Potencial inibitório do ácido elágico sobre a formação do complexo Keap1-Nrf2: implicações terapêuticas em doenças crônico-degenerativas / Inhibitory potential of ellagic acid on the formation of the keap1-Nrf2 complex: Therapeutical implications in chronic-degenerative diseases

Objetivos ­ Avaliar o potencial inibitório do ácido elágico sobre as interações do complexo Keap1-Nrf2, com o intuito de esclarecer um dos eventuais mecanismos associado à atividade antioxidante do ácido elágico. Métodos ­ Foram empregadas simulações de docagem molecular para prever o modo de ligação do ácido elágico no sítio ligante da proteína Keap1, o qual foi comparado com o modo de ligação obtido experimentalmente e descrito na literatura para o ligante natural, a proteína Nrf2, e um potente inibidor monoácido do complexo Keap1-Nrf2. Resultados ­ As simulações de docagem revelaram que o ácido elágico apresenta potencial para realizar uma rede de ligações de hidrogênio com resíduos de aminoácidos da proteína Keap1 considerados importantes para o reconhecimento do Nrf2, se assemelhando ao perfil observado para inibidores do complexo Keap1-Nrf2 descritos na literatura. Conclusão ­ O ácido elágico apresenta características químicas e espaciais favoráveis para a inibição do complexo Keap1-Nrf2 e a elucidação do seu modo de ligação pode auxiliar na identificação de novos produtos naturais com propriedades antioxidantes e potencializar o desenvolvimento de fármacos contra doenças crônico-degenerativas.

Blind docking of 4-Amino-7-Chloroquinoline analogs as potential dengue virus protease inhibitor using CB Dock a web server-Supplemenntary data

Currently, there is no approved drug to combat dengue. Various quinoline derivatives are known for potential antimalarial, antiviral activities, etc. In the present work docking between 4-Amino-7-Chloroquinoline analogs was performed with dengue virus NS2B/NS3 protease using CB dock, a web server. Lys74, Ile165, Val147, Asn152, Asn167, Trp83 and Leu149 amino acid residues were found to be in contact with designed 4-Amino-7-Chloroquinoline analogs. Different modes of binding like hydrogen bonding, hydrophobic interactions, etc with designed compounds improve potential anti-dengue characteristics in silico. ADME results are in acceptable range.

Blind docking of 4-Amino-7-Chloroquinoline analogs as potential dengue virus protease inhibitor using CB Dock a web server

Currently, there is no approved drug to combat dengue. Various quinoline derivatives are known for potential antimalarial, antiviral activities, etc. In the present work docking between 4-Amino-7-Chloroquinoline analogs was performed with dengue virus NS2B/NS3 protease using CB dock, a web server. Lys74, Ile165, Val147, Asn152, Asn167, Trp83 and Leu149 amino acid residues were found to be in contact with designed 4-Amino-7-Chloroquinoline analogs. Different modes of binding like hydrogen bonding, hydrophobic interactions, etc with designed compounds improve potential anti-dengue characteristics in silico. ADME results are in acceptable range.

Artificial intelligence-based drug development: current progress and future challenges / 中国药科大学学报

@#In recent years, artificial intelligence (AI) has been widely applied in the field of drug discovery and development.In particular, natural language processing technology has been significantly improved after the emergence of the pre-training model.On this basis, the introduction of graph neural network has also made drug development more accurate and efficient.In order to help drug developers more systematically and comprehensively understand the application of artificial intelligence in drug discovery, this article introduces cutting-edge algorithms in AI, and elaborates on the various applications of AI in drug development, including drug small molecule design, virtual screening, drug repurposing, and drug property prediction, finally discusses the opportunities and challenges of AI in future drug development.

Application and advance of artificial intelligence in biomedical field / 中国药科大学学报

@#Artificial intelligence (AI) has developed rapidly in the twentieth century, and has substantialy changed the modern way of life.At the same time, AI has greatly contributed to the development of the pharmaceutical industry, playing a key role in precision medicine, intelligent diagnosis, computer-aided drug design, and clinical trial decision-making, and has also greatly developed itself through its integration with the pharmaceutical industry.This paper outlines the key issues in research, describes the key applications of AI in the health and pharmaceutical industries, and finally analyzes the opportunities and challenges of AI in the health pharmaceutical industry to provide reference for the development of AI in the health and pharmaceutical fields.

