Sijin Wu has a Ph.D. in Biochemical Engineering and extensive experience in computational biology and computer-aided drug design. His research focuses on protein modeling, molecular dynamics simulation, and virtual screening. He has authored or co-authored over 15 publications and developed databases on proteins with targetable cysteines and cancer stem cell therapeutic targets. Wu seeks postdoctoral opportunities to further his work in these fields.
dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020dkNET
Abstract
Pharos (https://pharos.nih.gov/) is an integrated web-based informatics platform for the analysis of data aggregated by the Illuminating the Druggable Genome (IDG) Knowledge Management Center, an NIH Common Fund initiative. The current version of Pharos (as of October 2019) spans 20,244 proteins in the human proteome, 19,880 disease and phenotype associations, and 226,829 ChEMBL compounds. This resource not only collates and analyzes data from over 60 high-quality resources to generate these types, but also uses text indexing to find less apparent connections between targets, and has recently begun to collaborate with institutions that generate data and resources. Proteins are ranked according to a knowledge-based classification system, which can help researchers to identify less studied “dark” targets that could be potentially further illuminated. This is an important process for both drug discovery and target validation, as more knowledge can accelerate target identification, and previously understudied proteins can serve as novel targets in drug discovery. In this webinar, Dr. Tudor Oprea will introduce how to use Pharos to find targets of interest for drug discovery.
The top 3 key questions that Pharos can answer:
1. What are the novel drug targets that may play a role in a specific disease?
2. What are the diseases that are related directly or indirectly to a drug target?
3. Find researchers that are related directly or indirectly to a drug target.
Presenter: Tudor Oprea, MD, PhD, Professor of Medicine, Chief of Translational Informatics Division & Internal Medicine, University of New Mexico
dkNET Webinar Information: https://dknet.org/about/webinar
Researchers use animal models in basic research, in developing new therapeutic strategies for treating human diseases, and in drug discovery research (including target identification and validation, drug screening and lead optimization, and toxicity and safety screening), as well as in preclinical studies of drug safety and efficacy.
Contribution of genome-wide association studies to scientific research: a pra...Mutiple Sclerosis
Vito A. G. Ricigliano, Renato Umeton, Lorenzo Germinario, Eleonora Alma, Martina Briani, Noemi Di Segni, Dalma Montesanti, Giorgia Pierelli, Fabiana Cancrini, Cristiano Lomonaco, Francesca Grassi, Gabriella Palmieri, and Marco Salvetti,
Struan Frederick Airth Grant, Editor
The factual value of genome-wide association studies (GWAS) for the understanding of multifactorial diseases is a matter of intense debate. Practical consequences for the development of more effective therapies do not seem to be around the corner. Here we propose a pragmatic and objective evaluation of how much new biology is arising from these studies, with particular attention to the information that can help prioritize therapeutic targets. We chose multiple sclerosis (MS) as a paradigm disease and assumed that, in pre-GWAS candidate-gene studies, the knowledge behind the choice of each gene reflected the understanding of the disease prior to the advent of GWAS. Importantly, this knowledge was based mainly on non-genetic, phenotypic grounds. We performed single-gene and pathway-oriented comparisons of old and new knowledge in MS by confronting an unbiased list of candidate genes in pre-GWAS association studies with those genes exceeding the genome-wide significance threshold in GWAS published from 2007 on. At the single gene level, the majority (94 out of 125) of GWAS-discovered variants had never been contemplated as plausible candidates in pre-GWAS association studies. The 31 genes that were present in both pre- and post-GWAS lists may be of particular interest in that they represent disease-associated variants whose pathogenetic relevance is supported at the phenotypic level (i.e. the phenotypic information that steered their selection as candidate genes in pre-GWAS association studies). As such they represent attractive therapeutic targets. Interestingly, our analysis shows that some of these variants are targets of pharmacologically active compounds, including drugs that are already registered for human use. Compared with the above single-gene analysis, at the pathway level GWAS results appear more coherent with previous knowledge, reinforcing some of the current views on MS pathogenesis and related therapeutic research. This study presents a pragmatic approach that helps interpret and exploit GWAS knowledge.
