Ligand-receptor docking with the Mining Minima optimizer

Capture of activated dioxygen intermediates at the copper-active site of a lytic polysaccharide monooxygenase

Metalloproteins perform a diverse array of redox-related reactions facilitated by the increased chemical functionality afforded by their metallocofactors. Lytic polysaccharide monooxygenases (LPMOs) are a class of copper-dependent enzymes that are responsible for the breakdown of recalcitrant polysaccharides via oxidative cleavage at the glycosidic bond. The activated copper-oxygen intermediates and their mechanism of formation remains to be established. Neutron protein crystallography which permits direct visualization of protonation states was used to investigate the initial steps of oxygen activation directly following active site copper reduction in Neurospora crassa LPMO9D. Herein, we cryo-trap an activated dioxygen intermediate in a mixture of superoxo and hydroperoxo states, and we identify the conserved second coordination shell residue His157 as the proton donor. Density functional theory calculations indicate that both superoxo and hydroperoxo active site states are stable. The hydroperoxo formed is potentially an early LPMO catalytic reaction intermediate or the first step in the mechanism of hydrogen peroxide formation in the absence of substrate. We observe that the N-terminal amino group of the copper coordinating His1 remains doubly protonated directly following molecular oxygen reduction by copper. Aided by molecular dynamics and mining minima free energy calculations we establish that the conserved second-shell His161 in MtPMO3* displays conformational flexibility in solution and that this flexibility is also observed, though to a lesser extent, in His157 of NcLPMO9D. The imidazolate form of His157 observed in our structure following oxygen intermediate protonation can be attributed to abolished His157 flexibility due steric hindrance in the crystal as well as the solvent-occluded active site environment due to crystal packing. A neutron crystal structure of NcLPMO9D at low pH further supports occlusion of the active site since His157 remains singly protonated even at acidic conditions.

Estimating the Roles of Protonation and Electronic Polarization in Absolute Binding Affinity Simulations

Accurate prediction of binding free energies is critical to streamlining the drug development and protein design process. With the advent of GPU acceleration, absolute alchemical methods, which simulate the removal of ligand electrostatics and van der Waals interactions with the protein, have become routinely accessible and provide a physically rigorous approach that enables full consideration of flexibility and solvent interaction. However, standard explicit solvent simulations are unable to model protonation or electronic polarization changes upon ligand transfer from water to the protein interior, leading to inaccurate prediction of binding affinities for charged molecules. Here, we perform extensive simulation totaling ∼540 μs to benchmark the impact of modeling conditions on predictive accuracy for absolute alchemical simulations. Binding to urokinase plasminogen activator (UPA), a protein frequently overexpressed in metastatic tumors, is evaluated for a set of 10 inhibitors with extended flexibility, highly charged character, and titratable properties. We demonstrate that the alchemical simulations can be adapted to utilize the MBAR/PBSA method to improve the accuracy upon incorporating electronic polarization, highlighting the importance of polarization in alchemical simulations of binding affinities. Comparison of binding energy prediction at various protonation states indicates that proper electrostatic setup is also crucial in binding affinity prediction of charged systems, prompting us to propose an alternative binding mode with protonated ligand phenol and Hid-46 at the binding site, a testable hypothesis for future experimental validation.

Computation of host-guest binding free energies with a new quantum mechanics based mining minima algorithm

A new method called QM-VM2 is presented that efficiently combines statistical mechanics with quantum mechanical (QM) energy potentials in order to calculate noncovalent binding free energies of host-guest systems. QM-VM2 efficiently couples the use of semi-empirical QM (SEQM) energies and geometry optimizations with an underlying molecular mechanics (MM) based conformational search, to find low SEQM energy minima, and allows for processing of these minima at higher levels of ab initio QM theory. A progressive geometry optimization scheme is introduced as a means to increase conformational sampling efficiency. The newly implemented QM-VM2 is used to compute the binding free energies of the host molecule cucurbit[7]uril and a set of 15 guest molecules. The results are presented along with comparisons to experimentally determined binding affinities. For the full set of 15 host-guest complexes, which have a range of formal charges from +1 to +3, SEQM-VM2 based binding free energies show poor correlation with experiment, whereas for the ten +1 complexes only, a significant correlation (R2 = 0.8) is achieved. SEQM-VM2 generation of conformers followed by single-point ab initio QM calculations at the dispersion corrected restricted Hartree-Fock-D3(BJ) and TPSS-D3(BJ) levels of theory, as post-processing corrections, yields a reasonable correlation with experiment for the full set of host-guest complexes (R2 = 0.6 and R2 = 0.7, respectively) and an excellent correlation for the +1 formal charge set (R2 = 1.0 and R2 = 0.9, respectively), as long as a sufficiently large basis set (triple-zeta quality) is employed. The importance of the inclusion of configurational entropy, even at the MM level, for the achievement of good correlation with experiment was demonstrated by comparing the calculated ΔE values with experiment and finding a considerably poorer correlation with experiment than for the calculated free energy ΔE - TΔS. For the complete set of host-guest systems with the range of formal charges, it was observed that the deviation of the predicted binding free energy from experiment correlates somewhat with the net charge of the systems. This observation leads to a simple empirical interpolation scheme to improve the linear regression of the full set.

