Mol-Instructions

<h1 align="center"> 🧪 Mol-Instructions </h1> <h3 align="center"> An open, large-scale biomolecular instruction dataset for large language models. </h3> <p align="center"> 📃 <a href="https://arxiv.org/abs/2306.08018" target="_blank">Paper</a> • ⏬ <a href="https://huggingface.co/datasets/zjunlp/Mol-Instructions" target="_blank">Dataset</a><br> </p>

🆕 News

[May 2024] We've updated the results and models (molecule and biotext) of instruction-tuning on LLaMA3.
[February 2024] We've released ChatCell, a new paradigm that leverages natural language to make single-cell analysis more accessible and intuitive. Please visit our homepage and Github page for more information.
[January 2024] Our paper Domain-Agnostic Molecular Generation with Chemical Feedback is accepted by ICLR 2024.
[January 2024] Our paper Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models is accepted by ICLR 2024.
[October 2023] We've updated the train/test splits on Mol-Instructions, along with the evaluation code.
[September 2023] We've released the molecule and biotext model weights on Hugging Face, built upon LLaMa-7b-chat.
[August 2023] We've added quantitative experiments on Mol-Instructions.
[June 2023] We've open-sourced KnowLM, a knowledgeable large language model framework! It comes with pre-training and instruction fine-tuning code (supports multi-machine multi-GPU setup).
[June 2023] We release the first version (v1) of datasets and model weights.
[March 2023] We propose MolGen, a robust pre-trained molecular generative model with self-feedback.

📌 Contents

Overview
Tasks
Demo
Notices
- Usage and License
- Limitations
About
- References
- Acknowledgements

<h2 id="1">1. Overview</h2> <h3 id="1-1"> 📊 1.1 Data Stats</h3> <div align=center><img src="fig/stat.png" width="90%" height="90%" /></div>

Mol-Instructions comprises three cardinal components:

🔬 Molecule-oriented instructions: This component delves into the world of small molecules, emphasizing their inherent properties and behaviors. It sheds light on the fundamental challenges of diverse chemical reactions and molecular design, with 148,4K instructions across six tasks.
🧬 Protein-oriented instructions: Rooted in the biosciences, this component presents 505K instructions across five distinct categories of tasks. These tasks aim to predict the structure, function, and activity of proteins, and facilitate protein design based on textual directives.
🥼 Biomolecular text instructions: Predominantly designed to cater to NLP tasks within the fields of bioinformatics and chemoinformatics, this part encapsulates six information extraction and Q&A tasks represented through 53K instructions.

<h3 id="1-2"> 🛠️ 1.2 Data Construction</h3> <div align=center><img src="fig/construction.png" width="100%" height="100%" /></div>

🤖️ Human-AI Collaboration Task Description Creation: In real-world applications, task instructions must be able to accommodate the varied and dynamic nature of human needs and queries. We emulate this diversity by starting with a clear, human-crafted description for each task, which is then used as an input to GPT-3.5-turbo.
📖 Information Derivation from Existing Data: Biomolecular data often requires specialist laboratory experiments and expert analysis, making authoritative and recognized biochemistry databases an ideal source of our data. With suitable processing, these resources enable us to extract the required instruction data.
📜 Template-based Conversion of Biological Data into Textual Format: To facilitate the transformation of these structured annotations into a textual format, we design a diverse array of templates. Each resulting text-based annotation serves as a guideline for protein design.
✅ Quality Control: To expedite the model's ability to generate precise biomolecules, we implement stringent quality control measures for our biomolecular data.

<h3 id="1-3"> 🤗 1.3 Data Release</h3>

We release the dataset on Hugging Face at zjunlp/Mol-Instructions.

<h2 id="2">2. Tasks</h2> <h3 id="2-1"> 🔬 2.1 Molecule-oriented</h3> <details> <summary><b>Molecule description generation</b></summary>

Please give me some details about this molecule: [C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][=Branch1][C][=O][O][C@H1][Branch2][Ring1][=Branch1][C][O][C][=Branch1][C][=O][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][O][P][=Branch1][C][=O][Branch1][C][O][O][C][C@@H1][Branch1][=Branch1][C][=Branch1][C][=O][O][N]
```
The molecule is a 3-sn-phosphatidyl-L-serine in which the phosphatidyl acyl groups at positions 1 and 2 are specified as stearoyl and arachidonoyl respectively. 
It is functionally related to an arachidonic acid and an octadecanoic acid.
```

</details> <details> <summary><b>Description-guided molecule design</b></summary>

Create a molecule with the structure as the one described: The molecule is a primary arylamine in which an amino functional group is substituted for one of the benzene hydrogens. It is a primary arylamine and a member of anilines.
```
[N][C][=C][C][=C][C][=C][Ring1][=Branch1]
```

</details> <details> <summary><b>Forward reaction prediction</b></summary>

With the provided reactants and reagents, propose a potential product: [O][=N+1][Branch1][C][O-1][C][=C][N][=C][Branch1][C][Cl][C][Branch1][C][I][=C][Ring1][Branch2].[Fe]
```
[N][C][=C][N][=C][Branch1][C][Cl][C][Branch1][C][I][=C][Ring1][Branch2]
```

</details> <details> <summary><b>Retrosynthesis</b></summary>

Please suggest potential reactants used in the synthesis of the provided product: [C][=C][C][C][N][C][=Branch1][C][=O][O][C][Branch1][C][C][Branch1][C][C][C]
```
[C][=C][C][C][N].[C][C][Branch1][C][C][Branch1][C][C][O][C][=Branch1][C][=O][O][C][=Branch1][C][=O][O][C][Branch1][C][C][Branch1][C][C][C]
```

