Sustainable Drug Development Research Articles

Integrated Transcriptomics and Metabolomics Studies Reveal Steroid Biosynthesis Pathway and BCL2 Inhibitory Diazo-Progesterone of Drimia indica for Conservation and Sustainable Utilization.

This study is the first report on the sequence of the transcriptome of Drimia indica, a non-model plant with medicinal properties found in a forest tribal belt, using the Illumina NovaSeq platform. The primary objectives of this study were to elucidate the gene expression profiles in different tissues, identify key regulatory genes and pathways involved in secondary metabolite biosynthesis, and explore the plant's potential pharmacological properties. The study generated 670087 unigenes from both leaves and roots and identified putative homologs of annotated sequences against UniProt/Swiss-Prot and KEGG databases. The functional annotation of the identified unigenes revealed the secondary metabolite biosynthetic process as the most prominent pathway, with gene enrichment analysis predominantly accounting for secondary metabolite pathways, such as terpenoid, steroid, flavonoid, alkaloid, selenocompound, and cortisol synthesis. The study also identified regulatory genes NAC, Bhlh, WRKY, and C2H2 on the transcriptome dataset. The functionally annotated unigenes suggested phytocompounds in Drimia indica to have multi-potent properties, such as anti-cancer, anti-inflammatory, and anti-diabetic activities, which has been further validated by GC-MS-based metabolite profiling. Notably, we have identified two novel molecules, di-azo progesterone and 4H-pyran-4-one 2,3-dihydro-3,5-dihydroxy- 6-methyl, with potential BCL2 inhibitory anticancer properties, supported by stable binding interactions observed in molecular docking and dynamics simulations. Additionally, an abundance of mono-nucleotide SSR markers has been identified, useful for genetic diversity studies. This study provides a foundational understanding of the molecular mechanisms in Drimia indica, highlighting its potential as a source for novel therapeutic agents and contributing valuable insights for future pharmacological and agricultural applications. However, further in vivo studies are warranted to confirm these findings and validate their pharmacological efficacy and therapeutic potential. The SSR markers identified also offer valuable tools for molecular genetics, plant breeding, and sustainable drug development.

Bioprospecting of Aspergillus sp. as a promising repository for anti-cancer agents: a comprehensive bibliometric investigation.

Cancer remains a significant global health challenge, claiming nearly 10 million lives in 2020 according to the World Health Organization. In the quest for novel treatments, fungi, especially Aspergillus species, have emerged as a valuable source of bioactive compounds with promising anticancer properties. This study conducts a comprehensive bibliometric analysis to map the research landscape of Aspergillus in oncology, examining publications from 1982 to the present. We observed a marked increase in research activity starting in 2000, with a notable peak from 2005 onwards. The analysis identifies key contributors, including Mohamed GG, who has authored 15 papers with 322 citations, and El-Sayed Asa, with 14 papers and 264 citations. Leading countries in this research field include India, Egypt, and China, with King Saud University and Cairo University as the leading institutions. Prominent research themes identified are "endophyte," "green synthesis," "antimicrobial," "anti-cancer," and "biological activities," indicating a shift towards environmentally sustainable drug development. Our findings highlight the considerable potential of Aspergillus for developing new anticancer therapies and underscore the necessity for further research to harness these natural compounds for clinical use.

Assessing Environmental Risks during the Drug Development Process for Parasitic Vector-Borne Diseases: A Critical Reflection.

Parasitic vector-borne diseases (VBDs) represent nearly 20% of the global burden of infectious diseases. Moreover, the spread of VBDs is enhanced by global travel, urbanization, and climate change. Treatment of VBDs faces challenges due to limitations of existing drugs, as the potential for side effects in nontarget species raises significant environmental concerns. Consequently, considering environmental risks early in drug development processes is critically important. Here, we examine the environmental risk assessment process for veterinary medicinal products in the European Union and identify major gaps in the ecotoxicity data of these drugs. By highlighting the scarcity of ecotoxicological data for commonly used antiparasitic drugs, we stress the urgent need for considering the One Health concept. We advocate for employing predictive tools and nonanimal methodologies such as New Approach Methodologies at early stages of antiparasitic drug research and development. Furthermore, adopting progressive approaches to mitigate ecological risks requires the integration of nonstandard tests that account for real-world complexities and use environmentally relevant exposure scenarios. Such a strategy is vital for a sustainable drug development process as it adheres to the principles of One Health, ultimately contributing to a healthier and more sustainable world.