FBDD and drugs originated from FBDD / 药学学报

The binding of small molecule drugs to targets is mostly through non-covalent bonds, and hydrogen bond, electrostatic, hydrophobic and van der Waals interactions function to maintain the binding force. The more these binding factors lead to strong bindings and high activities. However, it is often accompanied by the increase of molecular size, resulting in pharmacokinetic problems such as membrane penetration and absorption, as well as metabolism, which ultimately affects the drug success. Fragment-based drug discovery (FBDD) is to screen high-quality fragment library to find hits. Combine with structural biology, FBDD generates lead compounds by means of fragment growth, linking and fusion, and finally drug candidates by the optimization operation. During the value chain FBDD is closely related to structure-based drug discovery (SBDD). In this paper, the principle of FBDD is briefly described by several launched drugs.

Structure-based drug discovery of novel fused-pyrazolone carboxamide derivatives as potent and selective AXL inhibitors

As a novel and promising antitumor target, AXL plays an important role in tumor growth, metastasis, immunosuppression and drug resistance of various malignancies, which has attracted extensive research interest in recent years. In this study, by employing the structure-based drug design and bioisosterism strategies, we designed and synthesized in total 54 novel AXL inhibitors featuring a fused-pyrazolone carboxamide scaffold, of which up to 20 compounds exhibited excellent AXL kinase and BaF3/TEL-AXL cell viability inhibitions. Notably, compound 59 showed a desirable AXL kinase inhibitory activity (IC50: 3.5 nmol/L) as well as good kinase selectivity, and it effectively blocked the cellular AXL signaling. In turn, compound 59 could potently inhibit BaF3/TEL-AXL cell viability (IC50: 1.5 nmol/L) and significantly suppress GAS6/AXL-mediated cancer cell invasion, migration and wound healing at the nanomolar level. More importantly, compound 59 oral administration showed good pharmacokinetic profile and in vivo antitumor efficiency, in which we observed significant AXL phosphorylation suppression, and its antitumor efficacy at 20 mg/kg (qd) was comparable to that of BGB324 at 50 mg/kg (bid), the most advanced AXL inhibitor. Taken together, this work provided a valuable lead compound as a potential AXL inhibitor for the further antitumor drug development.

Research of the mechanism of Huganning tablet in the treatment of nonalcoholic fatty liver disease based on network pharmacology and computer-aided drug design / 药学学报

In this study, we explored the mechanism of Huganning tablet (HGNP) in the treatment of nonalcoholic fatty liver disease (NAFLD) based on network pharmacology and computer-aided drug design. Firstly, the potential ingredients and targets of HGNP were identified from TCMSP database, Swiss Target Prediction database, Chinese pharmacopoeia (2015) and literatures, and then the targets of HGNP intersected with NAFLD disease targets that obtained in GeneCards database to acquired potential targets. The bioconductor bioinformatics package of R software was used for gene ontology (GO) enrichment and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. The network of “potential ingredient-key target-pathway” was formed in Cytoscape software to study the interactions between potential ingredients of HGNP, key targets, pathways and NAFLD. Based on the results of network pharmacology, the molecular docking analysis of the key targets and potential active ingredients in HGNP tablets with top degree in the network was conducted using Discovery Studio 2020 software, followed by molecular dynamics simulations, binding free energy calculation, drug-likeness properties analysis and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties prediction. In vitro, HepG2 cells were used to establish steatosis model, and the effects of five key compounds on hepatocyte steatosis were analyzed by oil red O staining and triglyceride (TG) content determination. The results showed that 141 ingredients and 151 potential targets were obtained. A total of 2 526 items and 151 pathways were identified by GO and KEGG enrichment analysis. The molecular docking suggested that five components, isorhamnetin, salvianolic acid B, emodin, resveratrol and rhein, exhibited strong binding ability with key targets [retinoic acid receptor RXR-alpha (RXRA), tumor necrosis factor (TNF), glycogen synthase kinase-3 beta (GSK3B), serine/threonine-protein kinase 1 (AKT1)]. It was further verified that isorhamnetin and salvianolic acid B bind to key targets with good structural stability and binding affinity based on molecular dynamics simulations and binding free energy calculations. The drug-likeness properties, pharmacokinetic properties and toxicity of five key compounds were more comprehensively analyzed through drug-likeness properties analysis and ADMET properties prediction. In vitro, all five compounds, isorhamnetin, salvianolic acid B, emodin, resveratrol, and rhein, improved hepatocyte steatosis of HepG2 cells, confirming the reliability of the present study. In conclusion, based on network pharmacology, computer-aided drug design and in vitro validation, this study investigated the mechanism of HGNP for the treatment of NAFLD at multiple levels and provided a basis for its clinical application.

