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使用基于多重質量虧損過濾的 UPLC-MS、化學計量學和計算機毒性預測對鹽酸艾司洛爾注射液進行雜質的創新分析

An innovative impurity profiling of esmolol hydrochloride injection using UPLC-MS based multiple mass defect filter, chemometrics and in-silico toxicity prediction

Zhang B, Li WB, Wang Q, Liu XY, Liu YM, Huang HP, Hu B, Yin S, Wang YK. Arab J Chem. Volume 16, Issue 4, April 2023, 104573. IF=6.0

使用斑馬魚模型研究樺木醇的組織再生機制：通過抑制 ROS/MAPKs/NF-?B 信號軸

Tissue regeneration effect of betulin via inhibition of ROS/MAPKs/NF-?B axis using zebrafish model

Ouyang T, Yin H, Yang J, Liu Y, Ma S. Biomed Pharmacotherapy. Volume 153, September 2022, 113420. IF=7.5

發現2-((2-甲基芐基)硫基)-6-氧代-4-(3,4,5-三甲氧基苯基)-1,6-二氫嘧啶-5-甲腈作為新型且有效的含溴結構域和額外終端域家族蛋白(BET ) 抑制劑：用于治療膿毒癥

Discovery of 2-((2-methylbenzyl) thio)-6-oxo-4-(3,4,5-trimethoxyphenyl)-1,6-dihydropyrimidine-5-carbonitrile as a novel and effective bromodomain and extra-terminal (BET) inhibitor for the treatment of sepsis

Chen X, Meng F, Zhang J, Zhang Z, Ye X, Zhang W, Tong Y, Ji X, Xu R, Xu XL, You QD. Eur J Med Chem. Volume 238, 5 August 2022, 114423. IF=6.7

一種新型化學抑制劑通過抑制 HPIP 癌蛋白來抑制乳腺癌細胞生長和轉移

A novel chemical inhibitor suppresses breast cancer cell growth and metastasis through inhibiting HPIP oncoprotein

Li P, Cao S, Huang Y, Zhang Y, Liu J, Cai X, Zhou L, Jiang Z, Ding L, Zheng Z, Li S, Ye Q. Cell Death Disc. 7,: 198 (2021) IF=7.0

使用計算機和體外方法預測決明子中26種成分的潛在毒性

Predicting the potential toxicity of 26 components in Cassiae semen using in silico and in vitro approaches

Yang J, Wang S, Zhang T, Sun Y, Han L, Banahene PO, Wang Q. Cur Res Tox. Volume 2, 2021, Pages 237-245. IF=3.7

