Flexible protein–ligand docking by global energy optimization in internal coordinates

GPCR agonist binding revealed by modeling and crystallography

Despite recent progress in structural coverage of the G-protein-coupled receptor (GPCR) family, high plasticity of these membrane proteins poses additional challenges for crystallographic studies of their complexes with different classes of ligands, especially agonists. The ability to predict computationally the binding of natural and clinically relevant agonists and corresponding changes in the receptor pocket, starting from inactive GPCR structures, is therefore of great interest for understanding GPCR biology and drug action. Comparison of computational models published in 2009 and 2010 with recently determined agonist-bound structures of β-adrenergic and adenosine A(2A) receptors reveals high accuracy of the predicted agonist binding poses (0.8 Å and 1.7 Å respectively) and receptor interactions. In the case of the β(2)AR, energy-based models with limited backbone flexibility have also allowed characterization of side-chain rotations and a finite backbone shift in the pocket region as determinants of full, partial or inverse agonism. Development of accurate models of agonist binding for other GPCRs will be instrumental for functional and pharmacological studies, complementing biochemical and crystallographic techniques.

In search of allosteric modulators of a7-nAChR by solvent density guided virtual screening

Nicotinic acetylcholine receptors (nAChR) are pentameric ligand gated ion channels whose activity can be modulated by endogenous neurotransmitters as well as by synthetic ligands that bind the same or distinct sites from the natural ligand. The subtype of α7 nAChR has been considered as a potenial therapeutic target for Alzheimer's disease, schizophrenia and other neurological and psychiatric disorders. Here we have developed a homology model of α7 nAChR based on two high resolution crystal structures with Brookhaven Protein Data Bank (PDB) codes 2QC1 and 2WN9 for threading on one monomer and then for building a pentamer, respectively. A number of small molecule binding sites are identified using Pocket Finder (J. An, M. Tortov, and R. Abagyan, Molecular & Cellular Proteomics, 4.6, 752-761 (2005)) of Internal Coordinate Mechanics (ICM). Remarkably, these computer-identified sites match perfectly with ordered solvent densities found in the high-resolution crystal structure of α1 nAChR, suggesting that the surface cavities in the α7 nAChR model are likely binding sites of small molecules. A high throughput virtual screening by flexible ligand docking of 5008 small molecule compounds was performed at three potential allosteric modulator (AM) binding sites of α7 nAChR using Molsoft ICM software (R. Abagyan, M. Tortov and D. Kuznetsov, J Comput Chem 15, 488-506, (1994)). Some experimentally verified allosteric modulators of α7 like CCMI comp-6, LY 7082101, 5-HI, TQS, PNU-120596, genistein, and NS-1738 ranked among top 100 compounds, while the rest of the compounds in the list could guide further search for new allosteric modulators.

Software and resources for computational medicinal chemistry

Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools.

AADS--an automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors

We report here a robust automated active site detection, docking, and scoring (AADS) protocol for proteins with known structures. The active site finder identifies all cavities in a protein and scores them based on the physicochemical properties of functional groups lining the cavities in the protein. The accuracy realized on 620 proteins with sizes ranging from 100 to 600 amino acids with known drug active sites is 100% when the top ten cavity points are considered. These top ten cavity points identified are then submitted for an automated docking of an input ligand/candidate molecule. The docking protocol uses an all atom energy based Monte Carlo method. Eight low energy docked structures corresponding to different locations and orientations of the candidate molecule are stored at each cavity point giving 80 docked structures overall which are then ranked using an effective free energy function and top five structures are selected. The predicted structure and energetics of the complexes agree quite well with experiment when tested on a data set of 170 protein-ligand complexes with known structures and binding affinities. The AADS methodology is implemented on an 80 processor cluster and presented as a freely accessible, easy to use tool at http://www.scfbio-iitd.res.in/dock/ActiveSite_new.jsp .

Toward a robust search method for the protein-drug docking problem

Predicting the binding mode(s) of a drug molecule to a target receptor is pivotal in structure-based rational drug design. In contrast to most approaches to solve this problem, the idea in this paper is to analyze the search problem from a computational perspective. By building on top of an existing docking tool, new methods are proposed and relevant computational results are proven. These methods and results are applicable for other place-and-join frameworks as well. A fast approximation scheme for the docking of rigid fragments is described that guarantees certain geometric approximation factors. It is also demonstrated that this can be translated into an energy approximation for simple scoring functions. A polynomial time algorithm is developed for the matching phase of the docked rigid fragments. It is demonstrated that the generic matching problem is NP-hard. At the same time, the optimality of the proposed algorithm is proven under certain scoring function conditions. The matching results are also applicable for some of the fragment-based de novo design methods. On the practical side, the proposed method is tested on 829 complexes from the PDB. The results show that the closest predicted pose to the native structure has the average RMS deviation of 1.06 A.

