Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: Molecular docking and 3D QSAR studies

The glycolytic enzyme glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) is as an attractive target for the development of novel antitrypanosomatid agents. In the present work, comparative molecular field analysis and comparative molecular similarity index analysis were conducted on a large series of selective inhibitors of trypanosomatid GAPDH. Four statistically significant models were obtained (r(2) > 0.90 and q(2) > 0.70), indicating their predictive ability for untested compounds. The models were then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results. Molecular modeling studies provided further insight into the structural basis for selective inhibition of trypanosomatid GAPDH.

Pharmacophore-based 3D QSAR studies on a series of high affinity 5-HT(1A) receptor ligands

5-HT(1A) receptor antagonists have been employed to treat depression, but the lack of structural information on this receptor hampers the design of specific and selective ligands. In this study, we have performed CoMFA studies on a training set of arylpiperazines (high affinity 5-HT(1A) receptor ligands) and to produce an effective alignment of the data set, a pharmacophore model was produced using Galahad. A statistically significant model was obtained, indicating a good internal consistency and predictive ability for untested compounds. The information gathered from our receptor-independent pharmacophore hypothesis is in good agreement with results from independent studies using different approaches. Therefore, this work provides important insights on the chemical and structural basis involved in the molecular recognition of these compounds. (C) 2010 Elsevier Masson SAS. All rights reserved.

2D QSAR and similarity studies on cruzain inhibitors aimed at improving selectivity over cathepsin L

Hologram quantitative structure-activity relationships (HQSAR) were applied to a data set of 41 cruzain inhibitors. The best HQSAR model (Q(2) = 0.77; R-2 = 0.90) employing Surflex-Sim, as training and test sets generator, was obtained using atoms, bonds, and connections as fragment distinctions and 4-7 as fragment size. This model was then used to predict the potencies of 12 test set compounds, giving satisfactory predictive R-2 value of 0,88. The contribution maps obtained from the best HQSAR model are in agreement with the biological activities of the study compounds. The Trypanosoma cruzi cruzain shares high similarity with the mammalian homolog cathepsin L. The selectivity toward cruzam was checked by a database of 123 compounds, which corresponds to the 41 cruzain inhibitors used in the HQSAR model development plus 82 cathepsin L inhibitors. We screened these compounds by ROCS (Rapid Overlay of Chemical Structures), a Gaussian-shape volume overlap filter that can rapidly identify shapes that match the query molecule. Remarkably, ROCS was able to rank the first 37 hits as being only cruzain inhibitors. In addition, the area under the curve (AUC) obtained with ROCS was 0.96, indicating that the method was very efficient to distinguishing between cruzain and cathepsin L inhibitors. (c) 2007 Elsevier Ltd. All rights reserved.

Physicochemical parameters involved in the lethal toxicity of N,N-[(dimethylamino)ethyl]-4-substituted benzoate hydrochlorides: A QSAR study

A set of sixteen para-substituted N,N-[(dimethylamino)ethyl] benzoate hydrochlorides structurally related to procaine was synthesized. The apparent partition coefficients were determined by either shake-flask or HPLC methods and were taken as hydrophobic parameters. The IR stretching frequencies of the carbonyl group were determined in chloroform and taken as one of the electronic parameters. Additional physicochemical parameters were either taken from the literature: pi, sigma, T and R, MR4, or calculated: log P. The lethal potency was determined in the mouse via the LD50. In order to verify the nature and the relative contributions of the physicochemical parameters to lethal toxicity, QSAR equations were derived using regression analysis. A major contribution of hydrophobicity to ether with a smaller but still significant contribution of electronic or polar properties was found to a describe the toxicity within this set of compounds.

