Comparative Molecular Field Analysis Results Research Articles

3D-QSAR (CoMFA, CoMSIA, HQSAR and topomer CoMFA), MD simulations and molecular docking studies on purinylpyridine derivatives as B-Raf inhibitors for the treatment of melanoma cancer

As per the World Health Organization (WHO), cancer is the second most leading cause of death after cardiovascular diseases in worldwide with around 9.88 million total new cases and 1.08 million were observed due to skin cancer in 2018. Amongst two types of skin cancer, progression of melanoma cancer is increasing day by day due to the environmental changes than non-melanoma cancer. Most of B-Raf mutation, specifically B-RafV600E, is responsible for the progression of the melanoma cancer. Here, various 3D-QSAR techniques like comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), molecular hologram QSAR (HQSAR) and topomer CoMFA were used to design novel B-Raf inhibitors by using 28 synthetic B-Raf inhibitors. Except for topomer CoMFA model, remaining models were generated by three different alignment methods in which distil-based alignment method was found best and gave prominent statistical values. After performing N-fold statistical validation, in CoMFA, q2, r2 and r2pred values were found to be 0.638, 0.969 and 0.848, respectively. Similarly, q2, r2 and r2pred values were found to be 0.796, 0.978 and 0.891 in CoMSIA (SHD) and 0.761, 0.973 and 0.852 in CoMSIA (SH) by N-fold statistical validation. In HQSAR analysis, statistical values were found for q2 as 0.984, r2 as 0.999 and r2pred as 0.634 with 97 as best hologram length (BHL). The results of topomer CoMFA showed the q2 value of 0.663 and the r2 value of 0.967. Important features of purinylpyridine were identified by contour map analysis of all 3D-QSAR techniques, which could be useful to design the novel molecules as B-Raf inhibitors for the treatment of melanoma cancer.

3D-QSAR-aided design of potent c-Met inhibitors using molecular dynamics simulation and binding free energy calculation

Mesenchymal-epithelial transition factor (c-Met) is a member of receptor tyrosine kinase. It involves in various cellular signaling pathways which includes proliferation, motility, migration, and invasion. Over-expression of c-Met has been reported in various cancers. Hence, it is an ideal therapeutic target for cancer. The main objective of the study is to identify crucial residues involved in the inhibition of c-Met kinase and to design a series of potent imidazo [4,5-b] pyrazine derivatives as c-Met inhibitors. Docking was used to identify important active site residues involved in the inhibition of c-Met kinase which was further validated by 100 ns of molecular dynamics simulation and free energy calculation using molecular mechanics generalized born surface area. Furthermore, binding energy decomposition identified that residues Tyr1230, Met1211, Asp1222, Tyr1159, Met1160, Val1092, Ala1108, and Leu1157 contributed favorably to the binding stability of compound 32. Receptor-guided Comparative Molecular Field Analysis (CoMFA) (q2 = 0.751, NOC = 6, r2 = 0.933) and Comparative Molecular Similarity Indices Analysis (COMSIA) (q2 = 0.744, NOC = 6, r2 = 0.950) models were generated based on the docked conformation of the most active compound 32. The robustness of these models was tested using various validation techniques and found to be predictive. The results of CoMFA and CoMSIA contour maps exposed the regions favorable to enhance the activity. Based on this information, 27 novel c-Met inhibitors were designed. These designed compounds exhibited potent activity than the most active compound of the existing dataset.Communicated by Ramaswamy H. Sarma

Combined HQSAR, topomer CoMFA, homology modeling and docking studies on triazole derivatives as SGLT2 inhibitors.

Sodium-glucose cotransporter 2 (SGLT2) is a promising target for diabetes therapy. We aimed to develop computational approaches to identify structural features for more potential SGLT2 inhibitors. In this work, 46 triazole derivatives as SGLT2 inhibitors were studied using a combination of several approaches, including hologram quantitative structure-activity relationships (HQSAR), topomer comparative molecular field analysis (CoMFA), homology modeling, and molecular docking. HQSAR and topomer CoMFA were used to construct models. Molecular docking was conducted to investigate the interaction of triazole derivatives and homology modeling of SGLT2, as well as to validate the results of the HQSAR and topomer CoMFA models. The most effective HQSAR and topomer CoMFA models exhibited noncross-validated correlation coefficients of 0.928 and 0.891 for the training set, respectively. External predictions were made successfully on a test set and then compared with previously reported models. The graphical results of HQSAR and topomer CoMFA were proven to be consistent with the binding mode of the inhibitors and SGLT2 from molecular docking. The models and docking provided important insights into the design of potent inhibitors for SGLT2.

