Probing the dynamic nature of water molecules and their influences on ligand binding in a model binding site

The model binding site of the cytochrome c peroxidase (CCP) W191G mutant is used to investigate the structural and dynamic properties of the water network at the buried cavity using computational methods supported by crystallographic analysis. In particular, the differences of the hydration pattern between the uncomplexed state and various complexed forms are analyzed as well as the differences between five complexes of CCP W191G with structurally closely related ligands. The ability of docking programs to correctly handle the water molecules in these systems is studied in detail. It is found that fully automated prediction of water replacement or retention upon docking works well if some additional preselection is carried out but not necessarily if the entire water network in the cavity is used as input. On the other hand, molecular interaction fields for water calculated from static crystal structures and hydration density maps obtained from molecular dynamics simulations agree very well with crystallographically observed water positions. For one complex, the docking and MD results sensitively depend on the quality of the starting structure, and agreement is obtained only after redetermination of the crystal structure and refinement at higher resolution.     

Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy

Probing protein surfaces to accurately predict the binding site and conformation of a small molecule is a challenge currently addressed through mainly two different approaches: blind docking and cavity detection-guided docking. Although cavity detection-guided blind docking has yielded high success rates, it is less practical when a large number of molecules must be screened against many detected binding sites. On the other hand, blind docking allows for simultaneous search of the whole protein surface, which however entails the loss of accuracy and speed. To bridge this gap, in this study, we developed and tested BLinDPyPr, an automated pipeline which uses FTMap and DOCK6 to perform a hybrid blind docking strategy. Through our algorithm, FTMap docked probe clusters are converted into DOCK6 spheres for determining binding regions. Because these spheres are solely derived from FTMap probes, their locations are contained in and specific to multiple potential binding pockets, which become the regions that are simultaneously probed and chosen by the search algorithm based on the properties of each candidate ligand. This method yields pose prediction results (45.2–54.3% success rates) comparable to those of site-specific docking with the classic DOCK6 workflow (49.7–54.3%) and is half as time-consuming as the conventional blind docking method with DOCK6.     

Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling

The W191G cavity of cytochrome c peroxidase is useful as a model system for introducing small molecule oxidation in an artificially created cavity. A set of small, cyclic, organic cations was previously shown to bind in the buried, solvent-filled pocket created by the W191G mutation. We docked these ligands and a set of non-binders in the W191G cavity using AutoDock 3.0. For the ligands, we compared docking predictions with experimentally determined binding energies and X-ray crystal structure complexes. For the ligands, predicted binding energies differed from measured values by +/- 0.8 kcal/mol. For most ligands, the docking simulation clearly predicted a single binding mode that matched the crystallographic binding mode within 1.0 A RMSD. For 2 ligands, where the docking procedure yielded an ambiguous result, solutions matching the crystallographic result could be obtained by including an additional crystallographically observed water molecule in the protein model. For the remaining 2 ligands, docking indicated multiple binding modes, consistent with the original electron density, suggesting disordered binding of these ligands. Visual inspection of the atomic affinity grid maps used in docking calculations revealed two patches of high affinity for hydrogen bond donating groups. Multiple solutions are predicted as these two sites compete for polar hydrogens in the ligand during the docking simulation. Ligands could be distinguished, to some extent, from non-binders using a combination of two trends: predicted binding energy and level of clustering. In summary, AutoDock 3.0 appears to be useful in predicting key structural and energetic features of ligand binding in the W191G cavity.     

Guest Binding with Sulfated Cyclodextrins: Does the Size of Cavity Matter?

