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43 results for “all-atom”
HEroBM: a deep equivariant graph neural network for high-fidelity backmapping from coarse-grained to all-atom structures
<p><span>Molecular simulations play a pivotal role in chemistry, biology, and material sciences, enabling the</span><br><span>study of complex dynamic properties within systems. Coarse-grained (CG) techniques have emerged</span><br><span>as indispensable tools in this domain, facilitating the sampling of large-scale systems and extending</span><br><span>simulation timescales by simplifying system representation. However, CG approaches involve a trade-</span><br><span>off: they sacrifice atomistic details that may be crucial for understanding the underlying processes.</span><br><span>To address this challenge, a recommended strategy is to identify key CG conformations and employ</span><br><span>backmapping methods to retrieve atomistic coordinates. Currently, rule-based methods often yield</span><br><span>suboptimal geometries and rely on energy relaxation, resulting in less-than-optimal outcomes. In</span><br><span>contrast, machine learning techniques offer higher accuracy but may lack transferability between</span><br><span>systems or be tied to specific CG mappings. In this study, we present HEroBM, a dynamic and scalable</span><br><span>method that utilizes deep equivariant graph neural networks and a hierarchical approach to achieve</span><br><span>high-resolution backmapping. HEroBM is capable of handling any type of CG mapping, providing a</span><br><span>versatile and efficient protocol for reconstructing atomistic structures with high accuracy. Grounded</span><br><span>in local principles, HEroBM spans the entire chemical space and can be applied across systems of</span><br><span>varying composition and sizes. We demonstrate the versatility of our framework through a range of</span><br><span>biological systems, including a complex real-case scenario. Here, our end-to-end backmapping approach</span><br><span>accurately generates atomistic coordinates for a G protein-coupled receptor bound to an organic small</span><br><span>molecule within a cholesterol/phospholipid bilayer. The high-fidelity HEroBM backmapping enables</span><br><span>researchers to effortlessly transition between CG and all-atom simulations, opening unprecedented</span><br><span>avenues for molecular investigations.</span></p>
All-atom 500-nano seconds Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 500 nano-seconds (ns) production run was performed for the simulation.</p>
All-atom molecular dynamics simulations of Synechocystis halorhodopsin (SyHR)
<p>The trajectories of all-atom MD simulations of:<br> 1) Cl<sup>-</sup>-bound SyHR in the ground (GR) state (SyHR_monomer_GR_POPC_CHARMM36_200ns)<br> 2) Cl<sup>-</sup>-bound SyHR in the K state (SyHR_monomer_K_POPC_CHARMM36_200ns)<br> in the monomeric form in a POPC bilayer.<br> 3) SO<sub>4</sub><sup>2-</sup>-bound SyHR in the GR state (SyHR_trimer_GR_POPC_CHARMM36_500ns)<br> in the trimeric form in a POPC bilayer.</p> <p>Simulations have been performed using the CHARMM36 force field, running with the GROMACS 2022 package.</p>
Dataset for: All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor
<p>This dataset contains relevant structures, input and other files that are associated with our article "<em>All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor", available at https://pubs.acs.org/doi/full/10.1021/acs.jcim.3c00249</em></p>
All-atom Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 100 ns production run was performed for the simulation.</p>
All-atom Molecular Dynamics Simulations of Meiosis 1-associated protein (M1AP) to Investagate the Impact of Known Missense Mutations Associated with Male Infertility through Non-obstructive Azoospermia
