3D Quantitative Structure-activity Relationship Research Articles

Analysis of B-Raf[Formula: see text] inhibitors using 2D and 3D-QSAR, molecular docking and pharmacophore studies.

In the present work, a molecular modeling study was carried out using 2D and 3D quantitative structure-activity relationships for the various series of compounds known as B-Raf[Formula: see text] inhibitors. For 2D-QSAR analysis, a linear model was developed by MLR based on GA-OLS with appropriate results [Formula: see text], which was validated by several external validation techniques. To perform a 3D-QSAR analysis, CoMFA and CoMSIA methods were used. The selected CoMFA model could provide reliable statistical values [Formula: see text] based on the training set in the biases of the selected alignment. Using the same selected alignment, a statistically reliable CoMSIA model, out of thirty-one different combinations, was also obtained [Formula: see text]. The predictive accuracy of the derived models was rigorously evaluated with the external test set of nineteen compounds based on several validation techniques. Molecular docking simulations and pharmacophore analyses were also performed to derive the true conformations of the most potent inhibitors with B-Raf[Formula: see text] kinase.

A Structure-Activity Relationship Study of Imidazole-5-Carboxylic Acid Derivatives as Angiotensin II Receptor Antagonists Combining 2D and 3D QSAR Methods.

Two-dimensional (2D) and three-dimensional (3D) quantitative structure-activity relationship (QSAR) studies were performed for correlating the chemical composition of imidazole-5-carboxylic acid analogs and their angiotensin II [Formula: see text] receptor antagonist activity using partial least squares and k-nearest neighbor, respectively. For comparing the three different feature selection methods of 2D-QSAR, k-nearest neighbor models were used in conjunction with simulated annealing (SA), genetic algorithm and stepwise coupled with partial least square (PLS) showed variation in biological activity. The statistically significant best 2D-QSAR model having good predictive ability with statistical values of [Formula: see text] and [Formula: see text] was developed by SA-partial least square with the descriptors like [Formula: see text]count, 5Chain count, SdsCHE-index, and H-acceptor count, showing that increase in the values of these descriptors is beneficial to the activity. The 3D-QSAR studies were performed using the SA-PLS. A leave-one-out cross-validated correlation coefficient [Formula: see text] and predicate activity [Formula: see text] = 0.7226 were obtained. The information rendered by QSAR models may lead to a better understanding of structural requirements of substituted imidazole-5-carboxylic acid derivatives and also aid in designing novel potent antihypertensive molecules.

Molecular Modeling Studies of Trisubstituted Thiazoles as Cdc7 Kinase Inhibitors through 3D‐QSAR and Molecular Docking Simulation

The cell division cycle 7 (Cdc7) is a serine‐threonine protein kinase which plays an essential role in replication and initiation of DNA synthesis. Overexpression of the Cdc7 in various tumor growths and in cell proliferation makes it a novel target for cancer therapy. In the present study, we have performed 3D quantitative structure–activity relationship (3D‐QSAR) studies on a series of trisubstituted thiazole derivatives targeting Cdc7 kinase. Reasonable CoMFA (q 2 = 0.838, NOC = 5, r 2 = 0.984) and CoMSIA (q 2 = 0.875, NOC = 6, r 2 = 0.979) models were developed. All the developed models were validated using an external validation test set, leave‐out‐five, bootstrapping, progressive samplings, and rm 2 metrics. Both the models exhibited acceptable values on all validation techniques and hence were considered to be robust and predictive. Molecular docking study revealed the crucial interaction of the most active compound (compound 49) with the conserved active site residues. Our results are in line with the previous studies. Contour map analysis revealed the important insights that would help in increasing the potency of the compounds. From these results, we could suggest that bulky positive substitutions are favored in the R2 position of the phenyl ring. Hydrogen‐bond acceptor groups in the R1 position could increase the activity. Hydrogen‐bond donor groups are favored near the amino group of R3 position. Long substitution in the R3 position will reduce the activity and must be avoided. Our results could be used to design more potent trisubstituted thiazole derivative of Cdc7 kinase inhibitors in future.

