An advanced LLM-powered article extraction pipeline delivers a database of buffers for protein studies and protein expression conditions.
- 1Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543, Singapore.
Abstract
Optimizing protein expression and buffer conditions is a major challenge in life-science research and biotechnology. We present an LLM-powered extraction pipeline that systematically converts unstructured scientific literature into a structured, queryable database. Leveraging advanced optical character recognition, custom reranker models, and large language models, our system achieves ~97% extraction accuracy. By processing 100 353 structural biology publications associated with the RCSB Protein Data Bank, we constructed a database containing 947 153 distinct buffer entries and 73 210 expression protocols for 35 690 unique proteins, establishing the largest resource of its kind. The ProBufEx (https://www.probufex.org/) web platform enables rapid exploration of optimal conditions by protein properties or functions. Case studies reveal distinct patterns in chemical usage on proteins with different post-translational modifications, and function-dependent expression strategies for proteins with different enzymatic activities. This resource transforms vast structural biology literature into actionable knowledge, accelerating evidence-based protocol design, reducing trial-and-error, and streamlining experiments in protein science.
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BibTeX
@article{chen2026advanced,
title = {{An advanced LLM-powered article extraction pipeline delivers a database of buffers for protein studies and protein expression conditions.}},
author = {Zhuojian Chen and Eng Aloysius and J Sivaraman},
journal = {Briefings in bioinformatics},
year = {2026},
month = sep,
doi = {10.1093/bib/bbag570},
url = {https://europepmc.org/article/MED/42905769},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - An advanced LLM-powered article extraction pipeline delivers a database of buffers for protein studies and protein expression conditions.
AU - Zhuojian Chen
AU - Eng Aloysius
AU - J Sivaraman
PY - 2026
DA - 2026/09/01
JO - Briefings in bioinformatics
DO - 10.1093/bib/bbag570
UR - https://europepmc.org/article/MED/42905769
AB - Optimizing protein expression and buffer conditions is a major challenge in life-science research and biotechnology. We present an LLM-powered extraction pipeline that systematically converts unstructured scientific literature into a structured, queryable database. Leveraging advanced optical character recognition, custom reranker models, and large language models, our system achieves ~97% extraction accuracy. By processing 100 353 structural biology publications associated with the RCSB Protein Data Bank, we constructed a database containing 947 153 distinct buffer entries and 73 210 expression protocols for 35 690 unique proteins, establishing the largest resource of its kind. The ProBufEx (https://www.probufex.org/) web platform enables rapid exploration of optimal conditions by protein properties or functions. Case studies reveal distinct patterns in chemical usage on proteins with different post-translational modifications, and function-dependent expression strategies for proteins with different enzymatic activities. This resource transforms vast structural biology literature into actionable knowledge, accelerating evidence-based protocol design, reducing trial-and-error, and streamlining experiments in protein science.
SN - 1467-5463
SN - 1477-4054
ER -