Application and development of systems biology in computer-aided drug design / 中国中药杂志

With the advances in medicine, people have deeply understood the complex pathogenesis of diseases. Revealing the mechanism of action and therapeutic effect of drugs from an overall perspective has become the top priority of drug design. However, the traditional drug design methods cannot meet the current needs. In recent years, with the rapid development of systems biology, a variety of new technologies including metabolomics, genomics, and proteomics have been used in drug research and development. As a bridge between traditional pharmaceutical theory and modern science, computer-aided drug design(CADD) can shorten the drug development cycle and improve the success rate of drug design. The application of systems biology and CADD provides a methodological basis and direction for revealing the mechanism and action of drugs from an overall perspective. This paper introduces the research and application of systems biology in CADD from different perspectives and proposes the development direction, providing reference for promoting the application.

Discovery of novel phosphodiesterase-1 inhibitors for curing vascular dementia: Suppression of neuroinflammation by blocking NF-κB transcription regulation and activating cAMP/CREB axis

Vascular dementia (VaD) is the second commonest type of dementia which lacks of efficient treatments currently. Neuroinflammation as a prominent pathological feature of VaD, is highly involved in the development of VaD. In order to verify the therapeutic potential of PDE1 inhibitors against VaD, the anti-neuroinflammation, memory and cognitive improvement were evaluated in vitro and in vivo by a potent and selective PDE1 inhibitor 4a. Also, the mechanism of 4a in ameliorating neuroinflammation and VaD was systematically explored. Furthermore, to optimize the drug-like properties of 4a, especially for metabolic stability, 15 derivatives were designed and synthesized. As a result, candidate 5f, with a potent IC50 value of 4.5 nmol/L against PDE1C, high selectivity over PDEs, and remarkable metabolic stability, efficiently ameliorated neuron degeneration, cognition and memory impairment in VaD mice model by suppressing NF-κB transcription regulation and activating cAMP/CREB axis. These results further identified PDE1 inhibition could serve as a new therapeutic strategy for treatment of VaD.

Application of self-assembly in polypeptide drugs: a review / 生物工程学报

Self-assembly refers to the spontaneous process where basic units such as molecules and nanostructured materials form a stable and compact structure. Peptides can self-assemble by non-covalent driving forces to form various morphologies such as nanofibers, nano layered structures, and micelles. Peptide self-assembly technology has become a hot research topic in recent years due to the advantages of definite amino acid sequences, easy synthesis and design of peptides. It has been shown that the self-assembly design of certain peptide drugs or the use of self-assembled peptide materials as carriers for drug delivery can solve the problems such as short half-life, poor water solubility and poor penetration due to physiological barrier. This review summarizes the formation mechanism of self-assembled peptides, self-assembly morphology, influencing factors, self-assembly design methods and major applications in biomedical field, providing a reference for the efficient use of peptides.

Discovery of novel exceptionally potent and orally active c-MET PROTACs for the treatment of tumors with MET alterations