Synthesis, antiviral activity, and 3D-QSAR study of novel chalcone derivatives containing malonate and pyridine moieties

Several novel chalcone derivatives containing malonate and pyridine moieties were synthesized, and their structures were confirmed by 1H nuclear magnetic resonance, 13C nuclear magnetic resonance, 19F nuclear magnetic resonance, infrared, and elemental analyses. Antiviral bioassays revealed that most of the compounds exhibited good antiviral activity against cucumber mosaic virus (CMV) at 500μg/mL. In particular, compounds 5l and 5n showed significant curative activities against CMV in vivo with 50% effective concentration (EC50) values of 186.2 and 211.5μg/mL, respectively; these values are even better than that of ningnanmycin (330.5μg/mL). A 3D quantitative structure–activity relationship study was carried out using the comparative molecular field analysis technique based on curative activities against CMV. Results revealed good predictive ability with cross-validated q2 and non-cross-validated r2 values of 0.517 and 0.990, respectively.

Exploring structural requirements of imaging agents against Aβ plaques in Alzheimer's disease: a QSAR approach.

Exploring molecular imaging agents against the beta amyloid (Aβ) plaques for an early detection of Alzheimer's disease (AD) is one of the emerging research areas in medicinal chemistry. In the present in-silico study, a congeneric series of 44 imaging agents, including 17 positron emission tomography (PET) and 27 single photon emission computed tomography (SPECT) imaging agents, was utilized to understand the structural features required for having essential binding affinity against Aβ plaques. Here, 2D-quantitative structure-activity relationship (2D-QSAR) and group-based QSAR (G-QSAR) models have been developed using genetic function approximation (GFA) and validated using various statistical metrics. Both the models showed satisfactory performance signifying the reliability and robustness of the developed QSAR models. The vital information gained from both the QSAR models will be useful in developing new PET and SPECT imaging agents and also in predicting their binding affinity against Aβ plaques. The results of this study would be important in view of the widespread clinical applicability of the SPECT imaging agents, especially in the developing countries. In this study, we have also designed some imaging agents based on the information provided by the models. Some of these designed compounds were predicted to be similar to or more active than the most active imaging agents present in the original dataset.

A Three-Dimensional Quantitative Structure Tribo-Ability Relationship Model

The prediction of lubrication characteristics for compounds through tribological models would aid in the discovery of new lubricant additives and improved lubricant design. But until recently, the field of tribological prediction has been sparse and not systematic. Tribological processes are complex and involve molecular energy exchange as well as conformation transitions. We have developed a platform of a “quantitative structure tribo-ability relationship (QSTR),” which enables us to introduce well-developed quantitative structure–activity relationships (QSAR) methods into tribology systematically. The present study applies “evaluation of infrared vibration-based” (EVA) descriptors, which are three-dimensional (3D) QSAR descriptors to simulate infrared (IR) vibration properties of molecules, in order to establish the QSTR prediction model. As structural changes take place under friction loads, the EVA descriptors characterize both molecular energy and conformations. The results show a strong correlation and robust predictability of the EVA model to tribological parameters. The approach paves a way to a systematic QSTR.

In silico prediction of hERG inhibition.

The voltage-gated potassium channel encoded by hERG carries a delayed rectifying potassium current (IKr) underlying repolarization of the cardiac action potential. Pharmacological blockade of the hERG channel results in slowed repolarization and therefore prolongation of action potential duration and an increase in the QT interval as measured on an electrocardiogram. Those are possible to cause sudden death, leading to the withdrawals of many drugs, which is the reason for hERG screening. Computational in silico prediction models provide a rapid, economic way to screen compounds during early drug discovery. In this review, hERG prediction models are classified as 2D and 3D quantitative structure-activity relationship models, pharmacophore models, classification models, and structure based models (using homology models of hERG).

Synthesis, biological activity and 3D-QSAR study of novel pyrrolidine-2,4-dione derivatives containing N-substituted phenylhydrazine moiety

Twenty-seven novel pyrrolidine-2,4-dione derivatives containing N-substituted phenylhydrazine moiety were synthesized. Their structures were confirmed by 1H NMR, 13C NMR and MS. The half effective concentration (EC50) values of the title compounds against the phytopathogenic fungi Rhizoctonia cerealis were evaluated. Compounds 6l and 6q displayed good bioactivity with EC50 values of 1.626 and 2.043 μg/mL, respectively. The 3D quantitative structure activity relationship(3D-QSAR) model of CoMFA was established with reliable cross-validated correlation coefficient q 2 value of 0.585 and Noncross-validated correlation coefficient r 2 value of 0.971. This model provided a tool for guiding further design and synthesis of novel pyrrolidine-2,4-dione derivatives with high fungicidal activity.

