Find research datasets worth reusing

opencc-by-4.0Nov 2022View details →

Structure prediction from SARS-CoV-2 accessory proteins ORF-6

Structure prediction made with Collabfold for SARS-CoV-2 accessory protein ORF-6. The archive contains both the structure and

opencc-by-4.0Nov 2022View details →

Structure prediction from SARS-CoV-2 accessory proteins ORF-7B

Structure prediction made with Collabfold for SARS-CoV-2 accessory protein ORF-7B. The archive contains both the structure and the logs from the prediction.

opencc-by-4.0Feb 2023View details →

Case studies from: Sequence assignment validation in protein crystal structure models with checkMySequence

Case studies from "Sequence assignment validation in protein crystal structure models with checkMySequence"

opencc-by-4.0Dec 2022View details →

Structural characterization of the protein-material interfacial interactions by using lysine reactivity profiling-mass spectrometry

The exploration of interfacial molecular interactions of protein-material integrations and how material modulate the protein structure and activity are essential to the safety evaluation of biomedical micro/nanomaterials, toxicity estimation and design of nano-drugs, and catalytic activity improvement of bio-inorganic functional hybrids. However, characterizing the interfacial molecular details of protein-micro/nanomaterial hybrids remains a great challenge. Herein, we introduce the protocol of lysine reactivity profiling-mass spectrometry (LRP-MS) strategy for probing the interfacial molecular structures between proteins and micro/nanomaterials. LRP-MS utilizes lysine residues as the endogenous probes to characterize the protein localization orientation, interaction sequence regions, binding sites, and modulated protein structures in the protein-material hybrids, which cannot be achieved by traditional spectroscopy methods. We describe the optimized heavy and light two-step isotope dimethyl labeling strategy for protein-material hybrids under their native and denaturing conditions in sequence. The comparative quantification results of lysine reactivity (referred as NLE) are only dependent on the native microenvironments of lysine local structures. We also highlight other critical steps including protein digestion, elution from materials, data processing, and interfacial structure analysis. The two-step isotope labeling steps need about 5 h, and the whole protocol including digestion, liquid chromatography-tandem mass spectrometry, data processing, and structure analysis needs about 3-5 days.

opencc-by-4.0Mar 2023View details →

Structural adaptation of the single-stranded DNA-binding protein C-terminal to DNA metabolizing partners guides in-hibitor design

<ul> <li>Fluorescence anisotropy metadata and polarization values </li> <li>Isotermal titration calorimetry raw files (protein-ligand and background titrations)</li> <li>Input files for PRALINE calculation in FASTA format</li> <li>CSV file containing the SSB sequences in SMILES format and binding data</li> <li>The input files for the ExoI-bound wtSSB-Ct, E1-sSSB-Ct, and E2-sSSB-Ct and RecO-bound wtSSB-Ct, R1-sSSB-Ct, and R2-sSSB-Ct together with the corresponding trajectory files </li> </ul>

opencc-by-4.0May 2023View details →

AlphaCutter-cleaned SwissProt Protein Structures

This repository contains AlphaCutter-cleaned SwissProt protein structures. Step 1: Download all parts files in this repo. Step 2: run the following cat 20230510_AlphaCutter_cleaned_SwissProt_parts-a? > 20230510_AlphaCutter_cleaned_SwissProt.tar.gz tar zxvf 20230510_AlphaCutter_cleaned_SwissProt.tar.gz

opencc-by-4.0Feb 2022View details →

Salt Induced Transitions in Structural Ensemble of Intrinsically Disordered Proteins

Simulation data and the corrosponding analysis script for the work "Salt Induced Transitions in Conformational Ensemble of Intrinsically Disordered Proteins "  by Hiranmay Maity, Lipika Baidya and Govardhan reddy are deposited here.  Analysis Scripts: The scripts for analysing the simulation data are in analysis_script.zip. The folder contains: <ul> <li> autocorrelation.c : code for calculating end_to_end distance autocorrelation function with time in C. </li> <li> average_property.cpp: code for calculating average property such as radius of gyration (Rg) from trajectory files in C++. </li> <li> calculate_saxs_kratky.c: code for calculating  scattering profile (SAXS and Kratky) from simulation data in C. </li> <li> compute_contact_map.cpp: code for calculating contact map in C. </li> <li> probablity_distribution.c:  code for calculating probablity distribution of Rg in C. </li> <li> structure_factor.c: code for calculating structure factor in C. </li> </ul>

openJul 2023View details →

A deep learning framework combining molecular image and protein structural representation identifies candidate drugs for chronic pain

Official dataset for A deep learning framework combining molecular image and protein structural representation identifies candidate drugs for chronic pain. The related code can be found at <a href="https://github.com/yuxin212/GPCR-public">here</a> and <a href="https://github.com/ChengF-Lab/LISA-CPI">here</a>. The dataset is now public.

opencc-by-4.0Dec 2022View details →

Initial and final MD simulation coordinates for "Multidisciplinary studies with mutated HIV-1 capsid proteins reveal structural mechanisms of lattice stabilization"

Initial and final coordinates for all MD simulations performed for the manuscript: "Multidisciplinary studies with mutated HIV-1 capsid proteins reveal structural mechanisms of lattice stabilization." File uploaded is a ZIP folder, containing sub-folders for each capsid construct (wild type and mutants). Additionally, a README file is given in the top-level folder, which contains a description of the file contents.

