciparum, the parasite that causes about 90% of all global malaria cases is increasingly becoming resistant to classical antimalarials, necessitating a search for new chemotherapeutics preferably with novel modes of action. Today, rational drug discovery strategy is gaining new impetus as knowledge of malaria parasite biology expands, aided by the parasite genome database and improved bioinformatics tools. Drug development is a laborious, time consuming and costly process, and thus the "useful therapeutic lives" (UTLs) of new drugs should be commensurate with the resources invested in their development. Historical evidence on development and evolution of resistance to classical antimalarial drugs shows that the mode of action of a drug influences its UTL. Drugs that target single and specific targets such as antimalarial antifolates and atovaquone (ATQ) are rendered ineffective within a short time of their clinical use, unlike drugs with pleiotropic action such as chloroquine (CQ) and artemisinins (ART) with long UTLs. Unfortunately, almost all new targets currently being explored for development of novel drugs belong to the "specific target" other than the "multiple target" category, and is plausible that such drugs will have short UTLs. This review relates the pleiotropic action of CQ and ART with their long UTLs, and discusses their relevance in rational drug development strategies. Novel targets with potential to yield drugs with long UTLs are also explored.     

Genetic association meets RNA interference: large-scale genomic screens for causation and mechanism of complex diseases

While the genomic era offers great promise for biomedicine in general and for biomarker discovery in particular, it has yet to significantly impact drug target discovery. Meanwhile, despite improvements over the past 20 years in reducing attrition in clinical trials due to adverse drug responses, the pharmaceutical industry continues to be beset by the high rate of attrition of compounds in late-stage development, primarily due to the lack of drug efficacy. Clearly, even highly potent drugs with ideal safety and pharmacokinetic profiles will fail to survive clinical trials if the drug target itself is not a key point of intervention for most patients. Genetic association studies and RNA interference are two scaleable genomic approaches that together can address the quality as well as quantity of candidate drug targets. Human genetic information has long been used to identify 'molecular bottlenecks' that can highlight the importance of a gene or pathway at the clinical level. The recent availability of the human HapMap and of high-throughput genotyping platforms now enables more systematic genetic screens for novel, clinically-relevant drug targets. In addition, RNA interference can help dissect the molecular role of a candidate drug target in preclinical model systems in vitro and in vivo. Wider applicability of RNA interference methods will closely follow continued progress on efficient delivery into appropriate cell models and target tissues.     

Genetically Engineered Mouse Models for Drug Development and Preclinical Trials

Drug development and preclinical trials are challenging processes and more than 80% to 90% of drug candidates fail to gain approval from the United States Food and Drug Administration. Predictive and efficient tools are required to discover high quality targets and increase the probability of success in the process of new drug development. One such solution to the challenges faced in the development of new drugs and combination therapies is the use of low-cost and experimentally manageable in vivo animal models. Since the 1980’s, scientists have been able to genetically modify the mouse genome by removing or replacing a specific gene, which has improved the identification and validation of target genes of interest. Now genetically engineered mouse models (GEMMs) are widely used and have proved to be a powerful tool in drug discovery processes. This review particularly covers recent fascinating technologies for drug discovery and preclinical trials, targeted transgenesis and RNAi mouse, including application and combination of inducible system. Improvements in technologies and the development of new GEMMs are expected to guide future applications of these models to drug discovery and preclinical trials.     

AI-powered therapeutic target discovery

Disease modeling and target identification are the most crucial initial steps in drug discovery, and influence the probability of success at every step of drug development. Traditional target identification is a time-consuming process that takes years to decades and usually starts in an academic setting. Given its advantages of analyzing large datasets and intricate biological networks, artificial intelligence (AI) is playing a growing role in modern drug target identification. We review recent advances in target discovery, focusing on breakthroughs in AI-driven therapeutic target exploration. We also discuss the importance of striking a balance between novelty and confidence in target selection. An increasing number of AI-identified targets are being validated through experiments and several AI-derived drugs are entering clinical trials; we highlight current limitations and potential pathways for moving forward.     

Accelerating drug development for neuroblastoma - New Drug Development Strategy: an Innovative Therapies for Children with Cancer,European Network for Cancer Research in Children and Adolescents and International Society of Paediatric Oncology Europe Neuroblastoma project

Introduction: Neuroblastoma, the commonest paediatric extra-cranial tumour, remains a leading cause of death from cancer in children. There is an urgent need to develop new drugs to improve cure rates and reduce long-term toxicity and to incorporate molecularly targeted therapies into treatment. Many potential drugs are becoming available, but have to be prioritised for clinical trials due to the relatively small numbers of patients.

Areas covered: The current drug development model has been slow, associated with significant attrition, and few new drugs have been developed for neuroblastoma. The Neuroblastoma New Drug Development Strategy (NDDS) has: 1) established a group with expertise in drug development; 2) prioritised targets and drugs according to tumour biology (target expression, dependency, pre-clinical data; potential combinations; biomarkers), identifying as priority targets ALK, MEK, CDK4/6, MDM2, MYCN (druggable by BET bromodomain, aurora kinase, mTORC1/2) BIRC5 and checkpoint kinase 1; 3) promoted clinical trials with target-prioritised drugs. Drugs showing activity can be rapidly transitioned via parallel randomised trials into front-line studies.

Expert opinion: The Neuroblastoma NDDS is based on the premise that optimal drug development is reliant on knowledge of tumour biology and prioritisation. This approach will accelerate neuroblastoma drug development and other poor prognosis childhood malignancies.     

Successes and setbacks of early investigational drugs for melanoma

Treatment of advanced and metastatic melanoma is a rapidly changing field. Over the past 10 years, there have been six new drugs approved by the FDA for the treatment of metastatic melanoma. These approved drugs include a number of immune checkpoint inhibitors and MAPK-pathway-targeted therapies. The discovery of such agents as ipilimumab, pembrolizumab, nivolumab, vemurafenib, trametininb and dabrafenib have revolutionized the way in which melanoma in managed. While these agents have succeeded in both early and later phase clinical trials, a large number of investigational therapies have not yet been developed or researched past Phase I clinical studies. Furthermore, there are dozens of potential agents in Phase I and Phase II clinical development that appear promising and are currently being explored. The field currently aims to determine the optimal sequence and combination of these therapies to best overcome such setbacks as toxicity and resistance and build upon the successes previously seen.     

Network analysis of FDA approved drugs and their targets

The global relationship between drugs that are approved for therapeutic use and the human genome is not known. We employed graph-theory methods to analyze the Federal Food and Drug Administration (FDA) approved drugs and their known molecular targets. We used the FDA Approved Drug Products with Therapeutic Equivalence Evaluations 26(th) Edition Electronic Orange Book (EOB) to identify all FDA approved drugs and their active ingredients. We then connected the list of active ingredients extracted from the EOB to those known human protein targets included in the DrugBank database and constructed a bipartite network. We computed network statistics and conducted Gene Ontology analysis on the drug targets and drug categories. We find that drug to drug-target relationship in the bipartite network is scale-free. Several classes of proteins in the human genome appear to be better targets for drugs since they appear to be selectively enriched as drug targets for the currently FDA approved drugs. These initial observations allow for development of an integrated research methodology to identify general principles of the drug discovery process.