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Towards Unified AI Drug Discovery with Multiple Knowledge Modalities [article]

Yizhen Luo, Xing Yi Liu, Kai Yang, Kui Huang, Massimo Hong, Jiahuan Zhang, Yushuai Wu, Zaiqing Nie
2023 arXiv   pre-print

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2023 pre-print arXiv:2305.01523v1 fatcat:pzuupq27prasvepdkgvsefffia
The framework first extracts underlying characteristics from heterogeneous inputs, and then applies multimodal fusion for accurate prediction.  ...  Benefiting from integrated knowledge, our framework achieves a deeper understanding of molecule entities, brings significant improvements over state-of-the-art methods on a wide range of tasks and benchmarks  ...  We also visualize the structural feature, explicit knowledge feature and implicit knowledge feature for each drug via t-sne (Van der Maaten and Hinton, 2008) in Figure 4 (c)∼(e).  ... 
arXiv:2305.01523v2 fatcat:db3hjjcj75c77e4373kbgcxirm
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Yizhen Luo, Xing Yi Liu, Kai Yang, Kui Huang, Massimo Hong, Jiahuan Zhang, Yushuai Wu, Zaiqing Nie. "Towards Unified AI Drug Discovery with Multiple Knowledge Modalities." arXiv (2023)

New Insights Into Drug Repurposing for COVID-19 Using Deep Learning

Chun Yen Lee, Yi-Ping Phoebe Chen
2021 IEEE Transactions on Neural Networks and Learning Systems  

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By optimizing hyperparameter settings, deploying suitable activation functions, and designing optimization algorithms, the improved DL approach will be able to perform feature extraction from quality big  ...  When adopted for drug repurposing for COVID-19, this improved approach will create a new generation of DL approaches that can establish a cause and effect relationship as to why the repurposed drugs are  ...  Utilization of Big Network-Based Data So far, most DR studies focus on using a drug compound and protein sequence data to predict drug-target binding affinity scores or binding energy.  ... 
doi:10.1109/tnnls.2021.3111745 pmid:34546931 pmcid:PMC8843052 fatcat:3zt7eoks5zejnjfrtvuplnl6ua
Citation

Chun Yen Lee, Yi-Ping Phoebe Chen. "New Insights Into Drug Repurposing for COVID-19 Using Deep Learning." IEEE Transactions on Neural Networks and Learning Systems PP.11 (2021) 1-11

VNARs: An Ancient and Unique Repertoire of Molecules That Deliver Small, Soluble, Stable and High Affinity Binders of Proteins

Caroline Barelle, Andy Porter
2015 Antibodies  

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In fact their small size, remarkable stability, molecular flexibility and solubility, together with their high affinity and selectivity for target, all reinforce the potential of these domains as drug  ...  The purpose of this review is to provide an overview of the existing basic biology of these unique domains, to highlight the drug-like properties of VNARs and describe current progress in their journey  ...  Acknowledgments This work was supported by Scottish Enterprise (SE) and the Biotechnology and Biological Sciences Research Council (BBSRC).  ... 
doi:10.3390/antib4030240 fatcat:3bulo4llb5hg5munbj7srrdtvq
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Caroline Barelle, Andy Porter. "VNARs: An Ancient and Unique Repertoire of Molecules That Deliver Small, Soluble, Stable and High Affinity Binders of Proteins." Antibodies 4.3 (2015) 240-258

Multimodal learning with graphs [article]

Yasha Ektefaie, George Dasoulas, Ayush Noori, Maha Farhat, Marinka Zitnik
2023 arXiv   pre-print

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2022 pre-print
arXiv:2209.03299v1 fatcat:zqsfe25a65dlbfzpkxhuro4qju
2022 pre-print
arXiv:2209.03299v2 fatcat:btetxv4xlzcjvkqpl3n6olc7em
2022 pre-print
arXiv:2209.03299v3 fatcat:q2imd2gc55aevbk6h24zhsesmi
2022 pre-print
arXiv:2209.03299v4 fatcat:lhqk3zzcxfdkrbqvblql2gursy
2023 pre-print
arXiv:2209.03299v5 fatcat:p6dpvr6lnnaxnc3fvhb52jq52u
Diverse datasets are combined using graphs and fed into sophisticated multimodal architectures, specified as image-intensive, knowledge-grounded and language-intensive models.  ...  However, the increasingly heterogeneous graph datasets call for multimodal methods that can combine different inductive biases: the set of assumptions that algorithms use to make predictions for inputs  ...  ., and M.Z. gratefully acknowledge the support of US Air Force Contract No.  ... 
arXiv:2209.03299v6 fatcat:qncvfy5yunaupeimwfsav7lsau
Open Access Multiple Versions
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Yasha Ektefaie, George Dasoulas, Ayush Noori, Maha Farhat, Marinka Zitnik. "Multimodal learning with graphs." arXiv (2023)

