PROTLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training

Le Zhuo, Zewen Chi, Minghao Xu, Heyan Huang*, Jianan Zhao, Heqi Zheng, Conghui He, Xian Ling Mao, Wentao Zhang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

We propose PROTLLM, a versatile cross-modal large language model (LLM) for both protein-centric and protein-language tasks. PROTLLM features a unique dynamic protein mounting mechanism, enabling it to handle complex inputs where the natural language text is interspersed with an arbitrary number of proteins. Besides, we propose the protein-as-word language modeling approach to train PROTLLM. By developing a specialized protein vocabulary, we equip the model with the capability to predict not just natural language but also proteins from a vast pool of candidates. Additionally, we construct a large-scale interleaved protein-text dataset, named InterPT, for pre-training. This dataset comprehensively encompasses both (1) structured data sources like protein annotations and (2) unstructured data sources like biological research papers, thereby endowing PROTLLM with crucial knowledge for understanding proteins. We evaluate PROTLLM on classic supervised protein-centric tasks and explore its novel protein-language applications. Experimental results demonstrate that PROTLLM not only achieves superior performance against protein-specialized baselines on protein-centric tasks but also induces zero-shot and in-context learning capabilities on protein-language tasks.

Original languageEnglish
Title of host publicationLong Papers
EditorsLun-Wei Ku, Andre F. T. Martins, Vivek Srikumar
PublisherAssociation for Computational Linguistics (ACL)
Pages8950-8963
Number of pages14
ISBN (Electronic)9798891760943
DOIs
Publication statusPublished - 2024
Event62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024 - Bangkok, Thailand
Duration: 11 Aug 202416 Aug 2024

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
Volume1
ISSN (Print)0736-587X

Conference

Conference62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024
Country/TerritoryThailand
CityBangkok
Period11/08/2416/08/24

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