Epigenetic alternations concern heritable yet reversible changes in histone or DNA modifications that regulate gene activity beyond the underlying sequence. Epigenetic dysregulation is often linked to human disease, notably cancer. With the development of various drugs targeting epigenetic regulators, epigenetic-targeted therapy has been applied in the treatment of hematological malignancies and has exhibited viable therapeutic potential for solid tumors in preclinical and clinical trials. In this review, we summarize the aberrant functions of enzymes in DNA methylation, histone acetylation and histone methylation during tumor progression and highlight the development of inhibitors of or drugs targeted at epigenetic enzymes.

Due to the advantages in efficacy and safety compared with traditional chemotherapy drugs, targeted therapeutic drugs have become mainstream cancer treatments. Since the first tyrosine kinase inhibitor imatinib was approved to enter the market by the US Food and Drug Administration (FDA) in 2001, an increasing number of small-molecule targeted drugs have been developed for the treatment of malignancies. By December 2020, 89 small-molecule targeted antitumor drugs have been approved by the US FDA and the National Medical Products Administration (NMPA) of China. Despite great progress, small-molecule targeted anti-cancer drugs still face many challenges, such as a low response rate and drug resistance. To better promote the development of targeted anti-cancer drugs, we conducted a comprehensive review of small-molecule targeted anti-cancer drugs according to the target classification. We present all the approved drugs as well as important drug candidates in clinical trials for each target, discuss the current challenges, and provide insights and perspectives for the research and development of anti-cancer drugs.

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The COVID-19 pandemic caused by the SARS-CoV-2 virus continually poses serious threats to global public health. The main protease (Mpro) of SARS-CoV-2 plays a central role in viral replication. We designed and synthesized 32 new bicycloproline-containing Mpro inhibitors derived from either Boceprevir or Telaprevir, both of which are approved antivirals. All compounds inhibited SARS-CoV-2 Mpro activity in vitro with IC50 values ranging from 7.6 to 748.5 nM. The co-crystal structure of Mpro in complex with MI-23, one of the most potent compounds, revealed its interaction mode. Two compounds (MI-09 and MI-30) showed excellent antiviral activity in cell-based assays. In a SARS-CoV-2 infection transgenic mouse model, oral or intraperitoneal treatment with MI-09 or MI-30 significantly reduced lung viral loads and lung lesions. Both also displayed good pharmacokinetic properties and safety in rats.

Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides opportunities for the discovery and development of innovative drugs. Various machine learning approaches have recently (re)­emerged, some of which may be considered instances of domain-specific AI which have been successfully employed for drug discovery and design. This review provides a comprehensive portrayal of these machine learning techniques and of their applications in medicinal chemistry. After introducing the basic principles, alongside some application notes, of the various machine learning algorithms, the current state-of-the art of AI-assisted pharmaceutical discovery is discussed, including applications in structure- and ligand-based virtual screening, de novo drug design, physicochemical and pharmacokinetic property prediction, drug repurposing, and related aspects. Finally, several challenges and limitations of the current methods are summarized, with a view to potential future directions for AI-assisted drug discovery and design.