Flexible protein‐ligand docking using the Fleksy protocol

Considering protein plasticity is important in accurately predicting the three‐dimensional geometry of protein‐ligand complexes. Here, we present the first public release of our flexible docking tool Fleksy, which is able to consider both ligand and protein flexibility in the docking process. We describe the workflow and different features of the software and present its performance on two cross‐docking benchmark datasets. © 2012 Wiley Periodicals, Inc.     

GRID: A high‐resolution protein structure refinement algorithm

The energy‐based refinement of protein structures generated by fold prediction algorithms to atomic‐level accuracy remains a major challenge in structural biology. Energy‐based refinement is mainly dependent on two components: (1) sufficiently accurate force fields, and (2) efficient conformational space search algorithms. Focusing on the latter, we developed a high‐resolution refinement algorithm called GRID. It takes a three‐dimensional protein structure as input and, using an all‐atom force field, attempts to improve the energy of the structure by systematically perturbing backbone dihedrals and side‐chain rotamer conformations. We compare GRID to Backrub, a stochastic algorithm that has been shown to predict a significant fraction of the conformational changes that occur with point mutations. We applied GRID and Backrub to 10 high‐resolution (≤ 2.8 Å) crystal structures from the Protein Data Bank and measured the energy improvements obtained and the computation times required to achieve them. GRID resulted in energy improvements that were significantly better than those attained by Backrub while expending about the same amount of computational resources. GRID resulted in relaxed structures that had slightly higher backbone RMSDs compared to Backrub relative to the starting crystal structures. The average RMSD was 0.25 ± 0.02 Å for GRID versus 0.14 ± 0.04 Å for Backrub. These relatively minor deviations indicate that both algorithms generate structures that retain their original topologies, as expected given the nature of the algorithms. © 2012 Wiley Periodicals, Inc.     

FIPSDock: A new molecular docking technique driven by fully informed swarm optimization algorithm

The accurate prediction of protein–ligand binding is of great importance for rational drug design. We present herein a novel docking algorithm called as FIPSDock, which implements a variant of the Fully Informed Particle Swarm (FIPS) optimization method and adopts the newly developed energy function of AutoDock 4.20 suite for solving flexible protein–ligand docking problems. The search ability and docking accuracy of FIPSDock were first evaluated by multiple cognate docking experiments. In a benchmarking test for 77 protein/ligand complex structures derived from GOLD benchmark set, FIPSDock has obtained a successful predicting rate of 93.5% and outperformed a few docking programs including particle swarm optimization (PSO)@AutoDock, SODOCK, AutoDock, DOCK, Glide, GOLD, FlexX, Surflex, and MolDock. More importantly, FIPSDock was evaluated against PSO@AutoDock, SODOCK, and AutoDock 4.20 suite by cross‐docking experiments of 74 protein–ligand complexes among eight protein targets (CDK2, ESR1, F2, MAPK14, MMP8, MMP13, PDE4B, and PDE5A) derived from Sutherland‐crossdock‐set. Remarkably, FIPSDock is superior to PSO@AutoDock, SODOCK, and AutoDock in seven out of eight cross‐docking experiments. The results reveal that FIPS algorithm might be more suitable than the conventional genetic algorithm‐based algorithms in dealing with highly flexible docking problems. © 2012 Wiley Periodicals, Inc.     

Low-mode conformational search elucidated: Application to C39H80 and flexible docking of 9-deazaguanine inhibitors into PNP

We previously described a new conformational search method, termed low-mode search (LMOD), and discussed its utility for conformational searches performed on cycloalkanes and a cyclic penta-peptide. 1 In this report, we discuss a rigorous implementation of mode following (c-LMOD) for conformational searching, and we demonstrate that for a conformational search involving cycloheptadecane, this rigorous implementation is capable of finding all of the previously known structures. To the best of our knowledge, this is the first computational proof that mode following can be used for conformational searches conducted on a complex molecular system. We show, however, that, as expected, it is generally inefficient to perform a conformational search in this manner. Nonetheless, c-LMOD has been shown to be an excellent method for conducting conformational analyses involving conformational interconversions, where the location of saddle points is important. We also describe refinement to our original LMOD procedure (l-LMOD) and discuss its utility for a difficult conformational search problem, namely locating the global minimum energy conformation of C₃₉H₈₀. For this search, l-LMOD combined with limited torsional Monte Carlo movement was able to locate the lowest energy structures yet reported, and significantly outperformed a pure torsional Monte Carlo and a genetic algorithm-based search. Furthermore, we also demonstrate the utility of l-LMOD combined with random translation/rotation of a ligand for the extremely difficult problem of docking flexible ligands into flexible protein binding sites on a system that includes 9-deaza-guanine-based inhibitors docked into the flexible biding site of PNP. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1671–1684, 1999     

