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MMP-2 overexpression is strongly related to several diseases including cancer. However, none of the MMP-2 inhibitors have been marketed as drug candidates due to various adverse effects. Here, a set of sulphonyl pyrrolidines was subjected to validation of molecular modelling followed by binding mode analysis to explore the crucial structural features required for the discovery of promising MMP-2 inhibitors. This study revealed the importance of hydroxamate as a potential zinc-binding group compared to the esters. Importantly, hydrophobic and sterical substituents were found favourable at the terminal aryl moiety attached to the sulphonyl group. The binding interaction study revealed that the S1′ pocket of MMP-2 similar to 'a basketball passing through a hoop' allows the aryl moiety for proper fitting and interaction at the active site to execute potential MMP-2 inhibition. Again, the sulphonyl pyrrolidine moiety can be a good fragment necessary for MMP-2 inhibition. Moreover, some novel MMP-2 inhibitors were also reported. They showed the significance of the 3rd position substitution of the pyrrolidine ring to produce interaction inside S2′ pocket. The current study can assist in the design and development of potential MMP-2 inhibitors as effective drug candidates for the management of several diseases including cancers in the future. [ABSTRACT FROM AUTHOR]

Nitrobenzene derivatives present an environmental concern to aquatic organisms, as well as a potential adverse effects on human health due to their toxicity. Therefore, monitoring nitrobenzene contamination levels is critical to protect both the ecosystem and the public. This study aims to quantitatively correlate the toxicity of nitrobenzene derivatives to their chemical structures using computational chemistry methods such as 3D‐QSPR, HQSPR, Molecular Docking and MD simulation. Additionally, to investigate the type of interactions and stability of nitrobenzene derivatives with the PP2 protein involved in the Phloem protein 2 (PP2). From each computational method a prediction model was extracted HQSPR (Atomic, Bonds, Donor/Acceptor, 3D‐QSPR (Steric, Electrostatic, Hydrophobic, Acceptor), and used for the design of X1 and X2 new nitrobenzene derivatives, which showed remarkable stability and better interactions. This study contributes to the understanding of the nitrobenzene derivatives' toxicity and offers materials towards the understanding of the mechanism of action of these substances in protein–ligand interactions. [ABSTRACT FROM AUTHOR]

Histone deacetylase 8 (HDAC8) is a verified biomolecular target associated with diverse diseases including cancer. Though several HDAC inhibitors emerged effective against such diseases, no selective HDAC8 inhibitor is approved to date. Therefore, the development of potent HDAC8-selective inhibitors is inevitable to combat such diseases. Here, some benzothiazine-derived HDAC8 inhibitors were considered for a comparative QSAR analysis which may elucidate the prime structural components responsible for modulating their efficacy. Several outcomes from these diverse modelling techniques justified one another and thus validated each other. The ligand-based pharmacophore modelling study identified ring aromatic, positive ionizable, and hydrophobic features as essential structural attributes for HDAC8 inhibition. Besides, MLR, HQSAR and field-based 3D-QSAR studies signified the utility of the positive ionizable and hydrophobic features for potent HDAC8 inhibition. Again, the field-based 3D-QSAR study provided useful insight regarding the substitution in the fused phenyl ring. Moreover, the current observations also validated the previously reported molecular docking observations. Based on the outcomes, some new molecules were designed and predicted. Therefore, this comparative structural analysis of these HDAC8 inhibitors will surely assist in the development of potent HDAC8 inhibitors as promising anticancer therapeutics in the future. [ABSTRACT FROM AUTHOR]

Lim kinase (Limk), as an important cytoskeletal regulator, plays an important role in cancer manifestations and neuronal diseases. Limk1 is a member of the Limk family, which is mainly involved in the invasion and metastasis of tumor cells and is abnormally expressed in a variety of cell carcinoma tissues. In this paper, a series of Limk1 inhibitors with aminothiazole skeleton were used to design potent and efficient Limk1 inhibitors by computational approaches. Firstly, the 3D-QSAR model was constructed, and both CoMFA and CoMSIA models have good correlation and prediction ability. The binding requirements between ligand and receptor protein were then further explored through molecular docking, including the critical forces between Limk1 inhibitors and active site residues. Finally, based on the 3D-QSAR model and molecular docking results analysis, three new compounds with theoretically better activity were designed and their ADME properties were predicted. [ABSTRACT FROM AUTHOR]

Dihydropyrimidines are widely recognized for their diverse biological properties and are often synthesized by the Biginelli reactions. In this backdrop, a novel series of Biginelli dihydropyrimidines were designed, synthesized, purified, and analyzed by FT-IR, 1H NMR, 13C NMR, and mass spectrometry. Anticancer activity against MCF-7 breast cancer cells was evaluated as part of their cytotoxicity in comparison with the normal Vero cells. The cytotoxicity of dihydropyrimidines ranges from moderate to significant. Among the 38 dihydropyrimidines screened, compounds 16 , 21 , and 39 exhibited significant cytotoxicity. These 3 compounds were subjected to flow cytometry studies and EGFRwt Kinase inhibition assay using lapatinib as a standard. The study included evaluation for the inhibition of EGFR and HER2 expression at five different concentrations. At a concentration of 1000 nM compound 21 showed 98.51 % and 96.79 % inhibition of EGFR and HER2 expression. Moreover, compounds 16 , 21 and 39 significantly inhibited EGFRwt activity with IC 50 = 69.83, 37.21 and 76.79 nM, respectively. In addition, 3D-QSAR experiments were conducted to elucidate Structure activity relationships in a 3D grid space by comparing the experimental and predicted cytotoxic activities. Molecular docking studies were performed to validate the results by in silico method. All together, we developed a new series of Biginelli dihydropyrimidines as dual EGFR/HER2 inhibitors. [Display omitted] • Multicomponent reactions help to swiftly synthesize and evaluate molecules for activity. • This research covers synthesis of 38 dihydropyrimidines and their activity against EGFR/HER2. • Novel dihydropyrimidines can be potential anticancer therapeutics. • Synthesized dihydropyrimidines are quite effective against breast cancer target. • Computational studies have been performed as predictive analysis to correlate with experimental studies. [ABSTRACT FROM AUTHOR]

Enoyl Acyl Carrier Protein (ACP) Reductase, a key enzyme, which catalyzes the last reductive step of fatty acid biosynthesis and it, is one of the key enzymes for the development of antitubercular agents. In this pursuit, molecular docking and 3D-QSAR studies (CoMFA and CoMSIA) have been performed on a series of pyrimidine derivatives (29 compounds) to understand the binding sites, interactions to improve over the existing leads in terms of improved biological and physico-chemical properties. Molecular docking was performed on a protein InhA (T2A mutant) (PDB ID: 5OIR) using the Surflex-Dock suite available in SYBYL-X 2.1.1 (Tripose Inc., USA). In addition, 3D-QSAR studies have been performed to validate the models using the data set, which was segregated into training and test set by using the Diversity and Dissimilarity method. Structural features required for the prediction of better inhibitory potency was generated in the form of contour maps from the CoMFA and CoMSIA models (Steric, Electrostatic, Hydrophobicity, H-bond donor and acceptor maps) and predicted values for r2 = 0.966, q2 = 0.22 for the CoMFA model and r2 = 0.925, q2 = 0.576 for the CoMSIA model. From this study, it is observed that interaction with amino acid residues TYR158, MET199, MET161, GLY96, and PHE97 are important for the activity that helped to predict SARs by providing important structural features. Both the models were good in understanding the specific activity of some of the compounds that will facilitate to develop new types of Enoyl ACP reductase inhibitors. [ABSTRACT FROM AUTHOR]

