179 related articles for article (PubMed ID: 35543232)
41. Identification of Potent Small-Molecule PCSK9 Inhibitors Based on Quantitative Structure-Activity Relationship, Pharmacophore Modeling, and Molecular Docking Procedure.
Mahmoudi A; Butler AE; Banach M; Jamialahmadi T; Sahebkar A
Curr Probl Cardiol; 2023 Jun; 48(6):101660. PubMed ID: 36841313
[TBL] [Abstract][Full Text] [Related]
42. Structure-Based Design and in Silico Screening of Virtual Combinatorial Library of Benzamides Inhibiting 2-trans Enoyl-Acyl Carrier Protein Reductase of
Kouman KC; Keita M; Kre N'Guessan R; Owono Owono LC; Megnassan E; Frecer V; Miertus S
Int J Mol Sci; 2019 Sep; 20(19):. PubMed ID: 31554227
[TBL] [Abstract][Full Text] [Related]
43. Screening for the selective inhibitors of MMP-9 from natural products based on pharmacophore modeling and molecular docking in combination with bioassay experiment, hybrid QM/MM calculation, and MD simulation.
Hou J; Zou Q; Wang Y; Gao Q; Yao W; Yao Q; Zhang J
J Biomol Struct Dyn; 2019 Aug; 37(12):3135-3149. PubMed ID: 30079817
[TBL] [Abstract][Full Text] [Related]
44. Drug repositioning to propose alternative modulators for glucocorticoid receptor through structure-based virtual screening.
Metin R; Akten ED
J Biomol Struct Dyn; 2022; 40(21):11418-11433. PubMed ID: 34355665
[TBL] [Abstract][Full Text] [Related]
45. Computer-aided screening for potential TMPRSS2 inhibitors: a combination of pharmacophore modeling, molecular docking and molecular dynamics simulation approaches.
Idris MO; Yekeen AA; Alakanse OS; Durojaye OA
J Biomol Struct Dyn; 2021 Sep; 39(15):5638-5656. PubMed ID: 32672528
[TBL] [Abstract][Full Text] [Related]
46. Identification of potential inhibitors for LLM of
Kumari R; Dalal V
J Biomol Struct Dyn; 2022; 40(20):9833-9847. PubMed ID: 34096457
[No Abstract] [Full Text] [Related]
47. Pharmacophore modelling, docking and molecular dynamic simulation studies in the discovery of potential human renin inhibitors.
Halimi M; Hajipasha A
J Mol Graph Model; 2022 Nov; 116():108272. PubMed ID: 35932508
[TBL] [Abstract][Full Text] [Related]
48. Structure based virtual screening, 3D-QSAR, molecular dynamics and ADMET studies for selection of natural inhibitors against structural and non-structural targets of Chikungunya.
Vora J; Patel S; Sinha S; Sharma S; Srivastava A; Chhabria M; Shrivastava N
J Biomol Struct Dyn; 2019 Aug; 37(12):3150-3161. PubMed ID: 30114965
[TBL] [Abstract][Full Text] [Related]
49. Pharmacophore-Based Virtual Screening, Quantum Mechanics Calculations, and Molecular Dynamics Simulation Approaches Identified Potential Natural Antiviral Drug Candidates against MERS-CoV S1-NTD.
Bouback TA; Pokhrel S; Albeshri A; Aljohani AM; Samad A; Alam R; Hossen MS; Al-Ghamdi K; Talukder MEK; Ahammad F; Qadri I; Simal-Gandara J
Molecules; 2021 Aug; 26(16):. PubMed ID: 34443556
[TBL] [Abstract][Full Text] [Related]
50. Quantitative structure activity relationship and molecular simulations for the exploration of natural potent VEGFR-2 inhibitors: an
Sharma N; Sharma M; Rahman QI; Akhtar S; Muddassir M
J Biomol Struct Dyn; 2021 May; 39(8):2806-2823. PubMed ID: 32363995
[TBL] [Abstract][Full Text] [Related]
51. Structure-guided pharmacophore based virtual screening, docking, and molecular dynamics to discover repurposed drugs as novel inhibitors against endoribonuclease Nsp15 of SARS-CoV-2.
Jha P; Saluja D; Chopra M
J Biomol Struct Dyn; 2023 Jul; 41(11):5096-5106. PubMed ID: 35652904
[TBL] [Abstract][Full Text] [Related]
52. Exploration and evaluation of bioactive phytocompounds against BRCA proteins by
Prabhavathi H; Dasegowda KR; Renukananda KH; Lingaraju K; Naika HR
J Biomol Struct Dyn; 2021 Sep; 39(15):5471-5485. PubMed ID: 32643536
[TBL] [Abstract][Full Text] [Related]
53. Design of novel dopamine D
Zhang C; Li Q; Meng L; Ren Y
J Biomol Struct Dyn; 2020 Feb; 38(3):860-885. PubMed ID: 30916624
[TBL] [Abstract][Full Text] [Related]
54. Computational investigation of potent inhibitors against YsxC: structure-based pharmacophore modeling, molecular docking, molecular dynamics, and binding free energy.
Kumari R; Rathi R; Pathak SR; Dalal V
J Biomol Struct Dyn; 2023 Feb; 41(3):930-941. PubMed ID: 34913841
[TBL] [Abstract][Full Text] [Related]
55. Identification of highly active natural thyroid hormone receptor agonists by pharmacophore-based virtual screening.
Tang S; Sun L; Wang F
J Biomol Struct Dyn; 2021 Feb; 39(3):901-910. PubMed ID: 31997713
[TBL] [Abstract][Full Text] [Related]
56. Pharmacophore modeling and virtual screening in search of novel Bruton's tyrosine kinase inhibitors.
Sharma A; Thelma BK
J Mol Model; 2019 Jun; 25(7):179. PubMed ID: 31172362
[TBL] [Abstract][Full Text] [Related]
57. Exploration of the structural requirements of HIV-protease inhibitors using pharmacophore, virtual screening and molecular docking approaches for lead identification.
Islam MA; Pillay TS
J Mol Graph Model; 2015 Mar; 56():20-30. PubMed ID: 25541527
[TBL] [Abstract][Full Text] [Related]
58. Developing new PI3Kγ inhibitors by combining pharmacophore modeling, molecular dynamic simulation, molecular docking, fragment-based drug design, and virtual screening.
Zhu J; Sun D; Li X; Jia L; Cai Y; Chen Y; Jin J; Yu L
Comput Biol Chem; 2023 Jun; 104():107879. PubMed ID: 37182359
[TBL] [Abstract][Full Text] [Related]
59. Identification of novel discoidin domain receptor 1 (DDR1) inhibitors using E-pharmacophore modeling, structure-based virtual screening, molecular dynamics simulation and MM-GBSA approaches.
Nada H; Lee K; Gotina L; Pae AN; Elkamhawy A
Comput Biol Med; 2022 Mar; 142():105217. PubMed ID: 35032738
[TBL] [Abstract][Full Text] [Related]
60.
Rajagopal K; Kalusalingam A; Bharathidasan AR; Sivaprakash A; Shanmugam K; Sundaramoorthy M; Byran G
Molecules; 2023 May; 28(10):. PubMed ID: 37241915
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
