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Facing small and biased data dilemma in Drug discovery with enhanced federated learning approaches

Science China(Life Sciences) 2022年第3期65卷 529-539页

作者： Zhaoping Xiong Ziqiang Cheng Xinyuan Lin Chi Xu Xiaohong Liu Dingyan Wang Xiaomin Luo Yong Zhang Hualiang Jiang Nan Qiao Mingyue Zheng Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and TechnologyShanghaiTech UniversityShanghai 200031China Drug discovery and Design Center State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of Sciences Beijing 100049China School of Information Science and Technology University of Science and Technology of ChinaHefei 230000China Laboratory of Health Intelligence Huawei Technologies Co.LtdShenzhen 518100China

Artificial intelligence(AI)models usually require large amounts of high-quality training data,which is in striking contrast to the situation of small and biased data faced by current Drug discovery pipelines.The concept of federated learning has been proposed to utilize distributed data from different sources without leaking sensitive information of the data.This emerging decentralized machine learning paradigm is expected to dramatically improve the success rate of AI-powered Drug discovery.Here,we simulated the federated learning process with different property and activity datasets from different sources,among which overlapping molecules with high or low biases exist in the recorded values.Beyond the benefit of gaining more data,we also demonstrated that federated training has a regularization effect superior to centralized training on the pooled datasets with high biases.Moreover,different network architectures for clients and aggregation algorithms for coordinators have been compared on the performance of federated learning,where personalized federated learning shows promising results.Our work demonstrates the applicability of federated learning in predicting drug-related properties and highlights its promising role in addressing the small and biased data dilemma in Drug discovery.

关键词： federated learning Drug discovery Fed AMP Non-IID data

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Artificial intelligence and machine learning in Drug discovery and development

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Intelligent Medicine 2022年第3期2卷 134-140页

作者： Veer Patel Manan Shah Ahmedabad International School AhmedabadGujaratIndia Department of Chemical Engineering School of TechnologyPandit Deendayal Energy UniversityGandhinagarGujaratIndia

The current rise of artificial intelligence and machine learning has been significant.It has reduced the human workload improved quality of life significantly.This article describes the use of artificial intelligence and machine learning to augment Drug discovery and development to make them more efficient and accurate.In this study,a systematic evaluation of studies was carried out;these were selected based on prior knowledge of the authors and a keyword search in publicly available databases which were filtered based on related context,abstract,methodology,and full text.This body of work supported the roles of machine learning and artificial intelligence in facilitating drug development and discovery processes,making them more cost-effective or altogether eliminating the need for clinical trials,owing to the ability to conduct simulations using these technologies.They also enabled researchers to study different molecules more extensively,without any trials.The results of this paper demonstrate the prevalent application of machine learning and artificial intelligence methods in Drug discovery,and indicate a promising future for these technologies;these results should enable researchers,students,and pharmaceutical industry to dive deeper into machine learning and artificial intelligence in a Drug discovery and development context.

关键词： Artificial intelligence Machine learning Drug discovery

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Three-dimensional aspects of formulation excipients in Drug discovery:a critical assessment on orphan excipients,matrix effects and drug interactions

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Journal of Pharmaceutical Analysis 2020年第6期10卷 522-531页

作者： Vijayabhaskar Veeravalli Hanumanth Srikanth Cheruvu Pratima Srivastava Lakshmi Mohan Vamsi Madgula Syngene International Limited Biocon ParkSEZBommasandra Industrial Area-Phase-IV Bommasandra-Jigani Link RoadBangalore560099India GVK BIO Pvt Ltd NacharamHyderabadTelangana500076India