MSEP and CoMFA Studies on the Melting Points of Nitroaromatic Compounds

A 3D quantitative structure–property relationship (3D‐QSPR) study was performed to predict the melting points of 51 nitroaromatic compounds using the molecular surface electrostatic potential (MSEP) approach developed by the authors and comparative molecular field analysis (CoMFA) implemented in the SYBYL package. The structures of all 51 compounds were optimized using the hybrid density functional theory (DFT) at the B3LYP/6‐31G(d) level of theory. In both approaches, 46 compounds were assigned as the training set and the rest as the test set. In the MSEP approach, a multiple linear regression (MLR) equation was obtained to estimate the melting points of the training set molecules using five descriptors. The best CoMFA results presented a cross‐validated value (q 2) of 0.615, and non‐cross‐validated value (r 2) of 0.978. The melting points of five test‐set molecules were predicted from the MLR and partial least squares (PLS) equations obtained from the MSEP and CoMFA approaches, respectively. This study shows that the CoMFA approach can be applied to estimate the melting point and some other physicochemical properties of high energy density materials (HEDMs) with reasonable accuracy if there are structural similarities in the dataset.

HQSAR and topomer CoMFA for predicting melanocortin-4 receptor binding affinities of trans-4-(4-chlorophenyl) pyrrolidine-3-carboxamides

Hologram quantitative structure–activity relationships (HQSAR) and topomer comparative molecular field analysis (CoMFA) were implemented on a group of 73 trans-4-(4-chlorophenyl) pyrrolidine-3-carboxamides of piperazinecyclohexane compounds, and their binding affinities to the melanocortin-4 receptor (MC4R) were determined. The most effective HQSAR model was obtained using atoms and bonds as fragment distinction, and its cross-validated (q2) and non-cross-validated (r2) correlation coefficients were 0.665 and 0.907, respectively. Several external validation parameters (i.e., four ways to calculate the correlation coefficients of the test set samples), namely, QF12, QF22, QF32, and CCC, were 0.781, 0.766, 0.789, and 0.901, respectively. Topomer CoMFA models were built based on three fragment cutting modes. The most effective topomer CoMFA (r2=0.850, q2=0.436, QF12=0.784, QF22=0.779, QF32=0.751, and CCC=0.894) used the amide bond as the cut bond. Meanwhile, the predictive capabilities of the most effective HQSAR and topomer CoMFA models were tested and verified via an external test set with 15 compounds, and then compared with those of previously reported models. Molecular docking was employed to validate the results of the HQSAR and topomer CoMFA models. Moreover, the graphical results of HQSAR, topomer CoMFA, and docking were analyzed and used as guides in designing new MC4R ligands. The results of this work would be useful in chemical library design, virtual screening, and high-throughput screening.

Ligand-based CoMFA and CoMSIA studies on chromone derivatives as radical scavengers

The antioxidant activity for a series of chromone compounds, evaluated by DPPH free radical scavenging assay, were subjected to 3D-QSAR studies using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). All 48 chromone derivatives were geometry optimized by AM1 and HF/6-31G* calculations. The CoMFA and CoMSIA results were compared between different alignment strategies. The best CoMFA model obtained from HF/6-31G* optimization with field fit alignment gave cross-validated r2 (q2)=0.821, noncross-validated r2=0.987, S=0.095, and F=388.255. The best CoMSIA model derived from AM1 optimized structures and superimposition alignment gave q2=0.876, noncross-validated r2=0.976, S=0.129, and F=208.073, including electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. The contour maps provide the fruitful structure–radical scavenging activity relationships which are useful for designing new compounds with higher activity.