Structure of the human histamine H1 receptor complex with doxepin

The biogenic amine histamine is an important pharmacological mediator involved in pathophysiological processes such as allergies and inflammations. Histamine H(1) receptor (H(1)R) antagonists are very effective drugs alleviating the symptoms of allergic reactions. Here we show the crystal structure of the H(1)R complex with doxepin, a first-generation H(1)R antagonist. Doxepin sits deep in the ligand-binding pocket and directly interacts with Trp 428(6.48), a highly conserved key residue in G-protein-coupled-receptor activation. This well-conserved pocket with mostly hydrophobic nature contributes to the low selectivity of the first-generation compounds. The pocket is associated with an anion-binding region occupied by a phosphate ion. Docking of various second-generation H(1)R antagonists reveals that the unique carboxyl group present in this class of compounds interacts with Lys 191(5.39) and/or Lys 179(ECL2), both of which form part of the anion-binding region. This region is not conserved in other aminergic receptors, demonstrating how minor differences in receptors lead to pronounced selectivity differences with small molecules. Our study sheds light on the molecular basis of H(1)R antagonist specificity against H(1)R.

Triazole-linked reduced amide isosteres: an approach for the fragment-based drug discovery of anti-Alzheimer's BACE1 inhibitors

In the course of a β-site APP-cleaving enzyme 1 (BACE1) inhibitor discovery project an in situ synthesis/screening protocol was employed to prepare 120 triazole-linked reduced amide isostere inhibitors. Among these compounds, four showed modest (single digit micromolar) BACE1 inhibition. Our ligand design was based on a potent reduced amide isostere 1, wherein the P(2) amide moiety was replaced with an anti-1,2,3-triazole unit. Unfortunately, this replacement resulted in a 1000-fold decrease in potency. Docking studies of triazole-linked reduced amide isostere A3Z10 and potent oxadiazole-linked tertiary carbinamine 2a with BACE1 suggests that the docking poses of A3Z10 and 2a in the active sites are quite similar, with one exception. In the docked structures the placement of the protonated amine that engages D228 differs considerably between 2a and A3Z10. This difference could account for the lower BACE1 inhibition potency of A3Z10 and related compounds relative to 2a.

Biological and structural characterization of the Mycobacterium smegmatis nitroreductase NfnB, and its role in benzothiazinone resistance

Tuberculosis is still a leading cause of death in developing countries, for which there is an urgent need for new pharmacological agents. The synthesis of the novel antimycobacterial drug class of benzothiazinones (BTZs) and the identification of their cellular target as DprE1 (Rv3790), a component of the decaprenylphosphoryl-β-d-ribose 2'-epimerase complex, have been reported recently. Here, we describe the identification and characterization of a novel resistance mechanism to BTZ in Mycobacterium smegmatis. The overexpression of the nitroreductase NfnB leads to the inactivation of the drug by reduction of a critical nitro-group to an amino-group. The direct involvement of NfnB in the inactivation of the lead compound BTZ043 was demonstrated by enzymology, microbiological assays and gene knockout experiments. We also report the crystal structure of NfnB in complex with the essential cofactor flavin mononucleotide, and show that a common amino acid stretch between NfnB and DprE1 is likely to be essential for the interaction with BTZ. We performed docking analysis of NfnB-BTZ in order to understand their interaction and the mechanism of nitroreduction. Although Mycobacterium tuberculosis seems to lack nitroreductases able to inactivate these drugs, our findings are valuable for the design of new BTZ molecules, which may be more effective in vivo.

Benzophenone-based derivatives: a novel series of potent and selective dual inhibitors of acetylcholinesterase and acetylcholinesterase-induced beta-amyloid aggregation

The leading mechanistic theory of Alzheimer's disease (AD) is the "amyloid hypothesis" which states that the accumulation of the amyloid β protein (Aβ), and its subsequent aggregation into plaques, is responsible for the initiation of a cascade of events resulting in neurodegeneration and dementia. The anti-amyloid disease-modifying approach, based on the decrease in the production of Aβ, gained thus a paramount importance. The aim of this study was the design and synthesis of a new series of acetylcholinesterase inhibitors (AChEIs) endowed with anti-Aβ aggregating capability. These dual binding inhibitors, being able to interact both with the peripheral anionic site (PAS) of AChE and the catalytic subsite, proved to be able to inhibit the AChE-induced Aβ aggregation. Thus, starting from the lead compound 1, an AChEI composed by a benzophenone scaffold and a N,N'-methylbenzylamino group, a substantial modification aimed at targeting the PAS was performed. To this aim, different amino-terminal side chains were incorporated into this main framework, in order to mimic the diethylmethylammonium alkyl moiety of the pure PAS ligand propidium. The synthesized compounds proved to effectively and selectively inhibit AChE. Moreover, compounds 16a-c and 18a,b, with a propoxy and a hexyloxy tether respectively, showed a good activity against the AChE-induced Aβ aggregation. In particular, molecular modeling studies confirmed that compounds carrying the diethylaminopropoxy and the diethylaminohexyloxy side chains (compounds 16a and 19a, respectively) could suitably contact the PAS pocket of the enzyme.

