366 related articles for article (PubMed ID: 32786511)
41. Can an Old Ally Defeat a New Enemy?
Gurbel PA; Bliden KP; Schrör K
Circulation; 2020 Jul; 142(4):315-317. PubMed ID: 32478567
[No Abstract] [Full Text] [Related]
42. In silico identification of potential inhibitors of key SARS-CoV-2 3CL hydrolase (Mpro) via molecular docking, MMGBSA predictive binding energy calculations, and molecular dynamics simulation.
Choudhary MI; Shaikh M; Tul-Wahab A; Ur-Rahman A
PLoS One; 2020; 15(7):e0235030. PubMed ID: 32706783
[TBL] [Abstract][Full Text] [Related]
43. In silico screening of natural compounds against COVID-19 by targeting Mpro and ACE2 using molecular docking.
Joshi T; Joshi T; Sharma P; Mathpal S; Pundir H; Bhatt V; Chandra S
Eur Rev Med Pharmacol Sci; 2020 Apr; 24(8):4529-4536. PubMed ID: 32373991
[TBL] [Abstract][Full Text] [Related]
44. COSMO-RS-Based Descriptors for the Machine Learning-Enabled Screening of Nucleotide Analogue Drugs against SARS-CoV-2.
Gusarov S; Stoyanov SR
J Phys Chem Lett; 2020 Nov; 11(21):9408-9414. PubMed ID: 33104327
[TBL] [Abstract][Full Text] [Related]
45. Negative Image-Based Screening: Rigid Docking Using Cavity Information.
Postila PA; Kurkinen ST; Pentikäinen OT
Methods Mol Biol; 2021; 2266():125-140. PubMed ID: 33759124
[TBL] [Abstract][Full Text] [Related]
46. Improving virtual screening results with MM/GBSA and MM/PBSA rescoring.
Sahakyan H
J Comput Aided Mol Des; 2021 Jun; 35(6):731-736. PubMed ID: 33983518
[TBL] [Abstract][Full Text] [Related]
47. Fragment Library of Natural Products and Compound Databases for Drug Discovery.
Chávez-Hernández AL; Sánchez-Cruz N; Medina-Franco JL
Biomolecules; 2020 Nov; 10(11):. PubMed ID: 33172012
[TBL] [Abstract][Full Text] [Related]
48. Targeting protein-protein interactions and fragment-based drug discovery.
Valkov E; Sharpe T; Marsh M; Greive S; Hyvönen M
Top Curr Chem; 2012; 317():145-79. PubMed ID: 22006238
[TBL] [Abstract][Full Text] [Related]
49. 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]
50. Ligand-Enhanced Negative Images Optimized for Docking Rescoring.
Kurkinen ST; Lehtonen JV; Pentikäinen OT; Postila PA
Int J Mol Sci; 2022 Jul; 23(14):. PubMed ID: 35887220
[TBL] [Abstract][Full Text] [Related]
51. Enrichment of chemical libraries docked to protein conformational ensembles and application to aldehyde dehydrogenase 2.
Wang B; Buchman CD; Li L; Hurley TD; Meroueh SO
J Chem Inf Model; 2014 Jul; 54(7):2105-16. PubMed ID: 24856086
[TBL] [Abstract][Full Text] [Related]
52. Target-Specific Machine Learning Scoring Function Improved Structure-Based Virtual Screening Performance for SARS-CoV-2 Drugs Development.
Tahir Ul Qamar M; Zhu XT; Chen LL; Alhussain L; Alshiekheid MA; Theyab A; Algahtani M
Int J Mol Sci; 2022 Sep; 23(19):. PubMed ID: 36232307
[TBL] [Abstract][Full Text] [Related]
53. Virtual fragment screening: exploration of MM-PBSA re-scoring.
Kawatkar S; Moustakas D; Miller M; Joseph-McCarthy D
J Comput Aided Mol Des; 2012 Aug; 26(8):921-34. PubMed ID: 22869295
[TBL] [Abstract][Full Text] [Related]
54. SMMPPI: a machine learning-based approach for prediction of modulators of protein-protein interactions and its application for identification of novel inhibitors for RBD:hACE2 interactions in SARS-CoV-2.
Gupta P; Mohanty D
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33839740
[TBL] [Abstract][Full Text] [Related]
55. Energetic analysis of fragment docking and application to structure-based pharmacophore hypothesis generation.
Loving K; Salam NK; Sherman W
J Comput Aided Mol Des; 2009 Aug; 23(8):541-54. PubMed ID: 19421721
[TBL] [Abstract][Full Text] [Related]
56. A Comparison between Enrichment Optimization Algorithm (EOA)-Based and Docking-Based Virtual Screening.
Spiegel J; Senderowitz H
Int J Mol Sci; 2021 Dec; 23(1):. PubMed ID: 35008467
[TBL] [Abstract][Full Text] [Related]
57. Machine learning on ligand-residue interaction profiles to significantly improve binding affinity prediction.
Ji B; He X; Zhai J; Zhang Y; Man VH; Wang J
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33758923
[TBL] [Abstract][Full Text] [Related]
58. AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening.
Pencheva T; Lagorce D; Pajeva I; Villoutreix BO; Miteva MA
BMC Bioinformatics; 2008 Oct; 9():438. PubMed ID: 18925937
[TBL] [Abstract][Full Text] [Related]
59. DockingApp RF: A State-of-the-Art Novel Scoring Function for Molecular Docking in a User-Friendly Interface to AutoDock Vina.
Macari G; Toti D; Pasquadibisceglie A; Polticelli F
Int J Mol Sci; 2020 Dec; 21(24):. PubMed ID: 33333976
[TBL] [Abstract][Full Text] [Related]
60. Towards an Enrichment Optimization Algorithm (EOA)-based Target Specific Docking Functions for Virtual Screening.
Spiegel J; Senderowitz H
Mol Inform; 2022 Nov; 41(11):e2200034. PubMed ID: 35790469
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]