Current Medicinal Chemistry - Volume 28, Issue 11, 2021

Complex common diseases are a significant burden for our societies and demand not only preventive measures but also more effective, safer, and more affordable treatments. The whole process of the current model of drug discovery and development implies a high investment by the pharmaceutical industry, which ultimately impact in high drug prices. In this sense, drug repurposing would help meet the needs of patients to access useful and novel treatments. Unlike the traditional approach, drug repurposing enters both the preclinical evaluation and clinical trials of the compound of interest faster, budgeting research and development costs, and limiting potential biosafety risks. The participation of government, society, and private investors is needed to secure the funds for experimental design and clinical development of repurposing candidates to have affordable, effective, and safe repurposed drugs. Moreover, extensive advertising of repurposing as a concept in the health community, could reduce prescribing bias when enough clinical evidence exists, which will support the employment of cheaper and more accessible repurposed compounds for common conditions.

Drug-target Interactions (DTIs) prediction plays a central role in drug discovery. Computational methods in DTIs prediction have gained more attention because carrying out in vitro and in vivo experiments on a large scale is costly and time-consuming. Machine learning methods, especially deep learning, are widely applied to DTIs prediction. In this study, the main goal is to provide a comprehensive overview of deep learning-based DTIs prediction approaches. Here, we investigate the existing approaches from multiple perspectives. We explore these approaches to find out which deep network architectures are utilized to extract features from drug compound and protein sequences. Also, the advantages and limitations of each architecture are analyzed and compared. Moreover, we explore the process of how to combine descriptors for drug and protein features. Likewise, a list of datasets that are commonly used in DTIs prediction is investigated. Finally, current challenges are discussed and a short future outlook of deep learning in DTI prediction is given.

The costs of developing, validating and buying new drugs are dramatically increasing. On the other hand, sobering economies have difficulties in sustaining their healthcare systems, particularly in countries with an elderly population requiring increasing welfare. This conundrum requires immediate action, and a possible option is to study the large, already present arsenal of drugs approved and to use them for innovative therapies. This possibility is particularly interesting in oncology, where the complexity of the cancer genome dictates in most patients a multistep therapeutic approach. In this review, we discuss a) Computational approaches; b) preclinical models; c) currently ongoing or already published clinical trials in the drug repurposing field in oncology; and d) drug repurposing to overcome resistance to previous therapies.

Drug repurposing, also known as drug repositioning/reprofiling, is a relatively new strategy for the identification of alternative uses of well-known therapeutics that are outside the scope of their original medical indications. Such an approach might entail a number of advantages compared to standard de novo drug development, including less time needed to introduce the drug to the market, and lower costs. The group of compounds that could be considered as promising candidates for repurposing in oncology include the central nervous system drugs, especially selected antidepressant and antipsychotic agents. In this article, we provide an overview of some antidepressants (citalopram, fluoxetine, paroxetine, sertraline) and antipsychotics (chlorpromazine, pimozide, thioridazine, trifluoperazine) that have the potential to be repurposed as novel chemotherapeutics in cancer treatment, as they have been found to exhibit preventive and/or therapeutic action in cancer patients. Nevertheless, although drug repurposing seems to be an attractive strategy to search for oncological drugs, we would like to clearly indicate that it should not replace the search for new lead structures, but only complement de novo drug development.

Background: Drug repurposing, the application of known drugs and compounds with a primary non-oncology purpose, might be an attractive strategy to offer more effective treatment options to cancer patients at a low cost and reduced time. Methods: This review described a total of 10 kinds of non-oncological drugs from more than 100 mechanical studies as well as evidence from population-based studies. The future direction of repurposed drug screening is discussed by using patient-derived tumor organoids. Results: Many old drugs showed previously unknown effects or off-target effects and can be intelligently applied for cancer chemoprevention and therapy. The identification of repurposed drugs needs to combine evidence from mechanical studies and population-based studies. Due to the heterogeneity of cancer, patient-derived tumor organoids can be used to screen the non-oncological drugs in vitro. Conclusion: These identified old drugs could be repurposed in oncology and might be added as adjuvants and finally benefit patients with cancers.

Drug repositioning is a strategy to identify new uses for approved or investigational drugs that are used off-label outside the scope of the original medical indication. In this review, we report the most relevant studies about drug repositioning in hematology, reporting the signalling pathways and molecular targets of these drugs, and describing the biological mechanisms which are responsible for their anticancer effects. Although the majority of studies on drug repositioning in hematology concern acute myeloid leukemia and multiple myeloma, numerous studies are present in the literature on the possibility of using these drugs also in other hematological diseases, such as acute lymphoblastic leukemia, chronic myeloid leukemia, and lymphomas. Numerous anti-infectious drugs and chemical entities used for the therapy of neurological or endocrine diseases, oral antidiabetics, statins and medications used to treat high blood pressure and heart failure, bisphosphonate and natural substance such as artemisin and curcumin, have found a place in the treatment of hematological diseases. Moreover, several molecules drastically reversed the resistance of the tumor cells to the chemotherapeutic drugs both in vitro and in vivo.

