Kernelized fourth quantification theory for mineral target prediction

This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantifica- tion theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal with the problem of mineral prediction without defining a training area. In mineral target prediction, the pre-defined statistical cells, such as grid cells, can be implicitly transformed using kernel techniques from input space to a high-dimensional feature space, where the nonlinearly separable clusters in the input space are ex- pected to be linearly separable. Then, the transformed cells in the feature space are mapped by the fourth quan- tifieation theory onto a low-dimensional scaling space, where the sealed cells can be visually clustered according to their spatial locations. At the same time, those cells, which are far away from the cluster center of the majority of the sealed cells, are recognized as anomaly cells. Finally, whether the anomaly cells can serve as mineral potential target cells can be tested by spatially superimposing the known mineral occurrences onto the anomaly ceils. A case study shows that nearly all the known mineral occurrences spatially coincide with the anomaly cells with nearly the smallest scaled coordinates in one-dimensional sealing space. In the case study, the mineral target cells delineated by the new model are similar to those predicted by the well-known WofE model.

Characterization of blueberry exosome-like nanoparticles and miRNAs with potential cross-kingdom human gene targets

Edible plant derived exosome-like nanoparticles(ELNs)have been shown to have multiple nutraceutical functions.However,the diversity of plant materials makes the plant derived ELN study challenging.More efforts are still needed to explore the feasible isolation methods of edible plant derived ELNs and the possible roles of food-derived ELNs in improving human health.In this study,a size exclusion chromatography based method was compared with the traditional ultracentrifugation method to isolate blueberry derived ELNs(B-ELNs),and the miRNA profile of B-ELNs was analyzed by high-throughput sequencing.A total of 36 miRNAs were found to be enriched in B-ELNs compared with berry tissue,and their potential cross-kingdom human gene targets were further predicted.Results showed that size exclusion chromatography was effective for B-ELN isolation.The most abundant miRNAs in B-ELNs mainly belonged to the miR166 family and miR396 family.Target gene prediction indicated that B-ELNs could potentially regulate pathways related to the human digestive system,immune system and infectious diseases.

Prediction of Potential Drug Activity and Therapeutic Targets of a Natural Compound Niga-ichigoside F1 Based on Network Pharmacology and Molecular Docking

Objective:To study the drug activity and therapeutic targets of Niga-ichigoside F1 predicted based on network pharmacology and molecular docking.Methods:Download the 2D and 3D structures of Niga-ichigoside F1 from the PubChem database for target prediction and molecular docking,respectively.Target information was predicted by PharmMapper and swiss ADME databases,target gene names were extracted and rechecked by Uniprot database,and disease information corresponding to target was queried by TTD database.The enrichment analysis of GO and KEGG signal pathway was conducted by Metascape database.AutoDuck Vina was used for molecular docking of Niga-ichigoside F1 3D structure with key proteins of related diseases and common pathways.Finally,the conformation of molecular docking was visualized by PyMOL.Results:A total of 34 targets and 69 related disease information were obtained from the database screening.The targets with high degree of acquisition of the association network between target and disease were AR,F2,VDR,PDE10A,mTOR,and NR3C2,etc..Diseases with a high degree of relief were solid tumour,breast cancer, acute myeloid leukemia, hypertension, and thrombocytopenia,etc..The items with significance in GO analysis included positive regulation of transferase activity,protein autophosphorylation,negative regulation of cGMP-mediated signaling,intracellular receptor signaling pathway,regulation of cellular response to stress,blood vessel development,reactive oxygen species metabolic process,negative regulation of immune response,regulation of transcription from RNA polymerase Ⅱ promoter in response to stress,and nucleobase-containing small molecule metabolic process,etc..The items with significance in KEGG enrichment analysis(P<0.01) included Pathways in cancer,Purine metabolism,Focal adhesion,MAPK signaling pathway,GnRH signaling pathway,AGE-RAGE signaling pathway in diabetic complications,Ras signaling pathway,Leukocyte transendothelial migration and Platelet activation,etc..Molecular docking suggested that the target of Niga-ichigoside F1 had good binding ability with related diseases and key proteins of common pathways.Conclusion:According to the results of network pharmacology and molecular docking,Niga-ichigoside F1 has rich drug activity and may act on a variety of diseases.After comprehensive analysis, we proposed for the first time the high correlation between Niga-ichigoside F1 and cancer,as well as the possible association with acute myeloid leukemia and hypertension.It has the characteristics of multi-target and multi-pathway,which is worthy of further research,development and utilization.