Two dimensional quantitative structure activity relationship models for 5alpha-reductase type 2 inhibitors

Prostate cancer in men is the major cause of cancer mortality and is the active area for the researchers to discover new drugs for prostate cancer. 5alpha-reductase inhibitors have been proved to inhibit the growth and development of prostate cancer, hence identifying the potential of such compounds is necessary to invent new drugs. Quantitative structure activity relationship (QSAR) modeling is a well-known in silico drug designing approach that relates the chemical structure of compounds with their biological activities. In the present work 2D QSAR models are built using machine learning techniques such as linear regression, SMO, simple logistic, decision tree j48 and random forest, from the functions available in Weka 3.7 version. The present in silico QSAR study will help to identify new bioactivities for the drug discovery of prostate cancer and also narrow down the time required for drug discovery process.

Structure-odor correlations in homologous series of alkanethiols and attempts to predict odor thresholds by 3D-QSAR studies.

Homologous series of alkane-1-thiols, alkane-2-thiols, alkane-3-thiols, 2-methylalkane-1-thiols, 2-methylalkane-3-thiols, 2-methylalkane-2-thiols, and alkane-1,ω-dithiols were synthesized to study the influence of structural changes on odor qualities and odor thresholds. In particular, the odor thresholds were strongly influenced by steric effects: In all homologous series a minimum was observed for thiols with five to seven carbon atoms, whereas increasing the chain length led to an exponential increase in the odor threshold. Tertiary alkanethiols revealed clearly lower odor thresholds than found for primary or secondary thiols, whereas neither a second mercapto group in the molecule nor an additional methyl substitution lowered the threshold. To investigate the impact of the SH group, odor thresholds and odor qualities of thiols were compared to those of the corresponding alcohols and (methylthio)alkanes. Replacement of the SH group by an OH group as well as S-methylation of the thiols significantly increased the odor thresholds. By using comparative molecular field analysis, a 3D quantitative structure-activity relationship model was created, which was able to simulate the odor thresholds of alkanethiols in good agreement with the experimental results. NMR and mass spectrometric data for 46 sulfur-containing compounds are additionally supplied.

Identification of new non-steroidal TGR5 agonists using virtual screening with combined pharmacophore models

Activation of Takeda G-protein receptor 5 (TGR5) plays a key role in pathways associated with diabetes, metabolic syndrome, and autoimmune disease. Pharmacophore and 3D-quantitative structure–activity relationship modeling were applied to study the structure–activity relationship of TGR5 agonists. The best HypoGen pharmacophore hypothesis Hypo1 with a correlation coefficient of 0.93 consists of one hydrogen-bond acceptor, one aromatic ring and three hydrophobic features, whereas the best phase hypothesis AHHRR.1321 with favorable statistics (q2 = 0.7613, r2 = 0.927) has one hydrogen-bond acceptor, two hydrophobic features and two ring aromatic features. Furthermore, comparing those two models, the preferable AHHRR.1321 was employed as a novel searching tool for chemical databases to conduct virtual screening for new potential lead candidates. Consequently, refined Lipinski ‘rule of five’ and ADME properties were utilized as a filter to reduce less drug-like molecules. Among the hits, 10 non-steroidal compounds with good fitness score and physicochemical properties were identified.

NovelN-Acylated Benzimidazolone Derivatives: Synthesis, 2D-QSAR and Targets Prediction

A series of novel N-acylated benzimidazolone derivatives, were synthesized from 4-aminobenzoic acid, and their antifungal activities against Botrytis cinerea were evaluated by spore germination assay. Preliminary results indicated that most of the benzimidazolone derivatives had inhibitory effect on spore germination, among which 6-carboxylate substituted derivatives were more effective than its 5-substituted regioisomers. Furthermore, 2D-quantitative structure-activity relationship (2D-QSAR) studies revealed good predictive and statistically significant QSAR models, as well as highlighted that the activities were strongly influenced by the type of introduced acyl groups in the benzimidazolone moiety. Potential targets of the title compounds were predicted using ligand profiling and validated by molecular docking, and the results implied that the title compounds might be a new type of fatty acid synthetase inhibitor.

