In silico study of porphyrin-anthraquinone hybrids as CDK2 inhibitor

Cyclin-Dependent Kinases (CDKs) are known to play crucial roles in controlling cell cycle progression of eukaryotic cell and inhibition of their activity has long been considered as potential strategy in anti-cancer drug research. In the present work, a series of porphyrin-anthraquinone hybrids bearing meso-substituents, i.e. either pyridine or pyrazole rings were designed and computationally evaluated for their Cyclin Dependent Kinase-2 (CDK2) inhibitory activity using molecular docking, molecular dynamics simulation, and binding free energy calculation. The molecular docking simulation revealed that all six porphyrin hybrids were able to bind to ATP-binding site of CDK2 and interacted with key residues constituted the active cavity of CDK2, while molecular dynamics simulation indicated that all porphyrins bound to CDK2 were stable for 6 ns. The binding free energies predicted by MM-PBSA method showed that most compounds exhibited higher affinity than that of native ligand (4-anilinoquinazoline, DTQ) and the affinity of mono-H₂PyP-AQ was about three times better than that of DTQ, indicating its potential to be advanced as a new CDK2 inhibitor.     

基于结构的新型CDK7抑制剂的设计、合成及其抗肿瘤活性

根据细胞周期依赖性激酶7(CDK7)的蛋白结构, 利用Discovery Studio 2.1程序包中的LigandFit模块建立了CDK7抑制剂的分子对接模型, 采用受试者工作特征曲线(ROC)方法选择LigScore2为最佳打分函数(ROC曲线下的面积为0.95), 并验证了该模型的准确性. 利用该模型对设计的化合物与CDK7蛋白进行对接分析, 得到了2个打分最高的化合物16、17, 进而通过13步的合成路线, 以中等至高的收率得到目标化合物, 并测定其体外抗肿瘤活性. 结果表明, 所合成的化合物对急性前髓细胞性白血病细胞(HL60)、鼻咽癌细胞(KB)、肝肿瘤细胞(SMMC-7721)、结肠腺癌细胞(HCT-116)、肺癌细胞(A549)细胞株均有抑制作用(IC50值为0.84-19.70 μmol·L-1), 其中化合物16对HL60细胞株的IC50值最低, 为0.84 μmol·L-1.     

Cross-docking of inhibitors into CDK2 structures. 2

In the preceding paper (Duca, J. S.; Madison, V. S.; Voigt, J. H. J. Chem. Inf. Model. 2008, 48, 659-668), the accuracy of docking and affinity predictions of the Gold and Glide programs were investigated using single protein conformations spanning 150 CDK2/inhibitor crystallographic complexes. High docking accuracy was observed with both methods; furthermore, Glide showed modest log(IC50)/score correlations. In this part of the study, the effect of combining docking results from multiple protein conformations in a consensus fashion was probed. This approach enhanced docking accuracy only for Glide, which was attributed to the nature of its scoring function. For log(IC50)/score correlations, particular emphasis was placed on considering only scores from correctly docked poses. Using multiple instead of single protein structures showed an improvement in the correlations. Validation sets and scrambling experiments were used to examine the statistical significance and predictivity of these correlations. Rather than actual improvements in scoring accuracy, docking to multiple protein conformations produced overfitting artifacts.     

Improving molecular docking through eHiTS’ tunable scoring function

We present three complementary approaches for score-tuning that improve docking performance in pose prediction, virtual screening and binding affinity assessment. The methodology utilizes experimental data to customize the scoring function for the system of interest considering the specific docking scenario. The tuning approach, which has been implemented as an automated utility in eHiTS, is introduced as a solution to one of the conundrums of the molecular docking paradigm, namely, the lack of a universally well performing scoring function. The accuracy of scoring functions has been shown to be generally system-dependent, and particularly lacking for binding energy and bio-activity predictions. In the proposed approach, pose and energy predictions are enhanced by adjusting the relative weights of the eHiTS energy terms to improve score-RMSD or score-affinity correlations. In a virtual screening context ligand-based similarity is used to rescale the docking score such that better enrichment factors are achieved. We discuss the algorithmic details of the methods, and demonstrate the effects of score tuning on a variety of targets, including CDK2, BACE1 and neuraminidase, as well as on the popular benchmarks—the Directory of Useful Decoys and the PDBBind database.     

