Structural dissection of sequence recognition and catalytic mechanism of human LINE-1 endonuclease

Long interspersed nuclear element-1 (L1) is an autonomous non-LTR retrotransposon comprising ∼20% of the human genome. L1 self-propagation causes genomic instability and is strongly associated with aging, cancer and other diseases. The endonuclease domain of L1’s ORFp2 protein (L1-EN) initiates de novo L1 integration by nicking the consensus sequence 5′-TTTTT/AA-3′. In contrast, related nucleases including structurally conserved apurinic/apyrimidinic endonuclease 1 (APE1) are non-sequence specific. To investigate mechanisms underlying sequence recognition and catalysis by L1-EN, we solved crystal structures of L1-EN complexed with DNA substrates. This showed that conformational properties of the preferred sequence drive L1-EN’s sequence-specificity and catalysis. Unlike APE1, L1-EN does not bend the DNA helix, but rather causes ‘compression’ near the cleavage site. This provides multiple advantages for L1-EN’s role in retrotransposition including facilitating use of the nicked poly-T DNA strand as a primer for reverse transcription. We also observed two alternative conformations of the scissile bond phosphate, which allowed us to model distinct conformations for a nucleophilic attack and a transition state that are likely applicable to the entire family of nucleases. This work adds to our mechanistic understanding of L1-EN and related nucleases and should facilitate development of L1-EN inhibitors as potential anticancer and antiaging therapeutics.

Mosquito Acetylcholinesterase as a Target for Novel Phenyl-Substituted Carbamates

New insecticides are needed for control of disease-vectoring mosquitoes and this research evaluates the activity of new carbamate acetylcholinesterase (AChE) inhibitors. Biochemical and toxicological characterization of carbamates based on the parent structure of terbam, 3-tert-butylphenyl methylcarbamate, was performed. In vitro enzyme inhibition selectivity (Anopheles gambiae versus human) was assessed by the Ellman assay, as well as the lethality to whole insects by the World Health Organization (WHO) paper contact assay. Bromination at the phenyl C6 position increased inhibitory potency to both AChEs, whereas a 6-iodo substituent led to loss of potency, and both halogenations caused a significant reduction of mosquitocidal activity. Similarly, installation of a hexyl substituent at C6 drastically reduced inhibition of AgAChE, but showed a smaller reduction in the inhibition of hAChE. A series of 4-carboxamido analogs of the parent compound gave reduced activity against AgAChE and generally showed more activity against hAChE than AgAChE. Replacement of the 3-t-buyl group with CF₃ resulted in poor anticholinesterase activity, but this compound did have measurable mosquitocidal activity. A series of methyl- and fluoro- analogs of 3-trialkylsilyl compounds were also synthesized, but unfortunately resulted in disappointing activity. Finally, a series of sulfenylated proinsecticides showed poor paper contact toxicity, but one of them had topical activity against adult female Anopheles gambiae. Overall, the analogs prepared here contributed to a better understanding of carbamate structure–activity relationships (SAR), but no new significant leads were generated.

Select β- and γ-branched 1-alkylpyrazol-4-yl methylcarbamates exhibit high selectivity for inhibition of Anopheles gambiae versus human acetylcholinesterase

The widespread emergence of pyrethroid-resistant Anopheles gambiae has intensified the need to find new contact mosquitocides for indoor residual spraying and insecticide treated nets. With the goal of developing new species-selective and resistance-breaking acetylcholinesterase (AChE)-inhibiting mosquitocides, in this report we revisit the effects of carbamate substitution on aryl carbamates, and variation of the 1-alkyl group on pyrazol-4-yl methylcarbamates. Compared to aryl methylcarbamates, aryl dimethylcarbamates were found to have lower selectivity for An. gambiae AChE (AgAChE) over human AChE (hAChE), but improved tarsal contact toxicity to G3 strain An. gambiae. Molecular modeling studies suggest the lower species-selectivity of the aryl dimethylcarbamates can be attributed to a less flexible acyl pocket in AgAChE relative to hAChE. The improved tarsal contact toxicity of the aryl dimethylcarbamates relative to the corresponding methylcarbamates is attributed to a range of complementary phenomena. With respect to the pyrazol-4-yl methylcarbamates, the previously observed low An. gambiae-selectivity of compounds bearing α-branched 1-alkyl groups was improved by employing β- and γ-branched 1-alkyl groups. Compounds 22a (cyclopentylmethyl), 21a (cyclobutylmethyl), and 26a (3-methylbutyl) offer 250-fold, 120-fold, and 96-fold selectivity, respectively, for inhibition of AgAChE vs. hAChE. Molecular modeling studies suggests the high species-selectivity of these compounds can be attributed to the greater mobility of the W84 side chain in the choline-binding site of AgAChE, compared to that of W86 in hAChE. Compound 26a has reasonable contact toxicity to G3 strain An. gambiae (LC₅₀ = 269 μg/mL) and low cross-resistance to Akron strain (LC₅₀ = 948 μg/mL), which bears the G119S resistance mutation.