opencc-by-4.0Aug 2023View details →

Structure-based self-supervised learning enables ultrafast prediction of stability changes upon mutation at the protein universe scale

Pythia computed all single mutations of E.coli proteome, high quality high quality of Swiss-Prot structures and thermophilic proteins used in analysis.

opencc-by-4.0Aug 2023View details →

Simulation data for "Structural biases in disordered proteins are prevalent in the cell " by Moses & Guadalupe et al. (2023)

This dataset contains complete atomistic ensembles, as reported by Moses & Guadalupe et al.  Structural biases in disordered proteins are prevalent in the cell  David Moses*, Karina Guadalupe*, Feng Yu, Eduardo Flores, Anthony Perez, Ralph McAnelly, Nora M. Shamoon, Gagandeep Kaur, Estefania Cuevas-Zepeda, Andrea D. Merg, Erik W. Martin, Alex S. Holehouse, Shahar Sukenik For all general inquiries regarding this work, please contact Shahar Sukenik directly. For any specific questions regarding this set of simulations, please contact Alex and Shahar.

Fig. 6 in TIM barrel fold and glycan moieties in the structure of ICChI, a protein with chitinase and lysozyme activity

Fig. 6. (A) Three-dimensional (3D) structural model of the ICChI- NAG complex illustrating by Docking. (B) DIMPLOT result revels the interacting amino acid residue during formation of complex.

Fig. 2 in TIM barrel fold and glycan moieties in the structure of ICChI, a protein with chitinase and lysozyme activity

Fig. 2. The three dimensional crystal structure of ICChI where outer ball and stick (green-red) are glycan ligands, Alpha helices (red coil); parallel beta sheets (yellow arrow); random coils or loop (green); (A) topview of ICChI structure, (B) side view of ICChI structure.

Fig. 1 in TIM barrel fold and glycan moieties in the structure of ICChI, a protein with chitinase and lysozyme activity

Fig. 1. (A) Silver stained 12.5% SDS-PAGE gel of purified ICChI. Lane 1 contains molecular weight markers (Pageruler prestained protein ladder, Fermentas SM0671) and lane 2 represents pure and homogeneous ICChI protein shown by arrow. (B) Crystals of ICChI grown in 4–5 days in a hanging drop at 291 K equilibrated against 750 μl reservoir solution containing 0.005 M Cobalt chloride, 0.005 M Cadmium chloride, 0.005 M Magnesium chloride, 0.005 M Nickel chloride and 11% (w/v) PEG 3350 in 0.1 M HEPES buffer, pH 7.0. The tetragonal bipyramide-shaped crystals had a typical size of 300 × 200 × 200 μm. (C) X-ray diffraction from the crystal of ICChI protein produced interference pattern.

Fig. 5. The electron density and N in TIM barrel fold and glycan moieties in the structure of ICChI, a protein with chitinase and lysozyme activity

Fig. 5. The electron density and N-linked glycosylation sites. (A) Asparagine residue 45. (B) Asparagine residue 172. (C) Asparagine residue 194.

Fig. 4 in TIM barrel fold and glycan moieties in the structure of ICChI, a protein with chitinase and lysozyme activity

Fig. 4. The catalytic residues of the ICChI structure are: aspartate 125; glutamate 127 and tyrosine 184. The grey mesh is electron density whereas the amino acid residues are green.

Fig. 6 in Structural characterization of the Pet c 1.0201 PR-10 protein isolated from roots of Petroselinum crispum (Mill.) Fuss

Fig. 6. Visualization of amino acid residues (yellow) that stabilize dimers and are responsible for IgE binding (red) in A: Api g 1.0101 (template 2BK0); B: Pet c 1.0201 in water; C: Pet c 1.0201 in 0.2 M salt. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5 in Structural characterization of the Pet c 1.0201 PR-10 protein isolated from roots of Petroselinum crispum (Mill.) Fuss

Fig. 5. Evolution of the inter-monomeric distances during the MD simulation with relative dispositions of monomeric units at the beginning (0 ns) and the end (200 ns) of each simulation. A: Api g 1.0101 in water; B: Pet c 1.0201 in water; C: Pet c 1.0201 in 0.2 M NaCl. Relative positions at 0 ns and after 200 ns for respective black and red trajectories are visualized; the blue trajectory shows a breakdown of a dimeric form into monomer units. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Structural characterization of the Pet c 1.0201 PR-10 protein isolated from roots of Petroselinum crispum (Mill.) Fuss

Fig. 1. IEF-PAGE (A) and SDS-PAGE (B) of the Coomassie Brilliant blue stained proteins purified from the Petroselinum crispum roots. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3 in Structural characterization of the Pet c 1.0201 PR-10 protein isolated from roots of Petroselinum crispum (Mill.) Fuss

Fig. 3. Multiple sequence alignment of Pet c 1.021 (C0HKF5) purified from the Petroselinum crispum roots with: A – proteins with the highest sequence identity Api g 2 - P92918 and Dau c 1 - AAL76932. B – PR-proteins previously found in Petroselinum crispum (PR1_PETCR - Q40795, PR2_PETCR - P27538, PR11_PETCR - P19417, PR13_PETCR - P19418), C – ribonuclease 1 (P80889) and ribonuclease 2 (P80890) from Panax ginseng with key amino acid residues implicated in the RNase activity (Chadha and Das, 2006) shown in black boxes.