HPLC-QE-MS 技術分析鹽酸倍他司汀注射液雜質譜及質量控制

王國英，周剛，王勤，紀紫薇，寧霄，崔黎. 《中國藥物警戒》.第20卷第12期2023年12月. 綜合影響因子 = 1.104

蘭索拉唑相關雜質的遺傳毒性研究

張倩，申蕓，趙恂，張銳，張靖溥，袁耀佐，陳民輝，張錦琳. 《中國藥學雜志》. 2023年12月第58卷第23期. 綜合影響因子 = 1.251

注射用頭孢美唑鈉的質量分析

耿悅，劉文欣，宋蕓峰，龐慶林，張錦琳，侯玉榮，袁耀佐，曹玲，張玫.《中國抗生素雜志》.2023年8月第48卷第8期. 綜合影響因子 = 1.396

基于化合物結構預測人體ADME / PK性質的效能評價

羅燕，陳濤，王鈺璽，任洪燦，高婕，吳卓璟，王晨.《中國藥事》.2023年7月第37卷第7期. 綜合影響因子 =1.060

奧美拉唑雜質毒性預測及細胞毒性研究

劉荷英，劉波，鄭洋濱，陳濤，劉寧.《藥品評價》.Drug Evaluation 2023,20（9）. 綜合影響因子 =0.228

阿齊沙坦有關物質遺傳毒性評估及限度研究

馮小龍，朱慧明.《中國現代應用藥學》.2023年5月第40卷第10期. 綜合影響因子 =1.365

鹽酸羅格列酮中雜質的ADMET 毒性預測分析

鄭媛媛，楊燁，聶鵬. 《廣東化工》.2023年第9期第50卷總第491期. 綜合影響因子 =0.336

注射用阿莫西林鈉克拉維酸鉀的質量評價

王松，張丹丹，趙海云，于明艷，楊蕙如，陳德俊. 《中國抗生素雜志》.2022年2月第47卷第2期. 綜合影響因子 = 1.396

頭孢拉定顆粒劑穩定性研究

崇小萌，田冶，王立新，姚尚辰，尹利輝，劉穎.《中國藥物評價》.2022年第39卷第1期. 綜合影響因子 = 0.781

替格瑞洛中7 個異構體的毒理評價及含量測定研究

漆欣筑，祝晶，何劼毅，聶鵬.《藥學研究》. 2022 Vol.41, No.6. 綜合影響因子 =0.712

替格瑞洛片有關物質的毒理評價及含量分析

祝晶，漆欣筑，曹桂紅，聶鵬. 《廣東化工》. 2022年第14期第49卷總第472期. 綜合影響因子 =0.336

青霉胺片的有關物質分析

王立萍，劉英 ，宋漢敏，李倚天，王晨.《藥物分析雜志》. 2022, 42(4) .綜合影響因子 =1.438

亮菌甲素注射劑雜質譜研究

尹菁，薛敏華，康麗潔，石蓓佳，陸益紅.《藥學與臨床研究》. 2022 Feb;30(1). 綜合影響因子 =0.739

基于生理藥代動力學模型對鹽酸莫西沙星有效性的研究

高婕，馮芳，王立新，崇小萌，王晨，尹利輝.《藥學學報》.2022, 57(7): 2153 ?2157. 綜合影響因子 =1.815

基于計算毒理學的遺傳毒性評價研究進展

蘭潔，王雪，黃芝瑛，汪祺，文海若.《中國藥事》. 2022年10月第36卷第10期. 綜合影響因子 =1.060

鹽酸普萘洛爾原料藥及片劑有關物質檢測方法的建立及未知雜質β- 同分異構體的研究分析

張樹棟，吳科春，張志軍，吳兆偉，王琳，孫毅，張喆，胡琴.《藥物分析雜志》.2021,41(9). 綜合影響因子 =1.438

數學模型預測藥源性肝損傷研究進展

李敏，李思澤，姚莉，相小強.《中國藥理學與毒理學雜志》.2021年5月第35卷第5期. 綜合影響因子 =0.882

計算機模擬技術與平行人工膜滲透模型在富馬酸比索洛爾片生物等效性豁免研究中的應用

郭志淵，謝華，雍子宜，唐敏，袁軍.《中國新藥雜志》.2021年第30卷第6期. 綜合影響因子 =1.447

LC－MS法測定肌苷片和肌苷口服溶液中的雜質

周明，胡亮，黃婧，李琦.《華西藥學雜志》. 2021，36(5):574~578. 綜合影響因子 =1.231

(定量)構效關系預測利伐沙班有機雜質遺傳毒性

馮小龍，朱慧明.《中國現代應用藥學》.2021年6月第38卷第11期. 綜合影響因子 =1.365

采用機器學習改善大鼠清除率的預測并引導生理藥代動力學建模的工作框架

A Machine Learning Framework to Improve Rat Clearance Predictions and Inform Physiologically Based Pharmacokinetic Modeling

Andrews-Morger A, Reutlinger M, Parrott N, Olivares-Morales A. Mol Pharm. 2023, 20, 10, 5052–5065. IF=4.9

AIDD，一種交互式人工智能驅動的藥物設計軟件，利用分子進化和機制性藥代動力學模擬來同時優化多性質目標

AIDD, an interactive AI-driven drug design system that uses molecular evolution and mechanistic pharmacokinetic simulation to optimize multiple property objectives simultaneously

Clark RD, Jones J, Lawless M, Miller D, Waldman M. Journal of Computer-Aided Molecular Design. Mar, 2024. IF=3.5

SHIP1治療靶點的落地:用于治療遲發型阿爾茨海默病的抑制劑的鑒定和評估

SHIP1 therapeutic target enablement: Identification and evaluation of inhibitors for the treatment of late-onset Alzheimer's disease.

Jesudason CD, Mason ER, Chu S, et al. Alzheimer's & Dementia: Translational Research & Clinical Interventions (TRCI). 2023 Nov 17; 9(4): e12429. CiteScore = 8.9

士的寧作為醛酮還原酶家族1成員B1和B10潛在抑制劑的再利用:計算建模和藥代動力學分析

Repurposing of Strychnine as the Potential Inhibitors of Aldo–keto Reductase Family 1 Members B1 and B10: Computational Modeling and Pharmacokinetic Analysis.

Sarfraz M, Aziz M, Afzal S, Channar PA, Alsfouk BA, Kandhro GA, Hassan S, Sultan A, Hamad A, Arafat M, Qaiser MN, Ahmed A, Siddique F, Ejaz SA. Protein J. 2023 Nov 8. IF=3.0

用于藥物篩選的預測模型：基于小分子的結構圖像和分子描述符

Predictive Models Based on Molecular Images and Molecular Descriptors for Drug Screening

Mamada H, Takahashi M, Ogino M, Nomura Y, Uesawa Y. ACS Omega. 2023, 8, 40, 37186–37195. IF=4.1

使用 α-生育酚作為佐劑的口服疫苗的第一個生理藥代動力學(PBPK) 模型

The First Physiologically Based Pharmacokinetic (PBPK) Model for an Oral Vaccine Using Alpha-Tocopherol as an Adjuvant

Saldanha L, Vale N. Pharmaceutics. 2023, 15(9), 2313. IF=5.4

胺可以同時成為弱堿和較強堿嗎？像變色龍一樣離子化的奇怪案例

Can an Amine Be a Weaker and a Stronger Base at the Same Time? Curious Cases of Chameleonic Ionization

Fraczkiewicz R. ACS Phys. Chem Au 2023, 3, 6, 512–514. CiteScore = 1.7

埃洛石納米管-纖維素醚基生物復合骨架，BCS I 類藥物鹽酸維拉帕米的潛在緩釋系統：壓片表征、體外釋放動力學和體內機制生理藥代動力學模型研究

Halloysite nanotubes-cellulose ether based biocomposite matrix, a potential sustained release system for BCS class I drug verapamil hydrochloride: Compression characterization, in-vitro release kinetics, and in-vivo mechanistic physiologically based pharmacokinetic modeling studies

Husain T, Shoaib MH, Ahmed FR, Yousuf RI, Siddiqui F, Saleem MT, Farooqi S, Jabeen S. International Journal of Molecular Sciences. Volume 251, 1 November 2023, 126409. IF=8.2

PB2205：一種TL-895共價 BTK 抑制劑的機制性吸收和藥代動力學模型：食物和胃酸減少劑酸的影響

PB2205: A Mechanistic Absorption and Pharmacokinetic Model of Covalent BTK Inhibitor TL-895: Influence of Food and Acid Reducing Agents