Discovery of Species-selective and Resistance-breaking Anticholinesterase Insecticides for the Malaria Mosquito

Great reductions in malaria mortality have been accomplished in the last 15 years, in part due to the widespread roll-out of insecticide-treated bednets across sub-Saharan Africa. To date, these nets only employ pyrethroids, insecticides that target the voltage-gated sodium ion channel of the malaria vector, Anopheles gambiae. Due to the growing emergence of An. gambiae strains that are resistant to pyrethroids, there is an urgent need to develop new public health insecticides that engage a different target and possess low mammalian toxicity. In this review, we will describe efforts to develop highly species-specific and resistance-breaking inhibitors of An. gambiae acetylcholinesterase (AgAChE). These efforts have been greatly aided by advances in knowledge of the structure of the enzyme, and two major inhibitor design strategies have been explored. Since AgAChE possesses an unpaired Cys residue not present in mammalian AChE, a logical strategy to achieve selective inhibition involves design of compounds that could ligate that Cys. A second strategy involves the design of new molecules to target the catalytic serine of the enzyme. Here the challenge is not only to achieve high inhibition selectivity vs human AChE, but also to demonstrate toxicity to An. gambiae that carry the G119S resistance mutation of AgAChE. The advances made and challenges remaining will be presented. This review is part of the special issue "Insecticide Mode of Action: From Insect to Mammalian Toxicity".

V1V2 multivalent scaffolds induce focused antibody responses with functional activity, prolonged durability, and modest neutralization potency

The V1V2 region of HIV-1 gp120 is vulnerable to a group of broadly neutralizing monoclonal antibodies (bnMAbs), and RV144 vaccinees developed strongly binding Abs to this region that correlated with a reduced risk of infection. This region of Env is now recognized as an important vaccine target, notwithstanding its relatively poorly immunogenic epitopes. We hypothesized that presenting V1V2 in multivalent scaffolds could improve immunogenicity and structurally constraining the epitopes could induce a more focused immune response in animal models. We designed of a panel of immunogens engrafting the V1V2 domain into trimeric and pentameric scaffolds. Here, we report results of immunogenicity studies in nonhuman primates (NHP) with 2 different V1V2 trimeric scaffolds. Our experimental approach in NHP consisted of 3 DNA and protein co-immunizations and a single protein boost. The DNA components consisted of 50μg of ZM109 gp120 plasmid delivered by gene gun with a simultaneous intramuscular injection of 100 μg of V1V2 scaffold protein immunogens. NHP immune responses were specific for V1V2 conformational epitopes with cross-reactive binding to heterologous gp120s and were functionally active in phagocytosis assays. Notably, V1V2 binding Ab responses were detectable 2 years after immunizations ceased. Neutralizing Abs developed in vaccinated NHP to Tier 1A and 1B, Clade B and Clade C viruses. The V1V2 structurally constrained scaffolds show promise as novel and highly effective at inducing functional antibody responses specifically targeted to the epitopes presented. Our results advance pre-clinical data in support of developing V1V2 vaccine candidates despite the structural complexity of the region.

Funding: P01AI100151-03

Structure/Function Studies Involving the V3 Region of the HIV-1 Envelope Delineate Multiple Factors That Affect Neutralization Sensitivity