Rhetorical moves and audience considerations in the discussion sections of ra...jodischneider
European Conference on Argumentation talk
Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu “Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions” [Conference Panel Presentation], 2nd European Conference on Argumentation: Argumentation and Inference, Fribourg, Switzerland, June 20-23
1 of 3 talks in Jodi Schneider and Sally Jackson, organizers, “Innovations in Reasoning and Arguing about Health ”[Conference Panel], 2nd European Conference on Argumentation: Argumentation and Inference, Fribourg, Switzerland, June 20-23.
dkNET Webinar: Illuminating The Druggable Genome With Pharos 10/23/2020dkNET
Abstract
Pharos (https://pharos.nih.gov/) is an integrated web-based informatics platform for the analysis of data aggregated by the Illuminating the Druggable Genome (IDG) Knowledge Management Center, an NIH Common Fund initiative. The current version of Pharos (as of October 2019) spans 20,244 proteins in the human proteome, 19,880 disease and phenotype associations, and 226,829 ChEMBL compounds. This resource not only collates and analyzes data from over 60 high-quality resources to generate these types, but also uses text indexing to find less apparent connections between targets, and has recently begun to collaborate with institutions that generate data and resources. Proteins are ranked according to a knowledge-based classification system, which can help researchers to identify less studied “dark” targets that could be potentially further illuminated. This is an important process for both drug discovery and target validation, as more knowledge can accelerate target identification, and previously understudied proteins can serve as novel targets in drug discovery. In this webinar, Dr. Tudor Oprea will introduce how to use Pharos to find targets of interest for drug discovery.
The top 3 key questions that Pharos can answer:
1. What are the novel drug targets that may play a role in a specific disease?
2. What are the diseases that are related directly or indirectly to a drug target?
3. Find researchers that are related directly or indirectly to a drug target.
Presenter: Tudor Oprea, MD, PhD, Professor of Medicine, Chief of Translational Informatics Division & Internal Medicine, University of New Mexico
dkNET Webinar Information: https://dknet.org/about/webinar
Researchers use animal models in basic research, in developing new therapeutic strategies for treating human diseases, and in drug discovery research (including target identification and validation, drug screening and lead optimization, and toxicity and safety screening), as well as in preclinical studies of drug safety and efficacy.
Contribution of genome-wide association studies to scientific research: a pra...Mutiple Sclerosis
Vito A. G. Ricigliano, Renato Umeton, Lorenzo Germinario, Eleonora Alma, Martina Briani, Noemi Di Segni, Dalma Montesanti, Giorgia Pierelli, Fabiana Cancrini, Cristiano Lomonaco, Francesca Grassi, Gabriella Palmieri, and Marco Salvetti,
Struan Frederick Airth Grant, Editor
The factual value of genome-wide association studies (GWAS) for the understanding of multifactorial diseases is a matter of intense debate. Practical consequences for the development of more effective therapies do not seem to be around the corner. Here we propose a pragmatic and objective evaluation of how much new biology is arising from these studies, with particular attention to the information that can help prioritize therapeutic targets. We chose multiple sclerosis (MS) as a paradigm disease and assumed that, in pre-GWAS candidate-gene studies, the knowledge behind the choice of each gene reflected the understanding of the disease prior to the advent of GWAS. Importantly, this knowledge was based mainly on non-genetic, phenotypic grounds. We performed single-gene and pathway-oriented comparisons of old and new knowledge in MS by confronting an unbiased list of candidate genes in pre-GWAS association studies with those genes exceeding the genome-wide significance threshold in GWAS published from 2007 on. At the single gene level, the majority (94 out of 125) of GWAS-discovered variants had never been contemplated as plausible candidates in pre-GWAS association studies. The 31 genes that were present in both pre- and post-GWAS lists may be of particular interest in that they represent disease-associated variants whose pathogenetic relevance is supported at the phenotypic level (i.e. the phenotypic information that steered their selection as candidate genes in pre-GWAS association studies). As such they represent attractive therapeutic targets. Interestingly, our analysis shows that some of these variants are targets of pharmacologically active compounds, including drugs that are already registered for human use. Compared with the above single-gene analysis, at the pathway level GWAS results appear more coherent with previous knowledge, reinforcing some of the current views on MS pathogenesis and related therapeutic research. This study presents a pragmatic approach that helps interpret and exploit GWAS knowledge.
Rhetorical moves and audience considerations in the discussion sections of ra...jodischneider
European Conference on Argumentation talk
Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu “Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions” [Conference Panel Presentation], 2nd European Conference on Argumentation: Argumentation and Inference, Fribourg, Switzerland, June 20-23
1 of 3 talks in Jodi Schneider and Sally Jackson, organizers, “Innovations in Reasoning and Arguing about Health ”[Conference Panel], 2nd European Conference on Argumentation: Argumentation and Inference, Fribourg, Switzerland, June 20-23.
