Insights into the Structural Basis of N2 and O6 Substituted Guanine Derivatives as Cyclin-Dependent Kinase 2 (CDK2) Inhibitors: Prediction of the Binding Modes and Potency of the inhibitors by Docking and ONIOM Calculations

Inhibitory potential of furanocoumarins against cyclin dependent kinase 4 using integrated docking, molecular dynamics and ONIOM methods

Cyclin Dependent Kinase 4 (CDK4) is vital in the process of cell-cycle and serves as a G1 phase checkpoint in cell division. Selective antagonists of CDK4 which are in use as clinical chemotherapeutics cause various side-effects in patients. Furanocoumarins induce anti-cancerous effects in a range of human tumours. Therefore, targeting these compounds against CDK4 is anticipated to enhance therapeutic effectiveness. This work intended to explore the CDK4 inhibitory potential of 50 furanocoumarin molecules, using a comprehensive approach that integrates the processes of docking, drug-likeness, pharmacokinetic analysis, molecular dynamics simulations and ONIOM (Our own N-layered Integrated molecular Orbital and Molecular mechanics) methods. The top five best docked compounds obtained from docking studies were screened for subsequent analysis. The molecules displayed good pharmacokinetic properties and no toxicity. Epoxybergamottin, dihydroxybergamottin and notopterol were found to inhabit the ATP-binding zone of CDK4 with substantial stability and negative binding free energy forming hydrogen bonds with key catalytic residues of the protein. Notopterol exhibiting the highest binding energy was subjected to ONIOM calculations wherein the hydrogen bonding interactions were retained with significant negative interaction energy. Hence, through these series of computerised methods, notopterol was screened as a potent CDK4 inhibitor and can act as a starting point in successive processes of drug design.Communicated by Ramaswamy H. Sarma.

Computational modelling of nanotube delivery of anti-cancer drug into glutathione reductase enzyme

Density functional theory method combined with docking and molecular dynamics simulations are used to understand the interaction of carmustine with human glutathione reductase enzyme. The active site of the enzyme is evaluated by docking simulation is used for molecular dynamics simulation to deliver the carmustine molecule by (5,5) single walled carbon nanotube (SWCNT). Our model of carmustine in the active site of GR gives a negative binding energy that is further refined by QM/MM study in gas phase and solvent phase to confirm the stability of the drug molecule inside the active site. Once released from SWCNT, carmustine forms multiple polar and non-polar hydrogen bonding interactions with Tyr180, Phe209, Lys318, Ala319, Leu320, Leu321, Ile350, Thr352 and Val354 in the range of 2–4 Å. The SWCNT vehicle itself is held fix at its place due to multiple pi-pi stacking, pi-amide, pi-sigma interactions with the neighboring residues. These interactions in the range of 3–5 Å are crucial in holding the nanotube outside the drug binding region, hence, making an effective delivery. This study can be extended to envisage the potential applications of computational studies in the modification of known drugs to find newer targets and designing new and improved controlled drug delivery systems.

The latest automated docking technologies for novel drug discovery

INTRODUCTION

Molecular docking has been consolidated as one of the most important methods in the molecular modeling field. It has been recognized as a prominent tool in the study of protein-ligand complexes, to describe intermolecular interactions, to accurately predict poses of multiple ligands, to discover novel promising bioactive compounds. Molecular docking methods have evolved in terms of their accuracy and reliability; but there are pending issues to solve for improving the connection between the docking results and the experimental evidence.

AREAS COVERED

In this article, the author reviews very recent innovative molecular docking applications with special emphasis on reverse docking, treatment of protein flexibility, the use of experimental data to guide the selection of docking poses, the application of Quantum mechanics(QM) in docking, and covalent docking.

EXPERT OPINION

There are several issues being worked on in recent years that will lead to important breakthroughs in molecular docking methods in the near future These developments are related to more efficient exploration of large datasets and receptor conformations, advances in electronic description, and the use of structural information for guiding the selection of results.

