Small molecule recognition of c-Src via the Imatinib-binding conformation

The cancer drug, Imatinib, is a selective Abl kinase inhibitor that does not inhibit the closely related kinase c-Src. This one drug and its ability to selectively inhibit Abl over c-Src has been a guiding principle in virtually all kinase drug discovery efforts in the last 15 years. A prominent hypothesis explaining the selectivity of Imatinib is that Abl has an intrinsic ability to adopt an inactive conformation (termed DFG-out), whereas c-Src appears to pay a high intrinsic energetic penalty for adopting this conformation, effectively excluding Imatinib from its ATP pocket. This explanation of the difference in binding affinity of Imatinib for Abl versus c-Src makes the striking prediction that it would not be possible to design an inhibitor that binds to the DFG-out conformation of c-Src with high affinity. We report the discovery of a series of such inhibitors. We use structure-activity relationships and X-ray crystallography to confirm our findings. These studies suggest that small molecules are capable of inducing the generally unfavorable DFG-out conformation in c-Src. Structural comparison between c-Src in complex with these inhibitors allows us to speculate on the differential selectivity of Imatinib for c-Src and Abl.     

The different flexibility of c-Src and c-Abl kinases regulates the accessibility of a druggable inactive conformation

c-Src and c-Abl are two closely related protein kinases that constitute important anticancer targets. Despite their high sequence identity, they show different sensitivities to the anticancer drug imatinib, which binds specifically to a particular inactive conformation in which the Asp of the conserved DFG motif points outward (DFG-out). We have analyzed the DFG conformational transition of the two kinases using massive molecular dynamics simulations, free energy calculations, and isothermal titration calorimetry. On the basis of the reconstruction of the free energy surfaces for the DFG-in to DFG-out conformational changes of c-Src and c-Abl, we propose that the different flexibility of the two kinases results in a different stability of the DFG-out conformation and might be the main determinant of imatinib selectivity.     

Molecular dynamics simulation reveals structural and thermodynamic features of kinase activation by cancer mutations within the epidermal growth factor receptor

The epidermal growth factor receptor (EGFR) is a major target for drugs in treating lung carcinoma as it promotes cell growth and tumor progression. Structural studies have demonstrated that EGFR exists in an equilibrium between catalytically active and inactive forms, and dramatic conformational transitions occur during its activation. It is known that EGFR mutations promote such conformational changes that affect its activation and drug efficacy. The most common point mutation in lung cancer patients is a leucine to arginine substitution at amino acid 834 (L834R). In a recent article, we have studied changes in drug binding affinities due to cancer mutations of EGFR using ensemble molecular dynamics (MD) simulations. Here, we address an enhanced activation mechanism thought to be associated with this mutation. Using extended timescale MD simulations, the structural and energetic properties are studied for both active and inactive conformations of EGFR. The thermodynamic stabilities of these two conformations are characterized by free energy landscapes estimated from molecular mechanics/Poisson-Boltzmann solvent area calculations. Our study reveals that the L834R mutation introduces conformational changes in both states, adjusting the relative stabilities of active and inactive conformations and hence the activation of the EGFR kinase.     

Pharmacophore Modeling and in Silico Screening Studies to Design Potential KDR Kinase Inhibitors

A novel ligand‐based pharmacophore model for KDR kinase was generated on the basis of chemical features of 30 KDR kinase inhibitors. This pharmacophore model consists of one hydrogen‐bond acceptor, one hydrogen‐bond donor and two hydrophobic groups. Several methods have been used to validate the model, suggesting that it can serve as a reliable tool for virtual screening to facilitate the discovery of novel KDR inhibitors. The model was then used as database search query from the National Cancer Institute (NCI) database for the rational design to identify new hit compound.     