3D-QSAR, docking and molecular dynamics for factor Xa inhibitors as anticoagulant agents

Factor Xa is an interesting target for design of new anticoagulants as it is positioned at the beginning of the coagulation common pathway. In this study, two different modelling methods, alignment dependent and alignment independent three-dimensional (3D) quantitative structure–activity relationship approaches, including comparative molecular field analysis (CoMFA) and GRid INdependent descriptors (GRIND) (AMANDA), along with molecular docking and molecular dynamics (MD) simulations have been conducted on a series of 50 N1-(5-chloro-2-pyridyl)-2-{[4-(alkylmethyl)benzoyl]amino}-5-chlorobenzamide analogues as factor Xa inhibitors to understand the 3D structural features affecting their inhibitory activity. Validation of the models was done using cross-validation method in addition to the external test set prediction. Both CoMFA (q 2 = 0.66, = 0.97, = 0.56, = 0.55) and GRIND models (q 2 = 0.86, = 0.93, = 0.71, = 0.71) yielded significant statistical results. The sensitivity of the optimised partial least square models was evaluated by performing progressive Y scrambling. In addition, to verify prediction reliability, the chemical applicability domains of the models were checked by the leverage approach. Furthermore, there is a good agreement between CoMFA and GRIND graphical results as well as MD-based docking analysis. The outcomes of this study may result in a better understanding of the inhibition mechanism of factor Xa and aided in the development of new and more potent anticoagulant drugs.

Optimization of (Phenylmethylidene)‐hydantoins as Prostate Cancer Migration Inhibitors: SAR‐Directed Design, Synthesis, and Pharmacophore Modeling

AbstractProstate cancer is one of the most common cancer forms among males of Western countries. Natural products proved to be an unparalleled source of molecular diversity. The 4‐(hydroxyphenylmethylidene)hydantoin (PMH; 1), (5Z)‐5‐(4‐hydroxybenzylidene)imidazolidine‐2,4‐dione, was isolated from the Red Sea sponge Hemimycale arabica, and recently showed junctional complexes stabilization, anti‐invasive, and antimetastatic activities in vitro and in vivo. The related synthetic analogue, (5Z)‐5‐[4‐(ethylsulfanyl)benzylidene]imidazolidine‐2,4‐dione (2), showed several‐fold‐improved in vivo antimetastatic properties against the highly invasive prostate cancer. To further optimize the activity of PMHs, various ligand‐based strategies were used including the extension of the structure, structural simplification, linker extension, and computer‐assisted CoMFA (Comparative Molecular Field Analysis) results. These strategies yielded thirty 2nd‐generation PMHs, designed based on the 1st‐generation PMHs, such as 1 and 2. Wound‐healing assay was selected to evaluate the in vitro anti‐migratory potential of these new PMHs against the PC‐3 cell line. Several active PMHs, including 10, 13, 24, 29, with nearly twelvefold enhancement of activity vs. 2, were identified. Active compounds were then used to build a pharmacophore model using the SYBYL's DIStance COmparison technique (DISCOtech). Active PMHs were also screened for fragment‐based drug likeness using the OSIRIS program, and an overall drug score was also calculated. Interestingly, the overall drug scores of 24 and 29 along with their anti‐migratory activity were significantly greater than those of 1 and 2. In conclusion, PMHs can be the appropriate scaffolds for the urgently needed drug candidates for the control of androgen independent prostate cancer.

Comparative docking and CoMFA analysis of curcumine derivatives as HIV-1 integrase inhibitors

The docking studies and comparative molecular field analysis (CoMFA) were performed on highly active molecules of curcumine derivatives against 3' processing activity of HIV-1 integrase (IN) enzyme. The optimum CoMFA model was selected with statistically significant cross-validated r(2) value of 0.815 and non-cross validated r (2) value of 0.99. The common pharmacophore of highly active molecules was used for screening of HIV-1 IN inhibitors. The high contribution of polar interactions in pharmacophore mapping is well supported by docking and CoMFA results. The results of docking, CoMFA, and pharmacophore mapping give structural insights as well as important binding features of curcumine derivatives as HIV-1 IN inhibitors which can provide guidance for the rational design of novel HIV-1 IN inhibitors.

Pharmacophore-based 3D-QSAR of HIF-1 inhibitors

(Aryloxyamino)benzoic acids and nicotinic/isonicotinic acids represent an important new class of small molecules that inhibit the activation of hypoxia-inducible factor (HIF)-1. In order to understand the factors affecting inhibitory potency of HIF-1 inhibitors, 3 dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed. Since no receptor structure are available, the pharmacophore-based alignment was used for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The CoMFA and CoMSIA models gave reasonable statistics (CoMFA: q(2) = 0.564, r(2)=0.945; CoMSIA: q(2) = 0.575, r(2)=0.929). Both CoMFA and CoMSIA results indicate that the steric interaction is a major factor, while CoMSIA suggests importance of hydrogen bonding. These findings about steric and H-bonding effects can be useful to design new inhibitors.