MCDB: A comprehensive curated mitotic catastrophe database for retrieval, protein sequence alignment, and target prediction

Mitotic catastrophe(MC)is a form of programmed cell death induced by mitotic process disorders,which is very important in tumor prevention,development,and drug resistance.Because rapidly increased data for MC is vigorously promoting the tumor-related biomedical and clinical study,it is urgent for us to develop a professional and comprehensive database to curate MC-related data.Mitotic Catastrophe Database(MCDB)consists of 1214 genes/proteins and 5014 compounds collected and organized from more than 8000 research articles.Also,MCDB defines the confidence level,classification criteria,and uniform naming rules for MC-related data,which greatly improves data reliability and retrieval convenience.Moreover,MCDB develops protein sequence alignment and target prediction functions.The former can be used to predict new potential MC-related genes and proteins,and the latter can facilitate the identification of potential target proteins of unknown MC-related compounds.In short,MCDB is such a proprietary,standard,and comprehensive database for MC-relate data that will facilitate the exploration of MC from chemists to biologists in the fields of medicinal chemistry,molecular biology,bioinformatics,oncology and so on.The MCDB is distributed on http://www.combio-lezhang.online/MCDB/indexhtml/.

Bufotenine and its derivatives:synthesis,analgesic effects identification and computational target prediction

Natural product bufotenine(5)which could be isolated from Venenum Bufonis,has been widely used as a tool in central nervous system(CNS)studies.We present here its quaternary ammonium salt(6)which was synthesized with high yields using 5-benzyloxyindole as raw materials,and we firstly discover its analgesic effects in vivo.The analgesic evaluation showed that compounds 5 and 6 had stronger effects on the behavior of formalin induced pain in mice.Moreover,the combination of compound 6 and morphine has a synergistic effect.We intended to explain the molecular mechanism of this effect.Therefore,36 analgesic-related targets(including 15 G protein-coupled receptors,6 enzymes,13 ion channels,and 2 others)were systemically evaluated using reverse docking.The results indicate that bufotenine and its derivatives are closely related to acetyl cholinesterase(AChE)orα_(4)β_(2) nicotinic acetylcholine receptor(nAChR).This study provides practitioners a new insight of analgesic effects.

One Decade of Development and Evolution of MicroRNA Target Prediction Algorithms

Nearly two decades have passed since the publication of the first study reporting the discovery of microRNAs （miRNAs）. The key role of miRNAs in post-transcriptional gene regulation led to the performance of an increasing number of studies focusing on origins, mech- anisms of action and functionality of miRNAs. In order to associate each miRNA to a specific functionality it is essential to unveil the rules that govern miRNA action. Despite the fact that there has been significant improvement exposing structural characteristics of the miRNA-mRNA interaction, the entire physical mechanism is not yet fully understood. In this respect, the development of computa- tional algorithms for miRNA target prediction becomes increasingly important. This manuscript summarizes the research done on miRNA target prediction. It describes the experimental data currently available and used in the field and presents three lines of compu tational approaches for target prediction. Finally, the authors put forward a number of considerations regarding current challenges and future directions.

ENSO Predictions in an Intermediate Coupled Model Influenced by Removing Initial Condition Errors in Sensitive Areas： A Target Observation Perspective

Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas（socalled ＂sensitive areas＂）. And yet, few studies have quantified improvements in prediction skill in the context of an optimal observing system. In this study, the impact on prediction skill is explored using an intermediate coupled model in which errors in initial conditions formed to make ENSO predictions are removed in certain areas. Based on ideal observing system simulation experiments, the importance of various observational networks on improvement of El Ni n？o prediction skill is examined. The results indicate that the initial states in the central and eastern equatorial Pacific are important to improve El Ni n？o prediction skill effectively. When removing the initial condition errors in the central equatorial Pacific, ENSO prediction errors can be reduced by 25%. Furthermore, combinations of various subregions are considered to demonstrate the efficiency on ENSO prediction skill. Particularly, seasonally varying observational networks are suggested to improve the prediction skill more effectively. For example, in addition to observing in the central equatorial Pacific and its north throughout the year,increasing observations in the eastern equatorial Pacific during April to October is crucially important, which can improve the prediction accuracy by 62%. These results also demonstrate the effectiveness of the conditional nonlinear optimal perturbation approach on detecting sensitive areas for target observations.

