Relevance of Molecular Docking Studies in Drug Designing

Ritu       Jakhar; Mehak       Dangi; Alka       Khichi; Anil    Kumar    Chhillar

Abstract

Molecular Docking is used to positioning the computer-generated 3D structure of small ligands into a receptor structure in a variety of orientations, conformations and positions. This method is useful in drug discovery and medicinal chemistry providing insights into molecular recognition. Docking has become an integral part of Computer-Aided Drug Design and Discovery (CADDD). Traditional docking methods suffer from limitations of semi-flexible or static treatment of targets and ligand. Over the last decade, advances in the field of computational, proteomics and genomics have also led to the development of different docking methods which incorporate protein-ligand flexibility and their different binding conformations. Receptor flexibility accounts for more accurate binding pose predictions and a more rational depiction of protein binding interactions with the ligand. Protein flexibility has been included by generating protein ensembles or by dynamic docking methods. Dynamic docking considers solvation, entropic effects and also fully explores the drug-receptor binding and recognition from both energetic and mechanistic point of view. Though in the fast-paced drug discovery program, dynamic docking is computationally expensive but is being progressively used for screening of large compound libraries to identify the potential drugs. In this review, a quick introduction is presented to the available docking methods and their application and limitations in drug discovery.

Keywords: Docking, MD simulation, drug designing, ensemble docking, dynamic docking, fragment-based docking.

« Previous Next »