Macwan J, Fraczkiewicz G, Podoll T, Allard M, Krejsa C, Slattter G. Hemasphere. 2023 Aug; 7(Suppl ): e722700f. IF=5.3

用于預測CYP450代謝酶介導的藥物代謝的計算機軟件的比較和總結

Comparison and summary of in silico prediction tools for CYP450-mediated drug metabolism

Zhai J, Man VH, Ji B, Cai L, Wang J. Drug Discov Today. Volume 28, Issue 10, October 2023, 103728. IF=7.4

CD44靶向長春新堿納米制劑在前列腺癌異種移植模型中的抗癌潛力評估：評估高級藥代動力學的多動態方法

Evaluation of the anticancer potential of CD44 targeted vincristine nanoformulation in prostate cancer xenograft model: a multi-dynamic approach for advanced pharmacokinetic evaluation

Naseer F, Kousar K, Abduh MS, Anjum S, Ahmad T. Cancer Nanotechnology. Volume 14, article number 65, (2023). IF=2.48

使用機器學習方法結合所需的最低實驗數據和物理化學描述符開發高精度的器官組織與血漿分配系數值的 2D-QSAR 模型

Development of a 2D-QSAR Model for Tissue-to-Plasma Partition Coefficient Value with High Accuracy Using Machine Learning Method, Minimum Required Experimental Values, and Physicochemical Descriptors

Handa K, Sakamoto S, Kageyama M, Iijima T. Eur J Drug Metab Pharmacokinet. Volume 48, pages 341–352, (2023). IF=1.9

小腸彎曲桿菌保守基因簇中差減序列介導的治療靶點及采用計算機方法評估抑制

Subtractive sequence-mediated therapeutic targets from the conserved gene clusters of Campylobacter hyointestinalis and computational inhibition assessment

Basharat Z, Alghamdi YS, Mashraqi MM, Makkawi M, Alasmari S, Alshamrani S. J Biomol Struct Dyn. 2024 Apr;42(6):2782-2792. IF=4.4

pK50─多質子化的化合物中單個官能團酸度/堿度的嚴格指標

pK50─A Rigorous Indicator of Individual Functional Group Acidity/Basicity in Multiprotic Compounds

Fraczkiewicz R, Waldman M. J Chem Inf Model. 2023, 63, 10, 3198–3208. IF=5.6

使用體外生物測定的安全性數值比較雌激素化合物的人類體內暴露，進行新一代的風險評估

Next generation risk assessment of human exposure to estrogens using safe comparator compound values based on in vitro bioactivity assays

van Tongeren TCA, Wang S, Carmichael PL, Rietjens IMCM, Li H. Regul Tox. Volume 97, pages 1547–1575, (2023). IF=6.1

人工智能在藥物的代謝和排泄預測中的應用：最新進展、挑戰和未來展望

Artificial Intelligence in Drug Metabolism and Excretion Prediction: Recent Advances, Challenges, and Future Perspectives

Tran TTV, Tayara H, Chong KT. Pharmaceutics. 2023, 15(4), 1260. IF=5.4

缺氧環境下神經神經母細胞瘤細胞對阿托伐他汀暴露的響應

The Involvement of Hypoxia in the Response of Neuroblastoma Cells to the Exposure of Atorvastatin

Correia AS, Marques L, Vale N. Mol Biol. 2023, 45(4), 3333-3346. IF=3.1

靶向 Olokizumab-Interleukin 6 表面相互作用以發現新型 的IL-6 抑制劑

Targeting Olokizumab-Interleukin 6 interaction interface to discover novel IL-6 inhibitors

Tran QH, Cao HN, Nguyen DN, Tran TTN, Le MT, Nguyen QT, Tran VH, Thai KM. J Biomol Struct Dyn. Volume 41, 2023 - Issue 23. IF=4.4

靶向超氧化物歧化酶 I 蛋白治療肌萎縮側索硬化癥的有前景候選藥物的計算機虛擬分析

In Silico Analyses of a Promising Drug Candidate for the Treatment of Amyotrophic Lateral Sclerosis Targeting Superoxide Dismutase I Protein

Pereira GRC, Abrahim-Vieira BA, de Mesquita JF. Pharmaceutics. 2023, 15(4), 1095. IF=5.4

采用生理藥代動力學PBPK模型預測 Enavogliflozin（一種鈉依賴性葡萄糖轉運蛋白2抑制劑）在人體中的藥代動力學

Physiologically Based Pharmacokinetic Modelling to Predict Pharmacokinetics of Enavogliflozin, a Sodium-Dependent Glucose Transporter 2 Inhibitor, in Humans

Kim MS, Choi JS, Ji HY, Yang E, Park JS, Kim HS, Kim MJ, Cho IK, Chung SJ, Chae YJ, Lee KR. Pharmaceutics. 2023, 15(3), 942. IF=5.4

加他汀及其衍生物分子作用模式的計算分析和實驗測試

Computational Analysis and Experimental Testing of the Molecular Mode of Action of Gatastatin and Its Derivatives

Vottero P, Wang Q, Michalak M, Aminpour M, Tuszynski JA. Cancer. IF=5.2

使用體外和體內方法對合成阿片類藥物的代謝評估在法醫毒理學中的應用：以U-47700 為例

Metabolic Evaluation of Synthetic Opioids on the Example of U-47700 with the Use of In Vitro and In Vivo Methods for Forensic Toxicology Application

Rojek S, Poljanska E, Chaim W, Maciow-G?ab M, Bystrowska B. Toxics. 2023, 11(3), 220. IF=5.2