Computational Graphics Software for Interactive Docking and Visualization of Ligand-Protein Complementarity

The Dockeye software is designed to complement automated docking protocols by allowing the user's chemical know-how and experience of what makes for good protein-ligand binding, knowledge that is not easily encoded into automated algorithms, to guide the docking. It allows the interactive manipulation of the ligand placement against a protein target. Real-time intuitively comprehensible feedback about the location, spatial density, and the extent of both favorable and unfavorable atomic interactions between ligand and protein is provided through a carefully designed graphical object. It is also a tool for the graphical analysis of the interactions of known protein-ligand complexes. Comparative docking of 58 protein-ligand complexes with Dockeye and Autodock Vina shows how this software can be used synergistically with automated docking programs to significantly improve the task of discovery of ligand placement.

The hydrolysis of indoxyl acetate: A versatile reaction to assay carbonic anhydrase activity by high-throughput screening

The interest in CO₂ capture and conversion by biological methodologies into various beneficial products is increased. In nature, there are enzymes, with hydration activity, which catalyze the reversible hydration of the CO₂ molecule and, thus, are of high interest for biotechnological applications. Such enzymes are carbonic anhydrases (CAs). Structural, functional and mutational studies have shown, that besides hydratase activity, CAs have exposed hydrolytic, particularly esterase activity, and importantly, both activities follow similar catalytic mechanisms in the same catalytic pocket. CAs activity measurement methods based on electrometric assays for hydration activity and nitrophenyl based esters for hydrolytic activity assays do not fulfill the requirements amenable for enzyme activity screening methods. By this study, we were aiming to develop an indigogenic assay method based on the esterase activity of CAs. The first time use of indoxyl acetate as a substrate for CA has shown promising results to gain simplicity, repeatability, and applicability to implement high-throughput screening methods.

Template-based modeling of diverse protein interactions in CAPRI rounds 38-45

Structures of proteins complexed with other proteins, peptides, or ligands are essential for investigation of molecular mechanisms. However, the experimental structures of protein complexes of interest are often not available. Therefore, computational methods are widely used to predict these structures, and, of those methods, template-based modeling is the most successful. In the rounds 38-45 of the Critical Assessment of PRediction of Interactions (CAPRI), we applied template-based modeling for 9 of 11 protein-protein and protein-peptide interaction targets, resulting in medium and high-quality models for six targets. For the protein-oligosaccharide docking targets, we used constraints derived from template structures, and generated models of at least acceptable quality for most of the targets. Apparently, high flexibility of oligosaccharide molecules was the main cause preventing us from obtaining models of higher quality. We also participated in the CAPRI scoring challenge, the goal of which was to identify the highest quality models from a large pool of decoys. In this experiment, we tested VoroMQA, a scoring method based on interatomic contact areas. The results showed VoroMQA to be quite effective in scoring strongly binding and obligatory protein complexes, but less successful in the case of transient interactions. We extensively used manual intervention in both CAPRI modeling and scoring experiments. This oftentimes allowed us to select the correct templates from available alternatives and to limit the search space during the model scoring.

Benzimidazole design, synthesis, and docking to build selective carbonic anhydrase VA inhibitors

The similarity of human carbonic anhydrase (CA) active sites makes it difficult to design selective inhibitors for one or several CA isoforms that are drug targets. Here we synthesize a series of compounds that are based on 5-[2-(benzimidazol-1-yl)acetyl]-2-chloro-benzenesulfonamide (1a) which demonstrated picomolar binding affinity and significant selectivity for CA isoform five A (VA), and explain the structural influence of inhibitor functional groups to the binding affinity and selectivity. A series of chloro-substituted benzenesulfonamides bearing a heterocyclic tail, together with molecular docking, was used to build inhibitors that explore substituent influence on the binding affinity to the CA VA isoform.