Antibodies (Abs) specific for the V3 loop of the HIV-1 gp120 envelope neutralize most tier 1 and many tier 2 viruses and are present in essentially all HIV-infected individuals as well as immunized humans and animals. Vaccine-induced V3 Abs are associated with reduced HIV infection rates in humans and affect the nature of transmitted viruses in infected vaccinees, despite the fact that V3 is often occluded in the envelope trimer. Here, we link structural and experimental data showing how conformational alterations of the envelope trimer render viruses exceptionally sensitive to V3 Abs. The experiments interrogated the neutralization sensitivity of pseudoviruses with single amino acid mutations in various regions of gp120 that were predicted to alter packing of the V3 loop in the Env trimer. The results indicate that the V3 loop is metastable in the envelope trimer on the virion surface, flickering between states in which V3 is either occluded or available for binding to chemokine receptors (leading to infection) and to V3 Abs (leading to virus neutralization). The spring-loaded V3 in the envelope trimer is easily released by disruption of the stability of the V3 pocket in the unliganded trimer or disruption of favorable V3/pocket interactions. Formation of the V3 pocket requires appropriate positioning of the V1V2 domain, which is, in turn, dependent on the conformation of the bridging sheet and on the stability of the V1V2 B-C strand-connecting loop.

IMPORTANCE

The levels of antibodies to the third variable region (V3) of the HIV envelope protein correlate with reduced HIV infection rates. Previous studies showed that V3 is often occluded, as it sits in a pocket of the envelope trimer on the surface of virions; however, the trimer is flexible, allowing occluded portions of the envelope (like V3) to flicker into an exposed position that binds antibodies. Here we provide a systematic interrogation of mechanisms by which single amino acid changes in various regions of gp120 (i) render viruses sensitive to neutralization by V3 antibodies, (ii) result in altered packing of the V3 loop, and (iii) activate an open conformation that exposes V3 to the effects of V3 Abs. Taken together, these and previous studies explain how V3 antibodies can protect against HIV-1 infection and why they should be one of the targets of vaccine-induced antibodies.

FOCUS--Development of a Global Communication and Modeling Platform for Applied and Computational Medicinal Chemists

Communication of data and ideas within a medicinal chemistry project on a global as well as local level is a crucial aspect in the drug design cycle. Over a time frame of eight years, we built and optimized FOCUS, a platform to produce, visualize, and share information on various aspects of a drug discovery project such as cheminformatics, data analysis, structural information, and design. FOCUS is tightly integrated with internal services that involve-among others-data retrieval systems and in-silico models and provides easy access to automated modeling procedures such as pharmacophore searches, R-group analysis, and similarity searches. In addition, an interactive 3D editor was developed to assist users in the generation and docking of close analogues of a known lead. In this paper, we will specifically concentrate on issues we faced during development, deployment, and maintenance of the software and how we continually adapted the software in order to improve usability. We will provide usage examples to highlight the functionality as well as limitations of FOCUS at the various stages of the development process. We aim to make the discussion as independent of the software platform as possible, so that our experiences can be of more general value to the drug discovery community.

Docking to multiple pockets or ligand fields for screening, activity prediction and scaffold hopping

BACKGROUND

Two recent technological advances dramatically reducing the rate of false-negatives in activity prediction by docking flexible 3D models of compounds include multi-conformational docking (mPockDock) and the docking of candidates to atomic property fields derived by co-crystallized ligands (mApfDock).

RESULTS

The mApfDock and mPockDock provide the AUC of 90.4 and 83.8%, respectively. The mApfDock gave better performance when compounds required large induced-fit pocket changes unseen in crystallography, whereas the mPockDock is superior when the co-crystallized ligands do not represent sufficient chemical and binding location diversity.

CONCLUSION

Both approaches proved to be efficient for scaffold hopping; they are complementary when the coverage of the co-crystallized complexes is poor but become convergent when the complexes are diverse enough.

ALiBERO: evolving a team of complementary pocket conformations rather than a single leader

Docking and virtual screening (VS) reach maximum potential when the receptor displays the structural changes needed for accurate ligand binding. Unfortunately, these conformational changes are often poorly represented in experimental structures or homology models, debilitating their docking performance. Recently, we have shown that receptors optimized with our LiBERO method (Ligand-guided Backbone Ensemble Receptor Optimization) were able to better discriminate active ligands from inactives in flexible-ligand VS docking experiments. The LiBERO method relies on the use of ligand information for selecting the best performing individual pockets from ensembles derived from normal-mode analysis or Monte Carlo. Here we present ALiBERO, a new computational tool that has expanded the pocket selection from single to multiple, allowing for automatic iteration of the sampling-selection procedure. The selection of pockets is performed by a dual method that uses exhaustive combinatorial search plus individual addition of pockets, selecting only those that maximize the discrimination of known actives compounds from decoys. The resulting optimized pockets showed increased VS performance when later used in much larger unrelated test sets consisting of biologically active and inactive ligands. In this paper we will describe the design and implementation of the algorithm, using as a reference the human estrogen receptor alpha.

