• 통합자연과학논문집
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• 제2권2호
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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.

• 통합자연과학논문집
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• 제3권3호
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• pp.143-147
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• 2010

Since it is of great importance to know how a ligand binds to a receptor, there have been a lot of efforts to improve the quality of prediction of docking poses. Earlier efforts were focused on improving search algorithm and scoring function in a docking program resulting in a partial improvement with a lot of variations. Although these are basically very important and essential, more tangible improvements came from the reduction of search space. In a normal docking study, the approximate active site is assumed to be known. After defining active site, scoring functions and search algorithms are used to locate the expected binding pose within this search space. A good search algorithm will sample wisely toward the correct binding pose. By careful study of receptor structure, it was possible to prioritize sub-space in the active site using "receptor-based pharmacophores" or "hot spots". In a sense, these techniques reduce the search space from the beginning. Further improvements were made when the bound ligand structure is available, i.e., the searching could be directed by molecular similarity using ligand information. This could be very helpful to increase the accuracy of binding pose. In addition, if the biological activity data is available, docking program could be improved to the level of being useful in affinity prediction for a series of congeneric ligands. Since the number of co-crystal structures is increasing in protein databank, "Ligand-Guided Docking" to reduce the search space would be more important to improve the accuracy of docking pose prediction and the efficiency of virtual screening. Further improvements in this area would be useful to produce more reliable docking programs.

• Bulletin of the Korean Chemical Society
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• 제32권7호
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• pp.2433-2442
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• 2011

The three dimensional quantitative structure activity relationship (3D QSAR) models were developed using Comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and docking studies. The fit of Quinazolinone antifolates inside the active site of modeled bovine dihydrofolate reductase (DHFR) was assessed. Both ligand based (LB) and receptor based (RB) QSAR models were generated, these models showed good internal and external statistical reliability that is evident from the $q^2_{loo}$, $r^2_{ncv}$ and $r^2_{pred}$. The identified key features enabled us to design new Quinazolinone analogues as DHFR inhibitors. This study is a building bridge between docking studies of homology modeled bovine DHFR protein as well as ligand and target based 3D QSAR techniques of CoMFA and CoMSIA approaches.

• EDISON SW 활용 경진대회 논문집
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• 제5회(2016년)
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• pp.126-130
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• 2016

Epidermal growth factor receptor(EGFR)는 HER family에 속하는 tyrosine kinase receptor로서 다양한 하류경로로 신호를 전달하여 세포 증식, 혈관 형성, 세포 사멸을 억제하는 역할을 한다. EGFR이 폐암의 형성에 중요한 역할을 하고 많은 상피세포 종양에서 비정상적으로 활성화됨에 따라 암 치료에 중요한 역할을 하고 있어 EGFR tyrosine kinase inhibitor(TKI)에 관한 많은 연구가 이루어졌다. 위와 같은 약 개발에 있어서 현재 가상 시뮬레이션을 통한 약 후보물질 개발이 진행되고 있다. 특히, Molecular docking 시뮬레이션은 기존의 실험적인 기술(X-ray crystallography, NMR)로는 연구하기가 어려웠던 protein과 ligand간의 상호작용을 예측하여 이에 대한 정보를 제공할 수 있다. 하지만, 우선적으로 Molecular docking 시뮬레이션은 정확한 validation을 기반으로 진행되어야 신뢰할 수 있는 정보를 얻을 수 있다. 따라서 이번 연구에서는 EDISON에서 제공하는 Dock 프로그램과 일반적으로 잘 알려진 Glide, Autodock 프로그램으로 protein data bank(PDB)에서 제공하는 EGFR wild type cocrystal을 redocking하는 방식을 통하여 최상위 rank pose의 RMSD 값을 통한 validation 성능을 비교함으로써 어떤 프로그램이 EGFR과 ligand 간의 결합예측을 하는데 있어서 보다 더 정확한 결과를 낼 수 있는지 알아보고자 하였고 시뮬레이션 결과 Autodock에서 가장 우수한 결과 값을 보여주었다.

• EDISON SW 활용 경진대회 논문집
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• 제2회(2013년)
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• pp.89-100
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• 2013