NNScore: a neural-network-based scoring function for the characterization of protein-ligand complexes

As high-throughput biochemical screens are both expensive and labor intensive, researchers in academia and industry are turning increasingly to virtual-screening methodologies. Virtual screening relies on scoring functions to quickly assess ligand potency. Although useful for in silico ligand identification, these scoring functions generally give many false positives and negatives; indeed, a properly trained human being can often assess ligand potency by visual inspection with greater accuracy. Given the success of the human mind at protein−ligand complex characterization, we present here a scoring function based on a neural network, a computational model that attempts to simulate, albeit inadequately, the microscopic organization of the brain. Computer-aided drug design depends on fast and accurate scoring functions to aid in the identification of small-molecule ligands. The scoring function presented here, used either on its own or in conjunction with other more traditional functions, could prove useful in future drug-discovery efforts.

Identification of new batrachotoxin-sensing residues in segment IIIS6 of the sodium channel

Ion permeation through voltage-gated sodium channels is modulated by various drugs and toxins. The atomistic mechanisms of action of many toxins are poorly understood. A steroidal alkaloid batrachotoxin (BTX) causes persistent channel activation by inhibiting inactivation and shifting the voltage dependence of activation to more negative potentials. Traditionally, BTX is considered to bind at the channel-lipid interface and allosterically modulate the ion permeation. However, amino acid residues critical for BTX action are found in the inner helices of all four repeats, suggesting that BTX binds in the pore. In the octapeptide segment IFGSFFTL in IIIS6 of a cockroach sodium channel BgNa(V), besides Ser_3i15 and Leu_3i19, which correspond to known BTX-sensing residues of mammalian sodium channels, we found that Gly_3i14 and Phe_3i16 are critical for BTX action. Using these data along with published data as distance constraints, we docked BTX in the Kv1.2-based homology model of the open BgNa(V) channel. We arrived at a model in which BTX adopts a horseshoe conformation with the horseshoe plane normal to the pore axis. The BTX ammonium group is engaged in cation-π interactions with Phe_3i16 and BTX moieties interact with known BTX-sensing residues in all four repeats. Oxygen atoms at the horseshoe inner surface constitute a transient binding site for permeating cations, whereas the bulky BTX molecule would resist the pore closure, thus causing persistent channel activation. Our study reinforces the concept that steroidal sodium channel agonists bind in the inner pore of sodium channels and elaborates the atomistic mechanism of BTX action.

Development of a new physics-based internal coordinate mechanics force field and its application to protein loop modeling

We report the development of internal coordinate mechanics force field (ICMFF), new force field parameterized using a combination of experimental data for crystals of small molecules and quantum mechanics calculations. The main features of ICMFF include: (a) parameterization for the dielectric constant relevant to the condensed state (ε = 2) instead of vacuum, (b) an improved description of hydrogen-bond interactions using duplicate sets of van der Waals parameters for heavy atom-hydrogen interactions, and (c) improved backbone covalent geometry and energetics achieved using novel backbone torsional potentials and inclusion of the bond angles at the C(α) atoms into the internal variable set. The performance of ICMFF was evaluated through loop modeling simulations for 4-13 residue loops. ICMFF was combined with a solvent-accessible surface area solvation model optimized using a large set of loop decoys. Conformational sampling was carried out using the biased probability Monte Carlo method. Average/median backbone root-mean-square deviations of the lowest energy conformations from the native structures were 0.25/0.21 Å for four residues loops, 0.84/0.46 Å for eight residue loops, and 1.16/0.73 Å for 12 residue loops. To our knowledge, these results are significantly better than or comparable with those reported to date for any loop modeling method that does not take crystal packing into account. Moreover, the accuracy of our method is on par with the best previously reported results obtained considering the crystal environment. We attribute this success to the high accuracy of the new ICM force field achieved by meticulous parameterization, to the optimized solvent model, and the efficiency of the search method.

Organoplatinum(II) complexes with nucleobase motifs as inhibitors of human topoisomerase II catalytic activity

Platinum(II) complexes bearing acetylide ligands containing nucleobase motifs are prepared and their impact on human topoisomerase II (TopoII) is evaluated. Both platinum(II) complexes [Pt(II)(C^N^N)(C≡CCH₂R)] (1a-c) and [Pt(II)(tBu₃terpy)(C≡CCH₂R)](+) (2a-c) (C^N^N=6-phenyl-2,2'-bipyridyl, tBu₃terpy=4,4',4''-tri-tert-butyl-2,2':6',2''-terpyridyl, and R=(a) adenine, (b) thymine, and (c) 2-amino-6-chloropurine) are stable in aqueous solutions for 48 hours at room temperature. The binding constants (K) for the platinum(II) complexes towards calf thymus DNA are in the order of 10⁵ dm³ mol⁻¹ as estimated by using UV/Vis absorption spectroscopy. Of the complexes examined, only complexes 1a-c are found to behave as intercalators. Both complexes 1a-c and 2a-c inhibit TopoII-induced relaxation of supercoiled DNA, while 2c is the most potent TopoII inhibitors among the tested compounds. Inhibition of DNA relaxation is detected at nanomolar concentrations of 2c. All of the platinum(II) complexes are cytotoxic to human cancer cells with IC₅₀ values of 0.5-13.7 μM, while they are less toxic against normal cells CCD-19 Lu.

