Hologram QSAR Research Articles

Fragment-Based Hologram QSAR Studies on a Series of 2,4-Dioxopyrimidine-1-Carboxamides As Highly Potent Inhibitors of Acid Ceramidase.

A series of structurally related 2,4-dioxopyrimidine-1-carboxamide derivatives as highly potent inhibitors against acid ceramidase were subjected to hologram quantitative structure-activity relationship (HQSAR) analysis. A training set containing 24 compounds served to establish the HQSAR model. The best HQSAR model was generated using atoms, bond, connectivity, donor and acceptor as fragment distinction and 3-6 as fragment size with six components showing cross-validated q2 value of 0.834 and conventional r2 value of 0.965. The model was then employed to predict the potency of test set compounds that were excluded in the training set, and a good agreement between the experimental and predicted values was observed exhibiting the powerful predictable capability of this model [Formula: see text]. Atom contribution maps indicate that the electron-withdrawing effects at position 5 of the uracil ring, the preferential acyl substitution at N3 position and the substitution of eight-carbon alkyl chain length at N1 position predominantly contribute to the inhibitory activity. Based upon these key structural features derived from atom contribution maps, we have designed novel inhibitors of acid ceramidase possessing better inhibitory activity.

Pharmacophore generation, atom-based 3D-QSAR, HQSAR and activity cliff analyses of benzothiazine and deazaxanthine derivatives as dual A2A antagonists/MAO‑B inhibitors

Dual inhibition of A2A and MAO-B is an emerging strategy in neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). In this study, atom-based three-dimensional quantitative structure–activity relationship (3D-QSAR) and hologram quantitative structure–activity relationship (HQSAR) models were generated with benzothiazine and deazaxanthine derivatives. Based on activity against A2A and MAO-B, two statistically significant 3D-QSAR models (r2 = 0.96, q2 = 0.76 and r2 = 0.91, q2 = 0.63) and HQSAR models (r2 = 0.93, q2 = 0.68 and r2 = 0.97, q2 = 0.58) were developed. In an activity cliff analysis, structural outliers were identified by calculating the Mahalanobis distance for a pair of compounds with A2A and MAO-B inhibitory activities. The generated 3D-QSAR and HQSAR models, activity cliff analysis, molecular docking and dynamic studies for dual target protein inhibitors provide key structural scaffolds that serve as building blocks in designing drug-like molecules for neurodegenerative diseases.

Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives.

Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer's disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r (2)=0.988, q (2)=0.757, ONC=6; r (2)=0.966, q (2)=0.645, ONC=5; and r (2)=0.957, q (2)=0.736, ONC=6. The predictabilities were validated using an external test sets, and the predictive r (2) values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors.

CoMFA, CoMSIA, HQSAR and Molecular Docking Analysis of Ionone-based Chalcone Derivatives as Antiprostate Cancer Activity.

Androgen receptor has been proved to be effective site for treatment of prostate cancer. Molecular modeling methods performed on forty-three ionone based chalcones derivatives as anti-prostate cancer activity. The designed comparative molecular field analysis, comparative similarity indices analysis and hologram quantitative structure activity relationship models produced statistically significant results with the cross-validated correlation coefficients (q(2)) of 0.527, 0.550 and 0.670, non-cross-validated correlation coefficients (r(2)) 0.636, 0.671 and 0.746 and predicted r(2) (Pred r(2)) of 0.621, 0.563 and 0.732, respectively. Furthermore, bioactive conformation was explored and explained by docking of the potent compound 25 into the binding site of androgen receptor. Present study deals with comparative molecular field analysis, comparative similarity indices analysis and hologram quantitative structure activity relationship and molecular docking studies of the ionone-based chalcones and their derivatives, obtained from literature. The model obtained could be effectively used as a channeling tool for further structure modification and designing of some novel potent anti-prostate cancer compounds.