Flexible ligand docking using a robust evolutionary algorithm

A flexible ligand docking protocol based on evolutionary algorithms is investigated. The proposed approach incorporates family competition and adaptive rules to integrate decreasing‐based mutations and self‐adaptive mutations to act as global and local search strategies, respectively. The method is applied to a dihydrofolate reductase enzyme with the anticancer drug methotrexate and two analogues of antibacterial drug trimethoprim. Conformations and orientations closed to the crystallographically determined structures are obtained, as well as alternative structures with low energy. Numerical results indicate that the new approach is very robust. The docked lowest‐energy structures have root‐mean‐square derivations ranging from 0.67 to 1.96 Å with respect to the corresponding crystal structures. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 988–998, 2000     

Protein farnesyltransferase: Flexible docking studies on inhibitors using computational modeling

Summary Using MacroModel, peptide, peptidomimetic and non-peptidomimetic inhibitors of the zinc metalloenzyme, farnesyltransferase (FTase), were docked into the enzyme binding site. Inhibitor flexibility, farnesyl pyrophosphate substrate flexibility, and partial protein flexibility were taken into account in these docking studies. In addition to CVFM and CVIM, as well as our own inhibitors FTI-276 and FTI-2148, we have docked other farnesyltransferase inhibitors (FTIs) including Zarnestra, which presently is in advanced clinical trials. The AMBER* force field was employed, augmented with parameters that were derived for zinc. A single binding site model that was derived from the crystal structure of CVFM complexed with farnesyltransferase and farnesylpyrophosphate was used for these studies. The docking results using the lowest energy structure from the simulation, or one of the lowest energy structures, were generally in excellent agreement with the X-ray structures. One of the most important findings of this study is that numerous alternative conformations for the methionine side chain can be accommodated by the enzyme suggesting that the methionine pocket can tolerate groups larger than methionine at the C-terminus of the tetrapeptide and suggesting alternative locations for the placement of side chains that may improve potency.     

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     

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.     

A nonredundant structure dataset for benchmarking protein‐RNA computational docking

Protein–RNA interactions play an important role in many biological processes. The ability to predict the molecular structures of protein–RNA complexes from docking would be valuable for understanding the underlying chemical mechanisms. We have developed a novel nonredundant benchmark dataset for protein–RNA docking and scoring. The diverse dataset of 72 targets consists of 52 unbound–unbound test complexes, and 20 unbound–bound test complexes. Here, unbound–unbound complexes refer to cases in which both binding partners of the cocrystallized complex are either in apo form or in a conformation taken from a different protein–RNA complex, whereas unbound–bound complexes are cases in which only one of the two binding partners has another experimentally determined conformation. The dataset is classified into three categories according to the interface root mean square deviation and the percentage of native contacts in the unbound structures: 49 easy, 16 medium, and 7 difficult targets. The bound and unbound cases of the benchmark dataset are expected to benefit the development and improvement of docking and scoring algorithms for the docking community. All the easy‐to‐view structures are freely available to the public at http://zoulab.dalton.missouri.edu/RNAbenchmark/ . © 2012 Wiley Periodicals, Inc.     

Fast and accurate grid representations for atom‐based docking with partner flexibility

Macromolecular docking methods can broadly be divided into geometric and atom‐based methods. Geometric methods use fast algorithms that operate on simplified, grid‐like molecular representations, while atom‐based methods are more realistic and flexible, but far less efficient. Here, a hybrid approach of grid‐based and atom‐based docking is presented, combining precalculated grid potentials with neighbor lists for fast and accurate calculation of atom‐based intermolecular energies and forces. The grid representation is compatible with simultaneous multibody docking and can tolerate considerable protein flexibility. When implemented in our docking method ATTRACT, grid‐based docking was found to be ∼35x faster. With the OPLSX forcefield instead of the ATTRACT coarse‐grained forcefield, the average speed improvement was >100x. Grid‐based representations may allow atom‐based docking methods to explore large conformational spaces with many degrees of freedom, such as multiple macromolecules including flexibility. This increases the domain of biological problems to which docking methods can be applied. © 2017 Wiley Periodicals, Inc.     

