GalaxyDock2: Protein–ligand docking using beta‐complex and global optimization

In this article, an enhanced version of GalaxyDock protein–ligand docking program is introduced. GalaxyDock performs conformational space annealing (CSA) global optimization to find the optimal binding pose of a ligand both in the rigid‐receptor mode and the flexible‐receptor mode. Binding pose prediction has been improved compared to the earlier version by the efficient generation of high‐quality initial conformations for CSA using a predocking method based on a beta‐complex derived from the Voronoi diagram of receptor atoms. Binding affinity prediction has also been enhanced by using the optimal combination of energy components, while taking into consideration the energy of the unbound ligand state. The new version has been tested in terms of binding mode prediction, binding affinity prediction, and virtual screening on several benchmark sets, showing improved performance over the previous version and AutoDock, on which the GalaxyDock energy function is based. GalaxyDock2 also performs better than or comparable to other state‐of‐the‐art docking programs. GalaxyDock2 is freely available at http://galaxy.seoklab.org/softwares/galaxydock.html . © 2013 Wiley Periodicals, Inc.     

Understanding the chiral recognitions between neuraminidases and inhibitors: Studies with DFT,docking, and MD methods

The chiral recognitions between various neuraminidases (NA) and 5‐[(1R,2S)‐1‐(acetylamino)‐2‐ methoxy‐2‐methylpentyl]‐4‐[(1Z)‐1‐propenyl)‐(4S,5R)]‐D‐proline (BL) stereoisomers have been theoretically studied. The zwitterions of BL are responsible for the bioactivities, and electrostatic rather than van der Waals (vdW) contributions play a significant role. With the presence of NA proteins, the orders of relative stabilities of the BL stereoisomers are greatly altered; meanwhile, the ranges are significantly enlarged, ensuring the respective recognitions of the BL9z, BL3z, BL2z, and BL1z stereoisomers by the N1, N2, N9 subtype, and B type NA proteins. It is mainly due to geometric complementarities of the NA active sites with the BL carboxyl and propenyl groups. The recognitions of proteins with chiral ligands are rather targeted, even applicable to N2 and N9 with high structural similarities. Thus, the significance of chirality is addressed for the designs of anti‐influenza drugs, which aids our understanding of chiral recognitions between proteins and ligands. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2011     

Assessing protein–ligand docking for the binding of organometallic compounds to proteins

Organometallic compounds are increasingly used as molecular scaffolds in drug development projects; their structural and electronic properties offering novel opportunities in protein–ligand complementarities. Interestingly, while protein–ligand dockings have long become a spearhead in computer assisted drug design, no benchmarking nor optimization have been done for their use with organometallic compounds. Pursuing our efforts to model metal mediated recognition processes, we herein present a systematic study of the capabilities of the program GOLD to predict the interactions of protein with organometallic compounds. The study focuses on inert systems for which no alteration of the first coordination sphere of the metal occurs upon binding. Several scaffolds are used as test systems with different docking schemes and scoring functions. We conclude that ChemScore is the most robust scoring function with ASP and ChemPLP providing with good results too and GoldScore slightly underperforming. This study shows that current state‐of‐the‐art protein‐ligand docking techniques are reliable for the docking of inert organometallic compounds binding to protein. © 2013 Wiley Periodicals, Inc.     

Binding structures of tri‐N‐acetyl‐β‐glucosamine in hen egg white lysozyme using molecular dynamics with a polarizable force field