Drug–target interaction prediction using knowledge graph embedding

The prediction of drug-target interactions (DTIs) is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs. Computational approaches to predicting DTIs can provide important insights into drug mechanisms of action. However, current methods for predicting DTIs based on the structural information of the knowledge graph may suffer from the sparseness and incompleteness of the knowledge graph and neglect the latent type information of the knowledge graph. In this paper, we propose TTModel, a knowledge graph embedding model for DTI prediction. By exploiting biomedical text and type information, TTModel can learn latent text semantics and type information to improve the performance of representation learning. Comprehensive experiments on two public datasets demonstrate that our model outperforms the state-of-the-art methods significantly on the task of DTI prediction.

Cytotoxic Evaluation and Elucidation of Dammarane-Type Triterpenoids Isolated from the Exocarp of Aglaia cucullata (Meliaceae)

Aglaia cucullata is a mangrove plant with a tropical Asian distribution. It is used as traditional medicine for the treatment of diarrhea, inflammation, skin diseases, and heart diseases. Several compounds isolated from A. cucullata have demonstrated cytotoxic activity against various human cancer cells. Cancer therapies such as surgery, chemo-, and radiotherapy have many side effects. However, the use of natural bioactive compounds such as triterpenoid in cancer treatment can be used as an alternative to reduce these side effects. Therefore, the discovery of bioactive compounds from plants is very important to improve aspects of discovery and development of sustainable new anticancer drug candidates. Here, we report the chemical structures of seven known dammarane-type triterpenoids (1–7) isolated from A. cucullata exocarp and evaluate their cytotoxicity against B16-F10 melanoma skin cancer cells. The isolated compounds included cabraleahydroxylactone 3α-acetate (1), (20S)-20-hydroxydammar,24-en-3α-ol (2), (20S)-20-hydroxydammar,24-en-3-on (3), methyl 20(S)-hydroxy-3,4-secodammar-4(28),24-diene-3-oic acid (4), 3-epi ocotillol II (5), cabraleone (6), and ocotillone (7). The n-hexane extract was found to be active against B16-F10 cells, exhibiting an IC50 value of 7.85 ± 0.22 µg/mL. Fractionation of this extract subsequently identified the compound (20S)-20-hydroxydammar 24-en-3-on (3) as an active substance with an IC50 value of 21.55 ± 0.25 µM, comparing favorably with the positive control cisplatin (12.90 µg/mL; 43.00 µM). These results provide further evidence of the genus Aglaia as a source of cytotoxic cancer drug leads. In addition, compound 3 has potential as a convincing therapeutic agent for further research in the context of sustainable drug development, especially the development of new safe cancer chemotherapeutic agents.

DTiGEMS+: drug\u2013target interaction prediction using graph embedding, graph mining, and similarity-based techniques

In silico prediction of drug–target interactions is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs. However, developing such computational methods is not an easy task, but is much needed, as current methods that predict potential drug–target interactions suffer from high false-positive rates. Here we introduce DTiGEMS+, a computational method that predicts Drug–Target interactions using Graph Embedding, graph Mining, and Similarity-based techniques. DTiGEMS+ combines similarity-based as well as feature-based approaches, and models the identification of novel drug–target interactions as a link prediction problem in a heterogeneous network. DTiGEMS+ constructs the heterogeneous network by augmenting the known drug–target interactions graph with two other complementary graphs namely: drug–drug similarity, target–target similarity. DTiGEMS+ combines different computational techniques to provide the final drug target prediction, these techniques include graph embeddings, graph mining, and machine learning. DTiGEMS+ integrates multiple drug–drug similarities and target–target similarities into the final heterogeneous graph construction after applying a similarity selection procedure as well as a similarity fusion algorithm. Using four benchmark datasets, we show DTiGEMS+ substantially improves prediction performance compared to other state-of-the-art in silico methods developed to predict of drug-target interactions by achieving the highest average AUPR across all datasets (0.92), which reduces the error rate by 33.3% relative to the second-best performing model in the state-of-the-art methods comparison.