Sensitivity Analysis and Charge-Optimization for Flexible Ligands: Applicability to Lead Optimization

Sensitivity analysis and charge-optimization have been suggested as methods to guide the optimization of lead compounds in early-stage drug discovery. However, applications to date have been restricted by the simplifying assumption of a rigid ligand. The present study applies both formalisms to the case of a flexible ligand in a model application to an HIV-protease inhibitor. The results suggest that sensitivity analysis is a fast and robust method for guiding charge changes in both a rigid and a flexible ligand, although its accuracy is limited by the fact that it represents a linear approximation. The more complete quadratic analysis provided by charge-optimization produces unexpected results when the ligand is considered to be flexible. For example, it can yield atomic charges which powerfully stabilize the bound conformation of the ligand relative to the conformation assumed for the free state, thus markedly destabilizing the assumed free conformation. Such results are traceable to the fact that the energy matrix possesses negative eigenvalues. However, optimizing charges under the assumption that the ligand does not change conformation upon binding leads to a set of charges that robustly improve affinity, even when the free conformation is later allowed to vary. Thus, both sensitivity analysis and charge-optimization appear to be useful techniques.

Monte Carlo Sampling with Hierarchical Move Sets: POSH Monte Carlo

We present a new Monte Carlo method for sampling rugged energy landscapes that allows for efficient transitions across sparsely distributed local basins. The trial move consists of two steps. The first step is a large initial trial move, and the second step is a Monte Carlo trajectory generated using smaller trial moves. To maintain detailed balance, a reverse transition probability is estimated along a path that differs from the forward path. Since the forward and reverse transitions are different, we name the algorithm POSH (port out, starboard home) Monte Carlo. The process obeys detailed balance to the extent that the transition probabilities are correctly estimated. There is an optimal range of performance for a given energy landscape, which depends on how sparsely the low energy states of the system are distributed. For simple model systems, adequate precision is obtained over a large range of inner steps settings. Side chain sampling of residues in the binding region of progesterone antibody 1dba are studied, and show that significant improvement over a comparable standard protocol can be obtained using POSH sampling. To compare with experimental data, the phosphopeptide Ace-Gly-Ser-pSer-Ser-Nma is also studied, and the resulting NMR observables compare well with experiment. For the biomolecular systems studied, we show that POSH sampling generates precise distributions using the number of inner steps set up to 20.

Saccharin sulfonamides as inhibitors of carbonic anhydrases I, II, VII, XII, and XIII

A series of modified saccharin sulfonamides have been designed as carbonic anhydrase (CA) inhibitors and synthesized. Their binding to CA isoforms I, II, VII, XII, and XIII was measured by the fluorescent thermal shift assay (FTSA) and isothermal titration calorimetry (ITC). Saccharin bound the CAs weakly, exhibiting the affinities of 1–10 mM for four CAs except CA I where binding could not be detected. Several sulfonamide-bearing saccharines exhibited strong affinities of 1–10 nM towards particular CA isoforms. The functional group binding Gibbs free energy additivity maps are presented which may provide insights into the design of compounds with increased affinity towards selected CAs.

Solvent interaction energy calculations on molecular dynamics trajectories: increasing the efficiency using systematic frame selection

End-point methods such as linear interaction energy (LIE) analysis, molecular mechanics generalized Born solvent-accessible surface (MM/GBSA), and solvent interaction energy (SIE) analysis have become popular techniques to calculate the free energy associated with protein-ligand binding. Such methods typically use molecular dynamics (MD) simulations to generate an ensemble of protein structures that encompasses the bound and unbound states. The energy evaluation method (LIE, MM/GBSA, or SIE) is subsequently used to calculate the energy of each member of the ensemble, thus providing an estimate of the average free energy difference between the bound and unbound states. The workflow requiring both MD simulation and energy calculation for each frame and each trajectory proves to be computationally expensive. In an attempt to reduce the high computational cost associated with end-point methods, we study several methods by which frames may be intelligently selected from the MD simulation including clustering and address the question of how the number of selected frames influences the accuracy of the SIE calculations.