Molecular dynamics simulation, free energy calculation and structure-based 3D-QSAR studies of B-RAF kinase inhibitors

(V600E)B-RAF kinase is the most frequent onco-genic protein kinase mutation in melanoma and is a promising target to treat malignant melanoma. In this work, a molecular modeling study combining QM-polarized ligand docking, molecular dynamics, free energy calculation, and three-dimensional quantitative structure-activity relationships (3D-QSAR) was performed on a series of pyridoimidazolone compounds as the inhibitors of (V600E)B-RAF kinase to understand the binding mode between the inhibitors and (V600E)B-RAF kinase and the structural requirement for the inhibiting activity. 3D-QSAR models, including CoMFA and CoMSIA, were developed from the conformations obtained by QM-polarized ligand docking strategy. The obtained models have a good predictive ability in both internal and external validation. Furthermore, molecular dynamics simulation and free energy calculations were employed to determine the detailed binding process and to compare the binding mode of the inhibitors with different activities. The binding free energies calculated by MM/PBSA gave a good correlation with the experimental biological activity. The decomposition of free energies by MM/GBSA indicates the van der Waals interaction is the major driving force for the interaction between the inhibitors and (V600E)B-RAF kinase. The hydrogen bond interactions between the inhibitors with Glu501 and Asp594 of the (V600E)B-RAF kinase help to stabilize the DFG-out conformation. The results from this study can provide some insights into the development of novel potent (V600E)B-RAF kinase inhibitors.     

Theoretical studies on the conformational change of adenosine kinase induced by inhibitors

Adenosine kinase (AK) is a two‐domain protein that catalyzes the phosphorylation of adenosine to adenosine monophosphate. Inhibitors of AK could increase adenosine to levels that activate nearby adenosine receptors and produce a wide variety of therapeutically beneficial activities. To get insight into the interaction mechanism between inhibitors and AK, we chose two kinds of novel inhibitors, alkynylpyrimidine inhibitor (APy) and aryl‐nucleoside inhibitor (AN), and used docking and molecular dynamics simulation methods to study the conformational changes of human AK on binding inhibitors. The calculation results revealed that both APy and AN could induce conformational changes of AK and stabilize AK at different semiopen conformations. On binding APy, the small lid‐domain rotated 14°, and the binding pocket rearranged after MD simulation. But in AK‐AN complex, the rotation of small domain is 22°, and the sugar ring of AN is mobile in the binding pocket. Further docking calculations on APy analogues indicate that the semiopen conformation could well explain the SAR of AK inhibitors. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011     

Approaches to solving the rigid receptor problem by identifying a minimal set of flexible residues during ligand docking

BACKGROUND: Using fixed receptor sites derived from high-resolution crystal structures in structure-based drug design does not properly account for ligand-induced enzyme conformational change and imparts a bias into the discovery and design of novel ligands. We sought to facilitate the design of improved drug leads by defining residues most likely to change conformation, and then defining a minimal manifold of possible conformations of a target site for drug design based on a small number of identified flexible residues. RESULTS: The crystal structure of thymidylate synthase from an important pathogenic target Pneumocystis carinii (PcTS) bound to its substrate and the inhibitor, BW1843U89, is reported here and reveals a new conformation with respect to the structure of PcTS bound to substrate and the more conventional antifolate inhibitor, CB3717. We developed an algorithm for determining which residues provide 'soft spots' in the protein, regions where conformational adaptation suggests possible modifications for a drug lead that may yield higher affinity. Remodeling the active site of thymidylate synthase with new conformations for only three residues that were identified with this algorithm yields scores for ligands that are compatible with experimental kinetic data. CONCLUSIONS: Based on the examination of many protein/ligand complexes, we develop an algorithm (SOFTSPOTS) for identifying regions of a protein target that are more likely to accommodate plastically to regions of a drug molecule. Using these indicators we develop a second algorithm (PLASTIC) that provides a minimal manifold of possible conformations of a protein target for drug design, reducing the bias in structure-based drug design imparted by structures of enzymes co-crystallized with inhibitors.     