Sulfated cyclodextrins have recently emerged as potential candidates for producing host–induced guest aggregation with properties better than p-sulfonatocalixarenes that have previously shown numerous applications involving the phenomena of host-induced guest aggregation. In the class of sulfated cyclodextrins (SCD), sulfated β-cyclodextrin (β-SCD) remains the most extensively investigated host molecule. Although it is assumed that the host-induced guest aggregation is predominantly an outcome of interaction of the guest molecule with the charges on the exterior of SCD cavity, it has not been deciphered whether the variation in the cavity size will make a difference in the efficiency of host-induced guest-aggregation process. In this investigation, we present a systematic study of host–induced guest aggregation of a cationic molecular rotor dye, Thioflavin T (ThT) with three different sulfated cyclodextrin molecules, α-SCD, β-SCD and γ-SCD, which differ in their cavity size, using steady-state emission, ground-state absorption and time-resolved emission measurements. The obtained photophysical properties of ThT, upon interaction with different SCD molecules, indicate that the binding strength of ThT with different SCD molecules correlate with the cavity size of the host molecule, giving rise to the strongest complexation of ThT with the largest host molecule (γ-SCD). The binding affinity of ThT towards different host molecules has been supported by molecular docking calculations. The results obtained are further supported with the temperature and ionic strength dependent studies performed on the host-guest complex. Our results indicate that for host–induced guest aggregation, involving oppositely charged molecules, the size of the cavity also plays a crucial role beside the charge density on the exterior of host cavity.     

Systematic and efficient side chain optimization for molecular docking using a cheapest‐path procedure

Molecular docking of small‐molecules is an important procedure for computer‐aided drug design. Modeling receptor side chain flexibility is often important or even crucial, as it allows the receptor to adopt new conformations as induced by ligand binding. However, the accurate and efficient incorporation of receptor side chain flexibility has proven to be a challenge due to the huge computational complexity required to adequately address this problem. Here we describe a new docking approach with a very fast, graph‐based optimization algorithm for assignment of the near‐optimal set of residue rotamers. We extensively validate our approach using the 40 DUD target benchmarks commonly used to assess virtual screening performance and demonstrate a large improvement using the developed side chain optimization over rigid receptor docking (average ROC AUC of 0.693 vs. 0.623). Compared to numerous benchmarks, the overall performance is better than nearly all other commonly used procedures. Furthermore, we provide a detailed analysis of the level of receptor flexibility observed in docking results for different classes of residues and elucidate potential avenues for further improvement. © 2013 Wiley Periodicals, Inc.     

Hammerhead: fast,fully automated docking of flexible ligands to protein binding sites

Background: Molecular docking seeks to predict the geometry and affinity of the binding of a small molecule to a given protein of known structure. Rigid docking has long been used to screen databases of small molecules, because docking techniques that account for ligand flexibility have either been too slow or have required significant human intervention. Here we describe a docking algorithm, Hammerhead, which is a fast, automated tool to screen for the binding of flexible molecules to protein binding sites.Results: We used Hammerhead to successfully dock a variety of positive control ligands into their cognate proteins. The empirically tuned scoring function of the algorithm predicted binding affinities within 1.3 log units of the known affinities for these ligands. Conformations and alignments close to those determined crystallographically received the highest scores. We screened 80 000 compounds for binding to streptavidin, and biotin was predicted as the top-scoring ligand, with other known ligands included among the highest-scoring dockings. The screen ran in a few days on commonly available hardware.Conclusions: Hammerhead is suitable for screening large databases of flexible molecules for binding to a protein of known structure. It correctly docks a variety of known flexible ligands, and it spends an average of only a few seconds on each compound during a screen. The approach is completely automated, from the elucidation of protein binding sites, through the docking of molecules, to the final selection of compounds for assay.     

Statistical relationships among docking scores for different protein binding sites

This report describes the existence of statistical relationships among scores computed with the DOCK program for a library of small molecules and a panel of protein binding sites. Multivariate relationships are observed in docking scores computed for a constant set of ligands in different binding sites of proteins that are dissimilar in structure and function. The structural basis for the correlations found among scores is analyzed in terms of size, shape and charge characteristics of the binding sites considered. Interestingly, these results parallel a growing body of evidence demonstrating the promiscuous behavior of small molecules in their interactions with macromolecules that could have an impact in future efforts in drug design.     

