Bibliography of computer-aided Drug Design
Updated on 7/18/2014. Currently 2130
Screening / Web services
istar: a web platform for large-scale protein-ligand docking.
Li, Hongjian and Leung, Kwong-Sak and Ballester, Pedro J and Wong, Man-Hon
PloS one, 2014, 9(1), e85678
Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at http://istar.cse.cuhk.edu.hk/idock.
Accessible high-throughput virtual screening molecular docking software for students and educators.
Jacob, Reed B. and Andersen, Tim and McDougal, Owen M.
PLoS computational biology, 2012, 8(5), e1002499
We survey low cost high- throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms.
ChemBioServer: a web-based pipeline for filtering, clustering and visualization of chemical compounds used in drug discovery
Athanasiadis, Emmanouil and Cournia, Zoe and Spyrou, George
Bioinformatics (Oxford, England), 2012, 28(22), 3002-3003
Summary: ChemBioServer is a publicly available web application for effectively mining and filtering chemical compounds used in drug discovery. It provides researchers with the ability to (i) browse and visualize compounds along with their properties, (ii) filter chemical compounds for a variety of properties such as steric clashes and toxicity, (iii) apply perfect match substructure search, (iv) cluster compounds according to their physicochemical properties providing representative compounds for each cluster, (v) build custom compound mining pipelines and (vi) quantify through property graphs the top ranking compounds in drug discovery procedures. ChemBioServer allows for pre-processing of compounds prior to an in silico screen, as well as for post-processing of top-ranked molecules resulting from a docking exercise with the aim to increase the efficiency and the quality of compound selection that will pass to the experimental test phase.Availability: The ChemBioServer web application is available at: http://bioserver-3.bioacademy.gr/Bioserver/ChemBioServer/.Contact: firstname.lastname@example.org
COPICAT: A software system for predicting interactions between proteins and chemical compounds.
Sakakibara, Yasubumi and Hachiya, Tsuyoshi and Uchida, Miho and Nagamine, Nobuyoshi and Sugawara, Yohei and Yokota, Masahiro and Nakamura, Masaomi and Popendorf, Kris and Komori, Takashi and Sato, Kengo
Bioinformatics (Oxford, England), 2012, 28(5), 745-746
SUMMARY: Since tens of millions of chemical compounds have been accumulated in public chemical databases, fast comprehensive computational methods to predict interactions between chemical compounds and proteins are needed for virtual screening of lead compounds. Previously, we proposed a novel method for predicting protein-chemical interactions using two-layer Support Vector Machine classifiers that require only readily available biochemical data, i.e., amino acid sequences of proteins and structure formulas of chemical compounds.In this paper, the method has been implemented as the COPICAT web service, with an easy-to-use front-end interface. Users can simply submit a protein-chemical interaction prediction job using a pre-trained classifier, or can even train their own classification model by uploading training data. COPICAT's fast and accurate computational prediction has enhanced lead compound discovery against a database of tens of millions of chemical compounds, implying that the search space for drug discovery is extended by more than 1,000 times compared with currently well-used high-throughput screening methodologies. AVAILABILITY: The COPICAT server is available at http://copicat.dna.bio.keio.ac.jp. All functions, including the prediction function are freely available via anonymous login without registration. Registered users, however, can use the system more intensively. CONTACT: email@example.com.
iSMART: an integrated cloud computing web server for traditional Chinese medicine for online virtual screening, de novo evolution and drug design.
Chang, Kai-Wei and Tsai, Tsung-Ying and Chen, Kuan-Chung and Yang, Shun-Chieh and Huang, Hung-Jin and Chang, Tung-Ti and Sun, Mao-Feng and Chen, Hsin-Yi and Tsai, Fuu-Jen and Chen, Calvin Yu-Chian
Journal of biomolecular structure & dynamics, 2011, 29(1), 243-250
iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan
Tsai, Tsung-Ying and Chang, Kai-Wei and Chen, Calvin Yu-Chian
Journal of computer-aided molecular design, 2011, 25(6), 525-531
The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.
MMsINC: a large-scale chemoinformatics database.