Graphical Abstract

[1] 
Wilms LR. Guide to Drugs in Canada.  3rd ed. Leo Paper Products 2009.
[2] 
Smith CM, Reynard AM. Textbook of Pharmacology. W. B. Saunders Company 1992.
[3] 
Murray PR, Baron EJ, Pfaller MA, Tenover FC, Yolke RH. Manual of Clinical Microbiology.  6th ed. London: Mosby Year Book 1995.
[4] 
Khan AU, Baig MH, Wadhwa G. Molecular docking analysis of new generation cephalosporins interactions with recently known SHV-variants. Bioinformation  2011; 5(8): 331-5.
[http://dx.doi.org/10.6026/97320630005331] [PMID: 21383920] 
[5] 
Shan Y, Kim ET, Eastwood MP, Dror RO, Seeliger MA, Shaw DE. How does a drug molecule find its target binding site? J Am Chem Soc  2011; 133(24): 9181-3.
[http://dx.doi.org/10.1021/ja202726y] [PMID: 21545110] 
[6] 
Merad M, Soufi W, Ghalem S, et al. Molecular interaction of acetylcholinesterase with carnosic acid derivatives: a neuroinformatics study. CNS Neurol Disord Drug Targets  2014; 13(3): 440-6.
[http://dx.doi.org/10.2174/18715273113126660157] [PMID: 24059305] 
[7] 
Xiang M, Cao Y, Fan W, Chen L, Mo Y. Computer-aided drug design: lead discovery and optimization. Comb Chem High Throughput Screen  2012; 15(4): 328-37.
[http://dx.doi.org/10.2174/138620712799361825] [PMID: 22221065] 
[8] 
Sliwoski G, Kothiwale S, Meiler J, Lowe EW Jr. Computational methods in drug discovery. Pharmacol Rev  2013; 66(1): 334-95.
[http://dx.doi.org/10.1124/pr.112.007336] [PMID: 24381236] 
[9] 
Michel J. Current and emerging opportunities for molecular simulations in structure-based drug design. Phys Chem Chem Phys  2014; 16(10): 4465-77.
[http://dx.doi.org/10.1039/C3CP54164A] [PMID: 24469595] 
[10] 
Kuntz ID, Blaney JM, Oatley SJ, Langridge R, Ferrin TEA. A geometric approach to macromolecule-ligand interactions. J Mol Biol  1982; 161(2): 269-88.
[http://dx.doi.org/10.1016/0022-2836(82)90153-X] [PMID: 7154081] 
[11] 
Mezei M. A new method for mapping macromolecular topography. J Mol Graph Model  2003; 21(5): 463-72.
[http://dx.doi.org/10.1016/S1093-3263(02)00203-6] [PMID: 12543141] 
[12] 
Levitt DG, Banaszak LJ. POCKET: A computer graphics method for identifying and displaying protein cavities and their surrounding amino acids. J Mol Graph  1992; 10(4): 229-34.
[http://dx.doi.org/10.1016/0263-7855(92)80074-N] [PMID: 1476996] 
[13] 
Brady GP Jr, Stouten PF. Fast prediction and visualization of protein binding pockets with PASS. J Comput Aided Mol Des  2000; 14(4): 383-401.
[http://dx.doi.org/10.1023/A:1008124202956] [PMID: 10815774] 
[14] 
Goodford PJ. A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J Med Chem  1985; 28(7): 849-57.
[http://dx.doi.org/10.1021/jm00145a002] [PMID: 3892003] 
[15] 
Kastenholz MA, Pastor M, Cruciani G, Haaksma EE, Fox T. GRID/CPCA: A new computational tool to design selective ligands. J Med Chem  2000; 43(16): 3033-44.
[http://dx.doi.org/10.1021/jm000934y] [PMID: 10956211] 
[16] 
Yuriev E, Holien J, Ramsland PA. Improvements, trends, and new ideas in molecular docking: 2012-2013 in review. J Mol Recognit  2015; 28(10): 581-604.
[http://dx.doi.org/10.1002/jmr.2471] [PMID: 25808539] 
[17] 
Vladimir B. Sulimov, Danil C. Kutov, and Alexey V. Sulimov, Advances in Docking. Curr Med Chem  2019; 26: 1-25.
[http://dx.doi.org/10.2174/0929867325666180904115000] 
[18] 
Morris GM, Huey R, Lindstrom W, et al. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem  2009; 30(16): 2785-91.
[http://dx.doi.org/10.1002/jcc.21256] [PMID: 19399780] 
[19] 
Brozell SR, Mukherjee S, Balius TE, Roe DR, Case DA, Rizzo RC. Evaluation of DOCK 6 as a pose generation and database enrichment tool. J Comput Aided Mol Des  2012; 26(6): 749-73.
[http://dx.doi.org/10.1007/s10822-012-9565-y] [PMID: 22569593] 
[20] 
Rarey M, Kramer B, Lengauer T. Multiple automatic base selection: Protein-ligand docking based on incremental construction without manual intervention. J Comput Aided Mol Des  1997; 11(4): 369-84.
[http://dx.doi.org/10.1023/A:1007913026166] [PMID: 9334903] 
[21] 
Schulz-Gasch T, Stahl M. Binding site characteristics in structure-based virtual screening: evaluation of current docking tools. J Mol Model  2003; 9(1): 47-57.
