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BioMed Research International Network Proteomics: From Protein Structure to Protein-Protein Interaction Guest Editors: Guang Hu, Luisa Di Paola, Filippo Pullara, Zhongjie Liang, and Intawat Nookaew Network Proteomics: From Protein Structure to Protein-Protein Interaction BioMed Research International Network Proteomics: From Protein Structure to Protein-Protein Interaction Guest Editors: Guang Hu, Luisa Di Paola, Filippo Pullara, Zhongjie Liang, and Intawat Nookaew Copyright © 2017 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Network Proteomics: From Protein Structure to Protein-Protein Interaction Guang Hu, Luisa Di Paola, Filippo Pullara, Zhongjie Liang, and Intawat Nookaew Volume 2017, Article ID 8929613, 1 page Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists Yuwei Wang, Rui Han, Huimin Zhang, Hongli Liu, Jiazhong Li, Huanxiang Liu, and Paola Gramatica Volume 2017, Article ID 3572394, 18 pages Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case Guang Hu, Luisa Di Paola, Zhongjie Liang, and Alessandro Giuliani Volume 2017, Article ID 2483264, 15 pages Biomolecular Network-Based Synergistic Drug Combination Discovery Xiangyi Li, Guangrong Qin, Qingmin Yang, Lanming Chen, and Lu Xie Volume 2016, Article ID 8518945, 11 pages Identification of Hot Spots in Protein Structures Using Gaussian Network Model and Gaussian Naive Bayes Hua Zhang, Tao Jiang, and Guogen Shan Volume 2016, Article ID 4354901, 9 pages Identification of Novel Inhibitors against Coactivator Associated Arginine Methyltransferase 1 Based onVirtualScreeningandBiologicalAssays Fei Ye, Weiyao Zhang, Wenchao Lu, Yiqian Xie, Hao Jiang, Jia Jin, and Cheng Luo Volume 2016, Article ID 7086390, 8 pages Potential Role of the Last Half Repeat in TAL Effectors Revealed by a Molecular Simulation Study Hua Wan, Shan Chang, Jian-ping Hu, Xu-hong Tian, and Mei-hua Wang Volume 2016, Article ID 8036450, 11 pages Networks Models of Actin Dynamics during Spermatozoa Postejaculatory Life: A Comparison among Human-Made and Text Mining-Based Models Nicola Bernabò, Alessandra Ordinelli, Marina Ramal Sanchez, Mauro Mattioli, and Barbara Barboni Volume 2016, Article ID 9795409, 8 pages Comparison of FDA Approved Kinase Targets to Clinical Trial Ones: Insights from Their System Profiles and Drug-Target Interaction Networks JingyuXu,PanpanWang,HongYang,JinZhou,YinghongLi,XiaoxuLi,WeiweiXue,ChunyanYu,Yubin Tian, and Feng Zhu Volume 2016, Article ID 2509385,9 pages Sequence- and Structure-Based Functional Annotation and Assessment of Metabolic Transporters in Aspergillus oryzae: A Representative Case Study Nachon Raethong, Jirasak Wong-ekkabut, Kobkul Laoteng, and Wanwipa Vongsangnak Volume 2016, Article ID 8124636, 13 pages Hindawi Publishing Corporation BioMed Research International Volume 2017, Article ID 8929613, 1 page http://dx.doi.org/10.1155/2017/8929613 Editorial Network Proteomics: From Protein Structure to Protein-Protein Interaction Guang Hu,1 Luisa Di Paola,2 Filippo Pullara,3 Zhongjie Liang,1 and Intawat Nookaew4 1 Center for Systems Biology, School of Electronic and Information Engineering, Soochow University, Suzhou 215006, China 2Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Engineering, Universita` Campus Bio-Medico, Rome, Italy 3Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA 4Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA Correspondence should be addressed to Guang Hu; [email protected] Received 3 January 2017; Accepted 4 January 2017; Published 16 February 2017 Copyright © 2017 Guang Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. With the emergence of high-throughput “omics” data, net- Protein-protein interactions not only are limited to work theory is being increasingly used to analyze biomolec- binary associations but also employ special topological struc- ular systems. In particular, proteins rarely act alone, which tures to perform their biological functions. N. Bernaboet` prompted the arrival of proteomics. “Network proteomics” al. approached the comparison of two networks models is just defined as the research area that introduces network obtained from two different text mining tools to suggest that theory to investigate biological networks ranging from pro- actin dynamics affect spermatozoa