Formulation/pharmaceutical excipients play a major role in formulating drug candidates,with the objectives of ease of administration,targeted delivery and complete availability.Many excipients used in pharmaceutical formulations are orphanized in preclinical Drug discovery.These orphan excipients could enhance formulatability of highly lipophilic compounds.Additionally,they are safe in preclinical species when used below the LD50 values.However,when the excipients are used in formulating compounds with diverse physico-chemical properties,they pose challenges by modulating study results through their bioanalytical matrix effects.Excipients invariably present in study samples and not in the calibration curve standards cause over-/under-estimation of exposures.Thus,the mechanism by which excipients cause matrix effects and strategies to nullify these effects needs to be revisited.Furthermore,formulation excipients cause drug interactions by moderating the pathways of drug metabolizing enzymes and drug transport proteins.Although it is not possible to get rid of excipient driven interactions,it is always advised to be aware of these interactions and apply the knowledge to draw meaningful conclusions from study results.In this review,we will comprehensively discuss a)orphan excipients that have wider applications in preclinical formulations,b)bioanalytical matrix effects and possible approaches to mitigating these effects,and c)excipient driven drug interactions and strategies to alleviate the impacts of drug interactions.

关键词： Formulation excipients Preclinical Drug discovery Matrix effects drug interactions Bioanalysis Pharmacokinetics Formulation development

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Recent insights for the emerging COVID-19:Drug discovery,therapeutic options and vaccine development

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Asian Journal of Pharmaceutical Sciences 2021年第1期16卷 4-23页

作者： Yuefei Zhu Jia Li Zhiqing Pang Department of Biomedical Engineering Columbia UniversityNew York 10027USA Key Laboratory of Smart drug Delivery Ministry of EducationSchool of PharmacyFudan UniversityShanghai 201203China Department of Biomedical Sciences Faculty of MedicineHealth and Human SciencesMacquarie UniversitySydney NSW 2109Australia

SARS-CoV-2 has been marked as a highly pathogenic coronavirus of COVID-19 disease into the human population,causing over 5.5 million confirmed cases worldwide.As COVID-19 has posed a global threat with significant human casualties and severe economic losses,there is a pressing demand to further understand the current situation and develop rational strategies to contain the drastic spread of the virus.Although there are no specific antiviral therapies that have proven effective in randomized clinical trials,currently,the rapid detection technology along with several promising therapeutics for COVID-19 have mitigated its drastic transmission.Besides,global institutions and corporations have commenced to parse out effective vaccines for the prevention of COVID-19.Herein,the present review will give exhaustive details of extensive researches concerning the Drug discovery and therapeutic options for COVID-19 as well as some insightful discussions of the status of COVID-19.

关键词： Coronavirus COVID-19 SARS-CoV-2 Precise prevention and control Drug discovery Vaccine development

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Anticancer Drug discovery by targeting cullin neddylation

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Acta Pharmaceutica Sinica B 2020年第5期10卷 746-765页

作者： Qing Yu Yihan Jiang Yi Sun Cancer Institute of the 2nd Affiliated Hospital Institute of Translational MedicineZhejiang University School of MedicineHangzhou 310029China Division of Radiation and Cancer Biology Department of Radiation OncologyUniversity of MichiganAnn ArborMI 48109.USA

Protein neddylation is a post-translational modification which transfers the ubiquitin-like protein NEDD8 to a lysine residue of the target substrate through a three-step enzymatic cascade.The bestknown substrates of neddylation are cullin family proteins,which are the core component of Cullin-RING E3 ubiquitin ligases(CRLs).Given that cullin neddylation is required for CRL activity,and CRLs control the turn-over of a variety of key signal proteins and are often abnormally activated in cancers,targeting neddylation becomes a promising approach for discovery of novel anti-cancer therapeutics.In the past decade,we have witnessed significant progress in the field of protein neddylation from preclinical target validation,to drug screening,then to the clinical trials of neddylation inhibitors.In this review,we first briefly introduced the nature of protein neddylation and the regulation of neddylation cascade,followed by a summary of all reported chemical inhibitors of neddylation enzymes.We then discussed the structure-based targeting of protein-protein interaction in neddylation cascade,and finally the available approaches for the discovery of new neddylation inhibitors.This review will provide a focused,up-to-date and yet comprehensive overview on the discovery effort of neddylation inhibitors.

