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Review Article *Corresponding author Khan T, Department of Chemistry, , Molecular Docking Simulation , UP, , Tel: 09793232443; Email: Submitted: 14 September 2018 with Special Reference to Flexible Accepted: 23 October 2018 Published: 25 October 2018 ISSN: 2333-6633 Docking Approach Copyright Tahmeena Khan1*, Alfred J. Lawrence2, Iqbal Azad1, Saman Raza2, and © 2018 Khan et al. Abdul Rahman Khan1 OPEN ACCESS 1Department of Chemistry, Integral University, India 2Department of Chemistry, College, India Keywords • Docking • Flexible Abstract • Ligand • Drug design Handling flexibility in molecular docking is a major challenge in chemical biology research. It has been observed that in most of the cases incorrect binding energies and poses are predicted by the docking algorithms. Neglecting receptor flexibility results in incorrect ligand binding scores. Conformational rearrangements of the receptor binding pocket while predicting binding pose and binding score is crucial for improving structure-based drug design and virtual ligand screening techniques, focusing on the algorithms and their rational. Direct modeling of protein binding site flexibility is a big challenge due to large conformational space that is to be sampled, and difficulties remain in predicting the accurate energy function. The review is an attempt to summarize the different approaches used in flexible docking analysis leading to correct predictions.

INTRODUCTION Types of Interactions Molecular docking The different interactions studied between the ligand and protein are- Most of the cellular processes require protein-protein interaction. Accurate prediction of three-dimensional structure 1. Electrostatic forces: These forces arise due to presence of of complexes as an outcome of protein-protein interaction may charge. Charge-charge, dipole-dipole and charge-dipole shed light on their functional mechanisms and their roles in the are common electrostatic interactions. cell [1]. Molecular docking studies help in understanding the Electrodynamic forces: Van der Waals’ interactions are interaction of drug molecule with biological target molecules. the most common types of Electrodynamic forces. The study involves binding of the ligand (suggested molecule) 2. 3. Steric forces: Steric forces are generated due to close with the preferred binding site (active site) of the target protein proximity of molecules and affect the reactivity and the or DNA which is referred to as receptor. The interaction takes chemical reactivity.

Crucial molecular mechanisms, ligand binding modes and factors 4. Solvent-related forces: These forces are the outcome of a effectingplace in a ligand-receptor covalent manner complex leading can to potentialbe studied specificity through [2].the chemical reaction between solvent and protein or ligand. docking results. The results can predict the binding energy as MOLECULAR DOCKING ALGORITHMS related to stability of complexes. The binding energy can be predicted beforehand using the molecular docking. The docking algorithms help in determination of all possible optimal conformations for a said complex. Binding energy Theory of Molecular Docking can also be calculated for the resultant complex. The common Docking studies are performed to determine the interaction algorithms used for docking analysis are- 1. Molecular dynamics ligand which would form a complex with overall minimum energy. Scoringbetween functions two molecules are analyzed and to which find converts out the best interacting orientation energy of into docking score. The interacting energy is also calculated. The 2.3. MonteGeneric Carlo algorithm methods 3D pose of the bound ligand can be visualized using tools like 4. Fragment-based methods Pymol, Rasmol etc.

Cite this article: Khan T, Lawrence AJ, Azad I, Raza S, Khan AR (2018) Molecular Docking Simulation with Special Reference to Flexible Docking Approach. JSM Chem 6(1): 1053. Khan et al. (2018) Email: [email protected]

Central Bringing Excellence in Open Access 5. Point complementary methods 6. Distance geometry methods 7. Systematic searches TYPES OF ENERGIES EVALUATED A molecular docking program uses scoring functions to estimate the binding energetics of the predicted ligand-receptor A) B) complexes. The energy variation, due to the formation of the ligand-receptor structure, is given by the binding constant (Kd) Figure 1 AutoDock windows showing docking interactions. docking is to have the stable ligand-receptor complex which has and the Gibbs free energy (ΔGL) [3]. The primary aim of molecular an optimized conformation with least binding free energy. The net L-L L-L P-P P-P P-L P-L ∆G= (V bound -V unbound) + (V bound -V unbound) + (V bound -V unbound +∆Sconf)

