• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.294-299
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• 2005

We have studied unbound docking for 12 protein-protein complexes using conformational space annealing (CSA) combined along with statistical pair potentials. The CSA, a powerful global optimization tool, is used to search the conformational space represented by a translational vector and three Euler amgles between two proteins. The energy function consists of three statistical pair-wise energy terms; one from the distance-scaled finite ideal-gas reference state (DFIRE) approach by Zhou and the other two derived from residue-residue contacts. The residue-residue contact terms describe both attractive and repulsive interactions between two residues in contact. The performance of the CSA docking is compared with that of ZDOCK, a well-established protein-protein docking method. The results show that the application of CSA to the protein-protein docking is quite successful, indicating that the CSA combined with a good scoring function is a promising method for the study of protein-protein interaction.

• 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.

• 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.

• Journal of Integrative Natural Science
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• v.6 no.2
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• pp.100-103
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• 2013

Using computational approaches we can dock small molecules into the structures of Macromolecular targets and then score their potential complementarity to binding sites is widely used in hit identification and lead optimization techniques. This review seeks to provide the application of docking in structure-based drug design (binding mode prediction, Lead Identification and Lead optimization), and also discussed how to manage errors in docking methodology in order to overcome certain limitations of docking and scoring algorithm.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4301-4305
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• 2014

Tanshinone IIA is a pharmacologically active ingredient extracted from Danshen, a Chinese traditional medicine. Its molecular mechanisms are still unclear. The present study utilized computational approaches to uncover the potential targets of this compound. In this research, PharmMapper server was used as the inverse docking tool andnd the results were verified by Autodock vina in PyRx 0.8, and by DRAR-CPI, a server for drug repositioning via the chemical-protein interactome. Results showed that the retinoic acid receptor alpha ($RAR{\alpha}$), a target protein in acute promyelocytic leukemia (APL), was in the top rank, with a pharmacophore model matching well the molecular features of Tanshinone IIA. Moreover, molecular docking and drug repurposing results showed that the complex was also matched in terms of structure and chemical-protein interactions. These results indicated that $RAR{\alpha}$ may be a potential target of Tanshinone IIA for APL. The study can provide useful information for further biological and biochemical research on natural compounds.

• Journal of Integrative Natural Science
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• v.5 no.3
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• pp.190-194
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• 2012

Human P-gp is one of the protein responsible for the multidrug resistance (MDR) develpment. MDR is a major cause of the cancer chemotherapy. In this paper, we performed homology modeling, docking study of papayriferic acid into the P-gp nucleotide binding domain (NBD2). For human P-gp, X-ray crystal structure is not known yet. We developed homology model for human NBD2 using HlyB ABC transporter structure (PDB code: 1XEF, resolution 2.5 ${\AA}$). Docking study was performed using Autodock. Docking result was analyzed, which shows that ligand docks into steroid binding site and interacts through hydrophobic and hydrophilic interactions.

• Journal of Integrative Natural Science
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• v.15 no.4
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• pp.153-161
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• 2022

c-Jun N-terminal kinases (JNKs) are members of MAPK family. Many genes can relay signals that promote inflammation, cell proliferation, or cell death which causes several diseases have been associated to mutations in the JNK gene family. The JNK2 gene is significantly more important in cancer development than the JNK1 and JNK3 genes. There are several different ways in which JNK2 contributes to breast cancer, and one of these is through its role in cell migration. As a result, this study's primary objective was to employ computational strategies to identify promising leads that potentially target the JNK2 protein in a strategy to alleviate breast cancer. We have derived these anticancer compounds from marine brown seaweed called Turbinaria conoides. We have identified compounds Ethane, 1, 1-diethoxy- and Butane, 2-ethoxy as promising anti-cancer drugs by molecular docking, DFT, and ADME study.

• Journal of the Korean Chemical Society
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• v.66 no.3
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• pp.194-201
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• 2022

A simple, efficient, and cost-effective method has been employed for the synthesis of 2,4,5-trisubstituted imidazole derivatives (3a-j) containing quinoline substituent at 2^nd position. Title compounds were obtained by multicomponent reaction (MCR), involving aryl substituted 1,2-diketone, quinoline carbaldehyde and ammonium acetate in the presence of acetic acid solvent under mild reaction conditions. The newly synthesized quinoline containing imidazole derivatives were confirmed through FT-IR, ¹H-NMR, ¹³C-NMR and mass spectral analysis. In-vitro microplate alamar blue assay (MABA) to determine the MIC (minimum inhibitory concentration) values against Mycobacterium tuberculosis H37Rv was performed for the synthesized compounds. The synthesized compounds exhibited activity against Mycobacterium tuberculosis and among which compounds, 3d, 3f and 3i showed good activity. The highest activity was showed with compound 3i. The anti-mycobacterial activity results are well correlated with the computational molecular docking analysis, which was performed for the synthesized compounds prior to the evaluation of the activity.

• Journal of Integrative Natural Science
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• v.15 no.4
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• pp.145-152
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• 2022

Colon rectal cancer is one of the frequently diagnosed cancers worldwide. In recent times the drug discovery for colon cancer is challenging because of their speedy metastasis and morality of these patients. C-jun N-terminal kinase signaling pathway controls the cell cycle survival and apoptosis. Evidence has shown that JNK1 promotes the tumor progression in various types of cancers like colon cancer, breast cancer and lung cancer. Recent study has shown that inhibiting, JNK1 pathway is identified as one of the important cascades in drug discovery. One of the recent approaches in the field of drug discovery is drug repurposing. In drug repurposing approach we have virtually screened ChEMBL dataset against JNK1 protein and their interactions have been studied through Molecular docking. Cross docking was performed with the top compounds to be more specific with JNK1 comparing the affinity with JNK2 and JNK3.The drugs which exhibited higher binding were subjected to Conceptual - Density functional theory. The results showed mainly Entrectinib and Exatecan showed better binding to the target.