关键词： Neddylation Anticancer Drug discovery Ubiquitin-proteasome system Small molecule inhibitors Virtual screen High-throughput screening

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Natural Products as Potential Lead Compounds for Drug discovery Against SARS-CoV-2

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Natural Products and Bioprospecting 2021年第6期11卷 611-628页

作者： Oyere Tanyi Ebob Smith B.Babiaka Fidele Ntie-Kang Department of Chemistry Faculty of ScienceUniversity of BueaP.O.Box 63BueaCameroon Institute for Pharmacy Martin-Luther-Universität Halle-WittenbergKurt-Mothes-Str.306120 Halle(Saale)Germany

For the past 2 years,the coronavirus responsible for the COVID-19 infection has become a world pandemic,ruining the lives and economies of several nations in the world.This has scaled up research on the virus and the resulting infection with the goal of developing new vaccines and therapies.Natural products are known to be a rich source of lead compounds for Drug discovery,including against infectious diseases caused by microbes(viruses,bacteria and fungi).In this review article,we conducted a literature survey aimed at identifying natural products with inhibitory concentrations against the coronaviruses or their target proteins,which lie below 10μM.This led to the identification of 42 compounds belonging to the alkaloid,flavonoid,terpenoid,phenolic,xanthone and saponin classes.The cut off concentration of 10μM was to limit the study to the most potent chemical entities,which could be developed into therapies against the viral infection to make a contribution towards limiting the spread of the disease.

关键词： Antivirals Drug discovery Inhibitors Lead compounds Natural products SARS-CoV-2

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PPARγLBD and its ligand specificity reveal a selection of potential partial agonist:Molecular dynamics based T2D Drug discovery initiative

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BIOCELL 2021年第4期45卷 953-961页

作者： BIDYUT MALLICK ASHISH RANJAN SHARMA MANOJIT BHATTACHARYA SANG-SOO LEE CHIRANJIB CHAKRABORTY Department of Applied Science Galgotias College of Engineering and TechnologyKnowledge Park-IIGreater Noida201306India Institute for Skeletal Aging&Orthopedic Surgery Hallym University-Chuncheon Sacred Heart HospitalChuncheon-si24252Korea Department of Zoology Fakir Mohan UniversityVyasa ViharBalasore756020India Department of Biotechnology School of Life Science and BiotechnologyAdamas UniversityKolkata700126India

PPARγis a peroxisome proliferator-activated receptor(PPAR)family protein and is a target for type 2 diabetes(T2D).In this paper,we have performed a molecular docking analysis between ligand molecules(CID9816265,CID11608015,CID20251380,CID20251343,CID20556263,CID624491,CID42609928,and CID86287562)and PPARγto determine the ligand specificity.It also helps to understand the ligand-binding domain(LBD)activity of PPARγduring the binding of the ligand.Further,a molecular dynamics simulation study was performed to determine the ligand biding stability in the PPARγLBD.Its ligand specificity informed us about the potentiality of selecting a partial agonist.The study also shows the binding conformation of Ceramicine B having hydrogen bonding affinity with a tricyclic polar head and stabilized theβ-sheet region.On the other hand,the tricyclic polar head of nimbolide also formed hydrogen bonding(Ser342),but it shows a lesser degree of stabilization in theβ-sheet region.It shows the binding conformation of partial agonist(PPARγ)in the Pocket-II of PPARγLBD,which has a significant role in stabilizing theβ-sheet region.It might help to regulate ERK/Cdk5 mediated phosphorylation of Ser245.The study helps us understand the valid pose of a set of ligands confirmation and target protein conformation using docking and molecular dynamics study.This in silico study will also help to initiate a Drug discovery process of T2D.