In this paper, a three-dimensional quantitative structure-activity relationship (3D-QSAR) namely CoMFA and CoMSIA has been carried out on a series (43 compounds) of capsid assembly inhibitors on N-phenyl-3-sulfamoyl-benzamide-based. The statistical parameters from the models (CoMFA: r2 = 0.998, q2 = 0.625, r2pred = 0.837; CoMSIA: r2 = 0.987, q2 = 0.645, r2pred = 0.698) indicate that the data are well fitted and have high predictive ability. Molecular docking was employed to explore the binding mode between these compounds and the receptor protein, as well as help understand the structure-activity relationship revealed by CoMFA and CoMSIA. Contour maps of the QSAR models were generated and validated by molecular docking study. The final models of CoMFA/CoMSIA and molecular docking could be useful for the design and development of novel potent HBV capsid assembly inhibitors. [ABSTRACT FROM AUTHOR]

DNA gyrase B (GyrB) plays a critical role in DNA replication, repair, recombination, and transcription and has become an attractive target for a number of antibacterial agents. In the present work, to better comprehend the structure–activity relationship and mechanism of action of novel series of GyrB inhibitors, a theoretical study of three-dimensional-quantitative structure–activity relationship (3D-QSAR), molecular docking, molecular dynamics (MD) simulations, and binding free energy analysis were performed. The results showed that CoMFA (R2cv = 0.591, R2pred = 0.7698) and CoMSIA (R2cv = 0.629, R2pred = 0.6848) models possessed robust stability and predictability. The derived contour maps of steric, electrostatic, and hydrogen bond donor field further displayed the modified information of these inhibitors. Molecular docking was further conducted to provide the initial binding conformation for MD simulations. Subsequently, MD simulations were applied to explore the key amino acids and binding modes at the active site. The binding free energy decomposition analysis further indicates that the residues Ile54, Glu55, Arg83, Ala85, Val86 and Thr128 are essential for the high selectivity of inhibitors. Overall, these results would serve as a significant guideline for the discovery and design of novel GyrB inhibitors.

Piperidine and piperazine derivatives exhibit a diverse range of biological applications, including antipsychotic activity. In this study, a dataset of molecules containing piperidine, piperazine moieties that possess serotonin 5-HT2A and dopamine D2 inhibitory activity have been chosen for Pharmacophore modeling, Quantitative Structure–Activity (3D-QSAR) Relationship, Molecular docking, and ADME studies. The pharmacophoric hypothesis was found to be AAHPRRR_1 having seven features as one H-bond acceptor (A), one hydrophobic (H), one positive ion acceptor (P), and three aromatic rings (R), with survival score = 6.465 and AUC = 0.92. Based on the best hypothesis, the ZINC-Data base was virtually screened to find out the lead molecules. 3D-QSAR model, including internal and external validation showed comparative molecular field analysis (CoMFA) against 5HT2A (q2 = 0.552, R2 = 0.889, and r2 poured. = 0.653 and number of component 5) and comparative molecular similarity indices analysis (CoMSIA) (q2 = 0.599, R2 = 0.893, and r2 pred. = 0.617), for D2 (CoMFA, q2 = 0.577, R2 = 0.863, and r2 pred. = 0.598) (CoMSIA, q2 = 0.532, R2 = 0.82) all results exhibited better productivity and significant statistical reliability of the model. The docking study was carried out on the crystal structure of 5-HT2A having PDB ID; 6A93 and D2 receptor having PDB ID; 6CM4. The screened compound ZINC74289318 possess a higher docking score − 10.744 and − 11.388 than co-crystallized ligand docking score − 8.840 and − 10.06 against 5-HT2A and D2 receptor respectively. Further, ZINC74289318 was screened for all drug-likeness parameters and no showed violation of the Lipinski rule of five. Also, it was found to possess good bioavailability of 0.55 with synthetic accessibility of 4.42 which is greater than risperidone. [ABSTRACT FROM AUTHOR]

PGAM1 is overexpressed in a wide range of cancers, thereby promoting cancer cell proliferation and tumor growth, so it is gradually becoming an attractive target. Recently, a series of inhibitors with various structures targeting PGAM1 have been reported, particularly anthraquinone derivatives. In present study, the structure–activity relationships and binding mode of a series of anthraquinone derivatives were probed using three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, r2 = 0.97, q2 = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r2 = 0.96, q2 = 0.82) techniques were performed to produce 3D-QSAR models, which demonstrated satisfactory results, especially for the good predictive abilities. In addition, molecular dynamics (MD) simulations technology was employed to understand the key residues and the dominated interaction between PGAM1 and inhibitors. The decomposition of binding free energy indicated that the residues of F22, K100, V112, W115, and R116 play a vital role during the ligand binding process. The hydrogen bond analysis showed that R90, W115, and R116 form stable hydrogen bonds with PGAM1 inhibitors. Based on the above results, 7 anthraquinone compounds were designed and exhibited the expected predictive activity. The study explored the structure–activity relationships of anthraquinone compounds through 3D-QSAR and molecular dynamics simulations and provided theoretical guidance for the rational design of new anthraquinone derivatives as PGAM1 inhibitors. [ABSTRACT FROM AUTHOR]

Background: Src homology 2 (SH2)-containing protein tyrosine phosphatase 2 (SHP2) as a major phosphatase would affect the development of tumors by regulating several cellular processes, and is a significant potential target for cancer treatment. Methods: In the present work, a series of pyridine derivatives possessing a wide range of inhibitory activity was employed to investigate the structural requirements by developing three dimensional quantitative structure–activity relationship (3D-QSAR) models using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The results show that CoMFA (R2cv = 0.646, R2pred = 0.5587) and CoMSIA (R2cv = 0.777, R2pred = 0.7131) have excellent stability and predictability. The relationship between the inhibitory activity and structure of the inhibitors was analyzed by the derived contour maps. Furthermore, the QSAR models were validated by molecular docking and molecular dynamics simulations, which were also applied to reveal the potential molecular mechanism of these inhibitors. Findings: It was found that Arg110, Asn216, Thr218, Thr252 and Pro490 play a crucial role in stabilizing the inhibitors. Additionally, MM/PBSA calculations provided the binding free energy were also conducted to explain the discrepancy of binding activities. Overall, the outcomes of this work could provide useful information and theoretical guidance for the development of novel and potent SHP2 inhibitors.

PGAM1 is overexpressed in a wide range of cancers, thereby promoting cancer cell proliferation and tumor growth, so it is gradually becoming an attractive target. Recently, a series of inhibitors with various structures targeting PGAM1 have been reported, particularly anthraquinone derivatives. In present study, the structure–activity relationships and binding mode of a series of anthraquinone derivatives were probed using three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, r2 = 0.97, q2 = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r2 = 0.96, q2 = 0.82) techniques were performed to produce 3D-QSAR models, which demonstrated satisfactory results, especially for the good predictive abilities. In addition, molecular dynamics (MD) simulations technology was employed to understand the key residues and the dominated interaction between PGAM1 and inhibitors. The decomposition of binding free energy indicated that the residues of F22, K100, V112, W115, and R116 play a vital role during the ligand binding process. The hydrogen bond analysis showed that R90, W115, and R116 form stable hydrogen bonds with PGAM1 inhibitors. Based on the above results, 7 anthraquinone compounds were designed and exhibited the expected predictive activity. The study explored the structure–activity relationships of anthraquinone compounds through 3D-QSAR and molecular dynamics simulations and provided theoretical guidance for the rational design of new anthraquinone derivatives as PGAM1 inhibitors.