Exploration of databases and methods supporting drug repurposing: a comprehensive survey

2020 Briefings in Bioinformatics  

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targets involved, and patient and cellular responses.  ...  We summarize the target coverage and types of data available in each database and provide several examples of how multi-database exploration can facilitate drug repurposing.  ...  affinity data, computational tools are being built to predict/infer new molecular targets using orthogonal drug-target space deconvolution, where the molecular structures of both the drugs and targets  ... 
doi:10.1093/bib/bbaa003 pmid:32055842 pmcid:PMC7986597 fatcat:gnj3dcblq5brhnnshvnueyliha
Citation

"Exploration of databases and methods supporting drug repurposing: a comprehensive survey." Briefings in Bioinformatics 22.2 (2020) 1656-1678

Applications of Artificial Intelligence in Battling Against Covid-19: A Literature Review

Mohammad-H. Tayarani-N.
2020 Chaos, Solitons & Fractals  

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Here, we perform an overview on the applications of AI in a variety of fields including diagnosis of the disease via different types of tests and symptoms, monitoring patients, identifying severity of  ...  The rapid growth of the pandemic has wreaked havoc and prompted the need for immediate reactions to curb the effects.  ...  In this scheme, a protein molecule binding affinity predictor is used to generate novel and optimal drug-like molecules for unseen viral targets.  ... 
doi:10.1016/j.chaos.2020.110338 pmid:33041533 pmcid:PMC7532790 fatcat:gl3i37hag5gflajsa7fh6khvva
Citation

Mohammad-H. Tayarani-N.. "Applications of Artificial Intelligence in Battling Against Covid-19: A Literature Review." Chaos, Solitons & Fractals (2020) 110338

Deep learning and multi-omics approach to predict drug responses in cancer

Conghao Wang, Xintong Lye, Rama Kaalia, Parvin Kumar, Jagath C. Rajapakse
2022 BMC Bioinformatics  

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build computational models to predict anticancer drug responses from molecular features.  ...  The network outperformed feedforward neural networks and reported 0.90 for $$R^2$$ R 2 values for prediction of drug responses from cancer cell lines data available in CCLE and GDSC.  ...  The authors would like to thank all research participants and organisations who provided data for this machine learning study.  ... 
doi:10.1186/s12859-022-04964-9 pmid:36443676 pmcid:PMC9703655 fatcat:rhvf6gennrcjpexwmcmti3ywja
DOAJ
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Conghao Wang, Xintong Lye, Rama Kaalia, Parvin Kumar, Jagath C. Rajapakse. "Deep learning and multi-omics approach to predict drug responses in cancer." BMC Bioinformatics 22.S10 (2022) 632

Targeted polymeric therapeutic nanoparticles: design, development and clinical translation

Nazila Kamaly, Zeyu Xiao, Pedro M. Valencia, Aleksandar F. Radovic-Moreno, Omid C. Farokhzad
2012 Chemical Society Reviews  

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Indeed this optimization of drug pharmacology as aided by careful design of multifunctional NPs can lead to improved drug safety and efficacy, and may be complimentary to drug enhancements that are traditionally  ...  wafers used as controlled drug release depots, to multifunctional nanoparticles (NPs) capable of targeting, and controlled release of therapeutic and diagnostic agents.  ...  Dr Farokhzad declares financial interests in BIND Biosciences and Selecta Biosciences. We thank Liang Guo for photography. Biographies  ... 
doi:10.1039/c2cs15344k pmid:22388185 pmcid:PMC3684255 fatcat:o5pkptet7vdfrlbxmw5d4ewy4m
Citation

Nazila Kamaly, Zeyu Xiao, Pedro M. Valencia, Aleksandar F. Radovic-Moreno, Omid C. Farokhzad. "Targeted polymeric therapeutic nanoparticles: design, development and clinical translation." Chemical Society Reviews 41.7 (2012) 2971

Computational analyses of mechanism of action (MoA): data, methods and integration

Maria-Anna Trapotsi, Layla Hosseini-Gerami, Andreas Bender
2022 RSC Chemical Biology  

