Over the years, numerous vaccines have been developed against viral infections; however, a complete database that provides comprehensive information on viral vaccines has been lacking. In this review, along with our freely accessible database ViralVacDB, we provide details of the viral vaccines, their type, routes of administration and approving agencies. This repository systematically covers additional information such as disease name, adjuvant, manufacturer, clinical status, age and dosage against 422 viral vaccines, including 145 approved vaccines and 277 in clinical trials. We anticipate that this database will be highly beneficial to researchers and others working in pharmaceuticals and immuno-informatics. Teaser: We describe a freely available database of viral vaccines, providing an overview of vaccine-related information to aid the scientific community working in the immuno-informatics sector.

High-throughput screening (HTS) is a vaunted technology in drug discovery, and drug repositioning a celebrated strategy with famous examples of successful stories; however, repositioned drugs have primarily resulted from serendipitous observations, retrospective studies, and pharmacological analyses as opposed to experimental routes. This observation points to a methodological paradox, considering that academic laboratories of the post-genomic era have benefited from unprecedented technological progress, and a facilitated access to powerful resources that, historically, were a prerogative of the pharma industry. This disconnect is exacerbated by financial, practical, and regulatory complexities affecting drug repositioning; however, the pivotal significance of stringent and rigorous data is what unconditionally sits at the crossroad of go/no-go decisions concerning the therapeutic significance, or predictive validity, of selected drugs. Here, I propose a visionary approach, to which I assigned the term labsourcing, to dramatically enhance efficiency and clinical relevance of academic drug screens and, ultimately, generate contextualized and reproducible data for correct interpretations and reliable selection of drug candidates. The overall concept implies intra- and intermural aggregation of expertise (e.g., assay development, cell biology, statistics, bioinformatics) to perform multiple bioassays, under multiple conditions and readouts, using a common screening collection. Advantages of high input screens can be manifold: i) to tackle discrepancies that may arise from the screens of libraries of variable size and content and assay types and conditions too narrow in scope; ii) the opportunity to generate massive amounts of data applicable for multiple publications and funding requests; iii) the educational benefits for students and post-docs collegially exposed to long-term programs; and iv) the opportunity to democratize research and recruit small labs that could not otherwise join screening programs due to costs, timelines, and risks.

Well-established animal models of depression have described a proximal relationship between stress and central nervous system (CNS) inflammation - a relationship mirrored in the peripheral inflammatory biomarkers of individuals with depression. Evidence also suggests that stress-induced proinflammatory states can contribute to the neurobiology of treatment-resistant depression. Interestingly, ketamine, a rapid-acting antidepressant, can partially exert its therapeutic effects via anti-inflammatory actions on the hypothalamic-pituitary-adrenal (HPA) axis, the kynurenine pathway or by cytokine suppression. Further investigations into the relationship between ketamine, inflammation and stress could provide insight into ketamine's unique therapeutic mechanisms and stimulate efforts to develop rapid-acting, anti-inflammatory-based antidepressants.

Histone methylation is the most common histone modification and a highly dynamic regulator of gene transcription. Methylation of lysine residues can alter the structure of chromatin, helping to regulate DNA-based nuclear activities. Lysine demethylases control and maintain epigenetic factors that affect chromatin structure and cell characteristics. A variety of diseases, including malignant tumors, are connected to their dysregulation. Advances in biochemistry and pathogenesis have prompted the discovery of small molecule inhibitors and tool compounds that disrupt lysine demethylation {AuQ: Edit OK?}. In this review, we focus on JmjC-domain-containing histone lysine demethylases (KDM2-7), discussing their structures and biological roles, representative inhibitors, and therapeutic potential in cancer therapy, and aiming to provide unique insights into the development of JmjC-KDM inhibitors.

There is increasing interest in clinical trials that use technologies and other innovative operational approaches to organise trial activities around trial participants instead of investigator sites. A range of terms has been introduced to refer to this operational clinical trial model, including virtual, digital, remote, and decentralised clinical trials (DCTs). However, this lack of standardised terminology can cause confusion over what a particular trial model entails and for what purposes it can be used, hampering discussions by stakeholders on its acceptability and suitability. Here, we review the different terms described in the scientific literature, advocate the consistent use of a unified term, 'decentralised clinical trial,' and provide a detailed definition of this term.

Drug development has become unbearably slow and expensive. A key underlying problem is the clinical prediction challenge: the inability to predict which drug candidates will be safe in the human body and for whom. Dramatic regulatory changes are now in motion, seeking to remove the mandated reliance on antiquated, ineffective animal studies. A new frontier is an integration of several disruptive technologies [machine learning (ML), patient-on-chip, real-time sensing, and stem cells], which when integrated, have the potential to address this challenge, drastically cutting the time and cost of developing drugs, and tailoring them to individual patients.

In mammals, N6-methyladenosine (m6A) is thought to be the most common and conserved mRNA modification. Methyltransferase-like 3 (METTL3) is the primary regulator of m6A methyl-transformed modification. Small molecules targeting METTL3 could be effective therapeutics for many disorders, given that a large body of research has linked METTL3 dysregulation with a variety of diseases and altered physiological states, especially with the growth and initiation of cancer. Here, we systematically reviewed the discovery of small molecules targeting METTL3, as well as their future development, for researchers studying in the field.

Over the past decade, the amount of biomedical data available has grown at unprecedented rates. Increased automation technology and larger data volumes have encouraged the use of machine learning (ML) or artificial intelligence (AI) techniques for mining such data and extracting useful patterns. Because the identification of chemical entities with desired biological activity is a crucial task in drug discovery, AI technologies have the potential to accelerate this process and support decision making. In addition, the advent of deep learning (DL) has shown great promise in addressing diverse problems in drug discovery, such as de novo molecular design. Herein, we will appraise the current state-of-the-art in AI-assisted drug discovery, discussing the recent applications covering generative models for chemical structure generation, scoring functions to improve binding affinity and pose prediction, and molecular dynamics to assist in the parametrization, featurization and generalization tasks. Finally, we will discuss current hurdles and the strategies to overcome them, as well as potential future directions.

Small interfering RNA (siRNA) therapeutics for cancer are a focus of increasing research interest. However, the major obstacle to their clinical application is the targeted delivery of siRNA to cancer cells at desirable levels. Cell membrane-coated nanocarriers have the advantage of combining the properties of both cell membranes and nanoparticles (NPs). In this review, we highlight the most common RNAi therapeutics and the extracellular and intracellular barriers to siRNA delivery. Moreover, we discuss clinical applications of different cell membrane-coated nanocarriers for targeted siRNA delivery, including cancer cell membranes (CCMs), platelet membranes, erythrocyte membranes, stem cell membranes, exosome membranes, and hybrid membranes. Taken together, biomimetic cell membrane-coated nanotechnology is a promising strategy for targeted siRNA delivery for cancer treatment.

T helper 17 cells are thought to significantly contribute to the neuroinflammation process during neurogenerative diseases via their signature cytokine: interleukin (IL)-17. Recently, an emerging key role of IL-17 and its receptors has been documented in inflammatory and autoimmune diseases. The clinical studies conducted on patients with neurodegenerative disease have also shown an increase in IL-17 levels in serum as well as cerebrospinal fluid samples. Therapeutic targeting of either IL-17 receptors or direct IL-17 neutralizing antibodies has shown a promising preclinical and clinical proof of concept for treating chronic autoimmune neurodegenerative diseases such as multiple sclerosis. Thus, IL-17 and its receptors have a central role in regulation of neuroinflammation and can be considered as one of the major therapeutic targets in chronic neuroinflammatory diseases.