Molecular dynamics simulation and free energy calculation studies of the binding mechanism of allosteric inhibitors with p38α MAP kinase

p38 MAP kinase is a promising target for anti-inflammatory treatment. The classical kinase inhibitors imatinib and sorafenib as well as BI-1 and BIRB-796 were reported to bind in the DFG-out form of human p38α, known as type II or allosteric kinase inhibitors. Although DFG-out conformation has attracted great interest in the design of type II kinase inhibitors, the structural requirements for binding and mechanism of stabilization of DFG-out conformation remain unclear. As allosteric inhibition is important to the selectivity of kinase inhibitor, herein the binding modes of imatinib, sorafenib, BI-1 and BIRB-796 to p38α were investigated by molecular dynamics simulation. Binding free energies were calculated by molecular mechanics/Poisson-Boltzmann surface area method. The predicted binding affinities can give a good explanation of the activity difference of the studied inhibitors. Furthermore, binding free energies decomposition analysis and further structural analysis indicate that the dominating effect of van der Waals interaction drives the binding process, and key residues, such as Lys53, Gly71, Leu75, Ile84, Thr106, Met109, Leu167, Asp168, and Phe169, play important roles by forming hydrogen bond, salt bridge, and hydrophobic interactions with the DFG-out conformation of p38α. Finally, we also conducted a detailed analysis of BI-1, imatinib, and sorafenib binding to p38α in comparison with BIRB-796 exploited for gaining potency as well as selectivity of p38 inhibitors. These results are expected to be useful for future rational design of novel type II p38 inhibitors.     

Sequence, structure, and active site analyses of p38 MAP kinase: exploiting DFG-out conformation as a strategy to design new type II leads

A new knowledge, structure, and sequence based strategy involving the effective exploitation of the DFG-out conformation is delineated. A comprehensive analysis of the structure, sequence, cocrystals, and active sites of p38 MAP kinase crystal structures present in Protein Data Bank (PDB) and the FDA approved MAP kinase drugs has been done, and the information is used for the design of type II leads. The 98 crystal structures, 138 cocrystals, and 31 FDA drugs comprise of 7 different sequences of 2 organisms viz., Homo sapiens and Mus musculus differing in sequence length, constituting both homo- and heterochains. Multiple sequence alignment with ClustalW showed >95% sequence similarity with highly conserved domains and a high propensity for mutations in the activation loop. The bound ligands were extracted, and their interactions with DFG in and out conformations were studied. These cocrystals and FDA drugs were fragmented on the basis of their binding interactions and their affinity to ATP and allosteric sites. The fragment library thus generated contains 106 fragments with overlapping drug fragments. A blue print constituting three main parts viz., head (ATP region), linker (DFG region), and tail (allosteric region) has thus been formulated and used to design 64 type II p38 MAP kinase inhibitors. The above strategy has been employed to design potent type II p38 MAP kinase inhibitors, which are shown to be very promising.     

Approximating protein flexibility through dynamic pharmacophore models: application to fatty acid amide hydrolase (FAAH)

A structure-based drug discovery method is described that incorporates target flexibility through the use of an ensemble of protein conformations. The approach was applied to fatty acid amide hydrolase (FAAH), a key deactivating enzyme in the endocannabinoid system. The resultant dynamic pharmacophore models are rapidly able to identify known FAAH inhibitors over drug-like decoys. Different sources of FAAH conformational ensembles were explored, with both snapshots from molecular dynamics simulations and a group of X-ray structures performing well. Results were compared to those from docking and pharmacophore models generated from a single X-ray structure. Increasing conformational sampling consistently improved the pharmacophore models, emphasizing the importance of incorporating target flexibility in structure-based drug design.     

杯[4]芳烃的构象间转换机理的CNDO/2法研究

利用CNDO／2近似方法对25，26，27，28－四羟基杯［4］芳烃的四种不同构象的平衡几何构型以及所有可能发生的构象间转换的势垒能量进行了计算．在此基础上提出了合理的杯［4］芳烃的构象间转换机理，指出部分锥形构象是必经途径．利用该机理可以圆满地解释某些实验现象．     

de novo design and synthesis of N-benzylanilines as new candidates for VEGFR tyrosine kinase inhibitors

N-Benzylanilines were designed and synthesized as vascular endothelial growth factor (VEGF)-2 inhibitors using de novo drug design systems based on the X-ray structure of VEGFR-2 kinase domain. Among compounds synthesized, compound showed the most potent inhibitory activity toward VEGFR-2 (KDR) tyrosine kinase and its IC(50) value was 0.57 microM.     