In silico modeling and molecular docking insights of kaempferitrin for colon cancer-related molecular targets

Colorectal cancer is one of the most common cancers worldwide, and it is also one of the major causes of mortality from cancer. Chemotherapy drugs are generally limited due to various complications, as well as the development of resistance and recurrence. The in silico docking investigation involved exploration of protein or nucleotide, 3D structural modeling, molecular docking, and binding energy calculation. Protein-protein interactions are significant to many biological processes, and their disruption is a leading cause of disease. The use of small molecules to modulate them is gaining popularity, but protein interfaces usually lack specific cavities for processing small molecules. MMP-2, PARP, iNOS, Chk1, proteins were used in the molecular docking analysis of kaempferitrin and 5-flurouracil. The compound kaempferitrin had the highest binding energy scores with most of the target proteins, according to molecular docking results. The findings suggest it could be used to develop new drugs for cancer therapy.     

New approach to molecular docking and its application to virtual screening of chemical databases

This paper describes the validation of a molecular docking method and its application to virtual database screening. The code flexibly docks ligand molecules into rigid receptor structures using a tabu search methodology driven by an empirically derived function for estimating the binding affinity of a protein-ligand complex. The docking method has been tested on 70 ligand-receptor complexes for which the experimental binding affinity and binding geometry are known. The lowest energy geometry produced by the docking protocol is within 2.0 A root mean square of the experimental binding mode for 79% of the complexes. The method has been applied to the problem of virtual database screening to identify known ligands for thrombin, factor Xa, and the estrogen receptor. A database of 10,000 randomly chosen "druglike" molecules has been docked into the three receptor structures. In each case known receptor ligands were included in the study. The results showed good separation between the predicted binding affinities of the known ligand set and the database subset.     

Immunoglobulin cross-reactivity examined by library screening, crystallography and docking studies

Antibodies are extremely diverse with respect to their specificities and affinities for target molecules. Despite rigorous selection, some antibodies are cross-reactive whereby they recognize their natural antigens along with other molecules. In this review, we discuss our efforts toward understanding the cross-reactivity of selected immunoglobulins. Investigations that are discussed employed screens of combinatorial peptide libraries, crystallography of ligand-protein complexes, and computer-based peptide docking simulations. In the first example, two different antibodies (NC6.8 and NC10.14) bound the same trisubstituted guanidine (NC174) with similar affinities, but utilized predominantly dissimilar binding strategies. However, there was one common binding strategy, in which the cyanophenyl portion of NC174 was inserted end-on into the binding crevices of the NC6.8 and NC10.14 antibodies. In the second example, scanning of peptide libraries and X-ray crystallography were used to design and test synthetic peptides for binding to the Mcg L chain dimer. Again, end-on insertion was favored for all peptides larger than dipeptides in the voluminous Mcg binding cavity. Finally, automated docking was used for rapid predictions of complexes for the Fv molecule from a broadly cross-reactive human IgM (Mez) and nearly two thousand peptides. Certain amino acids, including the aromatic residues Trp and Phe, functioned as anchoring groups in automated docking. Anchoring groups acted in most of the peptides that were otherwise accommodated by a variety of binding strategies in the docked complexes. We suggest that anchoring of at least a portion of a ligand in a binding site is a common mechanism for antibody recognition.     