2D QSAR Studies on a Series of Benzimidazole Type of Fluconazole Analogues as Antimicrobial Agents

Antimicrobial activity of benzimidazole type of Fluconazole analogues series were subjected to Quantitative Structure Activity Relationship (QSAR) studies with an effort to derive and understand a correlation between the biological activity as response variable and different molecular descriptors as independent variables. The QSAR results revealed that the presence of methoxy, hydroxy, chloro or fluoro substituents would increase the antimicrobial activity and presence of electron withdrawing groups at R1, R2, R3 and R4 position of benzimidazole ring would increase the activity. Such a theoretical study can help in designing more active molecules than the current ones.

3D-QSAR and Docking Studies on 2-acyliminobenzimidazoles Derivatives as Potent ALK Inhibitors

The overexpression of anaplastic lymphoma kinase (ALK) had been found in many types of cancers, especially the non-small-cell lung cancers (NSCLCs). So the discovery of novel ALK inhibitor had attracted a great deal of interest in anticancer drugs research area. Presently, a combined study of 3D-quantitative structure-activity relationship (3DQSAR) and molecular docking was undertaken to explore the structural insights of 36 2-acyliminobenzimidazoles compounds influencing the ALK inhibitory activities. Both the ligand-based resultant comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models exhibited good predictability (CoMFA with R2, 0.995; q2, 0.534; CoMSIA with R2, 0.993; q2, 0.519;). 3D contour maps and docking results suggested different groups on the core parts of the componds could enhance the biological activities. Finally, 10 derivatives as potential candidates of ALK inhibitors with excellent predicted activities were designed. Keywords: 3D-QSAR, ALK inhibitor, CoMFA, CoMSIA, docking.

Integrated pharmacophore and docking‐based designing of dual inhibitors of aldose reductase (ALR2) and protein tyrosine phosphatase 1B (PTP1B) as novel therapeutics for insulin‐resistant diabetes and its complications

The dual inhibitors against aldose reductase (ALR2) and protein tyrosine phosphatase 1B (PTP1B) may present an anti‐diabetic potency in insulin resistance without risks of serious diabetic complications. Therefore, in the present study, we constructed two separate pharmacophore mapping‐based 3D quantitative structure–activity relationship models for ALR2 (AADRR.11093 with standard deviation 0.663, 0.719, F 22.3, root‐mean‐square error 0.705, 0.647, Pearson‐r 0.802) and PTP1B (AARR.155 with standard deviation 0.146, 0.945, F 82.70, root‐mean‐square error 0.351, 0.621, Pearson‐r 0.831) employing the dataset of 54 flavonoids as ALR2 inhibitors and 46 naphthoquinones as PTP1B inhibitors to identify structural features necessary for the inhibition of both enzymes. These models were subsequently used as 3D query search for hierarchical virtual screening‐based designing using the PHASE database of 1.5 million compounds. Designed dual inhibitors were further subjected to GLIDE XP docking analysis using high‐resolution 3D structures of ALR2 (1US0, at resolution of 0.66 Å) and PTP1B (2F71 at resolution of 1.55 Å) available in the Protein Data Bank to authenticate identified structural features with important binding interactions necessary for dual inhibition. Copyright © 2014 John Wiley & Sons, Ltd.

Quantitative Structure-Activity Relationship and Molecular Modeling Studies on a Series of Hydroxamate Analogues Acting as HDAC Inhibitors

In this communication, a quantitative structure-activity relationship (QSAR) study has been performed on a series of trichostatin A (TSA) and suberanilo hydroxamic acid (SAHA) analogues acting as histone deacetylase (HDAC1) inhibitors to investigate their physicochemical properties that govern their activity. In this study, a significant 2D QSAR model was obtained correlating the activity of the compounds with their parachor and some indicator variables which suggested that molecules may have dispersion interaction with the receptor and that their surface tension may greatly help to this interaction. Further, the indicator parameters suggested that SO 2 NH moiety present in the molecule may not be conducive to the activity, but the straight chain joining the aromatic rings with hydroxamate moiety and having ≥6 single bonds may be favorable to the activity, provided it has no substituent at any carbon. Using the model, some new compounds in the series have been predicted and docked to see their interaction with the HDAC1. All compounds have been found to have better interaction with the enzyme than TSA and SAHA, the two FDA approved HDAC inhibitors, and all the compounds obey Lipinski’s rule of 5.

