# CMNPD Docs # Tutorial ## Quick Search #### Search by CMNPD ID, compound name, organism name, and target name. You can input CMNPD ID (compound ID, organism ID, target ID or document ID), compound name, organism name, or target name in the search bar for quick search. The bar will provide some suitable suggestions as you type. You can do a quick search at any time because the search bar appears on all pages. ![Keyword search](/files/-MDyP5AQvolPfWOJzTnL) ## Advanced Search Use the **Query Builder** to create or modify queries. Specify the domain you want to query, you can search by structure, compound representations, physicochemical properties, ADMET prediction, resources, bioactivities and bibliography separately or in combination. ### 1 Learn query parameters Before using Query Builder, you should understand the meaning and threshold of each parameter. The [**FAQ-Parameter Questions**](https://docs.cmnpd.org/frequently-asked-questions/parameter-questions) section will provide you with some reference information. You can also learn more by browsing the database. ### 2 Structure search You can draw a structure by [**Marvin JS sketcher**](https://chemaxon.com/products/marvin-js) and then do an exact search, substructure search or similarity search. In addition, you can upload a molecular file or paste SMILES to import a chemical structure. ![Click to open Marvin JS sketcher](/files/-M9WnzqwYH8Je52RTMeW) ![Draw a structure with Marvin JS sketcher](/files/-MDyRSqc4HJPl84IX58p) ![Select exact search, substructure search or similarity search](/files/-M9WpAnRucc-XQ2bRxAy) ### 3 Text search You can select several query conditions to do a text search. Some of them have both text entry and browse functions so that you have the choice of typing in a search term or selecting from the index. ![Text Search](/files/-M9Hpf5Iv1lQJc-t4-rx) ![Search term index](/files/-MDyS8WP_TRvGVWmC_lT) ### 4 Combined search You can search by combining a drawn structure with another parameter or set of parameters. ![Combine structure search and text search](/files/-M9WqJH2li1OAdVTbbm8) ### 5 Boolean operation All query conditions are connected via the Boolean operator **AND** (**OR** and **NOT** are optional). Drag and drop one condition onto another to group them together. The internal Boolean operations of the grouped conditions will be executed first. Using Boolean operators and conditions grouping effectively will greatly improve your search results, by making the results more specific. Understanding the concept of [**Set (mathematics)**](https://en.wikipedia.org/wiki/Set_\(mathematics\)) will help you make better use of our Query Builder. Here we will use an example to illustrate how to obtain specific search results with Boolean operators. e.g. If you want to search for compounds produced by organisms other than bacteria and fungi and whose molecular weight ≤ 500, you can use the following query settings: ![Search with Boolean operators](/files/-M9IIonNro_xPEAxawQj) In Boolean operations, CMNPD is regarded as the universal set U, and different query conditions are considered as subsets A, B, C, etc. Therefore, this search can be represented by the following Venn diagram: ![Venn diagram of the Boolean operations](/files/-M9IQOSoaFxcXit3IW3l) * Subset A (circle) represents bacterial compounds * Subset B (circle) represents fungal compounds * Subset C (rectangle) represents compounds with molecular weight ≤ 500 The logic of Boolean operations is as follows: **Step 1. Boolean operation OR.** As you group the query conditions A and B together, the system preferentially calculates the union of A and B. $$ A\cup B $$ **Step 2. Boolean operation NOT.** Next, the calculation is performed in order from top to bottom to get the complement of (A∪B) in U. $$ ∁\_U(A\cup B) $$ **Step 3. Boolean operation AND.