Efficiency of tabu‐search‐based conformational search algorithms

Efficient conformational search or sampling approaches play an integral role in molecular modeling, leading to a strong demand for even faster and more reliable conformer search algorithms. This article compares the efficiency of a molecular dynamics method, a simulated annealing method, and the basin hopping (BH) approach (which are widely used in this field) with a previously suggested tabu‐search‐based approach called gradient only tabu search (GOTS). The study emphasizes the success of the GOTS procedure and, more importantly, shows that an approach which combines BH and GOTS outperforms the single methods in efficiency and speed. We also show that ring structures built by a hydrogen bond are useful as starting points for conformational search investigations of peptides and organic ligands with biological activities, especially in structures that contain multiple rings. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

Exploring hierarchical refinement techniques for induced fit docking with protein and ligand flexibility

We present a series of molecular‐mechanics‐based protein refinement methods, including two novel ones, applied as part of an induced fit docking procedure. The methods used include minimization; protein and ligand sidechain prediction; a hierarchical ligand placement procedure similar to a‐priori protein loop predictions; and a minimized Monte Carlo approach using normal mode analysis as a move step. The results clearly indicate the importance of a proper opening of the active site backbone, which might not be accomplished when the ligand degrees of freedom are prioritized. The most accurate method consisted of the minimized Monte Carlo procedure designed to open the active site followed by a hierarchical optimization of the sidechain packing around a mobile flexible ligand. The methods have been used on a series of 88 protein‐ligand complexes including both cross‐docking and apo‐docking members resulting in complex conformations determined to within 2.0 Å heavy‐atom RMSD in 75% of cases where the protein backbone rearrangement upon binding is less than 1.0 Å α‐carbon RMSD. We also demonstrate that physics‐based all‐atom potentials can be more accurate than docking‐style potentials when complexes are sufficiently refined. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Predicting the accuracy of protein–ligand docking on homology models

Ligand–protein docking is increasingly used in Drug Discovery. The initial limitations imposed by a reduced availability of target protein structures have been overcome by the use of theoretical models, especially those derived by homology modeling techniques. While this greatly extended the use of docking simulations, it also introduced the need for general and robust criteria to estimate the reliability of docking results given the model quality. To this end, a large‐scale experiment was performed on a diverse set including experimental structures and homology models for a group of representative ligand–protein complexes. A wide spectrum of model quality was sampled using templates at different evolutionary distances and different strategies for target–template alignment and modeling. The obtained models were scored by a selection of the most used model quality indices. The binding geometries were generated using AutoDock, one of the most common docking programs. An important result of this study is that indeed quantitative and robust correlations exist between the accuracy of docking results and the model quality, especially in the binding site. Moreover, state‐of‐the‐art indices for model quality assessment are already an effective tool for an a priori prediction of the accuracy of docking experiments in the context of groups of proteins with conserved structural characteristics. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Focused grid‐based resampling for protein docking and mapping

The fast Fourier transform (FFT) sampling algorithm has been used with success in application to protein‐protein docking and for protein mapping, the latter docking a variety of small organic molecules for the identification of binding hot spots on the target protein. Here we explore the local rather than global usage of the FFT sampling approach in docking applications. If the global FFT based search yields a near‐native cluster of docked structures for a protein complex, then focused resampling of the cluster generally leads to a substantial increase in the number of conformations close to the native structure. In protein mapping, focused resampling of the selected hot spot regions generally reveals further hot spots that, while not as strong as the primary hot spots, also contribute to ligand binding. The detection of additional ligand binding regions is shown by the improved overlap between hot spots and bound ligands. © 2016 Wiley Periodicals, Inc.     

Accounting for observed small angle X‐ray scattering profile in the protein–protein docking server cluspro

The protein‐protein docking server ClusPro is used by thousands of laboratories, and models built by the server have been reported in over 300 publications. Although the structures generated by the docking include near‐native ones for many proteins, selecting the best model is difficult due to the uncertainty in scoring. Small angle X‐ray scattering (SAXS) is an experimental technique for obtaining low resolution structural information in solution. While not sufficient on its own to uniquely predict complex structures, accounting for SAXS data improves the ranking of models and facilitates the identification of the most accurate structure. Although SAXS profiles are currently available only for a small number of complexes, due to its simplicity the method is becoming increasingly popular. Since combining docking with SAXS experiments will provide a viable strategy for fairly high‐throughput determination of protein complex structures, the option of using SAXS restraints is added to the ClusPro server. © 2015 Wiley Periodicals, Inc.     

FWAVina: A novel optimization algorithm for protein-ligand docking based on the fireworks algorithm

Protein-ligand docking is an essential process that has accelerated drug discovery. How to accurately and effectively optimize the predominant position and orientation of ligands in the binding pocket of a target protein is a major challenge. This paper proposed a novel ligand binding pose search method called FWAVina based on the fireworks algorithm, which combined the fireworks algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon local search method adopted in AutoDock Vina to address the pose search problem in docking. The FWA was used as a global optimizer to rapidly search promising poses, and the Broyden-Fletcher-Goldfarb-Shannon method was incorporated into FWAVina to perform an exact local search. FWAVina was developed and tested on the PDBbind and DUD-E datasets. The docking performance of FWAVina was compared with the original Vina program. The results showed that FWAVina achieves a remarkable execution time reduction of more than 50 % than Vina without compromising the prediction accuracies in the docking and virtual screening experiments. In addition, the increase in the number of ligand rotatable bonds has almost no effect on the efficiency of FWAVina. The higher accuracy, faster convergence and improved stability make the FWAVina method a better choice of docking tool for computer-aided drug design. The source code is available at https://github.com/eddyblue/FWAVina/.     

