Article
Pharmacology & Pharmacy
Huizhen Ge, Lizeng Peng, Zhou Sun, Huanxiang Liu, Yulin Shen, Xiaojun Yao
Summary: In this study, novel HPK1 inhibitors were identified using virtual screening and kinase inhibition assays. Molecular dynamics simulations were performed to analyze the interaction between the identified compounds and HPK1 kinase domain. The most potent compound showed potential for further development as an HPK1 inhibitor for immunotherapy.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Biology
Hajar Sirous, Giuseppe Campiani, Vincenzo Calderone, Simone Brogi
Summary: HDAC inhibitors have shown potential in reversing cancer-associated epigenetic changes, but the non-selective profile of current inhibitors limits their clinical utility, leading to the search for isoform-selective inhibitors. This study focused on virtual screening for HDAC1 inhibitors, identifying novel benzamide-based analogs with potential inhibitory activity. The computational approach presented in this study offers guidelines for the development of improved benzamide-based derivatives targeting HDAC1 isoform.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Pharmacology & Pharmacy
Chujiao Hu, Zhirui Zeng, Dan Ma, Zhixin Yin, Shanshan Zhao, Tengxiang Chen, Lei Tang, Shi Zuo
Summary: In this study, novel inhibitors of IDH1-R132C were identified using virtual screening and cellular assays. Compound T001-0657 showed the most potent inhibitory effect against cancer cells harboring the IDH1-R132C mutation, while also exhibiting cytotoxicity against wild-type IDH1 cancer cells and normal cells.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Shilpi Sarkar, Thirukumaran Kandasamy, Rajib Shome, Siddhartha Sankar Ghosh
Summary: This study highlights the involvement of epigenomic reprogramming and the role of p300 in breast cancer. By using virtual screening and molecular docking, two potential repurposed drugs, Netarsudil and Imatinib, were identified as inhibitors of p300 activity.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Chemistry, Medicinal
Jing Guo, Shuang Xiang, Jie Wang, Yang Zhou, Zuqin Wang, Zhang Zhang, Ke Ding, Xiaoyun Lu
Summary: Tropomyosin receptor kinases A (TrkA) is a potential therapeutic target for the treatment of tumors and chronic pain. This study discovered a novel TrkA allosteric inhibitor through structure-based virtual screening and conducted preliminary research on its properties.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Review
Biochemistry & Molecular Biology
Ge Wang, Yuhao Bai, Jiarui Cui, Zirui Zong, Yuan Gao, Zhen Zheng
Summary: This review provides an overview of the importance of the RAS gene family and its relevance to cancer development, as well as the challenges in designing drugs targeting RAS. Computer-aided drug design (CADD) offers new approaches for finding RAS-targeted drugs.
Article
Biochemistry & Molecular Biology
Boqian Zhou, Yongguang Zhang, Wanyun Jiang, Haiyang Zhang
Summary: This study used computational methods to perform virtual screening of FDA-approved drugs and identified potential inhibitors against ALDH2. Some compounds showed a low toxicity and comparable or stronger binding strength than known potent inhibitors. However, further verification is needed to confirm the efficacy of these compounds.
Article
Pharmacology & Pharmacy
Tingting Jin, Wei Xu, Roufen Chen, Liteng Shen, Jian Gao, Lei Xu, Xinglong Chi, Nengming Lin, Lixin Zhou, Zheyuan Shen, Bo Zhang
Summary: This study successfully identified potential WEE1 inhibitors through virtual screening, and compound 4 exhibited excellent inhibitory activity and anti-proliferative effects, indicating its potential as a WEE1 inhibitor.
FRONTIERS IN PHARMACOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Dan Zhao, Lu Sun, Shijun Zhong
Summary: In this study, a combined virtual screening approach was used to identify three potential PTP1B inhibitors from multiple databases, which have favorable binding energy and oral bioavailability. These compounds stably bind to PTP1B and occupy both the catalytic and noncatalytic sites, potentially improving selectivity for treating type 2 diabetes.