Calculation of configurational entropy with a Boltzmann-quasiharmonic model: the origin of high-affinity protein-ligand binding

Accurate assessment of configurational entropy remains a large challenge in biology. While many methods exist to calculate configurational entropy, there is a balance between accuracy and computational demands. Here we calculate ligand and protein conformational entropies using the Boltzmann-quasiharmonic (BQH) method, which treats the first-order entropy term by the Boltzmann expression for entropy while determining correlations using the quasiharmonic model. This method is tested by comparison with the exact Clausius expression for entropy on a range of test molecules ranging from small ligands to a protein. Using the BQH method, we then analyze the rotational and translational (R/T) entropy change upon ligand binding for five protein complexes to explore the origins of extremely tight affinity. The results suggest that in these systems such affinity is achieved by a combination of simultaneously maintaining good protein-ligand contacts while allowing significant residual R/T motion of the ligand through suitable protein motions.

Efficient incorporation of protein flexibility and dynamics into molecular docking simulations

Flexibility and dynamics are protein characteristics that are essential for the process of molecular recognition. Conformational changes in the protein that are coupled to ligand binding are described by the biophysical models of induced fit and conformational selection. Different concepts that incorporate protein flexibility into protein-ligand docking within the context of these two models are reviewed. Several computational studies that discuss the validity and possible limitations of such approaches will be presented. Finally, different approaches that incorporate protein dynamics, e.g., configurational entropy, and solvation effects into docking will be highlighted.

New ultrahigh affinity host-guest complexes of cucurbit[7]uril with bicyclo[2.2.2]octane and adamantane guests: thermodynamic analysis and evaluation of M2 affinity calculations

A dicationic ferrocene derivative has previously been shown to bind cucurbit[7]uril (CB[7]) in water with ultrahigh affinity (ΔG(o) = -21 kcal/mol). Here, we describe new compounds that bind aqueous CB[7] equally well, validating our prior suggestion that they, too, would be ultrahigh affinity CB[7] guests. The present guests, which are based upon either a bicyclo[2.2.2]octane or adamantane core, have no metal atoms, so these results also confirm that the remarkably high affinities of the ferrocene-based guest need not be attributed to metal-specific interactions. Because we used the M2 method to compute the affinities of several of the new host-guest systems prior to synthesizing them, the present results also provide for the first blinded evaluation of this computational method. The blinded calculations agree reasonably well with experiment and successfully reproduce the observation that the new adamantane-based guests achieve extremely high affinities, despite the fact that they position a cationic substituent at only one electronegative portal of the CB[7] host. However, there are also significant deviations from experiment, and these lead to the correction of a procedural error and an instructive evaluation of the sensitivity of the calculations to physically reasonable variations in molecular energy parameters. The new experimental and computational results presented here bear on the physical mechanisms of molecular recognition, the accuracy of the M2 method, and the usefulness of host-guest systems as test-beds for computational methods.

Host-guest complexes with protein-ligand-like affinities: computational analysis and design

It has recently been discovered that guests combining a nonpolar core with cationic substituents bind cucurbit[7]uril (CB[7]) in water with ultrahigh affinities. The present study uses the Mining Minima algorithm to study the physics of these extraordinary associations and to computationally test a new series of CB[7] ligands designed to bind with similarly high affinity. The calculations reproduce key experimental observations regarding the affinities of ferrocene-based guests with CB[7] and beta-cyclodextrin and provide a coherent view of the roles of electrostatics and configurational entropy as determinants of affinity in these systems. The newly designed series of compounds is based on a bicyclo[2.2.2]octane core, which is similar in size and polarity to the ferrocene core of the existing series. Mining Minima predicts that these new compounds will, like the ferrocenes, bind CB[7] with extremely high affinities.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Evaluation of different virtual screening programs for docking in a charged binding pocket

Virtual screening of small molecules against a protein target often identifies the correct pose, but the ranking in terms of binding energy remains a difficult problem, resulting in unacceptable numbers of false positives and negatives. To investigate this problem, the performance of three docking programs, FRED, QXP/FLO, and GLIDE, along with their five different scoring functions, was evaluated with the engineered cavity in cytochrome c peroxidase (CCP). This small cavity is negatively charged and completely buried from solvent. A test set of 60 molecules, experimentally identified as 43 "binders" and 17 "non-binders", were tested with the CCP binding site. The docking methods' performance is quantified by the ROC curve and their reproduction of crystal poses. The effects from generation of different ligand tautomers and inclusion of water molecule in the cavity are also discussed.