Spatial chemical distance based on atomic property fields

Similarity of compound chemical structures often leads to close pharmacological profiles, including binding to the same protein targets. The opposite, however, is not always true, as distinct chemical scaffolds can exhibit similar pharmacology as well. Therefore, relying on chemical similarity to known binders in search for novel chemicals targeting the same protein artificially narrows down the results and makes lead hopping impossible. In this study we attempt to design a compound similarity/distance measure that better captures structural aspects of their pharmacology and molecular interactions. The measure is based on our recently published method for compound spatial alignment with atomic property fields as a generalized 3D pharmacophoric potential. We optimized contributions of different atomic properties for better discrimination of compound pairs with the same pharmacology from those with different pharmacology using Partial Least Squares regression. Our proposed similarity measure was then tested for its ability to discriminate pharmacologically similar pairs from decoys on a large diverse dataset of 115 protein–ligand complexes. Compared to 2D Tanimoto and Shape Tanimoto approaches, our new approach led to improvement in the area under the receiver operating characteristic curve values in 66 and 58% of domains respectively. The improvement was particularly high for the previously problematic cases (weak performance of the 2D Tanimoto and Shape Tanimoto measures) with original AUC values below 0.8. In fact for these cases we obtained improvement in 86% of domains compare to 2D Tanimoto measure and 85% compare to Shape Tanimoto measure. The proposed spatial chemical distance measure can be used in virtual ligand screening.

Computer applications for prediction of protein-protein interactions and rational drug design

In recent years, protein-protein interactions are becoming the object of increasing attention in many different fields, such as structural biology, molecular biology, systems biology, and drug discovery. From a structural biology perspective, it would be desirable to integrate current efforts into the structural proteomics programs. Given that experimental determination of many protein-protein complex structures is highly challenging, and in the context of current high-performance computational capabilities, different computer tools are being developed to help in this task. Among them, computational docking aims to predict the structure of a protein-protein complex starting from the atomic coordinates of its individual components, and in recent years, a growing number of docking approaches are being reported with increased predictive capabilities. The improvement of speed and accuracy of these docking methods, together with the modeling of the interaction networks that regulate the most critical processes in a living organism, will be essential for computational proteomics. The ultimate goal is the rational design of drugs capable of specifically inhibiting or modifying protein-protein interactions of therapeutic significance. While rational design of protein-protein interaction inhibitors is at its very early stage, the first results are promising.

Optimal docking area: a new method for predicting protein-protein interaction sites

Understanding energetics and mechanism of protein-protein association remains one of the biggest theoretical problems in structural biology. It is assumed that desolvation must play an essential role during the association process, and indeed protein-protein interfaces in obligate complexes have been found to be highly hydrophobic. However, the identification of protein interaction sites from surface analysis of proteins involved in non-obligate protein-protein complexes is more challenging. Here we present Optimal Docking Area (ODA), a new fast and accurate method of analyzing a protein surface in search of areas with favorable energy change when buried upon protein-protein association. The method identifies continuous surface patches with optimal docking desolvation energy based on atomic solvation parameters adjusted for protein-protein docking. The procedure has been validated on the unbound structures of a total of 66 non-homologous proteins involved in non-obligate protein-protein hetero-complexes of known structure. Optimal docking areas with significant low-docking surface energy were found in around half of the proteins. The 'ODA hot spots' detected in X-ray unbound structures were correctly located in the known protein-protein binding sites in 80% of the cases. The role of these low-surface-energy areas during complex formation is discussed. Burial of these regions during protein-protein association may favor the complexed configurations with near-native interfaces but otherwise arbitrary orientations, thus driving the formation of an encounter complex. The patch prediction procedure is freely accessible at http://www.molsoft.com/oda and can be easily scaled up for predictions in structural proteomics.

