Since the outbreak of SARS (severe acute respiratory syndrome) in November 2002 in Southern China's Guangdong Province, considerable progress has been made in the development of drugs for SARS therapy. The present mini review is focused on the area of computer-aided drug discovery, i.e., the advances achieved mainly from the approaches of structural bioinformatics, pharmacophore modeling, molecular docking, peptide-cleavage site prediction, and other computational means. It is highlighted that the compounds C(28)H(34)O(4)N(7)Cl, C(21)H(36(O)5)N(6) and C(21)H(36)O(5)N(6) (Wei et al., Amino Acids, 2006, 31: 73-80), as well as KZ7088 (Chou et al. Biochem. Biophys. Res. Commun., 2003, 308: 148-151), a derivative of AG7088, might be the promising candidates for further investigation, and that the octapeptides ATLQAIAS and ATLQAENV, as well as AVLQSGFR, might be converted to effective inhibitors against the SARS enzyme. Meanwhile, how to modify these octapeptides based on the "distorted key" theory to make them become potent inhibitors is explicitly elucidated. Finally, a brief introduction is given for how to use computer-generated graphs to rapidly diagnose SARS coronavirus.

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Immune checkpoint inhibitors (ICIs) have heralded the advent of a new era in oncology by holding the promise of prolonged survival in severe and otherwise treatment-refractory advanced cancers. However, the remarkable antitumor efficacy of these agents is overshadowed by their potential for inducing autoimmune toxic effects, collectively termed immune-related adverse events (irAEs). These autoimmune adverse effects are often difficult to predict, possibly permanent, and occasionally fatal. Hence, the identification of risk factors for irAEs is urgently needed to allow for prompt therapeutic intervention. This review discusses the potential mechanisms through which irAEs arise and summarizes the existing evidence regarding risk factors associated with the occurrence of irAEs. In particular, we examined available data regarding the effect of a series of clinicopathological and demographic factors on the risk of irAEs.