Rho-associated kinase-1 (ROCK1) has been recognized for its pivotal role in heart diseases, different types of malignancy, and many neurological disorders. Hyperactivity ofROCKphosphorylates the protein kinase-C (PKC), which ultimately induces smooth muscle cell contraction in the vascular system. Inhibition of ROCK1 has been shown to be a promising therapy for patients with cardiovascular disease. In this study, we have conducted molecular modeling techniques such as docking, molecular dynamics (MD), and 3-Dimensional structure-activity relationship (3D-QSAR) on a series of Nethyl- 4-(pyridin-4-yl)benzamide-based compounds. Docking and MD showed critical interactions and binding affinities between ROCK1 and its inhibitors. To establish the structure-activity relationship (SAR) of the compounds, 3D-QSAR techniques such as Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were used. The CoMFA (q² =0.774, r² =0.965, ONC = 6, and r²pred = 0.703) and CoMSIA (q² = 0.676, r² = 0.949, ONC = 6, and r²pred = 0.548) both models have shown reasonable external predictive activity, and contour maps revealed favorable and unfavorable substitutions for chemical group modifications. Based on the contour maps, we have designed forty new compounds, among which, seven compounds exhibited higher predictive activity (pIC50). Further, we conducted the MD study, ADME/Tox, and SA score prediction using the seven newly designed compounds. The combination of docking, MD, and 3D-QSAR studies helps to understand the coherence modification of existing molecules. Our study may provide valuable insight into the development of more potent ROCK1 inhibitors. [ABSTRACT FROM AUTHOR]

Focal adhesion kinase (FAK) is a promising target for developing more effective anticancer drugs. To better understand the structure-activity relationships and mechanism of actions of FAK inhibitors, a molecular modeling study using 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy analysis were conducted. Two types of satisfactory 3D-QSAR models were generated, comprising the CoMFA model (R2cv = 0.528, R2pred = 0.7557) and CoMSIA model (R2cv = 0.757, R2pred = 0.8362), for predicting the inhibitory activities of novel inhibitors. The derived contour maps indicate structural characteristics for substituents on the template. Molecular docking, molecular dynamic simulations and binding free energy calculations further reveal that the binding of inhibitors to FAK is mainly contributed from hydrophobic, electrostatic and hydrogen bonding interactions. In addition, some key residues (Arg14, Glu88, Cys90, Arg138, Asn139, Leu141, and Leu155) responsible for ligand-receptor binding are highlighted. All structural information obtained from 3D-QSAR models and molecular dynamics is consist with the available experimental activities. All the results will facilitate the optimization of this series of FAK inhibitors with higher inhibitory activities.

Abstract Background An alarming requirement for finding newer antidiabetic glitazones as agonists to PPARγ are on its utmost need from past few years as the side effects associated with the available drug therapy is dreadful. In this context, herein, we have made an attempt to develop some novel glitazones as PPARγ agonists, by rational and computer aided drug design approach by implementing the principles of bioisosterism. The designed glitazones are scored for similarity with the developed 3D pharmacophore model and subjected for docking studies against PPARγ proteins. Synthesized by adopting appropriate synthetic methodology and evaluated for in vitro cytotoxicity and glucose uptake assay. Illustrations about the molecular design of glitazones, synthesis, analysis, glucose uptake activity and SAR via 3D QSAR studies are reported. Results The computationally designed and synthesized ligands such as 2-(4-((substituted phenylimino)methyl)phenoxy)acetic acid derivatives were analysed by IR, 1H-NMR, 13C-NMR and MS-spectral techniques. The synthesized compounds were evaluated for their in vitro cytotoxicity and glucose uptake assay on 3T3-L1 and L6 cells. Further the activity data was used to develop 3D QSAR model to establish structure activity relationships for glucose uptake activity via CoMSIA studies. Conclusion The results of pharmacophore, molecular docking study and in vitro evaluation of synthesized compounds were found to be in good correlation. Specifically, CPD03, 07, 08, 18, 19, 21 and 24 are the candidate glitazones exhibited significant glucose uptake activity. 3D-QSAR model revealed the scope for possible further modifications as part of optimisation to find potent anti-diabetic agents.

Rising mortality due to cancer has led to the development and identification of newer targets and molecules to cure the disease. Telomerase is one of the attractive targets for design of many chemotherapeutic drugs. This research highlights the designing of novel telomerase inhibitors using ligand-based (3D-QSAR) and structure-based (molecular docking and molecular dynamics simulation) approaches. For the development of the 3D-QSAR model, 37 synthetic molecules reported earlier as telomerase inhibitors were selected from diversified literature. Three different alignment methods were explored; among them, distill alignment was found to be the best method with good statistical results and was used for the generation of QSAR model. Statistically significant CoMSIA model with a correlation coefficient (r2ncv) value of 0.974, leave one out (q2) value of 0.662 and predicted correlation coefficient (r2pred) value of 0.560 was used for the analysis of QSAR. For the MDS study, A-chain of telomerase was stabilised for 50 ns with respect to 1-atm pressure, with an average temperature of 299.98 k and with potential energy of 1,145,336 kJ/m converged in 997 steps. Furthermore, the behaviour study of variants towards the target revealed that active variable gave better affinity without affecting amino acid sequences and dimensions of protein which was accomplished through RMSD, RMSF and Rg analysis. Results of molecular docking study supported the outcomes of QSAR contour maps as ligand showed similar interactions with surrounded amino acids which were identified in contour map analysis. The results of the comprehensive study might be proved valuable for the development of potent telomerase inhibitors. [ABSTRACT FROM AUTHOR]

Genetic mutations in APC or CNTBB1 gene with aberrant canonical Wnt/β-catenin pathway are responsible for more than 90% of colorectal carcinogenesis. Tankyrases (TNKS) are known to downregulate Wnt signaling by stabilizing AXIN protein through poly(ADP ribose)polymerization or PARSylation process and subsequently, promoting degradation of intracellular β-catenin. Tankyrase enzymes are modulated by a range of known inhibitors that bind individually to any of the nicotinamide or induced adenosine pockets or as dual binding antagonists. Hence, for designing dual tankyrase inhibitors as Wnt signaling antagonist; we carried out 3D-QSAR studies using a data set of 51 molecules of reported 3,4,5-trisubstituted 4H-1,2,4-triazole derivatives. These reported 51 molecules were divided into a training set (39 molecules) and test set (12 molecules), aligned and subjected to generate CoMFA, CoMSIA, and HQSAR models. CoMFA analysis showed q2 value of 0.694, r2ncv value of 0.991 and r2pred value of 0.641. Optimized CoMSIA analysis (SEHA) showed q2 value of 0.624, r2ncv value of 0.909 and r2pred value of 0.850. Both internal and external validations were performed for generated models of CoMFA and CoMSIA (SEHA) and satisfactory results were obtained. HQSAR analysis showed q2, r2, and r2pred values of 0.781, 0.901, and 0.811, respectively. Applicability domain was also found to be satisfactory with all compounds falling within the range and no outlier was observed. Contour maps from all studies provided significant results with identification of desired spatial arrangement of different atoms or functional groups in a molecule. Triazole ring system-based molecules were reported as potent tankyrase inhibitors. These noteworthy results were employed for the design of different triazole derivatives as potent tankyrase inhibitors, wherein a series of 20 different molecules were designed for evaluation of their potentials as novel tankyrase inhibitors. [ABSTRACT FROM AUTHOR]

