Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Genome sequences of 4 644 representative strains from human gut microbiota were analyzed to mine gene clusters for biosynthesis of novel secondary metabolites, as well as genes encoding antibiotic resistance and virulence factors. AntiSMASH analysis showed that more than 60% of the representative strains encoded at least one secondary metabolite gene cluster, and 8 potential novel secondary metabolite gene clusters were identified from 8 unculturable bacteria. The secondary metabolite gene clusters in human intestine are mainly composed of nonribosomal peptide synthetase (NRPS), bacteriocin, arylpolyene, terpene, betalactone and NRPS like gene clusters distributed in Clostridia, Bacilli, Gammaproteobacteria, Bacteroidia, Actinobacteria and Negativicutes. PathoFact analysis showed that genes encoding antibiotic resistance and virulence factors are widely distributed in representative strains, but the frequency encoded by potential pathogens is significantly higher than that of non-potential pathogens. The frequency of genes encoding secretory toxins such as outer membrane protein, PapC N-terminal domain, PapC C-terminal domain, peptidase M16 inactive domain, and non-secretory toxins such as nitroreductase family, AcrB/AcrD/AcrF family, PLD-like domain, Cupin domain, putative hemolysin, S24-like peptidase, phosphotransferase enzyme family, endonuclease/ exonuclease/ phosphatase family, glyoxalase/ bleomycin resistance was high in potential pathogens. This study may facilitate mining new microbial natural products from the intestinal microbiome, understanding the colonization and infection mechanism of intestinal microorganisms, and providing targeted prevention and treatment of intestinal microbial related diseases.
Humans ; Virulence ; Multigene Family ; Bacteria ; Drug Resistance, Microbial ; Virulence Factors ; Peptide Hydrolases

The research on the relationship between gut microbiota and human health continues to be a hot topic in the field of life science. Culture independent 16S rRNA gene high-throughput sequencing is the current main research method. However, with the reduction of sequencing cost and the maturity of data analysis methods, shotgun metagenome sequencing is gradually becoming an important method for the study of gut microbiome due to its advantages of obtaining more information. With the support from the human microbiome project, 30 805 metagenome samples were sequenced in the United States. By searching NCBI PubMed and SRA databases, it was found that 72 studies collecting about 10 000 Chinese intestinal samples were used for metagenome sequencing. To date, only 56 studies were published, including 16 related to metabolic diseases, 16 related to infectious and immune diseases, and 12 related to cardiovascular and cerebrovascular diseases. The samples were mainly collected in Beijing, Guangzhou, Shanghai and other cosmopolitan cities, where great differences exist in sequencing platforms and methods. The outcome of most studies are based on correlation analysis, which has little practical value in guiding the diagnosis and treatment of clinical diseases. Standardizing sampling methods, sequencing platform and data analysis process, and carrying out multi center parallel research will contribute to data integration and comparative analysis. Moreover, insights into the functional verification and molecular mechanism by using the combination of transcriptomics, proteomics and culturomics will enable the gut microbiota research to better serve the clinical diagnosis and treatment.
China ; Gastrointestinal Microbiome/genetics* ; Humans ; Metagenome ; Microbiota ; RNA, Ribosomal, 16S/genetics* ; United States

Intestinal microbes play an important role in human health. The development of various clinical diseases, such as obesity, diabetes and cardiovascular disease, is closely related to the imbalance of intestinal microflora. With the development of high-throughput sequencing technology, there has been a breakthrough in the understanding of intestinal microorganism. The interaction between intestinal epithelial cells and intestinal microbes has become one of the hotspots and difficulties of current research. Because of the constraints of ethical review and experimental cost, people are more interested in the development of interaction models between the intestinal microflora and the host cells. In this paper, interaction models between intestinal microflora and host cells, and its working principle and application prospect are reviewed, hoping to provide new techniques and new ideas for studying functions of intestinal microbes.

Intestinal microbes play an important role in human health. The development of various clinical diseases, such as obesity, diabetes and cardiovascular disease, is closely related to the imbalance of intestinal microflora. With the development of high?throughput sequencing technology, there has been a breakthrough in the understanding of intestinal microorganism. The interaction between intestinal epithelial cells and intestinal microbes has become one of the hotspots and difficulties of current research. Because of the constraints of ethical review and experimental cost, people are more interested in the development of interaction models between the intestinal microflora and the host cells. In this paper, interaction models between intestinal microflora and host cells, and its working principle and application prospect are reviewed, hoping to provide new techniques and new ideas for studying functions of intestinal microbes.