<p>Protein structure of meiosis 1-associated protein (M1AP) was modelled by using GalaxyWeb (from Seok Lab). We used this model to investigate the impact of variants (i.e., S50P, R266Q, P389L, G317R, and L430P) in M1AP which were recently associated with non-obstructive azoospermia (NOA). NOA is a male infertility-related condition causing absence of sperm in the seminal fluid due to meiosis failure. We aimed to elucidate the pathogenicity mechanisms of these five missense NOA-related mutations on M1AP by performing molecular modeling and molecular dynamics (MD) simulations. This dataset includes the results of 1000 ns MD simulations (two repeats, each 500 ns) for each of the mutant and wild-type systems.</p> <p>Systems were prepared in Visual Molecular Dynamics (VMD 1.9.3) by placing them in a TIP3P water box with approximately 20 Å thickness from the protein surface and neutralizing the system charge with 0.15 M KCl. Of note, only protein parts were kept for the submission to reduce the size of files. Nanoscale Molecular Dynamics (NAMD 2.13-CUDA) was used to perform MD simulations with CHARMM36m force field. For pressure and temperature controls, Nosé-Hoover Langevin barostat and Langevin thermostat were used. ShakeH algorithm of NAMD was applied for water molecule constraints. 12 Å cut-off distance was used for van der Waals interactions. Switching function starts at 10 Å and reaches zero at 14 Å. Integration time-step was 2 fs. To compute the long-range Coulomb interactions, the particle-mash Ewald method was used. NPT ensemble was applied for whole simulations. Two step minimization & equilibration procedure was performed: (1) 5,000-step minimization and 1 ns equilibrium with constraints on the protein; (2) 5,000-step minimization and 1 ns equilibrium without the constraints on the protein. All related configuration files for wild-type system were also included to the dataset. Production simulations were run twice along 500 ns by using different random seeds to assign the velocities from Boltzmann distribution (total simulation time for each system was 1000 ns, which are given as 500 ns repeat 1, and 500 ns repeat 2). The production simulations were supplied in the dataset. "out" and "log" files were used for energy analysis.</p> <p>For all analysis scripts, see https://github.com/ugerlevik/M1AP_analysis.</p>
All-atom molecular dynamics simulations of phenylalanine-4-hydroxylase (PAH) tetramer to investigate the impact of two novel heterozygous mutations, p.Y198N and p.Y204F, observed in a classical phenylketonuria patient
<p>Phenylalanine-4-hydroxylase (PAH) tetramer system (Robetta modelling to complete the structure with template PDB ID: 6hyc) with parametrised BH<sub>4</sub> ligand (parameters are available in the dataset) and Fe(II) metal ions in a TIP3P water box ionised with 0.15 M KCl were presented as wild-type and carrying two novel mutations as Y198N on dimeric chains A and B, and Y204F on dimeric chains C and D. In addition, E353 and E422 are protonated as predicted by PROPKA. BH<sub>4</sub> molecule parametrization was performed by using GAFF, Antechamber and “amb2chm_par.py” program of Amber2018.</p> <p>5,000-step minimization and 1 ns equilibration were performed by fixing the protein to relax the system. Then, another 5,000-step minimization and 1 ns equilibration were performed without any constraints, except the SHAKE algorithm on water molecules, to relax the protein and system. The production simulations were performed along 100 ns trajectory at 310 K collected under NpT ensemble.</p> <p>All system preparation and simulation details for this dataset is available with the related background, results and conclusions in the following article:</p> <p>Tolga Aslan, Aslı Yenenler-Kutlu, Umut Gerlevik, Ayşe Çiğdem Aktuğlu Zeybek, Ertuğrul Kıykım, Osman Uğur Sezerman & Necla Birgul Iyison (2021) Identifying and elucidating the roles of Y198N and Y204F mutations in the PAH enzyme through molecular dynamic simulations, Journal of Biomolecular Structure and Dynamics, DOI: <a href="https://doi.org/10.1080/07391102.2021.1921619">10.1080/07391102.2021.1921619</a></p>
All-atom Gromacs Trajectory of POPC/TOCL bilayer mixture