Toward electron encapsulation: polynitrile approach

This study seeks an answer to the following question: Is it possible to design a supramolecular cage that would "solvate" the excess electron in the same fashion in which several solvent molecules do that cooperatively in polar liquids? Two general strategies are outlined for this "electron encapsulation", viz. electron localization using polar groups arranged on the (i) inside of the cage or (ii) outside of the cage. The second approach is more convenient from the synthetic standpoint, but it is limited to polynitriles. We demonstrate, experimentally and theoretically, that this second approach faces a problem: the electron attaches to the nitrile groups, forming molecular anions with bent C-C-N fragments. Because the energy cost of this bending is high, for dinitrile anions in n-hexane, the binding energies for the electron are low and, for mononitriles, these binding energies are lower still, and the entropy of electron attachment is anomalously small. Density functional theory modeling of electron trapping by mononitriles in n-hexane suggests that the solute molecules substitute for the solvent molecules at the electron cavity, "solvating" the electron by their methyl groups. We argue that such species would be more correctly viewed as multimer radical anions in which the electron density is shared (mainly) between C 2p orbitals in the solute/solvent molecules, rather than cavity electrons. The way in which the excess electron density is shared by such molecules is similar to the way in which this sharing occurs in large di- and polynitrile anions, such as 1,2,4,5,7,8,10,11-octacyanocyclododecane(-). Only in this sense is the electron encapsulation possible. The work thus reveals limitations of the concept of "solvated electron" for organic liquids: it is impossible to draw a clear line between such species and a certain class of radical anions.     

Molecular docking using shape descriptors

Molecular docking explores the binding modes of two interacting molecules. The technique is increasingly popular for studying protein-ligand interactions and for drug design. A fundamental problem problem with molecular docking is that orientation space is very large and grows combinatorially with the number of degrees of freedom of the interacting molecules. Here, we describe and evaluate algorithms that improve the efficiency and accuracy of a shape-based docking method. We use molecular organization and sampling techniques to remove the exponential time dependence on molecular size in docking calculations. The new techniques allow us to study systems that were prohibitively large for the original method. The new algorithms are tested in 10 different protein-ligand systems, including 7 systems where the ligand is itself a protein. In all cases, the new algorithms successfully reproduce the experimentally determined configurations of the ligand in the protein.     

Prediction of the binding sites of huperzine A in acetylcholinesterase by docking studies

Summary We have performed docking studies with the SYSDOC program on acetylcholinesterase (AChE) to predict the binding sites in AChE of huperzine A (HA), which is a potent and selective, reversible inhibitor of AChE. The unique aspects of our docking studies include the following: (i) Molecular flexibility of the guest and the host is taken into account, which permits both to change their conformations upon binding. (ii) The binding energy is evaluated by a sum of energies of steric, electrostatic and hydrogen bonding interactions. In the energy calculation no grid approximation is used, and all hydrogen atoms of the system are treated explicitly. (iii) The energy of cation- interactions between the guest and the host, which is important in the binding of AChE, is included in the calculated binding energy. (iv) Docking is performed in all regions of the host's binding cavity. Based on our docking studies and the pharmacological results reported for HA and its analogs, we predict that HA binds to the bottom of the binding cavity of AChE (the gorge) with its ammonium group interacting with Trp⁸⁴, Phe³³⁰, Glu¹⁹⁹ and Asp⁷² (catalytic site). At the the opening of the gorge with its ammonium group partially interacting with Trp²⁷⁹ (peripheral site). At the catalytic site, three partially overlapping subsites of HA were identified which might provide a dynamic view of binding of HA to the catalytic site.     

Efficient inclusion of receptor flexibility in grid-based protein-ligand docking

Accounting for receptor flexibility is an essential component of successful protein-ligand docking but still marks a major computational challenge. For many target molecules of pharmaceutical relevance, global backbone conformational changes are relevant during the ligand binding process. However, popular methods that represent the protein receptor molecule as a potential grid typically assume a rigid receptor structure during ligand-receptor docking. A new approach has been developed that combines inclusion of global receptor flexibility with the efficient potential grid representation of the receptor molecule. This is achieved using interpolation between grid representations of the receptor protein deformed in selected collective degrees of freedom. The method was tested on the docking of three ligands to apo protein kinase A (PKA), an enzyme that undergoes global structural changes upon inhibitor binding. Structural variants of PKA were generated along the softest normal mode of an elastic network representation of apo PKA. Inclusion of receptor deformability during docking resulted in a significantly improved docking performance compared with rigid PKA docking, thus allowing for systematic virtual screening applications at small additional computational cost.     

