Modeling Analysis of Potential Target of Dolastatin 16 by Computational Virtual Screening
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602 Chem. Pharm. Bull. 66, 602–607 (2018) Vol. 66, No. 6 Regular Article Highlighted Paper selected by Editor-in-Chief Modeling Analysis of Potential Target of Dolastatin 16 by Computational Virtual Screening Ting-Ting Liang,a,b Qi Zhao,c Shan He,d Fang-Zhou Mu,e Wei Deng,*,a and Bing-Nan Han*,b a School of Chemical and Environmental Engineering, Shanghai Institute of Technology; Shanghai 201418, China: b Department of Development Technology of Marine Resources, College of Life Sciences, Zhejiang Sci-Tech University; Zhejiang 310018, China: c Faculty of Health Sciences, University of Macau; Macau 999078, China: d Li Dak Sum Yip Yio Chin Kenneth Li Marine Biopharmaceutical Research Center, Ningbo University; Ningbo 315211, China: and e Pharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin-Madison; Wisconsin WI 53706, U.S.A. Received November 30, 2017; accepted March 21, 2018 Dolastatin 16 is a cyclic depsipeptide isolated from the marine invertebrates and cyanobacterium Lyng- bya majuscula, however, its bioactivity has been a historical question. In this study, peptidyl–prolyl cis–trans isomerase FKBP1A (FKBP12) was predicted as a potential target of dolastatin 16 via PharmMapper as well as verified using chemical–protein interactome (CPI) and molecular docking. FKBP1A has been previously identified as a target for the natural polyketide FK506 (tacrolimus), an immune suppressor inhibiting the rejection of organ transplantation in clinical use. The comparison study via the reverse pharmacophore screening and molecular docking of dolastatin 16 and FK506 indicated the good consistency of analysis with the computational approach. As the results, the lowest binding energy of dolastatin 16–FKBP1A complex was 7.4 kcal/mol and FK506–FKBP1A complex was 8.7 kcal/mol. The ligand dolastatin 16 formed three hydro- gen bonds vs. four of FK506, as well as seven hydrophobic interactions vs. six of FK506 within the active site residues. These functional residues are highly repetitive and consistent with previously reported active site of model of FK506–FKBP1A complex, and the pharmacophore model was shown feasibly matching with the molecular feature of dolastatin 16. Key words dolastatin 16; PharmMapper; FKBP1A; molecular docking In modern drug development, target fishing (target identi- inhibited the larval settlement and metamorphosis of the fication) is an important step for exploring the mechanism of barnacle Amphibalanus amphitrite with an EC50 value of 1) −1 14) action of bioactive small molecules. In recent years, using 0.003 µg mL . The LC50/EC50 ratio of dolastatin 16 is 6000, computer tools to identify new indications or new targets for due to its significant antifouling activity, but low toxicity, existing drugs has become a hot spot in drug research, such therefore, dolastatin 16 was expected to be a promising lead as target identification for Saffron2) and Capsaicin.3) Computa- compound alternative for the current use of heavy-metal-based tional target fishing technologies have increased the accuracy antifouling agents.15) Since we have successfully obtained the and efficiency of target identification and is expected to have crystal structure of dolastatin 16, and have some primary data a large impact on drug development.4–6) So far, many compu- showing that it exhibited certain anti-inflammation activity, tational target identification methods have been developed,7–9) we conducted a virtual screening to search for its possible such as the ligand-protein reverse docking approach for find- targets. ing potential protein targets of a small molecule by computer- In our study, FKBP1A (FK506 binding protein) was ranked automated docking search of a protein cavity database.10) as the top target for dolastatin 16 according to PharmMapper, Our long-term research goal is to isolate bioactive natural a reverse docking server for computational virtual screening. products from marine cyanobacteria and to understand their This enzyme is thought to play a role in accelerating protein mechanism of action. Just recently we have re-isolated a cyclic folding.16) FKBP modulates the release of calcium from skel- peptide, dolastatin 16 from cyanobacterium Lyngbya majus- cula collected from the South China Sea. In 1997 dolastatin 16 (Fig. 1(a)), was first isolated from sea hare Dolabella au- ricularia and showed impressive cytotoxicity against a variety of cancer cell lines reported.11) In 2015, synthesis of dolastatin 16 was completed.12) Surprisingly, synthetic dolastatin 16 loses potency in inhibiting cancer cell growth (growth inhibition, 12) 50% (GI50)>10 µg/mL) as opposed to its natural counterpart. Their analysis suggested that the strong cytotoxicity observed in the 1997 study might be due to a chemically undetected compound other than dolastatin 16. Over the past decade, re-discovery of dolastatin 16 from L. majuscula and other microalgae was occasionally reported.13) Tan’s group isolated dolastatin 16 from L. majuscula and showed that it effectively Fig. 1. The Chemical Structure of (a) Dolastatin 16 