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This review summarises different data, data resources and methods for computational mechanism of action (MoA) analysis, and highlights some case studies where integration of data types and methods enabled  ...  Notes and references  ...  Such prior knowledge or supplementary data is usually derived from experiments, but some databases feature inferred or predicted protein-protein interactions to improve coverage.  ... 
doi:10.1039/d1cb00069a pmid:35360890 pmcid:PMC8827085 fatcat:yqd77fs7nfdwdlbh437h23s2qm
DOAJ
Citation

Maria-Anna Trapotsi, Layla Hosseini-Gerami, Andreas Bender. "Computational analyses of mechanism of action (MoA): data, methods and integration." RSC Chemical Biology 3.2 (2022) 170-200

Identification of Protein Partners in Mycobacteria Using a Single-Step Affinity Purification Method

Przemysław Płociński, Daniel Laubitz, Dominik Cysewski, Krystian Stoduś, Katarzyna Kowalska, Andrzej Dziembowski, Anil Kumar Tyagi
2014 PLoS ONE  

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Efforts are being made to both prevent its spread and improve curability rates.  ...  We have implemented improved screening methods for protein-protein interactions based on affinity purification followed by high-resolution mass spectrometry.  ...  Acknowledgments The authors thank Aleksander Chlebowski for help with microscope imaging, Agata Malinowska, Jacek Olędzki and Agnieszka Fabijańska for LC-MS/MS technical help and discussion.  ... 
doi:10.1371/journal.pone.0091380 pmid:24664103 pmcid:PMC3963859 fatcat:ee2lf2qhdvey3bosrv5qneavfq
DOAJ
Citation

Przemysław Płociński, Daniel Laubitz, Dominik Cysewski, Krystian Stoduś, Katarzyna Kowalska, Andrzej Dziembowski, Anil Kumar Tyagi. "Identification of Protein Partners in Mycobacteria Using a Single-Step Affinity Purification Method." PLoS ONE 9.3 (2014) e91380

Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities [article]

Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, Valentina Tamma
2023 arXiv   pre-print

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2023 accepted arXiv:2309.17255v4 fatcat:jgl7qwiz3zfdlncwkdrqay7xpm

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2023 pre-print
arXiv:2309.17255v1 fatcat:ld4znhiainci5jeczj4qrx5zki
2023 pre-print
arXiv:2309.17255v2 fatcat:gvwizw2qdzeudfilqvbfkoy2ei
We focus on three broad topics: the construction and management of Knowledge Graphs (KGs), the use of KGs and associated technologies in the discovery of new knowledge, and the use of KGs in artificial  ...  The volume of data and the complexity of scientific concepts and relations referred to therein promote the application of advanced knowledge-driven technologies for managing and interpreting data, with  ...  Acknowledgements We would like to thank Uli Sattler (University of Manchester) for proposing the topic of this paper and Terry Payne (University of Liverpool) for the useful comments on a previous draft  ... 
arXiv:2309.17255v3 fatcat:cfys4jsghjhsjg7ucsoywxu3na
Open Access Multiple Versions
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Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, Valentina Tamma. "Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities." arXiv (2023)

Fast and accurate modeling and design of antibody-antigen complex using tFold [article]

Fandi Wu, Yu Zhao, Jiaxiang Wu, Biaobin Jiang, Bing He, Longkai Huang, Chenchen Qin, Fan Yang, Ningqiao Huang, Yang Xiao, Rubo Wang, Huaxian Jia (+7 others)
2024 bioRxiv   pre-print

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However, despite these advancements, fast and accurate prediction of antibody-antigen complex structures remains a challenging and unresolved issue.  ...  Currently, structure prediction for protein monomers has achieved considerable success, and promising progress has been made in extending this achievement to the prediction of protein complexes.  ...  We thank for Junhong Huang, Jie Ren, Zihan Wu, Xiaoyang Jing and Xiangzhe Kong for helpful discussion; Qiang Li for web server design; Zhenxing Zhang and IPRC for computational resources.  ... 
doi:10.1101/2024.02.05.578892 fatcat:i4o2penbebfqxhulmxp46qj62m
Citation

Fandi Wu, Yu Zhao, Jiaxiang Wu, Biaobin Jiang, Bing He, Longkai Huang, Chenchen Qin, Fan Yang, Ningqiao Huang, Yang Xiao, Rubo Wang, Huaxian Jia, Yu Rong, Yuyi Liu, Houtim Lai, Tingyang Xu, Wei Liu, Peilin Zhao, Jianhua Yao. "Fast and accurate modeling and design of antibody-antigen complex using tFold." bioRxiv (2024)

