A Suite of Advanced Tutorials for the GROMOS Biomolecular Simulation Software [Article v1.0]

Hansen, Niels; Öehlknecht, Christoph; Ruiter, Anita de; Lier, Bettina; Gunsteren, Wilfred F. van; Oostenbrink, Chris; Gebhardt, Julia

doi:10.33011/livecoms.2.1.18552

Cited by 4 publications

(3 citation statements)

References 35 publications

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“…Next, M acceleration regions are defined by indicating which terms should be treated together by using their indices, where i – i refers to the self-energy and bonded terms of group i and i – j refers to the nonbonded interaction between the groups with index i and index j . Examples on how to define these groups and regions can be found in the Supporting Information and a tutorial on how to use the proposed methodology can be found in the github version of the LiveCoMS tutorials for GROMOS . Once the M acceleration regions are defined, the user can select if they should be accelerated or not and which parameters ( E and k in eq ) to use for each of the biasing potentials, producing a set of M energy thresholds E and M force constants k .…”

Section: Methodsmentioning

confidence: 99%

“…Examples on how to define these groups and regions can be found in the Supporting Information and a tutorial on how to use the proposed methodology can be found in the github version of the LiveCoMS tutorials for GROMOS. 46 Once the M acceleration regions are defined, the user can select if they should be accelerated or not and which parameters (E and k in eq 1) to use for each of the biasing potentials, producing a set of M energy thresholds E and M force constants k. Additionally, the dihedral term of the bonded terms can be accelerated 48 (C) Schematic representation of the complex glycan NaNaF using the symbol nomenclature for glycans. 52 (D) Olfactory panda protein, 5NGH, 53 individually from the rest of the potential energy, which is usually referred as dual boosting.…”

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confidence: 99%

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Flexible Gaussian Accelerated Molecular Dynamics to Enhance Biological Sampling

Gracia Carmona,

Oostenbrink

2023

J. Chem. Theory Comput.

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Molecular dynamics simulations often struggle to obtain sufficient sampling to study complex molecular events due to high energy barriers separating the minima of interest. Multiple enhanced sampling techniques have been developed and improved over the years to tackle this issue. Gaussian accelerated molecular dynamics (GaMD) is a recently developed enhanced sampling technique that works by adding a biasing potential, lifting the energy landscape up, and decreasing the height of its barriers. GaMD allows one to increase the sampling of events of interest without the need of a priori knowledge of the system or the relevant coordinates. All required acceleration parameters can be obtained from a previous search run. Upon its development, several improvements for the methodology have been proposed, among them selective GaMD in which the boosting potential is selectively applied to the region of interest. There are currently four selective GaMD methods that have shown promising results. However, all of these methods are constrained on the number, location, and scenarios in which this selective boosting potential can be applied to ligands, peptides, or protein−protein interactions. In this work, we showcase a GROMOS implementation of the GaMD methodology with a fully flexible selective GaMD approach that allows the user to define, in a straightforward way, multiple boosting potentials for as many regions as desired. We show and analyze the advantages of this flexible selective approach on two previously used test systems, the alanine dipeptide and the chignolin peptide, and extend these examples to study its applicability and potential to study conformational changes of glycans and glycosylated proteins.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Flexible Gaussian Accelerated Molecular Dynamics to Enhance Biological Sampling

Gracia Carmona,

Oostenbrink

2023

J. Chem. Theory Comput.

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“…We presume that in general the local sampling yields a binding free energy more accurately than the global sampling does because of 𝑉𝑉 𝑙𝑙𝑙𝑙𝑐𝑐𝑚𝑚𝑙𝑙 ≪ 𝑉𝑉 𝑠𝑠𝑙𝑙𝑙𝑙𝑣𝑣𝑚𝑚𝑙𝑙 . Therefore, there has been many methods readily applicable [58][59][60][61][62][63][64] or having been applied [65][66][67][68][69][70][71][72][73] to the local sampling. The global sampling and local sampling should be used depending on the purpose of the study.…”

Section: Ribocil In the Rear Portion Of The Density Tunnelmentioning

confidence: 99%