The angiotensin I-converting enzyme (ACE) has been found to exhibit inhibitory capability against blood pressure. Recently, several ACE inhibitors with different structures have been reported. In the present work, molecular modeling studies using quantitative structure–activity relationship (QSAR) and molecular docking simulations were carried out. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were firstly used to generate 3D-QSAR models. The results indicate that the best CoMFA model has R cv 2 = 0.504, R pred 2 = 0.5896, and the best CoMSIA model has R cv 2 = 0.525, R pred 2 = 0.5666. Furthermore, 2D-QSAR models developed by multiple linear regression/MLR, partial least squares regression/PLSR, and support vector machine regression/SVR methods provide highly significant squared correlation coefficient Rtr2 values of 0.8380, 0.8650, and 0.8230, external validated correlation coefficient Qte2 of 0.8279, 0.8223, and 0.7255, respectively. The statistical results show satisfactory goodness-of-fit, robustness, and perfect external predictive performance. Moreover, molecular docking studies were employed to predict the binding mode between dipeptides and ACE receptor. The combination of QSAR studies and molecular docking indicates the requirement of certain physicochemical parameters for better ACE inhibitors. [ABSTRACT FROM AUTHOR]

Radiotherapy and chemotherapy are conventional cancer treatments. Around 60% of all patients who are diagnosed with cancer receive radio- or chemotherapy in combination with surgery during their disease. Only a few patients respond to the blockage of immune checkpoints alone, or in combination therapy, because their tumours might not be immunogenic. Under these circumstances, an increasing level of extracellular adenosine via the activation of ecto-5’-nucleotidase (CD73) and consequent adenosine receptor signalling is a typical mechanism that tumours use to evade immune surveillance. CD73 is responsible for the conversion of adenosine monophosphate to adenosine. CD73 is overexpressed in various tumour types. Hence, targetting CD73’s signalling is important for the reversal of adenosine-facilitated immune suppression. In this study, we selected a potent series of the non-nucleotide small molecule inhibitors of CD73. Molecular docking studies were performed in order to examine the binding mode of the inhibitors inside the active site of CD73 and 3D-QSAR was used to study the structure–activity relationship. The obtained CoMFA (q2 = 0.844, ONC = 5, r2 = 0.947) and CoMSIA (q2 = 0.804, ONC = 4, r2 = 0.954) models showed reasonable statistical values. The 3D-QSAR contour map analysis revealed useful structural characteristics that were needed to modify non-nucleotide small molecule inhibitors. We used the structural information from the overall docking and 3D-QSAR results to design new, potent CD73 non-nucleotide inhibitors. The newly designed CD73 inhibitors exhibited higher activity (predicted pIC50) than the most active compound of all of the derivatives that were selected for this study. Further experimental studies are needed in order to validate the new CD73 inhibitors.

In search of potent anti-mycobacterial agents, enoyl-ACP reductase enzyme found to be most probable due to its imperative role in type II fatty acid synthesis (FAS), while mycolic acid production in Mycobacterium tuberculosis (M. tuberculosis), which is the appropriate entity for the discovery of antimycobacterial agents due to its primary role in the metabolism. Hence, blocking of enoyl ACP reductase would be important to develop novel antitubercular drugs development. Pyrrole, which is one of the five membered heterocyclic moieties habitually institute in few of naturally occurring and organic products of various classes, plays a significant part in medicinal drug discovery. In this work, docking and 3D-QSAR (CoMFA and CoMSIA) studies were performed on a set of pyrrolyl phenoxy acetohydrazides. As per docking study, TYR158 and co-factor NAD+ are important amino acid residue at active site of enzyme for binding with the ligand. Among all the tested molecules, Compounds 4 and 28 have shown good docking scores of 7.08 and 8.85 respectively, steric and electrostatic field in CoMFA model displayed q2 = 0.511, r 2 = 0.822 while that of CoMSIA model displayed q2 = 0.625, r2 = 0.764 with the SEE values of of 0.314 and 0.607. Docking study revealed complete structurally imperative binding topographies between the pyrrole scaffolds and enoyl ACP reductase enzyme. Our studies offered useful information and evidence for designing of molecules with enhanced InhA inhibition. [ABSTRACT FROM AUTHOR]

Glycogen synthase kinase-3 (GSK3) is a potential therapeutic target in bipolar disorder. Here, a three-dimensional quantitative structure–activity relationship (3D-QSAR) namely CoMFA, CoMFA-RF (region focusing), and CoMSIA has been carried out on a series (44 compounds) of GSK3 inhibitors on maleimide-based. The data set was divided into training set (32 compounds) and test set (12 compounds) using Kennard and Stone algorithm. An alignment rule for the training set was defined on the basis of common substructure-based alignment. The all-orientation search (AOS) was used to achieve the best orientation and minimize the effect of initial orientation of the structures. The statistical parameters from the models (CoMFA: q2 = 0.56, r pred 2 = 0.92 , CoMFA-RF: q2 = 0.70, r pred 2 = 0.91 , and CoMSIA: q2 = 0.60, r pred 2 = 0.83 ) indicate that the data are well fitted and have high predictive ability. Molecular docking was employed to explore the binding mode between these compounds and the receptor, as well as help understand the structure–activity relationship revealed by CoMFA and CoMSIA. The computer-aided design of new compounds as potential GSK-3 inhibitors with the application of defined structural alerts was presented. [ABSTRACT FROM AUTHOR]

In the present work, three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed in an attempt to predict the key features of bitter-tasting tripeptides. The 3D-QSAR models were carried out by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods and the corresponding statistical correlation coefficients R2cv for the training set are 0.534 and 0.547, respectively, the predicted correlation coefficients R2pred for the test set are found to be 0.7162 and 0.5792, respectively. The information obtained from the QSAR contour maps enables the interpretation of the structure-activity relationship. In addition, molecular docking was also employed to investigate the interaction between bitter-tasting peptides and related receptor hTAS2R1, results indicate that the Lys76, Pro188 and His243 were significant for binding to the peptides, and some essential features were identified to deduce some interesting structure-activity relationships. The present QSAR models along with information contour maps and molecular docking study may be used for designing and predicting novel bitter-tasting peptides. [ABSTRACT FROM AUTHOR]

