PADFrag: a database built for the exploration of bioactive fragment

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PADFrag: a database built for the exploration of bioactive fragment space for drug discovery Jing-Fang Yang, Fan Wang, wen jiang, Guang-You Zhou, ChengZhang Li, Xiao Lei Zhu, Ge-Fei Hao, and Guang-Fu Yang J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.8b00285 • Publication Date (Web): 23 Aug 2018 Downloaded from http://pubs.acs.org on August 23, 2018

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Journal of Chemical Information and Modeling

PADFrag: A Database Built for the Exploration of Bioactive Fragment Space for Drug Discovery Jing-Fang Yang, †, #, ∥ Fan Wang, †, #, ∥ Wen Jiang, †, #, ∥ Guang-You Zhou, § Cheng-Zhang Li, †, # Xiao-Lei Zhu, †, # Ge-Fei Hao, †, #, * and Guang-Fu Yang †, ‡, #, *

†

Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan 430079, P.R. China #

International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University，Wuhan, 430079, China ‡

Collaborative Innovation Center of Chemical Science and Engineering, Tianjing 300072, P.R. China

§

School of Computer Science, Central China Normal University, Wuhan 430079

ABSTRACT: Structural analyses of drugs and pesticides can enable the identification of new bioactive compounds with novel and diverse scaffolds as well as improve our understanding of the bioactive fragment space. The Pesticide And Drug Fragments (The Pesticide And Drug Fragments (PADFrag) database is a unique bioinformatic–cheminformatic cross-referencing resource that combines detailed bioactive fragment data and potential targets with a strong focus on quantitative, analytic, and molecular-scale information for the exploration of bioactive fragment space for drug discovery). The main applications of PADFrag are the analysis of the privileged structures within known bioactive molecules, ab initio molecule library design, and core fragment discovery for fragment-based drug design. Other potential applications include prediction of fragment interactions and general pharmaceutical research.

encode an enormously large number of chemical strucINTRODUCTION tures in a very compact format both for similarity-based Strategies for drug discovery have signiﬁcantly changed (2D) and structure-based (3D) de novo design applicaover recent decades, but despite the manpower, materials, tions.5 Thus, exploration within chemical space may be and financial resources that have been invested, few new accomplished with a relatively small number of moleleading compounds have been discovered. Combinatorial cules. Methods in fragment-based drug discovery (FBDD) chemistry and high-throughput screening (HTS) reprecan be applied to exploration of chemical space to maxsent major milestones in drug discovery research.1 Conimize the chance of identifying leads.6 An increasing comitant with these advances, a fundamental scientific number FBDD tools are available for searching fragments question arose regarding the number of molecules that and providing precise descriptions of the fragment space. are theoretically possible, which led to the concept of Examples include the search for and classification of molchemical space.2 This concept is considered analogous to ecules using physicochemical constraints,7 scaffold hopthe cosmos in its broadness, with chemicals, rather than ping,8 design of molecular architectures based on ligstars, populating ‘space’. Estimates of the possible size of 13 180 ands,9 a structure-based search within large fragment the chemical universe range from 10 up to 10 mole3 spaces,10 and a similarity-driven library design.11 cules. Explorations of the huge space relevant to biology The experience from multiple fragment-screening efforts have advanced our knowledge of biological processes and has shown that commercially available fragment libraries led to new strategies to treat disease. Yet, only a tiny fracare inadequate for sampling the chemical space of drugtion of the chemical space has been explored.4 like molecules.12 To discover the 'stars' in fragment space Fragment space, or theoretical combinations of molecular that may have relevant biological activity, computational fragments, is exponentially smaller than the chemical tools have been designed to generate libraries of drug-like space relevant to biology. It can offer the possibility to ACS Paragon Plus Environment

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fragments.13 Fragment libraries have been developed by academics, such as the FragmentStore,14 e-Drug3D,15 FDB17,16 and other databases. Analyzing privileged structures in known bioactive molecules can provide shortcuts for drug design. This is because fragments from existing drugs are more likely to possess the appropriate ADMET (absorption, distribution, metabolism, excretion and toxicity) properties than are fragments chosen randomly.17 To facilitate the identification of novel lead compounds, we established a library of virtual fragments of drug and pesticide molecules and named it the Pesticide and Drug Fragment (PADFrag) database. The PADFrag database systematically lists the most popular, and therefore most easily used, substituents and ring systems for synthesizing new compounds and draws attention to unexplored areas of chemical space. PADFrag aids in the determination of the chemical space of active fragments, the frequency of fragments, and the co-occurrence of a single fragment in different molecules. To our knowledge, PADFrag is the first database to define and explore the biologically relevant fragment space by comparing pesticide and drug fragments.