<p>All-atom bilayer mixture of POPC/TOCL 1:1 simulated in an NPT ensemble with Gromacs and the CHARMM36 force field from Castillo et al, 2022, Mol. Pharmaceutics. 19:1839-1852 (<a href="https://doi.org/10.1021/acs.molpharmaceut.1c00926">https://doi.org/10.1021/acs.molpharmaceut.1c00926</a>). The trajectory represents 540 ns with frames output every 20 ps. The bilayer has 120 lipids total (60 lipids per leaflet) and is hydrated with 100 waters/lipid and sodium ions to neutralize the system. The simulation was done at 37C (310.15K).</p> <p>POPC is 16:0,18:1 PC; TOCL is tetraoleoyl cardiolipin</p>
All-atom Gromacs Trajectory of POPC/POPE/TOCL bilayer mixture
<p>All-atom bilayer mixture of POPC/POPE//TOCL 50/25/25 mol% simulated in an NPT ensemble with Gromacs and the CHARMM36 force field from Castillo et al, 2022, Mol. Pharmaceutics. 19:1839-1852 (<a href="https://doi.org/10.1021/acs.molpharmaceut.1c00926">https://doi.org/10.1021/acs.molpharmaceut.1c00926</a>). The trajectory represents 570 ns with frames output every 20 ps. The bilayer has 120 lipids total (60 lipids per leaflet) and is hydrated with 75 waters/lipid and sodium ions to neutralize the system. The simulation was done at 37C (310.15K).</p> <p>POPC is 16:0,18:1 PC; POPE is 16:0,18:1 PE; TOCL is tetraoleoyl cardiolipin</p>
All-atom Gromacs Trajectory of POPE/TOCL bilayer mixture
<p>All-atom bilayer mixture of POPE/TOCL 1:1 simulated in an NPT ensemble with Gromacs and the CHARMM36 force field from Castillo et al, 2022, Mol. Pharmaceutics. 19:1839-1852 (<a href="https://doi.org/10.1021/acs.molpharmaceut.1c00926">https://doi.org/10.1021/acs.molpharmaceut.1c00926</a>). The trajectory represents 530 ns with frames output every 20 ps. The bilayer has 120 lipids total (60 lipids per leaflet) and is hydrated with 100 waters/lipid and sodium ions to neutralize the system. The simulation was done at 37C (310.15K).</p> <p>POPE is 16:0,18:1 PE; TOCL is tetraoleoyl cardiolipin</p>
All-atom MD simulations of POPC/SSM/CHOL mixture
<p>All-atom MD simulation of lipid bilayer in water, with composition POPC/SSM/CHOL, at 321.15 K, NPT conditions.</p> <p>Force field: CHARMM36. Water model: TIP3P. Number of molecules: 100 POPC + 100 SSM + 100 CHOL + 9000 SOL + 18 Na+ + 18 Cl-.</p> <p>SSM is (d18:1/18:0) sphingomyelin.</p> <p>Duration of the simulation: 300 ns.</p>
hnRNPA1* and hSUMO-hnRNPA1* all-atom MD trajectories and protein-water rescaling MD trajectories
<pre>All-atom trajectories of hnRNPA1* and hSUMO-hnRNPA1* with varying NaCl concentrations back-mapped from CG simulations. CG trajectories of hnRNPA1* and hSUMO-hnRNPA1* with varying PW-rescaling parameter lambda (theta in file names). Supporting data for "Interplay of folded domains and the disordered low-complexity domain in mediating hnRNPA1 phase separation".</pre> <pre> </pre>
All-atom molecular dynamics simulations of incomplete ATP synthase rotor rings with unusually high stoichiometry predicted by the AlphaFold2-based method
<p>The trajectories of all-atom MD simulations of <span>AlphaFold2 4, 11, 16 or 18-mer structures of the subunit <em>c</em> from<br></span><span><em>Candidatus Kryptonium thompsoni</em></span><span> (CKt_Nmer_lipid_mix_CHM36m_303K_500ns) and <br></span><span><em>Thalassoglobus polymorphus </em>(Tp_Nmer_lipid_mix_CHM36m_303K_500ns), and <br>AlphaFold2 11-mer structure of the subunit <em>c</em> from <em>Spinacia oleracea</em> (So_11mer-c20_POPC_CHM36m_303K_300ns) </span><span>in a lipid bilayer.</span></p> <p><span>Simulations have been performed using the CHARMM36m force field, running with the GROMACS 2022 package.</span></p>
Generalized biomolecular modeling and design with RoseTTAFold all-atom