2D- and 3D-QSAR studies on 54 anti-tumor Rubiaceae-type cyclopeptides

RA-VII, a bicyclic hexapeptide isolated from the roots of Rubia cordifolia, Rubia akane belongs to Rubiaceae-type cyclopeptides (RAs) and has attracted much attention for its potent anti-tumor activity and its bicyclic structure incorporating the isodityrosine moiety. In this work, hologram quantitative structure–activity relationship (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) methods were employed to develop 2D- and 3D-QSAR models for 54 anti-tumor RAs. The LOO cross-validated q 2 values of HQSAR, CoMFA and CoMSIA models are 0.701, 0.510 and 0.613, respectively. The predictive ability of these models was validated by the test set including 7 RAs, and the predicted IC 50 values were in good agreement with the experimental IC 50 values. HQSAR result showed that chirality descriptor plays an important role in anti-tumor activity of RAs and OMe at R 1 and R 2 is necessary for increasing their activity. CoMFA and CoMSIA results demonstrated that small bulky and electropositive side chains at R 3 position and hydrophobic groups at R 7 and R 8 positions will increase their activity, and intra-molecular hydrogen bonds between residues 1 and 4 are necessary to maintain the pharmacophoric conformation of RAs. These results may be helpful in designing novel and potential anti-tumor RAs.

2D- and 3D-QSAR studies on 54 anti-tumor Rubiaceae-type cyclopeptides

RA-VII, a bicyclic hexapeptide isolated from the roots of Rubia cordifolia, Rubia akane belongs to Rubiaceae-type cyclopeptides (RAS) and has attracted much attention for its potent anti-tumor activity and its bicyclic structure incorporating the isodityrosine moiety. In this work, hologram quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) methods were employed to develop 2D- and 3D-QSAR models for 54 anti-tumor RAS. The LOO cross-validated q(2) values of HQSAR, CoMFA and CoMSIA models are 0.701, 0.510 and 0.613, respectively. The predictive ability of these models was validated by the test set including 7 RAS, and the predicted IC(50) values were in good agreement with the experimental IC50 values. HQSAR result showed that chirality descriptor plays an important role in anti-tumor activity of RAS and OMe at R(1) and R(2) is necessary for increasing their activity. CoMFA and CoMSIA results demonstrated that small bulky and electropositive side chains at R(3) Position and hydrophobic groups at R(7) and R(8) positions will increase their activity, and intra-molecular hydrogen bonds between residues 1 and 4 are necessary to maintain the pharmacophoric conformation of RAS. These results may be helpful in designing novel and potential anti-tumor RAS. (C) 2009 Elsevier Masson SAS. All rights reserved.

DFT‐based de novo QSAR of Phenoloxidase Inhibitors

The phenoloxidase or tyrosinase is a key enzyme in insects, which is responsible for hydroxylation of tyrosine into o-quinones via o-diphenols. A series of benzaldehyde thiosemicarbazone, benzaldehyde and benzoic acid families were taken with their pragmatic pIC(50) values against phenoloxidase from pieris rapae (Lepidoptera) larvae. Density functional theory-based quantitative structure-activity relationship (QSAR) analyses were performed to speculate the key interaction. The most fitted four different QSAR models were identified and discussed. The softness, electrophilicity index, molar refractivity and log P were identified as best descriptors; however, the atomic values of softness and philicity obtained from Fukui function are more significant than global values. The study reveals that electrostatic and steric fields jointly contribute to activity. To gain further insight, the three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses were performed using two molecular field techniques: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The successful 3D-QSAR models were obtained from CoMFA (q(2)= 0.94, r(2)= 0.99, r(2)(pred)= 0.92) and CoMSIA (q(2)= 0.94, r(2)= 0.98, r(2)(pred)= 0/95). The CoMFA and CoMSIA results indicate that, a bulky and negative group around sulfur atom but a small and positive group around nitrogen atom might have good effects on activity. The ortho and meta positions of ring are favorable for small group. These QSAR models might be helpful to design the novel and potent inhibitors.

