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873 results for “ligands”
ANI-2X test Dataset and PDB ligand molecule files
<p>Collected dataset for ANI-2X/CG-BS performance testing and ligands in PDB bound conformation which could have multiconformations.</p>
Potentiometric data for determination of Ge(IV) complexes with low molecular weight organic O/N-donor ligands
<p>Contains an archive of potentiometric titration data that served to determine the stability constants of Ge(IV) complexes with small organic O/N donor ligands. Files are in machine readable XML, generated by HYPERQUAD 6.0.1 (Protonic Software, UK). Data may be extracted from the files manually for use by other modeling codes. An annotated model file is provided to explain the structure of the files and a 'READ_ME' file with further info. </p>
FABind: Fast and Accurate Protein-Ligand Binding
<p>The preprocessed PDBbind2020 dataset for paper "FABind: Fast and Accurate Protein-Ligand Binding" with associated code at <a href="https://github.com/QizhiPei/FABind">https://github.com/QizhiPei/FABind</a>.</p><p>The dataset files are saved as .pt and lmdb file for the convenience of use.</p><p>We follow the same preprocessing as TankBind.<br><br><strong>Paper Abstract:</strong></p><p>Modeling the interaction between proteins and ligands and accurately predicting their binding structures is a critical yet challenging task in drug discovery. Recent advancements in deep learning have shown promise in addressing this challenge, with sampling-based and regression-based methods emerging as two prominent approaches. However, these methods have notable limitations. Sampling-based methods often suffer from low efficiency due to the need for generating multiple candidate structures for selection. On the other hand, regression-based methods offer fast predictions but may experience decreased accuracy. Additionally, the variation in protein sizes often requires external modules for selecting suitable binding pockets, further impacting efficiency. In this work, we propose FABind, an end-to-end model that combines pocket prediction and docking to achieve accurate and fast protein-ligand binding. FABind incorporates a unique ligand-informed pocket prediction module, which is also leveraged for docking pose estimation. The model further enhances the docking process by incrementally integrating the predicted pocket to optimize protein-ligand binding, reducing discrepancies between training and inference. Through extensive experiments on benchmark datasets, our proposed FABind demonstrates strong advantages in terms of effectiveness and efficiency compared to existing methods. Our code is available at <a href="https://github.com/QizhiPei/FABind">https://github.com/QizhiPei/FABind</a>.</p>
Ising model for nanocrystal ligand exchange
Open the record for dataset details and reuse information.
Molecular dynamics simulation data of designed cyclic peptide - ligand 4 (receptor-ligand bound)
<p>Trajectories of receptor-ligand bound simulation and simulation set-up files of designed cyclic peptide as MDM2 binders. This dataset contains simulations of ligand 4. Due to the file size limitation, ligand 1-3 data and simulation set-up files can be found here: http://doi.org/10.5281/zenodo.3780463<br> The original paper of these designed cyclic peptide: Danelius, E., Pettersson, M., Bred, M., Min, J., Waddell, M. B., Guy, R. K., et al. (2016). Flexibility is important for inhibition of the MDM2/p53 protein–protein interaction by cyclic β-hairpins. <em>Org. Biomol. Chem.</em>, <em>14</em>(44), 10386–10393. http://doi.org/10.1039/C6OB01510G</p>
Molecular dynamics simulation data of designed cyclic peptide - ligand 1-3 (receptor-ligand bound)
<p>Trajectories of receptor-ligand bound simulation and simulation set-up files of designed cyclic peptide as MDM2 binders. This dataset contains simulations of ligand 1-3. Ligand 4 data can be found here: http://doi.org/10.5281/zenodo.3782629<br> The original paper of these designed cyclic peptide: Danelius, E., Pettersson, M., Bred, M., Min, J., Waddell, M. B., Guy, R. K., et al. (2016). Flexibility is important for inhibition of the MDM2/p53 protein–protein interaction by cyclic β-hairpins. <em>Org. Biomol. Chem.</em>, <em>14</em>(44), 10386–10393. http://doi.org/10.1039/C6OB01510G</p>