postejaculatory life. J. Xu tein structure networks to protein-protein interaction net- et al. also compared the topologies of network modes of drug- works. In addition, the application of network proteomics in kinase interactions between established targets and those of biomedical fields has increased significantly. This special issue clinical trial ones. has collected contributions, not only focusing on the state of Both protein structures and protein-protein interactions the art of methodology in “network proteomics” itself but also areinvolvedinthesubjectofagrowingnumberofphar- focusing on the current status and future direction of their macological studies. F. Ye et al. identified that compounds applications in translational medical informatics. DC C11 and DC C66 are two small inhibitors against protein- protein interactions between CARM1 and its substrates, while This issue starts with discussing the role of protein struc- Y. Wang et al. identified that CID 70128824, CID 70127147, ture that participates in interactions. N. Raethong et al. devel- and CID 70126881 are three potential inhibitors for targeting oped a strategy to annotate Aspergillus oryzae,whichwould theandrogenreceptortotreatprostatecancer.Finally,a enhance its metabolic network reconstruction. By using the review paper completes the issue. X. Li et al. introduced molecular dynamics simulation and principle component recent advances in the development of network models of analysis, H. Wan et al. investigated the interaction between identifying synergistic drug combinations. the last half repeat in TAL effectors and its binding DNA. This Altogether, we wish this issue has given a wider devel- work would give a deeper understanding of the recognition opment of structural biology and systems biology with the mechanism of protein-DNA interactions. advantage of biological network analysis as well as prospect- Protein complexes offer detailed structural characteristics ing the future of this area towards translational bioinforma- of protein-protein interactions. H. Zhang et al. proposed a tics and systems pharmacology. method by combining the high frequency modes of Gaussian network model and Gaussian Naive Bayes to identify hot Guang Hu spots, which are residues that contribute largely to protein- Luisa Di Paola protein interaction energy. G. Hu et al. performed a com- Filippo Pullara parative study of elastic network model and protein contact Zhongjie Liang network for protein complexes in case of hemoglobin. Intawat Nookaew Hindawi Publishing Corporation BioMed Research International Volume 2017, Article ID 3572394, 18 pages http://dx.doi.org/10.1155/2017/3572394 Research Article Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists Yuwei Wang,1 Rui Han,1 Huimin Zhang,1 Hongli Liu,1 Jiazhong Li,1 Huanxiang Liu,1 and Paola Gramatica2 1 School of Pharmacy, Lanzhou University, 199 West Donggang Rd., Lanzhou 730000, China 2Department of Theoretical and Applied Sciences, University of Insubria, Via Dunant 3, 21100 Varese, Italy Correspondence should be addressed to Jiazhong Li; [email protected] Received 24 August 2016; Revised 11 October 2016; Accepted 16 November 2016; Published 15 February 2017 Academic Editor: Zhongjie Liang Copyright © 2017 Yuwei Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The antiandrogens, such as bicalutamide, targeting the androgen receptor (AR), are the main endocrine therapies for prostate cancer (PCa). But as drug resistance to antiandrogens emerges in advanced PCa, there presents a high medical need for exploitation of novel AR antagonists. In this work, the relationships between the molecular structures and antiandrogenic activities of a series of 7-substituted dihydrotestosterone derivatives were investigated. The proposed MLR model obtained high predictive ability. The thoroughly validated QSAR model was used to virtually screen new dihydrotestosterones derivatives taken from PubChem, resulting in the finding of novel compounds CID 70128824, CID 70127147, and CID 70126881, whose in silico bioactivities are much higher than the published best one, even higher than bicalutamide. In addition, molecular docking, molecular dynamics (MD) simulations, and MM/GBSA have been employed to analyze and compare the binding modes between the novel compounds and