<p>Although AlphaFold2 (AF2) and RoseTTAFold (RF) have transformed structural biology by enabling high-accuracy protein structure modeling, they are unable to model covalent modifications or interactions with small molecules and other non-protein molecules that can play key roles in biological function. Here, we describe RoseTTAFold All-Atom (RFAA), a deep network capable of modeling full biological assemblies containing proteins, nucleic acids, small molecules, metals, and covalent modifications given the sequences of the polymers and the atomic bonded geometry of the small molecules and covalent modifications. Following training on structures of full biological assemblies in the Protein Data Bank (PDB), RFAA has comparable protein structure prediction accuracy to AF2, excellent performance in CAMEO for flexible backbone small molecule docking, and reasonable prediction accuracy for protein covalent modifications and assemblies of proteins with multiple nucleic acid chains and small molecules which, to our knowledge, no existing method can model simultaneously. By fine-tuning on diffusive denoising tasks, we develop RFdiffusion All-Atom (RFdiffusionAA), which generates binding pockets by directly building protein structures around small molecules and other non-protein molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we design and experimentally validate proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and optically active bilin molecules with potential for expanding the range of wavelengths captured by photosynthesis. We anticipate that RFAA and RFdiffusionAA will be widely useful for modeling and designing complex biomolecular systems.</p>
All-atom simulations elucidate the molecular mechanism underlying RNA-membrane interactions
<p>Topology files and frames extracted from the minimum of the free energy profile F(d_z) (or F(d_min) for single-stranded RNAs), within 2.5kBT. These files can be used to reproduce the hydrogen bond analyses in the manuscript.</p> <p>Scripts which were used to extract hydrogen bond information are available on <a href="https://github.com/salvatoredimarco/rna-membrane">https://github.com/salvatoredimarco/rna-membrane</a></p> <p><strong>Systems:</strong></p> <p>4xN: nucleosides</p> <p>4xN2: dinucleotides</p> <p>4xN3: trinucleotides</p> <p>4xN_OPC: nucleosides simulated with OPC water model. Energy threshold is here 1.0*kBT, because of weaker binding.</p> <p>1xGA, 1xGU, 1xGC, 1xCU</p> <p>1xGGC, 1xGCG</p> <p>1xquadruplex: G-quadruplex</p> <p>1xstrand: 19-mer RNA strand</p> <p>1xhairpin: 16-mer folded hairpin</p> <p>1x16mer_elong: 16-mer unfolded, restrained</p> <p>2x16mer_loose1/2: 16-mer unfolded, unrestrained</p>
All-atom molecular dynamics simulations of synaptic vesicle fusion I: a glimpse at the primed Synaptotagmin-SNARE-complexin complex
<p>Synaptic vesicles are primed into a state that is ready for fast neurotransmitter release upon Ca<sup>2+</sup>-binding to Syt1. This state likely includes trans-SNARE complexes between the vesicle and plasma membranes that are bound to Syt1 and complexins. However, the nature of this state and the steps leading to membrane fusion are unclear, in part because of the difficulty of studying this dynamic process experimentally. To shed light into these questions, we performed all-atom molecular dynamics simulations of systems containing trans-SNARE complexes between two flat bilayers or a vesicle and a flat bilayer with or without fragments of Syt1 and/or complexin-1. Our results need to be interpreted with caution because of the limited simulation times and the absence of key components, but suggest mechanistic features that may control release and help visualize potential states of the primed Syt1-SNARE-complexin-1 complex. In particular, the simulations suggest that SNAREs alone induce formation of extended membrane-membrane contact interfaces that may fuse slowly, and that the primed state contains macromolecular assemblies of trans-SNARE complexes bound to the Syt1 C<sub>2</sub>B domain and complexin-1 in a spring-loaded configuration that prevents premature membrane merger and formation of extended interfaces but keeps the system ready for fast fusion upon Ca<sup>2+</sup> influx.</p>
All-atom molecular dynamics simulations of iRFP713/C15S/V254C/N136R
<p>The trajectories of all-atom MD simulations of monomeric and dimeric iRFP713/C15S/V254C/N136R with PCB (phycocyanobilin) and BV (biliverdin).</p> <p> </p> <p>Simulations have been performed using the CHARMM36 force field, running with the GROMACS 2022 package.</p>
Molecular dynamics trajectories of pYEEI:SH2 recognition, unbiased, at all-atom resolution.