关键词： PPARγ Partial agonist Molecular simulation T2D Drug discovery

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The application of sulfur-containing peptides in Drug discovery

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Chinese Chemical Letters 2018年第7期29卷 1079-1087页

作者： Jiaoyan Zhao Xuefeng Jiang Shanghai Key Laboratory of Green Chemistry and Chemical Process School of Chemistry and Molecular EngineeringEast China Normal University State Key Laboratory of Elemento-organic Chemistry Nankai University

In recent decades, peptides as potential drugs were more and more explored with the development of non-oral medicine. There into, sulfur-containing peptide is one of the most popular aspects in peptide drugs due to the introduction of sulfur atoms leading unique properties.The purpose of the present review is to focus on the discovery of various sulfur-containing peptides with particular emphasis on their pharmacological mechanisms. This review is organized according to the structures of the sulfurcontaining peptides.

关键词： Peptides Disulfide Thioether Thiazole Drug discovery

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Current status and challenges in Drug discovery against the globally important zoonotic cryptosporidiosis

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Animal Diseases 2021年第1期1卷 48-57页

作者： Guan Zhu Jigang Yin Gregory D.Cuny Key Laboratory of Zoonosis Research Ministry of Education/Institute of Zoonosis/and College of Veterinary MedicineJilin UniversityChangchunChina Department of Pharmacological&Pharmaceutical Sciences College of PharmacyUniversity of HoustonHoustonTXUSA.

The zoonotic cryptosporidiosis is globally distributed,one of the major diarrheal diseases in humans and animals.Cryptosporidium oocysts are also one of the major environmental concerns,making it a pathogen that fits well into the One Health concept.Despite its importance,fully effective drugs are not yet available.Anti-cryptosporidial Drug discovery has historically faced many unusual challenges attributed to unique parasite biology and technical burdens.While significant progresses have been made recently,anti-cryptosporidial Drug discovery still faces a major obstacle:identification of systemic drugs that can be absorbed by patients experiencing watery diarrhea and effectively pass through electron-dense(ED)band at the parasite-host cell interface to act on the epicellular parasite.There may be a need to develop an in vitro assay to effectively screen hits/leads for their capability to cross ED band.In the meantime,non-systemic drugs with strong mucoadhesive properties for extended gastrointestinal exposure may represent another direction in developing anti-cryptosporidial therapeutics.For developing both systemic and non-systemic drugs,a non-ruminant animal model exhibiting diarrheal symptoms suitable for routine evaluation of drug absorption and anti-cryptosporidial efficacy may be very helpful.

关键词： Cryptosporidium Cryptosporidiosis Drug discovery Watery diarrhea Electron-dense band drug delivery

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Strategies for translating proteomics discoveries into Drug discovery for dementia

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Neural Regeneration Research 2024年第1期19卷 132-139页

作者： Aditi Halder Eleanor Drummond School of Medical Sciences and Brain&Mind Center University of SydneyNSWSydneyAustralia Department of Aged Care Prince of Wales HospitalSydneyNSWAustralia

Tauopathies,diseases characterized by neuropathological aggregates of tau including Alzheimer's disease and subtypes of fro ntotemporal dementia,make up the vast majority of dementia cases.Although there have been recent developments in tauopathy biomarkers and disease-modifying treatments,ongoing progress is required to ensure these are effective,economical,and accessible for the globally ageing population.As such,continued identification of new potential drug targets and biomarkers is critical."Big data"studies,such as proteomics,can generate information on thousands of possible new targets for dementia diagnostics and therapeutics,but currently remain underutilized due to the lack of a clear process by which targets are selected for future drug development.In this review,we discuss current tauopathy biomarkers and therapeutics,and highlight areas in need of improvement,particularly when addressing the needs of frail,comorbid and cognitively impaired populations.We highlight biomarkers which have been developed from proteomic data,and outline possible future directions in this field.We propose new criteria by which potential targets in proteomics studies can be objectively ranked as favorable for drug development,and demonstrate its application to our group's recent tau interactome dataset as an example.

关键词： Alzheimer's disease biomarkers drug development Drug discovery druggability frontotemporal dementia interactome proteomics tau tauopathies therapeutics

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