ArticleBiophysical journal2019
Machine Learning for Prioritization of Thermostabilizing Mutations for G-Protein Coupled Receptors.
Article in Biophysical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Protein Frustration Reveals Orthosteric and Allosteric Active Sites in GPCR:G Protein Complexes.Journal of chemical information and modeling · 2026Article
- Discovery of Therapeutic Antibodies Targeting Complex Multi-Spanning Membrane Proteins.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2024Review
- Incorporating physics to overcome data scarcity in predictive modeling of protein function: A case study of BK channels.PLoS computational biology · 2023Article
- Incorporating physics to overcome data scarcity in predictive modeling of protein function: a case study of BK channels.bioRxiv : the preprint server for biology · 2023Article
- Fluorescence-Detection Size-Exclusion Chromatography-Based Thermostability Assay for Membrane Proteins.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Towards generalizable predictions for G protein-coupled receptor variant expression.Biophysical journal · 2022Article
- Sequence coevolution and structure stabilization modulate olfactory receptor expression.Biophysical journal · 2022Article
- Computational design of a cutinase for plastic biodegradation by mining molecular dynamics simulations trajectories.Computational and structural biotechnology journal · 2022Article
- An online GPCR structure analysis platform.Nature structural & molecular biology · 2021Article
- IMPROvER: the Integral Membrane Protein Stability Selector.Scientific reports · 2020Article
- Expression and purification of recombinant G protein-coupled receptors: A review.Protein expression and purification · 2020Review
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Although the three-dimensional structures of G-protein coupled receptors (GPCRs), the largest superfamily of drug targets, have enabled structure-based drug design, there are no structures available for 87% of GPCRs. This is due to the stiff challenge in purifying the inherently flexible GPCRs. Identifying thermostabilized mutant GPCRs via systematic alanine scanning mutations has been a successful strategy in stabilizing GPCRs, but it remains a daunting task for each GPCR. We developed a computational method that combines sequence-, structure-, and dynamics-based molecular properties of GPCRs that recapitulate GPCR stability, with four different machine learning methods to predict thermostable mutations ahead of experiments. This method has been trained on thermostability data for 1231 mutants, the largest publicly available data set. A blind prediction for thermostable mutations of the complement factor C5a receptor 1 retrieved 36% of the thermostable mutants in the top 50 prioritized mutants compared to 3% in the first 50 attempts using systematic alanine scanning.
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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.