Plasticity, ligand conformation and enzyme action of Mycobacterium smegmatis MutT1
<p><em>Mycobacterium smegmatis</em> MutT1 (<em>Ms</em>MutT1) is a sanitation enzyme made up of an N-terminal Nudix hydrolase domain and a C-terminal domain resembling a histidine phosphatase. It has been established that the action of MutT1 on 8-oxo-dGTP, 8-oxo-GTP and diadenosine polyphosphates is modulated by intermolecular interactions. In order to further explore this and to elucidate the structural basis of its differential action on 8-oxo-NTPs and unsubstituted NTPs, the crystal structures of complexes of <em>Ms</em>MutT1 with 8-oxo-dGTP, GMPPNP and GMPPCP have been determined. Replacement soaking was used in order to ensure that the complexes were isomorphous to one another. Analysis of the structural data led to the elucidation of a relationship between the arrangements of molecules observed in the crystals, molecular plasticity and the action of the enzyme on nucleotides. The dominant mode of arrangement involving a head-to-tail sequence predominantly leads to the generation of NDPs. The other mode of packing arrangement appears to preferentially generate NMPs. This work also provides interesting insights into the dependence of enzyme action on the conformation of the ligand. The possibility of modulating the enzyme action through differences in intermolecular interactions and ligand conformations makes <em>Ms</em>MutT1 a versatile enzyme.</p>
Plasticity, ligand conformation and enzyme action of Mycobacterium smegmatis MutT1
<p><em>Mycobacterium smegmatis</em> MutT1 (<em>Ms</em>MutT1) is a sanitation enzyme made up of an N-terminal Nudix hydrolase domain and a C-terminal domain resembling a histidine phosphatase. It has been established that the action of MutT1 on 8-oxo-dGTP, 8-oxo-GTP and diadenosine polyphosphates is modulated by intermolecular interactions. In order to further explore this and to elucidate the structural basis of its differential action on 8-oxo-NTPs and unsubstituted NTPs, the crystal structures of complexes of <em>Ms</em>MutT1 with 8-oxo-dGTP, GMPPNP and GMPPCP have been determined. Replacement soaking was used in order to ensure that the complexes were isomorphous to one another. Analysis of the structural data led to the elucidation of a relationship between the arrangements of molecules observed in the crystals, molecular plasticity and the action of the enzyme on nucleotides. The dominant mode of arrangement involving a head-to-tail sequence predominantly leads to the generation of NDPs. The other mode of packing arrangement appears to preferentially generate NMPs. This work also provides interesting insights into the dependence of enzyme action on the conformation of the ligand. The possibility of modulating the enzyme action through differences in intermolecular interactions and ligand conformations makes <em>Ms</em>MutT1 a versatile enzyme.</p>
Plasticity, ligand conformation and enzyme action of Mycobacterium smegmatis MutT1
<p><em>Mycobacterium smegmatis</em> MutT1 (<em>Ms</em>MutT1) is a sanitation enzyme made up of an N-terminal Nudix hydrolase domain and a C-terminal domain resembling a histidine phosphatase. It has been established that the action of MutT1 on 8-oxo-dGTP, 8-oxo-GTP and diadenosine polyphosphates is modulated by intermolecular interactions. In order to further explore this and to elucidate the structural basis of its differential action on 8-oxo-NTPs and unsubstituted NTPs, the crystal structures of complexes of <em>Ms</em>MutT1 with 8-oxo-dGTP, GMPPNP and GMPPCP have been determined. Replacement soaking was used in order to ensure that the complexes were isomorphous to one another. Analysis of the structural data led to the elucidation of a relationship between the arrangements of molecules observed in the crystals, molecular plasticity and the action of the enzyme on nucleotides. The dominant mode of arrangement involving a head-to-tail sequence predominantly leads to the generation of NDPs. The other mode of packing arrangement appears to preferentially generate NMPs. This work also provides interesting insights into the dependence of enzyme action on the conformation of the ligand. The possibility of modulating the enzyme action through differences in intermolecular interactions and ligand conformations makes <em>Ms</em>MutT1 a versatile enzyme.</p>