Cross-docking of inhibitors into CDK2 structures. 1

Predicting protein/ligand binding affinity is one of the most challenging computational chemistry tasks. Numerous methods have been developed to address this challenge, but they all have limitations. Failure to account for protein flexibility has been a shortcoming of many methods. In this cross-docking study the data set comprised 150 inhibitor complexes of the protein kinase CDK2. Gold and Glide performed well in terms of docking accuracy. The chance of cross-docking a ligand within a 2 A RMSD of its experimental pose was found to be 50%. Relative binding potency was not properly predicted from scoring functions, even though cross-docking of each inhibitor into each protein structure was performed and only scores of correctly docked ligands were considered. An accompanying paper (Voigt, J. H.; Elkin, C.; Madison, V. S. Duca, J. S. J. Chem. Inf. Model. 2008, 48, 669-678) covers cross-docking and docking accuracy from the perspective of using multiple protein structures.     

Lessons in molecular recognition. 2. Assessing and improving cross-docking accuracy

Docking methods are used to predict the manner in which a ligand binds to a protein receptor. Many studies have assessed the success rate of programs in self-docking tests, whereby a ligand is docked into the protein structure from which it was extracted. Cross-docking, or using a protein structure from a complex containing a different ligand, provides a more realistic assessment of a docking program's ability to reproduce X-ray results. In this work, cross-docking was performed with CDocker, Fred, and Rocs using multiple X-ray structures for eight proteins (two kinases, one nuclear hormone receptor, one serine protease, two metalloproteases, and two phosphodiesterases). While average cross-docking accuracy is not encouraging, it is shown that using the protein structure from the complex that contains the bound ligand most similar to the docked ligand increases docking accuracy for all methods ("similarity selection"). Identifying the most successful protein conformer ("best selection") and similarity selection substantially reduce the difference between self-docking and average cross-docking accuracy. We identify universal predictors of docking accuracy (i.e., showing consistent behavior across most protein-method combinations), and show that models for predicting docking accuracy built using these parameters can be used to select the most appropriate docking method.     

Protein–ligand docking with multiple flexible side chains

In this work, we validate and analyze the results of previously published cross docking experiments and classify failed dockings based on the conformational changes observed in the receptors. We show that a majority of failed experiments (i.e. 25 out of 33, involving four different receptors: cAPK, CDK2, Ricin and HIVp) are due to conformational changes in side chains near the active site. For these cases, we identify the side chains to be made flexible during docking calculation by superimposing receptors and analyzing steric overlap between various ligands and receptor side chains. We demonstrate that allowing these side chains to assume rotameric conformations enables the successful cross docking of 19 complexes (ligand all atom RMSD < 2.0 A) using our docking software FLIPDock. The number of side receptor side chains interacting with a ligand can vary according to the ligand's size and shape. Hence, when starting from a complex with a particular ligand one might have to extend the region of potential interacting side chains beyond the ones interacting with the known ligand. We discuss distance-based methods for selecting additional side chains in the neighborhood of the known active site. We show that while using the molecular surface to grow the neighborhood is more efficient than Euclidian-distance selection, the number of side chains selected by these methods often remains too large and additional methods for reducing their count are needed. Despite these difficulties, using geometric constraints obtained from the network of bonded and non-bonded interactions to rank residues and allowing the top ranked side chains to be flexible during docking makes 22 out of 25 complexes successful.     

Evaluation of the performance of four molecular docking programs on a diverse set of protein‐ligand complexes