[http://dx.doi.org/10.1007/s00894-002-0112-y] [PMID: 12638011] 
[22] 
Jones G, Wilett P, Glein RC, Leach AR, Taylor R. Development and Validation of genetic algorithm and an empirical binding free energy function. J Mol Biol  1997; 267: 727-48.
[http://dx.doi.org/10.1006/jmbi.1996.0897] [PMID: 9126849] 
[23] 
Friesner RA, Murphy RB, Repasky MP, et al. Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J Med Chem  2006; 49(21): 6177-96.
[http://dx.doi.org/10.1021/jm051256o] [PMID: 17034125] 
[24] 
Fernández-Recio J, Totrov M, Abagyan R. Soft protein-protein docking in internal coordinates. Protein Sci  2002; 11(2): 280-91.
[http://dx.doi.org/10.1110/ps.19202] [PMID: 11790838] 
[25] 
Sulimov AV, Kutov DC, Oferkin IV, Katkova EV, Sulimov VB. Application of the docking program SOL for CSAR benchmark. J Chem Inf Model  2013; 53(8): 1946-56.
[http://dx.doi.org/10.1021/ci400094h] [PMID: 23829357] 
[26] 
Oferkin IV, Katkova EV, Sulimov AV, et al. Evaluation of docking target functions by the comprehensive investigation of protein-ligand energy minima. Adv Bioinforma  2015; 2015 126858
[http://dx.doi.org/10.1155/2015/126858] 
[27] 
Sulimov AV, Zheltkov DA, Oferkin IV, et al. Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms. Comput Struct Biotechnol J  2017; 15: 275-85.
[http://dx.doi.org/10.1016/j.csbj.2017.02.004] [PMID: 28377797] 
[28] 
Krammer A, Kirchhoff PD, Jiang X, Venkatachalam CM, Waldman M. LigScore: a novel scoring function for predicting binding affinities. J Mol Graph Model  2005; 23(5): 395-407.
[http://dx.doi.org/10.1016/j.jmgm.2004.11.007] [PMID: 15781182] 
[29] 
Sadovnichii VA, Sulimov VB. Supercomputing technologies in medicineSupercomputing Technologies in Science, Education, and Industry.  Moscow University Publishing 2009; pp. 16-23.
[30] 
Sulimov AV, Kutov DC, Katkova EV, Ilin IS, Sulimov VB. New generation of docking programs: Supercomputer validation of force fields and quantum-chemical methods for docking. J Mol Graph Model  2017; 78: 139-47.
[http://dx.doi.org/10.1016/j.jmgm.2017.10.007] [PMID: 29055806] 
[31] 
Sulimov AV, Kutov DC, Katkova EV, Sulimov VB. Combined docking with classical force field and quantum chemical semiempirical method PM7. Adv Bioinforma  2017; 2017 7167691
[http://dx.doi.org/10.1155/2017/7167691] [PMID: 28191015] 
[32] 
Romanov AN, Kondakova OA, Grigoriev FV, et al. Calculation Methods and Programming  2008; 9: 213.
[33] 
Sulimov AV, Kutov DC, Katkova EV, Kondakova OA, Sulimov VB. Search for approaches to improving the calculation accuracy of the protein-ligand binding energy by docking In: Russian Chemical Bulletin, International Edition.   2017; 66: pp. 1913-24.
[34] 
Verdonk ML, Giangreco I, Hall RJ, Korb O, Mortenson PN, Murray CW. Docking performance of fragments and druglike compounds. J Med Chem  2011; 54(15): 5422-31.
[http://dx.doi.org/10.1021/jm200558u] [PMID: 21692478] 
[35] 
Hopkins AL, Groom CR, Alex A. Ligand efficiency: a useful metric for lead selection. Drug Discov Today  2004; 9(10): 430-1.
[36] 
Kutov DC, Katkova EV, Sulimov AV, Kondakova OA, Sulimov VB. Influence of the method of hydrogen atoms incorporation into the target protein on the protein-ligand binding energy. Bulletin of the South Ural State University. Ser. Mathematical Modelling. Program Comput Softw  2017; 10: 94-107.
[37] 
Romanov AN, Jabin SN, Martynov YB. SuliMov AV, Grigoriev FV, Sulimov VB. Surface generalized born method: a simple, fast, and precise implicit solvent model beyond the coulomb approximation. J Phys Chem A  2004; 108: 9323. [http://dx.doi.org/10.1021/jp046721s].
[38] 
Kupervasser OY, Zhabin SN, Martynov YB, et al. Continual model of solvent: the DISOLV software-algorithms, implementation, and validation. Calculation Methods Prog  2011; 12: 246.
[39] 
Mikhalev AY, Oferkin IV, Oseledets IV, Sulimov AV, Tyrtyshnikov EE, Sulimov VB. Application of the multicharge approximation for large dense matrices in the framework of the polarized continuum solvent model. Calculation Methods Prog  2014; 15: 9.