Halogenated derivatives of methotrexate as human dihydrofolate reductase inhibitors in cancer chemotherapy

Methotrexate is a widely used anti-metabolite in cancer chemotherapy. A series of halogenated drugs is designed from Methotrexate to assess their interactions with human dihydrofolate reductase. The aim of this study is to evaluate the performance of the modified drugs compared to the parent Methotrexate. Density Functional Theory is employed to optimize these drugs. Molecular docking calculation of these optimized drugs against dihydrofolate reductase is performed to find out binding affinity. In addition, molecular dynamics simulation is considered for the complexes of best two modified drugs with their receptors. Modifications by the halogens show significant changes in the charge distribution, dipole moment, thermodynamic stability, enthalpy and free energy. The highest binding affinity value (-36.401 KJ/mol) was obtained for M14. Hybrid quantum mechanics/molecular mechanics calculation shows a binding energy of -255.140 KJ/mol. Modified drugs have significant hydrogen and non-covalent bonding interactions with amino acids of the receptor. Molecular dynamics simulation disclosed that the root-mean-square-deviation of the alpha carbon associated with M6-1KMV and M14-1KMV complexes is 2.367 Å and 2.622 Å, respectively. Moreover, the interactions between modified drugs and receptor are mostly persevered in 25 nanosecond molecular dynamics simulation. Ensemble-based docking also confirmed that modified drugs show strong non-bonding interactions with different crystallographic and molecular dynamics based conformers. The best scored drugs show considerable pharmacokinetic properties. Modified derivatives M5, M6, M8, M10, M13 and M14 show the better binding affinity and a good number of hydrogen and other non-bonding interactions with the target protein which are similar to other anticancer drugs.Communicated by Ramaswamy H. Sarma.

Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data?

Molecular docking is the most frequently used computational method for studying the interactions between organic molecules and biological macromolecules. In this context, docking allows predicting the preferred pose of a ligand inside a receptor binding site. However, the selection of the “best” solution is not a trivial task, despite the widely accepted selection criterion that the best pose corresponds to the best energy score. Here, several rigid-target docking methods were evaluated on the same dataset with respect to their ability to reproduce crystallographic binding orientations, to test if the best energy score is a reliable criterion for selecting the best solution. For this, two experiments were performed: (A) to reconstruct the ligand-receptor complex by performing docking of the ligand in its own crystal structure receptor (defined as self-docking), and (B) to reconstruct the ligand-receptor complex by performing docking of the ligand in a crystal structure receptor that contains other ligand (defined as cross-docking). Root-mean square deviation (RMSD) was used to evaluate how different the obtained docking orientation is from the corresponding co-crystallized pose of the same ligand molecule. We found that docking score function is capable of predicting crystallographic binding orientations, but the best ranked solution according to the docking energy is not always the pose that reproduces the experimental binding orientation. This happened when self-docking was achieved, but it was critical in cross-docking. Taking into account that docking is typically used with predictive purposes, during cross-docking experiments, our results indicate that the best energy score is not a reliable criterion to select the best solution in common docking applications. It is strongly recommended to choose the best docking solution according to the scoring function along with additional structural criteria described for analogue ligands to assure the selection of a correct docking solution.

Recent advances on CDK inhibitors: An insight by means of in silico methods

The cyclin dependent kinases (CDKs) are a small family of serine/threonine protein kinases that can act as a potential therapeutic target in several proliferative diseases, including cancer. This short review is a survey on the more recent research progresses in the field achieved by using in silico methods. All the "armamentarium" available to the medicinal chemists (docking protocols and molecular dynamics, fragment-based, de novo design, virtual screening, and QSAR) has been employed to the discovery of new, potent, and selective inhibitors of cyclin dependent kinases. The results cited herein can be useful to understand the nature of the inhibitor-target interactions, and furnish an insight on the structural/molecular requirements necessary to achieve the required selectivity against cyclin dependent kinases over other types of kinases.

