• Bulletin of the Korean Chemical Society
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• v.26 no.5
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• pp.769-775
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• 2005

An efficiency of Monte Carlo (MC) docking simulations was examined for the prediction of chiral discrimination by cyclodextrins. Docking simulations were performed with various computational parameters for the chiral discrimination of a series of 17 enantiomers by $\beta$-cyclodextrin ($\beta$-CD) or by 6-amino-6-deoxy-$\beta$-cyclodextrin (am-$\beta$-CD). A total of 30 sets of enantiomeric complexes were tested to find the optimal simulation parameters for accurate predictions. Rigid-body MC docking simulations gave more accurate predictions than flexible docking simulations. The accuracy was also affected by both the simulation temperature and the kind of force field. The prediction rate of chiral preference was improved by as much as 76.7% when rigid-body MC docking simulations were performed at low-temperatures (100 K) with a sugar22 parameter set in the CHARMM force field. Our approach for MC docking simulations suggested that the conformational rigidity of both the host and guest molecule, due to either the low-temperature or rigid-body docking condition, contributed greatly to the prediction of chiral discrimination.

• Bulletin of the Korean Chemical Society
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• v.28 no.10
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• pp.1811-1814
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• 2007

• Bulletin of the Korean Chemical Society
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• v.24 no.1
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• pp.95-98
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• 2003

Enantioselectivity of the propranolol on β-cyclodextrin was simulated by molecular modeling. Monte Carlo (MC) docking and molecular dynamics (MD) simulations were applied to investigate the molecular mechanism of enantioselective difference of both enantiomeric complexes. An energetic analysis of MC docking simulations coupled to the MD simulations successfully explains the experimental elution order of propranolol enantiomers. Molecular dynamics simulations indicate that average energy difference between the enantiomeric complexes, frequently used as a measure of chiral recognition, depends on the length of the simulation time. We found that, only in case of much longer MD simulations, noticeable chiral separation was observed.

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.208-213
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• 2016

This paper proposes a potential field-based guidance law for docking a USV (unmanned surface vehicle). In most cases, a USV without side thrusters is an under-actuated system. Thus, there are undockable regions near docking stations where a USV cannot dock to a docking station without causing a collision or backward motion. This paper suggest a guidance law that prevents a USV from enter such a region by decreasing the lateral error to the docking station at the initial stage of the docking process. A Monte-carlo simulation was performed to validate the performance of the proposed method. The proposed method was compared to conventional guidance laws such as pure pursuit guidance and pure/lead pursuit guidance. As a result, the collision angle and lateral distance error of proposed method tended to have lower values compared to conventional methods.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.221-233
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• 2004

Molecular docking falls into the general category of global optimization problems since its main purpose is to find the most stable complex consisting of a receptor and its ligand. Conformational space annealing (CSA), a powerful global optimization method, is incorporated with the Tinker molecular modeling package to perform molecular docking simulations of six receptor-ligand complexes (3PTB, 1ULB, 2CPP, 1STP, 3CPA and 1PPH) from the Protein Data Bank. In parallel, Monte Carlo with minimization (MCM) method is also incorporated into the Tinker package for comparison. The energy function, consisting of electrostatic interactions, van der Waals interactions and torsional energy terms, is calculated using the AMBER94 all-atom empirical force field. Rigid docking simulations for all six complexes and flexible docking simulations for three complexes (1STP, 3CPA and 1PPH) are carried out using the CSA and the MCM methods. The simulation results show that the docking procedures using the CSA method generally find the most stable complexes as well as the native -like complexes more efficiently and accurately than those using the MCM, demonstrating that CSA is a promising search method for molecular docking problems.

• Journal of Integrative Natural Science
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• v.2 no.2
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• pp.55-58
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• 2009

A ligand-receptor docking program is an indispensible tool in modern pharmaceutical design. An accurate prediction of small molecular docking pose to a receptor is essential in drug design as well as molecular recognition. An effective docking program requires the ability to locate a correct binding pose in a surprisingly complex conformational space. However, there is an inherent difficulty to predict correct binding pose. The odds are more demanding than finding a needle in a haystack. This mainly comes from the flexibility of both ligand and receptor. Because the searching space to consider is so vast, receptor rigidity has been often applied in docking programs. Even nowadays the receptor may not be considered to be fully flexible although there have been some progress in search algorithm. Improving the efficiency of searching algorithm is still in great demand to explore other applications areas with inherently flexible ligand and/or receptor. In addition to classical search algorithms such as molecular dynamics, Monte Carlo, genetic algorithm and simulated annealing, rather recent algorithms such as tabu search, stochastic tunneling, particle swarm optimizations were also found to be effective. A good search algorithm would require a good balance between exploration and exploitation. It would be a good strategy to combine algorithms already developed. This composite algorithms can be more effective than an individual search algorithms.

• Journal of Integrative Natural Science
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• v.3 no.1
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• pp.49-53
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• 2010

Molecular docking is a critical event which mostly forms Van der waals complex in molecular recognition. Since the majority of developed drugs are small molecules, docking them into proteins has been a prime concern in drug discovery community. Since the binding pose space is too vast to cover completely, many search algorithms such as genetic algorithm, Monte Carlo, simulated annealing, distance geometry have been developed. Proper evaluation of the quality of binding is an essential problem. Scoring functions derived from force fields handle the ligand binding prediction with the use of potential energies and sometimes in combination with solvation and entropy contributions. Knowledge-based scoring functions are based on atom pair potentials derived from structural databases. Forces and potentials are collected from known protein-ligand complexes to get a score for their binding affinities (e.g. PME). Empirical scoring functions are derived from training sets of protein-ligand complexes with determined affinity data. Because non of any single scoring function performs generally better than others, some other approaches have been tried. Although numerous scoring functions have been developed to locate the correct binding poses, it still remains a major hurdle to derive an accurate scoring function for general targets. Recently, consensus scoring functions and target specific scoring functions have been studied to overcome the current limitations.

• Bulletin of the Korean Chemical Society
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• v.24 no.11
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• pp.1627-1631
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• 2003

Molecular modeling was performed to comprehend the chiral recognition of ${\alpha}$-methoxy-${\alpha}$-trifluoromethylphenylacetic acid (MTPA) enantiomers by cyclomaltoheptaose (${\beta}$-cyclodextrin,${\beta}$-CD) and 6-amino-6-deoxy-cyclomaltoheptaose (am-${\beta}$-CD). Monte Carlo (MC) docking coupled to constant temperature molecular dynamics (MD) simulations was applied to the investigation for the ${\alpha}$-methoxy-${\alpha}$-trifluoromethylphenylacetic acid complexation with two different CDs in terms of the relative distribution of the interaction energies. The calculated results are finely correlated with the experimental observations in chiral recognition thermodynamics. Am-${\beta}$-CD as a host showed the superior enantio-discrimination ability to the native ${\beta}$-CD where the amino group of am-${\beta}$-CD was critically involved in enhancing the ability of chiral discrimination via the Coulombic interaction with MTPA.