Structural basis for androgen receptor agonists and antagonists: Interaction of SPEED 98-listed chemicals and related compounds with the androgen receptor based on an in vitro reporter gene assay and 3D-QSAR

The androgen receptor (AR) activity of listed chemicals, so called SPEED 98, by the Ministry of the Environment, Japan, and structurally related chemicals was characterized using MDA-kb2 human breast cancer cells stably expressing an androgen-responsive luciferase reporter gene, MMTV-luc. Since our results suggested that chemicals with diverse chemical structures were capable of disrupting the endocrine systems mediated by AR, a comparative molecular field analysis (CoMFA) model was developed to analyze the structural requirements necessary to disrupt AR function. A significant CoMFA model with r 2 = 0.825 and q 2 = 0.332 was developed for AR antagonist activity of 35 pure antagonists excluding procymidone. On the other hand, a good CoMFA model with r 2 = 0.983 and q 2 = 0.555 was obtained for antagonist activity of 13 chemicals with both agonist and antagonist activities. The steric and electrostatic properties were sufficient to describe the structural requirements for AR antagonist activity. In addition, the structural difference of AR agonists and antagonists was explained based on CoMFA results and the AR-LBD crystal structure. As several ERα agonists such as diethylstilbestrol (DES) acted as AR antagonists, the surface area of the AR ligand-binding domain (LBD) was compared with that of the ERα-LBD based on their reported crystal structures to analyze how those ligands interact with LBDs. The surface area of AR-LBD was shown to be smaller than that of ERα-LBD and therefore compounds with both estrogenic and antiandrogenic activities can fit well into the ERα-LBD but may protrude from the AR-LBD. It is likely that this subtle difference of the surface areas of the LBDs determines whether an ERα agonist acts as an AR antagonist or an agonist.

The molecular basis for coxib inhibition of p38α MAP kinase

In this work, we present the results of two combined approaches, molecular docking and comparative molecular field analysis (CoMFA), to propose how the selective cyclooxygenase-2 inhibitor celecoxib could act as a p38 mitogen-activated protein (MAP) kinase inhibitor. The docking analysis revealed why celecoxib has a less favorable binding energy (Δ G = −12.4 kcal/mol) than the selective p38 MAP kinase (p38 MAPK) inhibitor, SB203580 (Δ G = −22.2 kcal/mol). The CoMFA results revealed unfavorable steric effects that can be related to the predicted lower p38 MAP kinase inhibitory activity of celecoxib. Additionally, FlexX and CoMFA results also suggested that etoricoxib, another selective COX-2 inhibitor, could inhibit p38 MAP kinase.

Binding Model Construction of Antifungal 2-Aryl-4-chromanones Using CoMFA, CoMSIA, and QSAR Analyses

Flavonoids, generated by plants upon attack by a range of pathogens, are demonstrated to have a role in biotic and abiotic stress response phenomena in plants, and there is increasing evidence for the antibacterial, antifungal, and antiviral activities of these compounds. Using the bioisosterism strategy, a series of 2-aryl-4-chromanone derivatives based upon the structure of flavanones, a kind of flavonoid phytoalexins, were synthesized and tested for the antifungal activity against Pyricularia grisea, which have been reported in our previous papers. To further explore the comprehensive structure-activity relationship and construct the binding model for the antifungal compounds, two kinds of molecular field analysis techniques, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), were performed following a Hansch-Fujita QSAR study. Superimpositions were performed using three alignment rules, that is, centroid-based alignment, common substructure-based alignment, and field fit alignment, and statistically reliable models with good predictive power (CoMFA r(2) = 0.952, q(2) = 0.727; CoMSIA r(2) = 0.965, q(2) = 0.751) were achieved on the basis of the common substructure-based alignment. The combined results of CoMFA, CoMSIA, and former Hansch-Fujita QSAR analyses resulted in comprehensive understanding about the structure-activity relationships, which led to this construction of a plausible binding model of the title compounds.

Three-dimensional quantitative structure–activity relationship for several bioactive peptides searched by a convex hull–comparative molecular field analysis approach

Three-dimensional (3D) convex hulls are computed for theoretically generated structures of a group of 18 bioactive tachykinin peptides. The number of peptides treated as a training set is 14, whereas that treated as a test set is four. The frequency of atoms of the same atomic type lying at the vertices of all the hulls computed for all the structures in a structural set is counted. Vertex atoms with non-zero frequency counted are collected together as a set of commonly exposed groups. These commonly exposed atoms are then treated as a set of correspondences for aligning all the other 13 structures in a structural set against a common template, which is the structure of the most potent peptide in the set using the FIT module of the sybyl 6.6 program. Each aligned structural set is then analyzed by the comparative molecular field analysis (CoMFA) module using the C.3 probe having a charge of +1.0. The corresponding cross-validated r 2 values range from −0.99 to 0.57 for a number of 73 structural sets studied. The comparative molecular similarity indices analysis (CoMSIA) module within the sybyl 6.6 package is also used to analyze some of these aligned structural sets. Although the CoMSIA results are in accord with those of CoMFA, it is also found that the CoMFA results of several structural sets can be improved somewhat for conformations of the structures in the sets that are adjusted by constraint energy minimization and then constraint molecular dynamics simulation runs using distance constraints derived from some commonly exposed groups determined for them. This result further implies that the convex hull–CoMFA is a feasible approach to screen the bioactive conformations for molecules of this class.