</details> <details> <summary><b>Reagent prediction</b></summary>

Please provide possible reagents based on the following chemical reaction: [C][C][=C][C][=C][Branch1][C][N][C][=N][Ring1][#Branch1].[O][=C][Branch1][C][Cl][C][Cl]>>[C][C][=C][C][=C][Branch1][Branch2][N][C][=Branch1][C][=O][C][Cl][C][=N][Ring1][O]
```
[C][C][C][O][C][Ring1][Branch1].[C][C][N][Branch1][Ring1][C][C][C][C].[O]
```

</details> <details> <summary><b>Property prediction</b></summary>

Please provide the HOMO energy value for this molecule: [C][C][O][C][C][Branch1][C][C][C][Branch1][C][C][C]
```
-0.2482
```

</details> <h3 id="2-2"> 🧬 2.2 Protein-oriented</h3> <details> <summary><b>Protein design</b></summary>

Design a protein sequence that exhibits the desired activity and specificity.

The presence of Mg(2+) is necessary for the protein to function in the desired environment.
The AMP, (6S)-NADPHX binding site should be located in a region of the protein that is accessible to the ligand.
The designed protein should have ATP binding, NADPHX epimerase activity, metal ion binding, ADP-dependent NAD(P)H-hydrate dehydratase activity to facilitate nicotinamide nucleotide metabolic process.
For general function, the protein need meet that Catalyzes the epimerization of the S- and R-forms of NAD(P)HX, a damaged form of NAD(P)H that is a result of enzymatic or heat-dependent hydration

MSNELVLSREQVRRVDQRAIEAYGVPGIVLMENAGRGAAEIIRAACPSAQRVLIACGPGNNGGDGFVIARHLANAGWMVELLLACPADRITGDAQGNHEIIRRMNLPCAVMADARDLEAANDRFATADVIVDALLGTGASGPPREPIASLIRAINEAHRRVSAQPAPSVFAVDIPSGLDCDTGEAANPTVRADHTITFVARKIGFRNPAARDLLGRVHVVDIGAPRAAIQDALTGKSG

</details> <details> <summary><b>Catalytic activity prediction</b></summary>

Please evaluate the following protein sequence and provide an explanation of the enzyme's catalytic activity, including the chemical reaction it facilitates: MDKVAVAGFLPEELCASLSLSPSFRGNQIFQWIGKGVDSFDAMTNLSAELRASLAEKAILRSTRVSDVLKADDGTVKLQIQTEDDLAVETVLLTDKAARKTACVSCQAGCAMGCAFCKTGTLGLARNLSAAEIVEQFLYLEKHAGALDNIVFMGMGEPLLNLDALRKAIAVLTDKRGRNLSSRRITVSTVGIVSGIYDLANNGPDVRLAVSLTTADETLRRELMPASLTNPLSDLRQAISYYIEKTGKRVTLEAVLLSGKNTSEKNADSLIAFAKGLDVHVNLIPWNPVEGLSFVTPDPEETAQFVSRLEKGGLNVTLRMHRGKSISGACGQLGKTNPYA
```
Based on the provided protein sequence, the enzyme appears to facilitate the chemical reaction: adenosine(37) in tRNA + 2 reduced [2Fe-2S]-[ferredoxin] + 2 S- adenosyl-L-methionine = 2-methyladenosine(37) in tRNA + 5'-   deoxyadenosine + L-methionine + 2 oxidized [2Fe-2S]-[ferredoxin] + S- adenosyl-L-homocysteine.
```

</details> <details> <summary><b>Protein function prediction</b></summary>

Analyze the following amino acid sequence, and determine the function of the resulting protein, its subcellular localization, and any biological processes it may be part of: MNGTVNASAPSKMSEVAVERLSNDKALKVIFVLGGPGSGKGTQCAKIAKHFGFTHLSVGDLLRAEINSGSKNGTMIESMINEGKIVRSEVTIKLLQRAMHESGNDKFLIDGFPRNEENRAAFENLEKIEPEFVLFFDCPMEEMERRILNRNQGRDDDKMETIRKRFKVFIESTLPVIEFYNLKGKLYKIDACKPADEVFEDVKAIFSRFRAKEDSSQQTNICTAKRFELVMCLIKRLFREIKRMWSSFFCKAL
```
The protein characterized by the amino acid sequence demonstrates ATP binding, cytidylate kinase activity, uridylate kinase activity and is implicated in the 'de novo' pyrimidine nucleobase biosynthetic process, phosphorylation, pyrimidine nucleotide biosynthetic process. Its subcellular localization is primarily within the cytoplasm, nucleus.
```

</details> <details> <summary><b>Functional description generation</b></summary>

Examine the given protein sequence and share a brief overview of its attributes: MKIVLASNNQGKLAELKAMLAPLGVQLLRQAELGIPEAAEPFRTFVENALAKARHASALSGLPALADDAGLCVEAFGGLPGVDTAFYAVQFGYAKGDANNVKALLAQMAGITDRRAALVSTLVAVRSAEDPEPLIACGRVAGEVALEPMGSNGFGFDPVMFIPEFGQTFAQLPVEVKNANSHRGKATRQMMALMRERWIT

A concise description of the protein with the specified amino acid sequence includes: Pyrophosphatase that catalyzes the hydrolysis of nucleoside triphosphates to their monophosphate derivatives, with a high preference for the non-canonical purine nucleotides XTP (xanthosine triphosphate), dITP (deoxyinosine triphosphate) and ITP. Seems to function as a house-cleaning enzyme that removes non-canonical purine nucleotides from the nucleotide pool, thus preventing their incorporation into DNA/RNA and avoiding chromosomal lesions.

</details> <details> <summary><b>Domain/Motif prediction</b></summary>