Lysozyme is a well‐studied enzyme that hydrolyzes the β‐(1,4)‐glycosidic linkage of N‐acetyl‐β‐glucosamine (NAG)_n oligomers. The active site of hen egg‐white lysozyme (HEWL) is believed to consist of six subsites, A‐F that can accommodate six sugar residues. We present studies exploring the use of polarizable force fields in conjunction with all‐atom molecular dynamics (MD) simulations to analyze binding structures of complexes of lysozyme and NAG trisaccharide, (NAG)₃. MD trajectories are applied to analyze structures and conformation of the complex as well as protein–ligand interactions, including the hydrogen‐bonding network in the binding pocket. Two binding modes (ABC and BCD) of (NAG)₃ are investigated independently based on a fixed‐charge model and a polarizable model. We also apply molecular mechanics with generalized born and surface area (MM‐GBSA) methods based on MD using both nonpolarizable and polarizable force fields to compute binding free energies. We also study the correlation between root‐mean‐squared deviation and binding free energies of the wildtype and W62Y mutant; we find that for this prototypical system, approaches using the MD trajectories coupled with implicit solvent models are equivalent for polarizable and fixed‐charge models. © 2012 Wiley Periodicals, Inc.     

Gaussian mapping of chemical fragments in ligand binding sites

We present a new approach to automatically define a quasi-optimal minimal set of pharmacophoric points mapping the interaction properties of a user-defined ligand binding site. The method is based on a fitting algorithm where a grid of sampled interaction energies of the target protein with small chemical fragments in the binding site is approximated by a linear expansion of Gaussian functions. A heuristic approximation selects from this expansion the smallest possible set of Gaussians required to describe the interaction properties of the binding site within a prespecified accuracy. We have evaluated the performance of the approach by comparing the computed Gaussians with the positions of aromatic sites found in experimental protein-ligand complexes. For a set of 53 complexes, good correspondence is found in general. At a 95% significance level, approximately 65% of the predicted interaction points have an aromatic binding site within 1.5 A. We then studied the utility of these points in docking using the program DOCK. Short docking times, with an average of approximately 0.18 s per conformer, are obtained, while retaining, both for rigid and flexible docking, the ability to sample native-like binding modes for the ligand. An average 4-5-fold speed-up in docking times and a similar success rate is estimated with respect to the standard DOCK protocol.     

Multiple ligand simultaneous docking: Orchestrated dancing of ligands in binding sites of protein

Present docking methodologies simulate only one single ligand at a time during docking process. In reality, the molecular recognition process always involves multiple molecular species. Typical protein–ligand interactions are, for example, substrate and cofactor in catalytic cycle; metal ion coordination together with ligand(s); and ligand binding with water molecules. To simulate the real molecular binding processes, we propose a novel multiple ligand simultaneous docking (MLSD) strategy, which can deal with all the above processes, vastly improving docking sampling and binding free energy scoring. The work also compares two search strategies: Lamarckian genetic algorithm and particle swarm optimization, which have respective advantages depending on the specific systems. The methodology proves robust through systematic testing against several diverse model systems: E. coli purine nucleoside phosphorylase (PNP) complex with two substrates, SHP2NSH2 complex with two peptides and Bcl‐xL complex with ABT‐737 fragments. In all cases, the final correct docking poses and relative binding free energies were obtained. In PNP case, the simulations also capture the binding intermediates and reveal the binding dynamics during the recognition processes, which are consistent with the proposed enzymatic mechanism. In the other two cases, conventional single‐ligand docking fails due to energetic and dynamic coupling among ligands, whereas MLSD results in the correct binding modes. These three cases also represent potential applications in the areas of exploring enzymatic mechanism, interpreting noisy X‐ray crystallographic maps, and aiding fragment‐based drug design, respectively. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

A randomized kinematics‐based approach to pharmacophore‐constrained conformational search and database screening

Computational tools have greatly expedited the pharmaceutical drug design process in recent years. One common task in this process is the search of a large library for small molecules that can achieve both a low‐energy conformation and a prescribed pharmacophore. The pharmacophore expresses constraints on the 3D structure of the molecule by specifying relative atom positions that should be maintained to increase the likelihood that the molecule will bind with the receptor site. This article presents a pharmacophore‐based database screening system that has been designed, implemented, and tested on a molecular database. The primary focus of this article is on a simple, randomized conformational search technique that attempts to simultaneously reduce energy and maintain pharmacophore constraints. This enables the identification of molecules in a database that are likely to dock with a given protein, which can serve as a powerful aid in the search for better drug candidates. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 731–747, 2000     