RESULTS AND DISCUSSION Database Description. Privileged fragments, commonly found in known drug and pesticide molecules, are valuable starting points for exploring biologically relevant chemical space. PADFrag was designed to provide free and ready-to-screen virtual collections of substructures of pesticides and drugs. In recent years, several drug- and pesticide-speciﬁc databases have become publicly available including ChEMBL,18 DrugBank,19 SuperDrug,20 Alan

Wood,21 and others. The most popular freely accessible annotated resource is DrugBank, which combines detailed drug data with comprehensive drug target information. ChEMBL contains bioactivity data as well as compound and target information from high-throughput screening experiments described in tens of thousands of scientific articles. SuperDrug contains 3-dimensional (3D) structures and data regarding the active ingredients of essential marketed drugs. The Alan Wood database is intended to provide detailed annotation of all pesticides, including: common and systematic chemical names, Chemical Abstracts Service (CAS) registry numbers, and structural and molecular formulae. These databases provide detailed annotative information regarding compounds but are not useful for FBDD. PADFrag fills this gap. PADFrag is a bioinformatic–cheminformatic cross reference database containing both bioactive fragments and potential targets. The focus is analytic, quantitative, and molecular-scale information. Via fragmenting and similarity mapping, our objective in developing PADFrag was to understand associations among fragments in molecules, the source and frequency of fragments, and the proteins they may bind (Figure 1). PADFrag currently contains 1652 Food and Drug Association (FDA)-approved drugs, 1259 commercial pesticides, and 5919 generated molecular fragments. External links are provided to the DrugBank and Alan Wood database, which are convenient for searching. Structure-based virtual screening has become popular, targets the interaction between receptor and ligands, and is used to predict the binding of ligands to target proteins

Figure 1. Flowchart of the design of PADFrag and its relevance to bioactive fragment space.

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Journal of Chemical Information and Modeling from the chemical library.22 However, users cannot download the 3D structures of pesticides from the Alan Wood or ChEMBL databases directly. Therefore, PADFrag has recorded the 3D structures, physicochemical properties, and target information for these molecules. Each molecule entry contains chemical data and target interaction data. PADFrag includes both data-rich biological target content, which was normally found in target databases, such as PDBbind23 with the equally rich data found in medicinal chemistry databases. Thus, we bring these disparate types of data together into one freely available resource, providing a platform for researchers from diverse disciplines and backgrounds to conduct in silico learning and discovery. Fragment Library Design. To understand the structure of drug and pesticide candidates, the first issue to consider is how to reasonably dissect drugs and pesticides into fragments. To develop PADFrag, an in silico fragment generation and recombination protocol was used to divide molecules into chains and rings, because any molecule can be considered a combination of chains and rings (Figure S1). The backbone of the drug or pesticide is usually a ring structure(s). Linker structures reflect degrees of freedom, while molecular diversity is enhanced by side chain structures. All fragments are filtered by the ‘rule of three’24 as follows: molecular weight (MW) 150 Da. In terms of polarity, histograms of the number of hydrogen bond acceptors (nHBAcc_Lipinski) and number of hydrogen bond donors (nHBDon_Lipinski) for drug fragments are similar to those for pesticide fragments, while the FDB-17 has a broader coverage of the scale. Furthermore, the FDB-17 fragments have a higher polarity than drug or pesticide fragments as estimated by the Ghose-Crippen LogKow (AlogP) and topological polar surface area (TopoPSA); 52% of FDB-17 fragments have AlogP values 45 Å2. The sampling across polarity values reveals that the FDB-17 has a broader coverage



