• The Plant Pathology Journal
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• 제33권6호
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• pp.529-542
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• 2017

Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.

• BMB Reports
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• 제36권2호
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• pp.207-213
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• 2003

Peroxisome proliferator-activated receptors (PPARs) are orphan nuclear hormone receptors that are known to control the expression of genes that are involved in lipid homeostasis and energy balance. PPARs activate gene transcription in response to a variety of compounds, including hypolipidemic drugs. Most of these compounds have high affinity to the ligand-binding domain (LBD) of PPARs and cause a conformational change within PPARs. As a result, the receptor is converted to an activated mode that promotes the recruitment fo co-activators such as the steroid receptor co-activator-1 (SRC-1). Based on the activation mechanism of PPARs (the ligand binding to $PPAR{\gamma}$ induces interactions of the receptor with transcriptional co-activators), we performed Western blot and ELISA. These showed that the indomethacin, a $PPAR{\gamma}$ ligand, increased the binding between $PPAR{\gamma}$ and SRC-1 in a ligand dose-dependent manner. These results suggested that the in vitro conformational change of $PPAR{\gamma}$ by ligands was also induced, and increased the levels of the ligand-dependent interaction with SRC-1. Collectively, we developed a novel and useful ELISA system for the mass screening of $PPAR{\gamma}$ ligands. This screening system (based on the interaction between $PPAR{\gamma}$ and SRC-1) may be a promising system in the development of drugs for metabolic disorders.

• Journal of Industrial and Engineering Chemistry
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• 제67권
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• pp.293-300
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• 2018

Lipocalins are diverse group of small extracellular proteins found in various organisms. In this study, members of 10 non-homologous lipocalin-ligand crystal complex structures were remodeled using rigid and flexible ligand modes to validate the prediction efficiency of molecular docking simulation. The modeled ligand conformations indicated a high prediction accuracy in rigid ligand mode using cluster based analysis for most cases whereas the flexible ligand mode required further considerations such as ligand binding energy and RMSD for some cases. This in silico study is expected to serve as a platform in the screening of novel ligands against lipocalin family of proteins.

• Asian Pacific Journal of Cancer Prevention
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• 제16권9호
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• pp.3817-3825
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• 2015

Background: The human protein methyl-transferase DOT1L catalyzes the methylation of histone H3 on lysine 79 (H3K79) at homeobox genes and is also involved in a number of significant processes ranging from gene expression to DNA-damage response and cell cycle progression. Inhibition of DOT1L activity by shRNA or small-molecule inhibitors has been established to prevent proliferation of various MLL-rearranged leukemia cells in vitro, establishing DOT1L an attractive therapeutic target for mixed lineage leukemia (MLL). Most of the drugs currently in use for the MLL treatment are reported to have low efficacy, hence this study focused on various natural compounds which exhibit minimal toxic effects and high efficacy for the target receptor. Materials and Methods: Structures of human protein methyl-transferase DOT1L and natural compound databases were downloaded from various sources. Virtual screening, molecular docking, dynamics simulation and drug likeness studies were performed for those natural compounds to evaluate and analyze their anti-cancer activity. Results: The top five screened compounds possessing good binding affinity were identified as potential high affinity inhibitors against DOT1L's active site. The top ranking molecule amongst the screened ligands had a Glide g-score of -10.940 kcal/mol and Glide e-model score of -86.011 with 5 hydrogen bonds and 12 hydrophobic contacts. This ligand's behaviour also showed consistency during the simulation of protein-ligand complex for 20000 ps, which is indicative of its stability in the receptor pocket. Conclusions: The ligand obtained out of this screening study can be considered as a potential inhibitor for DOT1L and further can be treated as a lead for the drug designing pipeline.

• 통합자연과학논문집
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• 제3권3호
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• pp.162-167
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• 2010

A pseudoreceptor combines structure-based and ligand-based techniques to represent a unifying concept for both receptor mapping and ligand matching. In this molecular modeling approach, there are opportunities to construct the pseudoreceptor models using a set of small molecules. To build a reliable pseudoreceptor model, we need a set of ligand molecules with known affinity (biological activity) to generate 3D bioactive conformation for each of these ligand molecules. Several software packages are available to generate a pseudoreceptor model and this can provide an entry point for structure based drug discovery in cases where receptor structure information is not available. In this review, we presented the concept of pseudoreceptor, as well as discussed about various software packages available to generate a pseudoreceptor model.