Using DFT methodology for more reliable predictive models: Design of inhibitors of Golgi α-Mannosidase II

Human Golgi α-mannosidase II (GMII), a zinc ion co-factor dependent glycoside hydrolase (E.C.3.2.1.114), is a pharmaceutical target for the design of inhibitors with anti-cancer activity. The discovery of an effective inhibitor is complicated by the fact that all known potent inhibitors of GMII are involved in unwanted co-inhibition with lysosomal α-mannosidase (LMan, E.C.3.2.1.24), a relative to GMII. Routine empirical QSAR models for both GMII and LMan did not work with a required accuracy. Therefore, we have developed a fast computational protocol to build predictive models combining interaction energy descriptors from an empirical docking scoring function (Glide-Schrödinger), Linear Interaction Energy (LIE) method, and quantum mechanical density functional theory (QM-DFT) calculations. The QSAR models were built and validated with a library of structurally diverse GMII and LMan inhibitors and non-active compounds. A critical role of QM-DFT descriptors for the more accurate prediction abilities of the models is demonstrated. The predictive ability of the models was significantly improved when going from the empirical docking scoring function to mixed empirical-QM-DFT QSAR models (Q(2)=0.78-0.86 when cross-validation procedures were carried out; and R(2)=0.81-0.83 for a testing set). The average error for the predicted ΔGbind decreased to 0.8-1.1kcalmol(-1). Also, 76-80% of non-active compounds were successfully filtered out from GMII and LMan inhibitors. The QSAR models with the fragmented QM-DFT descriptors may find a useful application in structure-based drug design where pure empirical and force field methods reached their limits and where quantum mechanics effects are critical for ligand-receptor interactions. The optimized models will apply in lead optimization processes for GMII drug developments.

Molecular modeling studies to characterize N-phenylpyrimidin-2-amine selectivity for CDK2 and CDK4 through 3D-QSAR and molecular dynamics simulations

Molecular modeling simulations were carried out to understand the structure–activity and selectivity correlation of N-phenylpyrimidin-2-amines binding to CDK2 and CDK4.

Design and synthesis of potent N-phenylpyrimidine derivatives for the treatment of skin cancer

The development of novel synthetic compounds for the treatment of skin cancer is much needed, as there is a sudden rise in the incidence of skin cancer throughout the world and the available chemotherapy is facing problems of resistance.

Prediction of binding modes and affinities of 4-substituted-2,3,5,6-tetrafluorobenzenesulfonamide inhibitors to the carbonic anhydrase receptor by docking and ONIOM calculations

Inhibition activities of a series of 4-substituted-2,3,5,6-tetrafluorobenzenesulfonamides against the human carbonic anhydrase II (HCAII) enzyme have been explored by employing molecular docking and hybrid QM/MM methods. The docking protocol has been employed to assess the best pose of each ligand in the active site cavity of the enzyme, and probe the interactions with the amino acid residues. The docking calculations reveal that the inhibitor binds to the catalytic Zn(2+) site through the deprotonated sulfonamide nitrogen atom by making several hydrophobic and hydrogen bond interactions with the side chain residues depending on the substituted moiety. A cross-docking approach has been adopted prior to the hybrid QM/MM calculation to validate the docked poses. A correlation between the experimental dissociation constants and the docked free energies for the enzyme-inhibitor complexes has been established. Two-layered ONIOM calculations based on QM/MM approach have been performed to evaluate the binding efficacy of the inhibitors. The inhibitor potency has been predicted from the computed binding energies after taking into account of the electronic phenomena associated with enzyme-inhibitor interactions. Both the hybrid (B3LYP) and meta-hybrid (M06-2X) functionals are used for the description of the QM region. To improve the correlation between the experimental biological activity and the theoretical results, a three-layered ONIOM calculation has been carried out and verified for some of the selected inhibitors. The charge transfer stabilization energies are calculated via natural bond orbital analysis to recognize the donor-acceptor interaction in the binding pocket of the enzyme. The nature of binding between the inhibitors and HCAII active site is further analyzed from the electron density distribution maps.

Interaction of ruthenium(ii) antitumor complexes with d(ATATAT)2 and d(GCGCGC)2: a theoretical study

We have investigated the interaction of three ruthenium(ii) complexes with d(ATATAT)₂ and d(GCGCGC)₂ sequences by using the molecular docking and quantum mechanics/molecular mechanics (QM/MM) hybrid method.