Many molecular docking programs are available nowadays, and thus it is of great practical value to evaluate and compare their performance. We have conducted an extensive evaluation of four popular commercial molecular docking programs, including Glide, GOLD, LigandFit, and Surflex. Our test set consists of 195 protein‐ligand complexes with high‐resolution crystal structures (resolution ≤2.5 Å) and reliable binding data [dissociation constant (K_d) or inhibition constant (K_i)], which are selected from the PDBbind database with an emphasis on diversity. The top‐ranked solutions produced by these programs are compared to the native ligand binding poses observed in crystal structures. Glide and GOLD demonstrate better accuracy than the other two on the entire test set. Their results are also less sensitive to the starting structures for docking. Comparison of the results produced by these programs at three different computation levels reveal that their accuracy are not always proportional to CPU cost as one may expect. The binding scores of the top‐ranked solutions produced by these programs are in low to moderate correlations with experimentally measured binding data. Further analyses on the outcomes of these programs on three suites of subsets of protein‐ligand complexes indicate that these programs are less capable to handle really flexible ligands and relatively flat binding sites, and they have different preferences to hydrophilic/hydrophobic binding sites. Our evaluation can help other researchers to make reasonable choices among available molecular docking programs. It is also valuable for program developers to improve their methods further. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Could the presence of sodium ion influence the accuracy and precision of the ligand-posing in the human A<Subscript>2A</Subscript> adenosine receptor orthosteric binding site using a molecular docking approach? Insights from <Emphasis Type="Italic">Dockbench</Emphasis>

The allosteric modulation of G protein-coupled receptors (GPCRs) by sodium ions has received considerable attention as crystal structures of several receptors, in their inactive conformation, show a Na⁺ ion bound to specific residues which, in the human A_2A adenosine receptor (hA_2A AR), are Ser91^3.39, Trp246^6.48, Asn280^7.45, and Asn284^7.49. A cluster of water molecules completes the coordination of the sodium ion in the putative allosteric site. It is absolutely consolidated that the progress made in the field of GPCRs structural determination has increased the adoption of docking-driven approaches for the identification or the optimization of novel potent and selective ligands. Despite the extensive use of docking protocols in virtual screening approaches, to date, almost any of these studies have been carried out without taking into account the presence of the sodium cation and its first solvation shell in the putative allosteric binding site. In this study, we have focused our attention on determining how the presence of sodium ion binding and additionally its first hydration sphere, in hA_2AAR could influence the ligand positioning accuracy during molecular docking simulations for most of the available resting and activated hA_2A AR crystal structures, using DockBench as a comparative benchmarking tool and implementing a new correlation coefficient (EM). This work provides indications on the evidence that the posing performance (accuracy and/or precision) of the docking protocols in reproducing the crystallographic poses of different hA_2A AR antagonists is generally increased in the presence of the sodium cation and its first solvation shell, in agreement with experimental observations. Consequently, the inclusion of sodium ion and its first solvation shell should be considered in order to facilitate the selection of new potential ligands in all molecular docking-based virtual screening protocols that aim to find novel GPCRs antagonists and inverse agonists.     

Computational analysis of ligand recognition mechanisms by prostaglandin E2 (subtype 2) and D2 receptors

The eight members of the prostanoid receptor family belong to the class A G protein-coupled receptors. We investigated the evolutionary relationship of the eight members by a molecular phylogenetic analysis and found that prostaglandin E₂ receptor subtype 2 (EP₂) and prostaglandin D₂ receptor (DP) were closely related. The structures of the ligands for the two receptors are similar to each other but are distinguished by the exchanged locations of the carbonyl oxygen and the hydroxy group in the cyclopentane ring. The ligand recognition mechanisms of the receptors were examined by an integrated approach using several computational methods, such as amino acid sequence comparison, homology modeling, docking simulation, and molecular dynamics simulation. The results revealed the similar location of the ligand between the two receptors. The common carboxy group of the ligands interacts with the Arg residue on the seventh transmembrane (TM) helix, which is invariant among the prostanoid receptors. EP₂ uses a Ser on TM1 to recognize the carbonyl oxygen in the cyclopentane ring of the ligand. The Ser is specifically conserved within EP₂. On the other hand, DP uses a Lys on TM2 to recognize the hydroxy group of the ?? chain of the ligand. The Lys is also specifically conserved within DP. The interaction network between the D(E)RY motif and TM6 was found in EP₂. However, DP lacked this network, due to the mutation in the D(E)RY motif. Based on these observations and the previously published mutational studies on the motif, the possibility of another activation mechanism that does not involve the interaction between the D(E)RY motif and TM6 will be discussed.     