of AlogP and TopoPSA. The minimal difference between the three datasets emerges when the number of rotatable bonds is considered. To compare active drug and pesticide fragments with virtual fragments from the FBD-17 based on molecular properties, principal component analysis (PCA) has been used to generate a reference chemical space with reduced dimensionality.27-29 Generally, PCA is an orthogonal linear transformation technique that is used to translate data into a new 2D or 3D coordinate system. The top three variables are termed the first, second, and third principal components (PC1, PC2, and PC3, respectively). The plot of these is shown in Figure S3A and accounts for 80% of the variance. The normalized loadings indicate that the first three principal components contain high loadings (Figure S3B). In addition, PC1, which was used to describe size and shape, has significant loadings from the number of heavy atoms (nHeavyAtom), number of carbon atoms (nC), first kappa shape index (Kier1), and molecular weight (MW). PC2, which was used to describe polarity and lipophilicity, contains contributions from GhoseCrippen LogKow (AlogP), number of hydrogen bond acceptors (nHBAcc_Lipinski), number of hydrogen bond donors (nHBDon_Lipinski), and topological polar surface area (TopoPSA). PC3, which was used to describe flexibility and rigidity, contains contributions from the number of rotatable bonds (nRotB), number of rings (nRing), and fraction of rotatable bonds (RotBFrac) (Table S1). The input matrix is given in the ‘Download’ module of PADFrag and can be downloaded from the ‘Download’ webpage of PADFrag. Figure S3C and S3D illustrate the PCA results with the descriptors in n-dimensional spaces mapped onto 3D space. Three databases are within the same space. The space occupied by the virtual fragments from the FDB-17 included almost of all the active fragments (Figure S3C, D). The drug or pesticide fragments are located within the densely populated area of the virtual fragments, and pesticide fragments are within the chemical space of the drugs. Therefore, the active fragments are in the focused library. However, there are drug and pesticide fragments that occupy space not shared by FDB-17 fragments. PADFrag Web Site. PADFrag is an available webenabled resource that includes features for viewing, sorting, and extracting fragment or related drug and pesticide data as well as building tools. The database can be searched through the designated links, which are located at the top of the PADFrag home website page. All of the summary tables of PADFrag can be rapidly searched and sorted and are linked to the DrugBank or Alan Wood databases in the same manner as other databases. The information is divided into sub-tables for convenience and rapid searching, and these are linked to ‘ID LINK’ in the summary table in the leftmost column, which opens a webpage describing the molecule in detail. In addition to structural, textual and comprehensive numeric data, each molecule entry also contains the fre-

quency, source, and analogs of the fragments. Abstracts, hyperlinks to other databases, digital images, and interactive applets to view molecular structures are included. As with other web-enabled databases, PADFrag supports standard text queries with a text search box located in the search module and offers structure queries through the structure search box for navigating to similar molecules in the same module. PADFrag provides a specialized ‘Build’ tool, which is designed to allow computational and medicinal chemists to perform in silico drug screening. This particular tool provides a growing virtual fragment to construct a novel molecule library. In addition, all the fragment 3D structure files can be freely downloaded from PADFrag using the ‘Download’ buttons. Detailed instructions for searching and using the tools are provided on the PADFrag homepage.

Figure 2. Inhibitors of MAPK. Database Utility. Protein kinases function to regulate cell signaling pathways and contribute to diseases such as cancer, chronic inflammation, diabetes, and Alzheimer’s disease. Members of the mitogen-activated protein kinase (MAPK) family are characterized by high sequence similarity and conserved motifs, including c-Jun N-terminal kinases (JNKs), p38, and others, which can be quickly activated. Nevertheless, the various MAPKs respond to different extracellular stimuli, and thus, selective modulation of MAPK activity may provide targets for therapy. To prove the validity of PADFrag, we collected many cases of scaffold optimization with bioactive fragments from literatures (see details in Table S2 in supporting information). Two examples are used herein to describe the usage of PADFrag for the discovery of bioactive fragments in MAPKs.30, 31 Case Study 1: Discovery of an inhibitor of p38 MAPK with high activity. A novel inhibitor (compound a) is shown in Figure 2. Its binding pocket, inside the target kinase, is distinct from that of ATP. To improve binding affinity, users can build a combinatorial library with the core pharmacophore (1-(3-(tert-butyl)-1-methyl-1Hpyrazol-5-yl)-3-phenylurea) and conduct virtual screening by applying the ‘Build’ module in PADFrag. The core is drawn in the JME molecular editor, with the link point (X) and select suitable active fragment database (fragments from FDA-approved drugs, fragments from com-