and (b) FK506 * To whom correspondence should be addressed. e-mail: [email protected]; [email protected] © 2018 The Pharmaceutical Society of Japan Vol. 66, No. 6 (2018) Chem. Pharm. Bull. 603 eton, and is necessary for T-cell receptor mediated activation cy, and has a new scoring function.23) At the same time, it also of interleukin-2 transcription.16) This target was evaluated and greatly increases the efficiency of the optimization and the analyzed via chemical–protein interactome (CPI) and molecu- accuracy of the binding mode predictions. PyRx0.8 is a valu- lar docking methods. Our results indicated that dolastatin 16 able tool for molecular docking, which contains autodock vina has good virtual binding capability to FKBP1A comparable to wizard with easy-to-handle user interface, as well as chemical its natural substrate FK506. spreadsheet-like functionality and powerful visualization en- gine. Autodock vina in PyRx0.8 is being widely used as a new Experimental program for molecular docking and virtual screening. Targets Predicted by PharmMapper PharmMapper is a The crystal structures of the potential target proteins were freely accessed web server that uses a pharmacophore map- obtained from the RCSB Protein Data Bank (1FKF, 1BL4, ping approach to identify potential target candidates for the http://www.rcsb.org/pdb), and prepared using the protein pre- given probe small molecules.17) PharmMapper contains 7302 paring tool in PyMOL. Which was used to extract ligand from pharmacophore models and its pharmacophore database con- binding site, deleting all water molecules and hydrogen atoms tains annotation from TargetBank, DrugBank, BindingDB and were then added, in addition, showed the ligand coordinates potential drug target database. It automatically searches for and radius information.24) During the docking procedure, the the best mapping poses in all pharmacophore models of Phar- grid box covered the binding site residues and the ligand was mTargetDB when a query molecule is uploaded, and lists the allowed to move freely. The box was set to 40×40×40, and top N best-fit hits with appropriate target annotations, as well the center coordinate was shown in Tables 4 and 5. Other pa- as the aligned poses of the respective molecules.17) rameters were kept to default values. Molecular file of dolastatin 16 was submitted to the Visualization Visualization of the complex structure was PharmMapper server. The parameters were set as follows; the performed using PyMOL molecular graphics system, and the generate conformers were set to yes, the maximum generated protein–ligand interactions were shown by discovery studio conformations were set to 300, targets setting was set to “All version 2016. Targets (7302),” and the number of reserved matched targets was set to 300.9,18) Other parameters were set to default. Results and Discussion Targets Checked by the CPI The chemical–protein Protein Target Prediction by PharmMapper We per- interactome (CPI) refers to the interaction information of a formed a virtual screening to identify the potential targets of panel of chemicals across a panel of target proteins in terms of dolastatin 16 that match the pharmacophore models within binding strength and binding conformation for each chemical- the protein database of PharmMapper. Our result shows 300 protein pocket pair.19) Both drug–drug interactions (DDI)–CPI hits, with the top ten listed in Table 1. Peptidyl–prolyl cis– and drug repositioning potential and adverse drug reactions trans isomerase FKBP1A (PDB ID: 1BL4) ranked number (DRAR)–CPI are free servers for predicting these interactions one virtual target for dolastatin 16, showing five hydrophobic via the CPI.20,21) sites and four acceptors (Fig. 2) within the pharmacophore The molecular file of FK506 was extracted from the groups. FKBP1A is the target of FK506,25) which is a novel complex of the target protein (PDB ID: 1FKF), which was immunosuppressant agent. The alignment of FK506 and downloaded from the RCSB Protein Data Bank, and together pharmacophore models using PharmMapper was depicted in with the molecular file of dolastatin 16 were then pretreated Fig. 3, showing six hydrophobic sites, one donor, as well as following the web instructions as described previously.21) Then two acceptors. Furthermore, alignment information of the two they were submitted to the DDI–CPI and DRAR–CPI servers, small molecules and the pharmacophore model candidates parameters used default values. shown in Figs. 2 and 3, further support the PharmMapper Molecular Docking Molecular docking is a computa- results. Molecular modeling study of FK506–FKBP1A has tional procedure, which attempts to predict binding of a small been extensively conducted, which provides applicable and molecule (ligand) and a macromolecule (receptor) efficiently.22) comparable pharmacophore information for modeling analysis Autodock vina is a new open-source program, useful for mo- of potential target of dolastatin 16 by computational virtual lecular docking and virtual screening which, when compared screening.26–28) Therefore, a detailed comparison study of dol- to autodock 4, performs docking at higher speed and accura- astatin 16–FKBP1A vs.