Easy and accurate protein structure prediction using ColabFold

Kim, Gyuri; Lee, Sewon; Karin, Eli Levy; Kim, Hyunbin; Moriwaki, Yoshitaka; Ovchinnikov, Sergey; Steinegger, Martin; Mirdita, Milot

doi:10.21203/rs.3.pex-2490/v1

Cited by 10 publications

(6 citation statements)

References 32 publications

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“…C,D and Supplementary Figure 2. C,D,E were adapted from 105 . Visualization of pdb files was done with Mol* 106 of RCSB PDB.…”

Section: Methodsmentioning

confidence: 99%

“…Structural predictions were done with ColabFold (v.1.5.3), a software package that offers an integrated protein prediction solution as a webbased interface (utilizing Google Colaboratory notebooks). More specifically, the AlphaFold2.ipynb notebook was used 101 . This tool integrates rapid homology searches, employing many-against-many sequence searching (MMseqS2) against the databases UniRef100, PDB100, and environmental sequence database, in conjunction with AlphaFold2 and RoseTTAFold methodologies [102][103][104] .…”

Section: Protein Structure and Protein Complex Predictionmentioning

confidence: 99%

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The Developmental Transcription Factor TBX3 Physically Engages with the Wnt/β-catenin Transcriptional Complex in Human Colorectal Cancer Cells to Regulate Metastasis Genes

Jauregi-Miguel,

Söderholm,

Weiss

et al. 2023

Preprint

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Wnt signaling orchestrates gene expression in a plethora of processes during development and adult cell homeostasis via the action of nuclear β-catenin. Furthermore, neoplasia of the colorectal epithelium begins with aberrant Wnt/β-catenin signaling. Yet, little is known about how β-catenin generates context-specific transcriptional outcomes. We have previously identified the developmental transcription factor TBX3 as a tissue-specific component of the Wnt/β-catenin nuclear complex during mouse forelimb development. In this study, we show that TBX3 is present and functionally active in human colorectal cancers. TBX3’s genomic binding pattern suggests a regulatory role that broadly coincides with that of Wnt/β-catenin. Moreover, proteomics proximity labelling indicated that, during Wnt pathway activation, TBX3 is vicinal to several protein partners, including the transcription factors TCF/LEF and chromatin remodeling complexes which are usually found at Wnt responsive elements. Sequence and structure analysis revealed that TBX3 possesses an exposed Asp-Pro-Phe (NPF) motif predicted by AlphaFold2 Multimer to mediate direct interactions with several Wnt-activated TBX3 partners. Deletion of NPF abrogates TBX3 proximity to these partners and its ability to modulate Wnt-dependent transcription. TBX3 emerges as a key modulator of the oncogenic activity of Wnt/β-catenin in colorectal cancer, and its mechanism of action exposes a novel druggable protein-interaction surface.

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“…C,D and Supplementary Figure 2. C,D,E were adapted from 105 . Visualization of pdb files was done with Mol* 106 of RCSB PDB.…”

Section: Methodsmentioning

confidence: 99%

Section: Protein Structure and Protein Complex Predictionmentioning

confidence: 99%

The Developmental Transcription Factor TBX3 Physically Engages with the Wnt/β-catenin Transcriptional Complex in Human Colorectal Cancer Cells to Regulate Metastasis Genes

Jauregi-Miguel,

Söderholm,

Weiss

et al. 2023

Preprint

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“…LazyAF consists of two open-source Google Colaboratory notebooks (see data availability). At the core of LazyAF is ColabFold BATCH which is also available via Google Colaboratory (https://github.com/sokrypton/ColabFold) (Kim et al, 2023; Mirdita et al, 2022). An outline of LazyAF is depicted in Figure 1.…”

Section: Software Descriptionmentioning

confidence: 99%

LazyAF, a pipeline for accessible medium-scalein silicoprediction of protein-protein interactions

McLean

2024

Preprint

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Artificial intelligence has revolutionized the field of protein structure prediction. However, with more powerful and complex software being developed, it is accessibility and ease of use rather than capability that is quickly becoming a limiting factor to end users. Here, I present a Google Colaboratory-based pipeline, named LazyAF, which integrates the existing ColabFold BATCH to streamline the process of medium-scale protein-protein interaction prediction. I apply LazyAF to predict the interactome of the 76 proteins encoded on a broad-host-range multi-drug resistance plasmid RK2, demonstrating the ease and accessibility the pipeline provides.

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“…At the core of LazyAF is ColabFold BATCH which is also available via Google Colaboratory (https://github.com/sokrypton/ColabFold) [3,5]. An outline of LazyAF is depicted in Fig.…”

Section: Software Descriptionmentioning

confidence: 99%

LazyAF, a pipeline for accessible medium-scale in silico prediction of protein-protein interactions

McLean

2024

Microbiology

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Artificial intelligence has revolutionized the field of protein structure prediction. However, with more powerful and complex software being developed, it is accessibility and ease of use rather than capability that is quickly becoming a limiting factor to end users. LazyAF is a Google Colaboratory-based pipeline which integrates the existing ColabFold BATCH software to streamline the process of medium-scale protein-protein interaction prediction. LazyAF was used to predict the interactome of the 76 proteins encoded on the broad-host-range multi-drug resistance plasmid RK2, demonstrating the ease and accessibility the pipeline provides.

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Easy and accurate protein structure prediction using ColabFold

Cited by 10 publications

References 32 publications

The Developmental Transcription Factor TBX3 Physically Engages with the Wnt/β-catenin Transcriptional Complex in Human Colorectal Cancer Cells to Regulate Metastasis Genes

The Developmental Transcription Factor TBX3 Physically Engages with the Wnt/β-catenin Transcriptional Complex in Human Colorectal Cancer Cells to Regulate Metastasis Genes

LazyAF, a pipeline for accessible medium-scalein silicoprediction of protein-protein interactions

LazyAF, a pipeline for accessible medium-scale in silico prediction of protein-protein interactions

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