Design,Synthesis, and In Vivo and In Silico Evaluation of Coumarin Derivatives with Potential Antidepressant Effects

In this study, a series of coumarin derivatives were designed and synthesized, their structures were characterized using nuclear magnetic resonance (NMR) and high-resolution mass spectrometry (HRMS) testing methods. In the pharmacological experiment, two behavior-monitoring methods, the forced swim test (FST) and the tail suspension test (TST), were used to determine the antidepressant activity of coumarin derivatives. Compounds that showed potential activity were analyzed for their effects on 5-hydroxytryptamine (5-HT) levels in the brains of mice. Molecular docking experiments to simulate the possible interaction of these compounds with the 5-HT_1A receptor was also be predicted. The results of the pharmacological experiments showed that most coumarin derivatives exhibited significant antidepressant activity. Among these compounds, 7-(2-(4-(4-fluorobenzyl)piperazin-1-yl)-2-oxoethoxy)-2H-chromen-2-one (6i) showed the highest antidepressant activity. The results of the measurement of 5-HT levels in the brains of mice indicate that the antidepressant activity of coumarin derivatives may be mediated by elevated 5-HT levels. The results of molecular docking demonstrated that compound 6i had a significant interaction with amino acids around the active site of the 5-HT_1A receptor in the homology model. The physicochemical and pharmacokinetic properties of the target compounds were also predicted using Discovery Studio (DS) 2020 and Chemdraw 14.0.     

In Silico Approach Using Free Software to Optimize the Antiproliferative Activity and Predict the Potential Mechanism of Action of Pyrrolizine-Based Schiff Bases

In the current study, a simple in silico approach using free software was used with the experimental studies to optimize the antiproliferative activity and predict the potential mechanism of action of pyrrolizine-based Schiff bases. A compound library of 288 Schiff bases was designed based on compound 10, and a pharmacophore search was performed. Structural analysis of the top scoring hits and a docking study were used to select the best derivatives for the synthesis. Chemical synthesis and structural elucidation of compounds 16a–h were discussed. The antiproliferative activity of 16a–h was evaluated against three cancer (MCF7, A2780 and HT29, IC₅₀ = 0.01–40.50 μM) and one normal MRC5 (IC₅₀ = 1.27–24.06 μM) cell lines using the MTT assay. The results revealed the highest antiproliferative activity against MCF7 cells for 16g (IC₅₀ = 0.01 μM) with an exceptionally high selectivity index of (SI = 578). Cell cycle analysis of MCF7 cells treated with compound 16g revealed a cell cycle arrest at the G₂/M phase. In addition, compound 16g induced a dose-dependent increase in apoptotic events in MCF7 cells compared to the control. In silico target prediction of compound 16g showed six potential targets that could mediate these activities. Molecular docking analysis of compound 16g revealed high binding affinities toward COX-2, MAP P38α, EGFR, and CDK2. The results of the MD simulation revealed low RMSD values and high negative binding free energies for the two complexes formed between compound 16g with EGFR, and CDK2, while COX-2 was in the third order. These results highlighted a great potentiality for 16g to inhibit both CDK2 and EGFR. Taken together, the results mentioned above highlighted compound 16g as a potential anticancer agent.     

Selective ATP competitive leads of CDK4: Discovery by 3D-QSAR pharmacophore mapping and molecular docking approach

The discovery of ATP competitive CDK4 inhibitors is an on-going challenging task in cancer therapy. Here, an attempt has been made to develop new leads targeting ATP binding site of CDK4 by applying 3D-QSAR pharmacophore mapping and molecular docking methods The outcome of 6 leads offers a significant contribution for selective CDK4 inhibition, since they show potential binding interactions with Val⁹⁶, Arg¹⁰¹, and Glu¹⁴⁴ residues of CDK4, that are unique and from other kinases. It is worth noting that there is a striking similarity in binding interactions of the leads and known CDK4 inhibitors, namely Abemaciclib, Palbociclib and Ribociclib. Further key features, including high dock score value, good predicted activity, scaffold diversity, and the acceptable ADME profile of leads, provide a great opportunity for the development of highly potent and selective ATP competitive inhibitors of CDK4.     