MOLECULAR DIVERSITY
(2022)
Article
Biochemistry & Molecular Biology
Mahmoud A. A. Ibrahim, Khlood A. A. Abdeljawaad, Laila A. Jaragh-Alhadad, Hesham Farouk Oraby, Mohamed A. M. Atia, Othman R. Alzahrani, Gamal A. H. Mekhemer, Mahmoud F. Moustafa, Ahmed M. Shawky, Peter A. Sidhom, Alaa H. M. Abdelrahman
Summary: The development of multidrug resistance (MDR) caused by overexpression of P-glycoprotein (P-gp/ABCB1/MDR1) is the main reason for the failure of chemotherapy in carcinoma treatment. An in silico study was conducted to discover potential P-gp inhibitors by assessing the binding energies of 512 drug candidates. Five promising drug candidates, valspodar, dactinomycin, elbasvir, temsirolimus, and sirolimus, showed strong binding energies against P-gp transporter and displayed good pharmacokinetic properties. These results indicate their potential as prospective P-gp inhibitors and require further in vitro/in vivo investigations.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Biochemistry & Molecular Biology
Oluwakemi Ebenezer, Maryam A. Jordaan, Nkululeko Damoyi, Michael Shapi
Summary: Noroviruses are non-enveloped viruses causing acute gastroenteritis in humans. The RNA-dependent RNA polymerase is a critical target for developing anti-norovirus agents. Compounds CID-57930781 and CID-44396095 show promising potential as human norovirus inhibitors.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Changyong Deng, Xiaobo Wang, Tangle Wang, Wei Liu, Xiaolan Yuan, Yan Huang, Shuang Cao
Summary: In this study, compound 4 was identified as a promising drug candidate against the drug-resistant influenza virus strain M2-V27A/S31N. Molecular dynamics simulation showed that compound 4 had stability and flexibility when binding to the target protein. The calculated binding free energy was -106.525 kcal/mol. Physicochemical and pharmacokinetic profiles predicted good bioavailability for compound 4.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Chemistry, Medicinal
Xueping Hu, Jinping Pang, Changwei Chen, Dejun Jiang, Chao Shen, Xin Chai, Liu Yang, Xujun Zhang, Lei Xu, Sunliang Cui, Tingjun Hou, Dan Li
Summary: This study identified a group of selective glucocorticoid receptor modulators (SGRMs) through virtual screening, which showed good transrepression activity without transactivation activity, suggesting their potential as novel anti-inflammatory drugs.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Article
Biochemical Research Methods
Bin Liu, Wei Zhang, Sheng Guo, Zhili Zuo
Summary: TRPC5 channel plays crucial roles in various physiological systems, but the evidence of its function is limited. In this study, potential hTRPC5 modulators were identified through virtual screening and molecular dynamics simulations, providing novel insights for the study and treatment of TRPC5-associated diseases.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2021)
Article
Multidisciplinary Sciences
Jingyu Zhu, Kan Li, Lei Xu, Yanfei Cai, Yun Chen, Xinling Zhao, Huazhong Li, Gang Huang, Jian Jin
Summary: A novel machine learning-based virtual screening model was developed to discover new PI3K gamma inhibitors. Among the identified inhibitors, JN-K13 displayed selective cytotoxicity on hematologic tumor cells at low concentrations and promoted apoptosis through the inhibition of PI3K signaling. This study suggests that PI3K gamma could be a potential target for hematologic tumor therapy.
JOURNAL OF ADVANCED RESEARCH
(2022)
Article
Chemistry, Medicinal
Yuwei Yang, Zhenxing Wu, Xiaojun Yao, Yu Kang, Tingjun Hou, Chang-Yu Hsieh, Huanxiang Liu
Summary: A conditional generative model combining a semisupervised variational autoencoder and a toxicity predictor was developed in this study to generate molecules with low toxicity, good drug-like properties, and structural diversity. The model efficiently generates low-toxicity molecules while maintaining structural diversity during the generation process.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Materials Science, Multidisciplinary
Ping Zhou, Fang Feng, Yameng Song, Jing Li, Qin Li, Zerong Xu, Jiamin Shi, Liying Qin, Fei He, Hongjiao Li, Yu Han, Rongzhi Zhang, Huanxiang Liu, Feng Lan
Summary: The design of novel peptide sequences and investigation of cell adhesion mechanisms are crucial for hiPSCs culture on peptide displaying surfaces. This study reveals the importance of near-Asp sequences in RGD-containing peptides and presents a novel peptide, Ac-KGGVFTMPRGDTYRAY, with excellent ability to sustain hiPSCs cultures. Structural modeling and molecular docking confirm the strong affinity between the peptide and ocV133 integrin protein, contributing to its superior performance. These findings shed light on the mechanisms underlying RGD-containing peptides' support of adhesion and offer a better peptide option for hiPSCs culture.