Parametrization of an Orbital-Based Linear-Scaling Quantum Force Field for Noncovalent Interactions

We parametrize a linear-scaling quantum mechanical force field called mDC for the accurate reproduction of nonbonded interactions. We provide a new benchmark database of accurate ab initio interactions between sulfur-containing molecules. A variety of nonbond databases are used to compare the new mDC method with other semiempirical, molecular mechanical, ab initio, and combined semiempirical quantum mechanical/molecular mechanical methods. It is shown that the molecular mechanical force field significantly and consistently reproduces the benchmark results with greater accuracy than the semiempirical models and our mDC model produces errors twice as small as the molecular mechanical force field. The comparisons between the methods are extended to the docking of drug candidates to the Cyclin-Dependent Kinase 2 protein receptor. We correlate the protein-ligand binding energies to their experimental inhibition constants and find that the mDC produces the best correlation. Condensed phase simulation of mDC water is performed and shown to produce O-O radial distribution functions similar to TIP4P-EW.

Molecular insights into the promiscuous interaction of human pregnane X receptor (hPXR) with diverse environmental chemicals and drug compounds

The nuclear receptor member human pregnane X receptor (hPXR) regulates enzymes and transporters involved in xenobiotic detoxification as well as maintains homeostatic balance of bile acids, thyroid and steroid hormones. hPXR can be recognized and activated by a structurally diverse array of environmental chemicals and drug compounds to initiate adverse biological effects, such as perturbing normal physiological functions and causing dangerous drug-drug interactions and exhibiting a high promiscuity in its ligand spectrum. Understanding of the molecular mechanism and biological implication underlying the promiscuous interaction of hPXR with its diverse ligands is fundamentally important for toxicological and pharmaceutical researches. In the current study, molecular docking and hybrid quantum mechanics/molecular mechanics (QM/MM) were employed to investigate the binding mode, structural basis and energetic property of hPXR interactions with various activators and non-activators. It was found that, as compared to non-activators, the activators adopt few dominant modes to tightly interact with hPXR, which are specified by few polar spots located on the hydrophobic surface of hPXR active pocket. Based on the findings, a novel method called multiple binding mode-based quantitative structure-activity relationship (MBMB-QSAR) that characterizes the nonbonded interaction profile of hPXR with its ligand in multiple binding modes was proposed to model and predict the activating potency of small-molecule compounds on hPXR. Several partial least square (PLS) predictors derived from the MBMB-QSAR modeling were demonstrated to be effective for quantitative characterization of the biological behavior of experimentally confirmed activators, and for qualitatively differentiating the activators from a large number of non-activators. From the predictor models it is suggested that the hydrophobic force and electrostatic interaction play an important role in hPXR-ligand binding, while steric factor contributes moderately to the binding.

Interactions of the aquated forms of ruthenium(iii) anticancer drugs with protein: a detailed molecular docking and QM/MM investigation

The interaction of monoaqua and diaqua ruthenium complexes which are formed after intracellular aquation of their respective complexes with human serum albumin (HSA) has been computationally investigated by molecular docking and two layer QM/MM hybrid methods.

Docking and quantitative structure-activity relationship of oxadiazole derivates as inhibitors of GSK3β

The binding modes of 42 oxadiazole derivates inside glycogen synthase kinase 3 beta (GSK3β were determined using docking experiments; thus, the preferred active conformations of these inhibitors are proposed. We found that these compounds adopt a scorpion-shaped conformation and they accept a hydrogen bond (HB) from the residue Val135 of the GSK3β ATP-binding site hinge region. In addition, quantitative structure-activity relationship (QSAR) models were constructed to explain the trend of the GSK3β inhibitory activities for the studied compounds. In a first approach, three-dimensional (3D) vectors were calculated using docking conformations and, by using multiple-linear regression, we assessed that GETAWAY vectors were able to describe the reported biological activities. In other QSAR approach, SMILES-based optimal descriptors were calculated. The best model included three-SMILES elements SSSβ leading to the identification of key molecular features that contribute to a high GSK3β inhibitory activity.