Rapid boundary element solvation electrostatics calculations in folding simulations: successful folding of a 23-residue peptide

Solvation effects play a profound role in the energetics of protein folding. While a continuum dielectric model of solvation may provide a sufficiently accurate estimate of the solvation effects, until now this model was too computationally expensive and unstable for folding simulations. Here we proposed a fast yet accurate and robust implementation of the boundary element solution of the Poisson equation, the REBEL algorithm. Using our earlier double-energy scheme, we included for the first time the mathematically rigorous continuous REBEL solvation term in our Biased Probability Monte Carlo (BPMC) simulations of the peptide folding. The free energy of a 23-residue beta beta alpha-peptide was then globally optimized with and without the solvation electrostatics contribution. An ensemble of beta beta alpha conformations was found at and near the global minimum of the energy function with the REBEL electrostatic solvation term. Much poorer correspondence to the native solution structure was found in the "control" simulations with a traditional method to account for solvation via a distance-dependent dielectric constant. Each simulation took less than 40 h (21 h without electrostatic solvation calculation) on a single Alpha 677 MHz CPU and involved more than 40,000 solvation energy evaluations. This work demonstrates for the first time that such a simulation can be performed in a realistic time frame. The proposed procedure may eliminate the energy evaluation accuracy bottleneck in folding simulations.

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.

Expression of the adenovirus receptor and its interaction with the fiber knob

The coxsackievirus group B (CVB) and adenovirus (Ad) receptor (HCVADR, formerly HCAR) is a cell surface protein with two immunoglobulin-like regions (IG1 and IG2) that serves as a receptor for two structurally unrelated viruses. We have established the tissue distribution of the receptor in the rodent by immunohistochemistry and show that the receptor is broadly expressed during embryonic development in the central and peripheral nervous systems and in several types of epithelial cells. The tissue distribution is more restricted in the adult but remains high mainly in epithelial cells. Using site-directed mutagenesis, based on computer modeling of the IG1 region, Ad5 binding could be inhibited but CVB attachment was unaffected. A double amino acid substitution in a three-stranded anti-parallel beta sheet that may form a face of the receptor completely inhibited Ad5 binding. Therefore, we conclude that the molecular interactions critical for Ad5 binding to HCVADR do not overlap with those of CVB3. In fact a specific antibody interfering with only CVB binding recognizes the IG2 domain in the receptor, suggesting that the CVB interacts with this region or an overlap between the IG1 and the IG2 regions.

Prediction of the binding energy for small molecules, peptides and proteins

A fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. Knowledge-based scoring schemes may not be sufficiently general and transferable, while molecular dynamics or Monte Carlo calculations with explicit solvent are too computationally expensive for many applications. Recently, several empirical schemes using finite difference Poisson-Boltzmann electrostatics to predict energies for particular types of complexes were proposed. Here, an improved empirical binding energy function has been derived and validated on three different types of complexes: protein-small ligand, protein-peptide and protein-protein. The function uses the boundary element algorithm to evaluate the electrostatic solvation energy. We show that a single set of parameters can predict the relative binding energies of the heterogeneous validation set of complexes with 2.5 kcal/mol accuracy. We also demonstrate that global optimization of the ligand and of the flexible side-chains of the receptor improves the accuracy of the evaluation.

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

Eight protein-ligand complexes were simulated by using global optimization of a complex energy function, including solvation, surface tension, and side-chain entropy in the internal coordinate space of the flexible ligand and the receptor side chains [Abagyan, R.A., Totrov, M.M. J. Mol. Biol. 235: 983-1002, 1994]. The procedure uses two types of efficient random moves, a pseudobrownian positional move [Abagyan, R.A., Totrov, M.M., Kuznetsov, D.A. J. Comp. Chem. 15:488-506, 1994] and a Biased-Probability multitorsion move [Abagyan, R.A., Totrov, M.M. J. Mol. Biol. 235: 983-1002, 1994], each accompanied by full local energy minimization. The best docking solutions were further ranked according to the interaction energy, which included intramolecular deformation energies of both receptor and ligand, the interaction energy, surface tension, side-chain entropic contribution, and an electrostatic term evaluated as a boundary element solution of the Poisson equation with the molecular surface as a dielectric boundary. The geometrical accuracy of the docking solutions ranged from 30% to 70% according to the relative displacement error measure at a 1.5 A scale. Similar results were obtained when the explicit receptor atoms were replaced with a grid potential.