A natural product-like inhibitor of NEDD8-activating enzyme

The natural product-like 6,6″-biapigenin has been identified as only the second inhibitor of NEDD8-activating enzyme using virtual screening. This compound was active in enzyme and cell-based assays, with potency in the micromolar range.

Preparation and refinement of model protein-ligand complexes

The formation of ligand-protein complexes are critical for the correct functioning of a cell. The prediction of these interactions is important for our understanding of how the cell works and for the development of new drug molecules. Homology modeling is a method for predicting the structure of a protein based on a crystal structure template. Once a model of the protein is complete, a ligand-docking algorithm predicts the ligand-protein model interaction by searching for the best steric and energetically favorable fit. A refinement of the ligand-binding pocket improves the predicted interactions by considering the flexible nature of the ligand-binding pocket. In this chapter, we describe, from first principles, methods to identify and prepare the ligand-binding pocket in a protein model, to dock the ligand, and refine the resulting complex.

Ligand-guided optimization of CXCR4 homology models for virtual screening using a multiple chemotype approach

CXCR4 is a G-protein coupled receptor for CXCL12 that plays an important role in human immunodeficiency virus infection, cancer growth and metastasization, immune cell trafficking and WHIM syndrome. In the absence of an X-ray crystal structure, theoretical modeling of the CXCR4 receptor remains an important tool for structure-function analysis and to guide the discovery of new antagonists with potential clinical use. In this study, the combination of experimental data and molecular modeling approaches allowed the development of optimized ligand-receptor models useful for elucidation of the molecular determinants of small molecule binding and functional antagonism. The ligand-guided homology modeling approach used in this study explicitly re-shaped the CXCR4 binding pocket in order to improve discrimination between known CXCR4 antagonists and random decoys. Refinement based on multiple test-sets with small compounds from single chemotypes provided the best early enrichment performance. These results provide an important tool for structure-based drug design and virtual ligand screening of new CXCR4 antagonists.

Modeling Protein-Ligand Binding by Mining Minima

We present the first application of the mining minima algorithm to protein-small molecule binding. This end-point approach use an empirical force field and implicit solvent models, treats the protein binding-site as fully flexible and estimates free energies as sums over local energy wells. The calculations are found to yield encouraging agreement with experiment for three sets of HIV-1protease inhibitors and a set of phosphodiesterase 10a inhibitors. The contributions of various aspects of the model to its accuracy are examined, and the Poisson-Boltzmann correction is found to be the most critical. Interestingly, the computed changes in configurational entropy upon binding fall roughly along the same entropy-energy correlation previously observed for smaller host-guest systems. Strengths and weaknesses of the method are discussed, as are the prospects for enhancing accuracy and speed.

Applying internal coordinate mechanics to model the interactions between 8R-lipoxygenase and its substrate

Background

Lipoxygenases (LOX) play pivotal roles in the biosynthesis of leukotrienes and other biologically active potent signalling compounds. Developing inhibitors for LOX is of high interest to researchers. Modelling the interactions between LOX and its substrate arachidonic acid is critical for developing LOX specific inhibitors. Currently, there are no LOX-substrate structures. Recently, the structure of a coral LOX, 8R-LOX, which is 41% sequence identical to the human 5-LOX was solved to 1.85Å resolution. This structure provides a foundation for modelling enzyme-substrate interactions.

Methods

In this research, we applied a computational method, Internal Coordinate Mechanics (ICM), to model the interactions between 8R-LOX and its substrate arachidonic acid. Docking arachidonic acid to 8R-LOX was performed. The most favoured docked ligand conformations were retained. We compared the results of our simulation with a proposed model and concluded that the binding pocket identified in this study agrees with the proposed model partially.

Results

The results showed that the conformation of arachidonic acid docked into the ICM-identified docking site has less energy than that docked into the manually defined docking site for pseudo wild type 8R-LOX. The mutation at I805 resulted in no docking pocket found near Fe atom. The energy of the arachidonic acid conformation docked into the manually defined docking site is higher in mutant 8R-LOX than in wild type 8R-LOX. The arachidonic acid conformations are not productive conformations.

Conclusions

We concluded that, for the wild type 8R-LOX, the conformation of arachidonic acid docked into the ICM-identified docking site is more stable than that docked into the manually defined docking site. Mutation affects the structure of the putative active site pocket of 8R-LOX, and leads no docking pockets around the catalytic Fe atom. The docking simulation in a mutant 8R-LOX demonstrated that the structural change due to the mutation impacts the enzyme activity. Further research and analysis is required to obtain the 8R-LOX-substrate model.