Coronavirus Disease 2019, Superinfections, and Antimicrobial Development: What Can We Expect?

Coronavirus disease 2019 (COVID-19) arose at a time of great concern about antimicrobial resistance (AMR). No studies have specifically assessed COVID-19-associated superinfections or AMR. Based on limited data from case series, it is reasonable to anticipate that an appreciable minority of patients with severe COVID-19 will develop superinfections, most commonly pneumonia due to nosocomial bacteria and Aspergillus. Microbiology and AMR patterns are likely to reflect institutional ecology. Broad-spectrum antimicrobial use is likely to be widespread among hospitalized patients, both as directed and empiric therapy. Stewardship will have a crucial role in limiting unnecessary antimicrobial use and AMR. Congressional COVID-19 relief bills are considering antimicrobial reimbursement reforms and antimicrobial subscription models, but it is unclear if these will be included in final legislation. Prospective studies on COVID-19 superinfections are needed, data from which can inform rational antimicrobial treatment and stewardship strategies, and models for market reform and sustainable drug development.

Repurposing of Drugs Is a Viable Approach to Develop Therapeutic Strategies against Central Nervous System Related Pathogenic Amoebae.

Brain-eating amoebae including Acanthamoeba spp., Naegleria fowleri, and Balamuthia mandrillaris cause rare infections of the central nervous system that almost always result in death. The high mortality rate, lack of interest for drug development from pharmaceutical industries, and no available effective drugs present an alarming challenge. The current drugs employed in the management and therapy of these devastating diseases are amphotericin B, miltefosine, chlorhexidine, pentamidine, and voriconazole which are generally used in combination. However, clinical evidence shows that these drugs have limited efficacy and high host cell cytotoxicity. Repurposing of drugs is a practical approach to utilize commercially available, U.S. Food and Drug Administration approved drugs for one disease against rare diseases caused by brain-eating amoebae. In this Perspective, we highlight some of the success stories of drugs repositioned against neglected parasitic diseases and identify future potential for effective and sustainable drug development against brain-eating amoebae infections.

Novel Sustainable-by-Design HDAC Inhibitors for the Treatment of Alzheimer's Disease.

Alzheimer's disease (AD) represents a global problem, with an estimation of the majority of dementia patients in low- and middle-income countries by 2050. Thus, the development of sustainable drugs has attracted much attention in recent years. In light of this, taking inspiration from the HDAC inhibitor vorinostat (1), we develop the first HDAC inhibitors derived from cashew nut shell liquid (CNSL), an inexpensive agro-food waste material. CNSL derivatives 8 and 9 display a HDAC inhibitory profile similar to 1, together with a more promising safety for 9 compared to 1. Moreover, both compounds and particularly 9 were able to effectively modulate glial cell-induced inflammation and to revert the pro-inflammatory phenotype. All these results demonstrate that the use of inexpensive food waste materials could be successfully applied for the development of accessible and sustainable drug candidates for the treatment of AD.

Development of antimalaria, antibacterial, anticancer and antitumour drugs from new chemical entities from plant sources

Higher plants are capable of synthesizing complex and advanced chemical substances. Many of the unique gene sources may be lost through extinction, but as plants have great potential for producing new drugs, some remed-ial actions are required to preserve medicinal potential of plants. In cancer treatment, the percentage of non-synthetic small molecules of new chemical entities has averaged about 62 %. In other therapeutic areas, such as cardiovascular, antimicrobials, sexual dysfunction, and metabolic diseases, there has been extensive developme-nt of new chemical entities. In anti-hypertensive treatment, out of 74 synthetic drugs, about 48 have been traced to natural products. Active pharmaceutical ingredients, as lead compounds from plant sources have been devel-oped for many cancer antibiotics and anti-parasitic drugs. Other challenges of medicinal plant research are link-ed to the loss of biodiversity and conservation within the framework of sustainable management. The advances in sourcing plant products for new chemical entities as lead compounds in pharmaceuticals are reviewed in this paper. Major aspects of therapeutics, such as anticancer, antibacterial, antitumour, antimicrobials, and the use of NAPRALERT Natural Product Database are also presented. Bulk packaging and labelling of pharmaceutical plant products, and loss of biodiversity are highlighted as key factors in sustainable drug development from plants.