• 대한약학회:학술대회논문집
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• 대한약학회 2002년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.2
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• pp.359.3-359.3
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• 2002

Protein-tyrosine phosphatase 1 B(PTP-l B). which plays a key role in insulin signaling. is rising as a fascinating target for type 2 diabetes and obesity. Many scientists in structural biology solved the three dimensional X-ray Crystal structure of this type of enzyme, so we could easily get the active site structure of PTP-1 B or complex structure with ligand. Our virtual screening study for PTP-1B exactly based on these crystal strucutures from public database. (omitted)

• Journal of Microbiology and Biotechnology
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• 제23권6호
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• pp.779-784
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• 2013

Leptospirosis is a worldwide zoonosis of global concern caused by Leptospira interrogans. The availability of ligand libraries has facilitated the search for novel drug targets using chemogenomics approaches, compared with the traditional method of drug discovery, which is time consuming and yields few leads with little intracellular information for guiding target selection. Recent subtractive genomics studies have revealed the putative drug targets in peptidoglycan biosynthesis pathways in Leptospira interrogans. Aligand library for the murD ligase enzyme in the peptidoglycan pathway has also been identified. Our approach in this research involves screening of the pre-existing ligand library of murD with related protein family members in the putative drug target assembly in the peptidoglycan biosynthesis pathway. A chemogenomics approach has been implemented here, which involves screening of known ligands of a protein family having analogous domain architecture for identification of leads for existing druggable protein family members. By means of this approach, one murC and one murF inhibitor were identified, providing a platform for developing an anti-leptospirosis drug targeting the peptidoglycan biosynthesis pathway. Given that the peptidoglycan biosynthesis pathway is exclusive to bacteria, the in silico identified mur ligase inhibitors are expected to be broad-spectrum Gram-negative inhibitors if synthesized and tested in in vitro and in vivo assays.

• 한국정보과학회논문지:시스템및이론
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• 제35권6호
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• pp.237-247
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• 2008

가상 탐색은 대규모의 화학분자 데이타베이스의 화학분자 데이타들을 분자 다킹과 같은 컴퓨팅 기술을 이용하여 한정된 소규모의 화학분자만을 스크리닝하는 과정으로, 대규모 컴퓨팅 파워와 데이터 저장 용량을 요구하는 대표적인 대규모의 과학 어플리케이션이다. AutoDock, FlexX, Glide, DOCK, LigandFit, ViSION 등과 같은 기존의 분자 다킹 소프트웨어나 어플리케이션들은 슈퍼 컴퓨터, 단일 클러스터, 또는 단일 워크스테이션 둥을 이용하여 작업을 수행하도록 개발되었다. 하지만 슈퍼컴퓨터를 이용한 가상 탐색은 너무 많은 비용이 든다는 문제점이 있고, 단일 클러스터나 워크스테이션을 이용한 가상 탐색은 오랜 수행 시간이 요구되는 문제점을 가지고 있다. 이에 본 논문에서는 대규모의 데이타 집약적인 연산을 지원하는 그리드 컴퓨팅 기술을 이용하는 서비스 기반 가상 탐색 시스템을 제안한다. 이를 위해 본 논문에서는 가상 탐색을 위한 3차원 화학 데이타베이스를 구축하였다. 그리고 효율적인 분자 다킹 서비스를 제공하기 위해 자원 브로커와 데이타 브로커를 설계하고 가상 탐색을 위한 다양한 서비스들을 제안하였다. 본 논문에서는 DOCK 5.0과 Globus 3.2를 이용하여 서비스 기반 가상 탐색 시스템을 구현하고 성능 평가를 실시하였다. 본 논문에서 구현한 서비스 기반 가상 탐색 시스템은 신약 개발이나 신소재 개발 과정에서 연구 개발 기간을 단축하고 개발 비용을 절감할 수 있다.

• 한국자기공명학회논문지
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• 제6권2호
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• pp.94-102
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• 2002

An interesting recent application of intermolecular NOE experiment is the saturation transfer difference NMR(STD-NMR) method that is useful in screening compound libraries to identify bio-active ligands. This technique also identifies the group epitopes of the bound ligand in a reversibly forming protein-ligand complex. We present here a complete relaxation and conformational exchange matrix (CORCEMA) theory (Moseley et al., J. Magn. Reson. B, 108, 243-261 (1995)) applicable for the STD-NMR experiment. Using some ideal model systems we have analyzed the factors that influence the STD intensity changes in the ligand proton NMR spectrum when the resonances from some protons on the receptor protein are saturated. These factors will be discussed and some examples of its application in some model systems will be presented. This CORCEMA theory for STD-NMR and the associated algorithm are useful in a quantitative interpretation of the STD-NMR effects, and are likely to be useful in structure-based drug design efforts. They are also useful in a quantitative characterization of protein-protein (or protein-nucleic acid) contact surfaces from an intermolecular cross-saturation NMR experiment.

• 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.