Q-Dock: Low-resolution flexible ligand docking with pocket-specific threading restraints

The rapidly growing number of theoretically predicted protein structures requires robust methods that can utilize low-quality receptor structures as targets for ligand docking. Typically, docking accuracy falls off dramatically when apo or modeled receptors are used in docking experiments. Low-resolution ligand docking techniques have been developed to deal with structural inaccuracies in predicted receptor models. In this spirit, we describe the development and optimization of a knowledge-based potential implemented in Q-Dock, a low-resolution flexible ligand docking approach. Self-docking experiments using crystal structures reveals satisfactory accuracy, comparable with all-atom docking. All-atom models reconstructed from Q-Dock's low-resolution models can be further refined by even a simple all-atom energy minimization. In decoy-docking against distorted receptor models with a root-mean-square deviation, RMSD, from native of approximately 3 A, Q-Dock recovers on average 15-20% more specific contacts and 25-35% more binding residues than all-atom methods. To further improve docking accuracy against low-quality protein models, we propose a pocket-specific protein-ligand interaction potential derived from weakly homologous threading holo-templates. The success rate of Q-Dock employing a pocket-specific potential is 6.3 times higher than that previously reported for the Dolores method, another low-resolution docking approach.     

A New Oxadiazole-Based Topsentin Derivative Modulates Cyclin-Dependent Kinase 1 Expression and Exerts Cytotoxic Effects on Pancreatic Cancer Cells

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal form of cancer characterized by drug resistance, urging new therapeutic strategies. In recent years, protein kinases have emerged as promising pharmacological targets for the treatment of several solid and hematological tumors. Interestingly, cyclin-dependent kinase 1 (CDK1) is overexpressed in PDAC tissues and has been correlated to the aggressive nature of these tumors because of its key role in cell cycle progression and resistance to the induction of apoptosis. For these reasons, CDK1 is one of the main causes of chemoresistance, representing a promising pharmacological target. In this study, we report the synthesis of new 1,2,4-oxadiazole compounds and evaluate their ability to inhibit the cell growth of PATU-T, Hs766T, and HPAF-II cell lines and a primary PDAC cell culture (PDAC3). Compound 6b was the most active compound, with IC₅₀ values ranging from 5.7 to 10.7 µM. Molecular docking of 6b into the active site of CDK1 showed the ability of the compound to interact effectively with the adenosine triphosphate binding pocket. Therefore, we assessed its ability to induce apoptosis (which increased 1.5- and 2-fold in PATU-T and PDAC3 cells, respectively) and to inhibit CDK1 expression, which was reduced to 45% in Hs766T. Lastly, compound 6b passed the ADME prediction, showing good pharmacokinetic parameters. These data demonstrate that 6b displays cytotoxic activity, induces apoptosis, and targets CDK1, supporting further studies for the development of similar compounds against PDAC.     

Virtual screening using docking and molecular dynamics of cannabinoid analogs against CB1 and CB2 receptors

BackgroundCannabis sativa has been attributed to different pharmacological properties. A number of secondary metabolites such as tetrahydrocannabinol (THC), cannabinol (CBD), and different analogs, with highly promising biological activity on CB₁ and CB₂ receptors, have been identified.MethodsThus, this study aimed was to evaluate the activity of THC, CBD, and their analogs using molecular docking and molecular dynamics simulations (MD) methods. Initially, the molecules (ligands) were selected by bioinformatics searches in databases. Subsequently, CB₁ and CB₂ receptors were retrieved from the protein data bank database. Afterward, each receptor and its ligands were optimized to perform molecular docking. Then, MD Simulation was performed with the most stable ligand-receptor complexes. Finally, the Molecular Mechanics-Generalized Born Surface Area (MM-PBSA) method was applied to analyze the binding free energy between ligands and cannabinoid receptors.ResultsThe results obtained showed that ligand LS-61176 presented the best affinity in the molecular docking analysis. Also, this analog could be a CB₁ negative allosteric modulator like CBD and probably an agonist in CB₂ like THC and CBD according to their dynamic behavior in silico. The possibility of having a THC and a CBD analog (LS-61176) as a promising molecule for experimental evaluation since it could have no central side-effects on CB₁ and have effects of CB₂ useful in pain, inflammation, and some immunological disorders. Docking results were validate using ROC curve for both cannabinoids receptor where AUC for CB1 receptor was 0.894±0.024, and for CB2 receptor AUC was 0.832±0032, indicating good affinity prediction.     