A normal cell can be transformed into a cancerous cell. Discuss the therapeutic strategies that are employed to target the cellular transformation process for cancer prevention and treatment.
New regulations requiring toxicity data on chemicals and an increasing number of efforts to predict the likelihood of failure of molecules earlier in the drug discovery process are combining to increase the utilization of computational models to toxicity. The potential to predict human toxicity directly from a molecular structure is feasible. By using the experimental properties of known compounds as the basis of predictive models it is possible to develop structure activity relationships and resulting algorithms related to toxicity. Several examples have been published recently, including those for drug-induced liver injury (DILI), the pregnane X receptor, P450 3A4 time dependent inhibition, and transporters associated
with toxicities. The versatility and potential of using such models in drug discovery may be illustrated by increasing the efficiency of molecular screening and decreasing the number of animal studies. With more computational power available on increasingly smaller devices, as well as many collaborative initiatives to make data and toxicology models available, this may enable the development of mobile apps for predicting human toxicities, further increasing their utilization.
Citation practices and the construction of scientific fact--ECA-facts-preconf...jodischneider
Citation practices and the construction of scientific fact. Presentation at the European Conference on Argumentation preconference on status, relevance, and authority of facts.
Herbal and Synthetic Drug Combinations in Cancer Therapy A Reviewijtsrd
Cancer is one of the leading and most serious diseases in the current decade, every year millions of people die because of various kinds of cancers. Many aspects relate to the cause of disease besides heredity, food habits, smoking, nutritional behaviors, radiation etc. Cancer is a high mortality disease and the therapeutics for cancer, especially for cancer metastasis is still imperfect. The successful cancer treatment till now has been under study, only chemotherapy and radiation treatments are at times successful. Alternative and less toxic medication is very much in need towards the disease, the use of concepts of herbal medicine with synthetic drug could present better drug leads towards the inhibitory treatment of Cancer. Nature shows plethora of medicinal plants with anticancer and antioxidant activities which may suppress the disease completely. By applying combination therapy instead of monotherapy can lead to improved efficacy and reduced toxicity of the conventional method of treatments of cancer. Anusree S | Dr. Silvia Navis A | Dr. Prashob G R "Herbal and Synthetic Drug Combinations in Cancer Therapy- A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25222.pdfPaper URL: https://www.ijtsrd.com/pharmacy/pharmacology-/25222/herbal-and-synthetic-drug-combinations-in-cancer-therapy--a-review/anusree-s
A novel use of biomarkers in the modeling of cancer activity based on the the...Kamyar Hedayat
Learn about a new approach to evaluating cancer that uses common biomarkers, but evaluates them using system theory. It looks as cancer as a whole-body disease expressed at the level of the cells, rather than a cellular disease expressed throughout the body.
A normal cell can be transformed into a cancerous cell. Discuss the therapeutic strategies that are employed to target the cellular transformation process for cancer prevention and treatment.
New regulations requiring toxicity data on chemicals and an increasing number of efforts to predict the likelihood of failure of molecules earlier in the drug discovery process are combining to increase the utilization of computational models to toxicity. The potential to predict human toxicity directly from a molecular structure is feasible. By using the experimental properties of known compounds as the basis of predictive models it is possible to develop structure activity relationships and resulting algorithms related to toxicity. Several examples have been published recently, including those for drug-induced liver injury (DILI), the pregnane X receptor, P450 3A4 time dependent inhibition, and transporters associated
with toxicities. The versatility and potential of using such models in drug discovery may be illustrated by increasing the efficiency of molecular screening and decreasing the number of animal studies. With more computational power available on increasingly smaller devices, as well as many collaborative initiatives to make data and toxicology models available, this may enable the development of mobile apps for predicting human toxicities, further increasing their utilization.
Citation practices and the construction of scientific fact--ECA-facts-preconf...jodischneider
Citation practices and the construction of scientific fact. Presentation at the European Conference on Argumentation preconference on status, relevance, and authority of facts.
