140 related articles for article (PubMed ID: 38280715)
1. Inactive-enriched machine-learning models exploiting patent data improve structure-based virtual screening for PDL1 dimerizers.
Gómez-Sacristán P; Simeon S; Tran-Nguyen VK; Patil S; Ballester PJ
J Adv Res; 2024 Jan; ():. PubMed ID: 38280715
[TBL] [Abstract][Full Text] [Related]
2. Structure-based virtual screening for PDL1 dimerizers: Evaluating generic scoring functions.
Tran-Nguyen VK; Simeon S; Junaid M; Ballester PJ
Curr Res Struct Biol; 2022; 4():206-210. PubMed ID: 35769111
[TBL] [Abstract][Full Text] [Related]
3. Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening?
Shen C; Weng G; Zhang X; Leung EL; Yao X; Pang J; Chai X; Li D; Wang E; Cao D; Hou T
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33418562
[TBL] [Abstract][Full Text] [Related]
4. Beware of the generic machine learning-based scoring functions in structure-based virtual screening.
Shen C; Hu Y; Wang Z; Zhang X; Pang J; Wang G; Zhong H; Xu L; Cao D; Hou T
Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32484221
[TBL] [Abstract][Full Text] [Related]
5. Machine-Learning Guided Discovery of Bioactive Inhibitors of PD1-PDL1 Interaction.
Patil SP; Fattakhova E; Hofer J; Oravic M; Bender A; Brearey J; Parker D; Radnoff M; Smith Z
Pharmaceuticals (Basel); 2022 May; 15(5):. PubMed ID: 35631439
[TBL] [Abstract][Full Text] [Related]
6. A practical guide to machine-learning scoring for structure-based virtual screening.
Tran-Nguyen VK; Junaid M; Simeon S; Ballester PJ
Nat Protoc; 2023 Nov; 18(11):3460-3511. PubMed ID: 37845361
[TBL] [Abstract][Full Text] [Related]
7. ML-PLIC: a web platform for characterizing protein-ligand interactions and developing machine learning-based scoring functions.
Zhang X; Shen C; Wang T; Deng Y; Kang Y; Li D; Hou T; Pan P
Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37738401
[TBL] [Abstract][Full Text] [Related]
8. Recent progress on the prospective application of machine learning to structure-based virtual screening.
Ghislat G; Rahman T; Ballester PJ
Curr Opin Chem Biol; 2021 Dec; 65():28-34. PubMed ID: 34052776
[TBL] [Abstract][Full Text] [Related]
9. Integration of cancer stemness and neoantigen load to predict responsiveness to anti-PD1/PDL1 therapy.
Luo K; Liu S; Shen X; Xu J; Shi C; Chao Y; Wen Z; Zhang K; Wang R; Liu B; Jiang Y
Front Cell Dev Biol; 2022; 10():1003656. PubMed ID: 36467413
[No Abstract] [Full Text] [Related]
10. Reducing false positive rate of docking-based virtual screening by active learning.
Wang L; Shi SH; Li H; Zeng XX; Liu SY; Liu ZQ; Deng YF; Lu AP; Hou TJ; Cao DS
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36642412
[TBL] [Abstract][Full Text] [Related]
11. Macrocyclic Compounds from Ansamycin Antibiotic Class as Inhibitors of PD1-PDL1 Protein-Protein Interaction.
Patil SP; Yoon SC; Aradhya AG; Hofer J; Fink MA; Enley ES; Fisher JE; Herb MC; Klingos A; Proulx JT; Fedorky MT
Chem Pharm Bull (Tokyo); 2018; 66(8):773-778. PubMed ID: 30068796
[TBL] [Abstract][Full Text] [Related]
12. TB-IECS: an accurate machine learning-based scoring function for virtual screening.
Zhang X; Shen C; Jiang D; Zhang J; Ye Q; Xu L; Hou T; Pan P; Kang Y
J Cheminform; 2023 Jul; 15(1):63. PubMed ID: 37403155
[TBL] [Abstract][Full Text] [Related]
13. Topology-Based and Conformation-Based Decoys Database: An Unbiased Online Database for Training and Benchmarking Machine-Learning Scoring Functions.
Zhang X; Shen C; Wang T; Kang Y; Li D; Pan P; Wang J; Wang G; Deng Y; Xu L; Cao D; Hou T; Wang Z
J Med Chem; 2023 Jul; 66(13):9174-9183. PubMed ID: 37317043
[TBL] [Abstract][Full Text] [Related]
14. Assessment of the Generalization Abilities of Machine-Learning Scoring Functions for Structure-Based Virtual Screening.
Zhu H; Yang J; Huang N
J Chem Inf Model; 2022 Nov; 62(22):5485-5502. PubMed ID: 36268980
[TBL] [Abstract][Full Text] [Related]
15. A Hybrid Docking and Machine Learning Approach to Enhance the Performance of Virtual Screening Carried out on Protein-Protein Interfaces.
Singh N; Villoutreix BO
Int J Mol Sci; 2022 Nov; 23(22):. PubMed ID: 36430841
[TBL] [Abstract][Full Text] [Related]
16. The impact of compound library size on the performance of scoring functions for structure-based virtual screening.
Fresnais L; Ballester PJ
Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32568385
[TBL] [Abstract][Full Text] [Related]
17. TocoDecoy: A New Approach to Design Unbiased Datasets for Training and Benchmarking Machine-Learning Scoring Functions.
Zhang X; Shen C; Liao B; Jiang D; Wang J; Wu Z; Du H; Wang T; Huo W; Xu L; Cao D; Hsieh CY; Hou T
J Med Chem; 2022 Jun; 65(11):7918-7932. PubMed ID: 35642777
[TBL] [Abstract][Full Text] [Related]
18. Research Trends and Most Influential Clinical Studies on Anti-PD1/PDL1 Immunotherapy for Cancers: A Bibliometric Analysis.
Liu Y; Xu Y; Cheng X; Lin Y; Jiang S; Yu H; Zhang Z; Lu L; Zhang X
Front Immunol; 2022; 13():862084. PubMed ID: 35493449
[TBL] [Abstract][Full Text] [Related]
19. Selecting machine-learning scoring functions for structure-based virtual screening.
Ballester PJ
Drug Discov Today Technol; 2019 Dec; 32-33():81-87. PubMed ID: 33386098
[TBL] [Abstract][Full Text] [Related]
20. SCORCH: Improving structure-based virtual screening with machine learning classifiers, data augmentation, and uncertainty estimation.
McGibbon M; Money-Kyrle S; Blay V; Houston DR
J Adv Res; 2023 Apr; 46():135-147. PubMed ID: 35901959
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