Are AM1 ligand‐protein binding enthalpies good enough for use in the rational design of new drugs?

We have examined the performance of semiempirical quantum mechanical methods in solving the problem of accurately predicting protein-ligand binding energies and geometries. Firstly, AM1 and PM3 geometries and binding enthalpies between small molecules that simulate typical ligand-protein interactions were compared with high level quantum mechanical techniques that include electronic correlation (e.g., MP2 or B3LYP). Species studied include alkanes, aromatic systems, molecules including groups with hypervalent sulfur or with donor or acceptor hydrogen bonding capability, as well as ammonium or carboxylate ions. B3LYP/6-311+G(2d,p) binding energies correlated very well with the BSSE corrected MP2/6-31G(d) values. AM1 binding enthalpies also showed good correlation with MP2 values, and their systematic deviation is acceptable when enthalpies are used for the comparison of interaction energies between ligands and a target. PM3 otherwise gave erratic energy differences in comparison to the B3LYP or MP2 approaches. As one would expect, the geometries of the binding complexes showed the known limitations of the semiempirical and DFT methods. AM1 calculations were subsequently applied to a test set consisting of "real" protein active site-ligand complexes. Preliminary results indicate that AM1 could be a valuable tool for the design of new drugs using proteins as templates. This approach also has a reasonable computational cost. The ligand-protein X-ray structures were reasonably reproduced by AM1 calculations and the corresponding AM1 binding enthalpies are in agreement with the results from the "small molecules" test set.     

Extended-ensemble docking to probe dynamic variation of ligand binding sites during large-scale structural changes of proteins

Proteins can sample a broad landscape as they undergo conformational transition between different functional states. At the same time, as key players in almost all cellular processes, proteins are important drug targets. Considering the different conformational states of a protein is therefore central for a successful drug-design strategy. Here we introduce a novel docking protocol, termed extended-ensemble docking, pertaining to proteins that undergo large-scale (global) conformational changes during their function. In its application to multidrug ABC-transporter P-glycoprotein (Pgp), extensive non-equilibrium molecular dynamics simulations employing system-specific collective variables are first used to describe the transition cycle of the transporter. An extended set of conformations (extended ensemble) representing the full transition cycle between the inward- and the outward-facing states is then used to seed high-throughput docking calculations of known substrates, non-substrates, and modulators of the transporter. Large differences are predicted in the binding affinities to different conformations, with compounds showing stronger binding affinities to intermediate conformations compared to the starting crystal structure. Hierarchical clustering of the binding modes shows all ligands preferably bind to the large central cavity of the protein, formed at the apex of the transmembrane domain (TMD), whereas only small binding populations are observed in the previously described R and H sites present within the individual TMD leaflets. Based on the results, the central cavity is further divided into two major subsites, first preferably binding smaller substrates and high-affinity inhibitors, whereas the second one shows preference for larger substrates and low-affinity modulators. These central subsites along with the low-affinity interaction sites present within the individual TMD leaflets may respectively correspond to the proposed high- and low-affinity binding sites in Pgp. We propose further an optimization strategy for developing more potent inhibitors of Pgp, based on increasing its specificity to the extended ensemble of the protein, instead of using a single protein structure, as well as its selectivity for the high-affinity binding site. In contrast to earlier in silico studies using single static structures of Pgp, our results show better agreement with experimental studies, pointing to the importance of incorporating the global conformational flexibility of proteins in future drug-discovery endeavors.

Functional states of P-glycoprotein formed during its full transition cycle (red to blue), captured by molecular dynamics simulations, form a structural framework for extended-ensemble docking of small-molecule ligands of diverse activities.     