Design of mutation-resistant HIV protease inhibitors with the substrate envelope hypothesis

There is a clinical need for HIV protease inhibitors that can evade resistance mutations. One possible approach to designing such inhibitors relies upon the crystallographic observation that the substrates of HIV protease occupy a rather constant region within the binding site. In particular, it has been hypothesized that inhibitors which lie within this region will tend to resist clinically relevant mutations. The present study offers the first prospective evaluation of this hypothesis, via computational design of inhibitors predicted to conform to the substrate envelope, followed by synthesis and evaluation against wild-type and mutant proteases, as well as structural studies of complexes of the designed inhibitors with HIV protease. The results support the utility of the substrate envelope hypothesis as a guide to the design of robust protease inhibitors.

Ligand configurational entropy and protein binding

The restriction of a small molecule's motion on binding to a protein causes a loss of configurational entropy, and thus a penalty in binding affinity. Some energy models used in computer-aided ligand design neglect this entropic penalty, whereas others account for it based on an expected drop in the number of accessible rotamers upon binding. However, the validity of the physical assumptions underlying the various approaches is largely unexamined. The present study addresses this issue by using Mining Minima calculations to analyze the association of amprenavir with HIV protease. The computed loss in ligand configurational entropy is large, contributing approximately 25 kcal/mol (4.184 kJ/kcal) to DeltaG degrees. Most of this loss results from narrower energy wells in the bound state, rather than a drop in the number of accessible rotamers. Coupling among rotation/translation and internal degrees of freedom complicates the decomposition of the entropy change into additive terms. The results highlight the potential to gain affinity by designing conformationally restricted ligands and have implications for the formulation of energy models for ligand scoring.

Protein-ligand docking: current status and future challenges

Understanding the ruling principles whereby protein receptors recognize, interact, and associate with molecular substrates and inhibitors is of paramount importance in drug discovery efforts. Protein-ligand docking aims to predict and rank the structure(s) arising from the association between a given ligand and a target protein of known 3D structure. Despite the breathtaking advances in the field over the last decades and the widespread application of docking methods, several downsides still exist. In particular, protein flexibility-a critical aspect for a thorough understanding of the principles that guide ligand binding in proteins-is a major hurdle in current protein-ligand docking efforts that needs to be more efficiently accounted for. In this review the key concepts of protein-ligand docking methods are outlined, with major emphasis being given to the general strengths and weaknesses that presently characterize this methodology. Despite the size of the field, the principal types of search algorithms and scoring functions are reviewed and the most popular docking tools are briefly depicted. Recent advances that aim to address some of the traditional limitations associated with molecular docking are also described. A selection of hand-picked examples is used to illustrate these features.

Structural and functional evidence for the role of the TLR2 DD loop in TLR1/TLR2 heterodimerization and signaling

The Toll/Interleukin-1 receptor (TIR) domain of the Toll-like receptors (TLRs) plays an important role in innate host defense signaling. The TIR-TIR platform formed by the dimerization of two TLRs promotes homotypic protein-protein interactions with additional cytoplasmic adapter molecules to form an active signaling complex resulting in the expression of pro- and anti-inflammatory cytokine genes. To generate a better understanding of the functional domains of TLR2 we performed a random mutagenesis analysis of the human TLR2 TIR domain and screened for TLR2/1 signaling-deficient mutants. Based upon the random mutagenesis results, we performed an alanine scanning mutagenesis of the TLR2 DD loop and part of the alphaD region. This resulted in the identification of four residues crucial for TLR2/1 signaling: Arg-748, Phe-749, Leu-752, and Arg-753. Computer-assisted energy minimization and docking studies indicated three regions of interaction in the TLR2/1 TIR-docked heterodimer. In Region I, residues Arg-748 and Phe-749 in TLR2 DD loop were involved in close contacts with Gly-676 in the TLR1 BB loop. Because this model suggested that steric hindrance would significantly alter the binding interactions between DD loop of TLR2 and BB loop of TLR1, Gly-676 in TLR1 was rationally mutated to Ala and Leu. As expected, in vitro functional studies involving TLR1 G676A and TLR1 G676L resulted in reduced PAM(3)CSK(4) mediated NF-kappaB activation lending support to the computerized predictions. Additionally, mutation of an amino acid residue (TLR2 Asp-730) in Region II also resulted in decreased activity in agreement with our model, providing new insights into the structure-function relationship of TLR2/1 TIR domains.