Extra precision docking, free energy calculation and molecular dynamics simulation studies of CDK2 inhibitors

Molecular docking, free energy calculation and molecular dynamics (MD) simulation studies have been performed, to explore the putative binding modes of 3,5-diaminoindazoles, imidazo(1,2-b)pyridazines and triazolo(1,5-a) pyridazines series of Cyclin-dependent kinase (CDK2) inhibitors. To evaluate the effectiveness of docking protocol in flexible docking, we have selected crystallographic bound compound to validate our docking procedure as evident from root mean square deviations (RMSDs). We found different binding sites namely catalytic, inhibitory phosphorylation, cyclin binding and CKS-binding site of the CDK2 contributing towards the binding of these compounds. Moreover, correlation between free energy of binding and biological activity yielded a statistically significant correlation coefficient. Finally, three representative protein-ligand complexes were subjected to molecular dynamics simulation to determine the stability of the predicted conformations. The low value of the RMSDs between the initial complex structure and the energy minimized final average complex structure suggests that the derived docked complexes are close to equilibrium. We suggest that the phenylacetyl type of substituents and cyclohexyl moiety make the favorable interactions with a number of residues in the active site, and show better inhibitory activity to improve the pharmacokinetic profile of compounds against CDK2. The structure-based drug design strategy described in this study will be highly useful for the development of new inhibitors with high potency and selectivity.

Investigation of the differences in activity between hydroxycycloalkyl N1 substituted pyrazole derivatives as inhibitors of B-Raf kinase by using docking, molecular dynamics, QM/MM, and fragment-based de novo design: study of binding mode of diastereomer compounds

N1 substituted pyrazole derivatives show diverse B-Raf kinase inhibitory activities when different hydroxy-substituted cycloalkyl groups are placed at this position. Docking, molecular dynamics (MD) simulations, and hybrid calculation methods (Quantum Mechanics/Molecular Mechanics (QM/MM)) were performed on the complexes, in order to explain these differences. Docking of the inhibitors showed the same orientation that X-ray crystal structure of the analogous (1E)-5-[1-(4-piperidinyl)-3-(4-pyridinyl)-1H-pyrazol-4-yl]-2,3-dihydro-1H-inden-1-one oxime. MD simulations of the most active diastereomer compounds containing cis- and trans-3-hydroxycyclohexyl substituents showed stable interactions with residue Ile463 at the entrance of the B-Raf active site. On the other hand, the less active diastereomer compounds containing cis- and trans-2-hydroxycyclopentyl substituents showed interactions with inner residues Asn580 and Ser465. We found that the differences in activity can be explained by considering the dynamic interactions between the inhibitors and their surrounding residues within the B-Raf binding site. We also explained the activity trend by using a testing scoring function derived from more reliable QM/MM calculations. In addition, we search for new inhibitors from a virtual screening carried out by fragment-based de novo design. We generated a set of approximately 200 virtual compounds, which interact with Ile463 and fulfill druglikeness properties according to Lipinski, Veber, and Ghose rules.

Study of differences in the VEGFR2 inhibitory activities between semaxanib and SU5205 using 3D-QSAR, docking, and molecular dynamics simulations

Semaxanib (SU5416) and 3-[4'-fluorobenzylidene]indolin-2-one (SU5205) are structurally similar drugs that are able to inhibit vascular endothelial growth factor receptor-2 (VEGFR2), but the former is 87 times more effective than the latter. Previously, SU5205 was used as a radiolabelled inhibitor (as surrogate for SU5416) and a radiotracer for positron emission tomography (PET) imaging, but the compound exhibited poor stability and only a moderate IC(50) toward VEGFR2. In the current work, the relationship between the structure and activity of these drugs as VEGFR2 inhibitors was studied using 3D-QSAR, docking and molecular dynamics (MD) simulations. First, comparative molecular field analysis (CoMFA) was performed using 48 2-indolinone derivatives and their VEGFR2 inhibitory activities. The best CoMFA model was carried out over a training set including 40 compounds, and it included steric and electrostatic fields. In addition, this model gave satisfactory cross-validation results and adequately predicted 8 compounds contained in the test set. The plots of the CoMFA fields could explain the structural differences between semaxanib and SU5205. Docking and molecular dynamics simulations showed that both molecules have the same orientation and dynamics inside the VEGFR2 active site. However, the hydrophobic pocket of VEGFR2 was more exposed to the solvent media when it was complexed with SU5205. An energetic analysis, including Embrace and MM-GBSA calculations, revealed that the potency of ligand binding is governed by van der Waals contacts.