苯氧吲哚衍生物的設計、合成、對抗淀粉樣蛋白 (Aβ) 聚集、抗乙酰膽堿酯酶和抗氧化的神經保護的活性

Design, Synthesis, and Neuroprotective Activity of Phenoxyindole Derivatives on Antiamyloid Beta (Aβ) Aggregation, Antiacetylcholinesterase, and Antioxidant Activities
Laivut S, Moongkarndi P, Kitphati W, Rukthong P, Sathirakul K, Sripha K. Pharmaceuticals. IF=4.6

解決奧沙尼喹體外-體內矛盾，促進新一代抗血吸蟲的藥物治療

Addressing the oxamniquine in vitro-in vivo paradox to facilitate a new generation of anti-schistosome treatments

Toth K, Alwan S, Khan S, McHardy SF, LoVerde PT, Cameron MD. Intl J Parasit Drugs and Drug Resistance. Volume 21, April 2023, Pages 65-73. IF=4.0

深入了解帶有雙酚結構的 2,5-二取代單四唑的藥物代謝：新興雙酚A結構同系物

An Insight into the Metabolism of 2,5-Disubstituted Monotetrazole Bearing Bisphenol Structures: Emerging Bisphenol A Structural Congeners

Gadgoli UB, Sunil Kumar YC, Kumar D. Molecules. Volume 28 Issue 3. IF=4.6

使用 QSAR/QSPR 初步評估AUC來預測藥物的乳轉移模型

Prediction model for milk transfer of drugs by primarily evaluating the area under the curve using QSAR/QSPR

Maeshima T, Yoshida S, Watanabe M, Itagaki F. Pharm Res. Volume 40, pages 711–719, (2023). IF=3.7

(Z)-甲基3-(4-氧代-2-硫代噻唑烷-5-亞基)甲基)-1H-吲哚-2-羧酸酯的N-衍生物作為抗菌劑—計算預測和體外評估

N-Derivatives of (Z)-Methyl 3-(4-Oxo-2-thioxothiazolidin-5-ylidene)methyl)-1H-indole-2-carboxylates as Antimicrobial Agents—In Silico and In Vitro Evaluation

Pertrou A, Geronikaki A, Kartsev V, Kousaxidis A, Papadimitriou-Tsantarliotou A, Kostic M, Ivanov M, Nicolaou I, IS Vizirianakis. Pharmaceuticals. 2023, 16(1), 131. IF=4.6

聚焦于天然植物藥品作為鐵死亡調節劑的綜述和化學信息學分析

Review and Chemoinformatic Analysis of Ferroptosis Modulators with a Focus on Natural Plant Products

Stepanic V, Kucerova-Chlupacova M. Molecules. 2023, 28(2), 475. IF=4.6

口服 VDAC1 衍生的小分子肽可增加雄性大鼠的循環睪酮水平

Oral administration of VDAC1-derived small molecule peptides increases circulating testosterone levels in male rats

Martinez-Arguelles DB, Nedow JW, Gukasyan HJ, Papadopoulos V. Front Endocrinol. Volume 13 – 2022. IF=5.2

常山堿鹽酸鹽作為一種新的口服化療藥物來治療內臟利什曼病感染

Febrifugine dihydrochloride as a new oral chemotherapeutic agent against visceral leishmaniasis infection

Exp Parasit. Volumes 236–237, May–June 2022, 108250. IF=2.1

評估ADMET Predictor在早期發現藥物代謝和藥代動力學項目工作中的作用

Evaluation of ADMET Predictor in Early Discovery Drug Metabolism and Pharmacokinetics Project Work

Anna-Karin Sohlenius-Sternbeck and Ylva Terelius. Drug Metabolism and Disposition. February 2022, 50 (2) 95-104. IF=3.9

3-氯聯苯 (PCB 2) 在相關人細胞系中的代謝：脫氯代謝物的論證

Metabolism of 3-Chlorobiphenyl (PCB 2) in a Human-Relevant Cell Line: Evidence of Dechlorinated Metabolites

Zhang CY, Li X, Flor S, Ruiz P, Kruve A, Ludewig G, Lehmler HJ. Environ Sci Technol. 2022, 56, 17, 12460–12472. IF=11.4

代謝參數來源影響新一代生理藥代動力學PBPK模型中的案例研究：職業中接觸三甲苯的影響

Case study on the impact of the source of metabolism parameters in next generation physiologically based pharmacokinetic models: Implications for occupational exposures to trimethylbenzenes

Sweeney LM. Regul Toxicol Pharmacol. Volume 134, October 2022, 105238. IF=3.4

通過計算機比較分析藥物和相關物質的藥物分析最新趨勢：促進藥物發現的現代化

Recent trends in pharmaceutical analysis to foster modern drug discovery by comparative in-silico profiling of drugs and related substances

Ganorkar SB, VanderHeyden Y. TrAC Trends Anal Chem. Volume 157, December 2022, 116747. IF=13.1

1,2,3-三唑醇的緩蝕作用及生態毒理學評價

Corrosion inhibition and ecotoxicological assessment of 1,2,3-triazolic alcohols

Fernandes CM, Palmeira-Mello MV, Leite MC, Oliveira JAM, Martins II, de Sác RG, de Almeida LA, Souza AMT, Campos VR. Mat Chem Phys. Volume 290, 15 October 2022, 126508. IF=4.6

藿香中 5'-甲氧基川膽堿的臨床前藥代動力學和藥效學研究：體內和計算機預測方法

Preclinical Pharmacokinetic and Pharmacodynamic Investigation of 5’-Methoxynobiletin from Ageratum conyzoides: In vivo and In silico Approaches