** Finally the system calculates the intersection of C and the above subset. $$ C\cap\[∁\_U(A\cup B)] $$ ## Browse CMNPD ### Full list You can quickly view the list of all compounds, documents, targets and organisms in CMNPD through the **Browse** button on the toolbar. ### Details page There are four types of report card pages that can provide you with detailed information about each compound, document, organism and target. You can enter relevant pages through internal links in the full list page, search results page, and another report card page. ## Data Visualization #### A visual overview of CMNPD and a starting point for exploring the database. In order to show in a better way what is inside CMNPD we have created some data visualizations. You can see them by **Visualization** button on the toolbar. There will be a short instruction above each chart to guide you how to use the visualization tools. ## Network A visual overview of the topological relationship between organisms, compounds and targets. Select a master node and then click the submit button to generate a network. Click on a node to explore the details. ![Network](/files/-MDyUcie1Hwl8q0pDWFP) ## Downloads #### Bulk download CMNPD data is available for bulk download in the [**Downloads**](https://docs.cmnpd.org/downloads) section. #### Customized download You can customize the compound download list through the advanced search and manual selection. ![Customize download list](/files/-MDyWGER5dCJkZUzBjwK) ## Deposit System #### Register A deposit account is required in order to submit data to CMNPD. You must agree to the [**Submission Policy**](https://docs.cmnpd.org/terms-and-conditions#submission-policy) when you create an account. #### Submit data After logging in, you will see the submission interface. In the upper left corner, you can choose to submit new compounds, new data for existing compounds or corrections. The submission history can be viewed by clicking **Your deposit**. ![Data deposition](/files/-MDyWfqdt3l8d06TrmqJ) # About ## Introduction CMNPD is a manually curated open access knowledge base dedicated to marine natural products research. The data is extracted from published scientific literature and authoritative databases. CMNPD provides information on chemical entities with various physicochemical and pharmacokinetic properties, standardized biological activity data, systematic taxonomy and geographical distribution of source organisms, and detailed literature citations. It is an integrated platform for structure dereplication of (marine) natural products, discovery of lead compounds, data mining of structure-activity relationships and investigation of chemical ecology. We are committed to providing a freely accessible database for not only professional marine natural product researchers but also the broad scientific community to facilitate drug discovery from the ocean. ## Content * Compound name (trivial name and systematic name) * Chemical structure (2D and 3D) * Computed descriptors (SMILES, InChI, InChI Key) * Calculated properties (physicochemical properties and ADMET prediction) * Structural classification based on ClassyFire * Systematic taxonomy of source organisms (kingdom, phylum, class, order, family, genus and species) * Sampling location (geographic region and coordinates) * Biological activities (pharmacological effects, targets, binding constants, etc.) * Spectral Information (IR, MS, NMR, UV/VIS, etc.) * Document citations (scientific literature and patent) * External links to ChEMBL and PubChem ## Statistics | Data collection | Live count | Description | | --------------- | ---------- | ----------------------------------------------- | | Compounds | 31 561 | Unique chemical structures | | Organisms | 3 354 | Source organisms by species level | | Targets | 2 652 | Targets classified according to ChEMBL category | | Bioactivities | 72 349 | Biological activity data | | Documents | 128 488 | Scientific literature and patents | ## Affiliation This project was established by [State Key Laboratory of Natural and Biomimetic Drugs](http://sklnbd.bjmu.edu.cn/English/), [School of Pharmaceutical Sciences](http://sps.bjmu.edu.cn/gbenglish/index.htm), [Peking University](http://english.pku.edu.cn/). ## Interface Developer Web interface was designed by Chuanyu Lyu. Website development and data visualization were provided by [EHBIO Gene Technology (Beijing) co., LTD.](http://www.ehbio.com/index_en.html) # Downloads {% hint style="info" %} Click the file name to download a dataset. {% endhint %} | File name | File content | File size | | ------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | [CMNPD\_1.0\_2d.sdf.gz](https://www.cmnpd.org/cmnpd/supplement/Downloads/CMNPD_1.0_2d.sdf.gz) | 2D structures of all compounds | \~11MB | | [CMNPD\_1.0\_3d.sdf.gz](https://www.cmnpd.org/cmnpd/supplement/Downloads/CMNPD_1.0_3d.sdf.gz) | 3D conformers of the compounds that meet the [criteria](https://docs.cmnpd.org/frequently-asked-questions/data-questions#what-is-the-3d-conformer) | \~39MB | | [CMNPD\_1.0\_calc\_prop.tsv](https://www.cmnpd.org/cmnpd/supplement/Downloads/CMNPD_1.0_calc_prop.tsv) | Calculated properties | \~14MB | | [CMNPD\_1.0\_act\_br.tsv](https://www.cmnpd.org/cmnpd/supplement/Downloads/CMNPD_1.0_act_br.tsv) | Biological activity data in brief | \~1MB | | [CMNPD\_1.0\_act\_std.tsv](https://www.cmnpd.org/cmnpd/supplement/Downloads/CMNPD_1.0_act_std.tsv) | Standardized experimental data | \~10MB | # Frequently Asked Questions Here you will find frequently asked questions about CMNPD, please use the menu on the left to access the sub-sections. # Data Questions ## How do you process the chemical structures? Skeletal formulae are usually used to represent the skeleton of organic molecules in publications, but some of them are generally not machine friendly. The most common problem is that certain stereochemistry is readable by humans, but cannot be recognized correctly by the computer software. In order to accurately present the stereochemistry in the database, we have performed some data processing for different situations. ### Wavy lines Wavy lines represent either unknown stereochemistry (R/S or E/Z) or a mixture of the two possible stereoisomers at that point. In order to better reflect the chemical space of marine natural products and reduce the redundancy of the database, we determine whether the structure with wavy lines is treated as one entry or multiple entries according to the following rules: ![Wavy lines](/files/-MDrpdtQ1-6JiDeM6Xit) ### Wedge-dash diagrams The chair conformation, Haworth projection and Fischer projection are converted to wedge-dash diagrams. Wedged bonds are used to describe the stereochemistry instead of axial bonds and equatorial bonds. ![Stereochemistry representation conversion](/files/-MDrrkJ446C_JA_M6w-6) ### Tautomers If the author indicates that the compound has tautomerism, each tautomer is treated as a separate entry. ![Tautomerism](/files/-M9P5_XqQs1C6HQXC_Yi) ## What is the 3D Conformer? 3D conformer is a three-dimensional representation of the compound. The 3D structure is not experimentally determined, but a low-energy conformer computed by OpenEye OMEGA. Since a certain number of complicated MNPs contain many undefined stereocenters and/or rotatable bonds, it makes no sense to compute 3D descriptions for all records.Therefore, according to the criterion of [PubChem3D conformer models](https://pubchemdocs.ncbi.nlm.nih.gov/pubchem3d), CMNPD provides a 3D conformer representation for each compound record that satisfies the following conditions: * Not too large (with no more than 50 heavy atoms) * Not too flexible (with no more than 15 rotatable bonds) * Has only a single covalent unit (salt, mixture or polymer keep only the largest fragment in the calculation) * Consists of only supported elements (H, C, N, O, F, Si, P, S, Cl, Br, and I) * Contains only atom types recognized by the MMFF94s force field * Has fewer than six undefined atom or bond stereocenters ## Why do some compounds have the same name? {% hint style="danger" %} All compounds with the same name are marked with "**Homonym**⚠️" in the **Name and Classification** section. {% endhint %} You should use the data for these compounds with caution, because there are many factors that may cause this phenomenon: * Some entries are tautomers * Some entries are homologues * Some entries are analogs * Some entries are enantiomers or diastereomers * Different authors use the same name in their articles to represent completely different substances * Some authors use axial bonds and equatorial bonds with blurred directions instead of wedge bonds to describe stereochemistry, which leads to ambiguity * With the development of structure determination technology, some compounds’ chemical structures have been revised or their absolute configurations have been identified It should be noted that CMNPD only objectively presents the chemical structure depictions of marine natural products based on published literature. We do not guarantee the accuracy of the structure described in the original article, nor will we have any tendency to indicate which structure is more reliable. {% hint style="info" %} Structures that are considered inappropriate or have no absolute configuration will not be treated as erroneous entries in CMNPD unless the reference document is retracted by the publisher. However, a special symbol "†" will be added after the compound name to indicate that these structures have been revised or have more precise stereochemistry in another paper. This feature allows you to track the stereochemical progress of related compounds. {% endhint %} ## What do the abbreviations in biological activity data mean? Brief description of the bicoactivies is mainly extracted from marine natural products reviews published in *Natural Product Reports*. In recent years, the authors have adopted many abbreviations to shorten the length of bioactivity data. Here is a comparison table of some useful abbreviations. | Abbreviation | Full name | | ------------ | ---------------------------------- | | AB | antibacterial | | AF | antifungal | | AI | anti-inflammatory | | AM | antimicrobial | | AM/AB | antimicrobial/antibacterial | | AO | antioxidant | | AV | antiviral | | HTCL | Human Tumour Cell Line | | IA | inactive | | MDR | multidrug resistant | | MIC | minimum inhibitory concentration | | MO | microorganism | | MOA | mechanism of action | | NO | nitrous oxide | | NT | not tested | | Norm. | normal | | SAR | Structure Activity Relationship(s) | | TRP | Transient Receptor Potential | | activ. | Activity | | anal. | analysis | | antifoul. | antifouling | | bact. | bacteria | | calc. | calculation | | compar. | Comparison | | connect. | connectivity | | cytotox. | cytotoxicity/cytotoxic | | degrad. | degradation | | deriv. | derivative | | determ. | Determined | | diffrac. | diffraction | | estab. | established | | expt. | experimental | | hum. | human | | immunomod. | immunomodulatory | | inhib. | inhibitor/inhibition/inhibitory | | insep. | Inseparable | | isol. | isolated | | microb. | microbial, microbe | | mixt. | mixture | | mod. | moderate | | prod. | production | | prop. | proposed | | recept. | receptor | | spec. rot. | specific rotation | ## What is the Assay Type? Standardized experimental data is incorporated from ChEMBL. The following is ChEMBL's description of assay type: > * Binding (B) - Data measuring binding of compound to a molecular target, e.g. Ki, IC50, Kd. > * Functional (F) - Data measuring the biological effect of a compound, e.g. %cell death in a cell line, rat weight. > * ADME (A) - ADME data e.g. t1/2, oral bioavailability. > * Toxicity (T) - Data measuring toxicity of a compound, e.g., cytotoxicity. > * Physicochemical (P) - Assays measuring physicochemical properties of the compounds in the absence of biological material e.g., chemical stability, solubility. > * Unclassified (U) - A small proportion of assays cannot be classified into one of the above categories e.g., ratio of binding vs efficacy. ## What is the Target Type? Targets are classified according to ChEMBL category. This slide shows how ChEMBL defines and classifies targets: ![ChEMBL Target Types](/files/-M9JigRdgkCQ55f_r43S) # General Questions ## How often do you update the data? Certified compound record data is updated annually, but biological activity data is updated regularly, with releases approximately every 3-4 months. ## What is the CMNPD ID? The CMNPD ID is a unique ID that has been assigned to compounds, organisms, targets and documents in CMNPD. It can be used to retrieve a Report Card page for these entities, or to search for them using the keyword search. ## What's the difference between CMNPD document library and MarinLit? [MarinLit](http://pubs.rsc.org/marinlit/) contains comprehensive literature on marine natural products, including new and revised compounds, synthesis, ecology and biological activities. CMNPD collects documents in any field as long as it contains the chemical structure of marine natural products. ## # Parameter Questions ## How are the SMILES, InChI and InChI Key created for CMNPD? These descriptors are calculated using [BIOVIA Pipeline Pilot ](https://www.3dsbiovia.com/products/collaborative-science/biovia-pipeline-pilot/)(version 