생물정보학의 다양한 이론적 내용과 계산적 방법들이 갈수록 전문화 되어짐에 따라 신약 개발, 신 물질 합성, 단백질의 구조 예측 등 다양한 분야에서 필요성이 커져가고 있다. 이 중 molecular docking 기술은 단백질과 특정 분자간의 결합 형태를 분자 모델링 기법을 통해 알아내는 방법이며 신약개발 연구에 큰 영향을 미치고 있다. Molecular docking을 통하여 분자간의 결합 형태를 예측하는 과정에서 Protein-ligand complex의 정확한 에너지 측정을 가능하게 하는 scoring function이 필요하다. 그런데 본 연구에서 사용한 B-Raf kinase protein 은 active site 부분에서 ligand와 receptor 간에 aromatic ring로 인한 ${\pi}-{\pi}$ interaction이 정확한 에너지 계산을 어렵게 한다. 이러한 ${\pi}-{\pi}$ interaction 부분의 에너지를 정확하게 계산하기 위해 양자역학 계산을 실시하였다. Active site 부분에서 ligand와 receptor에서 발생하는 각각 다른 5개의 ${\pi}-{\pi}$ interaction 구조를 준비하여 Gaussian을 통해 양자역학 에너지를 계산하였다. 그리고 이러한 결과 값들이 ligand의 활성 값과 어떤 상관관계를 갖는지 살펴보았다. 그 결과 ${\pi}-{\pi}$ interaction을 양자역학으로 계산한 값이 그렇지 않은 것보다 더 좋은 상관관계를 보여주었다. 이는 특별한 구조의 영향으로 ligand와 receptor 간의 결합에너지를 정확하게 계산하기 어려운 문제에서 양자역학을 적용할 경우 더욱 좋은 결과값을 얻을 수 있었다. 또한 이러한 데이터가 신 물질 개발이나 신약 개발 등의 다양한 분야에서 계산화학 방법이 신뢰성을 얻는데 도움 될 수 있다고 생각된다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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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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• 제29권8호
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• pp.1499-1504
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• 2008

Pyrazine derivatives bind to b-RAF receptor which is important in cancer therapy. The ligand-receptor interactions have been studied by comparative molecular field analysis (CoMFA) and molecular docking methods. Applying conventional ligand-based alignment schemes for the whole set was not successful. However, QM and DFT results suggested that some ligands have electrostatic interaction while others have steric interactions. On the basis of these results, we divided the dataset into two subsets. Electrostatic effect was found to be important in one set while steric effect for the other. Best docking modes were obtained for each subset based on the available crystal structure. These receptor-guided CoMFA models propose an interesting possibility which is difficult to obtain otherwise. i.e., in one binding mode the electrostatic interaction plays a key role for one subset ($q^2$ = 0.46, $r^2$ = 0.98), while in another binding mode steric effect is important with another subset ($q^2$ = 0.43, $r^2$ = 0.74).

• Bulletin of the Korean Chemical Society
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• 제34권4호
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• pp.1051-1054
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• 2013

Closo-carborane has been considered as an efficient boron-carrier for boron neutron capture therapy (BNCT) and an attractive surrogate of lipophilic phenyl or cyclohexyl ring in drug design. Despite a great number of carborane-containing ligands have been synthesized and evaluated, molecular modeling studies of carborane ligands with macromolecules have been rarely reported. We herein describe a facile docking and scoring-function strategy of 16 carborane ligands with an estrogen receptor by using the commercial Gaussian, Chem3D Pro and Discovery Studio (DS) computational programs. Docked poses of the carborane ligands in silico exhibited similar binding modes to that of the crystal ligand in the active site of estrogen receptor. Score analysis of the best docked pose for each ligand indicated that the Ligscore1 and the Dockscore have a moderate correlation with in vitro biological activity. This is the first report on the scoring-correlation studies of carborane ligands with macromolecules. The integrated Gaussian-DS approach has a potential application for virtual screening, De novo design, and optimization of carborane ligands in medicinal chemistry.

• 통합자연과학논문집
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• 제11권2호
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• pp.121-129
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• 2018

CXCR6 is a major target in drug design as it is a determinant receptor in many diseases like AIDS, Type I Diabetes, some cancer types, atherosclerosis, tumor formation, liver disease and steatohepatitis. In this study, we propose the active site residues of CXCR6 molecule. We employed homology modelling and molecular docking approach to generate the 3D structure for CXCR6 and to explore its interaction between the antagonists and agonists. 3D models were generated using 14 different templates having high sequence identity with CXCR6. Surflex docking studies using pyridine and pyrimidine derivatives enabled the analysis of the binding site and finding of the important residues involved in binding. 3D structure of CXCL16, a natural ligand for CXCR6, was modelled using PHYRE and protein - protein docking was performed using ClusPro. The residues which were found to be crucial in interaction with the ligand are THR110, PHE113, TYR114, GLN160, GLN195, CYS251 and SER255. This study can be used as a guide for therapeutic studies of human CXCR6.

• Bulletin of the Korean Chemical Society
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• 제32권6호
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• pp.2008-2014
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• 2011

Serotonin or 5-hydroxytryptamine subtype 2C ($5-HT_{2C}$) receptor belongs to class A amine subfamily of G-protein-coupled receptor (GPCR) super family and its ligands has therapeutic promise as anti-depressant and -obesity agents. So far, bovine rhodopsin from class A opsin subfamily was the mostly used X-ray crystal template to model this receptor. Here, we explained homology model using beta 2 adrenergic receptor (${\beta}$2AR), the model was energetically minimized and validated by flexible ligand docking with known agonists and antagonists. In the active site Asp134, Ser138 of transmembrane 3 (TM3), Arg195 of extracellular loop 2 (ECL2) and Tyr358 of TM7 were found as important residues to interact with agonists. In addition to these, V208 of ECL2 and N351 of TM7 was found to interact with antagonists. Several conserved residues including Trp324, Phe327 and Phe328 were also found to contribute hydrophobic interaction. The predicted ligand binding mode is in good agreement with published mutagenesis and homology model data. This new template derived homology model can be useful for further virtual screening based lead identification.