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Journal of Chemical Information and Modeling mercial

Figure 3. Screenshots of some PADFrag modules. A. Screenshot of the ‘Build’ module. B, C. Screenshots of the binding mode and energy decomposition of fragments in the binding site of p38α MAPK in the ‘Map2PDB’ module. After replacement and optimization, the IC50 for p38α pesticides, or all fragments). This is assembled onto the was improved from 4.3 nM to 0.74 nM, but not for JNKs core pharmacophore (Figure 3A). The physicochemical in accordance with the X-score, and the binding energy threshold is then set to filter the fragments in the fragdecomposition of it is similar to that of pyrido[3,2ment database. The job is submitted by clicking ‘BUILD.’ d]pyrimidin-2(1H)-one (Figure 3C, PDBID: 1OVE) .33 Users obtain the result through the webpage or a link sent through email. All the results can be downloaded, includCONCLUSION ing the mol2 file of input core pharmacophores and all Drug and pesticide compounds from the DrugBank and the combinatorial compounds library built through linkAlan Wood databases were segmented into linkers, rings, ing the chosen fragments to a core pharmacophore fragand side chains. This information was used to successfully ment at a specified linking point can be downloaded. In assemble PADFrag, a unique fragment library-relevant to the result, 2-morpholinoethanol (FDBF04167), which exbioactive fragment space. Herein, the uniqueness of ists in the drugs pinaverium bromide and pholcodine, was PADFrag was described and demonstrated as related to linked with the core to produce a new compound with the data types, their integration, and the database’s depth improved potency (∼11-fold). Alternatively, replacing the of coverage. Structural inspection and energy optimizamethyl substituent on the pyrazole ring with a toluene tion were performed for each fragment. The distributions group (FDBF00023, ∼140-fold enhancement in affinity) afof molecular size, structure, polarity, and flexibility of forded compound b. After structural optimization, the drug and pesticide fragments have been analyzed and are affinity of compound b was enhanced from 1,160 nM to 0.1 available. We believe that these data can be used to denM.32 termine the chemical space of active fragments, the freCase Study 2: Structural optimization of a MAPK inquency of fragments, and the co-occurrence of one fraghibitor with specificity based on a similar search. ment in different molecules. PADFrag can support the Compound c is a competitive inhibitor with ATP, binding creation of novel lead compounds for the synthesis of new to the ATP-binding site of p38α, rather than JNKs, and is a compounds by linking the most popular fragments or the candidate compound for optimization (Figure 2). Pyrido most easily used ring systems and substituents. Further[3, 2-d] pyrimidin-2(1H)-one is a core fragment that forms more, PADFrag enables core fragment discovery and ab a hydrogen bond with Met109 and Gly100 in‘Map2PDB’ initio molecule library design for FBDD. PADFrag should module (Figure 3B, PDBID: 1OUY), which is similar to 3, serve as a valuable platform for the pharmaceutical re4-dihydro-1H-quinolin-2-one (FDBF01179) in PADFrag.



search community, clinicians, students, educators, and even the general public.

ASSOCIATED CONTENT Supporting Information. The Supporting Information is available free of charge on the ACS Publications website and presents the method for building PADFrag, the process of fragmentation (Figure S1), the property histograms for FDB-17, drug, and pesticide fragments (Figure S2), and results of PCA (Figure S3).

AUTHOR INFORMATION Corresponding Authors * E-mail: [email protected] (G.-F.Y). * E-mail: [email protected] (G.-F.H).

