Tleap

Manufactured by Amber Molecular Dynamics

Sourced in United States

TLEaP is a software package used for the preparation of molecular dynamics simulations. It provides a graphical user interface for the setup and manipulation of molecular systems, including the assignment of force field parameters and the generation of input files for common molecular dynamics simulation software.

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Lab products found in correlation

6 protocols using tleap

Molecular Dynamics Simulations of Allergen Structures

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Starting structures for the cpH-MD simulations were prepared from the available crystal structures on the protein data bank, using the structures 5EVE (Amb a 8), 5EM0 (Art v 4) and 5NZB (Bet v 2) (30 (link)). All residues not corresponding to the actual allergen itself were removed during setup. Topologies and starting coordinates were prepared with the tLEaP module of AmberTools 20 (Case et al.), using the ff99SB force field (31 (link)), along with modification necessary for cpH-MD (32 (link)–34 (link)). Generalized Born (GB) radii of the titratable oxygens in the aspartate and glutamate side chains were reduced to 1.3 Å, as suggested by Swails et al. (34 (link)). Each system was soaked in a truncated octahedral box of TIP3P (35 (link)) water with a minimum wall distance of 10 Å. All systems were equilibrated with an extensive protocol before production (36 (link), 37 (link)).
Starting structures for the GaMD simulations were extracted from the obtained cpH-MD trajectories as follows: For each system, at each simulated pH value, the trajectories were clustered into 5 clusters with the program cpptraj of AmberTools 20 (38 ) using a hierarchical agglomerative approach and average linkage. Each cluster structure was then set up for subsequent GaMD simulations with the program tLEaP (38 ) using the ff14SB force field (39 (link)) and a cubic TIP3P water box, with 10 Å padding.

Hofer F., Fischer A.L., Kamenik A.S., Waibl F., Fernández-Quintero M.L, & Liedl K.R. (2022). pH-dependent structural diversity of profilin allergens determines thermal stability. Frontiers in Allergy, 3, 1007000.

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Conformational Exploration of Cyclic RGD Peptides

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In this study, we considered three RGD cyclic pentapeptides selected from the work of the Kessler group 39, 40 . The sequences of these peptides are presented in Table 1. For both the REMD simulations and EGSCyP method, all the cyclic structures were generated using UCSF-Chimera 70 . This tool allows modeling non-natural amino acids, such as D-amino acids or N-methylated ones. The cyclization was made head-to-tail, i.e., a peptidic bond was created between the N-ter and the C-ter amino acids. The exhaustive exploration process performed by EGSCyP is independent of the initial conformation. The topology files were created with Tleap from AmberTools 16 51 , using the Amber ff96 force field 52 . The Amber topologies and partial charges of the N-methylated residues were computed with the RED-Server 71 . For the REMD simulations, the Amber topology files were converted into Gromacs topology files with Acpype

Jusot M., Stratmann D., Vaisset M., Chomilier J, & Cortés J. (2018). Exhaustive Exploration of the Conformational Landscape of Small Cyclic Peptides Using a Robotics Approach. Journal of chemical information and modeling, 58(11).

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Structural Analysis of TSR2 O-Fucose

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A crystal structure of two repeating units of the thrombospondin-1 type 1 (PDB code 1LSL) was obtained from the PDB server (rcsb.org). The structure contained two β-linked fucose residues attached at Thr 432 and 489 and six disulfide bonds, which were defined using the TLEaP module of AmberTools (48 ). Prior to solvation, a single chloride ion was added using TLEaP to neutralize the overall charge on the system. Analysis focused on O-fucose of TSR2 because the O-fucose on TSR3 was too close to the C-terminus in the structure.

Berardinelli S.J., Eletsky A., Valero-González J., Ito A., Manjunath R., Hurtado-Guerrero R., Prestegard J.H., Woods R.J, & Haltiwanger R.S. (2022). O-fucosylation stabilizes the TSR3 motif in thrombospondin-1 by interacting with nearby amino acids and protecting a disulfide bond. The Journal of Biological Chemistry, 298(6), 102047.