Virtual ligand screening of the p300/CBP histone acetyltransferase: identification of a selective small molecule inhibitor

The histone acetyltransferase (HAT) p300/CBP is a transcriptional coactivator implicated in many gene regulatory pathways and protein acetylation events. Although p300 inhibitors have been reported, a potent, selective, and readily available active-site-directed small molecule inhibitor is not yet known. Here we use a structure-based, in silico screening approach to identify a commercially available pyrazolone-containing small molecule p300 HAT inhibitor, C646. C646 is a competitive p300 inhibitor with a K(i) of 400 nM and is selective versus other acetyltransferases. Studies on site-directed p300 HAT mutants and synthetic modifications of C646 confirm the importance of predicted interactions in conferring potency. Inhibition of histone acetylation and cell growth by C646 in cells validate its utility as a pharmacologic probe and suggest that p300/CBP HAT is a worthy anticancer target.

Structure-based design of platinum(II) complexes as c-myc oncogene down-regulators and luminescent probes for G-quadruplex DNA

A series of platinum(II) complexes with tridentate ligands was synthesized and their interactions with G-quadruplex DNA within the c-myc gene promoter were evaluated. Complex 1, which has a flat planar 2,6-bis(benzimidazol-2-yl)pyridine (bzimpy) scaffold, was found to stabilize the c-myc G-quadruplex structure in a cell-free system. An in silico G-quadruplex DNA model has been constructed for structure-based virtual screening to develop new Pt(II)-based complexes with superior inhibitory activities. By using complex 1 as the initial structure for hit-to-lead optimization, bzimpy and related 2,6-bis(pyrazol-3-yl)pyridine (dPzPy) scaffolds containing amine side-chains emerge as the top candidates. Six of the top-scoring complexes were synthesized and their interactions with c-myc G-quadruplex DNA have been investigated. The results revealed that all of the complexes have the ability to stabilize the c-myc G-quadruplex. Complex 3 a ([Pt(II)L2R](+); L2=2,6-bis[1-(3-piperidinepropyl)-1H-enzo[d]imidazol-2-yl]pyridine, R=Cl) displayed the strongest inhibition in a cell-free system (IC(50)=2.2 microM) and was 3.3-fold more potent than that of 1. Complexes 3 a and 4 a ([Pt(II)L3R](+); L3=2,6-bis[1-(3-morpholinopropyl)-1H-pyrazol-3-yl]pyridine, R=Cl) were found to effectively inhibit c-myc gene expression in human hepatocarcinoma cells with IC(50) values of approximately 17 microM, whereas initial hit 1 displayed no significant effect on gene expression at concentrations up to 50 microM. Complexes 3 a and 4 a have a strong preference for G-quadruplex DNA over duplex DNA, as revealed by competition dialysis experiments and absorption titration; 3 a and 4 a bind G-quadruplex DNA with binding constants (K) of approximately 10(6)-10(7) dm(3) mol(-1), which are at least an order of magnitude higher than the K values for duplex DNA. NMR spectroscopic titration experiments and molecular modeling showed that 4 a binds c-myc G-quadruplex DNA through an external end-stacking mode at the 3'-terminal face of the G-quadruplex. Intriguingly, binding of c-myc G-quadruplex DNA by 3 b is accompanied by an increase of up to 38-fold in photoluminescence intensity at lambda(max)=622 nm.

Enrichment of ligands with molecular dockings and subsequent characterization for human alcohol dehydrogenase 3

Alcohol dehydrogenase 3 (ADH3) has been assigned a role in nitric oxide homeostasis due to its function as an S-nitrosoglutathione reductase. As altered S-nitrosoglutathione levels are often associated with disease, compounds that modulate ADH3 activity might be of therapeutic interest. We performed a virtual screening with molecular dockings of more than 40,000 compounds into the active site of human ADH3. A novel knowledge-based scoring method was used to rank compounds, and several compounds that were not known to interact with ADH3 were tested in vitro. Two of these showed substrate activity (9-decen-1-ol and dodecyltetraglycol), where calculated binding scoring energies correlated well with the logarithm of the k (cat)/K (m) values for the substrates. Two compounds showed inhibition capacity (deoxycholic acid and doxorubicin), and with these data three different lines for specific inhibitors for ADH3 are suggested: fatty acids, glutathione analogs, and cholic acids.

Structure based prediction of subtype-selectivity for adenosine receptor antagonists

One of the major hurdles in the development of safe and effective drugs targeting G-protein coupled receptors (GPCRs) is finding ligands that are highly selective for a specific receptor subtype. Structural understanding of subtype-specific binding pocket variations and ligand-receptor interactions may greatly facilitate design of selective ligands. To gain insights into the structural basis of ligand subtype selectivity within the family of adenosine receptors (AR: A(1), A(2A), A(2B), and A(3)) we generated 3D models of all four subtypes using the recently determined crystal structure of the A(A2)AR as a template, and employing the methodology of ligand-guided receptor optimization for refinement. This approach produced 3D conformational models of AR subtypes that effectively explain binding modes and subtype selectivity for a diverse set of known AR antagonists. Analysis of the subtype-specific ligand-receptor interactions allowed identification of the major determinants of ligand selectivity, which may facilitate discovery of more efficient drug candidates.