MATERIALS & DESIGN
(2022)
Article
Chemistry, Physical
Huayi Liu, Yi Zhou, Yingjie Song, Qianqian Zhang, Yeyi Kan, Xinyue Tang, Qingjie Xiao, Qianyin Xiang, Huanxiang Liu, Yunzi Luo, Rui Bao
Summary: CRISPR-Cas9 from Streptococcus pyogenes is a powerful biotechnological tool for DNA sequence modification. Understanding the dynamic mechanism of the REC lobe is crucial for designing and engineering better Cas9 enzymes. The structure analysis of the xCas9 P411T variant and molecular dynamics simulations revealed the central role of REC1 in the activation and target site binding process of Cas9.
Article
Biochemistry & Molecular Biology
Qianqian Zhang, Jianting Han, Yongchang Zhu, Shuoyan Tan, Huanxiang Liu
Summary: In this study, the binding thermodynamic and kinetic information of direct inhibitors of InhA to phenoxyphenol derivatives were explored using multiple computer-aided drug design strategies. The results showed that van der Waals interactions were the main driving force for protein-ligand binding, and key amino acid residues contributed significantly to the binding energy.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemical Research Methods
Yanan Tian, Xiaorui Wang, Xiaojun Yao, Huanxiang Liu, Ying Yang
Summary: This paper proposes a novel graph neural network, IFGN, which gradually identifies the key atoms/groups in the molecule related to predicted properties by a multistep focus mechanism. It also generates multistep interpretations to provide a deeper understanding of the model's predictive behaviors.
BRIEFINGS IN BIOINFORMATICS
(2023)
Review
Biochemical Research Methods
Yuan-Qin Huang, Ping Sun, Yi Chen, Huan-Xiang Liu, Ge-Fei Hao, Bao-An Song
Summary: Drug resistance is a major issue impacting human health and agriculture. Developing approaches to address target mutation-induced drug resistance is crucial in biological research. Bioinformatics tools have been developed over the past decade to explore this type of drug resistance, offering a cost-effective and efficient means of analysis. However, these tools are underutilized and their strengths and limitations have not been thoroughly evaluated. This study systematically surveyed 59 freely available bioinformatics tools and analyzed their functionality, data volume, source, operating principle, and performance. The study also discussed the strengths, limitations, and application examples of these tools, providing a valuable toolbox for researchers in biomedical, pesticide, bioinformatics, and pharmaceutical engineering fields, as well as a platform for non-specialists to understand drug resistance prediction.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Shukai Gu, Chao Shen, Jiahui Yu, Hong Zhao, Huanxiang Liu, Liwei Liu, Rong Sheng, Lei Xu, Zhe Wang, Tingjun Hou, Yu Kang
Summary: This study evaluated the impact of structural dynamic information on binding affinity prediction and found that the optimized molecular dynamics protocol improved the predictive performance for the TAF1-BD2 target with high structural flexibility, but not for the less flexible JAK1 and DDR1 targets.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Fengling Wang, Wenling Ye, Yongxing He, Haiyang Zhong, Yongchang Zhu, Jianting Han, Xiaoqing Gong, Yanan Tian, Yuwei Wang, Shuang Wang, Shaoping Ji, Huanxiang Liu, Xiaojun Yao
Summary: Targeting the PD-1/PD-L1 immunologic checkpoint has provided a breakthrough in cancer therapy. A small molecule inhibitor called CBPA was identified as an effective PD-L1 inhibitor with blocking activity and T-cell reinvigoration capacity. CBPA also showed significant antitumor efficacy in mouse tumor models without observable organ toxicity.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biochemistry & Molecular Biology
Syed Jawad Ali Shah, Qianqian Zhang, Jingjing Guo, Hongli Liu, Huanxiang Liu, Jordi Villa-Freixa
Summary: The microtubule-associated protein tau plays a critical role in the development and protection of the nervous system. Dysfunction and accumulation of tau in the brain can lead to various neurodegenerative diseases. This study reveals the detailed mechanism of acetylation-driven tau aggregation.