Intestinal microbes play an important role in human health. The development of various clinical diseases, such as obesity, diabetes and cardiovascular disease, is closely related to the imbalance of intestinal microflora. With the development of high?throughput sequencing technology, there has been a breakthrough in the understanding of intestinal microorganism. The interaction between intestinal epithelial cells and intestinal microbes has become one of the hotspots and difficulties of current research. Because of the constraints of ethical review and experimental cost, people are more interested in the development of interaction models between the intestinal microflora and the host cells. In this paper, interaction models between intestinal microflora and host cells, and its working principle and application prospect are reviewed, hoping to provide new techniques and new ideas for studying functions of intestinal microbes.

Antimicrobial resistance is on the rise while the number of antibiotics being brought to market continues to drop. Drug-resistant genes and drug-resistant bacteria infection have seriously threatened human health. Therefore, antimicrobial resistance presents an ongoing challenge that requires multifaceted approaches including: biomedical innovation; improved surveillance of antibiotic consumption and antimicrobial resistance generated rates; prevention of health-care-associated infections and transmission of multidrug-resistant bacteria and environmental dissemination; rapid microbiological diagnosis; and curtailed clinical and veterinary misuse. Fortunately, combating antimicrobial resistance has been highly valued and supported by the government, scientists and entrepreneurs of various countries. With the continuous introduction of new technologies, new products, and new management measures, the problem of antimicrobial resistance must be controlled and alleviated.

Objective To study the clinical features of hand-foot-mouth disease(HFMD) in neonates.Method From April 2015 to May 2016,the clinical manifestations,laboratory examinations,treatments and prognosis of neonates with HFMD in our hospital were retrospectively analyzed.Result A total of 6 cases of neonatal HFMD were included,with 4 males and 2 females.The ages of 2 patients were ≤7 days and the other 4 patients 8 ～ 28 days.5 patients developed this disease during April to July,while the other one in January.2 cases had a definite contract history of HFMD.4 cases presented with fever and rashes in hand and foot,one case with fever,rash and oral ulcer,and one case with rash in hip and oral ulcer without fever.The nucleic acid test of enterovirus were positive in 4 cases.The symptoms of these neonatal HFMD were mild and recovered after symptom-relieving treatment.Conclusion HFMD in neonates with fever and/or rash should be considered during the HFMD epidemic period.

Objective To detect the urinary albumin level and urinary albumin/urine creatinine ratio in patients with acute cerebral infarction and explore their relations with NEW-TOAST typing.Methods One hundred and sixty-eight patients with acute cerebral infarction,admitted to our hospital from March 2011 to March 201,were chosen in our study; and other 45 healthy subjects were used as controls; according to NEW-TOAST typing,the patients were divided into different subgroups.Their clinical data were retrospectively analyzed; the 24 hour urinary albumin level and urinary albumin/urine creatinine ratio were detected and their relation was analyzed between patient group and controls,and between patients of different subtypes; besides,the correlation of neurologic impairment (NIHSS) scores with urinary albumin/urine creatinine ratio was analyzed.Results The 24 hour urinary albumin level and urinary albumin/urine creatinine ratio was positively correlated (r=0.301,P=0.001); according to the NEW-TOAST subtypes,patients with large artery atherosclerosis and small artery occlusion had significantly higher level of 24 hour urinary albumin level and urinary albumin/urine creatinine ratio (P＜0.05).NIHSS scores and urinary albumin/creatinine ratio in patient group were positively correlated (r=0.215,P=0.001).Conclusion Acute cerebral infarction and kidney disease are closely correlated;both 24 hour urinary albumin level and urinary albumin/urine creatinine ratio can be the predictor of acute cerebral infarction and influence the prognosis.

Objective To observe the efficacy and safety of tiopronin supplemented with chemotherapy in treating advanced breast cancer.Methods Sixty patients with advanced breast cancer were randomly divided into two groups:treatment group(n = 28) and control group (n = 32).Two groups were treated the same of NVB + DDP,the treatment group was supplemented with tiopronin,given for 10 days.Efficacy,toxicity in two groups were compared.Results The effective rate in the treatment group and the control group were 46.4% and 46.9% respectively, with no significant difference between the two groups ,P > 0.05.But the improved quality of life of patients in the treatment group was higher than that in the control group, P < 0.05.The rate of adverse reaction in liver function damaged (9.4%)and leucocyte lassitude(46.4%) were apparent lower than those in the control group(31.2% ,81.2% ),with significant difference between the two groups(P < 0.05, P < 0.01).Conclusion Tiopronin supplemented with chemotherapy show apparent effect in decreasing the adverse reaction of chemotherapy,improving the quality of life and not influence efficacy in advanced breast cancer.So tiopronln may act as protective drug for chemotherapy and deserve further testing in the clinic.