Update of the ATTRACT force field for the prediction of protein–protein binding affinity

Determining the protein–protein interactions is still a major challenge for molecular biology. Docking protocols has come of age in predicting the structure of macromolecular complexes. However, they still lack accuracy to estimate the binding affinities, the thermodynamic quantity that drives the formation of a complex. Here, an updated version of the protein–protein ATTRACT force field aiming at predicting experimental binding affinities is reported. It has been designed on a dataset of 218 protein–protein complexes. The correlation between the experimental and predicted affinities reaches 0.6, outperforming most of the available protocols. Focusing on a subset of rigid and flexible complexes, the performance raises to 0.76 and 0.69, respectively. © 2017 Wiley Periodicals, Inc.     

Combining the polarizable Drude force field with a continuum electrostatic Poisson–Boltzmann implicit solvation model

In this work, we have combined the polarizable force field based on the classical Drude oscillator with a continuum Poisson–Boltzmann/solvent‐accessible surface area (PB/SASA) model. In practice, the positions of the Drude particles experiencing the solvent reaction field arising from the fixed charges and induced polarization of the solute must be optimized in a self‐consistent manner. Here, we parameterized the model to reproduce experimental solvation free energies of a set of small molecules. The model reproduces well‐experimental solvation free energies of 70 molecules, yielding a root mean square difference of 0.8 kcal/mol versus 2.5 kcal/mol for the CHARMM36 additive force field. The polarization work associated with the solute transfer from the gas‐phase to the polar solvent, a term neglected in the framework of additive force fields, was found to make a large contribution to the total solvation free energy, comparable to the polar solute–solvent solvation contribution. The Drude PB/SASA also reproduces well the electronic polarization from the explicit solvent simulations of a small protein, BPTI. Model validation was based on comparisons with the experimental relative binding free energies of 371 single alanine mutations. With the Drude PB/SASA model the root mean square deviation between the predicted and experimental relative binding free energies is 3.35 kcal/mol, lower than 5.11 kcal/mol computed with the CHARMM36 additive force field. Overall, the results indicate that the main limitation of the Drude PB/SASA model is the inability of the SASA term to accurately capture non‐polar solvation effects. © 2018 Wiley Periodicals, Inc.     

A new peptide docking strategy using a mean field technique with mutually orthogonal Latin square sampling

The theoretical prediction of the association of a flexible ligand with a protein receptor requires efficient sampling of the conformational space of the ligand. Several docking methodologies are currently available. We propose a new docking technique that performs well at low computational cost. The method uses mutually orthogonal Latin squares to efficiently sample the docking space. A variant of the mean field technique is used to analyze this sample to arrive at the optimum. The method has been previously applied to explore the conformational space of peptides and identify structures with low values for the potential energy. Here we extend this method to simultaneously identify both the low energy conformation as well as a ‘high-scoring’ docking mode. Application of the method to 56 protein–peptide complexes, in which the length of the peptide ligand ranges from three to seven residues, and comparisons with Autodock 3.05, showed that the method works well. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Enhancing the accuracy of virtual screening: molecular dynamics with quantum-refined force fields

Summary A methodology aimed at improving the accuracy of current docking–scoring procedures is proposed, and validated through detailed tests of its performance in predicting the activity of HIV-1 protease inhibitors. This methodology is based on molecular dynamics simulations using a force field whose effective charges are refined by means of a novel procedure that relies on quantum-mechanical calculations and preserves the internal consistency of the parameterization scheme.     