Various c-mesenchymal-to-epithelial transition (c-MET) inhibitors are effective in the treatment of non-small cell lung cancer; however, the inevitable drug resistance remains a challenge, limiting their clinical efficacy. Therefore, novel strategies targeting c-MET are urgently required. Herein, through rational structure optimization, we obtained novel exceptionally potent and orally active c-MET proteolysis targeting chimeras (PROTACs) namely D10 and D15 based on thalidomide and tepotinib. D10 and D15 inhibited cell growth with low nanomolar IC50 values and achieved picomolar DC50 values and >99% of maximum degradation (Dmax) in EBC-1 and Hs746T cells. Mechanistically, D10 and D15 dramatically induced cell apoptosis, G1 cell cycle arrest and inhibited cell migration and invasion. Notably, intraperitoneal administration of D10 and D15 significantly inhibited tumor growth in the EBC-1 xenograft model and oral administration of D15 induced approximately complete tumor suppression in the Hs746T xenograft model with well-tolerated dose-schedules. Furthermore, D10 and D15 exerted significant anti-tumor effect in cells with c-METY1230H and c-METD1228N mutations, which are resistant to tepotinib in clinic. These findings demonstrated that D10 and D15 could serve as candidates for the treatment of tumors with MET alterations.

3D-QSARpy: Combining variable selection strategies and machine learning techniques to build QSAR models

Abstract Quantitative Structure-Activity Relationship (QSAR) is a computer-aided technology in the field of medicinal chemistry that seeks to clarify the relationships between molecular structures and their biological activities. Such technologies allow for the acceleration of the development of new compounds by reducing the costs of drug design. This work presents 3D-QSARpy, a flexible, user-friendly and robust tool, freely available without registration, to support the generation of QSAR 3D models in an automated way. The user only needs to provide aligned molecular structures and the respective dependent variable. The current version was developed using Python with packages such as scikit-learn and includes various techniques of machine learning for regression. The diverse techniques employed by the tool is a differential compared to known methodologies, such as CoMFA and CoMSIA, because it expands the search space of possible solutions, and in this way increases the chances of obtaining relevant models. Additionally, approaches for select variables (dimension reduction) were implemented in the tool. To evaluate its potentials, experiments were carried out to compare results obtained from the proposed 3D-QSARpy tool with the results from already published works. The results demonstrated that 3D-QSARpy is extremely useful in the field due to its expressive results.

Molecular mechanism of Cigu Xiaozhi formula interfering with HSC-T6 cell activation by regulating HIF-1α signaling pathway based on computer aided drug design / 药学学报

In this study, we investigated the effect of Cigu Xiaozhi formula on HSC-T6 activity in hypoxic microenvironment based on network pharmacology and computer-aided drug design, and predicted and verified its possible targets and related signaling pathways. The potential active components and targets of Cigu Xiaozhi formula were screened by searching Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Encyclopaedia of Traditional Chinese Medicine (ETCM) and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) databases, and the liver fibrosis related targets retrieved from Gene Cards and Pharm GK database were integrated to obtain the potential targets of Cigu Xiaozhi formula in the treatment of liver fibrosis. GO enrichment analysis and KEGG signaling pathway enrichment analysis were performed on Omic Share platform, and Cytoscape software was used to construct the "potential active ingredient-key target-pathway" network. The active components and target proteins were subjected to molecular docking analysis by Auto Dock software. According to the results of molecular dynamics simulation and binding free energy calculation, the top 5 active components with degree were scored. The active components stigmasterol and β-sitosterol were subjected to molecular docking. CoCl2 was used to induce HSC-T6 cells to construct hypoxia model in vitro. The cell viability was detected by CCK-8 assay, and the optimal time and concentration of hypoxia model of HSC-T6 cells was determined to be 100 µmol·L-1 CoCl2 for 24 h. Under hypoxia condition, HSC-T6 cells were activated, the wound healing rate was significantly increased, and the fluorescence signal of activation marker protein α-smooth muscle actin (α-SMA) was significantly enhanced. However, 6% drug-containing serum could inhibit the activation of HSC-T6 cells, and the wound healing rate was significantly decreased, and the fluorescence signal of α-SMA was significantly weakened. Further studies showed that the expressions of hypoxia-inducible factor-1α (HIF-1α), α-SMA and key proteins of Hedgehog (Hh) signaling pathway in HSC-T6 cells were up-regulated under hypoxia, while the expressions of HIF-1α, α-SMA, Patched-1 (Ptch-1) and glioma related oncogene homology-1 (Gli-1) were down-regulated in 6% drug-containing serum group, the YC-1 group and the cyclopamine group. These results indicated that HIF-1α and Hh signaling pathways were involved in the activation of HSC-T6 cells, and the traditional Chinese medicine Cigu Xiaozhi formula could inhibit the activation of HSC-T6 cells, and the mechanism may be related to the inhibition of HIF-1α expression and the blocking of Hh signaling pathway. In conclusion, Cigu Xiaozhi formula can inhibit the activation of HSC-T6 cells by directly acting on HIF-1α and Hh signaling pathway, and exert an anti-hepatic fibrosis effect. The animal experimental protocol has been reviewed and approved by Laboratory Animal Ethics Committee of Gansu University of Chinese Medicine, in compliance with the Institutional Animal Care Guidelines.

