Niu Huang

Determination of Electrostatic Parameters for a Polarizable Force Field Based on the Classical Drude Oscillator

A procedure to determine the electrostatic parameters has been developed for a polarizable empirical force field based on the classical Drude oscillator model. Atomic charges and polarizabilities for a given molecule of interest were derived from restrained fitting to quantum-mechanical electrostatic potentials (ESP) calculated at the B3LYP/ cc-pVDZ or B3LYP/aug-cc-pVDZ levels on grid points located on concentric Connolly surfaces. The determination of the atomic polarizabilities requires a series of perturbed ESP maps, each one representing the electronic response of the molecule in the presence of a background charge placed on Connolly surfaces primarily along chemical bonds and lone pairs. Reference values for the partial atomic charges were taken from the CHARMM27 additive all-atom force field, and those for the polarizabilities were based on adjusted Millers ahp atomic polarizability values. The fitted values of atomic polarizabilities were scaled to reflect the reduced polarization expected for the condensed media and/or to correct for the systematic underestimation of experimental molecular polarizabilities by B3LYP calculations. Following correction of the polarizabilities, the atomic charges were adjusted to reproduce gas-phase dipole moments. The developed scheme has been tested on a set of small molecules representing functional moieties of nucleic acids. The derived electrostatic parameters have been successfully applied in a preliminary polarizable molecular dynamics simulation of a DNA octamer in a box of water with sodium counterions. Thus, this study confirms the feasibility of the use of a polarizable force field based on a classical Drude model for simulations of biomolecules in the condensed phase.

Automated Docking Screens: A Feasibility Study

Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 Å rmsd 50−60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 Å rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org.

Consideration of Molecular Weight during Compound Selection in Virtual Target-Based Database Screening

Virtual database screening allows for millions of chemical compounds to be computationally selected based on structural complimentary to known inhibitors or to a target binding site on a biological macromolecule. Compound selection in virtual database screening when targeting a biological macromolecule is typically based on the interaction energy between the chemical compound and the target macromolecule. In the present study it is shown that this approach is biased toward the selection of high molecular weight compounds due to the contribution of the compound size to the energy score. To account for molecular weight during energy based screening, we propose normalization strategies based on the total number of heavy atoms in the chemical compounds being screened. This approach is computationally efficient and produces molecular weight distributions of selected compounds that can be selected to be (1) lower than that of the original database used in the virtual screening, which may be desirable for selection of leadlike compounds or (2) similar to that of the original database, which may be desirable for the selection of drug-like compounds. By eliminating the bias in target-based database screening toward higher molecular weight compounds it is anticipated that the proposed procedure will enhance the success rate of computer-aided drug design.

Physics-Based Scoring of Protein−Ligand Complexes: Enrichment of Known Inhibitors in Large-Scale Virtual Screening

We demonstrate that using an all-atom molecular mechanics force field combined with an implicit solvent model for scoring protein-ligand complexes is a promising approach for improving inhibitor enrichment in the virtual screening of large compound databases. The rescoring method is evaluated by the extent to which known binders for nine diverse, therapeutically relevant enzymes are enriched against a background of approximately 100,000 drug-like decoys. The improvement in enrichment is most robust and dramatic within the top 1% of the ranked database, that is, the first thousand compounds; below the first few percent of the ranked database, there is little overall improvement. The improved early enrichment is likely due to the more realistic treatment of ligand and receptor desolvation in the rescoring procedure. We also present anecdotal but encouraging results assessing the ability of the rescoring method to predict specificity of inhibitors for structurally related proteins.

Molecular mechanics methods for predicting protein–ligand binding

Ligand binding affinity prediction is one of the most important applications of computational chemistry. However, accurately ranking compounds with respect to their estimated binding affinities to a biomolecular target remains highly challenging. We provide an overview of recent work using molecular mechanics energy functions to address this challenge. We briefly review methods that use molecular dynamics and Monte Carlo simulations to predict absolute and relative ligand binding free energies, as well as our own work in which we have developed a physics-based scoring method that can be applied to hundreds of thousands of compounds by invoking a number of simplifying approximations. In our previous studies, we have demonstrated that our scoring method is a promising approach for improving the discrimination between ligands that are known to bind and those that are presumed not to, in virtual screening of large compound databases. In new results presented here, we explore several improvements to our computational method including modifying the dielectric constant used for the protein and ligand interiors, and empirically scaling energy terms to compensate for deficiencies in the energy model. Future directions for further improving our physics-based scoring method are also discussed.