18.1). ### SMILES The SMILES are calculated using the [Daylight's algorithm](https://www.daylight.com/dayhtml/doc/theory/theory.smiles.html). ### Standard InChI Standard InChI is calculated using the algorithm from IUPAC. The version of InChI used in CMNPD is 1.05. ### InChI Key InChI Key is based on a strong hash (SHA-256 algorithm) of an InChI string. ## How are the physicochemical properties in CMNPD calculated? All physicochemical properties are calculated using algorithms available in [RDKit](https://www.rdkit.org/docs/GettingStartedInPython.html#list-of-available-descriptors). ### Molecular Weight The sum of the atomic masses with the isotope average used for each atomic mass. ### Molecular Mass The sum of the atomic masses with the most common isotope is used for each atomic mass. ### ALogP Calculated value for the lipophilicity of a molecule expressed as log (octanol/water partition coefficient). Method used for the calculation is as described in "Prediction of physicochemical parameters by atomic contributions" by [Wildman, S. A. et al. *J. Chem. Inf. Comput. Sci.*, 1999, **39**, 868-873](https://www.doi.org/10.1021/ci990307l). ### Rotatable Bonds Number of rotatable bonds in the molecule. Based on matching this SMARTS pattern: ``` [!$(*#*)&!D1]-&!@[!$(*#*)&!D1] ``` ### HBA Number of hydrogen bond acceptors: number of heteroatoms (Oxygen, Nitrogen, Sulfur, or Phosphorus) with one or more lone pairs, excluding atoms with positive formal charges, amide and pyrrole-type Nitrogen, and aromatic Oxygen and Sulfur atoms in heterocyclic rings. Based on matching these SMARTS patterns: ``` [$([N;!H0;v3]),$([N;!H0;+1;v4]),$([O,S;H1;+0]),$([n;H1;+0])] ``` ### HBD Number of hydrogen bond donors: number of heteroatoms (Oxygen, Nitrogen, Sulfur, or Phosphorus) with one or more attached Hydrogen atoms. Based on matching these SMARTS patterns: ``` [$([O,S;H1;v2]-[!$(*=[O,N,P,S])]),$([O,S;H0;v2]),$([O,S;-]),$([N;v3;!$(N-*=!@[O,N,P,S])]),$([nH0,o,s;+0])] ``` ### Polar Surface Area The Molecular Polar Surface Area descriptors are calculated using a method based on the published method: "Fast calculation of molecular polar surface area as a sum of fragment based contributions and its application to the prediction of drug transport properties" by [Ertl P. et al., *J. Med. Chem.,* 2000, **43**, 3714-3717](https://www.doi.org/10.1021/jm000942e). ### Aromatic Rings The number of aromatic rings in the molecule. ### Heavy Atoms The number of non - hydrogen atoms in the molecule. ### QED Weighted This is the quantitative estimate of drug-likeness as described in "Quantifying the chemical beauty of drugs" by [Bickerton G. R. et al., *Nat. Chem.*, 2012, **4**, 90-98](https://www.doi.org/10.1038/nchem.1243). The values range from 0 -1 where 1 is the most drug-like and 0 the least drug-like. ## How are the predicted ADMET parameters in CMNPD calculated? All ADMET parameters are calculated using ADMET models available in [BIOVIA Pipeline Pilot](https://www.3dsbiovia.com/products/collaborative-science/biovia-pipeline-pilot/) (version 18.1). ### Blood Brain Barrier Penetration The model predicts blood-brain barrier penetration (BBB) after oral administration. Method used for the calculation is as described in "Prediction of drug absorption using multivariate statistics" by [Egan, W. J. et al., *J. Med. Chem.*, 2000, **43**, 3867-3877](https://www.doi.org/10.1021/jm000292e). The calculable properties of the component are: **Blood Brain Barrier Penetration:** Base 10 logarithm of (brain concentration)/(blood concentration) **Blood Brain Barrier Penetration Level:** Predicts the blood-brain permeation level based on the following categories | Level | Value | Description | | ----- | --------- | ------------------------------------- | | 0 | Very High | Brain-blood ratio greater than 5:1 | | 1 | High | Brain-blood ratio between 1:1 and 5:1 | | 2 | Medium | Brain-blood ratio between 1:1 and 5:1 | | 3 | Low | Brain-blood ratio less than 0.3:1 | | 4 | Undefined | Outside 99 percent confidence ellipse | ### Human Intestinal Absorption This model predicts human intestinal absorption (HIA) after oral administration. Method used for the calculation is as described in "Prediction of drug absorption using multivariate statistics" by [Egan, W. J. et al., *J. Med. Chem.