QSAR analysis of thiolactone derivatives using HQSAR, CoMFA and CoMSIA

The development of resistant malaria and lethality of the disease demands the search for new therapeutic candidates. In this line-up, thiolactone was identified as the potential lead structure and subjected to hologram quantitative structure–activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Overall, the QSAR results shows that the LOO cross-validated q2 values of HQSAR, CoMFA and CoMSIA models are 0.791, 0.737 and 0.753, respectively. According to HQSAR, the hydrogen bond donor and acceptor were found to play an important role in governing antimalarial activity of thiolactone derivatives. The fragment contribution map of HQSAR, and contour maps of CoMFA and CoMSIA showed the presence of an electronegative group at the fifth position, and a bulky group at the third and fourth positions of the thiolactone ring, positively contributing to antimalarial activity. Furthermore, molecular docking was performed to analyze the binding mode of newly designed thiolactones with the active site residues of pf KAS I/II. The prediction of newly designed thiolactone molecules based on QSAR and docking score are in good accordance with each other. Therefore the ligand-based QSAR models and target structure-based docking model developed in this study may be successfully utilized for the design of new antimalarial agents.

Hologram quantitative structure-activity relationship and comparative molecular interaction field analysis of aminothiazole and thiazolesulfonamide as reversible LSD1 inhibitors.

LSD-1 is an enzyme that removes methyl groups from lysine residues of histone proteins. LSD-1 inhibition decreases cellular proliferation and therefore represents a therapeutic target for cancer treatment. MAO and LSD-1 are both flavin adenine dinucleotide-dependent MAOs, and the MAO inhibitor, tranylcypromine, is currently undergoing clinical trials for cancer treatment because it acts as an irreversible LSD-1 inhibitor. The present study investigated new reversible LSD-1 inhibitors, in order to develop novel selective anticancer agents. We constructed 2 and 3D quantitative structure-activity relationship models by using a series of 54 aminothiazole and thiazolesulfonamide derivatives. The models were validated internally and externally (q(2) , 0.691 and 0.701; r(2) , 0.894 and 0.937; r(2) test , 0.785 and 0.644, for 2 and 3D models, respectively). Fragment contribution maps, as well as steric and electrostatic contour maps were generated in order to obtain chemical information related to LSD-1 inhibition. The thiazolesulfonamide group was fundamental to the inhibition of LSD-1 by these compounds and that bulky and aromatic substituents at the thiazole ring were important for their steric and electrostatic interactions with the active site of LSD-1.

Insight into the structural requirements of aminopyrimidine derivatives for good potency against both purified enzyme and whole cells of M. tuberculosis: combination of HQSAR, CoMSIA, and MD simulation studies

The Mycobacterium tuberculosis protein kinase B (PknB) is critical for growth and survival of M. tuberculosis within the host. The series of aminopyrimidine derivatives show impressive activity against PknB (IC50 < .5 μM). However, most of them show weak or no cellular activity against M. tuberculosis (MIC > 63 μM). Consequently, the key structural features related to activity against of both PknB and M. tuberculosis need to be investigated. Here, two- and three-dimensional quantitative structure–activity relationship (2D and 3D QSAR) analyses combined with molecular dynamics (MD) simulations were employed with the aim to evaluate these key structural features of aminopyrimidine derivatives. Hologram quantitative structure–activity relationship (HQSAR) and CoMSIA models constructed from IC50 and MIC values of aminopyrimidine compounds could establish the structural requirements for better activity against of both PknB and M. tuberculosis. The NH linker and the R1 substituent of the template compound are not only crucial for the biological activity against PknB but also for the biological activity against M. tuberculosis. Moreover, the results obtained from MD simulations show that these moieties are the key fragments for binding of aminopyrimidine compounds in PknB. The combination of QSAR analysis and MD simulations helps us to provide a structural concept that could guide future design of PknB inhibitors with improved potency against both the purified enzyme and whole M. tuberculosis cells.

Fragment-Based QSAR and Structural Analysis of a Series of Hydroxyethylamine Derivatives as HIV-1 Protease Inhibitors.