<div> </div> <p>Set of 772 all-atom trajectories simulated from an unbound (apo) configuration of the human p56 -lck tyrosine kinase SH2 domain with its high-specificity phosphopeptide recognition substrate pYEEI (initial structure based on PDB:<a href="https://www.rcsb.org/structure/1LKK">1LKK</a> ). Approximately 24 trajectories spontaneously reach a bound state with ligand RMSD < 2 Â from the crystal. System building and run details are described in [1].</p> <p>A preliminary version of this dataset have been analyzed and discussed in [1] (approx 200 ns per trajectory were available and used in [1]). </p> <p>The trajectories provided here are extended to ~800 ns each, for a total of ~640 μs sampled time. The full dataset is analyzed in [2] with a SOM-based technique.</p> <div> <h2>Notes</h2> </div> <div> <ul> <li>These are all-atom simulations (with TIP3P water). Water molecules have been stripped off from these files (filtered).</li> <li>Not all trajectories have the same length. Some are cut short due to the distributed computing setup.</li> <li>Frame-to-frame interval is 1 ns.</li> </ul> </div> <h2>Acknowledgments</h2> <p>We thank the volunteers of the GPUGRID.net project for donating computing time.</p> <p> </p> <h2>References</h2> <p>[1] T. Giorgino, I. Buch, and G. De Fabritiis. <a href="https://pubs.acs.org/doi/10.1021/ct300003f">Visualizing the Induced Binding of SH2-Phosphopeptide</a>, J. Chem. Theory Comput. 2012, 8, 4, 1171-1175. doi:10.1021/ct300003f</p> <p>[2] Lara Callea, Camilla Caprai, Laura Bonati, Toni Giorgino, Stefano Motta. Self-Organizing Maps of Unbiased Ligand-Target Binding Pathways and Kinetics. J. Chem. Phys, 2024. https://doi.org/10.1063/5.0225183 </p> <p> </p> <div> </div> <div> <p> </p> </div>
Molecular dynamics simulation input files: Dynamics of amphiphilic poly($\varepsilon$-caprolactone) micelles with doxorubicin and transition temperature predictions using all-atom molecular dynamics simulation
<p>The files uploaded contain the input files for simulations:<br><br>1) P10_Solv: Input files for drug-free micelles.<br>2) Micelle_Solv: Input files for drug-loaded micelles.</p>
All-atom MD trajectory TOCL:POPC (20%), 50mM KCl
<p>~400-ns MD simulation of a lipid bilayer, which monolayer was composed of 44 POPC (1-Palmitoyl-2-oleoylphosphatidylcholine) molecules and 6 TLCL (tetra-linoeoyl-cardiolipin) molecules. The background electrolyte is KCl; these ions were added in that amount, which imitates 50-mM ionic force in the bulk. The water amount is large (more than 140 water molecules per lipid), allowing it to equilibrate the electric double layer at a relatively low ionic force.</p> <p>TIP3P water model and CHARMM36 force field were used; the double-deprotonated form of cardiolipin was used (TLCL2). Production simulation was performed with MD integrator (2-fs step, bonds to hydrogen atoms were constrained), Nose-Hoover thermostat (303K, 1-ps time constant) and Parinello-Rahman semi-isotropic barostat (5-ps time constant, water compressibility). PME was used for electrostatics; cut-off radii were set to 1.2 nm. VDW switch radius was set to 1.0 nm.</p> <p>Resulting trajectories deposited:</p> <ul> <li><strong>COMBINED-50ps.trr</strong> [373 ns length, 50-ps step, with velocities]</li> <li><strong>COMBINED-10ps-100ns.trr</strong> [last 100 ns, 10-ps step, with velocities]</li> <li><strong>COMBINED.edr</strong> [373 ns length, 2-ps step]</li> </ul> <p>The additional ZIP archive contains intermediate TPR and MDP files and a force field folder.</p>
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