Systematic Derivation of AMBER Force Field Parameters Applicable to Zinc-Containing Systems

2010 ◽  
Vol 6 (6) ◽  
pp. 1852-1870 ◽  
Author(s):  
Fu Lin ◽  
Renxiao Wang
Keyword(s):  
Force Field ◽  
Amber Force Field ◽  
Force Field Parameters ◽  
Systematic Derivation

AMBER Force Field Parameters for Cobalt-Containing Biological Systems: A Systematic Derivation Study

2020 ◽  
Vol 124 (5) ◽  
pp. 777-787
Author(s):  
Hamed Haghshenas ◽  
Hossein Tavakol ◽  
Bita Kaviani ◽  
Gholamhossein Mohammadnezhad
Keyword(s):  
Force Field ◽  
Biological Systems ◽  
Amber Force Field ◽  
Force Field Parameters ◽  
Systematic Derivation

VFFDT: A New Software for Preparing AMBER Force Field Parameters for Metal-Containing Molecular Systems

2016 ◽  
Vol 56 (4) ◽  
pp. 811-818 ◽  
Author(s):  
Suqing Zheng ◽  
Qing Tang ◽  
Jian He ◽  
Shiyu Du ◽  
Shaofang Xu ◽  
...  
Keyword(s):  
Force Field ◽  
Amber Force Field ◽  
Molecular Systems ◽  
Force Field Parameters

scholarly journals Comparison of different approaches to derive classical bonded force-field parameters for a transition metal cofactor: a case study for non-heme iron site of ectoine synthase

2021 ◽  
Vol 140 (8) ◽  
Author(s):  
Justyna Andrys ◽  
Johann Heider ◽  
Tomasz Borowski
Keyword(s):  
Transition Metal ◽  
Force Field ◽  
Metal Ion ◽  
Geometry Optimization ◽  
Heme Iron ◽  
Energy Structure ◽  
Test Case ◽  
Amber Force Field ◽  
Force Field Parameters ◽  
And Function

AbstractComputational investigations into the structure and function of metalloenzymes with transition metal cofactors require proper preparation of the model, which requires obtaining reliable force field parameters for the cofactor. Here, we present a test case where several methods were used to derive amber force field parameters for a bonded model of the Fe(II) cofactor of ectoine synthase. Moreover, the spin of the ground state of the cofactor was probed by DFT and post-HF methods, which consistently indicated the quintet state is lowest in energy and well separated from triplet and singlet. The performance of the obtained force field parameter sets, derived for the quintet spin state, was scrutinized and compared taking into account metrics focused on geometric features of the models as well as their energetics. The main conclusion of this study is that Hessian-based methods yield parameters which represent the geometry around the metal ion, but poorly reproduce energy variance with geometrical changes. On the other hand, the energy-based method yields parameters accurately reproducing energy-structure relationships, but with bad performance in geometry optimization. Preliminary tests show that admixing geometrical criteria to energy-based methods may allow to derive parameters with acceptable performance for both energy and geometry.

AMBER Force Field Parameters for the Naturally Occurring Modified Nucleosides in RNA

2007 ◽  
Vol 3 (4) ◽  
pp. 1464-1475 ◽  
Author(s):  
Raviprasad Aduri ◽  
Brian T. Psciuk ◽  
Pirro Saro ◽  
Hariprakash Taniga ◽  
H. Bernhard Schlegel ◽  
...  
Keyword(s):  
Force Field ◽  
Modified Nucleosides ◽  
Amber Force Field ◽  
Naturally Occurring ◽  
Force Field Parameters

scholarly journals Intermolecular Force Field Parameters Optimization for Computer Simulations of CH4in ZIF-8