Exploring the mechanism of action of herb pair Pinellia Ternata-Magnolia Officinalis in the treatment of liver cancer based on network pharmacology and molecular docking

Background:Explore the anti-tumor mechanism of herb pair Pinellia ternate-Magnolia officinalis(BX-HP)in liver cancer through network pharmacology using molecular docking methods.Method:The active ingredients and corresponding targets of the herb pair Pinellia ternate-Magnolia officinalis were obtained from the HERB database.The relevant targets for liver cancer were obtained from GeneCards,DisGeNET,TTD,and Drugbank databases.Obtain common targets between herb pair Pinellia ternate-Magnolia officinalis and liver cancer through the Bioinformatics platform,establish a PPI network diagram using STRING software,and perform GO functional enrichment and KEGG pathway enrichment analysis on the DAVID platform.AutoDockTools 1.5.7 software and molecular dynamics simulation analysis are used to evaluate the binding of components to target proteins.HERB database,SwissTargetPrediction database,SwissADME database,UniProt database,GeneCards database,TTD database,DRUGBANK database,DisGeNET database,String,DAVID.Bioinformatics platform,PDB database,PubChem and TCMSP database.Result:A total of 22 active ingredients with a Probability>0.1 targets in Magnolia officinalis were screened,26 active ingredients with a Probability>0.1 targets in Pinellia ternata,ten vital active ingredients,corresponding to 979 and 803 targets with a Probability>0.1 targets,2536 liver cancer-related targets,and 279 targets in the herb pair Pinellia ternata-Magnolia officinalis.The GO functional enrichment analysis resulted in 1297 entries,namely 971 biological process entries,118 cell localization entries,and 208 molecular function entries.Three signaling pathways were annotated through the KEGG pathway.Based on molecular docking,ten vital active ingredients and five target proteins were validated to exhibit an excellent binding affinity.The above data indicates that combining the herb pair Pinellia ternata-Magnolia officinalis may treat liver cancer through specific targets and signaling pathways.Conclusion:Herb pair Pinellia ternata-Magnolia officinalis has a synergistic effect on treating liver cancer through multicomponent,multitarget,and multi-pathway approaches.This study provides a sufficient theoretical basis for subsequent research.

Potential targets and mechanism of Xingxiao Pill for the treatment of lung cancer were analyzed based on network pharmacology and molecular docking

Objective:To analyze the potential targets and mechanism of Xingxiao Pill for the treatment of lung cancer based on network pharmacology and molecular docking,providing reference for the research and clinical development of Xingxiao Pill.Method:The main chemical constituents and their targets of Xingxiao Pill was obtained through BATMAN-TCM database.Effective compounds were screened based on SwissADME and their targets were predicted by SwissTargetPrediction.Main lung cancer targets were obtained and integrated through GeneCards,OMIM(OMIM-Gene-Map-Retrieval),TTD and DRUGBANK databases.The intersection targets of Xingxiao Pill for lung cancer were obtained by Venn.The String platform was used to obtain the intersection targets.The core targets of Xingxiao Pill for lung cancer were screened by BisoGenet3.0.The Metasacpe database was used to analyze the biological processes and pathways involved in intersection targets.Cytoscape3.7.2 software was used to construct the"active ingredients of Xingxiao Pill-targets-pathways"network.Finally,Autodock was used for molecular docking verification.Results:The core active components of Xingxiao Pill for the treatment of lung cancer were morin,testosterone,17-Beta-Estradiol,alphaEstradiol,muscone,commiferin,commisterone,octyl acetate,etc.The primary pathways mainly included PI3K/Akt,MTOR,MAPK signaling pathway and MicroRNAs in cancer,etc.It has been proved that the combination of testosterone and estradiol with AKT1,SIRT7 and MDM2 was stable and could be used as reference.Conclusion:This study preliminarily revealed the mechanism of Xingxiao Pill on treating lung cancer with multiple components,targets and pathways,providing some ideas and references for clinical application and basic research in the future.