Aminopeptidase M1 (PfAM1) is one of the key enzymes involved in the development of new antimalarials. To accelerate the discovery of inhibitors with selective activity against PfAM1 and microsomal neutral aminopeptidase (pAPN), in the present work, the optimum comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were built based on PfAM1 and pAPN inhibitors. The results of the developed 3D-QSAR models were as follows: PfAM1/CoMFA: R cv 2 = 0.740, R pred 2 = 0.7781; PfAM1/CoMSIA: R cv 2 = 0.740, R pred 2 = 0.7354; pAPN/CoMFA: R cv 2 = 0.612, R pred 2 = 0.7318; pAPN/CoMSIA: R cv 2 = 0.609, R pred 2 = 0.7480, and the models derived from MLR, PLSR and SVR methods provided high R2 values of 0.6960, 0.6965, 0.7971 for PfAM1, 0.7700, 0.7697, 0.8228 for pAPN and Q2 of 0.7004, 0.7004, 0.5632 for PfAM1, 0.7551, 0.7566 and 0.8394 for pAPN, respectively, indicating that the developed 3D-QSAR and 2D-QSAR models possess good ability for prediction of the relative compound activities. Furthermore, all inhibitors were docked into the active site of the PfAM1 and pAPN receptors, the hydrogen-bond interactions between the compound 33 with Glu497, Glu463 and Arg489 of the PfAM1, and the compound 4 with Ala348, Glu384 and Phe467 of the receptor pAPN are able to help to stabilize the conformation. The above results would provide helpful clues to predicting the binding activity of novel inhibitors and the foundation for understanding the interaction mechanism between the inhibitors and the receptors. [ABSTRACT FROM AUTHOR]

Macrocyclic ring structures could have drug-like properties such as membrane permeability, metabolic stability, binding affinity, selectivity, and high-biological activities. Synthesized macrocyclic inhibitors have been studied and the effect of ring size has gained attention from drug design community. Marsault et al. showed a positive correlation between ring size and inhibitory activity against rennin. On the other hand, De Clercq et al. suggested that there would be some optimum ring size for histone deacetylase inhibitory activity. Therefore, macrocyclic effects appear elusive while intriguing. In this study, we have selected a large set of macrocyclic inhibitors (14–20-membered rings) to study macrocyclic effect on MerTK using molecular modeling techniques. We carefully positioned all the cyclic inhibitors into the binding pocket utilizing available information obtained from both experimental and theoretical means. Then, from the resultant binding poses, the ligand–receptor interactions were analyzed. Unlike previous reports, we could not observe any relevance between ring size and inhibitory activity. However, there is a correlation between the number of hydrogen bonds and inhibitory activity. Among these hydrogen-bonding interactions, active site residues Arg727, and Asn728 as well as two signature interactions at the hinge region were found to be crucial for MerTK inhibition. Furthermore, the importance of number of hydrogen bonding was further validated statistically by means of 3D-QSAR techniques such as CoMFA and CoMSIA. The involvement of Arg727 and Asn728 was checked graphically by CoMSIA hydrogen-bonding donor map. This outcome could be helpful for more potent MerTK inhibitor design. In addition, more detailed studies on ring size effect would be desirable to understand macrocyclic effects. [ABSTRACT FROM AUTHOR]

Estrogen receptors (ERs) are significant protein targets that can alter normal homeostatic transcription and signaling pathways. And the development of selective ER ligands is involved in the pharmacology of anticancer drugs, leading to the synthesis of numerous ER selective ligands. In the present work, three dimensional quantitative structure–activity relationship (3D-QSAR) models, including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) in combination with molecular docking were performed on a series of ER ligands to investigate the potential relationship between the structural features of the compounds and its activity and selectivity. Good statistical significance was achieved for the CoMFA (ERα: R2cv = 0.676, R2pred = 0.631. ERβ: R2cv = 0.578, R2pred = 0.5341) and CoMISA (ERα: R2cv = 0.693, R2pred = 0.5758. ERβ: R2cv = 0.653, R2pred = 0.615) models. In addition, molecular docking results confirmed that the substituents at ring A, ring D and ring E were crucial for interacting with receptors ERα and ERβ, respectively, which were in agreement with the QSAR results. The substituents in ring A and ring F for ERα and residues Thr347/Ala302, Met388/Leu343, Leu391/Arg346, Met421/Ile376, Gly521/Leu476 for ERα and ERβ, respectively, contribute the most to the subtype selectivity. These results obtained from this work provide valuable information for the design of novel selective ER ligands with enhanced activity. [ABSTRACT FROM AUTHOR]

ERRγinverse agonist is a powerful therapeutic target for the treatment of cancers and certain metabolic disorders. Until now, only GSK5814 was reported as selective ERRγinverse agonist. So 60 newly hydroxytamoxifen analogues were selected to perform molecular docking and 3D-QSAR study to design more selective inverse agonist of ERRγ. Both established CoMFA and CoMSIA models obtained high predictive and satisfactory value, demonstrated that bulky, hydrophobic and negative electrostatic substitutions are preferred at R2 position, and introducing hydrophilic and H-bond donor and acceptor groups at R1 and R4 positions is greatly important for improving binding activities. The obtained information will be useful to provide clues for rationally designing novel and high potency ERRγinverse agonists. [ABSTRACT FROM AUTHOR]

Polo‐like kinase‐2 (PLK2) is a member of a highly conserved serine/threonine kinase family. PLK2 is implicated in the regulation of cell division. It is activated in the early G1 phase in cell cycle progression and is required for centriole duplication. It has been observed that the low expression of PLK2 leads to B‐cell lymphoma and ovarian cancer. Furthermore, it was found to be associated with poor prognosis in non‐small cell lung cancer, breast cancer, head and neck carcinoma, and osteosarcoma. Thus, PLK2 is considered as an important therapeutic target for cancer drug design due to its multiple roles in several types of cancers. In this work, molecular docking and 3D‐QSAR techniques were performed on tetrahydropteridin derivatives as PLK2 inhibitors. Docking study identified crucial active site residues such as Leu88, Cys96, Ala109, Lys111, Val143, Leu159, Glu160, Cys162, and Phe212 which helps in the firm binding of the ligand. Receptor‐guided CoMFA (q2 = 0.859, NOC = 5, r2 = 0.996) and CoMSIA (q2 = 0.855, NOC = 6, r2 = 0.998) models were produced. The predictability and stability of these models were assessed using different validation techniques. Contour maps revealed that electrostatic and steric substitutions were favorable at R1 and R2 positions respectively. In addition, the substitution of H‐bond donor group at the R1 position was also favored. The results of this study could be helpful for designing more potent PLK2 inhibitors. [ABSTRACT FROM AUTHOR]

Compounds 1‐((1‐(4‐(2H‐benzo[e][1,3]oxazin‐3(4H)‐yl)phenyl)ethylidene)amino)‐6‐((arylidene)amino)‐4‐(4‐chlorophenyl)‐2‐oxo‐1,2‐dihydropyridine‐3,5‐dicarbonitriles (4a‐j) were prepared, characterized and screened for antimicrobial activity. 3D‐quantitative structure activity relationship (3D‐QSAR) was explained by CoMFA and CoMSIA models to rationalize the antimicrobial activity of the titled compounds. Statistically significant 3D‐QSAR (CoMFA and CoMSIA) models were created which could provide valuable information about the structural modification desired to improvise the biological activity. Additionally, the predictions based on the molecular docking study, against microbial DNA gyrase, were carried out. [ABSTRACT FROM AUTHOR]