Plasticity, ligand conformation and enzyme action of Mycobacterium smegmatis MutT1
<p><em>Mycobacterium smegmatis</em> MutT1 (<em>Ms</em>MutT1) is a sanitation enzyme made up of an N-terminal Nudix hydrolase domain and a C-terminal domain resembling a histidine phosphatase. It has been established that the action of MutT1 on 8-oxo-dGTP, 8-oxo-GTP and diadenosine polyphosphates is modulated by intermolecular interactions. In order to further explore this and to elucidate the structural basis of its differential action on 8-oxo-NTPs and unsubstituted NTPs, the crystal structures of complexes of <em>Ms</em>MutT1 with 8-oxo-dGTP, GMPPNP and GMPPCP have been determined. Replacement soaking was used in order to ensure that the complexes were isomorphous to one another. Analysis of the structural data led to the elucidation of a relationship between the arrangements of molecules observed in the crystals, molecular plasticity and the action of the enzyme on nucleotides. The dominant mode of arrangement involving a head-to-tail sequence predominantly leads to the generation of NDPs. The other mode of packing arrangement appears to preferentially generate NMPs. This work also provides interesting insights into the dependence of enzyme action on the conformation of the ligand. The possibility of modulating the enzyme action through differences in intermolecular interactions and ligand conformations makes <em>Ms</em>MutT1 a versatile enzyme.</p>
Open Data for Role of Inter-Cluster and Inter-Ligand Dynamics of [Ag25(DMBT)18]– Nanoclusters by Multinuclear Magnetic Resonance Spectroscopy.
<p>Open Data for publication "Role of Inter-Cluster and Inter-Ligand Dynamics of [Ag<sub>25</sub>(DMBT)<sub>18</sub>]<sup>–</sup> Nanoclusters by Multinuclear Magnetic Resonance Spectroscopy" published in The Journal of Physical Chemistry.</p>
KLIFS: A Knowledge-Based Structural Database To Navigate Kinase–Ligand Interaction Space
<p>The Kinase-Ligand Interaction Fingerprints and Structure database (KLIFS) contains a consistent structural alignment and deconstruction of the kinase domains from over 1734 PDB structures covering 190 different human kinases. </p> <p>Every crystal structure was structurally aligned in a consistent manner, subsequently broken down from the full complex into separate structural parts: the protein, the orthosteric ligand-binding pocket (85 aligned residues covering the catalytic cleft), orthosteric and allosteric ligand(s), ions, organometallics, cofactors, and waters. By combining the pocket with the orthosteric ligand all interactions are annotated using Interactions FingerPrints (IFPs) for systematic comparison.</p>
Proper modelling of ligand binding requires an ensemble of bound and unbound states
<p>Crystallographic data for structures described in the manuscript "Proper modelling of ligand binding requires an ensemble of bound and unbound states".</p>
LABind: Identifying Protein Binding Ligand-Aware Sites via Learning Interactions Between Ligand and Protein
<p>This dataset contains the three datasets used in LABind. For each dataset, we have saved the corresponding FASTA sequence files, the associated labels (0 for non-binding and 1 for binding), and the corresponding PDB files.</p>
Target-ligand binding affinity from single point enthalpy calculation and elemental composition
<p>This repository contains supporting files for the manuscript entitled: Target-ligand binding affinity from single point enthalpy calculation and elemental composition.</p>
Exploring Data-Driven Chemical SMILES Tokenization Approaches to Identify Key Protein-Ligand Binding Moieties