Figure 2 binding energy (ΔGbind) is calculated in terms ofhydrogen bond (ΔGHbond), electrostatic (ΔGelec), torsional free energy (ΔGtor), protein docking Force calculation. field equation showing six pair wise evaluations: [4].dispersion The software and repulsion usually (ΔGvdw), predicts desolvation the scoring (ΔGdesolv), functions total to where L refers to the “ligand” and P refers to the “protein” in a ligand- internal energy (ΔGtotal) and unbound system’s energy (ΔGunb) estimate the binding energetics of a ligand-receptor complex. The Analysis in AutoDock can be divided into following categories, energy is given as the binding constant (Kd) and in terms of Gibbs’ and entropic effects are some of the important factors considered (1) Initializing molecules (2) Running Auto Grid (3) Running whilefree energy predicting (ΔGL) the [3]. ligand-receptor Intermolecular interactions, binding .Greater desolvation is the AutoDockiGEMDOCK (4) Analyzing Interaction energy. number of physico-chemical parameters evaluated; greater is iGEMDOCK is a graphical-automated software for integration the accuracy of the scoring function. Optimized conformation is docking, screening and post-analysis. To do docking in the obtained by molecular docking between target and pre-defined most likely binding conformation requires- software, protein structure file and ligand file has to be prepared. ligand’s conformation in a specific groove. The recognition of the 1. Exploration of a large conformational space which The protein structure file can be obtained from Protein Data Bank represents potential binding modes nlm.nih.gov/sites/entrez?db=pccompound).(PDB) (http://www.rscb.org/). The ligand files The are available input format from ofZINC receptor (http://zinc.docking.org/) structure for iGEMDOCK or PubChem is PDB format.(http://www.ncbi. GEMDOCK computes a ligand conformation and orientation relative to the predicted binding conformations [5]. 2. Prediction of the interaction energy associated with binding site of target protein based on generic evolutionary SOME EFFICIENT MOLECULAR DOCKING method (GA) (Figure 3,4). Therefore, the GA parameters are SOFTWARES directly related to the docking performance. After generating a set of poses, iGEMDOCK recalculates the energy of each pose. AutoDock is automated software used for prediction of iGEMDOCK recalculates the energy of each pose The interaction interactions of ligands with bio macromolecular targets. The software provides the minimum energy between the substrate Fitness is the total energy of a predicted pose in the binding site. and the target protein, exploring all available degrees of The25 data empirical includes scoring summarized function energy of iGEMDOCK and individual is estimated energy as:terms. reproduciblefreedom (DOF) docking for the results system. for AutoDock ligands uses with the approximately Lamarckian Genetic algorithm and empirical scoring function. It provides Fitness = vdW + Hbond + Elec energies,Here, respectively.the vdW term The represents ligand can van be der docked Waal withenergy the whereas binding 10 flexible bonds. Docking is usually carried out using one of Hbond and Elect terms are hydrogen bonding and electro statistic the several search methods out of which Lamarckian genetic and simulated annealing are also used sometimes. AutoDock docking). Finally, the post analysis tool visualizes and ranks algorithm (LGA) is most efficient. Traditional genetic algorithm is run several times to give several docked conformations and thesite compound of each PDB to be files screened using accurateby merging docking the pharmacological function (slow analysis of the predicted energy and the consistency of results interactions and energy-based scoring function (Figure 5-7). are combined to identify the best solution (Figure 1). BASIC PROCESSES INVOLVED IN DOCKING evaluate conformations during docking simulations. The force Target Selection or protein preparation AutoDock uses a semi-emperical free energy force field to field evaluates binding in two steps. In the first step, the ligand evaluation of intermolecular energetics of combining the ligand Selection of a target is the first step in molecular docking. and protein start in an unbound conformation. In the second step, 3D structure of the target protein is known, its binding potential Target selection includes identification of binding sites. If the includes six pair-wise evaluations (V) and an estimate of the and protein in their bound conformation is made. The force field removal of solvent, addition of hydrogen atoms. Preparation of with the target can be identified. The target preparation involves conformational entropy lost upon binding (Figure 2). JSM Chem 6(1): 1053 (2018) 2/5 Khan et al. (2018) Email: [email protected]

Central Bringing Excellence in Open Access Ligand preparation and energy minimization