HIV-1 protease is a key enzyme for viral maturation because it cleaves precursor polypeptides into mature structural and functional proteins. The introduction of protease inhibitors into therapy in the mid-1990s has dramatically changed the AIDS panorama worldwide. However, resistance to currently available protease inhibitors remains a serious challenge that must be overcome. Herein, we report a fragment-based QSAR study of a series of highly potent HIV-1 protease inhibitors, as well as the structural basis of their binding affinity. Hologram QSAR (HQSAR) analyses were performed, resulting in robust statistical models that consistently correlated the bioactivity profile with the two dimensional molecular descriptors. The robustness of the best model was assessed based on the correlation coefficients (q(2) = 0.70 and r(2) = 0.90), as well as the prediction of the activity of an external test set (r(2) pred = 0.75). Structure-based molecular modeling studies were performed to investigate the binding mode of the best inhibitor in the active site of the enzyme. The HQSAR model and the structural findings provide valuable insights for the rational design of structurally related HIV-1 protease inhibitors.

Hologram Quantitative Structure Activity Relationship Analysis of JNK Antagonists

c-Jun N-terminal kinase-3 (JNK3) is a member of the mitogen-activated protein kinase family (MAPK), and plays an important role in neurological disorders. Therefore, identification of selective JNK3 inhibitor may contribute towards neuroprotection therapies. In this work, we performed hologram quantitative structure-activity relationship (HQSAR) on a series of thiophene trisubstituted derivatives. The best predictions were obtained for HQSAR model with q2 = 0.628 and r2 = 0.986. Statistical parameters from the generated QSAR models indicated the data is well fitted and have high predictive ability. HQSAR result showed that atom, bond and chirality descriptors play an important role in JNK3 activity and also shows that electronegative groups is highly favourble to enhance the biological activity. Our results could be useful to design novel and selective JNK3 inhibitors.

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.

Hologram QSAR models of a series of 6-arylquinazolin-4-amine inhibitors of a new Alzheimer's disease target: dual specificity tyrosine-phosphorylation-regulated kinase-1A enzyme.

Dual specificity tyrosine-phosphorylation-regulated kinase-1A (DYRK1A) is an enzyme directly involved in Alzheimer’s disease, since its increased expression leads to β-amyloidosis, Tau protein aggregation, and subsequent formation of neurofibrillary tangles. Hologram quantitative structure-activity relationship (HQSAR, 2D fragment-based) models were developed for a series of 6-arylquinazolin-4-amine inhibitors (36 training, 10 test) of DYRK1A. The best HQSAR model (q2 = 0.757; SEcv = 0.493; R2 = 0.937; SE = 0.251; R2pred = 0.659) presents high goodness-of-fit (R2 > 0.9), as well as high internal (q2 > 0.7) and external (R2pred > 0.5) predictive power. The fragments that increase and decrease the biological activity values were addressed using the colored atomic contribution maps provided by the method. The HQSAR contribution map of the best model is an important tool to understand the activity profiles of new derivatives and may provide information for further design of novel DYRK1A inhibitors.

Comparative Study to Predict Dipeptidyl Peptidase IV Inhibitory Activity of β-Amino Amide Scaffold.

Comparative study was performed on 34 β-amino amide derivatives as dipeptidyl peptidase IV inhibitors in order to determine their structural requirement to enhance the antidiabetic activities. Hologram quantitative structure activity relationships models utilized specialized fragment fingerprints (hologram length 353) which showed good predictivity with cross-validated q(2) and conventional r(2) values of 0.971 and 0.971, respectively. Models were validated and optimized by a test set of eight compounds and gave satisfactory predictive ability. Hologram quantitative structure activity relationships maps were helpful in prediction of the structural features of the ligands to account for the activity in terms of positively and negatively contributing towards activity. The information obtained from maps could be effectively use as a guiding tool for further structure modifications and synthesis of new potent antidiabetic agents.

A Predictive HQSAR Model for a Series of Tricycle Core Containing MMP-12 Inhibitors with Dibenzofuran Ring.