Identification of microRNA-21 as a valuable diagnostic marker of oral squamous cell carcinoma and potential target

Objective The aim of the study was to summarize the diagnostic value of miR-21 as a biomarker in oral squamous cell carcinoma(OSCC)using a review of the literature and data from the cancer genome atlas(TCGA)database.Methods Data from TCGA database was sorted and analyzed by bioinformatics to determine the expression level of miR-21 in OSCC.Further,we searched for relevant articles in Embase,PubMed/Medline,Scopus,and Web of Science published before March 2021,extracted the data,and conducted quality assessment.The bivariate meta-analysis model with Stata 16.0 was used to analyze the diagnostic value of miR-21 for OSCC.Results A total of 304 related articles were identified,and seven were selected for meta-analysis.The diagnostic results after analysis were as follows:sensitivity 0.76[95%confidence interval(CI),0.57-0.88];specificity 0.77(95%CI,0.58-0.89);positive likelihood ratio 3.34(95%CI,1.58-7.08);negative likelihood ratio 0.31(95%CI,0.15-0.63);diagnostic odds ratio 10.75(95%CI,2.85-40.51);and area under the curve 0.83(95%CI,0.80-0.86).The Deeks’funnel chart showed that there was no potential bias(P=0.54).Prediction analysis of the potential target genes of miR-21 was performed via the biological website,and DAVID was used to cross target genes for gene ontology(GO)annotation function analysis.Conclusion The results showed that miR-21-3p and miR-21-5p were significantly more highly expressed in OSCC tissues than in normal tissues(P<0.05),and the results of the meta-analysis indicated that they could be used as potential biomarkers in the diagnosis of OSCC.In addition,58 potential target genes of miR-21 were significantly enriched in 28 GO annotation functional pathways,which provided a biological basis for further clinical diagnostic value research.

SPATIAL TRAJECTORY PREDICTION OF VISUAL SERVOING

Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.

Dynamic Expression of MicroRNA-127 During Porcine Prenatal and Postnatal Skeletal Muscle Development

MicroRNAs （miRNAs）, evolutionarily conserved non-coding RNAs in length 21-24 bp, play a critical role in skeletal muscle development. In this study, to explore the function of mircoRNA-127 in porcine skeletal muscle development, eight tissue samples from adult pigs and longissimus muscle samples at 26 developmental stages were collected from Tongcheng and Landrace pigs. The spatial-temporal expression proifles of miRNA-127 were carried out using step-loop quantitative real-time PCR （stem-loop RT-PCR）. To explore the molecular functions of miRNA-127, we predicted its target genes and performed functional annotation using bioinformatics methods. Results suggested that miRNA-127 was abundantly expressed in heart, ovary, uterus and spleen tissues and was weakly expressed in liver, lung, kidney and small intestine in both Tongcheng and Landrace pigs. And miRNA-127 showed signiifcant expression differences in heart, ovary, spleen and uterus tissues between these two breeds. miRNA-127 basically kept at a relatively stable high level in middle and later embryonic stages and a low expression level in early embryonic stages and postnatal stages, but the expression levels of miRNA-127 were higher in Tongcheng pigs than in Landrace at most developmental stages. miRNA-127 potentially regulated 240 candidate genes. Results of Gene Ontology and KEGG pathway analysis indicated that these genes could be involved in many molecular functions and mechanisms, such as regulation of the force of heart contraction, regulation of transcription, regulation of T cell differentiation, MAPK signaling pathway and GnRH signaling pathway. Many signiifcantly enriched GO terms and KEGG pathways were related to skeletal muscle development. This study will be helpful to understand the biological function for miRNA-127 and identify candidate gene associated with meat production traits in pigs.

Computational Prediction of Rice (Oryza sativa) miRNA Targets

Bioinformatic approaches have complemented experimental efforts to inventorize plant miRNA targets. We carried out global computational analysis of rice （Oryza sativa） transcriptome to generate a comprehensive list of putative miRNA targets. Our predictions （684 unique transcripts） showed that rice miRNAs mediate regulation of diverse functions including transcription （41%）, catalysis （28%）, binding （18%）, and transporter activity （11%）. Among the predicted targets, 61.7% hits were in coding regions and nearly 72% targets had a solitary miRNA hit. The study predicted more than 70 novel targets of 34 miRNAs putatively regulating functions like stress-response, catalysis, and binding. It was observed that more than half （55%） of the targets were conserved between O. sativa indica and O. sativa japonica. Members of 31 miRNA families were found to possess conserved targets between rice and at least one of other grass family members. About 44% of the unique targets were common between two dissimilar miRNA prediction algorithms. Such an extent of cross-species conservation and algorithmic consensus confers confidence in the list of rice miRNA targets predicted in this study.