Novel Big Data-Driven Machine Learning Models for Drug Discovery Application

Most contemporary drug discovery projects start with a ‘hit discovery’ phase where small chemicals are identified that have the capacity to interact, in a chemical sense, with a protein target involved in a given disease. To assist and accelerate this initial drug discovery process, ’virtual docking calculations’ are routinely performed, where computational models of proteins and computational models of small chemicals are evaluated for their capacities to bind together. In cutting-edge, contemporary implementations of this process, several conformations of protein targets are independently assayed in parallel ‘ensemble docking’ calculations. Some of these protein conformations, a minority of them, will be capable of binding many chemicals, while other protein conformations, the majority of them, will not be able to do so. This fact that only some of the conformations accessible to a protein will be ’selected’ by chemicals is known as ’conformational selection’ process in biology. This work describes a machine learning approach to characterize and identify the properties of protein conformations that will be selected (i.e., bind to) chemicals, and classified as potential binding drug candidates, unlike the remaining non-binding drug candidate protein conformations. This work also addresses the class imbalance problem through advanced machine learning techniques that maximize the prediction rate of potential protein molecular conformations for the test case proteins ADORA2A (Adenosine A2a Receptor) and OPRK1 (Opioid Receptor Kappa 1), and subsequently reduces the failure rates and hastens the drug discovery process.     

Dynamic Equilibrium of the Aurora A Kinase Activation Loop Revealed by Single‐Molecule Spectroscopy

The conformation of the activation loop (T‐loop) of protein kinases underlies enzymatic activity and influences the binding of small‐molecule inhibitors. By using single‐molecule fluorescence spectroscopy, we have determined that phosphorylated Aurora A kinase is in dynamic equilibrium between a DFG‐in‐like active T‐loop conformation and a DFG‐out‐like inactive conformation, and have measured the rate constants of interconversion. Addition of the Aurora A activating protein TPX2 shifts the equilibrium towards an active T‐loop conformation whereas addition of the inhibitors MLN8054 and CD532 favors an inactive T‐loop. We show that Aurora A binds TPX2 and MLN8054 simultaneously and provide a new model for kinase conformational behavior. Our approach will enable conformation‐specific effects to be integrated into inhibitor discovery across the kinome, and we outline some immediate consequences for structure‐based drug discovery.     

Novel strategy for three-dimensional fragment-based lead discovery

Fragment-based drug design (FBDD) is considered a promising approach in lead discovery. However, for a practical application of this approach, problems remain to be solved. Hence, a novel practical strategy for three-dimensional lead discovery is presented in this work. Diverse fragments with spatial positions and orientations retained in separately adjacent regions were generated by deconstructing well-aligned known inhibitors in the same target active site. These three-dimensional fragments retained their original binding modes in the process of new molecule construction by fragment linking and merging. Root-mean-square deviation (rmsd) values were used to evaluate the conformational changes of the component fragments in the final compounds and to identify the potential leads as the main criteria. Furthermore, the successful validation of our strategy is presented on the basis of two relevant tumor targets (CDK2 and c-Met), demonstrating the potential of our strategy to facilitate lead discovery against some drug targets.     

Synthesis of polysubstituted 4-fluoroquinolinones

[reaction: see text] A convenient one-pot synthesis of 4-fluoroquinolinones that are active against KDR kinase is described. The mechanism of the reaction is believed to involve the formation of a quinone methide intermediate.     

