CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions. - Wikidata - awgldk - TriplyDB

CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions.

CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions.

http://www.wikidata.org/entity/Q35263970

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Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screening Focusing on shared subpockets - new developments in fragment-based drug discovery Protein flexibility in docking and surface mapping Comparability of mixed IC₅₀ data - a statistical analysis A Teach-Discover-Treat Application of ZincPharmer: An Online Interactive Pharmacophore Modeling and Virtual Screening Tool CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma.CSAR benchmark exercise 2011-2012: evaluation of results from docking and relative ranking of blinded congeneric series CSAR data set release 2012: ligands, affinities, complexes, and docking decoys Improved pose and affinity predictions using different protocols tailored on the basis of data availability.Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints.Blind prediction of host-guest binding affinities: a new SAMPL3 challenge.Multipose binding in molecular docking.Prospective evaluation of shape similarity based pose prediction method in D3R Grand Challenge 2015.Variability in docking success rates due to dataset preparation Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge Choosing the Optimal Rigid Receptor for Docking and Scoring in the CSAR 2013/2014 Experiment Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms.Neural-Network Scoring Functions Identify Structurally Novel Estrogen-Receptor Ligands.Induced fit docking, and the use of QM/MM methods in docking Lessons learned in empirical scoring with smina from the CSAR 2011 benchmarking exercise Combined Approach of Patch-Surfer and PL-PatchSurfer for Protein-Ligand Binding Prediction in CSAR 2013 and 2014.Check your confidence: size really does matter Lessons Learned over Four Benchmark Exercises from the Community Structure-Activity Resource.Latest developments in molecular docking: 2010-2011 in review.Does a more precise chemical description of protein-ligand complexes lead to more accurate prediction of binding affinity?Review structure- and dynamics-based computational design of anticancer drugs.Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2.Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015.Use of machine learning approaches for novel drug discovery.Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM Empirical Scoring Functions for Affinity Prediction of Protein-ligand Complexes.Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation.D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions.A D3R prospective evaluation of machine learning for protein-ligand scoring.Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach.One Size Does Not Fit All: The Limits of Structure-Based Models in Drug Discovery.Optimal affinity ranking for automated virtual screening validated in prospective D3R grand challenges.Theoretical characterization of galanin receptor type 3 (Gal3 ) and its interaction with agonist (GALANIN) and antagonists (SNAP 37889 and SNAP 398299): an in silico analysis.Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization.

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P2860

CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions.

http://www.wikidata.org/entity/Q35263970

description

2011 nî lūn-bûn

@nan

2011 թուականի Օգոստոսին հրատարակուած գիտական յօդուած

@hyw

2011 թվականի օգոստոսին հրատարակված գիտական հոդված

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2011年の論文

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2011年論文

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2011年論文

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2011年論文

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2011年論文

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2011年論文

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2011年论文

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CSAR benchmark exercise of 201 ...... l submitted scoring functions.

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CSAR benchmark exercise of 201 ...... l submitted scoring functions.

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CSAR benchmark exercise of 201 ...... l submitted scoring functions.

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CSAR benchmark exercise of 201 ...... l submitted scoring functions.

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CSAR benchmark exercise of 201 ...... l submitted scoring functions.

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CSAR benchmark exercise of 201 ...... l submitted scoring functions.

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P1433

Journal of Chemical Information and Modeling

P1476

CSAR benchmark exercise of 201 ...... ll submitted scoring functions

@en

P2093

Chao-Yie Yang

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James B Dunbar

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Richard D Smith

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P2860

MolProbity: all-atom contacts and structure validation for proteins and nucleic acids

PRO_SELECT: combining structure-based drug design and array-based chemistry for rapid lead discovery. 2. The development of a series of highly potent and selective factor Xa inhibitors

Selective and dual action orally active inhibitors of thrombin and factor Xa

Thiophene-anthranilamides as highly potent and orally available factor Xa inhibitors

SAR and X-ray structures of enantiopure 1,2-cis-(1R,2S)-cyclopentyldiamine and cyclohexyldiamine derivatives as inhibitors of coagulation Factor Xa

Discovery of 1-(4-methoxyphenyl)-7-oxo-6-(4-(2-oxopiperidin-1-yl)phenyl)-4,5,6,7-tetrahydro-1H-pyrazolo[3,4-c]pyridine-3-carboxamide (apixaban, BMS-562247), a highly potent, selective, efficacious, and orally bioavailable inhibitor of blood coagulat

AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

WHAT IF: a molecular modeling and drug design program

Remarks about protein structure precision

Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

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2115-2131

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scholarly article

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10.1021/CI200269Q

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9

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P478

51

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Emilio Xavier Esposito

Peter Man-Un Ung

Heather A Carlson

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2011-08-29T00:00:00Z

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51540966

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21809884

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3186041

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