The Legend of ATP: From Origin of Life to Precision Medicine.

Adenosine triphosphate (ATP) may be the most important biological small molecule. Since it was discovered in 1929, ATP has been regarded as life's energy reservoir. However, this compound means more to life. Its legend starts at the dawn of life and lasts to this day. ATP must be the basic component of ancient ribozymes and may facilitate the origin of structured proteins. In the existing organisms, ATP continues to construct ribonucleic acid (RNA) and work as a protein cofactor. ATP also functions as a biological hydrotrope, which may keep macromolecules soluble in the primitive environment and can regulate phase separation in modern cells. These functions are involved in the pathogenesis of aging-related diseases and breast cancer, providing clues to discovering anti-aging agents and precision medicine tactics for breast cancer.

Systems Pharmacology-Based Precision Therapy and Drug Combination Discovery for Breast Cancer.

Breast cancer (BC) is a common disease and one of the main causes of death in females worldwide. In the omics era, researchers have used various high-throughput sequencing technologies to accumulate massive amounts of biomedical data and reveal an increasing number of disease-related mutations/genes. It is a major challenge to use these data effectively to find drugs that may protect human health. In this study, we combined the GeneRank algorithm and gene dependency network to propose a precision drug discovery strategy that can recommend drugs for individuals and screen existing drugs that could be used to treat different BC subtypes. We used this strategy to screen four BC subtype-specific drug combinations and verified the potential activity of combining gefitinib and irinotecan in triple-negative breast cancer (TNBC) through in vivo and in vitro experiments. The results of cell and animal experiments demonstrated that the combination of gefitinib and irinotecan can significantly inhibit the growth of TNBC tumour cells. The results also demonstrated that this systems pharmacology-based precision drug discovery strategy effectively identified important disease-related genes in individuals and special groups, which supports its efficiency, high reliability, and practical application value in drug discovery.

NUDT5 as a novel drug target and prognostic biomarker for ER-positive breast cancer.

Breast cancer (BRCA) is the most common malignant tumor in women. The estrogen receptor-positive (ER+) subtype accounts for ∼70% of BRCA cases. Estrogen is a crucial hormone that directly stimulates the growth and development of mammary glands. Recent studies revealed that, as an estrogen cofactor, ATP has an important role in determining the action of estrogen by mediating phase separation. NUDT5 has been recognized as a key factor for ATP production in the nucleus of BRCA cells and, therefore, could represent a novel drug target for ER+ BRCA. Based on a survival analysis of patients with BRCA documented in The Cancer Genome Atlas (TGCA) database, we show that NUDT5 is also a potential prognostic biomarker for ER+ BRCA.

A Machine Learning Method for Drug Combination Prediction.

Drug combination is now a hot research topic in the pharmaceutical industry, but experiment-based methodologies are extremely costly in time and money. Many computational methods have been proposed to address these problems by starting from existing drug combinations. However, in most cases, only molecular structure information is included, which covers too limited a set of drug characteristics to efficiently screen drug combinations. Here, we integrated similarity-based multifeature drug data to improve the prediction accuracy by using the neighbor recommender method combined with ensemble learning algorithms. By conducting feature assessment analysis, we selected the most useful drug features and achieved 0.964 AUC in the ensemble models. The comparison results showed that the ensemble models outperform traditional machine learning algorithms such as support vector machine (SVM), naïve Bayes (NB), and logistic regression (GLM). Furthermore, we predicted 7 candidate drug combinations for a specific drug, paclitaxel, and successfully verified that the two of the predicted combinations have promising effects.

[Short-term memory characteristics of vibro-tactile perception in human fingertips].

This paper discusses the short-term memory of vibro-tactile perception of human fingertips. By using a self-developed vibro-tactile expression device, a recall experiment was firstly carried out among 20 subjects aged 20-30 (10 males and 10 females) to discover the memory span about the vibro-tactile perception of human fingertips. Within this memory span, a cognitive experiment analyzing the recognition accuracy and the reaction time was carried out. The results showed: (1) The vibro-tactile memory span of human fingertip is 4 ± 1; (2) The vibro-tactile memory span increases as the discrete intensity between vibration stimuli increases; (3) Too long or too short vibration duration will reduce the vibro-tactile memory span, and the optimal vibration duration for men is 400 ms, for women is 300 ms; (4) The more the number of vibration stimuli is perceived by the human fingertip, the lower the recognition accuracy and the longer the reaction time it needs; (5) Compared with the vibration stimuli in disorder, people are more likely to remember the vibration stimuli in increasing/decreasing order; (6) The information extraction mechanism of the short-term memory about fingertip vibro-tactile perception bases a point to point scanning process among these stimuli. These results help to understand the human fingertip tactile characteristics and provide a physiological basis for the study of tactile feedback technologies.

Identification of NUDT5 Inhibitors From Approved Drugs.

Recent studies have revealed the important role of NUDT5 in estrogen signaling and breast cancer, but research on the corresponding targeted therapy has just started. Drug repositioning strategy can effectively reduce the time and economic resources spent on drug discovery. To find novel inhibitors of NUDT5, we investigated the previously identified connectivity map-based drug association models and found eighteen FDA approved drugs as candidates. The molecular docking and molecular dynamic simulation were performed and revealed that fourteen organic drugs have the potential to bind the NUDT5 target. Eight representative drugs were selected to perform the cell line viability inhibition analysis, and the results showed that seven of them were able to suppress MCF7 breast cancer cells. Two drugs, nomifensine and isoconazole, showed lower IC50 than the known antiestrogens raloxifene and tamoxifen, and they deserve further pharmacodynamic investigations to test their feasibility for use as NUDT5 inhibitors.

Direct thiocarbamation of imidazoheterocycles via dual C-H sulfurization.

A copper-catalyzed DTBP oxidative dual C-H sulfurization has been developed for the direct thiocarbamation of imidazopyridines using a combination of elemental sulfur and formamides as carbamothioyl surrogates. NBS (bromo succinimide) was found to promote the thiocarbamation in good yields. This dual C-H sulfurization strategy enables access to a wide range of carbamothioyl imidazoheterocycles without the use of highly toxic phosgene.

Drug Repurposing for Japanese Encephalitis Virus Infection by Systems Biology Methods.

Japanese encephalitis is a zoonotic disease caused by the Japanese encephalitis virus (JEV). It is mainly epidemic in Asia with an estimated 69,000 cases occurring per year. However, no approved agents are available for the treatment of JEV infection, and existing vaccines cannot control various types of JEV strains. Drug repurposing is a new concept for finding new indication of existing drugs, and, recently, the concept has been used to discover new antiviral agents. Identifying host proteins involved in the progress of JEV infection and using these proteins as targets are the center of drug repurposing for JEV infection. In this study, based on the gene expression data of JEV infection and the phenome-wide association study (PheWAS) data, we identified 286 genes that participate in the progress of JEV infection using systems biology methods. The enrichment analysis of these genes suggested that the genes identified by our methods were predominantly related to viral infection pathways and immune response-related pathways. We found that bortezomib, which can target these genes, may have an effect on the treatment of JEV infection. Subsequently, we evaluated the antiviral activity of bortezomib using a JEV-infected mouse model. The results showed that bortezomib can lower JEV-induced lethality in mice, alleviate suffering in JEV-infected mice and reduce the damage in brains caused by JEV infection. This work provides an agent with new indication to treat JEV infection.