Oxytocin plays a vital role in the occurrence of preterm birth by interacting with oxytocin receptor (OTR), and thus OTR antagonists provide effective approaches for the treatment of early birth. Presently, for purpose of exploring the structural traits affecting the antagonism potency, the up-to-date largest set of 121 2,5-diketopiperazine derivatives as OTR antagonists was subjected to ligand-based three-dimensional quantitative structure–activity (3D-QSAR) analysis applying comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The resultant optimal CoMSIA model displays proper validity and predictability with cross-validated correlation coefficient Q2 = 0.614, non-cross-validated correlation coefficient R2 ncv = 0.969 and predicted correlation coefficient R2 pre = 0.912 for the test set of compounds, respectively. In addition, docking study was carried out for further elucidating the binding modes of OTR antagonists. The final docking cavity was located among the TM2-TM7 helices of the target protein and proved to be the same as described by other scholars' researches of other type of OTR antagonists. The major amino acids forming the cavity are Q92, Q96, K116, Q119, V120, M123, G196, I201, Q295, W288, F311 and M315. Representative compound 118 forms two H-bonds with Q119 and two H-bonds with Q295, with also a π - π stacking effect with F311, respectively. Meanwhile, as a supplementary tool to study the antagonists' conformation in the binding cavity, molecular dynamics (MD) simulation was also performed to further elucidate the changes in the ligand-receptor complex. We hope that the obtained models and information may help to provide an insight into the interaction mechanism of OTR antagonists and facilitate the design and optimization of novel antagonists for preventing premature birth. Image 1 • Oxytocin receptor antagonists are effective for preventing preterm labour. • Structural traits affecting antagonism potency were explored. • Crucial amino acids for antagonists binding of OTR were discovered. • Binding conformation of 2,5-diketopiperazine derivatives were analyzed. [ABSTRACT FROM AUTHOR]

• mTOR has become a promising target for the treatment of Breast Cancer. • Triazine Morpholino derivatives as mTOR inhibitors were selected for 3D-QSAR study. • 3D-QSAR contour maps were validated by MD/MS assisted molecular docking study. • Contour maps and molecular docking were used for the designing of mTOR inhibitors. mTOR has become a promising target for many types of cancer like breast, lung and renal cell carcinoma. CoMFA, CoMSIA, Topomer CoMFA and HQSAR were performed on the series of 39 triazine morpholino derivatives. CoMFA analysis showed q2 value of 0.735, r2 cv value of 0.722 and r2 pred value of 0.769. CoMSIA analysis (SEHD) showed q2 value of 0.761, r2 cv value of 0.775 and r2 pred value of 0.651. Topomer CoMFA analysis showed q2 value of 0.693, r2 (conventional correlation coefficient) value of 0.940 and r2 pred value of 0.720. HQSAR analysis showed q2 , r2 and r2 pred values of 0.694, 0.920 and 0.750, respectively. HQSAR analysis with the combination of atomic number (A), bond type (B) and atomic connections showed q2 and r2 values of 0.655 and 0.891, respectively. Contour maps from all studies provided significant insights. Molecular docking studies with molecular dynamics simulations were carried out on the highly potent compound 36. Furthermore, four acridine derivatives were designed and docking results of these designed compounds showed the same interactions as that of the standard PI-103 which proved the efficiency of 3D-QSAR and MD/MS study. In future, this study might be useful prior to synthesis for the designing of novel mTOR inhibitors. [ABSTRACT FROM AUTHOR]

Human histone deacetylase isoform 6 (HDAC6) has been shown to have an immense role in cell motility and aggresome formation and is being an attractive selective target for the treatment of multiple tumour types and neurodegenerative conditions. The discovery of selective HDAC6 inhibitors with new chemical functionalities is therefore of utmost interest to researchers. In order to examine the structural requirements for HDAC6‐specific inhibitors and to derive predictive model which can be used for designing new selective HDAC6 inhibitors, a three‐dimensional quantitative structure–activity relationship study was carried out on a diverse set of ligands using common feature‐based pharmacophore alignment followed by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The models displayed high correlation of 0.978 and 0.991 for best CoMFA and CoMSIA models, respectively, and a good statistical significance. The model could be used for predicting activities of the test set compounds as well as for deriving useful information regarding steric, electrostatic, hydrophobic properties of the molecules used in this study. Further, the training and test set molecules were docked into the HDAC6 binding site and molecular dynamics was carried out to suggest structural requirements for design of new inhibitors. [ABSTRACT FROM AUTHOR]

A RET (Rearranged during transfection) kinase belongs to a receptor tyrosine kinase family. It plays a major role in development, maturation, survival, and maintenance of cells and tissues. Oncogenic activation of RET has been reported in numerous cancers. Thus, it is a significant therapeutic target for cancer. Present work covers docking and 3D‐QSAR techniques executed on anilinoquinazoline derivatives as RET kinase antagonists. Docking study recognized important active site amino acid residues like Leu730, Gly731, Gly733, Glu734, Ala807, Gly810, Ser811, and Asp874 which inhibits the RET kinase. In 3D‐QSAR technique, receptor‐guided CoMFA (q2 = 0.723, NOC = 5, r2 = 0.980) as well as CoMSIA (q2 = 0.767, NOC = 6, r2 = 0.967) models were produced. The stabilities of these models were evaluated using diverse validation techniques. Contour maps showed that steric and hydrogen bond donor substitutions are favored at R1 and R2 positions whereas positive and negative substitutions are favored at the R1 position to enhance the potency. In addition, the substitution of H‐bond accepting group to the region which is close to both phenyl and piperazine is favored. Hence, the outcome of this study could be beneficial to design more potent inhibitors for RET kinase. [ABSTRACT FROM AUTHOR]

Abstract As a kind of potential anticancer compounds, Cyclin-dependent kinase (CDK) inhibitors have receved great attention in recent years. In order to deep research the bioactivity and corresponding key influence factors of CDK8/19 inhibitors on molecular level, quantum chemistry and 3D-QSAR have been performed on 64 molecules based on pyridine ring scaffold. Two high predictive QSAR models have been built, in which both the CoMFA model (q2 = 0.69, r2 = 0.98) and CoMSIA model (q2 = 0.61, r2 = 0.98) have displayed quite good external predictablility on test set with excellent values of r p r e d 2 (0.94 and 0.97). In these models, the steric, electrostatic and hydrophobic fields have played key roles on bioactivity. Docking simulation has been carried out to further investigate possible binding modes of compounds into the active site of CDK8 (PDB. 5I5Z), the results show that some high bioactivity molecules are quite well embedded in the active pocket. Nitrogen-atom of pyridine ring and some other groups (ie. NH, CO, SO. NH, CO, SO) have formed medium strength hydrogen bonds (1.5 Å to 2.2 Å) with the N, H, O atoms of the protein. The geometric structures of the inhibitor molecules have been changed differently during the processes of docking, surflex-dock has confirmed the acting force stability of predicted molecules in the protein. Our method and results can be helpful for finding new targets and developing new drugs. Graphical abstract 3D-surface of active site of CDK8 (pdb:5I5Z) included compound 28. Image 1 Highlights • The 3D-QSAR and molecular docking were carried out to study the CDK8 inhibitors. • All calculations were conducted using the Gaussian 09 program package. • QSAR models have excellent external predictive ability. • New compounds were designed and their biological activity were predicted by using built models. • The docking results among the existing CDK8 inhibitors and the target compounds were compared. [ABSTRACT FROM AUTHOR]