Screening Drug-Like Compounds by Docking to Homology Models: A Systematic Study

In the absence of an experimentally solved structure, a homology model of a protein target can be used instead for virtual screening of drug candidates by docking and scoring. This approach poses a number of questions regarding the choice of the template to use in constructing the model, the accuracy of the screening results, and the importance of allowing for protein flexibility. The present study addresses such questions with compound screening calculations for multiple homology models of five drug targets. A central result is that docking to homology models frequently yields enrichments of known ligands as good as that obtained by docking to a crystal structure of the actual target protein. Interestingly, however, standard measures of the similarity of the template used to build the homology model to the targeted protein show little correlation with the effectiveness of the screening calculations, and docking to the template itself often is as successful as docking to the corresponding homology model. Treating key side chains as mobile produces a modest improvement in the results. The reasons for these sometimes unexpected results, and their implications for future methodologic development, are discussed.

Comparative evaluation of eight docking tools for docking and virtual screening accuracy

Eight docking programs (DOCK, FLEXX, FRED, GLIDE, GOLD, SLIDE, SURFLEX, and QXP) that can be used for either single-ligand docking or database screening have been compared for their propensity to recover the X-ray pose of 100 small-molecular-weight ligands, and for their capacity to discriminate known inhibitors of an enzyme (thymidine kinase) from randomly chosen "drug-like" molecules. Interestingly, both properties are found to be correlated, since the tools showing the best docking accuracy (GLIDE, GOLD, and SURFLEX) are also the most successful in ranking known inhibitors in a virtual screening experiment. Moreover, the current study pinpoints some physicochemical descriptors of either the ligand or its cognate protein-binding site that generally lead to docking/scoring inaccuracies.

Free energy, entropy, and induced fit in host-guest recognition: calculations with the second-generation mining minima algorithm

This study applies a novel computational method to study molecular recognition for three sets of synthetic hosts: molecular clips, molecular tweezers, and a synthetic barbiturate receptor. The computed standard free energies of binding for the 12 binding reactions agree closely with experiment and provide insight into the roles of configurational entropy, preorganization, and induced fit in the systems studied. The computed changes in configurational entropy are comparable in magnitude to the changes in mean potential plus solvation energy, and they result primarily from changes in the average width of the energy wells upon binding. A strong correlation is observed between the changes in configurational energy and configurational entropy upon binding, resulting in near-linear compensation analogous to classical entropy-enthalpy compensation.

Comparing Ligand Interactions with Multiple Receptors via Serial Docking

Standard uses of ligand-receptor docking typically focus on the association of candidate ligands with a single targeted receptor, but actual applications increasingly require comparisons across multiple receptors. This study demonstrates that comparative docking to multiple receptors can help to select homology models for virtual compound screening and to discover ligands that bind to one set of receptors but not to another, potentially similar, set. A serial docking algorithm is furthermore described that reduces the computational costs of such calculations by testing compounds against a series of receptor structures and discarding a compound as soon as it fails to satisfy specified bind/no bind criteria for each receptor. The algorithm also realizes substantial efficiencies by taking advantage of the fact that a ligand typically binds in similar conformations to similar receptors. Thus, once detailed docking has been used to fit a ligand into the first of a series of similar receptors, much less extensive calculations can be used for the remaining structures.

Calculation of cyclodextrin binding affinities: energy, entropy, and implications for drug design

The second generation Mining Minima method yields binding affinities accurate to within 0.8 kcal/mol for the associations of alpha-, beta-, and gamma-cyclodextrin with benzene, resorcinol, flurbiprofen, naproxen, and nabumetone. These calculations require hours to a day on a commodity computer. The calculations also indicate that the changes in configurational entropy upon binding oppose association by as much as 24 kcal/mol and result primarily from a narrowing of energy wells in the bound versus the free state, rather than from a drop in the number of distinct low-energy conformations on binding. Also, the configurational entropy is found to vary substantially among the bound conformations of a given cyclodextrin-guest complex. This result suggests that the configurational entropy must be accounted for to reliably rank docked conformations in both host-guest and ligand-protein complexes. In close analogy with the common experimental observation of entropy-enthalpy compensation, the computed entropy changes show a near-linear relationship with the changes in mean potential plus solvation energy.

Structural model for an AxxxG-mediated dimer of surfactant-associated protein C

The pulmonary surfactant prevents alveolar collapse and is required for normal pulmonary function. One of the important components of the surfactant besides phospholipids is surfactant-associated protein C (SP-C). SP-C shows complex oligomerization behavior and a transition to beta-amyloid-like fibril structures, which are not yet fully understood. Besides this nonspecific oligomerization, MS and chemical cross-linking data combined with CD spectra provide evidence of a specific, mainly alpha-helical, dimer at low to neutral pH. Furthermore, resistance to CNBr cleavage and dual NMR resonances of porcine and human recombinant SP-C with Met32 replaced by isoleucine point to a dimerization site located at the C-terminus of the hydrophobic alpha-helix of SP-C, where a strictly conserved heptapeptide sequence is found. Computational docking of two SP-C helices, described here, reveals a dimer with a helix-helix interface that strikingly resembles that of glycophorin A and is mediated by an AxxxG motif similar to the experimentally determined GxxxG pattern of glycophorin A. It is highly likely that mature SP-C adopts such a dimeric structure in the lamellar bilayer systems found in the surfactant. Dimerization has been shown in previous studies to have a role in sorting and trafficking of SP-C and may also be important to the surfactant function of this protein.

Tork: Conformational analysis method for molecules and complexes

A conformational search method for organic molecules and bimolecular complexes is presented. The method, termed Tork, uses normal-mode analysis in bond-angle-torsion coordinates and focuses on a key subset of torsional coordinates to identify natural molecular motions that lead the initial conformation to new energy minima. New conformations are generated via distortion along these modes and their pairwise combinations, followed by energy minimization. For complexes, special treatment is accorded to the six coordinates that specify the position and orientation of one molecule relative to the other. Tests described here show that Tork is highly efficient for cyclic, acyclic, and mixed single molecules, as well as for host-guest complexes.

LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites

We present a new shape-based method, LigandFit, for accurately docking ligands into protein active sites. The method employs a cavity detection algorithm for detecting invaginations in the protein as candidate active site regions. A shape comparison filter is combined with a Monte Carlo conformational search for generating ligand poses consistent with the active site shape. Candidate poses are minimized in the context of the active site using a grid-based method for evaluating protein-ligand interaction energies. Errors arising from grid interpolation are dramatically reduced using a new non-linear interpolation scheme. Results are presented for 19 diverse protein-ligand complexes. The method appears quite promising, reproducing the X-ray structure ligand pose within an RMS of 2A in 14 out of the 19 complexes. A high-throughput screening study applied to the thymidine kinase receptor is also presented in which LigandFit, when combined with LigScore, an internally developed scoring function, yields very good hit rates for a ligand pool seeded with known actives.

Enhanced docking with the mining minima optimizer: acceleration and side-chain flexibility

The ligand-protein docking algorithm based on the Mining Minima method has been substantially enhanced. First, the basic algorithm is accelerated by: (1) adaptively determining the extent of each energy well to help avoid previously discovered energy minima; (2) biasing the search away from ligand positions at the surface of the receptor to prevent the ligand from staying at the surface when large sampling regions are used; (3) quickly testing multiple different ligand positions and orientations for each ligand conformation; and (4) tuning the source code to increase computational efficiency. These changes markedly shorten the time needed to discover an accurate result, especially when large sampling regions are used. The algorithm now also allows user-selected receptor sidechains to be treated as mobile during the docking procedure. The energies associated with the mobile side chains are computed as if they belonged to the ligand, except that atoms at the boundary between side chains and the rigid backbone are treated specially. This new capability is tested for several well-known ligand/protein systems, and preliminary application to an enzyme whose substrate is unknown--the recently solved hypothetical protein YecO (HI0319) from Haemophilus influenzae--indicates that side-chains relaxations allow candidate substrates of various sizes to be accommodated.

