Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

Emerging evidence showed that long non-coding RNAs (lncRNAs) play important roles in a wide range of biological processes and dysregulated lncRNAs are involved in many complex human diseases, including cancer. Although a few lncRNAs’ functions in cancer have been characterized, the detailed regulatory mechanisms of majority of lncRNAs in cancer initiation and progression remain largely unknown. In this review, we summarized recent progress on the mechanisms and functions of lncRNAs in cancer, especially focusing on the oncogenic and tumor suppressive roles of the newly identified lncRNAs, and the pathways these novel molecules might be involved in. Their potentials as biomarkers for diagnosis and prognosis in cancer are also discussed in this paper.

Marine natural products are potent and promising sources of drugs among other natural products of plant, animal, and microbial origin. To date, 20 drugs from marine sources are in clinical use. Most approved marine compounds are antineoplastic, but some are also used for chronic neuropathic pain, for heparin overdosage, as haptens and vaccine carriers, and for omega-3 fatty-acid supplementation in the diet. Marine drugs have diverse structural characteristics and mechanisms of action. A considerable increase in the number of marine drugs approved for clinical use has occurred in the past few decades, which may be attributed to increasing research on marine compounds in laboratories across the world. In the present manuscript, we comprehensively studied all marine drugs that have been successfully used in the clinic. Researchers and clinicians are hopeful to discover many more drugs, as a large number of marine natural compounds are being investigated in preclinical and clinical studies.

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

Curcumin, the yellow pigment of turmeric found in Southeast Indian food, is one of the most popular phytochemicals for cancer prevention. Numerous reports have demonstrated modulation of multiple cellular signaling pathways by curcumin and its molecular targets in various cancer cell lines. To identify a new molecular target of curcumin, we used shape screening and reverse docking to screen the Protein Data Bank against curcumin. Cyclin-dependent kinase 2 (CDK2), a major cell-cycle protein, was identified as a potential molecular target of curcumin. Indeed, in vitro and ex vivo kinase assay data revealed a dramatic suppressive effect of curcumin on CDK2 kinase activity. Furthermore, curcumin induced G1 cell-cycle arrest, which is regulated by CDK2 in HCT116 cells. Although the expression levels of CDK2 and its regulatory subunit, cyclin E, were not changed, the phosphorylation of retinoblastoma (Rb), a well-known CDK2 substrate, was reduced by curcumin. Because curcumin induced cell-cycle arrest, we investigated the antiproliferative effect of curcumin on HCT116 colon cancer cells. In this experiment, curcumin suppressed HCT116 cell proliferation effectively. To determine whether CDK2 is a direct target of curcumin, CDK2 expression was knocked down in HCT116 cells. As expected, HCT116 sh-CDK2 cells exhibited G1 arrest and reduced proliferation. Because of the low levels of CDK2 in HCT116 sh-CDK2 cells, the effects of curcumin on G1 arrest and cell proliferation were not substantially relative to HCT116 sh-control cells. From these results, we identified CDK2 as a direct target of curcumin in colon cancer cells. Cancer Prev Res; 7(4); 466–74. ©2014 AACR.