The 2D structure of the ligand can be prepared in Chem Draw professional. The SMILES & MOL file of the ligand was prepared in Chem Draw 3D. Biovia Discovery Studio version 2017 R2 foris usually energy used minimization. to prepare ASDF database and PDB of files ligands of the is constructedligand. The priorPDB file to ligand can be selection. transported The todatabase Gaussian consists View andof experimentally Gaussian 9W

known data. The commonly used databases are as follows: 1) NCI has more than 25,000 compounds. The database is usually used drugin industry. candidates. 2) ZINC The is a databasefree database also with includes more informationthan 35 million on biologicalcompounds’ activity. structures. 4) ADC, 3) contains MDDR includes all the data more of thanthe marketed 120,000 Figure 3 iGEMDOCK window. rule of 5 should be applied [8]. compounds and chemicals. For ideal selection of ligand, Lipinsky’s TYPES OF DOCKING Rigid ligand and rigid receptor docking Only three translational and rotational degrees of freedom

Figure 4 iGEMDOCK functions.

virtual screening. protein generally effects the refining of the final results of the Active Site Prediction

CASTp (Computed Atlas of Surface Topography of proteins) Figure 5 PDB window. The active sites in the target protein can be identified using probableserver. The binding server cavity identifies [6]. allAfter the the feasible receptor binding is built, pockets the activein the protein structure. The server identifies area and volume of each and heteroatom’s should be removed. site should be identified. From the active site water molecules Structural Cleaning and Energy Minimization of Receptor Protein cleaning is done to insert missing atoms in missing residues, removing water molecules, bound DNA and can be downloaded from RCB. The structure can be visualized in Discoverystandardization studio. of Receptor atoms etc. energy The minimization PDB files of targetcan be proteins carried out by using default constraint of 0.3Å RMSD (root mean square)

afterand Assisted structural Model cleaning Building and removing with Energy structural Refinement inconsistencies. (AMBER) Minimizationforce field 14SB routine using can Chimera. be performed Energy by calculations Molecular areModeling made Toolkit (MMTK) which is included with Chimera [7]. Figure 6 Pubchem window.

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Central Bringing Excellence in Open Access involving much potentially rotatable torsion. This number can be larger than the number of degrees of freedom for the ligand (up

each backbone movement affects multiple side-chains. Thus, fully to 6-12). The backbone movements may worsen the situation, as of an order of magnitude higher number of degrees of freedom flexible receptor/ligand docking simulation involves sampling used in current structure-based virtual screening processes. than typical rigid-receptor/flexible ligand simulations routinely

bindingSide-chain site flexibility is well described alone may in terms or may of movements not be sufficient of several for side-chainsadequate modeling. and a water Conformational molecule [11].variation On the in the contrary, HIV protease many kinases exhibit loop rearrangements delimiting the active site

Figure 7 Drug Bank window. unpredictability of receptor movement types makes the use of[12]. pre-determined Diversity in ligand (by experimental binding mechanisms or computational and the frequent means) are possible in this type of docking methodology. With the help multiple receptor conformations (MRC) an interesting area to work upon. Approaches used for the purpose. To deal with side DOCK and FTDOCK have been commonly used for rigid docking of a pre-computed set of ligand, its’ flexibility can be addressed. A ‘minimum rotation hypothesis’ was proposed by Zavodsky chain flexibility is easier and possible for small ligands [13]. [9].Flexible ligand and rigid receptor docking ligand–receptor steric clashes by a minimal number of side-chain rotations,and Kuhn. withTheir the docking cost of algorithm, side-chain SLIDE, movement attempts evaluated to resolve as a product of the rotation angle and the number of atoms moved Ligand and receptor are found to change their conformations One of the easiest ways to include multiple conformations of in order to obtain a minimum energy perfect fit complex. To take tend to modify their conformations. Though the methodology is a receptor in a docking experiment is to run multiple independent bitinto expensive, account the yet flexibilities softwares oflike the AutoDock ligand and and receptors FlexX can since be usedthey algorithm may also offer advantages in terms of calculation speedsimulations. as well Integration as helps in of data MRC management. sampling into Such the ‘ensemble docking forFlexible flexible Docking docking. docking’ extensions of original rigid-receptor algorithms have