Multipotent cholinesterase/monoamine oxidase inhibitors for the treatment of Alzheimer's disease: design, synthesis, biochemical evaluation, ADMET, molecular modeling, and QSAR analysis of novel donepezil-pyridyl hybrids.

The design, synthesis, and biochemical evaluation of donepezil-pyridyl hybrids (DPHs) as multipotent cholinesterase (ChE) and monoamine oxidase (MAO) inhibitors for the potential treatment of Alzheimer’s disease (AD) is reported. The 3D-quantitative structure-activity relationship study was used to define 3D-pharmacophores for inhibition of MAO A/B, acetylcholinesterase (AChE), and butyrylcholinesterase (BuChE) enzymes and to design DPHs as novel multi-target drug candidates with potential impact in the therapy of AD. DPH14 (Electrophorus electricus AChE [EeAChE]: half maximal inhibitory concentration [IC50] =1.1±0.3 nM; equine butyrylcholinesterase [eqBuChE]: IC50 =600±80 nM) was 318-fold more potent for the inhibition of AChE, and 1.3-fold less potent for the inhibition of BuChE than the reference compound ASS234. DPH14 is a potent human recombinant BuChE (hBuChE) inhibitor, in the same range as DPH12 or DPH16, but 13.1-fold less potent than DPH15 for the inhibition of human recombinant AChE (hAChE). Compared with donepezil, DPH14 is almost equipotent for the inhibition of hAChE, and 8.8-fold more potent for hBuChE. Concerning human monoamine oxidase (hMAO) A inhibition, only DPH9 and 5 proved active, compound DPH9 being the most potent (IC50 [MAO A] =5,700±2,100 nM). For hMAO B, only DPHs 13 and 14 were moderate inhibitors, and compound DPH14 was the most potent (IC50 [MAO B] =3,950±940 nM). Molecular modeling of inhibitor DPH14 within EeAChE showed a binding mode with an extended conformation, interacting simultaneously with both catalytic and peripheral sites of EeAChE thanks to a linker of appropriate length. Absortion, distribution, metabolism, excretion and toxicity analysis showed that structures lacking phenyl-substituent show better druglikeness profiles; in particular, DPHs13–15 showed the most suitable absortion, distribution, metabolism, excretion and toxicity properties. Novel donepezil-pyridyl hybrid DPH14 is a potent, moderately selective hAChE and selective irreversible hMAO B inhibitor which might be considered as a promising compound for further development for the treatment of AD.

Abstract LB-224: Identification of a binding site for the tyrosine kinase inhibitor Nilotinib on the human ABC drug transporter, P-glycoprotein as determined by 3D-QSAR, molecular docking and mutational mapping

