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dataset · Zenodo (CERN European Organization for Nuclear Research)

REPLICATED ENHANCED-SAMPLING DATA FOR THE SMP103-SORTASE A COMPLEX

In plain language

This computational study presents replicated enhanced-sampling simulation data evaluating the binding energetics of SMP103, a de novo-designed head-to-tail macrocyclic peptide, to Staphylococcus aureus Sortase A. Three independent replicas of steered molecular dynamics and subsequent umbrella sampling were conducted to model the dissociation of SMP103 from the enzyme active-site region. Trajectories were analysed using the weighted histogram analysis method to build potential of mean force profiles across 60, 63, and 57 umbrella windows for the respective replicas. The resulting calculations produced binding-direction free-energy estimates of -17.61, -16.34, and -12.74 kcal per mole, yielding a replica mean of -15.56 ± 2.53 kcal per mole. The averaged potential of mean force indicated a maximum free-energy rise of 15.54 kcal per mole with a bootstrap uncertainty of ±0.37 kcal per mole.

Key takeaways

  • SMP103 is a de novo-designed macrocyclic peptide engineered to target the active-site region of Staphylococcus aureus Sortase A.
  • Three independent umbrella-sampling simulations yielded binding-direction free-energy estimates of -17.61, -16.34, and -12.74 kcal per mole.
  • The replica-averaged potential of mean force exhibited a mean free-energy estimate of -15.56 ± 2.53 kcal per mole and a maximum free-energy rise of 15.54 ± 0.37 kcal per mole.

Why it matters

Staphylococcus aureus is a major bacterial pathogen, and Sortase A is an established target for developing new antivirulence strategies. Determining the thermodynamic properties and energetic barriers associated with peptide binding provides fundamental molecular insights, which can guide the computational design and refinement of more stable peptide-based enzyme inhibitors.

Commercialisation angle

This work represents very early-stage computational drug discovery. The data may assist academic or pharmaceutical researchers working on antivirulence therapeutics and peptide-based inhibitor development against Staphylococcus aureus infections. However, because the study is entirely computational and characterises dissociation energetics in silico, it remains far from real-world application, requiring extensive experimental validation and preclinical testing before any commercial pathway can be established.

AI-generated from the published abstract. Always read the original work before citing.

Abstract

This dataset accompanies the computational study of the de novo-designed head-to-tail macrocyclic peptide SMP103 targeting Staphylococcus aureus Sortase A (SrtA). It contains data from three independent enhanced-sampling calculations performed to characterize the energetic response associated with dissociation of SMP103 from the SrtA substrate-recognition/active-site region. For each independent replica, a center-of-mass steered molecular dynamics (SMD) simulation was used to generate a peptide-dissociation pathway. Configurations distributed along the resulting reaction coordinate were subsequently selected at approximately 0.1-nm intervals and subjected to equilibration followed by production umbrella sampling. The resulting biased trajectories were analyzed using the weighted histogram analysis method (WHAM) to reconstruct replica-specific potential of mean force (PMF) profiles. Because configuration selection was performed independently from each replica-specific SMD pathway, the exact configuration identities and numbers of successfully completed umbrella windows differ among the three calculations. The deposited datasets contain 60, 63, and 57 successfully completed umbrella windows for Replicas 1, 2, and 3, respectively. Only production windows included in the corresponding PMF reconstruction are retained in the archive. Each replica directory contains the SMD trajectory (pull.xtc) and corresponding GROMACS run-input file (pull.tpr), together with the production run-input files (umbrella_win*.tpr), restraint-force data (*_pullf.xvg), and reaction-coordinate data (*_pullx.xvg) for the successfully completed umbrella-sampling windows. Replica-specific PMF profiles, histogram-overlap data, and associated WHAM analysis outputs are provided within the corresponding Data_Analysis_PMF directories. The three independently reconstructed PMF profiles yielded PMF-derived binding-direction free-energy estimates of -17.61, -16.34, and -12.74 kcal mol⁻¹ for Replicas 1, 2, and 3, respectively, corresponding to a replica mean of -15.56 ± 2.53 kcal mol⁻¹. These values were calculated as the difference between the minimum and maximum of the corresponding zero-referenced one-dimensional PMF profiles and therefore describe the energetic separation between the sampled PMF states along the defined dissociation coordinate rather than an absolute standard-state binding free energy. Analysis of the averaged three-replica PMF yielded a maximum free-energy rise of 15.54 kcal mol⁻¹, with a bootstrap uncertainty of ±0.37 kcal mol⁻¹. SMP103 was represented using an explicitly bonded head-to-tail macrocyclic topology, and all enhanced-sampling calculations employed the CHARMM36 force field (charmm36-jul2021.ff) with the TIP3P water model. The small, human-readable molecular topology, SMD and umbrella-sampling parameter files, index groups, and replica-specific window-selection information are provided separately in the associated GitHub repository. The complete README included in this archive provides detailed descriptions of the deposited files and their organization. Associated enhanced-sampling input files:https://github.com/Olanrewaju-Durojaye/Enhanced-Sampling_Input_Files_for_the-_SMP103-Sortase_A_Complex Analysis scripts:https://github.com/Olanrewaju-Durojaye/Scripts_for_SMP_Project_analyses Associated replicated unbiased MD dataset:https://doi.org/10.5281/zenodo.21888186 Associated molecular dynamics input files:https://github.com/Olanrewaju-Durojaye/Molecular-Dynamics-Input-Files-for-De-Novo-Macrocyclic-Peptide-Sortase-A-Complexes

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.5281/zenodo.22108760

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