Bioinformatic Analysis of Functional Characteristics of miR172 Family in Tomato

MicroRNAs, a class of endogenous non-coding small RNAs about 21 nucleotides in length, play pivotal roles in plant physiological and biochemical processes. Tomato is important economic crop throughout the world. Recently, involvement of miRNAs in tomato has received significant attention. MiR172 is one of the conserved miRNAs in tomato. Investigation into the roles and the target genes of this small RNA molecular in Arabidopsis illustrated that miR172 functions in regulating the transitions between developmental stages and in specifying floral organ identify. Herein, we combined bioinformatics and molecular biology approaches to profile the functional characteristics of miR172 in tomato. The results of target prediction showed that AP2-like ethylene-responsive transcription factors were major targets of miR172, analysis of upstream sequence indicated the presence of stress-related cis-elements in its promoter regions, and further analysis of qRT-PCR confirmed that miR172 participated in various stress responses. Our research provided a paradigm for further in-depth investigation of the functional characteristics of miRNAs in tomato.

Mechanism of Magnoliae Flos and Xanthii Fructus herb pair in treatment of allergic rhinitis based on network pharmacology

Objective: To explore the molecular mechanism of Magnoliae Flos and Xanthii Fructus herb pair for allergic rhinitis based on network pharmacology. Methods: From the Traditional Chinese Medicine Systems Pharmacology database, Uniprot database, and Gene Cards database, the relevant chemical constituents information, pharmacokinetic information and hub target of allergic rhinitis were obtained. The protein-protein interaction network was constructed by STRING online database, analyzed and showed by the Cytoscape software. The screened target information was analyzed by the Metascape database for Gene Ontology biological function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Results: Main components of Magnoliae Flos and Xanthii Fructus herb pair, such as aloe-emodin, stigmasterol, beta-sitosterol and Yangambin, depend on the interaction of Nitric Oxide Synthase 3, Tumor Necrosis Factor, Caspase-3 and other functions involve G protein-coupled (amine) receptor activity, RNA polymerase II basic transcription factor binding, protease binding, heme binding, and integrin binding;can regulate calcium signal pathway, serotonergic synapse, Kyoto Encyclopedia of Genes and Genomes signal pathway, tryptophan inflammatory mediator regulation pathway, estrogen signal pathway alone or in combination, and play a role in the treatment of allergic rhinitis. Conclusion: Magnoliae Flos combined with Xanthii Fructus can regulate biomolecular network in multiple targets and pathways to treat allergic rhinitis.

Network pharmacology-based approach to investigate the mechanisms of Guizhi Fuling pill in the treatment of atherosclerosis

Objective:To investigate the mechanism of action of Guizhi Fuling pill in the treatment of atherosclerosis with network pharmacology.Methods:The active components of Guizhi Fuling pill were screened by specific ADME features on Traditional Chinese Medicine Systems Pharmacology platform,and their targets were obtained.Targets of atherosclerosis were extracted and screened from GeneCards database,OMIM database,DrugBank database and DisGeNET database,and the intersection of component targets and disease targets were regarded as potential targets.The protein-protein interaction network of potential targets was constructed by STRING database and Cytoscape 3.7.2.GO analysis and KEGG pathway analysis of potential targets were performed by Metascape platform.The“drugs-componenst-targets-pathways”network was constructed by Cytoscape 3.7.2.SwissDock was used for molecular docking of active components and key targets.Results:The main components of Guizhi Fuling pill in the treatment of atherosclerosis were quercetin,beta-sitosterol,kaempfero,hederagenin,baicalein,etc.The key targets mainly included PGST2,RELA,AKT1,etc.Molecular docking analysis showed that the binding energy of the main active components to the core target was less than-7 kcal/mol.The associated pathways mainly included fluid shear stress and atherosclerosis,PI3K-Akt signaling pathway and AGE-RAGE signaling pathway.Conclusion:Through this study,we initially revealed the possible mechanism of Guizhi Fuling pill in treating atherosclerosis through anti-inflammatory,reducing blood lipids,and regulating endothelial function.

