• Title/Summary/Keyword: QSAR modeling

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Novel Lead Optimization Strategy Using Quantitative Structure-Activity Relationship and Physiologically-Based Pharmacokinetics Modeling (정량적 구조-활성 상관 관계와 생리학 기반 약물동태를 사용한 새로운 선도물질 최적화 전략)

  • Byeon, Jin-Ju;Park, Min-Ho;Shin, Seok-Ho;Shin, Young Geun
    • YAKHAK HOEJI
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    • v.59 no.4
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    • pp.151-157
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    • 2015
  • The purpose of this study is to demonstrate how lead compounds are best optimized with the application of in silico QSAR and PBPK modeling at the early drug discovery stage. Several predictive QSAR models such as $IC_{50}$ potency model, intrinsic clearance model and brain penetration model were built and applied to a set of virtually synthesized library of the BACE1 inhibitors. Selected candidate compounds were also applied to the PBPK modeling for comparison between the predicted animal pharmacokinetic parameters and the observed ones in vivo. This novel lead optimization strategy using QSAR and PBPK modelings could be helpful to expedite the drug discovery process.

QM and Pharmacophore based 3D-QSAR of MK886 Analogues against mPGES-1

  • Pasha, F.A.;Muddassar, M.;Jung, Hwan-Won;Yang, Beom-Seok;Lee, Cheol-Ju;Oh, Jung-Soo;Cho, Seung-Joo;Cho, Hoon
    • Bulletin of the Korean Chemical Society
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    • v.29 no.3
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    • pp.647-655
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    • 2008
  • Microsomal prostaglandin E2 synthase (mPGES-1) is a potent target for pain and inflammation. Various QSAR (quantitative structure activity relationship) analyses used to understand the factors affecting inhibitory potency for a series of MK886 analogues. We derived four QSAR models utilizing various quantum mechanical (QM) descriptors. These QM models indicate that steric, electrostatic and hydrophobic interaction can be important factors. Common pharmacophore hypotheses (CPHs) also have studied. The QSAR model derived by best-fitted CPHs considering hydrophobic, negative group and ring effect gave a reasonable result (q2 = 0.77, r2 = 0.97 and Rtestset = 0.90). The pharmacophore-derived molecular alignment subsequently used for 3D-QSAR. The CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) techniques employed on same series of mPGES-1 inhibitors which gives a statistically reasonable result (CoMFA; q2 = 0.90, r2 = 0.99. CoMSIA; q2 = 0.93, r2 = 1.00). All modeling results (QM-based QSAR, pharmacophore modeling and 3D-QSAR) imply steric, electrostatic and hydrophobic contribution to the inhibitory activity. CoMFA and CoMSIA models suggest the introduction of bulky group around ring B may enhance the inhibitory activity.

Prediction of Sorption/Desorption Parameters of Halogenated Aliphatic Compounds Using QSAR (QSAR을 이용한 지방족 할로겐화합물 흡착 및 탈착 계수의 예측)

  • 김종오;박증석;최연돈
    • Journal of Environmental Science International
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    • v.11 no.7
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    • pp.737-742
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    • 2002
  • Sorption and desorption is an important phenomenon to determine the fate of halogenated aliphatic hydrocarbons in the aqueous phase. This study was conducted to develope a predictive equation capable of estimating the sorption and desorption potentials of halogenated aliphatic hydrocarbons onto the sludge from activated process, sediment, and clay. It has shown that the sorption and desorption parameters can be accurately estimated using Quantitative Structural Activity Relationship(QSAR) models based on molecular connectivity indexes of test compounds. The QSAR model could be applied to predict the sorption and desorption capacity of the other halogenated aliphatic hydrocarbons. The QSAR modeling would provide a useful tool to predict the sorption and desorption capacity without time-consuming experiments.

Pharmacophore Modelling, Quantitative Structure Activity Relationship (QSAR) and Docking Studies of Pyrimidine Analogs as Potential Calcium Channel Blockers

  • Choudhari, Prafulla B.;Bhatia, Manish S.;Jadhav, Swapnil D.
    • Journal of the Korean Chemical Society
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    • v.57 no.1
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    • pp.99-103
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    • 2013
  • The present communication deals with the Pharmacophore modeling, 3D QSAR and docking analysis on series of Pyrimidine derivatives as potential calcium channel blockers. The computational studies showed hydrogen bond donor, hydrogen bond acceptor, and hydrophobic group are important features for calcium channel blocking activity. These studies showed that Pyrimidine scaffold can be utilized for designing of novel calcium channels blockers for CVS disorders.

