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32 results for “deep mutational scan”
Overcoming Limitation of AlphaFold2 by Deep-mutational Scanning and Stability-Selection of Protein Sequences
<p>This repository contains the processed datasets and corresponding code used in our study. While AlphaFold2 revolutionizes protein structure prediction, its accuracy critically depends on evolutionary information from natural homologs—limiting applications for proteins with sparse sequence families. Here, we bypass this bottleneck by employing deep mutational scanning and stability-guided selection to generate artificial homologs. Fed into AlphaFold2, these synthetic sequences match the accuracy achieved on well-predicted proteins with rich natural homology, while providing highly accurate predictions for difficult targets—including orphan proteins previously deemed "unpredictable." Our approach achieves high accuracy (<3 Å RMSD for 5/8 and <2 Å RMSD for 7/8 targets after excluding intrinsically flexible regions). Thus, integrating simple, scalable molecular biology (mutagenesis/selection) with high-throughput sequencing can deliver the accuracy similar to but at a fraction of the cost and time of traditional experimental structure-determination methods. This hybrid framework could democratize high-resolution structural biology, opening avenues to determine structures of protein complexes, modified proteins, and condition-dependent conformations. </p>
Data from: Deep mutational scanning of HBV reveals a mechanism for cis preferential reverse transcription
<p>Hepatitis B virus (HBV) is a small double-stranded DNA virus that chronically infects 296 million people. Over half of its compact genome encodes protein in two overlapping reading frames, and during evolution, multiple selective pressures can act on shared nucleotides. This study combines an RNA-based HBV cell culture system with deep mutational scanning to uncouple <em>cis-</em> and <em>trans</em>-acting sequence requirements in the HBV genome. The results support a leaky ribosome scanning model for polymerase translation, provide a fitness map of the HBV polymerase at single nucleotide resolution, and identify conserved prolines adjacent to the HBV polymerase termination codon that stall ribosomes. Further experiments indicated that stalled ribosomes tether the nascent polymerase to its template RNA, ensuring <em>cis</em>-preferential RNA packaging and reverse transcription of the HBV genome.</p>
Data from: Deep mutational scanning of the multi-domain phosphatase SHP2 reveals mechanisms of regulation and pathogenicity
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Data from: Deep mutational scanning of HBV reveals a mechanism for cis preferential reverse transcription
Open the record for dataset details and reuse information.
Raw NGS Data for "Deep mutational scanning and machine learning reveal structural and molecular rules governing allosteric hotspots in homologous proteins"
<p>This directory contains relevant fastq files used for deep sequencing analysis in the publication “Deep mutational scanning and machine learning reveal structural and molecular rules governing allosteric hotspots in homologous proteins”. </p> <p>Fastq files are provided for presorted, uninduced and induced populations from DMS experiments of four homologs (TtgR, TetR, RolR, and MphR). Three replicates were performed for each sample.</p> <p>Data analysis of this deep sequencing data was performed using custom scripts, which are described in the methods section of the publication.</p>
High resolution deep mutational scanning of the melanocortin-4 receptor enables target characterization for drug discovery
<p>This record contains supplementary data files related to <a href="https://www.biorxiv.org/content/10.1101/2024.10.11.617882v1">High resolution deep mutational scanning of the melanocortin-4 receptor enables target characterization for drug discovery</a>, described below. For more information regarding statistical modeling and subsequent biological interpretation, please see <a href="https://github.com/octantbio/mc4r-dms">the mc4r-dms Github repository</a>.</p> <p> - <strong>MC4R-DMS-barcode-maps.tar.gz</strong> contains two large TSV files, each containing an oligonucleotide-barcode map for either the CRE or UAS system. Each map contains two columns: (i) the barcode sequence and (ii) the oligonucleotide (variant) identifier.