Faqueti LG, da Silva LAL, Moreira GSG, Kraus S, de Jesus GdSC, Honorato LA, de Araújo BV, dos Santos ARS, Biavatti MW. Pharmaceutical Research. Volume 39, pages 2135–2145, (2022). IF=3.7

基于片段的藥物發現——高質量分子庫的重要性

Fragment-based drug discovery—the importance of high-quality molecule libraries

Bon M, Bilsland A, Bower J, McAula K. Mol Onco. November 2022. IF=6.6

從傳統方法到數據驅動的藥物化學：案例研究

From traditional to data-driven medicinal chemistry: A case study

Kunimoto R, Bajorath J, Aoki K. Drug Discov Today. Volume 27, Issue 8, August 2022, Pages 2065-2070. IF=7.4

機器學習引導小分子藥物的早期發現

Machine Learning guided early drug discovery of small molecules

Pillai N, Dasgupta A, Sudsakorn S, Fretland J, Mavroudisa PD. Drug Discov Today. Volume 27, Issue 8, August 2022, Pages 2209-2215. IF=7.4

羥氯喹治療瘧疾的生理藥代動力學模型及針對不同人群的優化給藥方案

Physiologically-Based Pharmacokinetics Modeling for Hydroxychloroquine as a Treatment for Malaria and Optimized Dosing Regimens for Different Populations

Zhai J, Ji B, Cai L, Liu S, Sun Y, Wang J. J. Pers. Med. 2022, 12(5), 796. IF=3.4

滅螺劑3-芳基-2-羥基-1,4-萘醌抗光滑雙臍螺的活性

Molluskicidal activity of 3-aryl-2-hydroxy-1,4-naphthoquinones against Biomphalaria glabrata

de Luna Martins D, Silva NAA, Ferreira VF, Rangel LS, Santos JAA, Faria RX. Acta Tropica. Volume 231, July 2022, 106414. IF=2.7

通過藥物設計方法策略發現雙 5-HT2A/D2 受體拮抗劑的新化學型

Discovery of new chemotypes of dual 5-HT2A/D2 receptor antagonists with a strategy of drug design methodologies

Radan M, Djikic T, Nikolic K. Future Med Chem. VOL. 14, NO. 13. IF=4.2

氟化 N-苯甲酰胺烯胺酮作為T型 Ca2+ 通道阻滯劑的潛在抗驚厥藥的評價

Evaluation of potential anticonvulsant fluorinated N-benzamide enaminones as T-type Ca2+ channel blockers

Amaye IL, Jackson-Ayotunde PL, Martin-Caraballo M. Bioorg Med Chem. Volume 65, 1 July 2022, 116766. IF=3.5

評估基于高通量生理藥代動力學 (HT-PBPK) 建模預測的成功與否，為早期藥物發現提供信息

Evaluation of the Success of High-Throughput Physiologically Based Pharmacokinetic (HT-PBPK) Modeling Predictions to Inform Early Drug Discovery

Naga D, Parrott N, Ecker GF, Olivares-Morales A. Mol Pharm. 2022, 19, 7, 2203–2216. IF=4.9

292種化學品體外微核試驗結果的全面解讀：從危害識別到風險評估應用

Comprehensive interpretation of in vitro micronucleus test results for 292 chemicals: from hazard identification to risk assessment application

Kuo B, Beal MA, Wills JW, White PA, Marchetti F, Nong A, Barton-Maclaren TS, Houck K, Yauk CL. Arch Toxicol. Volume 96, pages 2067–2085, (2022). IF=6.1

體外代謝活化后激活p53信號傳導的環境化學物質的鑒定

Identification of environmental chemicals that activate p53 signaling after in vitro metabolic activation

Ooka M, Zhao J, Shah P, Travers J, Klumpp-Thomas C, Xu X, Huang R, Ferguson S, Witt KL, Smith-Roe SL, Simeonov A, Xia M. Arch Toxicol. Volume 96, pages 1975–1987, (2022). IF=6.1

使用基于結構和基于配體的方法來設計具有鐵螯合特性的雙重 COX-2和5-LOX 抑制劑

Design of Dual COX-2 and 5-LOX Inhibitors with Iron-Chelating Properties Using Structure-Based and Ligand-Based Methods

Bo?kovi? J, Ruzic D, ?udina O, Nikolic K, Dobri?i? V. Drug Design & Discovery. Volume 19, Number 4. IF=1.099

PBPK建模在局部給藥中的應用和Cmax 估算不確定性的表征：案例研究方法

PBK modelling of topical application and characterisation of the uncertainty of Cmax estimate: A case study approach

Li H, Reynolds J, Sorrell I, Sheffield D, Pendlington R, Cubberley R, Nicol B. Toxicol Appl Pharmacol. Volume 442, 1 May 2022, 115992. IF=3.8

通過LC-Q-TOF-MS 和 NMR 鑒定和表征烏拉地爾應激降解產物：降解產物的毒性預測

Identification and characterization of urapidil stress degradation products by LC-Q-TOF-MS and NMR: Toxicity prediction of degradation products

Velip L, Dhiman V, Kushwah BS, Madhyanapu V, Gananadhamu GS. J Pharm Biomed Anal. Volume 211, 20 March 2022, 114612. IF=3.4

使用計算機預測和體外方法篩選肝毒性化學品和CYP450 酶抑制劑

Use In Silico and In Vitro Methods to Screen Hepatotoxic Chemicals and CYP450 Enzyme Inhibitors

Yitong Liu. High-Throughput Screening Assays in Toxicology. p189–198. Book.