Theory and mechanism analysis of Wuji Pill in Anti-lung Cancer:A study based on network pharmacology and molecular docking technology

Background:To explore the effective components and mechanism of Classic ancient prescription Wuji pill on lung cancer(LC)with the help of network pharmacology and molecular docking technology.Methods:TCMSP database,Chinese Pharmacopoeia(2020 Edition)and related literature were searched to identify the main chemical composition and targets of constituent drugs in Wuji pill,including Houpo(Magnoliae Officinalis Cortex),Huangqin(Scutellariae Radix),Badou(Crotonis Fructus),Huanglian(Coptidis Rhizoma)and Renshen(Ginseng Radix et Rhizoma).Meanwhile,Genecards,OMIM,TTD,Drugbank and PharmGkb databases were used to obtain the main targets of LC.The"chemical compound-target"network was constructed by using Cytoscape 3.8.2 software with the disease drug intersection gene as the research target.The PPI network was constructed by using the string database for protein interaction analysis,and the core target genes were sorted out.The Gene ontology go function enrichment analysis and KEGG signal pathway enrichment analysis were carried out based on the ClusterProfiler of R software.Finally,the Autodock Vina software was used to conduct molecular docking between the core target with high value and the key components.Results:A total of 60 active components,190 corresponding targets and 2516 GO and 163 KEGG pathways of Wuji pill were screened out,including 179 potential targets of LC.The core targets were ESR1,CDKN1A,TP53,NR3C1,MAPK1,AKT1,MAPK8,JUN,RELA,the core components were quercetin,kaempferol,β-sitosterol,stigmasterol,tetrahedron,protoopioid,etc,and the core pathways were PI3K-Akt,MAPK,IL-17,etc.Conclusion:This study preliminarily revealed the mechanism of action of Wuji pill on multi component-multi target-multi pathway of LC,which provided reference for the further clinical development and research of Wuji pill.

A Correlation Tracking Algorithm Based on Template Partition Motion Estimation

A correlation tracking algorithm based on template partition motion estimation proposed for improving real time performance of the conventional correlation matching algorithms. The target trajectory fitted using the least square with equal space in whole interval and the target prediction point is found out. According to the requirements of block motion estimation(BME) algorithm,the template divided into some macro blocks. The searching process is conducted by using diamond search algorithm around the prediction point and the optimal motion vector of each block is calculated. A point corresponding to the motion vector with the best matching is taken as a rough matching point of the template. The relation of relative position between the block with matching point and the searching area determined to decide whether to conduct precise matching search or to construct a new search area in the gradient direction. The target tracking experiment results show that over 70% time cost can be reduced caompared with the conventional correlation matching algorithm based on full search method.

Prediction of underwater target strength

A model as well as its numerical method to calculate target strength of rigid body using Lighthill's acoustic analogy approach which developed from the propeller aircraft sound field study have been presented. The cases of ellipsoid target has been used to demonstrate the approach. The comparison of the numerical results with that of analytical formulation provides a satisfactory check for the validity of the approach. Some reasonable results have been discussed. The advantage of the present model is that it is suitable for any arbitrarily shaped rigid body moving with small Mach number.

D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19

A highly effective medicine is urgently required to cure coronavirus disease 2019(COVID-19).For the purpose,we developed a molecular docking based webserver,namely D3 Targets-2019-nCoV,with two functions,one is for predicting drug targets for drugs or active compounds observed from clinic or in vitro/in vivo studies,the other is for identifying lead compounds against potential drug targets via docking.This server has its unique features,(1)the potential target proteins and their different conformations involving in the whole process from virus infection to replication and release were included as many as possible;(2)all the potential ligand-binding sites with volume larger than 200 A^3 on a protein structure were identified for docking;(3)correlation information among some conformations or binding sites was annotated;(4)it is easy to be updated,and is accessible freely to public(https://www.d3 pharma.com/D3 Targets-2019-nCoV/index.php).Currently,the webserver contains 42 proteins[20 severe acute respiratory syndrome-related coronavirus 2(SARS-CoV-2)encoded proteins and 22 human proteins involved in virus infection,replication and release]with 69 different conformations/structures and 557 potential ligand-binding pockets in total.With 6 examples,we demonstrated that the webserver should be useful to medicinal chemists,pharmacologists and clinicians for efficiently discovering or developing effective drugs against the SARS-CoV-2 to cure COVID-19.