</p> <p> - <strong>MC4R-DMS5-Gs-barcode-counts.tar.gz</strong>, <strong>MC4R-DMS8-Gq-barcode-counts.tar.gz</strong>, and <strong>MC4R-DMS11-Gs-barcode-counts.tar.gz</strong> each contain a set of TSV files representing the raw barcode counts for each sample, with one TSV file per sample. Each individual sample TSV file has two columns: (i) the read count and (ii) the barcode sequence</p> <p> - <strong>sample-properties.tar.gz</strong> contains three small TSV files each with three columns: (i) a sample ID matching the individual sample files in the barcode-counts directories, (ii) a condition or treatment label, and (iii) a condition or treatment dosage if applicable</p> <p> - <strong>MC4R-mapped-counts.tar.gz</strong> contains three TSV files, one per dataset (DMS5, DMS8, and DMS11), containing all barcodes joined to the relevant barcode map across all samples. Each file contains the following columns:</p> <table> <tbody> <tr> <td>sample</td> <td>the sample identifier corresponding to the file names in each barcode-counts directory</td> </tr> <tr> <td>barcode</td> <td>barcode sequence</td> </tr> <tr> <td>count</td> <td>read count</td> </tr> <tr> <td>lib</td> <td>library ID (always OCNT-DMSLIB-0)</td> </tr> <tr> <td>chunk</td> <td>chunk identifier</td> </tr> <tr> <td>wt_aa</td> <td>reference amino acid</td> </tr> <tr> <td>pos</td> <td>amino acid position</td> </tr> <tr> <td>mut_aa</td> <td>mutated amino acid</td> </tr> <tr> <td>wt_codon</td> <td>reference codon sequence</td> </tr> <tr> <td>mut_codon</td> <td>mutated codon sequence</td> </tr> <tr> <td>condition</td> <td>name of treatment condition</td> </tr> <tr> <td>condition_conc</td> <td>dosage of treatment compound, if relevnat</td> </tr> <tr> <td>stop_counts</td> <td>the natural log of the sum of stop-associated barcodes for the containing chunk</td> </tr> </tbody> </table> <p> </p>
Machine Learning on the Impacts of Mutations in the SARS-CoV-2 Spike RBD on Binding Affinity to Human ACE2 based on Deep Mutational Scanning Data
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Structural and Functional Characterization of G Protein-Coupled Receptors with Deep Mutational Scanning
GEO Series GSE144819. Homo sapiens; Escherichia coli. 27 samples. Type: Expression profiling by high throughput sequencing; Other.
Deep mutational scanning of the interaction of JUN's leucine zipper domain and other human bZIPs in different experimental conditions
GEO Series GSE245485. Saccharomyces cerevisiae. 102 samples. Type: Other.
CRISPR/Cas9 recombineering-mediated deep mutational scanning of essential genes in Escherichia coli
GEO Series GSE143629. Escherichia coli. 48 samples. Type: Other.
Deep mutational scanning reveals a tight correlation between protein degradation and toxicity of thousands of non-native aspartoacylase protein variants
GEO Series GSE254639. synthetic construct. 61 samples. Type: Other.
Molecular determinants of Hsp90 recognition of Src kinase revealed by deep mutational scanning
GEO Series GSE218190. Saccharomyces cerevisiae. 8 samples. Type: Other.
Deep mutational scanning quantifies DNA binding and predicts clinical outcomes of PAX6 variants
GEO Series GSE253580. synthetic construct; Saccharomyces cerevisiae. 15 samples. Type: Other.
Deep mutational scanning of the human insulin receptor ectodomain to inform precision therapy for insulin resistance
GEO Series GSE277112. Mus musculus; Escherichia coli. 69 samples. Type: Other.
piggyBac-Mediated Genomic Integration of Linear dsDNA-Based Library for Deep Mutational Scanning in Mammalian Cells
GEO Series GSE226719. Homo sapiens. 19 samples. Type: Other.
Deep mutational scan of a drug efflux pump reveals its structure-function landscape
GEO Series GSE189399. Enterococcus faecalis. 21 samples. Type: Other.
Deep Mutational Scanning Reveals EGFR Mutations Conferring Resistance to the 4th-generation EGFR tyrosine kinase inhibitor BLU-945
GEO Series GSE305057. Mus musculus. 8 samples. Type: Other.
Deep mutational scanning of CYP2C19 reveals a substrate specificity-abundance tradeoff
GEO Series GSE244489. Homo sapiens; synthetic construct. 29 samples. Type: Other.
A focused deep mutational scan on the Env transmembrane and proximal cytosolic regions reveals an absence of sequence features for MA association
GEO Series GSE126136. Human immunodeficiency virus 1. 5 samples. Type: Other.
Deep mutational scan of tapasin-TM, a variant of the MHC class 1 chaperone tapasin
GEO Series GSE311856. Homo sapiens. 2 samples. Type: Other.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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