• The Plant Pathology Journal
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• v.33 no.6
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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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• v.36 no.2
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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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• v.67
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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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• v.16 no.9
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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.

• Journal of Integrative Natural Science
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• v.3 no.3
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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.

• Proceedings of the PSK Conference
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• 2002.10a
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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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• v.23 no.6
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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.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.6
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• pp.237-247
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• 2008

A virtual screening is the process of reducing an unmanageable number of compounds to a limited number of compounds for the target of interest by means of computational techniques such as molecular docking. And it is one of a large-scale scientific application that requires large computing power and data storage capability. Previous applications or softwares for molecular docking such as AutoDock, FlexX, Glide, DOCK, LigandFit, ViSION were developed to be run on a supercomputer, a workstation, or a cluster-computer. However the virtual screening using a supercomputer has a problem that a supercomputer is very expensive and the virtual screening using a workstation or a cluster-computer requires a long execution time. Thus we propose a service-based virtual screening system using Grid computing technology which supports a large data intensive operation. We constructed 3-dimensional chemical molecular database for virtual screening. And we designed a resource broker and a data broker for supporting efficient molecular docking service and proposed various services for virtual screening. We implemented service based virtual screening system with DOCK 5.0 and Globus 3.2 toolkit. Our system can reduce a timeline and cost of drug or new material design.

• Journal of the Korean Magnetic Resonance Society
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• v.6 no.2
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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.

• Journal of Integrative Natural Science
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• v.3 no.3
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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.