ArticlePLoS computational biology2020
Improving homology modeling from low-sequence identity templates in Rosetta: A case study in GPCRs.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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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
23 citing papers in PubMed, 44 citations in OpenAlex.
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- Engineered odorant receptors illuminate structural principles of odor discrimination.bioRxiv : the preprint server for biology · 2023Article
- Structure-Based Discovery of Mouse Trace Amine-Associated Receptor 5 Antagonists.Journal of chemical information and modeling · 2023Article
- Improving the Modeling of Extracellular Ligand Binding Pockets in RosettaGPCR for Conformational Selection.International journal of molecular sciences · 2023Article
- Development of anti-PD-L1 antibody based on structure prediction of AlphaFold2.Frontiers in immunology · 2023Article
- Evaluating GPCR modeling and docking strategies in the era of deep learning-based protein structure prediction.Computational and structural biotechnology journal · 2023Article
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- Structural Comparative Modeling of Multi-Domain F508del CFTR.Biomolecules · 2022Article
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- Ligand-binding and -scavenging of the chemerin receptor GPR1.Cellular and molecular life sciences : CMLS · 2021Article
- Accurate prediction of protein structures and interactions using a three-track neural network.Science (New York, N.Y.) · 2021Article
- Bitter Taste and Olfactory Receptors: Beyond Chemical Sensing in the Tongue and the Nose.The Journal of membrane biology · 2021Article
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
Abstract
As sequencing methodologies continue to advance, the availability of protein sequences far outpaces the ability of structure determination. Homology modeling is used to bridge this gap but relies on high-identity templates for accurate model building. G-protein coupled receptors (GPCRs) represent a significant target class for pharmaceutical therapies in which homology modeling could fill the knowledge gap for structure-based drug design. To date, only about 17% of druggable GPCRs have had their structures characterized at atomic resolution. However, modeling of the remaining 83% is hindered by the low sequence identity between receptors. Here we test key inputs in the model building process using GPCRs as a focus to improve the pipeline in two critical ways: Firstly, we use a blended sequence- and structure-based alignment that accounts for structure conservation in loop regions. Secondly, by merging multiple template structures into one comparative model, the best possible template for every region of a target can be used expanding the conformational space sampled in a meaningful way. This optimization allows for accurate modeling of receptors using templates as low as 20% sequence identity, which accounts for nearly the entire druggable space of GPCRs. A model database of all non-odorant GPCRs is made available at www.rosettagpcr.org. Additionally, all protocols are made available with insights into modifications that may improve accuracy at new targets.
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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 Socratic graph.