of the popular FlexX algorithm, FlexE not only utilizes MRC In bound state proteins undergo conformational changes individually,been reported but foralso AUTODOCK extends the search [13] or space ICM beyond [14]. Extension the input including backbone and side-chain movements. Ignoring set of conformations by detecting distinct dissimilar parts and flexibility could prevent docking algorithms from recovering native associations. Accounting for flexibility is also essential for receptor conformations are thus generated during the search. the accuracy of the solutions [10]. The protein flexibility analysis joining them combinatorially [15]. New potentially accessible methods1. For can be generation classified into of three discrete major groups- conformations. The different conformations can be assigned by analyzing onHowever, two targets consideration of pharmaceutical of too many interest, conformations b-secretase can and lead JNK- to experimentally deduced protein structures or by using 3,reduced the algorithm performance. was unable In a recent to handle critical large evaluation loop movements of FlexE Molecular Dynamics (MD) simulation. and could not match enrichment factors obtained by running For determination of a continuous protein conformational multiple independent FlexX runs on each receptor structure [16].

2. calculated conformational space in order to generate a that introduces a highly sophisticated data structure for the MRC setspace. of discreteMany flexible conformations docking methods including sample Normal this Modes pre- representation,FLIP Dock is another termed algorithm Flexibility using Tree the(FT) AutoDock [17]. A hierarchical force field Analysis (NMA) and Essential Dynamics. and multi resolution description of the pocket structure and 3. including the rigidity theory and hinge detection For identifying rigid and flexible regions in the protein flexibility provides a framework for incorporating various types algorithms. of flexibility into AutoDock. Challenges and requirements in flexible approach: FITTED algorithm, a recently developed algorithm allows two receptor flexibility modes [18]. The first mode, termed ‘semi- Though ligand flexibility has been dealt with by a variety of differentflexible’, is combinations essentially an of MRC side-chain ensemble rotamers docking. and The backbone second algorithms, receptor flexibility is still a challenge. Direct modeling ‘fully flexible’ mode allows genetic algorithm (GA) to generate of protein movements associated with binding site flexibility algorithm is capable of simulating replaceable interface water dimensionality of the conformational space and of the complexity conformations found in the input ensemble. In addition, the ofrepresents energy function.a major glitch A typical because ligand of the binding twin challenges site for aof drug- high molecules by a combination of special functional form for like molecule may have ten to twenty amino acid-side chains water interaction and sampling absence/presence of waters in

GA. Ensemble methods may offer significant advantages over JSM Chem 6(1): 1053 (2018) 4/5 Khan et al. (2018) Email: [email protected]

