Protein−Ligand Binding Free Energy Calculation by the Smooth Reaction Path Generation (SRPG) Method

Fukunishi, Yoshifumi; Mitomo, Daisuke; Nakamura, Haruki

doi:10.1021/ci9002156

Cited by 26 publications

(29 citation statements)

References 43 publications

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“…Fukunishi et al proposed a filling potential (FP) method and a smooth reaction-path generation (SRPG) method, which compute a binding free energy of protein-ligand docking along a protein-ligand dissociation path. [33,47] In the FP method, the ligand position is restricted on the dissociation path, and the free energy along the path is computed by a histogram method. In the SRPG method, after setting a number of sites in the path, sampling is performed at each site, and an average force is computed at those sites.…”

Section: Resultsmentioning

confidence: 99%

Virtual‐system‐coupled adaptive umbrella sampling to compute free‐energy landscape for flexible molecular docking

et al. 2015

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A novel enhanced conformational sampling method, virtual-system-coupled adaptive umbrella sampling (V-AUS), was proposed to compute 300-K free-energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V-AUS was applied to complex formation of two disordered amyloid-β (Aβ30-35 ) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300-K free-energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β-sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V-AUS converged to uniform distribution more effectively than conventional AUS sampling did.

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Section: Resultsmentioning

confidence: 99%

Virtual‐system‐coupled adaptive umbrella sampling to compute free‐energy landscape for flexible molecular docking

et al. 2015

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“…When PMF is calculated up to a position of where the slope of PMF is zero, G(r ∞ ) can be replaced by PMF at the zero slope. PMF values are calculated by TI method [20]:…”

Section: Step 3: Calculating the Binding Free Energymentioning

confidence: 99%

“…Therefore, many different methods were developed to calculate PMFs for protein-ligand binding as the filling potential (FP) method [15], the meta-dynamics method [16,17], the MP-CAFEE method [18], Jarzynski's method [19], and the smooth reaction path generation (SRPG) method [20].…”

Section: Introductionmentioning

confidence: 99%

Computational Study of Drug Binding Affinity to Influenza A Neuraminidase Using Smooth Reaction Path Generation (SRPG) Method

Nguyen

Tran

Fukunishi

et al. 2015

J. Chem. Inf. Model.

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Assessment of accurate drug binding affinity to a protein remains a challenge for in silico drug development. In this research, we used the smooth reaction path generation (SRPG) method to calculate binding free energies and determine potential of mean forces (PMFs) along the smoothed dissociation paths of influenza A neuraminidase and its variants with oseltamivir (Tamiflu) and zanamivir (Relenza) inhibitors. With the gained results, we found that the binding free energies of neuraminidase A/H5N1 in WT and two mutants (including H274Y and N294S) with oseltamivir and zanamivir show good agreement with experimental results. Additionally, the thermodynamic origin of the drug resistance of the mutants was also discussed from the PMF profiles.

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“…The smooth reaction path generation (SRPG) method is a modified version of the FP method [45]. The SRPG method consists of three steps: (1) generation of a compound dissociation path starting from a stable protein compound complex structure, (2) calculation of the free energy surface along the dissociation path, and (3) calculation of the freeenergy surface of a small area around the protein compound complex structure constituting the free energy minimum.…”

Section: Introductionmentioning

confidence: 99%

Post Processing of Protein-Compound Docking for Fragment-Based Drug Discovery (FBDD): In-Silico Structure-Based Drug Screening and Ligand-Binding Pose Prediction

Fukunishi

2010

CTMC

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For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

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Protein−Ligand Binding Free Energy Calculation by the Smooth Reaction Path Generation (SRPG) Method

Cited by 26 publications

References 43 publications

Virtual‐system‐coupled adaptive umbrella sampling to compute free‐energy landscape for flexible molecular docking

Virtual‐system‐coupled adaptive umbrella sampling to compute free‐energy landscape for flexible molecular docking

Computational Study of Drug Binding Affinity to Influenza A Neuraminidase Using Smooth Reaction Path Generation (SRPG) Method

Post Processing of Protein-Compound Docking for Fragment-Based Drug Discovery (FBDD): In-Silico Structure-Based Drug Screening and Ligand-Binding Pose Prediction

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