Inovação do método MIA-QSAR: aplicação para doenças tropicais negligenciadas

Multivariate image analysis applied to the quantitative structure-activity relationships (MIA-QSAR) is a 2D QSAR technique that has been presenting promising outcomes for the development of new drug candidates, due to its simplicity, rapidity and low cost. In this way, the present study aims at introducing, consolidating and improving the new dimensions named aug-MIA-QSAR and aug-MIA-QSARcolor, as well as applying them to the study of neglected diseases, in order to obtain new drug targets using chemico-biological interpretation of the MIA molecular descriptors. Four compound data sets with experimental bioactivities against Chagas disease, malaria, dengue and schistosomiasis were evaluated using three approaches: MIA-QSARt, aug-MIA-QSAR and aug-MIA-QSARcolor. In general, representations of atoms as spheres with different colors and sizes proportional to the corresponding van der Waals radii (aug-MIA approaches) improved the predictive ability and interpretability in all data sets. The use of colors proportional to the Pauling´s electronegativity showed that MIA descriptors are capable of identifying periodic properties relevant for the studied activity. Finally, solid colors instead of spotlighted atoms allowed a correct identification of atoms by means of pixel values in the studies for malaria, dengue and schistosomiasis, which were, subsequently, useful for the chemical interpretation related to the bioactivity. It can be inferred that semicarbazones and thiosemicarbazones derivative with a tri-substituted ring in R1 group and a trifluoro methyl group in the R 3 position instead of a chlorine antitripanossoma resulted in higher activity. The antimalarial activity of quinolon-4(1H)imines can be improved if: 1) R1 and R2 are electron donor groups, 2) R3 has long aminoalkyl chains, and 3) R4 possesses substituents with big atomic volume. In the study for dengue, it was found that tetrapeptides with unbranched small size amino acids in the A1 and A4 positions can increase the substrate affinity (Km) to the NS3 protein, and when in A1 and A2 positions, the substrate cleavage rate (kcat). On the other hand, acidic amino acids in the A2 and A4 positions were found to be related with low substrate affinity to the NS3 protein and when present in A1, with low substrate cleavage rate. Finally, the presence of metoxy substituents in R1 (or R2) and R5 in the neolignan backbone can favor their antischistosomal activity.

Novel aryl beta-aminocarbonyl derivatives as inhibitors of Trypanosoma cruzi trypanothione reductase: binding mode revised by docking and GRIND2-based 3D-QSAR procedures

Trypanothione reductase has long been investigated as a promising target for chemotherapeutic intervention in Chagas disease, since it is an enzyme of a unique metabolic pathway that is exclusively present in the pathogen but not in the human host, which has the analog Glutathione reductase. In spite of the present data-set includes a small number of compounds, a combined use of flexible docking, pharmacophore perception, ligand binding site prediction, and Grid-Independent Descriptors GRIND2-based 3D-Quantitative Structure-Activity Relationships (QSAR) procedures allowed us to rationalize the different biological activities of a series of 11 aryl beta-aminocarbonyl derivatives, which are inhibitors of Trypanosoma cruzi trypanothione reductase (TcTR). Three QSAR models were built and validated using different alignments, which are based on docking with the TcTR crystal structure, pharmacophore, and molecular interaction fields. The high statistical significance of the models thus obtained assures the robustness of this second generation of GRIND descriptors here used, which were able to detect the most important residues of such enzyme for binding the aryl beta-aminocarbonyl derivatives, besides to rationalize distances among them. Finally, a revised binding mode has been proposed for our inhibitors and independently supported by the different methodologies here used, allowing further optimization of the lead compounds with such combined structure- and ligand-based approaches in the fight against the Chagas disease.

Advanced QSAR Studies on PPAR delta Ligands Related to Metabolic Diseases

PPAR delta is a nuclear receptor that, when activated, regulates the metabolism of carbohydrates and lipids and is related to metabolic syndrome and type 2 diabetes. To understand the main interactions between ligands and PPAR delta, we have constructed 2D and 3D QSAR models and compared them with HOMO, LUMO and electrostatic potential maps of the compounds studied, as well as docking results. All QSAR models showed good statistical parameters and prediction outcomes. The QSAR models were used to predict the biological activity of an external test set, and the predicted values are in good agreement with the experimental results. Furthermore, we employed all maps to evaluate the possible interactions between the ligands and PPAR delta. These predictive QSAR models, along with the HOMO, LUMO and MEP maps, can provide insights into the structural and chemical properties that are needed in the design of new PPAR delta ligands that have improved biological activity and can be employed to treat metabolic diseases.

Consensus hologram QSAR modeling for the prediction of human intestinal absorption

Consistent in silico models for ADME properties are useful tools in early drug discovery. Here, we report the hologram QSAR modeling of human intestinal absorption using a dataset of 638 compounds with experimental data associated. The final validated models are consistent and robust for the consensus prediction of this important pharmacokinetic property and are suitable for virtual screening applications. (C) 2012 Elsevier Ltd. All rights reserved.

QSAR models for inhibitors of physiological impact of Escherichia coli that leads to diarrhea

Quantitative structure – activity relationships (QSARs) developed to evaluate percentage of inhibition of STa-stimulated (Escherichia coli) cGMP accumulation in T84 cells are calculated by the Monte Carlo method. This endpoint represents a measure of biological activity of a substance against diarrhea. Statistical quality of the developed models is quite good. The approach is tested using three random splits of data into the training and test sets. The statistical characteristics for three splits are the following: (1) n = 20, r2 = 0.7208, q2 = 0.6583, s = 16.9, F = 46 (training set); n = 11, r2 = 0.8986, s = 14.6 (test set); (2) n = 19, r2 = 0.6689, q2 = 0.5683, s = 17.6, F = 34 (training set); n = 12, r2 = 0.8998, s = 12.1 (test set); and (3) n = 20, r2 = 0.7141, q2 = 0.6525, s = 14.7, F = 45 (training set); n = 11, r2 = 0.8858, s = 19.5 (test set). Based on the proposed here models hypothetical compounds which can be useful agents against diarrhea are suggested.

CP-MLR Directed QSAR Studies on the Antimycobacterial Activity of Functionalised Alkenols - Topological Descriptors in Modeling the Activity

The antimycobacterial activity of nitro/ acetamido alkenol derivatives and chloro/ amino alkenol derivatives has been analyzed through combinatorial protocol in multiple linear regression (CP-MLR) using different topological descriptors obtained from Dragon software. Among the topological descriptor classes considered in the study, the activity is correlated with simple topological descriptors (TOPO) and more complex 2D autocorrelation descriptors (2DAUTO). In model building the descriptors from other classes, that is, empirical, constitutional, molecular walk counts, modified Burden eigenvalues and Galvez topological charge indices have made secondary contribution in association with TOPO and / or 2DAUTO classes. The structure-activity correlations obtained with the TOPO descriptors suggest that less branched and saturated structural templates would be better for the activity. For both the series of compounds, in 2DAUTO the activity has been correlated to the descriptors having mass, volume and/ or polarizability as weighting component. In these two series of compounds, however, the regression coefficients of the descriptors have opposite arithmetic signs with respect to one another. Outwardly these two series of compounds appear very similar. But in terms of activity they belong to different segments of descriptor-activity profiles. This difference in the activity of these two series of compounds may be mainly due to the spacing difference between the C1 (also C6) substituents and rest of the functional groups in them.

C-3 Alkyl /Arylalkyl-2,3-dideoxy hex-2-enopyranosides as Antitubercular Agents: Synthesis, Biological Evaluation and QSAR Study

A series of C-3 alkyl and arylalky 2,3-dideoxy hex-2-enopyranoside derivatives were synthesized by Morita-Baylis-Hillman reaction using enulosides 4, 5 and 6 and various aliphatic and aromatic aldehydes. The compounds were evaluated in vitro for the complete inhibition of growth of Mycobacterium tuberculosis H37Rv. They exhibited moderate to good activity in the range of 25-1.56 µg/mL. Among these, 4d, 4h, 5c and 4hr showed activity at minimum inhibitory concentrations, 3.12, 6.25, 1.56 and 1.56µg/mL, respectively. These compounds were safe against cytotoxicity in VERO cell line and mouse macrophage cell line J 744A.1. A QSAR analysis by CP-MLR with alignment-free 3D-descriptors indicated the relevance of structure space comparable to the minimum energy conformation (from conformational analysis) of 5c to the activity. The study indicates that the compounds attaining conformational space 5c and reflecting some symmetry, minimum eccentricity and closely placed geometric and electronegativity centers therein are favorable for activity.

QSAR Studies on Thiazolidines: A Biologically Privileged Scaffold

A large number of drugs and biologically relevant molecules contain heterocyclic systems. Often the presence of hetero atoms or groupings imparts preferential specificities in their biological responses. Amongst the heterocyclic systems, thiazolidine is a biologically important scaffold known to be associated with several biological activities. Some of the prominent biological responses attributed to this skeleton are antiviral, antibacterial, antifungal, antihistaminic, hypoglycemic, anti-inflammatory activities. This diversity in the biological response profiles of thiazolidine has attracted the attention of many researchers to explore this skeleton to its multiple potential against several activities. Many of these synthetic and biological explorations have been subsequently analyzed in detailed quantitative structure-activity relationship (QSAR) studies to correlate the respective structural features and physicochemical properties with the activities to identify the important structural components in deciding their activity behavior. In this, drugs or any biologically active molecules may be viewed as structural frames consisting of strategically positioned functional groups that will interact effectively with the complementary groups/sites of the receptor. With this in focus, the present article reviews the QSAR studies of diverse biological activities of the thiazolidines published during the past decade.