*, 2000, **43**, 3867-3877](https://www.doi.org/10.1021/jm000292e) and "Prediction of intestinal permeability" by [Egan, W. J. et al., *Adv. Drug Delivery Rev.*, 2002, **54**, 273-289](https://www.doi.org/10.1016/S0169-409X\(02\)00004-2). Intestinal absorption is defined as a percentage absorbed rather than as a ratio of concentrations (cf.blood-brain penetration); a well-absorbed compound is one that is absorbed at least 90 percent into the bloodstream in humans. The levels are defined as: * 0 = Good * 1 = Moderate * 2 = Low * 3 = Very low ### Aqueous Solubility The Aqueous Solubility descriptor uses linear regression to predict the aqueous solubility of each compound in water at 25 degrees Celsius. Method used for the calculation is as described in "Prediction of aqueous solubility of a diverse set of compounds using quantitative structure−property relationships" by [Cheng, A. et al., *J. Med. Chem.*, 2003, **46**, 3572-3580](https://www.doi.org/10.1021/jm020266b). **Aqueous Solubility:** The base 10 logarithm of the molar solubility as predicted by the regression. **Aqueous Solubility Level:** Assigns the molecule to one of seven solubility classes based on the value of ADMET Solubility. The classes define the solubility relative to a compendium of known drugs: | Level | Value | Description | | ----- | ------------ | ---------------------------------------------------------- | | 0 | < -8.0 | Extremely low solubility, lower than 95 percent of drugs | | 1 | (-8.0, -6.0) | Very low solubility, at border line of 95 percent of drugs | | 2 | (-6.0, -4.0) | Low solubility, at lower end of 95 percent of drugs | | 3 | (-4.0, -2.0) | Good, slight soluble to soluble | | 4 | (-2.0, 0.0) | Optimal solubility | | 5 | > 0.0 | Very soluble, perhaps too soluble | ### CYP2D6 Binding Model This model predicts whether a particular compound is an inhibitor of the CYP2D6 isozyme of cytochrome P-450 with a value of True or False This model trained on a data set of compounds as described in "Use of robust classification techniques for the prediction of human cytochrome P450 2D6 inhibition" by [Susnow R. G. et al., *J. Chem. Inf. Comput. Sci.*, 2003, **43**, 1308-1315](https://www.doi.org/10.1021/ci030283p). ### Hepatotoxicity Model This model predicts dose-dependent human hepatotoxicity with a value of True (toxic) or False (nontoxic). This model trained on a data set of 436 compounds as described in "In silico models for the prediction of dose-dependent human hepatotoxicity" by [Cheng A. et al., *J. Comput.-Aided Mol. Des.*, 2003,**17**, 811-823](https://www.doi.org/10.1023/B:JCAM.0000021834.50768.c6). ### Plasma Protein Binding Model This model predicts Plasma-Protein binding - whether compound is likely to be highly bound to carrier proteins in the blood. If True, the compound is estimated to be a binder (>=90%). Otherwise, it is estimated to be weaker or non-binder (<90%). This model trained on several data sets of compounds using modified Bayesian learning as described in "Classification of kinase inhibitors using a Bayesian model" [by Xia, X. et al., *J. Med. Chem.*, 2004, **47**, 4463-4470](https://www.doi.org/10.1021/jm0303195). # Acknowledgments ## Funding #### This project was supported by grants from the following funding: * National Major Scientific and Technological Special Project for "Significant New Drugs Development" (No. 2018ZX09735001-003) * National Key Technology R\&D Program "New Drug Innovation" of China (No. 2019YFC1708902) * National Major Scientific and Technological Special Project for "Significant New Drugs Development" (No. 2019ZX09201005-001-002) ## Public Resources CMNPD cites data from the following public resources: * [ChEMBL](https://www.ebi.ac.uk/chembl/) * [PubChem](https://pubchem.ncbi.nlm.nih.gov/) * [DrugBank](https://www.drugbank.ca/) * [SpectraBase](https://spectrabase.com/) * [Catalogue of Life (CoL)](https://www.catalogueoflife.org/) * [World Register of Marine Species (WoRMS)](http://www.marinespecies.org/) * [Integrated Taxonomic Information System (ITIS)](https://www.itis.gov/) * [Index Fungorum](http://www.indexfungorum.org/) * [Universal Protein Resource (UniProt)](https://www.uniprot.org/) * [Protein Data Bank in Europe (PDBe)](https://www.ebi.ac.uk/pdbe/) * [Gene Ontology Annotation (GOA) resource](https://www.ebi.ac.uk/QuickGO/) * [Therapeutic Target Database (TTD)](http://db.idrblab.net/ttd/) * [Open Targets Platform](https://www.targetvalidation.org/) * [Cell Line Ontology (CLO)](http://www.clo-ontology.org/) * [Cell Ontology (CL)](http://www.ontobee.org/ontology/cl) * [Experimental Factor Ontology (EFO)](https://www.ebi.ac.uk/efo/) * [Cellosaurus](https://web.expasy.org/cellosaurus/) * [Library of Integrated Network-based Cellular Signatures (LINCS) NIH program](http://www.lincsproject.org/) ## Open Source Project This website is modelled on the[ New Web Interface of ChEMBL](https://www.ebi.ac.uk/chembl). We sincerely thank the ChEMBL group for providing open source resources on [GitHub](https://github.com/chembl). # Disclaimer We endeavor to provide a reasonable level of service based on the published literature and authoritative public databases, but neither CMNPD nor any contributor has made any specific commitments to the services, including the content or any submissions therein. CMNPD team cannot guarantee the accuracy or completeness of the information in the current release. Be aware that CMNPD is still incomplete and undoubtedly contains errors. Neither CMNPD nor any contributing database can be made liable for any direct or indirect damage arising out of the use of CMNPD. # Terms and Conditions ## Data Licensing The CMNPD data is made available under a Creative Commons [Attribution-NonCommercial-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-nc-sa/4.0/) license. Except as otherwise provided in any additional terms for a service, you may print or download content from the services for your own personal, non-commercial, informational or scholarly use. ## Cite Us **If you use the database in your research, please cite:**\ Chuanyu Lyu, Tong Chen, Bo Qiang, Ningfeng Liu, Heyu Wang, Liangren Zhang, Zhenming Liu, CMNPD: a comprehensive marine natural products database towards facilitating drug discovery from the ocean, *Nucleic Acids Research*, **2021**, 49(D1): D509-D515. doi: [10.1093/nar/gkaa763](https://doi.org/10.1093/nar/gkaa763). ## Submission Policy 1. CMNPD deposit system requires registration. When registering, you need to provide accurate and complete information.
2. Compared with unregistered users, you do not have any permissions or rights in this service to access additional content other than public data and your own deposited data.
3. CMNPD reserves the right to modify your deposited data for the purpose of providing a consistent representation of all information within the service.
4. Your deposited data will be made available without cost and without restriction to the public.
5. You can delete your deposited data at any time before publishing. Once the data is reviewed and published, however, you will need to contact the CMNPD team to apply for deletion of your data from the public region. ## Privacy Notice This website requires cookies, and the limited processing of your personal data in order to function. We collect the following personal data: * Email address * IP addresses * Date and time of a visit to the service website * Amount of data transmitted * Date and time when the feedback was sent We will use the personal data: * To provide the user access to the service * To better understand the needs of the users and guide future improvements of the service * To conduct and monitor data protection activities * To create anonymous usage statistics * To conduct and monitor security activities The personal data will be disclosed to authorized CMNPD staff only and will not be transferred to third organizations. # Contact ## Email Dr. Zhenming Liu \[] Mr. Chuanyu Lyu \[] ## Address CMNPD\ State Key Laboratory of Natural and Biomimetic Drugs\ School of Pharmaceutical Sciences\ Peking University Health Science Center\ 38 Xueyuan Rd, Beijing 100191[📍](https://www.google.com/maps/place/%E5%A4%A9%E7%84%B6%E8%8D%AF%E7%89%A9%E5%8F%8A%E4%BB%BF%E7%94%9F%E8%8D%AF%E7%89%A9%E5%9B%BD%E5%AE%B6%E9%87%8D%E7%82%B9%E5%AE%9E%E9%AA%8C%E5%AE%A4/@39.9847005,116.3499824,14z/data=!4m12!1m6!3m5!1s0x35f0547180e4f28f:0xa80d88ce14f10a5f!2z5aSp54S26I2v54mp5Y-K5Lu_55Sf6I2v54mp5Zu95a626YeN54K55a6e6aqM5a6k!8m2!3d39.985132!4d116.354617!3m4!1s0x35f0547180e4f28f:0xa80d88ce14f10a5f!8m2!3d39.985132!4d116.354617)\ P. R. China