The 3D QSAR analysis using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques is performed on novel nalidixic acid based 1,2,4-triazole derivatives suggested earlier as antibacterial agents. The CoMFA and CoMSIA models employed for a training set of 28 compounds gives reliable values of Q2 (0.53 and 0.52, respectively) and R2 (0.79 and 0.85, respectively). The contour maps produced by the CoMFA and CoMSIA models are used to determine a three-dimensional quantitative structure-activity relationship. Based on the 3D QSAR contours new molecules with high predicted activities are designed. In addition, surflex-docking is performed to confirm the stability of predicted molecules in the receptor. [ABSTRACT FROM AUTHOR]

BTK inhibitors have been proved as an effective target for B-cell malignancies. Ibrutinib is the most advanced irreversible BTK inhibitor for treating mantle cell lymphoma/chronic lymphocytic leukaemia but with existing drug resistance and adverse effects. To design novel effective and safety reversible BTK inhibitors, 115 newly cinnoline analogues were selected to perform molecular docking and 3D-QSAR study because of the main scaffold similarity to Ibrutinib. Both established CoMFA and CoMSIA models obtained high predictive and satisfactory value. CoMFA/CoMSIA contour maps demonstrated that bulky substitutions are preferred at R1 and R3 positions, and introducing hydrophilic and negative electrostatic substitutions at R1 positions is important for improving BTK inhibitory activities. These results will be useful to provide clues for rationally designing novel and high potency BTK inhibitors. [ABSTRACT FROM AUTHOR]

The study deals with CoMFA, CoMSIA and HQSAR to explore the important features of tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepinone (TIBO) derivatives for exerting potent HIV-1 reverse transcriptase (HIV-1 RT) inhibitors activity. The cross-validated q 2 value of CoMFA model is 0.641 and the non-cross-validated r 2 value is 0.847. The best cross-validated q 2 value of CoMSIA Model is 0.706 and the non-cross-vaildated r 2 value is 0.939. The most effective HQSAR model was obtained that the cross-validation q 2 value of 0.839, the non-cross-validated r 2 value of 0.942, the standard error of prediction SD CV value of 0.604, and the best hologram length value of 307 using atoms and bonds as fragment distinctions. The statistical parameters from models indicate that the data are well fitted and have high predictive ability. Furthermore, Molecular docking was employed to explore the binding requirements between the ligands and the receptor protein which included several hydrogen bonds between the TIBO inhibitors and active site residues. Observations derived from these QSAR modeling study may be utilized further in designing promising HIV-1 reverse transcriptase inhibitors. [ABSTRACT FROM AUTHOR]

The bromodomain containing protein 4 (BRD4) recognizes acetylated histone proteins and plays numerous roles in the progression of a wide range of cancers, due to which it is under intense investigation as a novel anti-cancer drug target. In the present study, we performed three-dimensional quantitative structure activity relationship (3D-QSAR) molecular modeling on a series of 60 inhibitors of BRD4 protein using ligand- and structure-based alignment and different partial charges assignment methods by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The developed models were validated using various statistical methods, including non-cross validated correlation coefficient (r2), leave-one-out (LOO) cross validated correlation coefficient (q2), bootstrapping, and Fisher’s randomization test. The highly reliable and predictive CoMFA (q2 = 0.569, r2 = 0.979) and CoMSIA (q2 = 0.500, r2 = 0.982) models were obtained from a structure-based 3D-QSAR approach using Merck molecular force field (MMFF94). The best models demonstrate that electrostatic and steric fields play an important role in the biological activities of these compounds. Hence, based on the contour maps information, new compounds were designed, and their binding modes were elucidated in BRD4 protein’s active site. Further, the activities and physicochemical properties of the designed molecules were also predicted using the best 3D-QSAR models. We believe that predicted models will help us to understand the structural requirements of BRD4 protein inhibitors that belong to quinolinone and quinazolinone classes for the designing of better active compounds. [ABSTRACT FROM AUTHOR]

Protein tyrosine phosphatase 1B (PTP1B) is an intracellular non-receptor phosphatase that is implicated in signal transduction of insulin and leptin pathways, thus PTP1B is considered as potential target for treating type II diabetes and obesity. The present article is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling of a series of compounds possessing PTP1B inhibitory activities using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The optimum template ligand-based models are statistically significant with great CoMFA (R 2 cv  = 0.600, R 2 pred  = 0.6760) and CoMSIA (R 2 cv  = 0.624, R 2 pred  = 0.8068) values. Molecular docking was employed to elucidate the inhibitory mechanisms of this series of compounds against PTP1B. In addition, the CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of PTP1B active site. The knowledge of structure-activity relationship and ligand-receptor interactions from 3D-QSAR model and molecular docking will be useful for better understanding the mechanism of ligand-receptor interaction and facilitating development of novel compounds as potent PTP1B inhibitors. [ABSTRACT FROM AUTHOR]

Pathogenic Gram-negative bacteria are responsible for nearly half of the serious human infections. Hologram quantitative structure-activity relationships (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) were implemented on a group of 32 of potent Gram-negative LpxC inhibitors. The most effective HQSAR model was obtained using atoms, bonds, donor, and acceptor as fragment distinction. The cross-validated correlation coefficient (q2), non-cross-validated correlation coefficient (r2), and predictive correlation coefficient (r2Pred) for test set of HQSAR model were 0.937, 0.993, and 0.892, respectively. The generated models were found to be statistically significant as the CoMFA model had (r2 = 0.967, q2 = 0.804, r2Pred = 0.827); the CoMSIA model had (r2 = 0.963, q2 = 0.752, r2Pred = 0.857). Molecular docking was employed to validate the results of the HQSAR, CoMFA, and CoMSIA models. Based on the obtained information, six new LpxC inhibitors have been designed. [ABSTRACT FROM AUTHOR]

Type 2 diabetes is becoming a global pandemic disease. As an important target for the generation and development of diabetes mellitus, peroxisome proliferator-activated receptor γ (PPARγ) has been widely studied. PPARγ agonists have been designed as potential anti-diabetic agents. The advanced development of PPARγ agonists represents a valuable research tool for diabetes therapy. To explore the structural requirements of PPARγ agonists, three-dimensional quantitative structure–activity relationship (3D-QSAR) and molecular docking studies were performed on a series of N-benzylbenzamide derivatives employing comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and surflex-dock techniques. The generated models of CoMFA and CoMSIA exhibited a high cross-validation coefficient (q2) of 0.75 and 0.551, and a non-cross-validation coefficient (r2) of 0.958 and 0.912, respectively. The predictive ability of the models was validated using external validation with predictive factor (r2pred) of 0.722 and 0.682, respectively. These results indicate that the model has high statistical reliability and good predictive power. The probable binding modes of the best active compounds with PPARγ active site were analyzed, and the residues His323, Tyr473, Ser289 and Ser342 were found to have hydrogen bond interactions. Based on the analysis of molecular docking results, and the 3D contour maps generated from CoMFA and CoMSIA models, the key structural features of PPARγ agonists responsible for biological activity could be determined, and several new molecules, with potentially higher predicted activity, were designed thereafter. This work may provide valuable information in further optimization of N-benzylbenzamide derivatives as PPARγ agonists. [ABSTRACT FROM AUTHOR]