Protein-facilitated base flipping in DNA by cytosine-5-methyltransferase

DNA methylation, various DNA repair mechanisms, and possibly early events in the opening of DNA as required for transcription and replication are initiated by flipping of a DNA base out of the DNA double helix. The energetics and structural mechanism of base flipping in the presence of the DNA-processing enzyme, cytosine 5-methyltransferase from HhaI (M.HhaI), were obtained through molecular dynamics based upon free-energy calculations. Free-energy profiles for base flipping show that, when in the closed conformation, M.HhaI lowers the free-energy barrier to flipping by 17 kcal/mol and stabilizes the fully flipped state. Flipping is shown to occur via the major groove of the DNA. Structural analysis indicates that flipping is facilitated by destabilization of the DNA double-helical structure and substitution of DNA base-pairing and base-stacking interactions with DNA–protein interactions. The fully flipped state is stabilized by DNA–protein interactions that are enhanced upon binding of coenzyme. This study represents an atomic detail description of the mechanism by which a protein facilitates specific structural distortion in DNA.

Molecular Determinants of Enterovirus 71 Viral Entry CLEFT AROUND GLN-172 ON VP1 PROTEIN INTERACTS WITH VARIABLE REGION ON SCAVENGE RECEPTOR B 2

Background: SCARB2 is the cellular receptor for EV71. Results: Seven highly variable amino acids on SCARB2 and a region in proximity to residue Gln-172 of VP1 are critical for EV71 infection. Conclusion: EV71 might adopt the canyon receptor engagement mode for viral entry. Significance: Elucidation of receptor and viral determinants revealed a possible target for anti-EV71 interventions. Enterovirus 71 (EV71) is one of the major pathogens that cause hand, foot, and mouth disease outbreaks in young children in the Asia-Pacific region in recent years. Human scavenger receptor class B 2 (SCARB2) is the main cellular receptor for EV71 on target cells. The requirements of the EV71-SCARB2 interaction have not been fully characterized, and it has not been determined whether SCARB2 serves as an uncoating receptor for EV71. Here we compared the efficiency of the receptor from different species including human, horseshoe bat, mouse, and hamster and demonstrated that the residues between 144 and 151 are critical for SCARB2 binding to viral capsid protein VP1 of EV71 and seven residues from the human receptor could convert murine SCARB2, an otherwise inefficient receptor, to an efficient receptor for EV71 viral infection. We also identified that EV71 binds to SCARB2 via a canyon of VP1 around residue Gln-172. Soluble SCARB2 could convert the EV71 virions from 160 S to 135 S particles, indicating that SCARB2 is an uncoating receptor of the virus. The uncoating efficiency of SCARB2 significantly increased in an acidic environment (pH 5.6). These studies elucidated the viral capsid and receptor determinants of enterovirus 71 infection and revealed a possible target for antiviral interventions.

Structural basis for activation and inhibition of the secreted chlamydia protease CPAF

The obligate intracellular pathogen Chlamydia trachomatis is the most common cause of sexually transmitted bacterial disease. It secretes a protease known as chlamydial protease/proteasome-like activity factor (CPAF) that degrades many host molecules and plays a major role in Chlamydia pathogenesis. Here, we show that mature CPAF is a homodimer of the catalytic domains, each of which comprises two distinct subunits. Dormancy of the CPAF zymogen is maintained by an internal inhibitory segment that binds the CPAF active site and blocks its homodimerization. CPAF activation is initiated by trans-autocatalytic cleavage, which induces homodimerization and conformational changes that assemble the catalytic triad. This assembly leads to two autocatalytic cleavages and removal of the inhibitory segment, enabling full CPAF activity. CPAF is covalently bound and inhibited by the proteasome inhibitor lactacystin. These results reveal the activation mechanism of the CPAF serine protease and suggest new opportunities for anti-Chlamydia drug development.

A bacterial type III effector family uses the papain-like hydrolytic activity to arrest the host cell cycle

Pathogenic bacteria deliver effector proteins into host cells through the type III secretion apparatus to modulate the host function. We identify a family of proteins, homologous to the type III effector Cif from enteropathogenic Escherichia coli, in pathogens including Yersinia, Photorhabdus, and Burkholderia that contain functional type III secretion systems. Like Cif, this family of proteins is capable of arresting the host cell cycle at G2/M. Structure of one of the family members, Cif homolog in Burkholderia pseudomallei (CHBP), reveals a papain-like fold and a conserved Cys-His-Gln catalytic triad despite the lack of primary sequence identity. For CHBP and Cif, only the putative catalytic Cys is susceptible to covalent modification by E-64, a specific inhibitor of papain-like cysteine proteases. Unlike papain-like enzymes where the S2 site is the major determinant of cleavage-site specificity, CHBP has a characteristic negatively charged pocket occupying surface areas corresponding to the S1/S1′ site in papain-like proteases. The negative charge is provided by a conserved aspartate, and the pocket best fits an arginine, as revealed by molecular docking analysis. Mutation analysis establishes the essential role of the catalytic triad and the negatively charged pocket in inducing cell cycle arrest in host cells. Our results demonstrate that bacterial pathogens have evolved a unique papain-like hydrolytic activity to block the normal host cell cycle progression.

Binding-site assessment by virtual fragment screening.

The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules) would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock ∼11000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates measured experimentally in a previously published NMR-based screening method. Secondly, we show that the in silico fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors.