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Dr. Hualiang Jiang is a pharmaceutical scientist. He was conferred a bachelor’s degree in Chemistry from the Nanjing University in 1987. He received his master’s degree in Physical Chemistry (Quantum Chemistry) from East China Normal University in 1992. In 1995, he obtained his Ph.D. degree in Medicinal Chemistry from Shanghai Institute of Materia Medica (SIMM), Chinese Academy of Sciences (CAS). In 2004, he was appointed as Deputy Director of SIMM followed by his directorship from 2012 up to now. He was a chief scientist of two 973 National Basic Research Projects in drug discovery. He was a member of scientific committees of several major research programs in China, such as 863 National High Technology Program, National Basic Research Program, and Major Research Project of National Natural Science Foundation of China. He also serves as Associate Editor ofJournal of Medicinal Chemistry and editorial board members of several journals such asThe Journal of Biological Chemistry. Over the years, Dr. Jiang has received numerous awards including the Natural Science Award of China, the 5th Prize of Yong Scientist Award of China, the Science and Technology Progress Prize from Ho Leung Ho Lee Foundation, etc. He was elected as Member of the Chinese Academy of Sciences in 2017.

Dr. Jiang's research is mainly focused on developing new computational methods for target identification and drug design and their applications in drug discovery. He has devised and developed a series of new computational methods for target identification and function predication, such as TarFisDock (Li et al., 2006), PhamMapper (Liu et al., 2010), TarPred (Liu et al, 2015) and SPPS (Shen et al, 2007). These methods have been widely used by big pharmaceutical companies and academic community at large. So far, more than 20,000 users from more than 70 countries and regions have employed his methods to identify new targets, and more than 20 target candidates have been experimentally validated according to the users’ publications. He has also developed new methods for drug design and ADME/T predication. For example, he developed the first computational method for drug design based on the drug-target binding kinetics (Bai et al., 2013). This method enables both the binding affinity and the binding kinetics to be accurately estimated, and thus can predict the drug efficacies for some targets, partially resolving the problem of current drug design methods that cannot predict efficacy.

Employing the strategy of computational prediction combined with experimental validation, Dr. Jiang and his team have discovered and studied the druggable properties of a series of proteins, such as copper trafficking proteins (Atox1 and CCS) (Wang et al., 2015), speckle-type POZ protein (SPOP) (Guo et al., 2016), glucokinase (GK) (Zhang et al., 2006), GPCRs (Zhang et al, 2017), and beta-amyloid (Xu et al., 2005). He designed the first inhibitor of Atox1/CCS DC_AC50, and used this small molecule as a probe to prove that copper chaperones are potential new targets for anticancer therapies (Wang et al., 2015). He and his co-workers also designed the first inhibitor of SPOP, and validated the druggability of SPOP-subtract protein interaction to clear-cell renal cell carcinoma (Guo et al., 2016).

Targeting several diseases such as pulmonary hypertension, schizophrenia, type 2 diabetes, erectile disorder and Alzheimer’s disease, Dr. Jiang and his co-workers obtained a number of drug candidates by using computational drug design, organic synthesis and drug development technologies. One compound has entered into phase II clinical trial, three are undergoing phase I clinical trial.

Dr. Jiang has published 193 corresponding/co-corresponding author papers, 266 non-corresponding author papers, and 13 review articles in international journals such as Nature, Nature Chemistry, Cancer Cell, Nature Chemical Biology, Nature Communications, JACS and PNAS. These papers have been cited more than 20,000 times. He was invited to write chapters for 4 books.