FLT3受體酪氨酸激酶胞外抑制劑的高通量篩選揭示了化學多樣性和可成藥性的負向變構調節劑

High-Throughput Screening for Extracellular Inhibitors of the FLT3 Receptor Tyrosine Kinase Reveals Chemically Diverse and Druggable Negative Allosteric Modulators

Hany R, Leyris JP, Bret G, Mallié S, Sar C, Thouaye M, Hamze A, Provot O, Sokoloff P, Valmier J, Rognan D. ACS Chem Bio. 2022, 17, 3, 709–722. IF=4.0

ASP5878的發現：作為泛FGFR抑制劑的嘧啶衍生物的合成和構效關系分析，最終化合物的代謝穩定性和hERG通道抑制活性得到了改善

Discovery of ASP5878: Synthesis and structure–activity relationships of pyrimidine derivatives as pan-FGFRs inhibitors with improved metabolic stability and suppressed hERG channel inhibitory activity

Kuriwaki I, Kameda M, Iikubo K, Hisamichi H, Kawamoto Y, Kikuchi S, Moritomo H, Terasaka T, Iwai Y, Noda A, Tomiyama H, Kikuchi A, Hirano M. Bioorg Med Chem. Volume 59, 1 April 2022, 116657. IF=3.5

具有雙酚結構的四唑衍生物的雌激素活性：計算研究、合成和體外評估

Estrogenic Activity of Tetrazole Derivatives Bearing Bisphenol Structures: Computational Studies, Synthesis, and In Vitro Assessment

Gadgoli UB, Kumar S, Kumar D, Pai M, Pulya S, Ghosh B, Kulkarni OP. J Chem Inf Model. 2022, 62, 4, 854–873. IF=5.6

減少生物醫學研究中使用動物的替代實驗方法

Alternative experimental approaches to reduce animal use in biomedical studies

Lee SY, Lee DY, Kang JH, Jeong JW, Kim JH, Kim HW, Oh DH, Kim JM, Rhim SJ, Kim GD, Kim HS, Jang YD, Park Y, Hura SJ. J Drug Deliv Sci Technol. Volume 68, February 2022, 103131. IF=5.0

將體外試驗和計算機預測作為輸入數據的下一代人體生理動力學 (PBK) 模型的預測性能

Predictive Performance of Next Generation Human Physiologically Based Kinetic (PBK) Models Based on In Vitro and In Silico Input Data

Punt A, Louisse J, Beekmann K, Pinckaers N, Fabian E, van Ravenzwaay B, Carmichael PL, Sorrell I, Moxon TE. Altex.  2022;39(2):221–234. IF=5.6

植物產品質體醌類似物在結直腸癌治療中有效性的體外和計算機研究

In Vitro and In Silico Study of Analogs of Plant Product Plastoquinone to Be Effective in Colorectal Cancer Treatment

Ciftci HI, Sever B, Ocak F, Bayrak N, Y?ld?z M, Y?ld?r?m H, DeMirci H, Tateishi H, Otsuka M, Fujita M, Tuyun AF. Molecules. 2022 Jan 21;27(3):693. IF=4.6

通過表達分析和計算機預測研究鑒定苯基氨基甲酰嗪烷-1,3,4-惡二唑酰胺作為脂氧合酶抑制劑

Identification of phenylcarbamoylazinane-1,3,4-oxadiazole amides as lipoxygenase inhibitors with expression analysis and in silico studies

Bashir B, Shahid W, Ashraf M, Saleem M, Rehman AU, Muzaffar S, Imran M, Amjad H, Bhattarai K. Bioorg Chem. Volume 115, October 2021, 105243. IF=5.1

通過pH調節劑改善具有 pH 依賴性溶解度的藥物的溶出行為和口服吸收：生理學真實的質量轉運分析

Improving Dissolution Behavior and Oral Absorption of Drugs with pH-Dependent Solubility Using pH Modifiers: A Physiologically Realistic Mass Transport Analysis

Salehi N, Kuminek G, Al-Gousous J, Sperry DC, Greenwood DE, Waltz NM, Amidon GL, Ziff RM, Amidon GE. Molecular Pharmaceutics. 2021, 18, 9, 3326–3341. IF=4.9

PBPK模型作為預測和理解尿苷 5'-二磷酸-葡萄糖醛酸基轉移酶底物在腸道中代謝的工具

PBPK Modeling as a Tool for Predicting and Understanding Intestinal Metabolism of Uridine 5′-Diphospho-Glucuronosyltransferase Substrates

Reddy MB, Bolger MB, Fraczkiewicz G, Del Frari L, Luo L, Lukacova V, Mitra A, Macwan JS, Mullin JM, Parrott N, Heikkinen AT. Pharmaceutics. 2021, 13(9), 1325. IF=5.4

具有抗HIV-1蛋白酶活性的苯丙酮衍生物的3D-QSAR、分子對接和ADMET計算機預測研究

3D-QSAR, molecular docking and in silico ADMET studies of propiophenone derivatives with anti-HIV-1 protease activity

Jovanovi? M, Turkovi? N, Ivkovic B, Vuji? Z, Nikolic K, Grubi?i? S. Struct Chem. Volume 32, pages 2341–2353, (2021). IF=1.7

用于預測SAMPL7親脂性 (logP) 的機器學習多任務模型面臨的挑戰

Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge

Lenselink EB, Stouten PFW. J Comput Aided Mol Des. Volume 35, pages 901–909, (2021). IF=3.5

洞見10-脫甲氧基-10-甲基氨基秋水仙堿的氨基甲酸酯和硫代氨基甲酸酯的抗癌潛力

An insight into the anticancer potential of carbamates and thiocarbamates of 10-demethoxy-10-methylaminocolchicine