ORCID Guang-Fu Yang: 0000-0003-4384-2593 Ge-Fei Hao: 0000-0003-4090-8411 Jing-Fang Yang: 0000-0002-3507-1664 Fan Wang: 0000-0003-2664-9214 Wen Jiang: 0000-0003-0870-3934 Guang-You Zhou: 0000-0002-7675-6619 Cheng-Zhang Li: 0000-0002-4352-9110 Xiao-Lei Zhu: 0000-0002-5672-5209

Author Contributions ∥These authors contributed equally.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT This research was supported in part by the National Key R&D Program (2017YFA0505203), the National Natural Science Foundation of China (No. 21332004 and 21472060), and A Foundation for the Author of National Excellent Doctoral Dissertation of PR China (No. 201472).

CONFLICT OF INTEREST The authors declare that there is no conflict of interest, financial or otherwise.

REFERENCES (1) Munos, B. Can Open-Source Drug R&D Repower Pharmaceutical Innovation? Clin. Pharmacol. Ther. 2010, 87, 534-536. (2) Lipinski, C.; Hopkins, A. Navigating chemical space for biology and medicine. Nature 2004, 432, 855-861. (3) Gorse, A. D. Diversity in medicinal chemistry space. Curr. Top. Med. Chem. 2006, 6, 3-18. (4) Dobson, C. M. Chemical space and biology. Nature 2004, 432, 824828. (5) Mauser, H.; Stahl, M. Chemical fragment spaces for de novo design. J. Chem. Inf. Model. 2007, 47, 318-324. (6) Hajduk, P. J.; Greer, J. A decade of fragment-based drug design: strategic advances and lessons learned. Nat. Rev. Drug Discov. 2007, 6, 211-219.