Improved docking, screening and selectivity prediction for small molecule nuclear receptor modulators using conformational ensembles

Nuclear receptors (NRs) are ligand dependent transcriptional factors and play a key role in reproduction, development, and homeostasis of organism. NRs are potential targets for treatment of cancer and other diseases such as inflammatory diseases, and diabetes. In this study, we present a comprehensive library of pocket conformational ensembles of thirteen human nuclear receptors (NRs), and test the ability of these ensembles to recognize their ligands in virtual screening, as well as predict their binding geometry, functional type, and relative binding affinity. 157 known NR modulators and 66 structures were used as a benchmark. Our pocket ensemble library correctly predicted the ligand binding poses in 94% of the cases. The models were also highly selective for the active ligands in virtual screening, with the areas under the ROC curves ranging from 82 to a remarkable 99%. Using the computationally determined receptor-specific binding energy offsets, we showed that the ensembles can be used for predicting selectivity profiles of NR ligands. Our results evaluate and demonstrate the advantages of using receptor ensembles for compound docking, screening, and profiling.

Stable anticancer gold(III)-porphyrin complexes: effects of porphyrin structure

In the design of physiologically stable anticancer gold(III) complexes, we have employed strongly chelating porphyrinato ligands to stabilize a gold(III) ion [Chem. Commun. 2003, 1718; Coord. Chem. Rev. 2009, 253, 1682]. In this work, a family of gold(III) tetraarylporphyrins with porphyrinato ligands containing different peripheral substituents on the meso-aryl rings were prepared, and these complexes were used to study the structure-bioactivity relationship. The cytotoxic IC(50) values of [Au(Por)](+) (Por=porphyrinato ligand), which range from 0.033 to >100 microM, correlate with their lipophilicity and cellular uptake. Some of them induce apoptosis and display preferential cytotoxicity toward cancer cells than to normal noncancerous cells. A new gold(III)-porphyrin with saccharide conjugation [Au(4-glucosyl-TPP)]Cl (2a; H(2)(4-glucosyl-TPP)=meso-tetrakis(4-beta-D-glucosylphenyl)porphyrin) exhibits significant cytostatic activity to cancer cells (IC(50)=1.2-9.0 microM) without causing cell death and is much less toxic to lung fibroblast cells (IC(50)>100 microM). The gold(III)-porphyrin complexes induce S-phase cell-cycle arrest of cancer cells as indicated by flow cytometric analysis, suggesting that the anticancer activity may be, in part, due to termination of DNA replication. The gold(III)-porphyrin complexes can bind to DNA in vitro with binding constants in the range of 4.9 x 10(5) to 4.1 x 10(6) dm(3) mol(-1) as determined by absorption titration. Complexes 2a and [Au(TMPyP)]Cl(5) (4a; [H(2)TMPyP](4+)=meso-tetrakis(N-methylpyridinium-4-yl)porphyrin) interact with DNA in a manner similar to the DNA intercalator ethidium bromide as revealed by gel mobility shift assays and viscosity measurements. Both of them also inhibited the topoisomerase I induced relaxation of supercoiled DNA. Complex 4a, a gold(III) derivative of the known G-quadruplex-interactive porphyrin [H(2)TMPyP](4+), can similarly inhibit the amplification of a DNA substrate containing G-quadruplex structures in a polymerase chain reaction stop assay. In contrast to these reported complexes, complex 2a and the parental gold(III)-porphyrin 1a do not display a significant inhibitory effect (<10%) on telomerase. Based on the results of protein expression analysis and computational docking experiments, the anti-apoptotic bcl-2 protein is a potential target for those gold(III)-porphyrin complexes with apoptosis-inducing properties. Complex 2a also displays prominent anti-angiogenic properties in vitro. Taken together, the enhanced stabilization of the gold(III) ion and the ease of structural modification render porphyrins an attractive ligand system in the development of physiologically stable gold(III) complexes with anticancer and anti-angiogenic activities.

Identification of natural product fonsecin B as a stabilizing ligand of c-myc G-quadruplex DNA by high-throughput virtual screening

Fonsecin B has been identified as stabilizing ligand of c-myc G-quadruplex DNA using high-throughput virtual screening of a natural product database, and inhibited Taq polymerase-mediated DNA extension in vitro through stabilization of the G-quadruplex secondary structure.