Krzywik J, Aminpour M, Maj E, Moshari M, Mozga W, Wietrzyk J, Tuszynski JA, Huczyńskia A. Eur J Med Chem. Volume 215, 5 April 2021, 113282. IF=6.7

口服APX3330可減少臨床前小鼠模型中的L-CNV 損傷，并使用 PBPK模型確認臨床2期 DR/DME 的臨床給藥劑量在人視網膜具有足夠的濃度分布

Oral APX3330 treatment reduces L-CNV lesions in preclinical mouse model and confirms Phase 2 DR/DME clinical dose with sufficient distribution to human retina using PBPK modeling

Silva LL, Lambert-Cheatham N, Stratford RE, Quinney SK, Corson TW, Kelley MR. Invest. Ophthal. and Vis. Sci. Volume 62, Issue 8. IF=4.4

分解曲線數據分析，深入了解天然產物的多重藥效

Decomposition Profile Data Analysis for Deep Understanding of Multiple Effects of Natural Products

Nemoto S, Morita K, Mizuno T, Kusuhara H. J Nat Prod. 2021, 84, 4, 1283–1293. IF=5.1

熱帶藥用植物中獲得的潛在組織蛋白酶L抑制劑被鑒定為新型抗光老化劑的分子建模

Molecular modeling for potential cathepsin L inhibitor identification as new anti-photoaging agents from tropical medicinal plants

Damayanti S, Fabelle N.R, Yooin W, Insanu M, Jiranusornkul S, Wongrattanakamon P. J Bioenerg Biomemb. Volume 53, pages 259–274, (2021). IF=3.0

醫學物理學家在成像機器學習和深度學習的基礎

Basic of machine learning and deep learning in imaging for medical physicists

Manco L, Maffei N, Strolin S, Vichi S, Bottazzi L, Strigari L. Physica Medica. Volume 83, March 2021, Pages 194-205. IF=3.4

在數據有限的情況下, 預測兒童的血漿藥物游離百分數以開展人體健康風險評估

Prediction of fraction unbound in plasma in children in data-limited scenarios for human health risk assessment

Yun YE, Edginton AN. Computational Toxicology. Volume 18, May 2021, 100168. CiteScore=5.6

通過 UPLC、UHPLC-Q-TOF/MS/MS 和NMR表征尼達尼布的應激降解產物：具有致突變警示結構的降解產物的論證

Characterization of stress degradation products of nintedanib by UPLC, UHPLC-Q-TOF/MS/MS and NMR: Evidence of a degradation product with a structure alert for mutagenicity

Balhara A, Singh S, Tiwari S, Gananadhamu S, Kumar Talluri MVN. J Pharm Biomed Anal. Volume 199, 30 May 2021, 114037. IF=3.4

使用新定義的比較化合物閾值開展抗雄激素在人體中暴露的新一代風險評估

Next generation risk assessment of human exposure to anti-androgens using newly defined comparator compound values

van Tongeren TCA, Moxon TE, Dent MP, Li H, Carmichael PL, Rietjens IMCM. Toxicol In Vitro. Volume 73, June 2021, 105132. IF=3.4

噴他脒類似物在人體內的沉積—光譜和計算機預測的方法

Deposition of pentamidine analogues in the human body – spectroscopic and computational approaches

Zo?eka T, D?m?t?r O, Rezler M, Enyedy EA, Maciejewska D. Eur J Pharm Sci. Volume 161, 1 June 2021, 105779. IF=4.6

新型2-硫代-咪唑啶-4-伯氨喹的合成、生物活性及計算機藥代動力學預測

Synthesis, Biological Activity and In Silico Pharmacokinetic Prediction of a New 2-Thioxo-Imidazoldidin-4-One of Primaquine

Pereira M, Caljon G, Gouveia MJ, Maes L, Vale N. Pharmaceuticals. 2021, 14(3), 196. IF=4.6

開發長春瑞濱的透皮水凝膠制劑，并評估其體外特性和抗黑色素瘤細胞的活性，通過計算機模擬預測其藥物吸收

Development of transdermal based hydrogel formulations of vinorelbine with an evaluation of their in vitro profiles and activity against melanoma cells and in silico prediction of drug absorption

Fonseca AM, Araújo CCB, Henriques da Silva J, Honorio TS, Nasciutti LE, Cabral LM, Almada do Carmo F, Pereira de Sousa V. J Drug Deliv Sci Technol. Volume 63, June 2021, 102449. IF=5.0

弱堿性藥物在胃-腸液變化系統中的溶出曲線的體外敏感性分析:口服給藥后藥物在血漿中暴露變化的解釋

In Vitro Sensitivity Analysis of the Gastrointestinal Dissolution Profile of Weakly Basic Drugs in the Stomach-to-Intestine Fluid Changing System: Explanation for Variable Plasma Exposure after Oral Administration

Takagi T, Masada T, Minami K, Kataoka M, Izutsu K, Matsui K, Yamashita S. Mol Pharm. 2021, 18, 4, 1711–1719. IF=4.9

開發用于預測腦毛細血管內皮細胞上P-糖蛋白外排可能性的計算機模型，用于預測化合物透過腦的滲透性

Development of an In Silico Prediction Model for P-glycoprotein Efflux Potential in Brain Capillary Endothelial Cells toward the Prediction of Brain Penetration

Watanabe R, Esaki T, Ohashi R, Kuroda M, Kawashima H, Komura H, Natsume-Kitatani Y, Mizuguchi K. J Med Chem.2021, 64, 5, 2725–2738. IF=7.3