[40] 
Sulimov VB, Mikhalev AY, Oferkin IV, et al. Polarized continuum solvent model: considerable acceleration with the multicharge matrix approximation. Int J App Engine Res  2015; 10: 44815.
[41] 
Stewart JJP. Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters. J Mol Model  2013; 19(1): 1-32.
[http://dx.doi.org/10.1007/s00894-012-1667-x] [PMID: 23187683] 
[42] 
Ng W, Lobach ARM, Zhu X, et al. Animal models of idiosyncratic drug reactions. Adv Pharmacol  2012; 63: 81-135.
[http://dx.doi.org/10.1016/B978-0-12-398339-8.00003-3] [PMID: 22776640] 
[43] 
Vliegenthart ADB, Tucker CS, Del Pozo J, Dear JW. Zebrafish as model organisms for studying drug-induced liver injury. Br J Clin Pharmacol  2014; 78(6): 1217-27.
[http://dx.doi.org/10.1111/bcp.12408] [PMID: 24773296] 
[44] 
Watkins PB. Drug safety sciences and the bottleneck in drug development. Clin Pharmacol Ther  2011; 89(6): 788-90.
[http://dx.doi.org/10.1038/clpt.2011.63] [PMID: 21593756] 
[45] 
van Meer PJK, Graham ML, Schuurman HJ. The safety, efficacy and regulatory triangle in drug development: Impact for animal models and the use of animals. Eur J Pharmacol  2015; 759: 3-13.
[http://dx.doi.org/10.1016/j.ejphar.2015.02.055] [PMID: 25818943] 
[46] 
Karha J, Topol EJ. The sad story of Vioxx, and what we should learn from it. Cleve Clin J Med  2004; 71(12): 933-934, 936, 938-939.
[http://dx.doi.org/10.3949/ccjm.71.12.933] [PMID: 15641522] 
[47] 
Komajda M, McMurray JJV, Beck-Nielsen H, et al. Heart failure events with rosiglitazone in type 2 diabetes: data from the RECORD clinical trial. Eur Heart J  2010; 31(7): 824-31.
[http://dx.doi.org/10.1093/eurheartj/ehp604] [PMID: 20118174] 
[48] 
Luo H, Fokoue-Nkoutche A, Singh N, Yang L, Hu J, Zhang P. Molecular Docking for Prediction and Interpretation of Adverse Drug Reactions. Comb Chem High Throughput Screen  2018; 21(5): 314-22.
[http://dx.doi.org/10.2174/1386207321666180524110013] [PMID: 29792141] 
[49] 
McConkey BJ, Sobolev V, Edelman M. The performance of current methods in ligand-protein docking. Curr Sci  2002; 83: 845-55.
[50] 
El-Naggar M, Sallam HA, Shaban SS, et al. Design, synthesis, and molecular docking study of novel heterocycles incorporating 1,3,4-thiadiazole moiety as potential antimicrobial and anticancer agents. Molecules  2019; 24(6): 1066-87.
[http://dx.doi.org/10.3390/molecules24061066] [PMID: 30889918] 
[51] 
Amr AEE, Abo-Ghalia MH, Moustafa GO, Al-Omar MA, Nossier ES, Elsayed EA. Design, synthesis and docking studies of novel macrocyclic pentapeptides as anticancer multi-targeted kinase inhibitors. Molecules  2018; 23(10): 2416.
[http://dx.doi.org/10.3390/molecules23102416] [PMID: 30241374] 
[52] 
Elzahabi HSA, Nossier ES, Khalifa NM, Alasfoury RA, El-Manawaty MA. Anticancer evaluation and molecular modeling of multi-targeted kinase inhibitors based pyrido[2,3-d]pyrimidine scaffold. J Enzyme Inhib Med Chem  2018; 33(1): 546-57.
[http://dx.doi.org/10.1080/14756366.2018.1437729] [PMID: 29482389] 
[53] 
Friesner RA, Banks JL, Murphy RB, et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem  2004; 47(7): 1739-49.
[http://dx.doi.org/10.1021/jm0306430] [PMID: 15027865] 
[54] 
Hou X, Du J, Zhang J, Du L, Fang H, Li M. How to improve docking accuracy of AutoDock4.2: a case study using different electrostatic potentials. J Chem Inf Model  2013; 53(1): 188-200.
[http://dx.doi.org/10.1021/ci300417y] [PMID: 23244516] 
[55] 
Lee MR, Sun Y. Improving docking accuracy through molecular mechanics generalized born optimization and scoring. J Chem Theory Comput  2007; 3(3): 1106-19.
[http://dx.doi.org/10.1021/ct6003406] [PMID: 26627430] 
[56] 
Huedo C, Zani F, Mendiola A, Pradhan S, Sinha C, Torres EL. Synthesis, antimicrobial activity and molecular docking of di‐ and triorganotin (IV) complexes with thiosemicarbazide derivatives. Appl Organomet Chem  2018; 33(2): 4700.
[http://dx.doi.org/10.1002/aoc.4700] 
[57] 
Carlson HA. Protein flexibility and drug design: how to hit a moving target. Curr Opin Chem Biol  2002; 6(4): 447-52.