Does the molecular structure of CaH2 affect the dihydrogen bonding in CaH2 … HY (Y = CH3, C2H3, C2H, CN, and NC) complexes? A quantum chemistry study using MP2 and B3LYP methods

Second-order M ller-Plesset(MP2) and density functional theory(DFT) calculations have been carried out in order to investigate the structures and properties of dihydrogen-bonded CaH 2 HY(Y = CH 3,C 2 H 3,C 2 H,CN,and NC) complexes.Our calculations revealed two possible structures for CaH 2 in CaH 2 HY complexes:linear(I) and bent(II).The bond lengths,interaction energies,and strengths for H H interactions obtained by both MP2 and B3LYP methods are quite close to each other.It was found that the interaction energy decreases with increasing electron density at the Ca-H bond critical point.Atom-in-molecule(AIM) results show that for all of Ca-H H-Y interactions considered here,the Laplacian of the electron density at the H H bond critical point is positive,indicating the electrostatic nature of these Ca-H H-Y dihydrogen bonded systems.     

靛玉红类CDK1抑制剂的同源模建、分子对接及3D-QSAR研究

细胞周期蛋白依赖性激酶1的异常表达会导致G2期的停滞及多种肿瘤的发生,故CDK1近年来已成为一个理想的治疗靶点. 本文以细胞分裂调控蛋白2的同源体为模板,同源模建了CDK1的结构,并与靛玉红类小分子抑制剂进行分子对接. 分别运用三种叠合方法进行分子叠合,并在此基础上采用Sybyl 7.1中的比较分子场分析(CoMFA)模块及Discovery Studio 3.0中的三维定量构效关系(3D-QSAR)模块(以下简称为DS)分别建立了3D-QSAR模型. 其中,将分子对接叠合与公共骨架叠合联合运用的叠合方法所得3D-QSAR模型的评价参数是最佳的(CoMFA：q²=0.681,r²=0.909,r_pred.²=0.836; DS：q²=0.579,r²=0.971,r_pred.²=0.795,其中q²为交叉验证系数,r²为非交叉验证系数). 本文的研究结果在对靛玉红类小分子进行结构修饰设计出新的CDK1抑制剂方面,可提供重要的理论基础.     

Molecular docking,PKPD, and assessment of toxicity of few chalcone analogues as EGFR inhibitor in search of anticancer agents

In the present work, molecular docking of the chalcone analogues with receptor EGFR carried out using erlotinib as reference drug is reported. About 15 chalcone analogues were analyzed CHL(1–15). Molecules CHL2, CHL3, CHL9, CHL11, and CHL15 found strong affinity for receptor EGFR exhibiting binding energies ??7.7 kcal/mol, ??7.5 kcal/mol, ??7.6 kcal/mol, ??7.9 kcal/mol, and ??8.1 kcal/mol, respectively, when erlotinib a reference drug exhibits binding energy ??7.6 kcal/mol. Toxicity for molecules was assessed against the cytochromes P450 (CYP) and P-gp using Swiss ADMET. Molecule CHL9 could be a suitable lead compound inhibitor to CYP1A2 followed by CHL2 inhibitor of CYP1A2 and CYP2C9 and CHL15 with a most stable binding affinity of ??8.1 kcal/mol, inhibiting CYP1A2, CYP2C19, and CYP2D6. CHL3 has a binding affinity of ??7.5 kcal/mol, inhibiting all the 05 CYP enzymes (CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4). CHL11 has a binding affinity of ??7.9 kcal/mol, inhibiting CYP1A2, CYP2C19, and CYP2C9. Considering inhibition of CYP family enzymes by molecules, further here we have perform the enrichment analysis to these CYP family enzymes and reported the metabolic pathways which were probably affected by inhibition of these enzymes using EnrichR online enrichment analysis server. The current predictions over these 15 chalcone derivatives will be needed to further investigate in vivo and in vitro conditions to identify the optimum therapeutic efficacy and least toxicity.