Hessian‐free low‐mode conformational search for large‐scale protein loop optimization: application to c‐jun N‐terminal kinase JNK3

A Hessian‐free low‐mode search algorithm has been developed for large‐scale conformational searching. The new method is termed LLMOD, and it utilizes the ARPACK package to compute low‐mode eigenvectors of a Hessian matrix that is only referenced implicitly, through its product with a series of vectors. The Hessian × vector product is calculated utilizing a finite difference formula based on gradients. LLMOD is the first conformational search method that can be applied to fully flexible, unconstrained protein structures for complex loop optimization problems. LLMOD has been tested on a particularly difficult model system, c‐jun N‐terminal kinase JNK3. We demonstrate that LLMOD was able to correct a P38/ERK2/HCL‐based homology model that grossly misplaced the crucial glycine‐rich loop in the ATP‐binding site. © 2000 John Wiley & Sons, Inc. J Comput Chem 22: 21–30, 2001     

Cluster expansion models for flexible‐backbone protein energetics

Protein structure prediction and design often involve discrete modeling of side‐chain conformations on structural templates. Introducing backbone flexibility into such models has proven important in many different applications. Backbone flexibility improves model accuracy and provides access to larger sequence spaces in computational design, although at a cost in complexity and time. Here, we show that the influence of backbone flexibility on protein conformational energetics can be treated implicitly, at the level of sequence, using the technique of cluster expansion. Cluster expansion provides a way to convert structure‐based energies into functions of sequence alone. It leads to dramatic speed‐ups in energy evaluation and provides a convenient functional form for the analysis and optimization of sequence‐structure relationships. We show that it can be applied effectively to flexible‐backbone structural models using four proteins: α‐helical coiled‐coil dimers and trimers, zinc fingers, and Bcl‐x_L/peptide complexes. For each of these, low errors for the sequence‐based models when compared with structure‐based evaluations show that this new way of treating backbone flexibility has considerable promise, particularly for protein design. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009     

Synthesis of novel VO (II)‐thaizole complexes; spectral,conformational characterization,MOE‐docking and genotoxicity

New VO (II)‐thaizolyl hydrazine complexes were synthesized and characterized by analytical, spectral and theoretical techniques. Bi‐nuclear complexes were suggested for all synthesizes upon neutral poly‐dentate mode of bonding. UV–Vis and EPR spectra, proposed two structural geometries as, square‐planer and octahedral. TGA confirmed the contribution of solvent molecules through physical and/or coordinate‐bonding. XRD parameters calculated, displayed outstanding nanometer‐sizes for all nano‐crystalline compounds, which suffering slight imperfections. Also, SEM images showed, spherical‐shape that observed for most topographic particulates. Conformational study executed for all new synthesizes, demonstrated their optimized structural‐forms. Furthermore, important physical parameters were computed that predict essential characteristics as, biological efficiency. Predictable parameters as softness and electrophilicity, point to priority of VO (II)‐4d complex. Genotoxic study, was already examined, for all new synthesizes, against CT‐DNA and displayed complete deterioration for DNA, by influence of most tested compounds. Moreover, MOE‐docking technique, was executed against receptors of Y‐family DNA‐polymerase (4irk) and Key‐Enzyme Linking‐Metabolic Inflammation (4cyf). This docking study displayed the following ascending order; VO (II)‐4c,4irk ? VO (II)‐4d,4cyf ? VO (II)‐4c, 4cyf ? VO (II)‐4b, 4cyf, based on scoring‐energy values. This study concluded with promising prediction of these complexes in relation to DNA‐polymerase as well as inflammation enzyme that compared with known anti‐inflammatory drug (meloxicam).     

Virtual‐system‐coupled adaptive umbrella sampling to compute free‐energy landscape for flexible molecular docking

A novel enhanced conformational sampling method, virtual‐system‐coupled adaptive umbrella sampling (V‐AUS), was proposed to compute 300‐K free‐energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V‐AUS was applied to complex formation of two disordered amyloid‐β (Aβ_30–35) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300‐K free‐energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β‐sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V‐AUS converged to uniform distribution more effectively than conventional AUS sampling did. © 2015 Wiley Periodicals, Inc.