Homology modeling with internal coordinate mechanics: deformation zone mapping and improvements of models via conformational search

Five models by homology containing insertions and deletions and ranging from 33% to 48% sequence identity to the known homologue, and one high sequence identity (85%) model were built for the CASP2 meeting. For all five low identity targets: (i) our starting models were improved by the Internal Coordinate Mechanics (ICM) energy optimization, (ii) the refined models were consistently better than those built with the automatic SWISS-MODEL program, and (iii) the refined models differed by less than 2% from the best model submitted, as judged by the residue contact area difference (CAD) measure [Abagyan, R.A., Totrov, M.J. Mol. Biol. 268:678-685, 1997]. The CAD measure is proposed for ranking models built by homology instead of global root-mean-square deviation, which is frequently dominated by insignificant yet large contributions from incorrectly predicted fragments or side chains. We demonstrate that the precise identification of regions of local backbone deviation is an independent and crucial step in the homology modeling procedure after alignment, since aligned fragments can strongly deviate from the template at various distances from the alignment gap or even in the ungapped parts of the alignment. We show that a local alignment score can be used as an indicator of such local deviation. While four short loops of the meeting targets were predicted by database search, the best loop 1 target T0028, for which the correct database fragment was not found, was predicted by Internal Coordinate Mechanics global energy optimization at 1.2 A accuracy. A classification scheme for errors in homology modeling is proposed.

The hydration of globular proteins as derived from volume and compressibility measurements: cross correlating thermodynamic and structural data

We report the first thermodynamic characterization of protein hydration that does not depend on model compound data but rather is based exclusively on macroscopic (volumetric) and microscopic (X-ray) measurements on protein molecules themselves. By combining these macroscopic and microscopic characterizations, we describe a quantitative model that allows one for the first time to predict the partial specific volumes, v(zero), and the partial specific adiabatic compressibilities, ks(zero), of globular proteins from the crystallographic coordinates of the constituent atoms, without using data derived from studies on low-molecular-mass model compounds. Specifically, we have used acoustic and densimetric techniques to determine v(zero) and ks(zero) for 15 globular proteins over a temperature range from 18 to 55 degrees C. For the subset of the 12 proteins with known three-dimensional structures, we calculated the molecular volumes as well as the solvent-accessible surface areas of the constituent charged, polar and nonpolar atomic groups. By combining these measured and calculated properties and applying linear regression analysis, we determined, as a function of temperature, the average hydration contributions to v(zero) and ks(zero) of 1 A2 of the charged, polar, and nonpolar solvent-accessible protein surfaces. We compared these results with those derived from studies on low-molecular-mass compounds to assess the validity of existing models of protein hydration based on small molecule data. This comparison revealed the following features: the hydration contributions to v(zero) and ks(zero) of charged protein surface groups are similar to those of charged groups in small organic molecules. By contrast, the hydration contributions to v(zero) and ks(zero) of polar protein surface groups are qualitatively different from those of polar groups in low-molecular-mass compounds. We suggest that this disparity may reflect the presence of networks of water molecules adjacent to polar protein surface areas, with these networks involving waters from second and third coordination spheres. For nonpolar protein surface groups, we find the ability of low-molecular-mass compounds to model successfully protein properties depends on the temperature domain being examined. Specifically, at room temperatures and below, the hydration contribution to ks(zero) of protein nonpolar surface atomic groups is close to that of nonpolar groups in small organic molecules. By contrast, at higher temperatures, the hydration contribution to ks(zero) of protein nonpolar surface groups becomes more negative than that of nonpolar groups in small organic molecules. We suggest that this behaviour may reflect nonpolar groups on protein surfaces being hydrated independently at low temperatures, while at higher temperatures some of the solvating waters become influenced by neighboring polar groups. We discuss the implications of our aggregate results in terms of various approaches currently being used to describe the hydration properties of globular proteins, particularly focusing on the limitations of existing additive models based on small molecule data.

Molecular docking programs successfully predict the binding of a beta-lactamase inhibitory protein to TEM-1 beta-lactamase

Crystallization of the 1:1 molecular complex between the beta-lactamase TEM-1 and the beta-lactamase inhibitory protein BLIP has provided an opportunity to put a stringent test on current protein-docking algorithms. Prior to the successful determination of the structure of the complex, nine laboratory groups were given the refined atomic coordinates of each of the native molecules. Other than the fact that BLIP is an effective inhibitor of a number of beta-lactamase enzymes (KI for TEM-1 approximately 100 pM) no other biochemical or structural data were available to assist the practitioners in their molecular docking. In addition, it was not known whether the molecules underwent conformational changes upon association or whether the inhibition was competitive or non-competitive. All six of the groups that accepted the challenge correctly predicted the general mode of association of BLIP and TEM-1.