針對 SARS-CoV-2主要蛋白酶的選擇性潛在抗病毒藥物的分子對接、結合模式分析、分子動力學和 ADMET/毒性特性預測：抗COVID-19的老藥新用

Molecular docking, binding mode analysis, molecular dynamics, and prediction of ADMET/toxicity properties of selective potential antiviral agents against SARS-CoV-2 main protease: an effort toward drug repurposing to combat COVID-19

Rai H, Barik A, Singh YP, Suresh A, Singh G, Nayak UY, Dubey VK, Modi G. Mol Divers. Volume 25, pages 1905–1927, (2021). IF=3.8

地中海地區水生環境中的藥物代謝產物和轉化產物的出現

Occurrence of pharmaceutical metabolites and transformation products in the aquatic environment of the Mediterranean area

Ibá?ez M, Bijlsma L, Pitarch E, Lopez FJ, Hernández F. Trends Analyt Chem. Volume 29, March 2021, e00118. IF=11.2

使用先進的藥物技術開發激酶抑制劑作為抗梨型鞭毛蟲病治療的一個奇怪案例

A Curious Case for Development of Kinase Inhibitors as Antigiardiasis Treatments Using Advanced Drug Techniques

Michaels SA, Hennessey KM, Paragas N, Paredez AR, Ojo KK. ACS Infect Dis. 2021, 7, 5, 943–947. IF=5.3

通過基于合理轉錄組學的老藥新用方法鑒定37種用于治療COVID-19的異質候選藥物

Identification of 37 Heterogeneous Drug Candidates for Treatment of COVID-19 via a Rational Transcriptomics-Based Drug Repurposing Approach

Gelemanovic A, Vidovic T, Stepanic V, Trajkovic K. Pharmaceuticals. 2021 Feb; 14(2): 87. IF=4.6

人工智能在生命科學研究中的最佳實踐

Best practices for artificial intelligence in life sciences research

Makarov VA, Stouch T, Allgood B, Willis CD, Lynch N. Drug Discov Today. Volume 26, Issue 5, May 2021, Pages 1107-1110. IF=7.4

基于化學信息學鑒定非洲來源的天然產物作為潛在新型抗SARS-CoV-2 化合物

Cheminformatics-Based Identification of Potential Novel Anti-SARS-CoV-2 Natural Compounds of African Origin

Kwofie SK, Broni E, Asiedu SO, Kwarko GB, Dankwa B, Enninful KS, Tiburu EK, Wilson MD. Molecules. 26(406):406. IF=4.6

采用生理藥代動力學模型研究達比加群酯仿制藥的替代制劑處方因素

Physiologically-based pharmacokinetics modeling to investigate formulation factors influencing the generic substitution of dabigatran etexilate

Farhan N, Cristofoletti R, Basu S, Kim S, Lingineni K, Jiang S, brown JD, Fang L, Lesko LJ, Schmidt S. CPT Pharmacometrics Syst Pharmacol.CiteScore=6.3

N-去乙酰硫代秋水仙堿及4-碘-N-去乙酰硫代秋水仙堿衍生物的合成、抗癌活性及分子對接研究

Synthesis, anticancer activity and molecular docking studies of N-deacetylthiocolchicine and 4-iodo-N-deacetylthiocolchicine derivatives

Klejborowska G, Urbaniak A, Maj E, Wietrzyk J, Moshari M, Preto J, Tuszynski JA, Chambers TC, Huczynski A. Bioorg Med Chem. Volume 32, 15 February 2021, 116014. IF=3.5

通過基于結構的虛擬篩選方法發現化合物 GSK575594A、地西泮和氟馬西尼對豬蛔蟲煙堿乙酰膽堿受體 (nAChR) 的潛在調節作用

Potential modulating effect of the Ascaris suum nicotinic acetylcholine receptor (nAChR) by compounds GSK575594A, diazepam and flumazenil discovered by structure-based virtual screening approach

Stevanovic S, Marjanovi? DS, Trailovi? SM, Zdravkovi? N, Perdih A, Nikolica K. Mol Biochem Parasitology. Volume 242, March 2021, 111350. IF=1.5

一硫代碳腙衍生物的合成、理化表征和TD-DFT計算

Synthesis, physicochemical characterization, and TD–DFT calculations of monothiocarbohydrazone derivatives

Mr?an GS, Vastag GG, ?kori? D?, Radanovi? MM, Verbi? T?, Mil?i? MK, Stojiljkovi? IN, Markovi? OS, Matijevi? BM. Struct Chem. Volume 32, pages 1231–1245, (2021). IF=1.7

4,5,6,7-四溴-2,3-二氫-1,1,3-三甲基-3-(2,3,4,5-四溴苯基)-1H-茚 (OBTMPI)：在人體內的水平和計算機毒理學曲線

4,5,6,7-Tetrabromo-2,3-dihydro-1,1,3-trimethyl-3-(2,3,4,5-tetrabromophenyl)-1H-indene (OBTMPI): Levels in humans and in silico toxicological profiles

Das D, Kulkarni S, Barton-Maclaren T, Zhu J. Environmental Pollution. Volume 273, 15 March 2021, 116457. IF=8.9

綜述預測SAMPL6 pKa 面臨的挑戰：評估小分子微觀和宏觀 pKa預測

Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions

Isik M, Rustenburg AS, Rizzi A, Gunner MR, Mobley DL, Chodera JD. J Comput Aided Mol Des. Volume 35, pages 131–166, (2021). IF=3.5

使用PBPK模型和治療藥物監測進行萬古霉素的計算機藥代動力學研究

In silico pharmacokinetic study of vancomycin using PBPK modeling and therapeutic drug monitoring

Ferreira A, Martins H, Oliveira JC, Lapa R, Vale N. Curr Drug Metab. 2021;22(2):150-162. IF=2.3