Dynamics of proton exchange in a model phosphonic acid‐functionalized polymer

The dynamics and mechanism of proton exchange in phosphonic acid‐functionalized polymers were studied using poly(vinyl‐phosphonic acid) (PVPA) as a model system along with quantum chemical calculations and Born–Oppenheimer molecular dynamics (BOMD) simulations at the B3LYP/TZVP level as model calculations. This theoretical study began with searching for the smallest, most active polymer segments and their intermediate conformations which could be involved in the local proton‐exchange process. The B3LYP/TZVP results confirmed that a low local dielectric environment and excess proton conditions are required to generate the intermediate conformations, and the shapes of the potential energy curves of the proton exchange between the two phosphonic acid functional groups are sensitive to the local conformational changes. In contrast, a high local dielectric environment increases the energy barriers, thereby preventing the proton from returning to the original functional group. Based on the static results, a mechanism for the proton exchange between the two functional groups involving fluctuations in the local dielectric environment and a local conformational change was proposed. The BOMD results confirmed the proposed mechanism by showing that the activation energies for the proton exchange in the hydrogen bond between two immobilized phosphonic acid moieties, obtained from the exponential relaxation behaviors of the envelopes of the velocity autocorrelation functions and the ¹H Nuclear Magnetic Resonance (NMR) line‐shape analyses, are too low to be the rate‐determining process. Instead, coupled librational motion in the backbone which leads to the interconversion between the two intermediate conformations possesses higher activation energy, and therefore represents one of the most important rate‐determining processes. These findings suggested that the rate of the proton exchange in the model phosphonic acid‐functionalized polymer is determined by the polymer mobility which, in this case, is the large‐amplitude librational motion of the vinyl backbone. © 2015 Wiley Periodicals, Inc.     

Molecular Modeling Studies of Vascular Endothelial Growth Factor Receptor Tyrosine Kinase Inhibitors Combining Molecular Docking and 3D-QSAR Methods

The vascular endothelial growth factor (VEGF) and its receptor tyrosine kinases VEGFR-2 or kinase insertdomain receptor (KDR) have emerged as attractive targets for the design of novel anticancer agents. In the present work, molecular docking method combined with three dimensional quantitative structure-activity relationships (comparative molecular field analysis (CoMFA) and comparative molecular similarity indice analysis (CoMSIA)) to analyze the possible interactions between KDR and those derivatives which acted as selective inhibitors. The CoMFA and CoMSIA models gave a cross-validated coefficient Q2 of 0.713 and 0.549, non-cross-validated R2 values of 0.974 and 0.878, and predicted R2 values of 0.966 and 0.823, respectively. The 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. The information obtained from 3D-QSAR and docking studies were very helpful to design novel selective inhibitors of KDR with desired activity and good chemical property.     

A fast and efficient method to generate biologically relevant conformations

Summary Mutual binding between a ligand of low molecular weight and its macromolecular receptor demands structural complementarity of both species at the recognition site. To predict binding properties of new molecules before synthesis, information about possible conformations of drug molecules at the active site is required, especially if the 3D structure of the receptor is not known. The statistical analysis of small-molecule crystal data allows one to elucidate conformational preferences of molecular fragments and accordingly to compile libraries of putative ligand conformations. A comparison of geometries adopted by corresponding fragments in ligands bound to proteins shows similar distributions in conformation space. We have developed an automatic procedure that generates different conformers of a given ligand. The entire molecule is decomposed into its individual ring and open-chain torsional fragments, each used in a variety of favorable conformations. The latter ones are produced according to the library information about conformational preferences. During this building process, an extensive energy ranking is applied. Conformers ranked as energetically favorable are subjected to an optimization in torsion angle space. During minimization, unfavorable van der Waals interactions are removed while keeping the open-chain torsion angles as close as possible to the experimentally most frequently observed values. In order to assess how well the generated conformers map conformation space, a comparison with experimental data has been performed. This comparison gives some confidence in the efficiency and completeness of this approach. For some ligands that had been structurally characterized by protein crystallography, the program was used to generate sets of some 10 to 100 conformers. Among these, geometries are found that fall convincingly close to the conformations actually adopted by these ligands at the binding site.     

Predicting binding energies of CDK6 inhibitors in the hit-to-lead process

The main challenge for the ??hit-to-lead?? stage in the drug discovery process relies on the accuracy of existing docking methods. In fact, accuracy of docking methods depends not only on the scoring function used to rank the poses but also on the ability of the docking method to reproduce the experimental binding mode. At this purpose, the performance of different approximations to properly dock and score compounds with known activity in a narrow range of IC₅₀ values was analyzed. A set of five ATP-competitive CDK6 inhibitors and three receptor conformations for CDK6 were considered for analysis, and three methodologies were used and analyzed in order to include different degrees of receptor flexibility. Thus, a completely rigid receptor is considered when using Glide, while the so-called Induced Fit Docking Protocol accounts for receptor sidechain rearrangements. Finally, force field calculations were also performed in order to consider a completely flexible receptor.