190 related articles for article (PubMed ID: 37515872)
1. Geometric graph learning with extended atom-types features for protein-ligand binding affinity prediction.
Rana MM; Nguyen DD
Comput Biol Med; 2023 Sep; 164():107250. PubMed ID: 37515872
[TBL] [Abstract][Full Text] [Related]
2. GGL-Tox: Geometric Graph Learning for Toxicity Prediction.
Jiang J; Wang R; Wei GW
J Chem Inf Model; 2021 Apr; 61(4):1691-1700. PubMed ID: 33719422
[TBL] [Abstract][Full Text] [Related]
3. AGL-Score: Algebraic Graph Learning Score for Protein-Ligand Binding Scoring, Ranking, Docking, and Screening.
Nguyen DD; Wei GW
J Chem Inf Model; 2019 Jul; 59(7):3291-3304. PubMed ID: 31257871
[TBL] [Abstract][Full Text] [Related]
4. Geometric Graph Learning to Predict Changes in Binding Free Energy and Protein Thermodynamic Stability upon Mutation.
Rana MM; Nguyen DD
J Phys Chem Lett; 2023 Dec; 14(49):10870-10879. PubMed ID: 38032742
[TBL] [Abstract][Full Text] [Related]
5. GB-score: Minimally designed machine learning scoring function based on distance-weighted interatomic contact features.
Rayka M; Firouzi R
Mol Inform; 2023 Mar; 42(3):e2200135. PubMed ID: 36722733
[TBL] [Abstract][Full Text] [Related]
6. Multi-shelled ECIF: improved extended connectivity interaction features for accurate binding affinity prediction.
Shiota K; Akutsu T
Bioinform Adv; 2023; 3(1):vbad155. PubMed ID: 37928345
[TBL] [Abstract][Full Text] [Related]
7. A new paradigm for applying deep learning to protein-ligand interaction prediction.
Wang Z; Wang S; Li Y; Guo J; Wei Y; Mu Y; Zheng L; Li W
Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38581420
[TBL] [Abstract][Full Text] [Related]
8. PLANET: A Multi-objective Graph Neural Network Model for Protein-Ligand Binding Affinity Prediction.
Zhang X; Gao H; Wang H; Chen Z; Zhang Z; Chen X; Li Y; Qi Y; Wang R
J Chem Inf Model; 2024 Apr; 64(7):2205-2220. PubMed ID: 37319418
[TBL] [Abstract][Full Text] [Related]
9. Extended connectivity interaction features: improving binding affinity prediction through chemical description.
Sánchez-Cruz N; Medina-Franco JL; Mestres J; Barril X
Bioinformatics; 2021 Jun; 37(10):1376-1382. PubMed ID: 33226061
[TBL] [Abstract][Full Text] [Related]
10. Ligand binding affinity prediction with fusion of graph neural networks and 3D structure-based complex graph.
Dong L; Shi S; Qu X; Luo D; Wang B
Phys Chem Chem Phys; 2023 Sep; 25(35):24110-24120. PubMed ID: 37655493
[TBL] [Abstract][Full Text] [Related]
11. Protein-ligand binding affinity prediction exploiting sequence constituent homology.
Abdel-Rehim A; Orhobor O; Hang L; Ni H; King RD
Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37572302
[TBL] [Abstract][Full Text] [Related]
12. Machine-learning scoring functions trained on complexes dissimilar to the test set already outperform classical counterparts on a blind benchmark.
Li H; Lu G; Sze KH; Su X; Chan WY; Leung KS
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34169324
[TBL] [Abstract][Full Text] [Related]
13. Iterative Knowledge-Based Scoring Function for Protein-Ligand Interactions by Considering Binding Affinity Information.
Zhao X; Li H; Zhang K; Huang SY
J Phys Chem B; 2023 Oct; 127(42):9021-9034. PubMed ID: 37822259
[TBL] [Abstract][Full Text] [Related]
14. Water Network-Augmented Two-State Model for Protein-Ligand Binding Affinity Prediction.
Qu X; Dong L; Luo D; Si Y; Wang B
J Chem Inf Model; 2024 Apr; 64(7):2263-2274. PubMed ID: 37433009
[TBL] [Abstract][Full Text] [Related]
15. Comparative assessment of scoring functions on an updated benchmark: 2. Evaluation methods and general results.
Li Y; Han L; Liu Z; Wang R
J Chem Inf Model; 2014 Jun; 54(6):1717-36. PubMed ID: 24708446
[TBL] [Abstract][Full Text] [Related]
16. Leveraging scaffold information to predict protein-ligand binding affinity with an empirical graph neural network.
Xia C; Feng SH; Xia Y; Pan X; Shen HB
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36627113
[TBL] [Abstract][Full Text] [Related]
17. A simple spatial extension to the extended connectivity interaction features for binding affinity prediction.
Orhobor OI; Rehim AA; Lou H; Ni H; King RD
R Soc Open Sci; 2022 May; 9(5):211745. PubMed ID: 35573039
[TBL] [Abstract][Full Text] [Related]
18. OnionNet-2: A Convolutional Neural Network Model for Predicting Protein-Ligand Binding Affinity Based on Residue-Atom Contacting Shells.
Wang Z; Zheng L; Liu Y; Qu Y; Li YQ; Zhao M; Mu Y; Li W
Front Chem; 2021; 9():753002. PubMed ID: 34778208
[TBL] [Abstract][Full Text] [Related]
19. Boosting Protein-Ligand Binding Pose Prediction and Virtual Screening Based on Residue-Atom Distance Likelihood Potential and Graph Transformer.
Shen C; Zhang X; Deng Y; Gao J; Wang D; Xu L; Pan P; Hou T; Kang Y
J Med Chem; 2022 Aug; 65(15):10691-10706. PubMed ID: 35917397
[TBL] [Abstract][Full Text] [Related]
20. An ensemble-based approach to estimate confidence of predicted protein-ligand binding affinity values.
Rayka M; Mirzaei M; Mohammad Latifi A
Mol Inform; 2024 Apr; 43(4):e202300292. PubMed ID: 38358080
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