Molecular Modeling of Small Molecules as BVDV RNA-Dependent RNA Polymerase Allosteric Inhibitors

  • Chai, Han-Ha;Lim, Dajeong;Chai, Hee-Yeoul;Jung, Eunkyoung
    • Bulletin of the Korean Chemical Society
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    • v.34 no.3
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    • pp.837-850
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    • 2013
  • Bovine viral diarrhea virus (BVDV), a major pathogen of cattle, is a well-characterized pestivirus which has been used as a good model virus for HCV. The RNA-dependent RNA polymerase (RdRp) plays a key role in the RNA replication process, thus it has been targeted for antivirus drugs. We employed two-dimensional quantitative structure-activity relationship (2D-QSAR) and molecular field analysis (MFA) to identify the molecular substructure requirements, and the particular characteristics resulted in increased inhibitory activity for the known series of compounds to act as effective BVDV inhibitors. The 2D-QSAR study provided the rationale concept for changes in the structure to have more potent analogs focused on the class of arylazoenamines, benzimidazoles, and acridine derivatives with an optimal subset of descriptors, which have significantly contributed to overall anti-BVDV activity. MFA represented the molecular patterns responsible for the actions of antiviral compound at their receptors. We conclude that the polarity and the polarizability of a molecule play a main role in the inhibitory activity of BVDV inhibitors in the QSAR modeling.

QSAR Modeling of Toxicant Concentrations(EC50) on the Use of Bioluminescence Intensity of CMC Immobilized Photobacterium Phosphoreum (CMC 고정화 Photobacterium phosphoreum 의 생체발광량을 이용한 독성농도(EC50)의 QSAR 모델)

  • 이용제;허문석;이우창;전억한
    • KSBB Journal
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    • v.15 no.3
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    • pp.299-306
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    • 2000
  • Concern for the effects of toxic chemicals on the environment leads the search for better bioassay test organisms and test procedures. Photobacterium phosphoreum was used successfully as a test organism and the luminometer detection technique was an effective and simple method for determining the concentration of toxic chemicals. With EC50 a total of 14 chlorine substituted phenols benzenes and ethanes were used for the experiments. The test results showed that the toxicity to P. phosphoreum increased in the order of phenol > benzene > ethane and the toxicity also increased with the number of chlorine substitution. Quantitative structure activity relationship (QSARO) model can be used to predict EC50 to save time and endeavor. Correlation was well established with the QSAR parameters such as log P, log S and solvatochromic parameter(Vi/100 $\pi$, ${\beta}$m and am). The QSAR modeling was used with multi-regression analysis and mono-regression analysis. These analyses resulted in the following QSAR : $log EC_{50} =2.48 + 0.914 log S(n=9 R2=85.5% RE=0.378) log EC_{50}=0.35 - 4.48 Vi/100 + 2.84 \pi^* +9.46{\beta}m-4.48am (n =14 R2=98.2% RE=0.012) log EC_{50} =2.64 -1.66 log P(n=5, R2=98.8% RE=0.16) log EC_{50}=3.44 -1.09 log P(n=9 R2= 80.8% Re=0.207)$

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Modeling Aided Lead Design of FAK Inhibitors

  • Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.4 no.4
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    • pp.266-272
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    • 2011
  • Focal adhesion kinase (FAK) is a potential target for the treatment of primary cancers as well as prevention of tumor metastasis. To understand the structural and chemical features of FAK inhibitors, we report comparative molecular field analysis (CoMFA) for the series of 7H-pyrrolo(2,3-d)pyrimidines. The CoMFA models showed good correlation between the actual and predicted values for training set molecules. Our results indicated the ligand-based alignment has produced better statistical results for CoMFA ($q^2$ = 0.505, $r^2$ = 0.950). Both models were validated using test set compounds, and gave good predictive values of 0.537. The statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The contour map from 3D-QSAR models explains nicely the structure-activity relationships of FAK inhibitors and our results would give proper guidelines to further enhance the activity of novel inhibitors.

Computational Drug Discovery Approach Based on Nuclear Factor-κB Pathway Dynamics

  • Nam, Ky-Youb;Oh, Won-Seok;Kim, Chul;Song, Mi-Young;Joung, Jong-Young;Kim, Sun-Young;Park, Jae-Seong;Gang, Sin-Moon;Cho, Young-Uk;No, Kyoung-Tai
    • Bulletin of the Korean Chemical Society
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    • v.32 no.12
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    • pp.4397-4402
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    • 2011
  • The NF-${\kappa}B$ system of transcription factors plays a crucial role in inflammatory diseases, making it an important drug target. We combined quantitative structure activity relationships for predicting the activity of new compounds and quantitative dynamic models for the NF-${\kappa}B$ network with intracellular concentration models. GFA-MLR QSAR analysis was employed to determine the optimal QSAR equation. To validate the predictability of the $IKK{\beta}$ QSAR model for an external set of inhibitors, a set of ordinary differential equations and mass action kinetics were used for modeling the NF-${\kappa}B$ dynamic system. The reaction parameters were obtained from previously reported research. In the IKKb QSAR model, good cross-validated $q^2$ (0.782) and conventional $r^2$ (0.808) values demonstrated the correlation between the descriptors and each of their activities and reliably predicted the $IKK{\beta}$ activities. Using a developed simulation model of the NF-${\kappa}B$ signaling pathway, we demonstrated differences in $I{\kappa}B$ mRNA expression between normal and different inhibitory states. When the inhibition efficiency increased, inhibitor 1 (PS-1145) led to long-term oscillations. The combined computational modeling and NF-${\kappa}B$ dynamic simulations can be used to understand the inhibition mechanisms and thereby result in the design of mechanism-based inhibitors.