Abstract Nilotinib (Tasigna®) is a novel tyrosine kinase inhibitor (TKI) that has been used to treat chronic phase chronic myeloid leukemia patients who develop resistance due to the emergence of point mutations within the BCR-ABL kinase domain. It is known to be transported by the ATP binding-cassette (ABC) drug efflux transporters P-glycoprotein (P-gp) and ABCG2, which not only alters the efficacy of nilotinib but might also result in lower bioavailability. Identification of a nilotinib binding conformation in the drug-binding pocket of these transporters is important to understand its interactions and can be used to design the next generation of TKIs that do not interact with ABC drug transporters. A structure-activity relationship (SAR)-based approach for nilotinib was used in this study to identify an initial pharmacophore interacting with P-gp. [125I]-Iodoarylazidoprazosin (IAAP) photolabeling and FACS-based transport of fluorescent substrates were carried out with 26 structural derivatives of nilotinib to evaluate their potency for inhibiting the binding of substrate and the transport function of P-gp. IC50 values from these assays were used for 3D pharmacophore modeling and quantitative structure-activity relationships (QSARs) to propose the spatial arrangement of chemical features that are essential for inhibitory activity of nilotinib towards P-gp. Molecular docking of nilotinib in a homology model of human P-gp was performed to identify interactions with the drug-binding pocket. This docked model was evaluated by mutational mapping studies replacing the Y307, M949 and A985 residues with Cysteine in the primary-binding site, which resulted in the loss of nilotinib's activity to inhibit substrate binding to P-gp. The orientation of nilotinib in this binding pocket was further substantiated by assessing the interaction of nilotinib's structural derivatives with P-gp using photoaffinity labeling, ATP hydrolysis and transport assays. These results demonstrate that the pyridine and pyrimidine rings in nilotinib play a key role in its interaction with the drug-binding pocket, while orientation of the imidazole ring determines the affinity of nilotinib for P-gp. These results for the first time identify the primary binding site of nilotinib in the drug-binding pocket of P-gp and can be exploited to design novel tyrosine kinase inhibitors that would not be recognized by ABC drug transporters. Citation Format: Suneet Shukla, Eduardo E. Chufan, Satyakam Singh, Amanda P. Skoumbourdis, Khyati Kapoor, Matthew B. Boxer, Damien Y. Duveau, Craig J. Thomas, Tanaji T. Talele, Suresh V. Ambudkar. Identification of a binding site for the tyrosine kinase inhibitor Nilotinib on the human ABC drug transporter, P-glycoprotein as determined by 3D-QSAR, molecular docking and mutational mapping. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-224. doi:10.1158/1538-7445.AM2014-LB-224

In vitro antiviral effects and 3D QSAR study of resveratrol derivatives as potent inhibitors of influenza H1N1 neuraminidase.

The anti-influenza virus activities of 50 resveratrol (RV: 3, 5, 4'-trihydroxy-trans-stilbene) derivatives were evaluated using a neuraminidase (NA) activity assay. The results showed that 35 compounds exerted an inhibitory effect on the NA activity of the influenza virus strain A/PR/8/34 (H1N1) with 50% inhibitory concentration (IC50) values ranging from 3.56 to 186.1 μm. Next, the 35 RV derivatives were used to develop 3D quantitative structure-activity relationship (3D QSAR) models for understanding the chemical-biological interactions governing their activities against NA. The comparative molecular field analysis (CoMFA r2=0.973, q2=0.620, qtest2=0.661) and the comparative molecular similarity indices analysis (CoMSIA r2=0.956, q2=0.610, qtest2=0.531) were applied. Afterward, molecular docking was performed to study the molecular interactions between the RV derivatives and NA. Finally, a cytopathic effect (CPE) reduction assay was used to evaluate the antiviral effects of the RV derivatives in vitro. Time-of-addition studies demonstrated that the RV derivatives might have a direct effect on viral particle infectivity. Our results indicate that the RV derivatives are potentially useful antiviral compounds for new drug design and development for influenza treatment.

A structure-activity relationship study of imidazole-5-carboxylic acids derivatives as angiotensin II receptor antagonists combining 2D and 3D QSAR methods.

Two Dimensional (2D) and Three Dimensional (3D) Quantitative Structure-Activity Relationship (QSAR) studies were performed for correlating the chemical composition of Imidazole-5-carboxylic Acids analogues and their Angiotensin II AT1 Receptor Antagonists activity using partial least squares and k Nearest Neighbor respectively. For Comparing the three different feature selection methods of 2D-QSAR, k Nearest Neighbor models was used in conjunction with simulated annealing (SA), genetic algorithm (GA) and stepwise (SW) coupled with Partial least square (PLS) showed variation in biological activity. The statistically significant best 2D-QSAR model having good predictive ability with statistical values of r2 = 0.8040, and pred_r2 = 0.7764, was developed by SA-Partial least square with the descriptors like SsCH3Count, 5Chain Count, SdsCHE-index and H-acceptor count showed that increase in the values of these descriptors are beneficial for the activity. The 3D-QSAR studies were performed using the SA-PLS a leave-one-out cross-validated correlation coefficient q2=0.7188 and predicate activity pred_r2 =0.7226 were obtained. The information rendered by QSAR models may lead to a better understanding of structural requirements of substituted Imidazole-5-carboxylic Acids derivatives and also aid in designing novel potent antihypertensive molecules.