Drug repurposing has lately received increasing interest in several diseases especially in cancers, due to its advantages in facilitating the development of new therapeutic strategies, by adopting a cost-friendly approach and avoiding the strict Food and Drug Administration (FDA) regulations. Acriflavine (ACF) is an FDA approved molecule that has been extensively studied since 1912 with antiseptic, trypanocidal, anti-viral, anti-bacterial and anti-cancer effects. ACF has been shown to block the growth of solid and hematopoietic tumor cells. Indeed, ACF acts as an inhibitor of various proteins, including DNA-dependent protein kinases C (DNA-PKcs), topoisomerase I and II, hypoxia-inducible factor 1α (HIF-1α), in addition to its recent discovery as an inhibitor of the signal transducer and activator of transcription (STAT). Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder characterized by the expression of the constitutively active tyrosine kinase BCR-ABL. This protein allows the activation of several signaling pathways known for their role in cell proliferation and survival, such as the JAK/STAT pathway. CML therapy, based on tyrosine kinase inhibitors (TKIs), such as imatinib (IM), is highly effective. However, 15% of patients are refractory to IM, where in some cases, 20-30% of patients become resistant. Thus, we suggest the repurposing of ACF in CML after IM failure or in combination with IM to improve the anti-tumor effects of IM. In this review, we present the different pharmacological properties of ACF along with its anti-leukemic effects in the hope of its repurposing in CML therapy.

Idiopathic pulmonary fibrosis (IPF) is an aggressive pulmonary disease which shares several molecular, pathophysiological and clinical aspects with lung cancer, including high mortality rates. The antifibrotic drugs Nintedanib and Pirfenidone have recently been introduced in clinical practice for the treatment of IPF. Nintedanib is also used for the treatment of several malignancies, including non-small cell lung cancer (NSCLC) in combination with Docetaxel, while Pirfenidone showed some anti-neoplastic effects in preclinical studies. On the other hand, novel targeted agents and immunotherapies have been introduced in the last decade for the treatment of NSCLC, and some of them showed anti-fibrotic properties in recent studies. These evidences, based on the common pathophysiological backgrounds of IPF and lung cancer, make possible the mutual or combined use of anti-fibrotic and anti-neoplastic drugs to treat these highly lethal diseases. The aim of the present review is to depict the current scientific landscape regarding the repurposing of anti-neoplastic drugs in IPF and anti-fibrotic drugs in lung cancer, and to identify future research perspectives on the topic.

The concepts of drug repurposing and Sildenafil or blue pill are tightly linked over the years. Indeed, in addition to its initial clinical application as an anti-hypertensive drug in the pulmonary system, Sildenafil is also known for its beneficial effects in erectile dysfunction. Moreover, evidence has been accumulated to support its value in anti-cancer therapy, either alone or in combination with other clinically efficient chemotherapy drugs. In this review, we focused on the old and recent in vitro and in vivo studies demonstrating the cellular and molecular rationale for the application of Sildenafil in combination therapy in various types of cancer. We emphasized on the different molecular targets as well as the different signaling pathways involved in cancer cells. The pro-apoptotic effect of Sildenafil through nitric oxide (NO)/ phosphodiesterase type 5 (PDE5)-dependent manner seems to be one of the most common mechanisms. However, the activation of autophagy, as well as the modulation of the anti-tumor immunity, constitutes the other pathways triggered by Sildenafil. Overall, the studies converged to reveal the complexity of the anti-cancer potential of Sildenafil. Thus, through our review, we aimed to present an updated and simplified picture of such repurposing of Sildenafil in the field of oncology.

Emerging evidence supports an intertwining framework for the involvement of different inflammatory pathways in a common pathological background for a number of disorders. Of importance are pathways involving arachidonic acid metabolism by cyclooxygenase-2 (COX-2) and 15-lipoxygenase (15-LOX). Both enzyme activities and their products are implicated in a range of pathophysiological processes encompassing metabolic impairment leading to adipose inflammation and the subsequent vascular and neurological disorders, in addition to various pro- and antitumorigenic effects. A further layer of complexity is encountered by the disparate, and often reciprocal, modulatory effect COX-2 and 15-LOX activities and metabolites exert on each other or on other cellular targets, the most prominent of which is peroxisome proliferator-activated receptor gamma (PPARγ). Thus, effective therapeutic intervention with such multifaceted disorders requires the simultaneous modulation of more than one target. Here, we describe the role of COX-2, 15-LOX, and PPARγ in cancer and complications of metabolic disorders, highlight the value of designing multi-target directed ligands (MTDLs) modifying their activity, and summarizing the available literature regarding the rationale and feasibility of design and synthesis of these ligands together with their known biological effects. We speculate on the potential impact of MTDLs in these disorders as well as emphasize the need for structured future effort to translate these early results facilitating the adoption of these, and similar, molecules in clinical research.