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--- |
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license: unknown |
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task_categories: |
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- tabular-classification |
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- graph-ml |
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- text-classification |
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tags: |
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- chemistry |
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- biology |
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- medical |
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pretty_name: MoleculeNet HIV |
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size_categories: |
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- 10K<n<100K |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: "hiv.csv" |
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--- |
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# MoleculeNet HIV |
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HIV dataset [[1]](#1), part of MoleculeNet [[2]](#2) benchmark. It is intended to be used through |
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[scikit-fingerprints](https://github.com/scikit-fingerprints/scikit-fingerprints) library. |
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The task is to predict ability of molecules to inhibit HIV replication. |
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| **Characteristic** | **Description** | |
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|:------------------:|:---------------:| |
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| Tasks | 1 | |
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| Task type | classification | |
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| Total samples | 41127 | |
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| Recommended split | scaffold | |
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| Recommended metric | AUROC | |
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**Warning:** in newer RDKit vesions, 7 molecules from the original dataset are not read correctly due to disallowed |
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hypervalent states of some atoms (see [release notes](https://github.com/rdkit/rdkit/releases/tag/Release_2024_09_1)). |
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This version of the HIV dataset contains manual fixes for those molecules, made by cross-referencing original |
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NCI data [[1]](#1), PubChem substructure search, and visualization with ChemAxon Marvin. In OGB scaffold split, used |
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for benchmarking, first 2 of those problematic 7 are from the test set. Applied mapping is: |
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``` |
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"O=C1O[Al]23(OC1=O)(OC(=O)C(=O)O2)OC(=O)C(=O)O3" -> "C1(=O)C(=O)O[Al-3]23(O1)(OC(=O)C(=O)O2)OC(=O)C(=O)O3" |
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"Cc1ccc([B-2]2(c3ccc(C)cc3)=NCCO2)cc1" -> "[B-]1(NCCO1)(C2=CC=C(C=C2)C)C3=CC=C(C=C3)C" |
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"Oc1ccc(C2Oc3cc(O)cc4c3C(=[O+][AlH3-3]35([O+]=C6c7c(cc(O)cc7[OH+]3)OC(c3ccc(O)cc3O)C6O)([O+]=C3c6c(cc(O)cc6[OH+]5)OC(c5ccc(O)cc5O)C3O)[OH+]4)C2O)c(O)c1" -> "C1[C@@H]([C@H](OC2=C1C(=CC(=C2C3=C(OC4=CC(=CC(=C4C3=O)O)O)C5=CC=C(C=C5)O)O)O)C6=CC=C(C=C6)O)O" |
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"CC1=C2[OH+][AlH3-3]34([O+]=C2C=CN1C)([O+]=C1C=CN(C)C(C)=C1[OH+]3)[O+]=C1C=CN(C)C(C)=C1[OH+]4" -> "CC1=C(C(=O)C=CN1C)[O-].CC1=C(C(=O)C=CN1C)[O-].CC1=C(C(=O)C=CN1C)[O-].[Al+3]" |
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"CC(c1cccs1)=[N+]1[N-]C(N)=[S+][AlH3-]12[OH+]B(c1ccccc1)[OH+]2" -> "B1(O[Al](O1)N(C(=S)N)/N=C(/C)\C2=CC=CS2)C3=CC=CC=C3" |
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"CC(c1ccccn1)=[N+]1[N-]C(N)=[S+][AlH3-]12[OH+]B(c1ccccc1)[OH+]2" -> "B1(O[Al](O1)N(C(=S)N)/N=C(/C)\C2=CC=CC=N2)C3=CC=CC=C3" |
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"[Na+].c1ccc([SH+][GeH2+]2[SH+]c3ccccc3[SH+]2)c([SH+][GeH2+]2[SH+]c3ccccc3[SH+]2)c1" -> "C1=CC=C(C(=C1)[SH2+])[SH2+].C1=CC=C(C(=C1)[SH2+])[SH2+].C1=CC=C(C(=C1)[SH2+])[SH2+].[Ge].[Ge]" |
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``` |
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## References |
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<a id="1">[1]</a> |
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AIDS Antiviral Screen Data |
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https://wiki.nci.nih.gov/display/NCIDTPdata/AIDS+Antiviral+Screen+Data |
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<a id="2">[2]</a> |
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Wu, Zhenqin, et al. |
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"MoleculeNet: a benchmark for molecular machine learning." |
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Chemical Science 9.2 (2018): 513-530 |
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https://pubs.rsc.org/en/content/articlelanding/2018/sc/c7sc02664a |