On the calculation of absolute macromolecular binding free energies

The standard framework for calculating the absolute binding free energy of a macromolecular association reaction A + B --> AB with an association constant K(AB) is to equate chemical potentials of the species on the left- and right-hand sides of this reaction and evaluate the chemical potentials from theory. This theory involves (usually hidden) assumptions about what constitutes the bound species, AB, and where the contribution of the solvent appears. We present here an alternative derivation that can be traced back to Bjerrum, in which the expectation value of K(AB) is obtained directly through the statistical mechanical method of evaluating its ensemble (Boltzmann-weighted) average. The generalized Bjerrum approach more clearly delineates: (i) the different contributions to binding; (ii) the origin of the much-discussed and somewhat controversial association entropy term; and (iii) where the solvent contribution appears. This approach also allows approximations required for practical evaluation of the binding constant in complex macromolecular systems, to be introduced in a well defined way. We provide an example, with application to test cases that illustrate a range of binding behavior.

Lead discovery using molecular docking

As the structures of more and more proteins and nucleic acids become available, molecular docking is increasingly considered for lead discovery. Recent studies consider the hit-rate enhancement of docking screens and the accuracy of docking structure predictions. As more structures are determined experimentally, docking against homology-modeled targets also becomes possible for more proteins. With more docking studies being undertaken, the 'drug-likeness' and specificity of docking hits is also being examined.

A review of protein-small molecule docking methods

The binding of small molecule ligands to large protein targets is central to numerous biological processes. The accurate prediction of the binding modes between the ligand and protein, (the docking problem) is of fundamental importance in modern structure-based drug design. An overview of current docking techniques is presented with a description of applications including single docking experiments and the virtual screening of databases.

Evaluation of docking functions for protein-ligand docking

Docking functions are believed to be the essential component of docking algorithms. Both physically and statistically based functions have been proposed, but there is no consensus about their relative performances. Here, we propose an evaluation approach based on exhaustive enumeration of all possible docking solutions obtained with a discretized description of a rigid docking process. We apply the approach to study both molecular mechanics and statistical potentials. It is found that the statistical potential evaluated is less effective than the AMBER molecular mechanics function to provide an accurate description of the docking process when the exact experimental coordinates are used. However, when coordinates of crystal structures obtained with analogous ligands are used, similar performances are obtained in both cases. Possible reasons for the successes and failures of both docking schemes have been uncovered using linear discriminant analysis, on the basis of a set of physicochemical descriptors capturing the main physical effects at play during protein-ligand docking. In both types of potentials steric effects appear critical to obtain a successful docking. Our results also indicate that neglecting desolvation effects and the explicit treatment of hydrogen bonds are the main source of the failures observed with the molecular mechanics potential. On the other hand, detailed consideration of steric interactions, with a careful treatment of dispersive forces, seems to be needed when using statistical potentials derived from a structural database. The possibility of filtering combinatorial libraries in order to maximize the probability of correct docking is discussed.

High-throughput docking for lead generation

Recent improvements in flexible docking technology may lead to a bigger role for computational methods in lead discovery. Although fast and accurate computational prediction of binding affinities for an arbitrary molecule is still beyond the limits of current methods, the docking and screening procedures can select small sets of likely lead candidates from large libraries of either commercially or synthetically available compounds.

Interpreting trends in the binding of cyclic ureas to HIV-1 protease

The design of new HIV protease inhibitors requires an improved understanding of the physical basis of inhibitor/protein binding. Here, the binding affinities of seven aliphatic cyclic ureas to HIV-1 protease are calculated using a predominant states method and an implicit solvent model based upon finite difference solutions of the Poisson-Boltzmann equation. The calculations are able to reproduce the observed U-shaped trend of binding free energy as a function of aliphatic chain length. Interestingly, the decrease in affinity for the longest chains is attributable primarily to the energy cost of partly desolvating charged aspartic and arginine groups at the mouths of the active site. Even aliphatic chains too short to contact these charged groups directly are subject to considerable desolvation penalties. We are not aware of other systems where binding affinity trends have been attributed to long-ranged electrostatic desolvation of ionized groups. A generalized Born/surface area solvation model yields a much smaller change in desolvation energy with chain length and, therefore, does not reproduce the experimental binding affinity trends. This result suggests that the generalized Born model should be used with caution for complex, partly desolvated systems like protein binding sites. We also find that changing the assumed protonation state of the active site aspartyl dyad significantly affects the computed binding affinity trends. The protonation state of the aspartyl dyad in the presence of cyclic ureas is discussed in light of the observation that the monoprotonated state reproduces the experimental results best.