Deep learning-based de novo drug design: principles, tools and practice / 药学学报

Design of structurally-novel drug molecules with deep learning can overcome the technical bottleneck of classical computer-aided drug design. It has become the frontier of new technique research on drug design, and has shown great potential in drug research and development practice. This review starts from the basic principles of deep learning-driven de novo drug design, goes on with the brief introduction to deep molecular generation techniques as well as computational tools and the analysis on representative successful cases, and eventually provides our perspective for future direction and application prospect about this technique. This review will provide ideas on new technique research and references for new drug research and development practice to which this technique is applied.

Need for artificial intelligence in pharmaceutical industry and its limitations

Artificial intelligence (AI) is often being touted as the means to bring about the fourth industrial revolution and its role in almost all sectors of our society is almost certain. This brings about an urgent need for evaluating the benefits and limitations of AI and machine learning (ML) across various sectors. Pharmaceutical industry has pioneered in embracing the use of AI in all its core areas but the success as of now seems very limited. The major advantage of AI is that it reduces the time that is needed for drug development, and in turn, it reduces the costs that are associated with drug development, enhances the returns on investment, and may even cause a decrease in cost for the end user along with improved drug safety. Hence, in this article, we will review the scope and limitations of AI in the pharmaceutical industry along with the brief review of how AI/ML can impact geriatric health care.

Desenvolvimento de novos medicamentos para doenças negligenciadas: uma análise bibliométrica / New drug development for neglected diseases: a bibliometric analysis / Desarrollo de nuevos fármacos para enfermedades desatendidas: un análisis bibliométrico

Doenças negligenciadas impõem um fardo humano, social e econômico devastador a mais de um bilhão de pessoas em todo o mundo. Embora existam ferramentas para controlar e até mesmo eliminar muitas dessas doenças, novos produtos terapêuticos precisam urgentemente ser desenvolvidos. Este artigo se baseia em um estudo que buscou quantificar e caracterizar a produção científica global sobre desenvolvimento de novos medicamentos para doenças negligenciadas, por meio de uma análise bibliométrica. De modo a investigar a pesquisa relacionada ao desenvolvimento de novos medicamentos para as doenças negligenciadas em âmbito global na última década, foi utilizada a base de dados Scopus. Observou-se aumento da produção de conhecimento sobre o tema, com relevante participação de autores, instituições e financiamento brasileiros, sobretudo de instituições públicas. Contudo, os esforços realizados têm sido insuficientes, sendo necessária a implementação de estratégias futuras de pesquisa e de financiamento que propiciem maior produção científica e uma tradução da pesquisa básica para a prática clínica.

Neglected diseases impose a devastating human, social, and economic burden on more than one billion people worldwide. While tools exist to control and even eliminate many of these diseases, new therapeutic products urgently need to be developed. This article is based on a study that sought to quantify and characterize the global scientific production on new drug development for neglected diseases through a bibliometric analysis. The Scopus database was used to investigate the research related to the development of new drugs for neglected diseases globally in the last decade. An increase in the production of knowledge about the theme and the relevant participation of Brazilian authors, institutions and funding, especially from public institutions were observed. However, their efforts have been insufficient, and the implementation of future research and funding strategies that provide greater scientific production and a translation of basic research into clinical practice is necessary.