Binding studies and quantitative structure-activity relationship of 3-amino-1H-indazoles as inhibitors of GSK3β

Docking of 3-amino-1H-indazoles complexed with glycogen synthase kinase 3 beta (GSK3β) was performed to gain insight into the structural requirements and preferred conformations of these inhibitors. The study was conducted on a selected set of 57 compounds with variation in structure and activity. We found that the most active compounds established three hydrogen bonds with the residues of the hinge region of GSK3β, but some of the less active compounds have other binding modes. In addition, models able to predict GSK3β inhibitory activities (IC(50) ) of the studied compounds were obtained by 3D-QSAR methods CoMFA and CoMSIA. Ligand-based and receptor-guided alignment methods were utilized. Adequate R(2) and Q(2) values were obtained by each method, although some striking differences existed between the obtained contour maps. Each of the predictive models exhibited a similar ability to predict the activity of a test set. The application of docking and quantitative structure-activity relationship together allowed conclusions to be drawn for the choice of suitable GSK3β inhibitors.

Docking and quantitative structure-activity relationship studies for 3-fluoro-4-(pyrrolo[2,1-f][1,2,4]triazin-4-yloxy)aniline, 3-fluoro-4-(1H-pyrrolo[2,3-b]pyridin-4-yloxy)aniline, and 4-(4-amino-2-fluorophenoxy)-2-pyridinylamine derivatives as c-Met kinase inhibitors

We have performed docking of 3-fluoro-4-(pyrrolo[2,1-f][1,2,4]triazin-4-yloxy)aniline (FPTA), 3-fluoro-4-(1H-pyrrolo[2,3-b]pyridin-4-yloxy)aniline (FPPA), and 4-(4-amino-2-fluorophenoxy)-2-pyridinylamine (AFPP) derivatives complexed with c-Met kinase to study the orientations and preferred active conformations of these inhibitors. The study was conducted on a selected set of 103 compounds with variations both in structure and activity. Docking helped to analyze the molecular features which contribute to a high inhibitory activity for the studied compounds. In addition, the predicted biological activities of the c-Met kinase inhibitors, measured as IC(50) values were obtained by using quantitative structure-activity relationship (QSAR) methods: Comparative molecular similarity analysis (CoMSIA) and multiple linear regression (MLR) with topological vectors. The best CoMSIA model included steric, electrostatic, hydrophobic, and hydrogen bond-donor fields; furthermore, we found a predictive model containing 2D-autocorrelation descriptors, GETAWAY descriptors (GETAWAY: Geometry, Topology and Atom-Weight AssemblY), fragment-based polar surface area (PSA), and MlogP. The statistical parameters: cross-validate correlation coefficient and the fitted correlation coefficient, validated the quality of the obtained predictive models for 76 compounds. Additionally, these models predicted adequately 25 compounds that were not included in the training set.

Computational study on the interaction of N1 substituted pyrazole derivatives with B-raf kinase: an unusual water wire hydrogen-bond network and novel interactions at the entrance of the active site

Docking and molecular dynamics (MD) simulations of N1 substituted pyrazole derivatives complexed with B-Raf kinase were performed to gain insight into the structural and energetic preferences of these inhibitors. First, a comparative study of fully automated docking programs AutoDock, ICM, GLIDE, and Surflex-Dock in closely approximating the X-ray crystal structure of the inhibitor (1E)-5-[1-(4-piperidinyl)-3-(4-pyridinyl)-1H-pyrazol-4-yl]-2,3-dihydro-1H-inden-1-one oxime was performed. Afterward, the dynamics of the above-mentioned compound and the less active analogous compounds with 1-methyl-4-piperidinyl and tetrahydro-2H-pyran-4-yl groups at position N1 of pyrazole ring inside the B-Raf active site were analyzed by MD simulations. We found that the most active compound has stable interactions with residues Ile463 and His539 at the entrance of the B-Raf active site. Those interactions were in very good agreement with more reliable quantum mechanics/molecular mechanics calculations performed on the torsional angle phi between the pyrazole ring and the substituents at position N1. In addition, we identified a water wire connecting N2 of the pyrazole ring, Cys532, and Ser536, which is composed of three water molecules for the most active compound. We found some differences in the water wire hydrogen-bond network formed by less active compounds. We suggest that the differences between these structural features are responsible for the differences in activity among the studied compounds.