2016 ◽  
Vol 2016 ◽  
pp. 1-6
Author(s):  
Phannika Kanthima ◽  
Pikul Puphasuk ◽  
Tawun Remsungnen
Keyword(s):  
Force Field ◽  
Md Simulations ◽  
Binding Energies ◽  
Parameters Optimization ◽  
Interaction Energies ◽  
Intermolecular Force ◽  
Amber Force Field ◽  
De Algorithm ◽  
Force Field Parameters ◽  
Structural Behaviors

The differential evolution (DE) algorithm is applied for obtaining the optimized intermolecular interaction parameters between CH4and 2-methylimidazolate ([C4N2H5]−) using quantum binding energies of CH4-[C4N2H5]−complexes. The initial parameters and their upper/lower bounds are obtained from the general AMBER force field. The DE optimized and the AMBER parameters are then used in the molecular dynamics (MD) simulations of CH4molecules in the frameworks of ZIF-8. The results show that the DE parameters are better for representing the quantum interaction energies than the AMBER parameters. The dynamical and structural behaviors obtained from MD simulations with both sets of parameters are also of notable differences.

Generation of AMBER force field parameters for zinc centres of M1 and M17 family aminopeptidases

2017 ◽  
Vol 36 (10) ◽  
pp. 2595-2604 ◽  
Author(s):  
Wei Yang ◽  
Blake T. Riley ◽  
Xiangyun Lei ◽  
Benjamin T. Porebski ◽  
Itamar Kass ◽  
...  
Keyword(s):  
Force Field ◽  
Amber Force Field ◽  
Force Field Parameters

scholarly journals Force Field Parameters for Fe2+4S2−4 Clusters of Dihydropyrimidine Dehydrogenase, the 5-Fluorouracil Cancer Drug Deactivation Protein: A Step towards In Silico Pharmacogenomics Studies

Molecules ◽  
2021 ◽  
Vol 26 (10) ◽  
pp. 2929
Author(s):  
Maureen Bilinga Tendwa ◽  
Lorna Chebon-Bore ◽  
Kevin Lobb ◽  
Thommas Mutemi Musyoka ◽  
Özlem Tastan Bishop
Keyword(s):  
Force Field ◽  
In Silico ◽  
Molecular Mechanisms ◽  
Dihydropyrimidine Dehydrogenase ◽  
Protein A ◽  
Cancer Drug ◽  
Missense Mutations ◽  
Amber Force Field ◽  
In Silico Studies ◽  
Force Field Parameters

The dimeric dihydropyrimidine dehydrogenase (DPD), metalloenzyme, an adjunct anti-cancer drug target, contains highly specialized 4 × Fe2+4S2−4 clusters per chain. These clusters facilitate the catalysis of the rate-limiting step in the pyrimidine degradation pathway through a harmonized electron transfer cascade that triggers a redox catabolic reaction. In the process, the bulk of the administered 5-fluorouracil (5-FU) cancer drug is inactivated, while a small proportion is activated to nucleic acid antimetabolites. The occurrence of missense mutations in DPD protein within the general population, including those of African descent, has adverse toxicity effects due to altered 5-FU metabolism. Thus, deciphering mutation effects on protein structure and function is vital, especially for precision medicine purposes. We previously proposed combining molecular dynamics (MD) and dynamic residue network (DRN) analysis to decipher the molecular mechanisms of missense mutations in other proteins. However, the presence of Fe2+4S2−4 clusters in DPD poses a challenge for such in silico studies. The existing AMBER force field parameters cannot accurately describe the Fe2+ center coordination exhibited by this enzyme. Therefore, this study aimed to derive AMBER force field parameters for DPD enzyme Fe2+ centers, using the original Seminario method and the collation features Visual Force Field Derivation Toolkit as a supportive approach. All-atom MD simulations were performed to validate the results. Both approaches generated similar force field parameters, which accurately described the human DPD protein Fe2+4S2−4 cluster architecture. This information is crucial and opens new avenues for in silico cancer pharmacogenomics and drug discovery related research on 5-FU drug efficacy and toxicity issues.

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