Masciocchi, Joel and Frau, Gianfranco and Fanton, Marco and Sturlese, Mattia and Floris, Matteo and Pireddu, Luca and Palla, Piergiorgio and Cedrati, Fabian and Rodriguez-Tomé, Patricia and Moro, Stefano
Nucleic acids research, 2009, 37(Database issue), D284-90
MMsINC (http://mms.dsfarm.unipd.it/MMsINC/search) is a database of non-redundant, richly annotated and biomedically relevant chemical structures. A primary goal of MMsINC is to guarantee the highest quality and the uniqueness of each entry. MMsINC then adds value to these entries by including the analysis of crucial chemical properties, such as ionization and tautomerization processes, and the in silico prediction of 24 important molecular properties in the biochemical profile of each structure. MMsINC is consequently a natural input for different chemoinformatics and virtual screening applications. In addition, MMsINC supports various types of queries, including substructure queries and the novel 'molecular scissoring' query. MMsINC is interfaced with other primary data collectors, such as PubChem, Protein Data Bank (PDB), the Food and Drug Administration database of approved drugs and ZINC.
Automated Docking Screens: A Feasibility Study
Irwin, John J and Shoichet, Brian K and Mysinger, Michael M. and Huang, Niti and Colizzi, Francesco and Wassam, Pascal and Cao, Yiqun
Journal of medicinal chemistry, 2009, 52(18), 5712-5720
Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 angstrom rmsd 50-60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 angstrom rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org.
PDTD: a web-accessible protein database for drug target identification
Gao, Zhenting and Li, Honglin and Zhang, Hailei and Liu, Xiaofeng and Kang, Ling and Luo, Xiaomin and Zhu, Weiliang and Chen, Kaixian and Wang, Xicheng and Jiang, Hualiang
Bmc Bioinformatics, 2008, 9, -
Background: Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D) structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking) http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD), and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation.Description: PDTD is a web-accessible protein database for in silico target identification. It currently contains > 1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of > 830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling) pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores.Conclusion: PDTD serves as a comprehensive and unique repository of drug targets. Integrated with TarFisDock, PDTD is a useful resource to identify binding proteins for active compounds or existing drugs. Its potential applications include in silico drug target identification, virtual screening, and the discovery of the secondary effects of an old drug (i.e. new pharmacological usage) or an existing target (i.e. new pharmacological or toxic relevance), thus it may be a valuable platform for the pharmaceutical researchers. PDTD is available online at http://www.dddc.ac.cn/pdtd/.
TarFisDock: a web server for identifying drug targets with docking approach
Li, Honglin and Gao, Zhenting and Kang, Ling and Zhang, Hailei and Yang, Kun and Yu, Kunqian and Luo, Xiaomin and Zhu, Weiliang and Chen, Kaixian and Shen, Jianhua and Wang, Xicheng and Jiang, Hualiang
Nucleic acids research, 2006, 34(Web Server issue), W219-W224
TarFisDock is a web-based tool for automating the procedure of searching for small molecule-protein interactions over a large repertoire of protein structures. It offers PDTD (potential drug target database), a target database containing 698 protein structures covering 15 therapeutic areas and a reverse ligand protein docking program. In contrast to conventional ligand-protein docking, reverse ligand-protein docking aims to seek potential protein targets by screening an appropriate protein database. The input file of this web server is the small molecule to be tested, in standard mol2 format; TarFisDock then searches for possible binding proteins for the given small molecule by use of a docking approach. The ligand-protein interaction energy terms of the program DOCK are adopted for ranking the proteins. To test the reliability of the TarFisDock server, we searched the PDTD for putative binding proteins for vitamin E and 4H-tamoxifen. The top 2 and 10% candidates of vitamin E binding proteins identified by TarFisDock respectively cover 30 and 50% of reported targets verified or implicated by experiments; and 30 and 50% of experimentally confirmed targets for 4H-tamoxifen appear amongst the top 2 and 5% of the TarFisDock predicted candidates, respectively. Therefore, TarFisDock may be a useful tool for target identification, mechanism study of old drugs and probes discovered from natural products. TarFisDock and PDTD are available at http://www.dddc.ac.cn/tarfisdock/.