Structure-based discovery of novel chemotypes for adenosine A(2A) receptor antagonists

The recent progress in crystallography of G-protein coupled receptors opens an unprecedented venue for structure-based GPCR drug discovery. To test efficiency of the structure-based approach, we performed molecular docking and virtual ligand screening (VLS) of more than 4 million commercially available "drug-like" and ''lead-like'' compounds against the A(2A)AR 2.6 A resolution crystal structure. Out of 56 high ranking compounds tested in A(2A)AR binding assays, 23 showed affinities under 10 microM, 11 of those had sub-microM affinities and two compounds had affinities under 60 nM. The identified hits represent at least 9 different chemical scaffolds and are characterized by very high ligand efficiency (0.3-0.5 kcal/mol per heavy atom). Significant A(2A)AR antagonist activities were confirmed for 10 out of 13 ligands tested in functional assays. High success rate, novelty, and diversity of the chemical scaffolds and strong ligand efficiency of the A(2A)AR antagonists identified in this study suggest practical applicability of receptor-based VLS in GPCR drug discovery.

GPCR 3D homology models for ligand screening: lessons learned from blind predictions of adenosine A2a receptor complex

Proteins of the G-protein coupled receptor (GPCR) family present numerous attractive targets for rational drug design, but also a formidable challenge for identification and conformational modeling of their 3D structure. A recently performed assessment of blind predictions of adenosine A2a receptor (AA2AR) structure in complex with ZM241385 (ZMA) antagonist provided a first example of unbiased evaluation of the current modeling algorithms on a GPCR target with approximately 30% sequence identity to the closest structural template. Several of the 29 groups participating in this assessment exercise (Michino et al., doi: 10.1038/nrd2877) successfully predicted the overall position of the ligand ZMA in the AA2AR ligand binding pocket, however models from only three groups captured more than 40% the ligand-receptor contacts. Here we describe two of these top performing approaches, in which all-atom models of the AA2AR were generated by homology modeling followed by ligand guided backbone ensemble receptor optimization (LiBERO). The resulting AA2AR-ZMA models, along with the best models from other groups are assessed here for their vitual ligand screening (VLS) performance on a large set of GPCR ligands. We show that ligand guided optimization was critical for improvement of both ligand-receptor contacts and VLS performance as compared to the initial raw homology models. The best blindly predicted models performed on par with the crystal structure of AA2AR in selecting known antagonists from decoys, as well as from antagonists for other adenosine subtypes and AA2AR agonists. These results suggest that despite certain inaccuracies, the optimized homology models can be useful in the drug discovery process.

Structure-based discovery of natural-product-like TNF-α inhibitors

Small but effective: two natural-product-like inhibitors of tumor necrosis factor α (TNF-α; represented in green in the picture) have been identified using structure-based virtual screening. These compounds represent only the third and fourth examples of direct targeting of TNF-α by a small molecule, and display potency comparable to that of the strongest TNF-α inhibitor reported to date.

Alisol B, a novel inhibitor of the sarcoplasmic/endoplasmic reticulum Ca(2+) ATPase pump, induces autophagy, endoplasmic reticulum stress, and apoptosis

Emerging evidence suggests that autophagic modulators have therapeutic potential. This study aims to identify novel autophagic inducers from traditional Chinese medicinal herbs as potential antitumor agents. Using an image-based screen and bioactivity-guided purification, we identified alisol B 23-acetate, alisol A 24-acetate, and alisol B from the rhizome of Alisma orientale as novel inducers of autophagy, with alisol B being the most potent natural product. Across several cancer cell lines, we showed that alisol B-treated cells displayed an increase of autophagic flux and formation of autophagosomes, leading to cell cycle arrest at the G(1) phase and cell death. Alisol B induced calcium mobilization from internal stores, leading to autophagy through the activation of the CaMKK-AMPK-mammalian target of rapamycin pathway. Moreover, the disruption of calcium homeostasis induces endoplasmic reticulum stress and unfolded protein responses in alisol B-treated cells, leading to apoptotic cell death. Finally, by computational virtual docking analysis and biochemical assays, we showed that the molecular target of alisol B is the sarcoplasmic/endoplasmic reticulum Ca(2+) ATPase. This study provides detailed insights into the cytotoxic mechanism of a novel antitumor compound.

Docking flexible ligands in proteins with a solvent exposure- and distance-dependent dielectric function

Physics-based force fields for ligand-protein docking usually determine electrostatic energy with distance-dependent dielectric (DDD) functions, which do not fully account for the dielectric permittivity variance between approximately 2 in the protein core and approximately 80 in bulk water. Here we propose an atom-atom solvent exposure- and distance-dependent dielectric (SEDDD) function, which accounts for both electrostatic and dehydration energy components. Docking was performed using the ZMM program, the AMBER force field, and precomputed libraries of ligand conformers. At the seeding stage, hundreds of thousands of positions and orientations of conformers from the libraries were sampled within the rigid protein. At the refinement stage, the ten lowest-energy structures from the seeding stage were Monte Carlo-minimized with the flexible ligand and flexible protein. A search was considered a success if the root mean square deviation (RMSD) of the ligand atoms in the apparent global minimum from the x-ray structure was <2 A. Calculations on an examining set of 60 ligand-protein complexes with different DDD functions and solvent-exclusion energy revealed outliers in most of which the ligand-binding site was located at the protein surface. Using a training set of 16 ligand-protein complexes, which did not overlap with the examining set, we parameterized the SEDDD function to minimize the RMSD of the apparent global minima from the x-ray structures. Recalculation of the examining set with the SEDDD function demonstrated a 20% increase in the success rate versus the best-performing DDD function.