Extension of the CHARMM general force field to sulfonyl‐containing compounds and its utility in biomolecular simulations

Presented is an extension of the CHARMM General Force Field (CGenFF) to enable the modeling of sulfonyl‐containing compounds. Model compounds containing chemical moieties such as sulfone, sulfonamide, sulfonate, and sulfamate were used as the basis for the parameter optimization. Targeting high‐level quantum mechanical and experimental crystal data, the new parameters were optimized in a hierarchical fashion designed to maintain compatibility with the remainder of the CHARMM additive force field. The optimized parameters satisfactorily reproduced equilibrium geometries, vibrational frequencies, interactions with water, gas phase dipole moments, and dihedral potential energy scans. Validation involved both crystalline and liquid phase calculations showing the newly developed parameters to satisfactorily reproduce experimental unit cell geometries, crystal intramolecular geometries, and pure solvent densities. The force field was subsequently applied to study conformational preference of a sulfonamide based peptide system. Good agreement with experimental IR/NMR data further validated the newly developed CGenFF parameters as a tool to investigate the dynamic behavior of sulfonyl groups in a biological environment. CGenFF now covers sulfonyl group containing moieties allowing for modeling and simulation of sulfonyl‐containing compounds in the context of biomolecular systems including compounds of medicinal interest. © 2012 Wiley Periodicals, Inc.     

Stabilizer‐Guided Inhibition of Protein–Protein Interactions

The discovery of novel protein–protein interaction (PPI) modulators represents one of the great molecular challenges of the modern era. PPIs can be modulated by either inhibitor or stabilizer compounds, which target different though proximal regions of the protein interface. In principle, protein–stabilizer complexes can guide the design of PPI inhibitors (and vice versa). In the present work, we combine X‐ray crystallographic data from both stabilizer and inhibitor co‐crystal complexes of the adapter protein 14‐3‐3 to characterize, down to the atomic scale, inhibitors of the 14‐3‐3/Tau PPI, a potential drug target to treat Alzheimer’s disease. The most potent compound notably inhibited the binding of phosphorylated full‐length Tau to 14‐3‐3 according to NMR spectroscopy studies. Our work sets a precedent for the rational design of PPI inhibitors guided by PPI stabilizer–protein complexes while potentially enabling access to new synthetically tractable stabilizers of 14‐3‐3 and other PPIs.     

Evaluation of the searching abilities of HBOP and HBSITE for binding pocket detection

We evaluated the pocket‐searching abilities of the computer programs HBOP and HBSITE, in which hydrophobic potentials calculated on grid points generated around a protein function as an indicator of the pocket‐like property‐using a test set of 458 experimentally observed structures of protein–ligand complexes. The results were compared with those obtained using the alternative algorithms PASS and SiteID, which only consider geometric properties, and Q‐SiteFinder, which considers not only geometry but also physicochemical properties. The comparison revealed that HBOP and HBSITE could detect experimentally observed ligand‐binding pockets for more test complexes than PASS and SiteID. In addition, the success rate of HBOP for detecting binding pockets was higher than that of Q‐SiteFinder, and that of HBSITE was comparable with that of Q‐SiteFinder. Results of tests for ligand‐unbound state proteins indicated that HBSITE was more appropriate than Q‐SiteFinder for pocket searches of ligand‐unbound proteins, and HBSITE was more robust than Q‐SiteFinder against structural differences between ligand‐bound and ‐unbound state proteins. © 2009 Wiley Periodicals, Inc. J Comput Chem 2009     

Thermodynamic Parameters for the Association of Fluorinated Benzenesulfonamides with Bovine Carbonic Anhydrase II

This paper describes a calorimetric study of the association of a series of seven fluorinated benzenesulfonamide ligands (C₆H_nF_5?nSO₂NH₂) with bovine carbonic anhydrase II (BCA). Quantitative structure–activity relationships between the free energy, enthalpy, and entropy of binding and pK_a and log P of the ligands allowed the evaluation of the thermodynamic parameters in terms of the two independent effects of fluorination on the ligand: its electrostatic potential and its hydrophobicity. The parameters were partitioned to the three different structural interactions between the ligand and BCA: the Zn^II cofactor–sulfonamide bond (≈65 % of the free energy of binding), the hydrogen bonds between the ligand and BCA (≈10 %), and the contacts between the phenyl ring of the ligand and BCA (≈25 %). Calorimetry revealed that all of the ligands studied bind in a 1:1 stoichiometry with BCA; this result was confirmed by ¹⁹F NMR spectroscopy and X‐ray crystallography (for complexes with human carbonic anhydrase II).