QSAR e dinâmica molecular no estudo de sistemas biomoleculares: predição da atividade biológica de antagonistas do receptor sigma-1 e simulações de bicamadas lipídicas

Diferentes abordagens teóricas têm sido utilizadas em estudos de sistemas biomoleculares com o objetivo de contribuir com o tratamento de diversas doenças. Para a dor neuropática, por exemplo, o estudo de compostos que interagem com o receptor sigma-1 (Sig-1R) pode elucidar os principais fatores associados à atividade biológica dos mesmos. Nesse propósito, estudos de Relações Quantitativas Estrutura-Atividade (QSAR) utilizando os métodos de regressão por Mínimos Quadrados Parciais (PLS) e Rede Neural Artificial (ANN) foram aplicados a 64 antagonistas do Sig-1R pertencentes à classe de 1-arilpirazóis. Modelos PLS e ANN foram utilizados com o objetivo de descrever comportamentos lineares e não lineares, respectivamente, entre um conjunto de descritores e a atividade biológica dos compostos selecionados. O modelo PLS foi obtido com 51 compostos no conjunto treinamento e 13 compostos no conjunto teste (r² = 0,768, q² = 0,684 e r²teste = 0,785). Testes de leave-N-out, randomização da atividade biológica e detecção de outliers confirmaram a robustez e estabilidade dos modelos e mostraram que os mesmos não foram obtidos por correlações ao acaso. Modelos também foram gerados a partir da Rede Neural Artificial Perceptron de Multicamadas (MLP-ANN), sendo que a arquitetura 6-12-1, treinada com as funções de transferência tansig-tansig, apresentou a melhor resposta para a predição da atividade biológica dos compostos (r²treinamento = 0,891, r²validação = 0,852 e r²teste = 0,793). Outra abordagem foi utilizada para simular o ambiente de membranas sinápticas utilizando bicamadas lipídicas compostas por POPC, DOPE, POPS e colesterol. Os estudos de dinâmica molecular desenvolvidos mostraram que altas concentrações de colesterol induzem redução da área por lipídeo e difusão lateral e aumento na espessura da membrana e nos valores de parâmetro de ordem causados pelo ordenamento das cadeias acil dos fosfolipídeos. As bicamadas lipídicas obtidas podem ser usadas para simular interações entre lipídeos e pequenas moléculas ou proteínas contribuindo para as pesquisas associadas a doenças como Alzheimer e Parkinson. As abordagens usadas nessa tese são essenciais para o desenvolvimento de novas pesquisas em Química Medicinal Computacional.

The use of computational QSAR analysis in the toxicological evaluation of a series of 2-pyridylcarboxamidrazone candidate anti-tuberculosis compounds

A series of N1-benzylidene pyridine-2-carboxamidrazone anti-tuberculosis compounds has been evaluated for their cytotoxicity using human mononuclear leucocytes (MNL) as target cells. All eight compounds were significantly more toxic than dimethyl sulphoxide control and isoniazid (INH) with the exception of a 4-methoxy-3-(2-phenylethyloxy) derivative, which was not significantly different in toxicity compared with INH. The most toxic agent was an ethoxy derivative, followed by 3-nitro, 4-methoxy, dimethylpropyl, 4-methylbenzyloxy, 3-methoxy-4-(-2-phenylethyloxy) and 4-benzyloxy in rank order. In comparison with the effect of selected carboxamidrazone agents on cells alone, the presence of either N-acetyl cysteine (NAC) or glutathione caused a significant reduction in the toxicity of INH, as well as on the 4-benzyloxy derivative, although both increased the toxicity of a 4-N,N-dimethylamino-1-naphthylidene and a 2-t-butylthio derivative. The derivatives from this and three previous studies were subjected to computational analysis in order to derive equations designed to establish quantitative structure activity relationships for these agents. Twenty-five compounds were thus resolved into two groups (1 and 2), which on analysis yielded equations with r2 values in the range 0.65-0.92. Group 1 shares a common mode of toxicity related to hydrophobicity, where cytotoxicity peaked at logP of 3.2, while Group 2 toxicity was strongly related to ionisation potential. The presence of thiols such as NAC and GSH both promoted and attenuated toxicity in selected compounds from Group 1, suggesting that secondary mechanisms of toxicity were operating. These studies will facilitate the design of future low toxicity high activity anti-tubercular carboxamidrazone agents. © 2003 Elsevier Science B.V. All rights reserved.

The HLA-A2-supermotif:a QSAR definition

Identification of epitopes capable of binding multiple HLA types will significantly rationalise the development of epitope-based vaccines. A quantitative method assessing the contribution of each amino acid at each position was applied to over 500 nonamer peptides binding to 5 MHC alleles — A*0201, A*0202, A*0203, A*0206 and A*6802 — which together define the HLA-A2-like supertype. FXIGXI (L)IFV was identified as a supermotif for the A2-supertype based on the contributions of the common preferred amino acids at each of the nine positions. The results indicate that HLA-A*6802 is an intermediate allele standing between A2 and A3 supertypes: at anchor position 2 it is closer to A3 and at anchor position 9 it is nearer to A2. Models are available free on-line at http://www.jenner.ac.uk/MHCPred and can be used for binding affinity prediction.