Central Bringing Excellence in Open Access sequential docking to multiple conformations by conventional 7057. all-atom Monte Carlo simulations. Nucleic Acids Res. 2005; 33: 7048- should depend on the diversity of the receptor conformations, 3. ifrigid-receptor the ensemble algorithms. only involves The efficiency minor ofstructural ensemble variations, methods its exploration may contribute only additively to the overall 3583-3608.Foloppe N, Hubbard R. Towards predictive ligand design with free- energy based computational methods? Curr Med Chem. 2006; 13: computational cost; however, if highly dissimilar binding site 4. Agarwal S, Chadha D, Mehrotra R. Molecular modeling and conformations are included, each of them will have to be explored spectroscopic studies of semustine binding with DNA and its virtually independently, potentially multiplying the search time comparison with lomustine-DNA adduct formation. J Biomol Str and by the number of conformations. Post-docking optimization may help to further improve both docking pose and its score. Nabuurs, 5. Dyn. 2015; 33: 1653-1668. Wagener, and de Vlieg demonstrated a robust performance of a combination of FlexX-Ensemble docking combined with a post- Kapetanovic IM. Computer-aided drug discovery and development docking explicit receptor ligand optimization on a benchmark of 35 (CADDD): In silico-chemico-biological approach. Chem Biol Interac. 6. 2008; 171: 165-176. MD, Balasubramanium S, Dhiraviam KN. In silico pharmacokinetic help to further improve both docking pose and its score. Nabuurs, andParamashivam molecular SK,docking Elayaperumal studies of K, small Natarajan molecules BB, Ramamoorthy derived from Wagener,ligand–receptor and de complexes Vlieg demonstrated [19]. Post-docking a robust optimizationperformance mayof a combination of FlexX-Ensemble docking combined with a post- Indigoferaaspalathoides Vahl targeting receptor tyrosine kinases. docking explicit receptor ligand optimization on a benchmark 7. Bioinformation. 2015; 11: 73-84. Meng EC, et al. UCSF Chimera--a visualization system for exploratory combination of FlexX-Ensemble docking with the Yasara/ Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, of 35 ligand–receptor complexes [19]. The authors used a 8. research and analysis. J Comput Chem. 2004; 25: 1605-1612. achievements of evidence-based traditional Chinese medicine in wereYamber2 pre-selected program using for conformational a set of rules. The generation protocol andwas testedfull atom on Chao J, Dai Y, Varpoote R, Lam W, Cheng YC, Pao LH, et al. Major refinement of the high-ranking complexes. The ‘flexible’ residues treating major diseases. Biochem Pharmol. 2017; 139: 94-104. approach for structure-based drug discovery. Curr Comput Aided 20CONCLUSION cross docking ligand–protein pairs 9. Meng XY, Zhang HX, Mezei M, Cui M. Molecular docking: a powerful The principles and methods in this review highlight the 10. Drug Des. 2011; 7: 146-157. Andrusier N, Mashiach E, Nussinov R, Wolfson HJ. Principles of flexible growthstrategies in theby whichnumber flexible of protein docking structures can be in PDB,applied improved in the 11. protein-proteinOsterberg F, Morris docking. GM, Sanner Proteins. MF, 2008; Olson 73: AJ, 271-289. Goodsell DS. Automated identification of novel bioactive compounds. With the exceptional docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock. Proteins. method has made it an interesting approach to explore. This MRCunderstanding approach is of comparatively the flexible dockingless time approach taking and through still suitable MCR 2002; 46: 34-40. receptor conformations is relatively small and carefully chosen. 12. Cavasotto CN, Abagyan RA. Protein flexibility in ligand docking and Stillfor virtual the challenge ligand screening remains for as issues long as involving the number the accuracy of fixed 13. virtual screening to protein kinases. J Mol Biol. 2004; 337: 209-225.

1114.Zavodszky MI, Kuhn LA. Side-chain flexibility in protein-ligand binding: the minimal rotation hypothesis. Protein Sci. 2005; 14: 1104- of the important available scoring issues that functions. need more Handling exploration. of solvent Successful effects, 14. Schapira M, Abagyan R, Totrov M. Nuclear hormone receptor targeted molecularentropic effects docking and protocol dealing requires with receptor clear useflexibility of fundamental are some methods. Understanding these principles is necessary for 15. virtual screening. J Med Chem. 2003; 46: 3045-3059. obtaining meaningful results. Claussen H, Buning C, Rarey M, Lengauer T. FlexE: efficient molecular ACKNOWLEDGEMENTS docking considering protein structure variations. J Mol Biol. 2001; 16. 308: 377-395. The authors greatly acknowledge the faculty members of Critical evaluation of FlexE against JNK-3 and beta-secretase. J Chem Polgar T, Keseru GM. Ensemble docking into flexible active sites.

17. Department of Chemistry, Integral University and Department of Inf Model. 2006; 46: 1795-1805. Chemistry,REFERENCES Isabella Thoburn College, Lucknow for the support. Zhao Y, Sanner MF. FLIP Dock: docking flexible ligands into flexible 18. receptors. Proteins. 2007; 68: 726-737. 1. and solvated macromolecules. 1. Development and validation of Corbeil CR, Englebienne P, Moitessier N. Docking ligands into flexible Han K, Zhang L, Wang M, Zhang R, Wang C, Zhang C. Molecules. 2018; 23: 2303. drug docking to DNA: binding-site and binding-mode transitions in FITTED 1.0. J Chem Inf Model. 2007; 47: 435-449. 2. Rohs R, Bloch I, Sklenar H, Shakked Z. Molecular flexibility in ab initio 19. Nabuurs SB, Wagener M, de Vlieg J. A flexible approach to induced fit docking. J Med Chem. 2007; 50: 6507-6518.

Cite this article Khan T, Lawrence AJ, Azad I, Raza S, Khan AR (2018) Molecular Docking Simulation with Special Reference to Flexible Docking Approach. JSM Chem 6(1): 1053.

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