Herbal and Synthetic Drug Combinations in Cancer Therapy A Reviewijtsrd
Cancer is one of the leading and most serious diseases in the current decade, every year millions of people die because of various kinds of cancers. Many aspects relate to the cause of disease besides heredity, food habits, smoking, nutritional behaviors, radiation etc. Cancer is a high mortality disease and the therapeutics for cancer, especially for cancer metastasis is still imperfect. The successful cancer treatment till now has been under study, only chemotherapy and radiation treatments are at times successful. Alternative and less toxic medication is very much in need towards the disease, the use of concepts of herbal medicine with synthetic drug could present better drug leads towards the inhibitory treatment of Cancer. Nature shows plethora of medicinal plants with anticancer and antioxidant activities which may suppress the disease completely. By applying combination therapy instead of monotherapy can lead to improved efficacy and reduced toxicity of the conventional method of treatments of cancer. Anusree S | Dr. Silvia Navis A | Dr. Prashob G R "Herbal and Synthetic Drug Combinations in Cancer Therapy- A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25222.pdfPaper URL: https://www.ijtsrd.com/pharmacy/pharmacology-/25222/herbal-and-synthetic-drug-combinations-in-cancer-therapy--a-review/anusree-s
A novel use of biomarkers in the modeling of cancer activity based on the the...Kamyar Hedayat
Learn about a new approach to evaluating cancer that uses common biomarkers, but evaluates them using system theory. It looks as cancer as a whole-body disease expressed at the level of the cells, rather than a cellular disease expressed throughout the body.
Noted for job excellence to leave training program early per client services manager request.
Analyzed health insurance reimbursement & denial reasons to increase client reimbursement.
Reconciled 3 employee productivity reports, including diagnosing issues and proposing solutions.
Spent several weeks diagnosing system speed issues to effectively determine total labor hours lost.
CHI's Bioassays for Immuno-Oncology Symposium, Oct. 23, 2017 in Washington, DCJames Prudhomme
Biological assays demonstrating drug characteristics such as potency, mechanism-of-action, and stability, are one of the most critical components of an FDA biologic submission. However, with more complex mechanisms-of-action, immunotherapies add a layer of difficulty to bioassay selection and development. At Cambridge Healthtech Institute's Inaugural Bioassays for Immuno-Oncology symposium, experts in bioassays for immuno-oncology therapies will discuss selection, development, and standards for bioassays and immunoassays. Special attention will be given to understanding the mechanism-of-action for immunotherapies, whether they be antibody- or cell-based. Overall, this one-day immersive symposium will outline a product life cycle approach for developing and implementing biological assays from preclinical studies to clinical development. This symposium is part of the Immunogenicity & Bioassay Summit.
1. 1
Curriculum Vitae
Sijin Wu, Ph. D.
Center for Molecular Medicine,
School of Life Science and Biotechnology/School of Pharmacology,
Dalian University of Technology, Dalian, China.
E-mail: sijin_wu@foxmail.com, aj426q@163.com
Tel: +86 13130416631
SUMMARY
With strong background in structural bioinformatics and medicinal chemistry, Sijin WU
has rich experiences in computer aided drug design and takes part in many key projects.
As a well-trained and highly-motivated computational biologist with great enthusiasms
in protein folding and protein-protein interaction, he boldly seeks and cherishes the
opportunity of pursuing his postdoctoral training in the fields of computational biology,
computer aided drug design or other fields concerned.
EDUCATION
• Ph. D. in Biochemical Engineering September 2009– present
Center for Molecular Medicine, Dalian University of Technology, Dalian, China
Mentors: Dr. Yongliang Yang, Prof. Weijie Zhao
• M. S. in Microbiology September 2006– July 2009
Institute of Materia Medica, Nanjing University of Technology, Nanjing, China
Mentor: Prof. Aihua Zhang
• B. S. in Bioengineering September 2002– July 2006
School of Biotechnology and Pharmaceutical Engineering, Nanjing University of
Technology, Nanjing, China
TECHNICAL SKILLS
• Computational Skills
1. Be skilled in protein modeling, protein-protein docking, molecular dynamics simulation
and free energy calculation methods.
2. Be experienced in small molecular library collection, virtual screening and computer
aided structure optimization.
2. 2
3. Be proficient in uses of Gromacs, NAMD, Amber, Rosetta, Modeller, Autodock,
Discovery Studio, Pymol, VMD, ChemOffice and Matlab.
• Programming Skills
Be Familiar with Python and TCL programming.
RESEARCH EXPERIENCE
• Computational Biology
Projects:
1. Uses protein modeling, protein-protein docking and molecular dynamics to study the
difference of protein phosphorylation level between CDK5-P35 and CDK5-P25 for
neurodegenerative disease.