<p>This repository contains materials for the paper, "Exploring Data-Driven Chemical SMILES Tokenization Approaches to Identify Key Protein-Ligand Binding Moieties", published in <a href="https://onlinelibrary.wiley.com/doi/10.1002/minf.202300249">Molecular Informatics.</a></p> <p>`data.zip` contains vocabulary and dataset files for identifying chemical vocabularies and key chemical words associated with protein ligand binding. </p> <p>`results.zip` comprises outputs specific to vocabularies and datasets, as well as various related statistics.</p> <p> </p> <p> </p>
Data from: Compromise docking power evaluation of liganded crystal structures of Mpro SARS-CoV-2
<p>A set of 406 liganded SARS-CoV-2 M<sup>pro</sup> crystal structures originally downloaded from RCSB PBD database is provided. Ligand and protein files are processed and corrected for various types of structural errors and are provided in pdbqt and mol2 formats for immediate use in molecular docking programs AutoDock, AutoDock Vina, and PLANTS. Data are utilized in calculations of newly defined compromise docking power to monitor the performance of above-mentioned software. The provided dataset can also be used for benchmarking of other software and molecular docking protocols on liganded SARS-CoV-2 M<sup>pro</sup> systems.</p>
A Comprehensive Dataset of protein-protein interactions and Ligand Binding Pockets for Advancing Drug Discovery
<p>This dataset presents a comprehensive collection of structural data related to protein-protein interactions (PPIs) and ligand binding pockets. The dataset includes high-quality structural information that can aid researchers in the fields of bioinformatics, structural biology, and drug discovery. It encompasses a diverse set of PPI complexes and associated ligands, enabling detailed investigations into molecular interactions at the atomic level. This article introduces an indispensable resource designed to unlock the full potential of PPIs while pioneering a novel metric for pocket similarity for repurposing protein partners.</p>
03_HTMD_Bulk: Incorporating prior knowledge in the seeds of adaptive sampling molecular dynamics simulations of ligand transport in enzymes with buried active sites
<p># Contains input, output and restart files used for HTMD (High-throughput molecular dynamics) adaptive sampling simulations at 310K for Bulk schemes. </p> <p># The forders are organized as:</p> <p>Input_files/ # Contains .parm7 and .rst files of 30 seed conformations obtained from equilibrations and used for adaptive sampling inputs, **run_adaptiveMD.py** : Script file executing the adaptive sampling using distance matrix considering protein C-alpha atoms and heavy atoms of DBE.<br>rep1/<br>└── adaptive_data/<br> ├── generators/ # Contains the initial generator files provided by the user<br> │ ├── ../structure.parm7<br> │ ├── ../input.ncrst<br> │ └── ...<br> ├── input/ # Contains the files needed to start all simulations of all epochs (automatically generated)<br> │ ├── ../equil1.log<br> │ ├── ../input.ncrst<br> │ └── ...<br>└──rep2/<br>...<br>...<br> </p> <p> </p> <p> </p>
06_HTMD_Tunnels: Incorporating prior knowledge in the seeds of adaptive sampling molecular dynamics simulations of ligand transport in enzymes with buried active sites
<p># Contains input, output and restart files used for HTMD (High-throughput molecular dynamics) adaptive sampling simulations at 310K for Tunnels schemes. </p> <p># The folders are organized as:</p> <p>Input_files/ # Contains .parm7 and .rst files of 30 seed conformations obtained from equilibrations and used for adaptive sampling inputs, <em>run_adaptiveMD.py</em> : Script file executing the adaptive sampling using distance matrix considering protein C-alpha atoms and heavy atoms of DBE.<br>rep1/<br>└── adaptive_data/<br> ├── generators/ # Contains the initial generator files provided by the user<br> │ ├── ../structure.parm7<br> │ ├── ../input.ncrst<br> │ └── ...<br> ├── input/ # Contains the files needed to start all simulations of all epochs (automatically generated)<br> │ ├── ../equil1.log<br> │ ├── ../input.ncrst<br> │ └── ...<br>└──rep2/<br>...<br>...<br> </p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
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.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.