MMP-12 is a member of matrix metalloproteinases (MMPs) family involved in pathogenesis of some inflammatory based diseases. Design of selective matrix MMPs inhibitors is still challenging because of binding pocket similarities among MMPs family. We tried to generate a HQSAR (hologram quantitative structure activity relationship) model for a series of MMP-12 inhibitors. Compounds in the series of inhibitors with reported biological activity against MMP-12 were used to construct a predictive HQSAR model for their inhibitory activity against MMP-12. The HQSAR model had statistically excellent properties and possessed good predictive ability for test set compounds. The HQSAR model was obtained for the 26 training set compounds showing cross-validated q 2 value of 0.697 and conventional r 2 value of 0.986. The model was then externally validated using a test set of 9 compounds and the predicted values were in good agreement with the experimental results (r pred 2 = 0.8733). Then, the external validity of the model was confirmed by Golbraikh-Tropsha and r m 2 metrics. The color code analysis based on the obtained HQSAR model provided useful insights into the structural features of the training set for their bioactivity against MMP-12 and was useful for the design of some new not yet synthesized MMP-12 inhibitors.

Combined 2D and 3D-QSAR, molecular modelling and docking studies of pyrazolodiazepinones as novel phosphodiesterase 2 inhibitors

Selective inhibition of phosphodiesterase 2 (PDE2) in cells where it is located elevates cyclic guanosine monophosphate (cGMP) and acts as novel analgesic with antinociceptive activity. Three-dimensional quantitative structure–activity relationship (QSAR) studies for pyrazolodiazepinone inhibitors exhibiting PDE2 inhibition were performed using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and Topomer CoMFA, and two-dimensional QSAR study was performed using a Hologram QSAR (HQSAR) method. QSAR models were generated using training set of 23 compounds and were validated using test set of nine compounds. The optimum partial least squares (PLS) for CoMFA-Focusing, CoMSIA-SDH, Topomer CoMFA and HQSAR models exhibited good ‘leave-one-out’ cross validated correlation coefficient (q2) of 0.790, 0.769, 0.840 and 0.787, coefficient of determination (r2) of 0.999, 0.964, 0.979 and 0.980, and high predictive power (r2pred) of 0.796, 0.833, 0.820 and 0.803 respectively. Docking studies revealed that those inhibitors able to bind to amino acid Gln859 by cGMP binding orientation called ‘glutamine-switch’, and also bind to the hydrophobic clamp of PDE2 isoform, could possess high selectivity for PDE2. From the results of all the studies, structure–activity relationships and structural requirements for binding to active site of PDE2 were established which provide useful guidance for the design and future synthesis of potent PDE2 inhibitors.

Molecular modeling application on hapten epitope prediction: an enantioselective immunoassay for ofloxacin optical isomers.

To deepen our understanding of the physiochemical principles that govern hapten-antibody recognition, ofloxacin enantiomers were chosen as a model for epitope prediction of small molecules. In this study, two monoclonal antibodies (mAbs) mAb-WR1 and mAb-MS1 were raised against R-ofloxacin and S-ofloxacin, respectively. The enantioselective mAbs have a high sensitivity and specificity, and the enantioselectivity is not affected by heterologous coating format reactions. The epitopes of the ofloxacin isomers were predicted using the hologram quantitative structure-activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) approaches. The results consistently show that the epitope of the chiral hapten should be primarily composed of the oxazine ring and the piperazinyl ring and mAbs recognize the hapten from the side of this moiety. The enantioselectivity of mAbs is most likely due to the steric hindrance caused by the stereogenic center of the epitope. Modeling of chiral hapten-protein mimics reveals that ofloxacin isomers remain upright on the surface of the carrier protein. Suggestions to improve the enantioselectivity of antibodies against ofloxacin isomers were also proposed. This study provided a simple, efficient, and general method for predicting the epitopes of small molecules via molecular modeling. The epitope predictions for small molecules may create a theoretical guide for hapten design.

Hologram quantitative structure activity relationship, docking, and molecular dynamics studies of inhibitors for CXCR4.

