scholarly journals Checkpoint therapeutic target database (CKTTD): the first comprehensive database for checkpoint targets and their modulators in cancer immunotherapy

2020 ◽  
Vol 8 (2) ◽  
pp. e001247
Author(s):  
Yixiao Zhang ◽  
Yuan Yao ◽  
Peng Chen ◽  
Yu Liu ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Cancer Immunotherapy ◽  
Therapeutic Target ◽  
Immune Escape ◽  
Depth Information ◽  
Biological Databases ◽  
Mining System ◽  
Protein Targets ◽  
Comprehensive Database ◽  
Target Database

BackgroundCheckpoint targets play a key role in tumor-mediated immune escape and therefore are critical for cancer immunotherapy. Unfortunately, there is a lack of bioinformatics resource that compile all the checkpoint targets for translational research and drug discovery in immuno-oncology.MethodsTo this end, we developed checkpoint therapeutic target database (CKTTD), the first comprehensive database for immune checkpoint targets (proteins, miRNAs and LncRNAs) and their modulators. A scoring system was adopted to filter more relevant targets with high confidence. In addition, a few biological databases such as Oncomine, Drugbank, miRBase and Lnc2Cancer database were integrated into CKTTD to provide an in-depth information. Moreover, we computed and provided ligand-binding site information for all the targets which may support bench scientists for drug discovery efforts.ResultsIn total, CKTTD compiles 105 checkpoint protein targets, 53 modulators (small-molecules and antibody), 30 miRNAs and 18 LncRNAs in cancer immunotherapy with validated experimental evidences curated from 10 649 literatures via an enhanced text-mining system.ConclusionsIn conclusion, the CKTTD may serve as a useful platform for the research of cancer immunotherapy and drug discovery. The CKTTD database is freely available to public at http://www.ckttdb.org/.

scholarly journals Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery

2011 ◽  
Vol 40 (D1) ◽  
pp. D1128-D1136 ◽  
Author(s):  
F. Zhu ◽  
Z. Shi ◽  
C. Qin ◽  
L. Tao ◽  
X. Liu ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Therapeutic Target ◽  
Target Database

scholarly journals Cancer Stem Cells Therapeutic Target Database: The First Comprehensive Database for Therapeutic Targets of Cancer Stem Cells

2016 ◽  
Vol 6 (2) ◽  
pp. 331-334 ◽  
Author(s):  
Xiaoqing Hu ◽  
Ye Cong ◽  
Huizhe Howard Luo ◽  
Sijin Wu ◽  
Liyuan Eric Zhao ◽  
...  
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Therapeutic Target ◽  
Therapeutic Targets ◽  
Comprehensive Database ◽  
Target Database

scholarly journals Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics

2019 ◽  
Author(s):  
Yunxia Wang ◽  
Song Zhang ◽  
Fengcheng Li ◽  
Ying Zhou ◽  
Ying Zhang ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Therapeutic Target ◽  
International Classification Of Diseases ◽  
Interacting Proteins ◽  
Targeted Therapeutics ◽  
Drug Candidates ◽  
Classification Of Diseases ◽  
Target Database ◽  
Early Drug

Abstract Knowledge of therapeutic targets and early drug candidates is useful for improved drug discovery. In particular, information about target regulators and the patented therapeutic agents facilitates research regarding druggability, systems pharmacology, new trends, molecular landscapes, and the development of drug discovery tools. To complement other databases, we constructed the Therapeutic Target Database (TTD) with expanded information about (i) target-regulating microRNAs and transcription factors, (ii) target-interacting proteins, and (iii) patented agents and their targets (structures and experimental activity values if available), which can be conveniently retrieved and is further enriched with regulatory mechanisms or biochemical classes. We also updated the TTD with the recently released International Classification of Diseases ICD-11 codes and additional sets of successful, clinical trial, and literature-reported targets that emerged since the last update. TTD is accessible at http://bidd.nus.edu.sg/group/ttd/ttd.asp. In case of possible web connectivity issues, two mirror sites of TTD are also constructed (http://db.idrblab.org/ttd/ and http://db.idrblab.net/ttd/).

Advances in mRNA-based drug discovery in cancer immunotherapy

2021 ◽  
Author(s):  
Claudia Augusta Di Trani ◽  
Myriam Fernandez-Sendin ◽  
Assunta Cirella ◽  
Aina Segués ◽  
Irene Olivera ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Cancer Immunotherapy

scholarly journals Artificial intelligence and big data facilitated targeted drug discovery

2019 ◽  
Vol 4 (4) ◽  
pp. 206-213 ◽  
Author(s):  
Benquan Liu ◽  
Huiqin He ◽  
Hongyi Luo ◽  
Tingting Zhang ◽  
Jingwei Jiang
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Drug Discovery ◽  
Three Dimensional ◽  
Data Bank ◽  
The Cancer Genome Atlas ◽  
Biological Databases ◽  
Cancer Genome Atlas ◽  
Targeted Drug ◽  
Targeted Drug Discovery

Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database including detailed information of approved, investigational and withdrawn drugs, as well as other nutraceutical and metabolite structures. PubChem is a chemical compound database including all commercially available compounds as well as other synthesisable compounds. Protein Data Bank is a crystal structure database including X-ray, cryo-EM and nuclear magnetic resonance protein three-dimensional structures as well as their ligands. On the other hand, artificial intelligence (AI) is playing an important role in the drug discovery progress. The integration of such big data and AI is making a great difference in the discovery of novel targeted drug. In this review, we focus on the currently available advanced methods for the discovery of highly effective lead compounds with great absorption, distribution, metabolism, excretion and toxicity properties.

Targeting the Tumor-Draining Lymph Node With Adjuvant Nanoparticles for Cancer Immunotherapy

2013 ◽  
Author(s):  
Susan N. Thomas
Keyword(s):  
Drug Delivery ◽  
Lymph Node ◽  
Cancer Immunotherapy ◽  
Cancer Progression ◽  
Targeted Delivery ◽  
Immune Escape ◽  
Material Design ◽  
Draining Lymph Node ◽  
Clinical Interest ◽  
Tumor Draining Lymph Node

Immunotherapy-based approaches for cancer treatment are of increasing clinical interest. Principles of drug delivery and the emerging field of material design for immunomodulation might hold significant promise for novel approaches in cancer immunotherapy since biomaterials engineering strategies enable enhanced delivery of immune modulatory agents to tissues and cells of the immune system1. One tissue of significant clinical interest in a cancer setting is the tumor-draining lymph node (TDLN), which participates in cancer progression by enabling both metastatic dissemination as well as tumor-induced immune escape. Hence, the TDLN represents a novel target for drug delivery schemes for cancer immunotherapy. We hypothesize that targeted delivery of adjuvants (Adjs) to the TDLN using a biomaterials-based approach might promote antitumor immunity and hinder tumor growth.

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