Stabilization of G-quadruplex DNA with platinum(II) Schiff base complexes: luminescent probe and down-regulation of c-myc oncogene expression

The interactions of a series of platinum(II) Schiff base complexes with c-myc G-quadruplex DNA were studied. Complex [PtL(1a)] (1 a; H(2)L(1a)=N,N'-bis(salicylidene)-4,5-methoxy-1,2-phenylenediamine) can moderately inhibit c-myc gene promoter activity in a cell-free system through stabilizing the G-quadruplex structure and can inhibit c-myc oncogene expression in cultured cells. The interaction between 1 a and G-quadruplex DNA has been examined by (1)H NMR spectroscopy. By using computer-aided structure-based drug design for hit-to-lead optimization, an in silico G-quadruplex DNA model has been constructed for docking-based virtual screening to develop new platinum(II) Schiff base complexes with improved inhibitory activities. Complex [PtL(3)] (3; H(2)L(3)=N,N'-bis{4-[1-(2-propylpiperidine)oxy]salicylidene}-4,5-methoxy-1,2-phenylenediamine) has been identified with a top score in the virtual screening. This complex was subsequently prepared and experimentally tested in vitro for its ability to stabilize or induce the formation of the c-myc G-quadruplex. The inhibitory activity of 3 (IC(50)=4.4 muM) is tenfold more than that of 1 a. The interaction between 1 a or 3 with c-myc G-quadruplex DNA has been examined by absorption titration, emission titration, molecular modeling, and NMR titration experiments, thus revealing that both 1 a and 3 bind c-myc G-quadruplex DNA through an external end-stacking mode at the 3' terminal face of the G-quadruplex. Such binding of G-quadruplex DNA with 3 is accompanied by up to an eightfold increase in the intensity of photoluminescence at lambda(max)=652 nm. Complex 3 also effectively down-regulated the expression of c-myc in human hepatocarcinoma cells.

Tea catechins inhibit hepatocyte growth factor receptor (MET kinase) activity in human colon cancer cells: kinetic and molecular docking studies

Most cancer deaths result from spread of the primary tumor to distant sites (metastasis). MET is an important protein for metastasis in multiple tumor types. Here we report on the ability of tea catechins to suppress MET activation in human colon cancer cells and propose a mechanism by which they might compete for the kinase domain of the MET protein.

Modeling of the aryl hydrocarbon receptor (AhR) ligand binding domain and its utility in virtual ligand screening to predict new AhR ligands

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor; the AhR Per-AhR/Arnt-Sim (PAS) domain binds ligands. We developed homology models of the AhR PAS domain to characterize previously observed intra- and interspecies differences in ligand binding using molecular docking. In silico structure-based virtual ligand screening using our model resulted in the identification of pinocembrin and 5-hydroxy-7-methoxyflavone, which promoted nuclear translocation and transcriptional activation of AhR and AhR-dependent induction of endogenous target genes.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

Influence of protonation, tautomeric, and stereoisomeric states on protein-ligand docking results

In this work, we present a systematical investigation of the influence of ligand protonation states, stereoisomers, and tautomers on results obtained with the two protein-ligand docking programs GOLD and PLANTS. These different states were generated with a fully automated tool, called SPORES (Structure PrOtonation and Recognition System). First, the most probable protonations, as defined by this rule based system, were compared to the ones stored in the well-known, manually revised CCDC/ASTEX data set. Then, to investigate the influence of the ligand protonation state on the docking results, different protonation states were created. Redocking and virtual screening experiments were conducted demonstrating that both docking programs have problems in identifying the correct protomer for each complex. Therefore, a preselection of plausible protomers or the improvement of the scoring functions concerning their ability to rank different molecules/states is needed. Additionally, ligand stereoisomers were tested for a subset of the CCDC/ASTEX set, showing similar problems regarding the ranking of these stereoisomers as the ranking of the protomers.

Peptidic modulators of protein-protein interactions: progress and challenges in computational design

With the decline in productivity of drug-development efforts, novel approaches to rational drug design are being introduced and developed. Naturally occurring and synthetic peptides are emerging as novel promising compounds that can specifically and efficiently modulate signaling pathways in vitro and in vivo. We describe sequence-based approaches that use peptides to mimic proteins in order to inhibit the interaction of the mimicked protein with its partners. We then discuss a structure-based approach, in which protein-peptide complex structures are used to rationally design and optimize peptidic inhibitors. We survey flexible peptide docking techniques and discuss current challenges and future directions in the rational design of peptidic inhibitors.