Las enfermedades desatendidas imponen una carga humana, social y económica devastadora a más de mil millones de personas en todo el mundo. A pesar de haber herramientas para controlar y incluso eliminar muchas de estas enfermedades, es necesario desarrollar con urgencia nuevos productos terapéuticos. Este artículo se basa en un estudio lo cual ha buscado cuantificar y caracterizar la producción científica global sobre el desarrollo de nuevos fármacos para enfermedades desatendidas, a través de un análisis bibliométrico. Para inspeccionar investigaciones relacionadas con el desarrollo de nuevos medicamentos para enfermedades desatendidas en ámbito mundial durante la última década se utilizó la base de datos Scopus. Hubo un aumento de la producción de conocimiento sobre el tema, con una participación relevante de autores, instituciones y financiamiento brasileños, especialmente de instituciones públicas. Sin embargo, los esfuerzos realizados siguen siendo insuficientes, requiriendo la implementación de futuras estrategias de investigación y financiamiento que propicien una mayor producción científica y una traducción de la investigación básica a la práctica clínica.

Design,synthesis,and evaluation of fluoroquinolone derivatives as microRNA-21 small-molecule inhibitors / 药物分析学报

MicroRNA-21(miRNA-21)is highly expressed in various tumors.Small-molecule inhibition of miRNA-21 is considered to be an attractive novel cancer therapeutic strategy.In this study,fluoroquinolone de-rivatives Al-A43 were synthesized and used as miRNA-21 inhibitors.Compound A36 showed the most potent inhibitory activity and specificity for miRNA-21 in a dual-luciferase reporter assay in HeLa cells.Compound A36 significantly reduced the expression of mature miRNA-21 and increased the protein expression of miRNA-21 target genes,including programmed cell death protein 4(PDCD4)and phos-phatase and tensin homology deleted on chromosome ten(PTEN),at 10 uM in HeLa cells.The Cell Counting Kit-8 assay(CCK-8)was used to evaluate the antiproliferative activity of A36;the results showed that the IC50 value range of A36 against six tumor cell lines was between 1.76 and 13.0 μM.Meanwhile,A36 did not display cytotoxicity in BEAS-2B cells(lung epithelial cells from a healthy human donor).Furthermore,A36 significantly induced apoptosis,arrested cells at the G0/G1 phase,and inhibited cell-colony formation in HeLa cells.In addition,mRNA deep sequencing showed that treatment with A36 could generate 171 dysregulated mRNAs in HeLa cells,while the expression of miRNA-21 target gene dual-specificity phosphatase 5(DUSP5)was significantly upregulated at both the mRNA and protein levels.Collectively,these findings demonstrated that A36 is a novel miRNA-21 inhibitor.

Research progress in antisense drug mechanism and chemical modification strategies / 药学学报

Over the past three decades, more and more antisense drugs have been approved for marketing or clinical trails. Antisense technology has become the focus of pharmaceutical research due to its unique advantages in treating diseases and strong clinical development potential. There is a big difference from traditional small molecule chemical drugs, and macromolecular protein biological drugs. Antisense drugs are a very independent drug form. Antisense drugs were initially used to treat diseases with single gene mutations, but recently they have gradually begun to be used for the treatment of common diseases. Rational antisense drug design is crucial for disease treatment based on genetics. This paper reviews the latest progress in the field of action mechanism, chemical modification and delivery strategy of antisense drugs, and analyzes the current intractable problems. It is believed that with the resolution of these problems, the research of antisense drugs can reach a new level.

Structure-based discovery of orally efficient inhibitors via unique interactions with H-pocket of PDE8 for the treatment of vascular dementia

Our previous study demonstrated that phosphodiesterase 8 (PDE8) could work as a potential target for vascular dementia (VaD) using a chemical probe 3a. However, compound 3a is a chiral compound which was obtained by chiral resolution on HPLC, restricting its usage in clinic. Herein, a series of non-chiral 9-benzyl-2-chloro-adenine derivatives were discovered as novel PDE8 inhibitors. Lead 15 exhibited potent inhibitory activity against PDE8A (IC50 = 11 nmol/L), high selectivity over other PDEs, and remarkable drug-like properties (worthy to mention is that its bioavailability was up to 100%). Oral administration of 15 significantly improved the cAMP level of the right brain and exhibited dose-dependent effects on cognitive improvement in a VaD mouse model. Notably, the X-ray crystal structure of the PDE8A-15 complex showed that the potent affinity and high selectivity of 15 might come from the distinctive interactions with H-pocket including T-shaped π-π interactions with Phe785 as well as a unique H-bond network, which have never been observed in other PDE-inhibitor complex before, providing new strategies for the further rational design of novel selective inhibitors against PDE8.