Page 6 of 9

(7) Parn, J.; Degen, J.; Rarey, M. Exploring fragment spaces under multiple physicochemical constraints. J. Comput. Aided Mol. Des. 2007, 21, 327-340. (8) Maass, P.; Schulz-Gasch, T.; Stahl, M.; Rarey, M. Recore: A fast and versatile method for scaffold hopping based on small molecule crystal structure conformations. J. Chem. Inf. Model. 2007, 47, 390-399. (9) Schneider, G.; Lee, M. L.; Stahl, M.; Schneider, P. De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks. J. Comput. Aided Mol. Des. 2000, 14, 487-494. (10) Degen, J.; Rarey, M. FlexNovo: Structure-based searching in large fragment spaces. ChemMedChem 2006, 1, 854-868. (11) Fischer, J. R.; Lessel, U.; Rarey, M. LoFT: Similarity-Driven Multiobjective Focused Library Design. J. Chem. Inf. Model. 2010, 50, 121. (12) Arnold, E. Fragment Screening for Drug Discovery: Efficient Approaches for Exploring Chemical Space. Prog. Biophys. Mol. Biol. 2014, 116, 81-81. (13) Lauck, F.; Rarey, M. FSees: Customized Enumeration of Chemical Subspaces with Limited Main Memory Consumption. J. Chem. Inf. Model. 2016, 56, 1641-1653. (14) Ahmed, J.; Worth, C. L.; Thaben, P.; Matzig, C.; Blasse, C.; Dunkel, M.; Preissner, R. FragmentStore—a comprehensive database of fragments linking metabolites, toxic molecules and drugs. Nucleic Acids Res. 2011, 39, D1049-D1054. (15) Pihan, E.; Colliandre, L.; Guichou, J.-F.; Douguet, D. e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design. Bioinformatics 2012, 28, 1540-1541. (16) Visini, R.; Awale, M.; Reymond, J.-L. Fragment Database FDB-17. J. Chem. Inf. Model. 2017, 57, 700-709. (17) Wang, J. M.; Hou, T. J. Drug and Drug Candidate Building Block Analysis. J. Chem. Inf. Model. 2010, 50, 55-67. (18) Gaulton, A.; Bellis, L. J.; Bento, A. P.; Chambers, J.; Davies, M.; Hersey, A.; Light, Y.; McGlinchey, S.; Michalovich, D.; Al-Lazikani, B.; Overington, J. P. ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res. 2012, 40, D1100-D1107. (19) Law, V.; Knox, C.; Djoumbou, Y.; Jewison, T.; Guo, A. C.; Liu, Y.; Maciejewski, A.; Arndt, D.; Wilson, M.; Neveu, V.; Tang, A.; Gabriel, G.; Ly, C.; Adamjee, S.; Dame, Z. T.; Han, B.; Zhou, Y.; Wishart, D. S. DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res. 2014, 42, D1091-D1097. (20) Siramshetty, V. B.; Eckert, O. A.; Gohlke, B. O.; Goede, A.; Chen, Q.; Devarakonda, P.; Preissner, S.; Preissner, R. SuperDRUG2: a one stop resource for approved/marketed drugs. Nucleic Acids Res. 2018, 46, D1137-D1143. (21) A database of pesticide. http://www.alanwood.net/pesticides/index.html (accessed Mar 2, 2018). (22) Shoichet, B. K. Virtual screening of chemical libraries. Nature (London) 2004, 432, 862-865. (23) Liu, Z. H.; Li, Y.; Han, L.; Li, J.; Liu, J.; Zhao, Z. X.; Nie, W.; Liu, Y. C.; Wang, R. X. PDB-wide collection of binding data: current status of the PDBbind database. Bioinformatics 2015, 31, 405-412. (24) Jhoti, H.; Williams, G.; Rees, D. C.; Murray, C. W. The 'rule of three' for fragment-based drug discovery: where are we now? Nat. Rev. Drug Discov. 2013, 12, 644-645. (25) Teague, S. J. Learning lessons from drugs that have recently entered the market. Drug Discov. Today 2011, 16, 398-411. (26) Leach, A. R.; Hann, M. M. The in silico world of virtual libraries. Drug Discov. Today 2000, 5, 326-336. (27) Bender, A.; Jenkins, J. L.; Scheiber, J.; Sukuru, S. C. K.; Glick, M.; Davies, J. W. How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space. J. Chem. Inf. Model. 2009, 49, 108-119. (28) Oprea, T. I.; Gottfries, J. Chemography: the art of navigating in chemical space. J. Comb. Chem. 2001, 3, 157-166. (29) Lachance, H.; Wetzel, S.; Kumar, K.; Waldmann, H. Charting, Navigating, and Populating Natural Product Chemical Space for Drug Discovery. J. Med. Chem. 2012, 55, 5989-6001. (30) Derijard, B.; Hibi, M.; Wu, I. H.; Barrett, T.; Su, B.; Deng, T.; Karin, M.; Davis, R. J. JNK1: a protein kinase stimulated by UV light and HaRas that binds and phosphorylates the c-Jun activation domain. Cell 1994, 76, 1025-1037. (31) Han, J.; Lee, J. D.; Bibbs, L.; Ulevitch, R. J. A MAP kinase targeted by endotoxin and hyperosmolarity in mammalian cells. Science (New York,


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Journal of Chemical Information and Modeling N.Y.) 1994, 265, 808-811. (32) Pargellis, C.; Tong, L.; Churchill, L.; Cirillo, P. F.; Gilmore, T.; Graham, A. G.; Grob, P. M.; Hickey, E. R.; Moss, N.; Pav, S.; Regan, J. Inhibition of p38 MAP kinase by utilizing a novel allosteric binding site. Nat. Struct. Biol. 2002, 9, 268-272. (33) Fitzgerald, C. E.; Patel, S. B.; Becker, J. W.; Cameron, P. M.; Zaller, D.; Pikounis, V. B.; O'Keefe, S. J.; Scapin, G. Structural basis for p38alpha MAP kinase quinazolinone and pyridol-pyrimidine inhibitor specificity. Nat. Struct. Biol. 2003, 10, 764-769.




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Journal of Chemical Information and Modeling

TOC: PADFrag: a database built for the exploration of bioactive frag-ment space for drug discovery JingFang Yang †, ‡, ∥, Fan Wang†, ‡, ∥, Wen Jiang†, ‡, ∥, Guang-You Zhou§, Cheng-Zhang Li†, Xiao-Lei Zhu†, Ge-Fei Hao†,*, and Guang-Fu Yang†, ‡,* 66x34mm (300 x 300 DPI)


PADFrag: a database built for the exploration of bioactive fragment

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