2. Uses Ab initio protein modeling and protein-protein docking to study the mechanism of
Fibrous sheath-interacting protein 1 related to cell differentiation in breast cancer.
3. Investigates the mechanism of core fucosyltransferase FUT8 in regulation the CD4+
T
cell activation and proliferation by protein modeling, molecular dynamics and free
energy calculation.
4. Uses Ab initio protein modeling, molecular dynamics simulation and free energy
calculation to investigate the effects of recurrent ECSIT V140A mutation in NK/T cell
lymphoma.
5. Investigates the mutation influence of ATP-binding protein TmcN in ATP regulation of
Tautomycetin biosynthesis in Streptomyces griseochromogenes by Ab initio protein
modeling, molecular dynamics simulation and free energy calculation.
6. Characterizes the structural features of Cathelicidins from different species to perform
the anti-inflammatory activity by protein modeling, protein-protein docking and
molecular dynamics.
• Computer Aided Drug Design
Projects:
1. Uses molecular dynamics and free energy calculation to investigate the host-guest
interaction and the dissociation pathway of the specific guest with α- and β-Cyclodextrin.
2. Uses protein modeling, virtual screening, dynamics simulation and free energy
calculation to aid the study of mechanism of lipid metabolism disorder lead to non-
alcoholic fatty liver disease and hyperlipidemia.
3. Discovers of hypotoxicity OGT inhibitors by structure-based virtual screening
of natural products, and further study by virtual mutations and molecular
dynamics simulation.
4. Uses virtual screening, molecular dynamics simulation to develop the multi-target
inhibitors to decrease the nuclear transport of CDK5 and inhibit the kinase activity
directly in gastric cancer to suppresses gastric tumorigenesis.
3. 3
5. Uses virtual screening and rational drug design targeting nuclear transport Xpo1 with
natural products library and FDA-approved drugs library, obtained several compounds
such as curcumin and caffeic acid phenethyl ester, and further study by molecular
dynamics simulation and free energy calculation to investigate the inhibit mechanism.
6. Identifies of EGFR inhibitor gefitinib as a putative lead compound for β-secretase from
a kinase inhibitors in-house library by molecular docking and molecular dynamics.
• Database Development
Projects:
1. Design and develop the first online database for proteins with targetable cysteine and
their covalent inhibitors, Cysteinome website: www.cysteinome.org.
2. Design and develop the Cancer Stem Cells Therapeutic Target Database, which is the
first database for therapeutic targets of CSCs. CSCTT website: www.csctt.org.
TEACHING EXPERIENCE
• Graduate Teaching Assistant, School of Life Science and Biotechnology
Biological statistics and bioinformatics, Course Instructor: Dr. Yongliang Yang,
2013-2016.
- Presented lectures in molecular docking, molecular dynamics and protein modeling.
PUBLICATIONS
➢ First author:
1. S. Wu, K. Zhang, H. Qin, M. Niu, W. Zhao, M. Ye, H. Zou, Y. Yang, Caffeic acid
phenethyl ester (CAPE) revisited: covalent modulation of XPO1/CRM1 activities
and implication for its mechanism of action, Chemical Biology & Drug Design,
(2016). (SCI, IF: 2.802)
2. S. Wu, H. Luo, H. Wang, W. Zhao, Q. Hu, Y. Yang, Cysteinome: The first
comprehensive database for proteins with targetable cysteine and their covalent
inhibitors, Biochemical and Biophysical Research Communications, 478 (2016)
1268-1273. (SCI, IF: 2.371)
3. L. Cao, J. Zhou, J. Zhang, S. Wu, X. Yang, X. Zhao, H. Li, M. Luo, Q. Yu, G. Lin,
Cyclin-dependent kinase 5 decreases in gastric cancer and its nuclear accumulation
suppresses gastric tumorigenesis, Clinical Cancer Research, 21 (2015) 1419-1428.
(Co-first author. SCI, IF: 8.738)
4. M. Niu, J. Hu, S. Wu, X. Zhang, H. Xu, Y. Zhang, J. Zhang, Y. Yang, Structural
Bioinformatics‐Based Identification of EGFR Inhibitor Gefitinib as a Putative
Lead Compound for BACE, Chemical Biology & Drug Design, 83 (2014) 81-88.