The contour-buildup algorithm to calculate the analytical molecular surface

A new algorithm is presented to calculate the analytical molecular surface defined as a smooth envelope traced out by the surface of a probe sphere rolled over the molecule. The core of the algorithm is the sequential build up of multi-arc contours on the van der Waals spheres. This algorithm yields substantial reduction in both memory and time requirements of surface calculations. Further, the contour-buildup principle is intrinsically "local", which makes calculations of the partial molecular surfaces even more efficient. Additionally, the algorithm is equally applicable not only to convex patches, but also to concave triangular patches which may have complex multiple intersections. The algorithm permits the rigorous calculation of the full analytical molecular surface for a 100-residue protein in about 2 seconds on an SGI indigo with R4400++ processor at 150 Mhz, with the performance scaling almost linearly with the protein size. The contour-buildup algorithm is faster than the original Connolly algorithm an order of magnitude.

Homology modeling by the ICM method

Five models have been built by the ICM method for the Comparative Modeling section of the Meeting on the Critical Assessment of Techniques for Protein Structure Prediction. The targets have homologous proteins with known three-dimensional structure with sequence identity ranging from 25 to 77%. After alignment of the target sequence with the related three-dimensional structure, the modeling procedure consists of two subproblems: side-chain prediction and loop prediction. The ICM method approaches these problems with the following steps: (1) a starting model is created based on the homologous structure with the conserved portion fixed and the nonconserved portion having standard covalent geometry and free torsion angles; (2) the Biased Probability Monte Carlo (BPMC) procedure is applied to search the subspaces of either all the nonconservative side-chain torsion angles or torsion angles in a loop backbone and surrounding side chains. A special algorithm was designed to generate low-energy loop deformations. The BPMC procedure globally optimizes the energy function consisting of ECEPP/3 and solvation energy terms. Comparison of the predictions with the NMR or crystallographic solutions reveals a high proportion of correctly predicted side chains. The loops were not correctly predicted because imprinted distortions of the backbone increased the energy of the near-native conformation and thus made the solution unrecognizable. Interestingly, the energy terms were found to be reliable and the sampling of conformational space sufficient. The implications of this finding for the strategies of future comparative modeling are discussed.

Detailed ab initio prediction of lysozyme-antibody complex with 1.6 A accuracy

The fundamental event in biological assembly is association of two biological macromolecules. Here we present a successful, accurate ab initio prediction of the binding of uncomplexed lysozyme to the HyHel5 antibody. The prediction combines pseudo Brownian Monte Carlo minimization with a biased-probability global side-chain placement procedure. It was effected in an all-atom representation, with ECEPP/2 potentials complemented with the surface energy, side-chain entropy and electrostatic polarization free energy. The near-native solution found was surprisingly close to the crystallographic structure (root-mean-square deviation of 1.57 A for all backbone atoms of lysozyme) and had a considerably lower energy (by 20 kcal mol-1) than any other solution.

Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins

Two major components are required for a successful prediction of the three-dimensional structure of peptides and proteins: an efficient global optimization procedure which is capable of finding an appropriate local minimum for the strongly anisotropic function of hundreds of variables, and a set of free energy components for a protein molecule in solution which are computationally inexpensive enough to be used in the search procedure, yet sufficiently accurate to ensure the uniqueness of the native conformation. We here found an efficient way to make a random step in a Monte Carlo procedure given knowledge of the energy or statistical properties of conformational subspaces (e.g. phi-psi zones or side-chain torsion angles). This biased probability Monte Carlo (BPMC) procedure randomly selects the subspace first, then makes a step to a new random position independent of the previous position, but according to the predefined continuous probability distribution. The random step is followed by a local minimization in torsion angle space. The positions, sizes and preferences for high-probability zones on phi-psi maps and chi-angle maps were calculated for different residue types from the representative set of 191 and 161 protein 3D-structures, respectively. A fast and precise method to evaluate the electrostatic energy of a protein in solution is developed and combined with the BPMC procedure. The method is based on the modified spherical image charge approximation, efficiently projected onto a molecule of arbitrary shape. Comparison with the finite-difference solutions of the Poisson-Boltzmann equation shows high accuracy for our approach. The BPMC procedure is applied successfully to the structure prediction of 12- and 16-residue synthetic peptides and the determination of protein structure from NMR data, with the immunoglobulin binding domain of streptococcal protein G as an example. The BPMC runs display much better convergence properties than the non-biased simulations. The advantage of a true global optimization procedure for NMR structure determination is its ability to cope with local minima originating from data errors and ambiguities in NMR data.