CXCR4 plays a crucial role as a co-receptor with CCR5 for HIV-1 anchoring to mammalian cell membrane and is implicated in cancer metastasis and inflammation. In the current work, we study the relationship of structure and activity of AMD11070 derivatives and other inhibitors of CXCR4 using HQSAR, docking and molecular dynamics (MD) simulations. We obtain an HQSAR model (q(2) = 0.779), and the HQSAR result illustrates that AMD11070 shows a high antiretroviral activity. As HQSAR only provides 2D information, we perform docking and MD to study the interaction of It1t, AMD3100, and AMD3465 with CXCR4. Our results illustrate that the binding are affected by two crucial residues Asp97 and Glu288. The butyl amine moiety of AMD11070 contributes to its high antiretroviral activity. Without a butyl amine moiety, (2,7a-Dihydro-1H-benzoimidazol-2-ylmethyl)-methyl-(5,6,7,8-tetrahydro-quinolin-8-yl)-amine (compound 5a) shows low antiretroviral activity. Our results provide structural details about the interactions between the inhibitors and CXCR4, which are useful for rational drug design of CXCR4.

Extracting structural requirements for activity of GPR119 agonists: a hologram quantitative structure activity relationship (HQSAR) study

GPR119 is a potential target for the treatment of diabetes mellitus. GPR119 agonists minimize the side-effects observed with sulphonyl ureas and glucagon-like peptide 1 analogs. Various reported GPR119 agonists from various patents were selected for the study and a 2D-QSAR study (HQSAR) was carried out. Fifty-five molecules were selected for the study. The study was performed on a training set of 40 structurally diverse molecules with reported biological activity. The most significant HQSAR model (q2 = 0.87, r2 = 0.99) was obtained using atoms, bond, connection, and acceptor and donor as fragment distinction. The fragment size was kept at 4–7. The predictive ability of the model was evaluated by an external test set containing 15 molecules not included in the training set, and the predicted values were in good agreement with the experimental values. The important fragments determined by the study were used to design new drug candidates having increased biological activity and comparable physicochemical properties.

Identifying structural features related to the biological activity of a series of AT1 antagonists from fragment-based drug design.

Antagonists of AT1 receptor are interesting substances to develop drugs that can be used for the treatment of hypertension and other diseases that affect the cardiovascular system. This study investigates the main interactions between various AT1 antagonists and the biological target by applying fragment-based drug design (Hologram QSAR - HQSAR). The proposed HQSAR model yielded significant correlation coefficients (q(2) = 0.764 and r(2) = 0.914), indicating that the method is rigorous and reliable. All models were externally validated using a test set and the results showed good agreement between the experimental and predicted data (r(2) test = 0.740). Therefore, our model can positively contribute to understand the structural features involved in the main interactions between the AT1 antagonists and the residues of the binding site.

3D CoMFA, CoMSIA, topomer CoMFA and HQSAR studies on aromatic acid esters for carbonic anhydrase inhibitory activity

Molecular modelling studies [comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), topomer CoMFA and hologram quantitative structure–activity relationship (HQSAR)] have been performed on the series of 28 molecules belonging to the series of aromatic acid ester derivatives for their carbonic anhydrase inhibitory activity. The model exhibited good correlation coefficient (r2) and cross‐validated correlation coefficient (q2) for CoMFA, CoMSIA and HQSAR methods. On the basis of the findings from all these studies, a structure–activity relationship was established. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Flavonoids promoting HaCaT migration: I. Hologram quantitative structure–activity relationships

Cell migration plays an important role in multicellular development and preservation. Because wound healing requires cell migration, compounds promoting cell migration can be used for wound repair therapy. Several plant-derived polyphenols are known to promote cell migration, which improves wound healing. Previous studies of flavonoids on cell lines have focused on their inhibitory effects and not on wound healing. In addition, studies of flavonoids on wound healing have been performed using mixtures. In this study, individual flavonoids were used for cellular migration measurements. Relationships between the cell migration effects of flavonoids and their structural properties have never been reported. Here, we investigated the migration of keratinocytes caused by 100 flavonoids and examined their relationships using hologram quantitative structure-activity relationships. The structural conditions responsible for efficient cell migration on keratinocyte cell lines determined from the current study will facilitate the design of flavonoids with improved activity.