Clustering of atoms relative to vector space in the Z-matrix coordinate system and 'graphical fingerprint' analysis of 3D pharmacophore structure.

The behavior of a molecule within its environment is governed by chemical fields present in 3D space. However, beyond local descriptors in 3D, the conformations a molecule assumes, and the resulting clusters also play a role in influencing structure-activity models. This study focuses on the clustering of atoms according to the vector space of four atoms aligned in the Z-Matrix Reference system for molecular similarity. Using 3D-QSAR analysis, it was aimed to determine the pharmacophore groups as interaction points in the binding region of the ß2-adrenoceptor target of fenoterol stereoisomers. Different types of local reactive descriptors of ligands have been used to elucidate points of interaction with the target. Activity values for ligand-receptor interaction energy were determined using the Levenberg-Marquardt algorithm. Using the Molecular Comparative Electron Topology method, the 3D pharmacophore model (3D-PhaM) was obtained after aligning and superimposing the molecules and was further validated by the molecular docking method. Best guesses were calculated with a non-output validation (LOO-CV) method. Finally, the data were calculated using the 'graphic fingerprint' technique. Based on the eLKlopman (Electrostatic LUMO Klopman) descriptor, the Q2 value of this derivative set was calculated as 0.981 and the R2ext value is calculated as 0.998.

Investigation of 3D pharmacophore of N-benzyl benzamide molecules of melanogenesis inhibitors using a new descriptor Klopman index: uncertainties in model.

We used a new descriptor called the Klopman index in our software of the "molecular comparative electron topology" (MCET) method to reduce the uncertainty resulting from the descriptors used in QSAR studies. The 3D pharmacophore model (3D-PhaM), which can demonstrate three-dimensional interaction between the ligand -receptor (L-R), is only possible with local reactive descriptors (LRD). The Klopman index, containing both Coulombic and frontier orbital and interactions of atoms of the ligand, is a good LRD. Molecular conformers having the best matching atoms with the template conformer can be selected as one of the most suitable spatial structures for interaction with the receptor, and the LRD values of the atoms in this conformer serve to determine 3D-PhaM. The 3D-PhaM of the N-benzyl benzamide derivatives, such as the melanogenesis inhibitor, was determined by ligand-based MCET and confirmed by the structure-based FlexX docking method. For compounds of the training set (42) and the external cross validation test set (6), the Q2 (0.862) and R2 (0.913) of the statistical parameters were calculated, respectively, and were checked by rm2 (0.85) of the stringent validation.

Molecular docking and 4D-QSAR studies of metastatic cancer inhibitor thiazoles.

By using the molecular docking and 4D-QSAR analysis, it is aimed to find the interaction points in the receptor binding site of transforming growth factor-beta (TGF-beta) used to inhibit invasion and metastasis. To elucidate the interaction points of receptor, different types of local reactive descriptor (LRD) of ligands have been used. Activity values related to interaction energy between the ligand-receptor (L-R) were determined by nonlinear least squares (NLLS) using the Levenberg-Marquardt (LM) algorithm. Using the Molecule Comparative Electron Topology (MCET) method, the 3D pharmacophore model (3D-PhaM) was obtained after alignment and superimposition of the molecules, and also confirmed by molecular docking method. With the leave one out-cross validation (LOO-CV) method, the best predictions are q2 or rCV2 = 0.789 for the 51 compounds in the internal training set and r2 = 0.785 for the 13 compounds in the external test set. Furthermore, the predictive capability of the advanced QSAR model is more precisely calculated with the rm2 metric (rm2 = 0.769).

4D-QSAR Studies Using a New Descriptor of the Klopman Index: Antibacterial Activities of Sulfone Derivatives Containing 1, 3, 4-Oxadiazole Moiety Based on MCET Model.

INTRODUCTION: In this paper, we have introduced a new atomic descriptor with Klopman index to determine the local reactive sites of the molecular systems during electrophilic, and nucleophilic attacks. This index, similar to other local reactivity descriptors but more advanced, has been used as a realistic descriptor to discover new aspects of molecular structure. METHODS: Nonlinear Least Squares (NLLS) methods to define the parameters maximizing the fit between the observed points and the computed simulation results were performed according to the Levenberg- Marquardt (LM) algorithm. We have attempted to demonstrate the structural properties of compounds that contribute not only basic pharmacophore (b-Pha) but also positive (Auxiliary Group- AG) or negative (Anti-Pharmacophore Shielding-APS) due to the new local atomic reactivity. RESULTS AND CONCLUSION: In the 4D-QSAR study, nonparametric regression analysis was used to determine the adjustable constants. Using the leave One Out Cross-Validation (LOO-CV), antibacterial activities (pEC50-µM) were predicted as r2 loo-cv (q2) = 0.979, r2 pred (r2) = 0.911, respectively, for 27 training sets and 9 test set compounds. Also, the rm2 (overall) value, which indicates the closeness between the predicted and corresponding observed data, was calculated to be 0.957. The model obtained by the Molecular Conformer Electron Topological (MCET) method was compared with the q2 loo-cv and R2 non-cv values determined by the CoMFA and CoMSIA methods and more satisfactory results were obtained.

Amino substituted nitrogen heterocycle ureas as kinase insert domain containing receptor (KDR) inhibitors: Performance of structure-activity relationship approaches.

A quantitative structure-activity relationship (QSAR) study was performed on a set of amino-substituted nitrogen heterocyclic urea derivatives. Two novel approaches were applied: (1) the simplified molecular input-line entry systems (SMILES) based optimal descriptors approach; and (2) the fragment-based simplex representation of molecular structure (SiRMS) approach. Comparison with the classic scheme of building up the model and balance of correlation (BC) for optimal descriptors approach shows that the BC scheme provides more robust predictions than the classic scheme for the considered pIC50 of the heterocyclic urea derivatives. Comparison of the SMILES-based optimal descriptors and SiRMS approaches has confirmed good performance of both techniques in prediction of kinase insert domain containing receptor (KDR) inhibitory activity, expressed as a logarithm of inhibitory concentration (pIC50) of studied compounds.

Three-dimensional model of nonsteroidal estrogen receptor ligand binding/electron topological method.

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been obtained using the electron topological method (ETM) for estrogen (estrone, CAS 53-16-7) receptor (ER) affinities. This method was used to identify regions of the enzyme and inhibitors where steric and electrostatic effects correlate strongly with biological activity. Thirty compounds belong to a series of diethylstilbestrol (CAS 56-53-1, DES) and indenestrol (CAS 24643-94-5) analogues whose affinities for ER have been, theoretically, investigated. After energy minimizations and molecular dynamics calculations were performed to find the ground state conformer for each molecule, quantum chemical properties of each molecule were defined and in ETM their matrices were compared with those of the reference molecule. It is shown that the molecular fragments responsible for this affinity possess fixed electronic and geometric characteristics associated with a distinct arrangement and steric accessibility of an oxygen atom and a group of carbon atoms. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities. The highest correlation coefficient (R2 = 0.930, SE = 0.403) was obtained with the structure of the active fragment and the orientation of aliphatic and phenolic substituents.

Study of the binding affinity for corticosteroid-binding globulin (CBG) using the electron topological method (ETM) as three-dimensional quantitative structure-activity relationship (3D QSAR).

The Electron Topological Method, called ETM, is a descriptor for predicting the biological activities of molecules based on three-dimensional quantitative structure-activity relations (3D QSAR). ETM uses a modified electron topological state index to substitute for electronic properties and a topological distance for the relative distance in the molecule. It is shown that the molecular fragments responsible for this activity possess fixed electronic and geometric characteristics associated with a distinct arrangement and the steric accessibility of an oxygen atom and a group of carbon atoms. After that, it is essential to employ a linear regression analysis technique to derive a 3D QSAR model relating the biological activities to the ETM. The ETM is used to study the 3D QSAR of the corticosteroid-binding globulin (CBG) binding affinity to 31 steroids, and resulting models have a comparable to current 3D methods such as CoMFA. Though the ETM is a descriptor based on 3D topological information obtained by quantum chemical derived descriptors, give the best answer for both the similarity analysis and the statistical fitting.

Investigation of antiulcer activities of imidazo[1,2-alpha]pyridinyl-2-alkylaminobenzoxazoles and 5,6,7,8-tetahydroimidazo[1,2-alpha]pyridinyl-benzoxazoles with electron-topological (ET) method.

The study presents structure-activity considerations of a series of imidazo[1,2-alpha]pyridiny-2-alkylaminobenzoxazoles(I) and 5,6,7,8-tetahydroimidazo[1,2-alpha]pyridinylbenzoxazoles(II) investigated for anti-stress ulcer activity with the electron-topological method. A series of 39 compounds including 24 active and 15 weakly active was studied. It is shown that the fragment determined by the electron-topological method in an active molecule is responsible for anti-stress ulcer activity. Quantitative structure-activity relationships with electron topological approach of these compounds are discussed in terms of the statistical program STATGRAF-7.0.