3-D QSAR analysis of inhibition of murine soluble epoxide hydrolase (MsEH) by benzoylureas, arylureas, and their analogues

Two hundred and seventy-one compounds including benzoylureas, arylureas and related compounds were assayed using recombinant murine soluble epoxide hydrolase (MsEH) produced from a baculovirus expression system. Among all the insect growth regulators assayed, 18 benzoylphenylurea congeners showed weak activity against MsEH. Newly synthesized cyclohexylphenylurea, 1-benzyl-3-phenylurea, and 1,3-dibenzylurea analogues were rather potent. The introduction of a methyl group at the para-position of the phenyl ring of cyclohexylphenylurea enhanced the activity 6-fold, though similar substituent effects were not seen for any of the benzoylphenylureas. The activities of these compounds, including several previously reported compounds, such as dicyclohexylurea, diphenylurea, and their related analogues (Morisseau et al., Proc. Natl. Acad. Sci., 1999, 96, 8849), were quantitatively analyzed using comparative molecular field analysis (CoMFA), a three-dimensional quantitative structure–activity relationship (3-D QSAR) method. Both steric and electrostatic factors contributing to variations in the activity were visualized using CoMFA. CoMFA results showed that one side of the cyclohexylurea moiety having a trans-amide conformation (A-ring moiety) is surrounded by large sterically unfavorable fields, while the other side of A-ring moiety and the other cyclohexyl group (B-ring moiety) is encompassed by sterically favored fields. Electrostatically negative fields were scattered around the entire molecule, and a positive field surrounds the carbon of the carbonyl group. Hydrophobic fields were visualized using Kellogg's hydropathic interaction (HINT) in conjunction with CoMFA. Hydrophobically favorable fields appeared beside the 4- and 4′-carbon atoms of the cyclohexyl groups, and hydrophobically unfavorable fields surrounded the urea bridge. The addition of the molecular hydrophobicity, it> /it>, to CoMFA did not improve the correlation significantly. The ligand-binding interactions shown by X-ray crystallographic data were rationalized using the results of the CoMFA and HINT analyses, and the essential physicochemical parameters for the design of new MsEH inhibitors were disclosed.

Threshold-based structure-activity relationships of pyrazines with bell-pepper flavor.

Quantitative structure activity relationships (QSAR) and comparative molecular field analysis (CoMFA) are applied in order to explain the aroma of 46 bell-pepper aroma compounds. Biological activities log(1/c) values are used, where c stands for the detection threshold value of the aroma compound in water. Results of conventional QSAR and CoMFA are both satisfactory in statistical significance and predictive ability. We construct a qualitative model using the graphic features of CoMFA together with the results of "classical" QSAR analysis, which is performed by multiple linear regression. Finally, the human olfactory detection threshold values of excluded pyrazines are successfully predicted. This makes CoMFA and QSAR two important tools for designing new aroma compounds and in elucidating the mechanism of odor-receptor interaction.

QSAR and 3D-QSAR analysis of structurally diverse ALS inhibitors: sulfonylureas and triazolopyrimidine-2-sulfonamides

For the purpose of better understanding the molecular mechanism of action of sulfonylurea and sulfonamide herbicides, the quantitative relationship between their structure and herbicidal activity against rape, Brassica campestris L, was analysed using physicochemical parameters and regression analysis and comparative molecular field analysis (CoMFA). The results showed that the structure–activity relationships of the two sets of compounds were identical, which suggested that the two different sets of compounds affect a common region of the receptor site. The CoMFA results were consistent with those derived from traditional QSAR analysis. Combining the traditional QSAR analysis with the CoMFA results, we can conclude that the variations in the herbicidal activity of the two sets of ALS inhibitors were governed dominantly by the three-dimensional steric and electrostatic field parameters of molecules participating in the interaction with the receptor site and there is apparently an optimum electronic property (Σσ or pKa) for the molecules to fit the receptor. © 1999 Society of Chemical Industry