QMOD: physically meaningful QSAR

Computational methods for predicting ligand affinity where no protein structure is known generally take the form of regression analysis based on molecular features that have only a tangential relationship to a protein/ligand binding event. Such methods have utility in retrospective rationalization of activity patterns of substituents on a common scaffold, but are limited when either multiple scaffolds are present or when ligand alignment varies significantly based on structural changes. In addition, such methods generally assume independence and additivity of effect from scaffold substituents. Collectively, these non-physical modeling assumptions sharply limit the utility of widely used QSAR approaches for prospective prediction of ligand activity. The recently introduced Surflex-QMOD approach, by virtue of constructing physical models of binding sites, comes closer to a modeling approach that is congruent with protein ligand binding events. A set of congeneric CDK2 inhibitors showed that induced binding pockets can be quite congruent with the enzyme's active site but that model predictivity within a chemical series does not necessarily depend on congruence. Muscarinic antagonists were used to show that the QMOD approach is capable of making accurate predictions in cases where highly non-additive structure activity effects exist. The QMOD method offers a means to go beyond non-causative correlations in QSAR analysis.

The assessment of density functionals for DNA–protein stacked and T-shaped complexes

The present work uses 129 nucleobase – amino acid CCSD(T)/CBS stacking and T-shaped interaction energies as reference data to test the ability of various density functionals with double-zeta quality basis sets, as well as some semi-empirical and molecular mechanics methods, to accurately describe noncovalent DNA–protein π–π and π+–π interactions. The goal of this work is to identify methods that can be used in hybrid approaches (QM/MM, ONIOM) for large-scale modeling of enzymatic systems involving active-site (substrate) π–π contacts. Our results indicate that AMBER is a more appropriate choice for the lower-level method in hybrid techniques than popular semi-empirical methods (AM1, PM3), and suggest that AMBER accurately describes the π–π interactions found throughout DNA–protein complexes. The M06–2X and PBE-D density functionals were found to provide very promising descriptions of the 129 nucleobase – amino acid interaction energies, which suggests that these may be the most suitable methods for describing high-level regions. Therefore, M06–2X and PBE-D with both the 6–31G(d) and 6–31+G(d,p) basis sets were further examined through potential-energy surface scans to better understand how these techniques describe DNA–protein π–π interactions in both minimum and nonminimum regions of the potential-energy surfaces, which is critical information when modeling enzymatic reaction pathways. Our results suggest that studies of stacked nucleobase – amino acid systems should implement the PBE-D/6–31+G(d,p) method. However, if T-shaped contacts are involved and (or) smaller basis sets must be considered due to limitations in computational resources, then M06–2X/6–31G(d) provides an overall excellent description of both nucleobase – amino acid stacking and T-shaped interactions for a range of DNA–protein π–π and π+–π interactions.

Computational study of the interactions between guanine derivatives and cyclin-dependent kinase 2 (CDK2) by CoMFA and QM/MM

Comparative molecular field analysis (CoMFA) and QM/MM hybrid calculations were performed on 9H-purine derivatives as CDK2 inhibitors. CoMFA was carried out to describe the activities of 78 analogues. The models were applied to a training set including 64 compounds. The best CoMFA model included steric and electrostatic fields, had a good Q(2) value of 0.845, and adequately predicted the compounds contained in the test set. Furthermore, plots of the steric CoMFA field allowed conclusions to be drawn for the choice of suitable inhibitors. In addition, the dynamical behavior of compounds with 4-(aminosulfonyl)phenyl, 4-[(methylamino)sulfonyl]phenyl, 4-[(dimethylamino)sulfonyl]phenyl, and [3-methoxy-4-(aminosulfonyl)]phenyl groups at position 2 of the 9H-purine scaffold inside the CDK2 active site were analyzed by QM/MM calculations. The interactions of these compounds with residues Lys89, Asp86, and Ile10 were characterized.