Large-Scale Production and Structural and Biophysical Characterizations of the Human Hepatitis B Virus Polymerase

J. Voros, A. Urbanek, G. J. P. Rautureau, M. O'Connor, H. C. Fisher, A. E. Ashcroft, N. Ferguson
2013 Journal of Virology  

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Thus, no empirical structural data exist for hPOL, and this impedes medicinal chemistry and rational lead discovery efforts targeting HBV.  ...  While hPOL remains an attractive therapeutic target, it is notoriously difficult to express and purify in a soluble form at yields appropriate for structural studies.  ...  Addition of an MBP fusion partner marginally improved the expression levels of RT-RH 285-832 , RT-RH 303-778 , and RT-RH 303-783 (Fig. 3B , lanes 1 to 6) compared to constructs lacking fusion partners  ... 
doi:10.1128/jvi.02575-13 pmid:24352439 pmcid:PMC3958071 fatcat:drfpegckbjgdjgqbh3yknewyvq
Citation

J. Voros, A. Urbanek, G. J. P. Rautureau, M. O'Connor, H. C. Fisher, A. E. Ashcroft, N. Ferguson. "Large-Scale Production and Structural and Biophysical Characterizations of the Human Hepatitis B Virus Polymerase." Journal of Virology 88.5 (2013) 2584-2599

Surface display of glycosylated Tyrosinase related protein-2 (TRP-2) tumour antigen on Lactococcus lactis

Jeevanathan Kalyanasundram, Suet Lin Chia, Adelene Ai-Lian Song, Abdul Rahim Raha, Howard A. Young, Khatijah Yusoff
2015 BMC Biotechnology  

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The Generally Regarded as Safe (GRAS) status of the Lactococcus lactis coupled with a non-recombinant strategy of in-trans surface display, provide a safe platform for therapeutic drug and vaccine development  ...  Results: A total amount of 33 μg of partially purified TRP-2-cA from ~6.0 g in wet weight of CHO-S cells was purified by His-tag affinity chromatography.  ...  Acknowledgements The research was funded by Malaysian Ministry of Science, Technology and Innovation (Grant Number: 02-01-04-SF1273). We would like to thank Dr.  ... 
doi:10.1186/s12896-015-0231-z pmid:26715153 pmcid:PMC4696278 fatcat:sgzha2lgf5aapf2iy3tqhc2hey
DOAJ
Citation

Jeevanathan Kalyanasundram, Suet Lin Chia, Adelene Ai-Lian Song, Abdul Rahim Raha, Howard A. Young, Khatijah Yusoff. "Surface display of glycosylated Tyrosinase related protein-2 (TRP-2) tumour antigen on Lactococcus lactis." BMC Biotechnology 15.1 (2015)

Retrieval-Augmented Generation for AI-Generated Content: A Survey [article]

Penghao Zhao, Hailin Zhang, Qinhan Yu, Zhengren Wang, Yunteng Geng, Fangcheng Fu, Ling Yang, Wentao Zhang, Jie Jiang, Bin Cui
2024 arXiv   pre-print

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2024 pre-print arXiv:2402.19473v3 fatcat:pxmzedbqtffgrhugtqtqth3jgu

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2024 pre-print
arXiv:2402.19473v1 fatcat:vkaenqbhhva5bhcwu6mgfsaiha
2024 pre-print
arXiv:2402.19473v2 fatcat:rk3on6i6tnefvhawmb2kmbbuui
2024 pre-print
arXiv:2402.19473v4 fatcat:vacgwmt66vf2nnslykxmmmkzhq
Despite its notable successes, AIGC still faces hurdles such as updating knowledge, handling long-tail data, mitigating data leakage, and managing high training and inference costs.  ...  We first classify RAG foundations according to how the retriever augments the generator, distilling the fundamental abstractions of the augmentation methodologies for various retrievers and generators.  ...  The retriever is further trained based on knowledge distillation.  ... 
arXiv:2402.19473v5 fatcat:r6h7z2xkmnh4hitzuwuc2uqa2y
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Penghao Zhao, Hailin Zhang, Qinhan Yu, Zhengren Wang, Yunteng Geng, Fangcheng Fu, Ling Yang, Wentao Zhang, Jie Jiang, Bin Cui. "Retrieval-Augmented Generation for AI-Generated Content: A Survey." arXiv (2024)

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