[http://dx.doi.org/10.1016/S1367-5931(02)00341-1] [PMID: 12133719] 
[58] 
Cozzini P, Kellogg GE, Spyrakis F, et al. Target flexibility: an emerging consideration in drug discovery and design. J Med Chem  2008; 51(20): 6237-55.
[http://dx.doi.org/10.1021/jm800562d] [PMID: 18785728] 
[59] 
McGovern SL, Shoichet BK. Information decay in molecular docking screens against holo, apo, and modeled conformations of enzymes. J Med Chem  2003; 46(14): 2895-907.
[http://dx.doi.org/10.1021/jm0300330] [PMID: 12825931] 
[60] 
Amaro RE, Schnaufer A, Interthal H, Hol W, Stuart KD, McCammon JA. Discovery of drug-like inhibitors of an essential RNA-editing ligase in Trypanosoma brucei. Proc Natl Acad Sci USA  2008; 105(45): 17278-83.
[http://dx.doi.org/10.1073/pnas.0805820105] [PMID: 18981420] 
[61] 
Ellingson SR, Miao Y, Baudry J, Smith JC. Multi-conformer ensemble docking to difficult protein targets. J Phys Chem B  2015; 119(3): 1026-34.
[http://dx.doi.org/10.1021/jp506511p] [PMID: 25198248] 
[62] 
Evangelista W, Weir RL, Ellingson SR, et al. Ensemble-based docking: From hit discovery to metabolism and toxicity predictions. Bioorg Med Chem  2016; 24(20): 4928-35.
[http://dx.doi.org/10.1016/j.bmc.2016.07.064] [PMID: 27543390] 
[63] 
Murray CW, Baxter CA, Frenkel AD. The sensitivity of the results of molecular docking to induced fit effects: application to thrombin, thermolysin and neuraminidase. J Comput Aided Mol Des  1999; 13(6): 547-62.
[http://dx.doi.org/10.1023/A:1008015827877] [PMID: 10584214] 
[64] 
Huang SY, Zou X. Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking. Proteins  2007; 66(2): 399-421.
[http://dx.doi.org/10.1002/prot.21214] [PMID: 17096427] 
[65] 
Cavalli A, Bottegoni G, Raco C, De Vivo M, Recanatini M. A computational study of the binding of propidium to the peripheral anionic site of human acetylcholinesterase. J Med Chem  2004; 47(16): 3991-9.
[http://dx.doi.org/10.1021/jm040787u] [PMID: 15267237] 
[66] 
Seeliger D, de Groot BL. Conformational transitions upon ligand binding: holo-structure prediction from apo conformations. PLOS Comput Biol  2010; 6(1) e1000634
[http://dx.doi.org/10.1371/journal.pcbi.1000634] [PMID: 20066034] 
[67] 
Felder CB, Graul RC, Lee AY, Merkle HP, Sadee W. The Venus flytrap of periplasmic binding proteins: an ancient protein module present in multiple drug receptors. AAPS PharmSci  1999; 1(2) E2
[http://dx.doi.org/10.1208/ps010202] [PMID: 11741199] 
[68] 
Huang SY, Zou X. Efficient molecular docking of NMR structures: application to HIV-1 protease. Protein Sci  2007; 16(1): 43-51.
[http://dx.doi.org/10.1110/ps.062501507] [PMID: 17123961] 
[69] 
Craig IR, Essex JW, Spiegel K. Ensemble docking into multiple crystallographically derived protein structures: an evaluation based on the statistical analysis of enrichments. J Chem Inf Model  2010; 50(4): 511-24.
[http://dx.doi.org/10.1021/ci900407c] [PMID: 20222690] 
[70] 
Novoa EM, Ribas de Pouplana L, Barril X, Orozco M. Ensemble docking from homology models. J Chem Theory Comput  2010; 6(8): 2547-57.
[http://dx.doi.org/10.1021/ct100246y] [PMID: 26613506] 
[71] 
Velazquez HA, Riccardi D, Xiao Z, et al. Ensemble docking to difficult targets in early-stage drug discovery: Methodology and application to fibroblast growth factor 23. Chem Biol Drug Des  2018; 91(2): 491-504.
[http://dx.doi.org/10.1111/cbdd.13110] [PMID: 28944571] 
[72] 
Brenke R, Kozakov D, Chuang G-Y, et al. Fragment-based identification of druggable ‘hot spots’ of proteins using Fourier domain correlation techniques. Bioinformatics  2009; 25(5): 621-7.
[http://dx.doi.org/10.1093/bioinformatics/btp036] [PMID: 19176554] 
[73] 
Kozakov D, Grove LE, Hall DR, et al. The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins. Nat Protoc  2015; 10(5): 733-55.
[http://dx.doi.org/10.1038/nprot.2015.043] [PMID: 25855957] 
[74] 
Xiao Z, Riccardi D, Velazquez HA, et al. A computationally identified compound antagonizes excess FGF-23 signaling in renal tubules and a mouse model of hypophosphatemia. Sci Signal  2016; 9(455): ra113.
