ArticleProteins2019
Rapid and accurate structure-based therapeutic peptide design using GPU accelerated thermodynamic integration.
Article in Proteins, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Oncogenic EME1 promotes tumor progression and immune modulation in human cancers with therapeutic targeting potential.Discover oncology · 2025Article
- Computational design of a cyclic peptide that inhibits the CTLA4 immune checkpoint.RSC medicinal chemistry · 2023Article
- Protocol for iterative optimization of modified peptides bound to protein targets.Journal of computer-aided molecular design · 2022Article
- Essential meiotic structure-specific endonuclease1 (Bioengineered · 2021Article
- How Computational Chemistry and Drug Delivery Techniques Can Support the Development of New Anticancer Drugs.Molecules (Basel, Switzerland) · 2020Review
- Rigorous Computational and Experimental Investigations on MDM2/MDMX-Targeted Linear and Macrocyclic Peptides.Molecules (Basel, Switzerland) · 2019Article
- Predicting changes in protein stability caused by mutation using sequence-and structure-based methods in a CAGI5 blind challenge.Human mutation · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Peptide-based therapeutics are an alternative to small molecule drugs as they offer superior specificity, lower toxicity, and easy synthesis. Here we present an approach that leverages the dramatic performance increase afforded by the recent arrival of GPU accelerated thermodynamic integration (TI). GPU TI facilitates very fast, highly accurate binding affinity optimization of peptides against therapeutic targets. We benchmarked TI predictions using published peptide binding optimization studies. Prediction of mutations involving charged side-chains was found to be less accurate than for non-charged, and use of a more complex 3-step TI protocol was found to boost accuracy in these cases. Using the 3-step protocol for non-charged side-chains either had no effect or was detrimental. We use the benchmarked pipeline to optimize a peptide binding to our recently discovered cancer target: EME1. TI calculations predict beneficial mutations using both canonical and non-canonical amino acids. We validate these predictions using fluorescence polarization and confirm that binding affinity is increased. We further demonstrate that this increase translates to a significant reduction in pancreatic cancer cell viability.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.