scholarly journals RNA force field with accuracy comparable to state-of-the-art protein force fields

2018 ◽  
Vol 115 (7) ◽  
pp. E1346-E1355 ◽  
Author(s):  
Dazhi Tan ◽  
Stefano Piana ◽  
Robert M. Dirks ◽  
David E. Shaw
Keyword(s):  
Force Field ◽  
Md Simulation ◽  
State Of The Art ◽  
Force Fields ◽  
Md Simulations ◽  
Physical Models ◽  
Rna Structures ◽  
Rna Molecules ◽  
Wide Range ◽  
Protein Force Fields

Molecular dynamics (MD) simulation has become a powerful tool for characterizing at an atomic level of detail the conformational changes undergone by proteins. The application of such simulations to RNA structures, however, has proven more challenging, due in large part to the fact that the physical models (“force fields”) available for MD simulations of RNA molecules are substantially less accurate in many respects than those currently available for proteins. Here, we introduce an extensive revision of a widely used RNA force field in which the parameters have been modified, based on quantum mechanical calculations and existing experimental information, to more accurately reflect the fundamental forces that stabilize RNA structures. We evaluate these revised parameters through long-timescale MD simulations of a set of RNA molecules that covers a wide range of structural complexity, including single-stranded RNAs, RNA duplexes, RNA hairpins, and riboswitches. The structural and thermodynamic properties measured in these simulations exhibited dramatically improved agreement with experimentally determined values. Based on the comparisons we performed, this RNA force field appears to achieve a level of accuracy comparable to that of state-of-the-art protein force fields, thus significantly advancing the utility of MD simulation as a tool for elucidating the structural dynamics and function of RNA molecules and RNA-containing biological assemblies.

scholarly journals Developing a molecular dynamics force field for both folded and disordered protein states

2018 ◽  
Vol 115 (21) ◽  
pp. E4758-E4766 ◽  
Author(s):  
Paul Robustelli ◽  
Stefano Piana ◽  
David E. Shaw
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Md Simulation ◽  
State Of The Art ◽  
Force Fields ◽  
Md Simulations ◽  
Disordered Proteins ◽  
Disordered Protein ◽  
Data Points ◽  
Folded Proteins

Molecular dynamics (MD) simulation is a valuable tool for characterizing the structural dynamics of folded proteins and should be similarly applicable to disordered proteins and proteins with both folded and disordered regions. It has been unclear, however, whether any physical model (force field) used in MD simulations accurately describes both folded and disordered proteins. Here, we select a benchmark set of 21 systems, including folded and disordered proteins, simulate these systems with six state-of-the-art force fields, and compare the results to over 9,000 available experimental data points. We find that none of the tested force fields simultaneously provided accurate descriptions of folded proteins, of the dimensions of disordered proteins, and of the secondary structure propensities of disordered proteins. Guided by simulation results on a subset of our benchmark, however, we modified parameters of one force field, achieving excellent agreement with experiment for disordered proteins, while maintaining state-of-the-art accuracy for folded proteins. The resulting force field, a99SB-disp, should thus greatly expand the range of biological systems amenable to MD simulation. A similar approach could be taken to improve other force fields.

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2020 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2019 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2019 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Extensive Evaluation of Force Fields for G-Quadruplexes

2021 ◽  
Author(s):  
Na Li ◽  
Tong Zhu
Keyword(s):  
Force Field ◽  
Md Simulation ◽  
Comprehensive Evaluation ◽  
Force Fields ◽  
Md Simulations ◽  
Extensive Evaluation ◽  
Explicit Solvent ◽  
Quantum Chemistry Calculations ◽  
Anti Cancer ◽  
Sticking Point

<p><a></a><a></a><a>G-Quadruplexes</a> (GQs), folded by guanine-rich <a></a><a></a><a>nucleic acid</a> <a></a><a></a><a></a><a>sequences</a>, involve in gene expression processes and closely associated with the formation of tumors. So far, GQ has drawn widespread attention for its notable application of serving as potential anti-cancer target. Recently, theoretical studies for GQs have achieved significant progress, most of which are inseparable from molecular dynamics (MD) simulation. As a necessary tool to explore <a></a><a></a><a>dynamics behavior</a> of molecules, MD simulations strictly depend on force field parameters, which is a sticking point to obtain accurate results. Currently, many force fields for nucleic acids have been developed, but none of them have been accepted widely for GQs. In this paper, we selected five popular force fields, which are parmbsc0, parmbsc1, OL15, Drude2017 and AMOEBANUC17, and conducted explicit-solvent MD simulations on two DNA GQs respectively. We evaluated these force fields from many aspects in detail. Meanwhile, we compared conformational energy using quantum chemistry calculations. With the comprehensive evaluation, Drude2017 achieved better description for GQs, which we suggest that using Drude2017 force field should <a></a><a></a><a>be taken into account</a> first when investigating GQs by MD simulation<a></a><a></a><a></a><a></a><a>.</a></p>

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2019 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2020 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Extensive Evaluation of Force Fields for G-Quadruplexes

2021 ◽  
Author(s):  
Na Li ◽  
Tong Zhu
Keyword(s):  
Force Field ◽  
Md Simulation ◽  
Comprehensive Evaluation ◽  
Force Fields ◽  
Md Simulations ◽  
Extensive Evaluation ◽  
Explicit Solvent ◽  
Quantum Chemistry Calculations ◽  
Anti Cancer ◽  
Sticking Point

<p><a></a><a></a><a>G-Quadruplexes</a> (GQs), folded by guanine-rich <a></a><a></a><a>nucleic acid</a> <a></a><a></a><a></a><a>sequences</a>, involve in gene expression processes and closely associated with the formation of tumors. So far, GQ has drawn widespread attention for its notable application of serving as potential anti-cancer target. Recently, theoretical studies for GQs have achieved significant progress, most of which are inseparable from molecular dynamics (MD) simulation. As a necessary tool to explore <a></a><a></a><a>dynamics behavior</a> of molecules, MD simulations strictly depend on force field parameters, which is a sticking point to obtain accurate results. Currently, many force fields for nucleic acids have been developed, but none of them have been accepted widely for GQs. In this paper, we selected five popular force fields, which are parmbsc0, parmbsc1, OL15, Drude2017 and AMOEBANUC17, and conducted explicit-solvent MD simulations on two DNA GQs respectively. We evaluated these force fields from many aspects in detail. Meanwhile, we compared conformational energy using quantum chemistry calculations. With the comprehensive evaluation, Drude2017 achieved better description for GQs, which we suggest that using Drude2017 force field should <a></a><a></a><a>be taken into account</a> first when investigating GQs by MD simulation<a></a><a></a><a></a><a></a><a>.</a></p>

Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2020 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

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