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Molecular Dynamics Simulation of Luteolin-Protein Interactions

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The general AMBER force field was used to model luteolin, while the ff14SB force field was used to model proteins [30 (link)]. Hydrogen atoms were added using the tLEAP module of the Amber Tools program. Initial parameterization of luteolin was carried out using the Gaussian 09 software. All the molecular dynamics simulations were performed with the Sander and Pmemd modules of the AMBER14 software [31 (link)]. Each complex was placed in a TIP3P water box after the addition of antechamber ions to maintain the system electrically neutral, leading to a minimum of 10.0 Å between the solvent and the nearest box edge. In the MD simulation process, nonbonded interactions were calculated utilizing the Particle-Mesh Ewald method with a cutoff of 10 Å [32 (link)], and the SHAKE algorithm was used to constrain all bonds involving hydrogen atoms with a 2 fs timestep [33 (link)]. Under constant volume conditions, the system was heated from 0 K to 300 K within 60 ps, followed by equilibration of the solvent density at a constant pressure system (T = 300 K, P = 1 atm) and finally, sampling for 100 ns at constant pressure, saving one frame (conformation) per ps for subsequent analysis.

Huang R., Dong R., Wang N., Lan B., Zhao H, & Gao Y. (2021). Exploring the Antiglioma Mechanisms of Luteolin Based on Network Pharmacology and Experimental Verification. Evidence-based Complementary and Alternative Medicine : eCAM, 2021, 7765658.

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Molecular Dynamics Simulation of PAN Domain

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MD simulations were initiated from the top five models generated with ColabFold^{27 (link),62 (link)} of the WT and 4Cys-4Ala mutant PAN domain. The program tleap from AmberTools20⁶³ was used to prepare the parameter and coordinate files for each structure. The ff14SB force field^{64 (link)} and TIP3P water model^{65 (link)} were used to describe the protein and solvent, respectively. Energy minimization was performed using sander from AmberTools20. At least a 12 Å solvent buffer between the protein and the periodic images. Sodium and chloride ions were added to neutralize charge and maintain a 0.10 M ion concentration. The simulations were performed with OpenMM version 7.5.1^{66 (link)}) on the Cuda platform (version 11.0.3) using Python 3.8.0. ParmEd was used to incorporate the force field parameters into the OpenMM platform^{67 (link)}. The Langevin integrator and Monte Carlo barostat were used to maintain the systems at 300 K and 1 bar, respectively. Direct non-bonded interactions were calculated up to a 12 Å distance cutoff. All bonds involving hydrogen atom were constrained to their equilibrium values. The particle mesh Ewald method was used to compute long-range Coulombic interactions^{68 (link)}. A 2 fs integration time step was used with energies and positions written every 2 ps.

Pal D., De K., Shanks C.M., Feng K., Yates T.B., Morrell-Falvey J., Davidson R.B., Parks J.M, & Muchero W. (2022). Core cysteine residues in the Plasminogen-Apple-Nematode (PAN) domain are critical for HGF/c-MET signaling. Communications Biology, 5, 646.

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Computational Modeling of Dipeptide Derivatives

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All studied dipeptides, namely [26 (link)] aspartic acid–β-methyl ester derivative (Lig1), aspartate–glutamate (Lig2), aspartate–citrulline (Lig3), aspartate–lysine (Lig4), aspartate–arginine (Lig5), aspartate–canavanine (Lig6), aspartate–ornithine (Lig7), and aspartate–homoarginine (Lig8), as well reference ligands kojic acid (KA) and 4-hydroxy-cinnamic acid (CA), presented in Table 1, were optimized with Gaussian09 (ver. D.01, Gaussian, INC., Wallingford, CT, USA) [67 ] at B3LYP [68 (link)]/6-31+g(d,p) [69 (link)] level of theory. Optimized ligand structures were used to generate parameters by using GAFF [70 (link)] delivered in tLeaP (AmberTools, version 20, University of California, San Francisco, CA, USA). For each ligand, the three-dimensional plots of molecular electrostatic potential (ESP) [71 ] were generated; ESP measures interaction energy between the charge distribution of a molecule and a positive charge, where a negative value corresponds to an attractive interaction and a positive value corresponds to repulsion.

Krzemińska A., Kwiatos N., Arenhart Soares F, & Steinbüchel A. (2022). Theoretical Studies of Cyanophycin Dipeptides as Inhibitors of Tyrosinases. International Journal of Molecular Sciences, 23(6), 3335.

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