ACS CHEMICAL NEUROSCIENCE
(2023)
Article
Biochemistry & Molecular Biology
Shuoyan Tan, Jun Wang, Peng Gao, Guotong Xie, Qianqian Zhang, Huanxiang Liu, Xiaojun Yao
Summary: Understanding the selectivity mechanisms of inhibitors for highly similar proteins is crucial in new drug discovery. Developing highly selective targeting of leucine-rich repeat kinase 2 (LRRK2) kinases for Parkinson's disease is challenging due to the similarity of the kinase ATP binding pocket. In this study, computational methods and comprehensive analyses were conducted to investigate the selectivity mechanisms of two representative LRRK2 inhibitors (DNL201 and GNE7915). The results suggest that structural and kinetic differences between the proteins may play a key role in determining the activity of selective small-molecule inhibitors. The proposed selectivity mechanisms could aid in the rational design of novel LRRK2 kinase inhibitors for Parkinson's disease.
ACS CHEMICAL NEUROSCIENCE
(2023)
Article
Biochemical Research Methods
Yang Yue, Shu Li, Lingling Wang, Huanxiang Liu, Henry H. Y. Tong, Shan He
Summary: In this study, a novel framework called MpbPPI is proposed for accurate prediction of amino acid mutations on protein-protein interactions. Pre-training on a strictly screened dataset enables MpbPPI to generate high-quality representations and support flexible application on different mutant-type protein-protein complexes.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Yunhao Ma, Hongmei Zhu, Xinrong Jiang, Zhongkun Zhou, Yong Zhou, Yanan Tian, Hao Zhang, Mengze Sun, Lixue Tu, Juan Lu, Yuqing Niu, Huanxiang Liu, Yingqian Liu, Peng Chen
Summary: This study evaluated the cytotoxicity of 8-methoxy-2,5-dimethyl-5H-indolo[2,3-b]quinoline (MMNC) in colorectal cancer cells and found that MMNC exerted cytotoxicity by inhibiting the expression of PI3K/AKT/mTOR signaling pathway-related proteins, inhibiting cell proliferation, blocking the cell cycle, and inducing apoptosis.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Chemistry, Medicinal
Zhe Wang, Haiyang Zhong, Jintu Zhang, Peichen Pan, Dong Wang, Huanxiang Liu, Xiaojun Yao, Tingjun Hou, Yu Kang
Summary: This study systematically evaluates the performance of traditional methods and AI models in small-molecule conformer generation. The results show that traditional methods outperform AI models in reproducing bioactive conformations, while an AI model has an advantage in generating low-energy conformations.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Medicinal
Jieyu Jin, Dong Wang, Guqin Shi, Jingxiao Bao, Jike Wang, Haotian Zhang, Peichen Pan, Dan Li, Xiaojun Yao, Huanxiang Liu, Tingjun Hou, Yu Kang
Summary: Recently, deep generative models, such as FFLOM, have shown promise in fragment-based drug design by generating molecules with desired properties. FFLOM achieves state-of-the-art performance in terms of validity, uniqueness, novelty, and recovery of generated molecules. It also demonstrates excellent potential in practical scenarios including fragment linking, PROTAC design, R-group growing, and R-group optimization, generating molecules with novel fragments and higher binding affinity.
JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Review
Chemistry, Multidisciplinary
Jingjing Guo, Yiqiong Bao, Mengrong Li, Shu Li, Lili Xi, Pengyang Xin, Lei Wu, Huanxiang Liu, Yuguang Mu
Summary: Biological membranes are complex structures vital for life. Experimental investigation of biomembranes is challenging, but computational approaches such as molecular dynamics (MD) simulations have provided insights into their atomic details and cellular functions. This review highlights the latest advancements in computational methods, from force fields to MD simulations and trajectory analysis. It also discusses current research topics, challenges, and future directions for applying computational technologies in biomembrane systems.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2023)