[http://dx.doi.org/10.1126/scisignal.aaf5034] [PMID: 27879395] 
[75] 
Wiczew D, Borowska A, Szkaradek K, et al. Molecular mechanism of vSGLT inhibition by gneyulin reveals antiseptic properties against multidrug-resistant gram-negative bacteria. J Mol Model  2019; 25(7): 186.
[http://dx.doi.org/10.1007/s00894-019-4073-9] [PMID: 31187300] 
[76] 
Carlson HA, McCammon JA. Accommodating protein flexibility in computational drug design. Mol Pharmacol  2000; 57(2): 213-8.
[PMID: 10648630] 
[77] 
Lin JH, Perryman AL, Schames JR, McCammon JA. Computational drug design accommodating receptor flexibility: the relaxed complex scheme. J Am Chem Soc  2002; 124(20): 5632-3.
[http://dx.doi.org/10.1021/ja0260162] [PMID: 12010024] 
[78] 
McCammon JA. Target flexibility in molecular recognition. Biochim Biophys Acta  2005; 1754(1-2): 221-4.
[http://dx.doi.org/10.1016/j.bbapap.2005.07.041] [PMID: 16181817] 
[79] 
Claussen H, Buning C, Rarey M, Lengauer T. FlexE: efficient molecular docking considering protein structure variations. J Mol Biol  2001; 308(2): 377-95.
[http://dx.doi.org/10.1006/jmbi.2001.4551] [PMID: 11327774] 
[80] 
Tian S, Sun H, Pan P, et al. Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility. J Chem Inf Model  2014; 54(10): 2664-79.
[http://dx.doi.org/10.1021/ci500414b] [PMID: 25233367] 
[81] 
Liang Z-X, Nocek JM, Huang K, et al. Dynamic docking and electron transfer between Zn-myoglobin and cytochrome b 5. J Am Chem Soc  2002; 124(24): 6849-59.
[http://dx.doi.org/10.1021/ja0127032] [PMID: 12059205] 
[82] 
Gioia D, Bertazzo M, Recanatini M, Masetti M, Cavalli A. Dynamic docking: a paradigm shift in computational drug discovery. Molecules  2017; 22(11): 2029.
[http://dx.doi.org/10.3390/molecules22112029] [PMID: 29165360] 
[83] 
De Vivo M, Cavalli A. Recent advances in dynamic docking for drug discovery. Wiley Interdiscip Rev Comput Mol Sci  2017; 7(6) e1320
[http://dx.doi.org/10.1002/wcms.1320] 
[84] 
Gervasio FL, Laio A, Parrinello M. Flexible docking in solution using metadynamics. J Am Chem Soc  2005; 127(8): 2600-7.
[http://dx.doi.org/10.1021/ja0445950] [PMID: 15725015] 
[85] 
Coveney PV, Wan S. On the calculation of equilibrium thermodynamic properties from molecular dynamics. Phys Chem Chem Phys  2016; 18(44): 30236-40.
[http://dx.doi.org/10.1039/C6CP02349E] [PMID: 27165501] 
[86] 
Edink E, Rucktooa P, Retra K, et al. Fragment growing induces conformational changes in acetylcholine-binding protein: a structural and thermodynamic analysis. J Am Chem Soc  2011; 133(14): 5363-71.
[http://dx.doi.org/10.1021/ja110571r] [PMID: 21322593] 
[87] 
Bollag G, Hirth P, Tsai J, et al. Clinical efficacy of a RAF inhibitor needs broad target blockade in BRAF-mutant melanoma. Nature  2010; 467(7315): 596-9.
[http://dx.doi.org/10.1038/nature09454] [PMID: 20823850] 
[88] 
Hessler G, Baringhaus KH. The scaffold hopping potential of pharmacophores. Drug Discov Today Technol  2010; 7(4): e203-70.
[http://dx.doi.org/10.1016/j.ddtec.2010.09.001] [PMID: 24103802] 
[89] 
Maggiora G, Vogt M, Stumpfe D, Bajorath J. Molecular similarity in medicinal chemistry. J Med Chem  2014; 57(8): 3186-204.
[http://dx.doi.org/10.1021/jm401411z] [PMID: 24151987] 
[90] 
Casu B, Arya T, Bessette B, Baron C. Fragment-based screening identifies novel targets for inhibitors of conjugative transfer of antimicrobial resistance by plasmid pKM101. Sci Rep  2017; 7(1): 14907.
[http://dx.doi.org/10.1038/s41598-017-14953-1] [PMID: 29097752] 
[91] 
Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem  2010; 31(2): 455-61.
[PMID: 19499576] 

Rights & Permissions Print Cite

Article Metrics

65

5

Journal Information

For Authors

For Editors

For Reviewers

Explore Articles

Open Access

Open Access Articles

For Visitors

DOI https://dx.doi.org/10.2174/1574893615666191219094216	Print ISSN 1574-8936
Publisher Name Bentham Science Publisher	Online ISSN 2212-392X

Current Bioinformatics

Relevance of Molecular Docking Studies in Drug Designing

Abstract

Graphical Abstract

Related Journals

Related Books

Related Articles