| scholarly article | Q13442814 |
| P819 | ADS bibcode | 2012PLoSO...738086L |
| P356 | DOI | 10.1371/JOURNAL.PONE.0038086 |
| P932 | PMC publication ID | 3372491 |
| P698 | PubMed publication ID | 22701601 |
| P5875 | ResearchGate publication ID | 225376706 |
| P2093 | author name string | Shu Liu | |
| Li-Hua Zhou | |||
| Rao Fu | |||
| Sheng-Ping Chen | |||
| P2860 | cites work | DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases | Q27231136 |
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| The transcriptionally active amyloid precursor protein (APP) intracellular domain is preferentially produced from the 695 isoform of APP in a {beta}-secretase-dependent pathway | Q39641837 | ||
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| Derivation of class II force fields. VIII. Derivation of a general quantum mechanical force field for organic compounds | Q44239882 | ||
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| Comparative evaluation of 11 scoring functions for molecular docking | Q44457437 | ||
| P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P433 | issue | 6 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | principal component analysis | Q2873 |
| virtual screening | Q4112105 | ||
| P304 | page(s) | e38086 | |
| P577 | publication date | 2012-01-01 | |
| P1433 | published in | PLOS One | Q564954 |
| P1476 | title | Application of consensus scoring and principal component analysis for virtual screening against β-secretase (BACE-1) | |
| P478 | volume | 7 |
| Q52654613 | Changing paradigm from one target one ligand towards multi target directed ligand design for key drug targets of Alzheimer disease: An important role of Insilco methods in multi target directed ligands design. |
| Q30607323 | Docking challenge: protein sampling and molecular docking performance |
| Q57492456 | Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges |
| Q30585969 | Enhanced ranking of PknB Inhibitors using data fusion methods |
| Q42056130 | Evaluation of 11 scoring functions performance on matrix metalloproteinases |
| Q64121450 | Exponential consensus ranking improves the outcome in docking and receptor ensemble docking |
| Q48875877 | Fusing Docking Scoring Functions Improves the Virtual Screening Performance for Discovering Parkinson's Disease Dual Target Ligands. |
| Q64059641 | Hybrid approach to sieve out natural compounds against dual targets in Alzheimer's Disease |
| Q90193662 | Key Topics in Molecular Docking for Drug Design |
| Q37563518 | Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme |
| Q40166866 | Repositioning FDA Drugs as Potential Cruzain Inhibitors from Trypanosoma cruzi: Virtual Screening, In Vitro and In Vivo Studies. |
| Q64949997 | Rescoring and Linearly Combining: A Highly Effective Consensus Strategy for Virtual Screening Campaigns. |
| Q38995015 | Targeting of AMP-activated protein kinase: prospects for computer-aided drug design |
| Q27902311 | vSDC: a method to improve early recognition in virtual screening when limited experimental resources are available |
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