(Co-first author. SCI, IF: 2.802)
4. 4
➢ Corresponding author
5. X. Hu, Y. Cong, H.H. Luo, S. Wu, L.E. Zhao, Q. Liu, Y. Yang, Cancer Stem Cells
Therapeutic Target Database: The First Comprehensive Database for Therapeutic
Targets of Cancer Stem Cells, Stem Cells Translational Medicine, (2016) sctm.
2015-0289. (The first corresponding author. SCI, IF: 4.247)
➢ Other
6. H. Wen, H. Ma, Q. Cai, S. Lin, Z. Wang, B. He, X. Lei, Y. Gao, S. Wu, W. Liu, W.
Liu, Q. Tao, Z. Long, M. Yan, K. W. Kelley, Y. Yang, H. Huang and Q. Liu.
Recurrent ECSIT V140A mutation triggers hyperinflammation and promotes
hemophagocytic syndrome in NK/T cell lymphoma, Nature Medicine, in second
round revision. (SCI, IF: 30.357)
7. M. Li, Y. Chen, S. Wu, Y. Tang, Y. Deng, J. Yuan, J. Dong, H. Li, L. Tang, TmcN
is involved in ATP regulation of tautomycetin biosynthesis in Streptomyces
griseochromogenes, Biochemical and Biophysical Research Communications, 478
(2016) 221-226. (SCI, IF: 2.371)
8. H. Yu, X. Liu, C. Wang, X. Qiao, S. Wu, H. Wang, L. Feng, Y. Wang, Assessing
the potential of four cathelicidins for the management of mouse candidiasis and
Candida albicans biofilms, Biochimie, 121 (2016) 268-277. (SCI, IF: 2.474)
9. L. Wei, J. Gao, S. Zhang, S. Wu, Z. Xie, G. Ling, Y.-Q. Kuang, Y. Yang, H. Yu, Y.
Wang, Identification and characterization of the first Cathelicidin from sea snakes
with potent antimicrobial and anti-inflammatory activity and special mechanism,
Journal of Biological Chemistry, 290 (2015) 16633-16652. (SCI, IF: 4.258)
10. Z. Hou, X. Luo, W. Zhang, F. Peng, B. Cui, S. Wu, F. Zheng, J. Xu, L. Xu, Z. Long,
Flubendazole, FDA-approved anthelmintic, targets breast cancer stem-like cells,
Oncotarget, 6 (2015) 6326. (SCI, IF 5.008)
11. M. Niu, S. Wu, L. Mao, Y. Yang, CRM1 is a cellular target of curcumin: new
insights for the myriad of biological effects of an ancient spice, Traffic, 14 (2013)
1042-1052. (SCI, IF: 3.721)
12. H. Luo, Y. Liu, S. Wu. Comprehensive comparative study of protein-peptide
docking algorithms performance. Computer Engineering and Applications, 2016.
(CSTPCD)
13. A. Zhang, Y. Shen, S. Wu, X. Zhang. Synthesis derivatives of aromatic
heterocyclic substituted diphenyl thiourea and their use, CN101372475,
2009.02.25. (China patent)
➢ In preparation
14. S. Wu, J. Wang, Y. Yang. Computational study of the selectivity in cyclodextrin-
based supramolecular host-guest nanoparticles for encapsulation of Chinese
5. 5
traditional medicine-derived sulforaphene.
15. Y. Liu, Y. Ren, Y. Cao, H. Huang, Q. Wu, W. Li, S. Wu, J. Zhang. Discovery of a
hypotoxicity O‑GlcNAc transferase (OGT) inhibitor by structure-based virtual
screening of natural products. (Corresponding author)
16. J. Zhang, S. Wu, Y. Yang, K. Herrup. Protein phosphorylation is enhanced by
CDK5-P35 but not CDK5-P25: a SILAC and computational study with
implications for neurodegenerative disease. (Co-first author)
17. H. Luo, S. Wu, Y. Yang, Y. Liu. An enhanced mutual learning artificial bee colony
algorithm applied to protein-peptide docking. (Co-first author)
REFERENCES
• Yongliang Yang, Ph.D.
everbright99@foxmail.com
Associate Professor, Center for Molecular Medicine, School of Life Science and
Biotechnology, Dalian University of Technology, Dalian, China.
• Guohui Li, Ph.D.
ghli@dicp.ac.cn
Principal Investigator, Laboratory of Molecular Simulation and Design, State Key
Laboratory of Molecular Reaction Dynamics, Institute of Chemical Physics, Dalian,
Chinese Academy of Sciences, China.
