Medicinal chemistry is a discipline at the intersection of chemistry and various biological and pharmacological research
areas, where system biology and cheminformatics are highly involved. System biology is a holistic approach that focused on
the complex interactions within the biological systems. Cheminformatics is a combination of different working fields, including
biochemistry, biophysics, and computer science. Both have increasingly been playing important roles in stimulating the
development of medicinal chemistry [1-5]. The main goal of this special issue is to report recent progresses of medicinal
chemistry from the angles of system biology and cheminformatics.
Cells need high-sensitivity detection of non-self molecules in order to fight against pathogens. These cellular sensors are
thus of significant importance to medicinal purposes, especially for treating novel emerging pathogens. IG-I-like receptors
(RLRs) are intracellular sensors for viral RNAs (vRNAs). The review article titled “Structural variability in the RLR-MAVS
pathway and sensitive detection of viral RNAs” by Prof. Qiu-Xing Jiang of the University of Florida in USA [6], discussed
the molecular events of RLR-MAVS (mitochondrial antiviral signaling protein) pathway from the angle of detecting single
copy or a very low copy number of vRNAs in the presence of non-specific competition from cytosolic RNAs, and the key
structural variabilities in the RLR / vRNA complexes, the MAVS helical polymers, and the adapter-mediated interactions
between the active RLR / vRNA complex, and the inactive MAVS were also reviewed. These structural variations may reflect
the adaptation of the signaling pathways to different conditions or reach different levels of sensitivity in its response to
exogenous vRNAs.
Hyperbaric Oxygenation Therapy (HBOT) is used as an adjunctive method for multiple diseases. The review article titled
“The Multiple Applications and Possible Mechanisms of the Hyperbaric Oxygenation Therapy” by Dr. Chunxia Chen
and Dr. Luying Huang, and their colleagues of the People’s Hospital of Guangxi Zhuang Autonomous Region in China [7],
reviewed the current applications and possible mechanisms of HBOT, and concluded that the comprehensive consideration of the
advantages and the disadvantages of HBOT is required to obtain a satisfying therapeutic outcome.
Information of protein subcellular localization is crucially important for both basic research and drug development [8, 9].
With the explosive growth of protein sequences discovered in the post-genomic age, it is highly demanded to develop powerful
bioinformatics tools for timely and effectively identifying their subcellular localization purely based on the sequence
information alone. The Research article titled “pLoc_bal-mEuk: predict subcellular localization of eukaryotic proteins by quasibalancing
training dataset and PseAAC” by Professor Dr. Kuo-Chen Chou of Gordon Life Science Institute in USA [10], and
his colleagues discussed the development of a new predictor termed pLoc bal-mEuk by quasi-balancing the training dataset.
Cross-validation tests on exactly the same experiment-confirmed dataset have indicated that the proposed new predictor is
remarkably superior as compared to pLoc-mEuk, the existing state-of-the-art predictor in identifying the subcellular
localization of eukaryotic proteins. It has not escaped our notice that the quasi-balancing treatment can also be used to deal with
many other biological systems.
Polysialic acid (polySia) is a unique carbohydrate polymer produced on the surface of neuronal cell adhesion molecule
(NCAM) in a number of cancer cells, and strongly correlates with the migration and invasion of tumor cells with aggressive
propagation, metastasis and poor clinical prognosis [11]. polySia synthesis is catalyzed by two polysialyltransferases
(polySTs), ST8SiaIV (PST) and ST8SiaII (STX) [12]. The research paper titled “The Inhibition of Polysialyltransferase
ST8SiaIV through Heparin binding to Polysialytransferase Domain (PSTD)” by Professors Drs. Guo-Ping Zhou and Ri-Bo
Huang and their colleagues of Guangxi Academy of Sciences in China [13], verified that the PSTD is the binding domain of the
inhibitors of Polysialyltransferase ST8Sia IV, and further determined the binding sites between the different type of heparins,
unfractionated heparin (UFH), low molecular heparin (LMWH) and heparin tetrasaccharide (DP4) and the PSTD by the
fluorescence quenching analysis, the CD spectra, and NMR spectroscopy experiments. Their results indicate that each type of
heparins could be bound to the specific residues in the PSTD. These important findings provided new insights into an inhibition
mechanism of the polysialyltransferases and should be helpful to design more effective drugs for treatment of metastatic cancer.
With the avalanche of protein sequences emerging in the post-genomic age, it is highly desirable to develop computational
tools for timely and effectively identifying their subcellular localization based on the sequence information alone. The research
article titled “pLoc_bal-mVirus: predict subcellular localization of virus proteins by PseAAC and balancing training
dataset” by Prof. Drs. Kuo-Chen Chou (Gordon Life Science Institute, USA), and Xuan Xiao (University of Electronic Science and Technology of China) and their colleagues defined the development of a new predictor called pLoc_bal-mVirus by
balancing the training dataset [14]. Cross-validation tests on exactly the same experiment-confirmed dataset have indicated that
the proposed new predictor is remarkably superior to pLoc-mVirus, the existing state-of-the-art predictor in identifying the
subcellular localization of virus proteins. To maximize the convenience for most experimental scientists, a user-friendly webserver
for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mVirus/, by which users can easily get
their desired results. It is anticipated that the proposed predictor will become a useful high throughput tool for both basic
research and drug development, particularly in designing multi-target drugs [15].
Inhibiting the activity of α-amylase is an important strategy in the treatment of diabetes mellitus. Most inhibitors of α-
amylase have serious adverse effects, and the α-amylase inactivation mechanisms for the design of safer inhibitors are yet to be
revealed. The last research article titled “Inhibition of α-amylase activity by Zn2+: Insights from spectroscopy and
molecular dynamics simulations” by Prof. Drs. Guo-Ping Zhou and Ri-Bo Huang, and their colleagues in Guangxi Academy
of Sciences studied the inhibitory effect of Zn2+ on the structure and dynamic characteristics of α-amylase from Anoxybacillus
sp. GXS-BL (AGXA) [16], which shares the same catalytic residues and similar structures as human pancreatic (HPA) and
salivary