Matrix metalloproteinase-2 (MMP-2) is established as one of the most important metalloenzymes for targeting cancer. However, homologous MMP-9 of the gelatinase family is implicated as an antitarget of cancer. Therefore, it is an important and challenging task to achieve MMP-2 selectivity over MMP-9. In this article, robust validated chemico-biological quantitative approaches were conducted on a series of in house glutamate-based selective MMP-2 inhibitors over MMP-9 for further refinement of our MMP-2 inhibitor designing approach. The two-dimensional quantitative structure-activity relationship (2D-QSAR) study suggested that arylsulfonamide moiety was better than arylcarboxamide function, which in turn, supported by the hologram QSAR (HQSAR), 3D-QSAR comparative molecular field analysis (CoMFA), and comparative molecular similarity analysis (CoMSIA) studies. Regarding the MMP-2 selectivity, glutamines were better than isoglutamines as evidenced by the quantitative activity-activity relationship (QAAR) and molecular docking studies. Favorable hydrophobic and steric features of aryl function directed towards the S1′ pocket were also well attributed. Naphthyl and p-bromophenoxyphenyl moieties in place of biphenyl function were found to be unfavorable for MMP-2 inhibition and selectivity over MMP-9. Linear or cyclic aliphatic group directed towards the S2′ pocket was favorable, whereas branching was unfavorable for MMP-2 inhibition and selectivity. The importance of biphenyl and 3,5-bistrifluoromethylbenzyl functions directed towards the S1′ and S2′ pockets, respectively, was well attributed for potent MMP-2 inhibition and selectivity over MMP-9. [ABSTRACT FROM AUTHOR]

Mechanistic target of rapamycin is involved in the formation of tumor microvasculature was an ideal target for computer-aided drug design. The predictive study of quantitative structure-activity relationship and molecular docking can shorten the cycle and reduce the cost of designing the higher activity mTOR inhibitors. In this article, comparative molecular field analysis and comparative molecular similarity indices analysis fields were used to analyse three-dimensional quantitative structure-activity relationship model. The model (comparative molecular similarity indices analysis with q2=0.607, r2=0.909; comparative molecular similarity indices analysis with q2=0.703, r2=0.935) has a good predictability. Three-dimensional quantitative structure-activity relationship model contour maps indicate the electrostatic, hydrophobic and hydrogen bond donor fields have crucial effects to derivatives biological activity. Molecular docking was employed to explore the conformations of 55 compounds with key amino acid residues. Finally, combining contour maps with molecular docking results, ten derivatives as potential mechanistic target of rapamycin inhibitors were designed to further verify established three-dimensional quantitative structure-activity relationship models. These data provide significant theoretical foundation for designing better activity mechanistic target of rapamycin inhibitors. [ABSTRACT FROM AUTHOR]

Recently, great attention has been paid to the identification and prediction of the androgen disrupting potencies of polybrominated diphenyl ethers (PBDEs). However, few existing models can discriminate active and inactive compounds, which make the quantitative prediction process including the quantitative structure-activity relationship (QSAR) technique unreliable. In this study, different grouping methods were investigated and compared for qualitative identification, including molecular docking and molecular dynamics simulations (MD). The results showed that qualitative identification based on MD, which is lab-independent, accurate and closer to the real transcriptional activation process, could separate 90.5% of active and inactive chemicals and was preferred. The 3D-QSAR models built as the quantitative simulation method showed r 2 and q 2 values of 0.513 and 0.980, respectively. Together, a novel workflow combining qualitative identification and quantitative simulations was generated with processes including activeness discrimination and activity prediction. This workflow, for analyzing the antagonism of androgen receptor (AR) of PBDEs is not only allowing researchers to reduce their intense laboratory experiments but also assisting them in inspecting and adjusting their laboratory systems and results. [ABSTRACT FROM AUTHOR]

A collection of 36 thiosemicarbazone analogues possessed a broad span of tyrosinase inhibitory activities was designed and obtained. Robust and reliable CoMFA and CoMSIA models were gained to predict the structure–activity relationship and the new modifier direction. Inhibitory activities of the compounds were found to greatly depend upon molecular shape, size, and charge. The sterically bulky group at the C-4 position of the thiophene ring contributed a high capacity for biological activity. Some bulky substituents at the C1-position and C12-position, and electron-negative groups at the C3-position, helped to improve the activity of these analogues. The molecular docking results provided visual evidence for QSAR analysis and detailed information about binding mode, affinity, and the principal mechanism between the ligands and tyrosinase. Based on these, a prospective structure modification and optimization of the most potent compound, T32 , was suggested for further research. [ABSTRACT FROM AUTHOR]

Rearranged during transfection is a transmembrane receptor tyrosine kinase. It is involved in medullary thyroid cancer and lung adenocarcinoma in humans. In this work, molecular docking and three-dimensional quantitative structure-activity relationship studies were performed on recently reported series of two-substituted phenol quinazoline derivatives as rearranged during transfection inhibitors. Docking study identified key active site residues such as Ala807, Lys758, Leu802, Leu730, Tyr806, Ala756, Val804, Asp892, and Glu775 that participate in the inhibition of rearranged during transfection. A reasonable comparative molecular field analysis ( q = 0.592, optimal number of components = 4, r = 0.921) and comparative molecular similarity indices analysis ( q = 0.580, optimal number of components = 6, r = 0.963) models were generated in three-dimensional quantitative structure-activity relationship study. Various validation techniques such as external test set validation, bootstrapping analysis, and progressive scrambling were carried out to check the predictive ability of the obtained models. The validated models resulted in acceptable statistical values and proved to be predictive and robust. comparative molecular similarity indices analysis model was selected as the final model based on the reasonable statistical values of q , r , standard error of estimate, and r . The contour maps analysis of comparative molecular similarity indices analysis model revealed the favorable regions to enhance the inhibitory activity of compounds. R and R positions were favorable for bulky substitution. Hydrophilic and negative substitutions at R position were favorable. Thus results of our study can provide insights in the designing potent and selective rearranged during transfection kinase inhibitors. [ABSTRACT FROM AUTHOR]

Acetyl-CoA carboxylase (ACC) is a crucial metabolic enzyme, which plays a vital role in fatty acid metabolism and obesity induced type 2 diabetes. Herein, we have performed 3D-QSAR and molecular docking analysis on a novel series of (4-piperidinyl)-piperazines to design potent ACC inhibitors. This study correlates the ACC inhibitory activities of 68 (4-piperidinyl)-piperazine derivatives with several stereo-chemical parameters representing steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. The CoMFA and CoMSIA models exhibited excellent rncv2 values of 0.974 and 0.985, and rcv2 values of 0.671 and 0.693, respectively. CoMFA predicted rpred2 of 0.910 and CoMSIA predicted rpred2 of 0.963 showed that the predicted values were in good agreement with experimental values. Glide5.5 program was used to explore the binding mode of inhibitors inside the active site of ACC. We have accordingly designed novel ACC inhibitors by utilising the LeapFrog and predicted with excellent inhibitory activity in the developed models.

To explore the relationship between the structures of substituted pyrrolidine derivatives and their inhibition of dipeptidyl peptidase IV inhibitors. The QSAR, including CoMFA, CoMSIA and HQSAR, were applied to identify the key structures impacting their inhibitory potencies. The CoMFA, CoMSIA and HQSAR with cross-validated correlation coefficient (q) value of 0.727, 0.870 and 0.939 and r value of 0.973, 0.981 and 0.949. Based on the structure-activity relationship revealed by the present study, we have designed a set of novel dipeptidyl peptidase IV inhibitors that showed excellent potencies in the developed models. Thus, our results allowed us to design new derivatives with desired activities. [ABSTRACT FROM AUTHOR]