Shape-specific detection based on fluorescence resonance energy transfer using a flexible water-soluble conjugated polymer

We present the detection of the shape-specific conformation of DNA based on the fluorescence resonance energy transfer (FRET) by using a novel flexible water-soluble cationic conjugated polymer (CCP). The flexible backbone of CCP has more conformational freedom with the potential to be responsive to analyte shape by electrostatic interaction between flexible CCP and negatively charged DNA. The analyte shape dependent recognition is accomplished by structural changes that compressed or extended the flexible CCP. The morphology-dependent spectral properties of the novel flexible polymer related to the analyte shapes are investigated in detail, where two types of chromophores, referred to as "isolated" segment and "packed" segment aggregates, within the flexible polymer are identified by means of ensemble and single molecule measurements upon binding with different geometric DNA. The change in fluorescence intensity upon binding with shape-specific DNA without obvious color shifts makes this novel flexible polymer a suitable CCP donor for FRET measurements. The results provide insights for understanding the spectral properties of flexible water-soluble CCP and CCP/DNA interaction related to the geometry of target analyte.     

Protein-ligand docking against non-native protein conformers

In the validation of protein-ligand docking protocols, performance is mostly measured against native protein conformers, i.e. each ligand is docked into the protein conformation from the structure that contained that ligand. In real-life applications, however, ligands are docked against non-native conformations of the protein, i.e. the apo structure or a structure of a different protein-ligand complex. Here, we have constructed an extensive test set for assessing docking performance against non-native protein conformations. This new test set is built on the Astex Diverse Set (which we recently constructed for assessing native docking performance) and contains 1112 non-native structures for 65 drug targets. Using the protein-ligand docking program GOLD, the Astex Diverse Set and the new Astex Non-native Set, we established that, whereas docking performance (top-ranked solution within 2 A rmsd of the experimental binding mode) is approximately 80% for native docking, this drops to 61% for non-native docking. A similar drop-off is observed for sampling performance (any solution within 2 A): 91% for native docking vs 72% for non-native docking. No significant differences were observed between docking performance against apo and nonapo structures. We found that, whereas small variations in protein conformation are generally tolerated by our rigid docking protocol, larger protein movements result in a catastrophic drop-off in performance. Some docking performance and nearly all sampling performance can be recovered by considering dockings produced against a small number of non-native structures simultaneously. Docking against non-native structures of complexes containing ligands that are similar to the docked ligand also significantly improves both docking performance and sampling performance.     

Sensitivity of molecular docking to induced fit effects in influenza virus neuraminidase

Many proteins undergo small side chain or even backbone movements on binding of different ligands into the same protein structure. This is known as induced fit and is potentially problematic for virtual screening of databases against protein targets. In this report we investigate the limits of the rigid protein approximation used by the docking program, GOLD, through cross-docking using protein structures of influenza neuraminidase. Neuraminidase is known to exhibit small but significant induced fit effects on ligand binding. Some neuraminidase crystal structures caused concern due to the bound ligand conformation and GOLD performed poorly on these complexes. A `clean' set, which contained unique, unambiguous complexes, was defined. For this set, the lowest energy structure was correctly docked (i.e. RMSD < 1.5 Å away from the crystal reference structure) in 84% of proteins, and the most promiscuous protein (1mwe) was able to dock all 15 ligands accurately including those that normally required an induced fit movement. This is considerably better than the 70% success rate seen with GOLD against general validation sets. Inclusion of specific water molecules involved in water-mediated hydrogen bonds did not significantly improve the docking performance for ligands that formed water-mediated contacts but it did prevent docking of ligands that displaced these waters. Our data supports the use of a single protein structure for virtual screening with GOLD in some applications involving induced fit effects, although care must be taken to identify the protein structure that performs best against a wide variety of ligands. The performance of GOLD was significantly better than the GOLD implementation of ChemScore and the reasons for this are discussed. Overall, GOLD has shown itself to be an extremely good, robust docking program for this system.