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New Scoring Functions for Virtual Screening from Molecular Dynamics Simulations with a Quantum-Refined Force-Field (QRFF-MD). Application to Cyclin-Dependent Kinase 2

https://doi.org/10.1021/ci050289+
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/jcc.20047openalex-snapshot
Binding affinity prediction with different force fields: Examination of the linear interaction energy method
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Absolute free energies of binding of peptide analogs to the HIV‐1 protease from molecular dynamics simulations
inferredcites →https://doi.org/10.1006/jmbi.1996.0477openalex-snapshot
A Fast Flexible Docking Method using an Incremental Construction Algorithm
inferredcites →https://doi.org/10.1007/978-1-4613-3111-7_1openalex-snapshot
Intermolecular Forces
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Calculating Structures and Free Energies of Complex Molecules: Combining Molecular Mechanics and Continuum Models
inferredcites →https://doi.org/10.1021/ar010014popenalex-snapshot
Ligand Binding Affinities from MD Simulations
inferredcites →https://doi.org/10.1021/ci034289qopenalex-snapshot
Virtual Screening Using Protein−Ligand Docking: Avoiding Artificial Enrichment
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Incorporating Protein Flexibility in Structure-Based Drug Discovery: Using HIV-1 Protease as a Test Case
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Estimation of Binding Affinities for Selective Thrombin Inhibitors via Monte Carlo Simulations
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Prediction of Activity for Nonnucleoside Inhibitors with HIV-1 Reverse Transcriptase Based on Monte Carlo Simulations
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Toward Selective ERβ Agonists for Central Nervous System Disorders: Synthesis and Characterization of Aryl Benzthiophenes
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Calculation of the Binding Affinity of β-Secretase Inhibitors Using the Linear Interaction Energy Method
inferredcites →https://doi.org/10.1021/jm030209yopenalex-snapshot
Lessons in Molecular Recognition: The Effects of Ligand and Protein Flexibility on Molecular Docking Accuracy
inferredcites →https://doi.org/10.1021/jm0304358openalex-snapshot
General Model for Estimation of the Inhibition of Protein Kinases Using Monte Carlo Simulations
inferredcites →https://doi.org/10.1021/jm030489hopenalex-snapshot
Assessing Scoring Functions for Protein−Ligand Interactions
inferredcites →https://doi.org/10.1021/jm0306430openalex-snapshot
Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy
inferredcites →https://doi.org/10.1021/jm049081qopenalex-snapshot
Validation and Use of the MM-PBSA Approach for Drug Discovery
inferredcites →https://doi.org/10.1021/jm049312topenalex-snapshot
Interaction Profiles of Protein Kinase−Inhibitor Complexes and Their Application to Virtual Screening
inferredcites →https://doi.org/10.1021/jp011698lopenalex-snapshot
Insertion of Lithium Ions into Carbon Nanotubes: An ab Initio Study
inferredcites →https://doi.org/10.1023/a:1007996124545openalex-snapshot
Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes
inferredcites →https://doi.org/10.1023/a:1012266200343openalex-snapshot
Improved convergence of binding affinities with free energy perturbation: Application to nonpeptide ligands with pp60src SH2 domain
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Free energies of ligand binding for structurally diverse compounds
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Crystallographic Approach to Identification of Cyclin-dependent Kinase 4 (CDK4)-specific Inhibitors by Using CDK4 Mimic CDK2 Protein
inferredcites →https://doi.org/10.1093/nar/28.1.235openalex-snapshot
The Protein Data Bank
inferredcites →https://doi.org/10.2174/0929867043455684openalex-snapshot
Virtual Screening for Kinase Targets

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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QM and QM / MM Approaches to Evaluating Binding Affinities
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Computational Approaches in Peptide and Protein Design: An Overview
inferred← citeshttps://doi.org/10.1002/9783527633326.ch7openalex-snapshot
The Challenge of Affinity Prediction: Scoring Functions for Structure‐Based Virtual Screening
inferred← citeshttps://doi.org/10.1002/9783527645947.ch7openalex-snapshot
Quantum Mechanics in Structure‐Based Ligand Design
inferred← citeshttps://doi.org/10.1002/chin.200617221openalex-snapshot
New Scoring Functions for Virtual Screening from Molecular Dynamics Simulations with a Quantum‐Refined Force‐Field (QRFF‐MD). Application to Cyclin‐Dependent Kinase 2.
inferred← citeshttps://doi.org/10.1002/jcc.24473openalex-snapshot
Exponential repulsion improves structural predictability of molecular docking
inferred← citeshttps://doi.org/10.1007/978-90-481-2368-1_2openalex-snapshot
Complementarity of Hydrophobic/Hydrophilic Properties In Protein—Ligand Complexes: A New Tool to Improve Docking Results
inferred← citeshttps://doi.org/10.1007/s10822-011-9413-5openalex-snapshot
Transferable scoring function based on semiempirical quantum mechanical PM6-DH2 method: CDK2 with 15 structurally diverse inhibitors
inferred← citeshttps://doi.org/10.1016/b978-1-60805-865-5.50004-6openalex-snapshot
Recent advances in the discovery and development of protein- protein interaction modulators by virtual screening
inferred← citeshttps://doi.org/10.1016/j.bmc.2011.12.004openalex-snapshot
Prediction of sites of metabolism in a substrate molecule, instanced by carbamazepine oxidation by CYP3A4
inferred← citeshttps://doi.org/10.1016/j.bmcl.2010.07.103openalex-snapshot
Application of a novel in silico high-throughput screen to identify selective inhibitors for protein–protein interactions
inferred← citeshttps://doi.org/10.1016/j.bmcl.2012.10.018openalex-snapshot
Impact of protein binding cavity volume (PCV) and ligand volume (LV) in rigid and flexible docking of protein–ligand complexes
inferred← citeshttps://doi.org/10.1016/j.cplett.2008.03.022openalex-snapshot
The binding domain of the HMGB1 inhibitor carbenoxolone: Theory and experiment
inferred← citeshttps://doi.org/10.1016/j.ejmech.2017.07.067openalex-snapshot
Recent advances on CDK inhibitors: An insight by means of in silico methods
inferred← citeshttps://doi.org/10.1021/acsomega.8b00175openalex-snapshot
Use of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein–Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors
inferred← citeshttps://doi.org/10.1021/ci5002026openalex-snapshot
Enrichment of Chemical Libraries Docked to Protein Conformational Ensembles and Application to Aldehyde Dehydrogenase 2
inferred← citeshttps://doi.org/10.1021/jm070077zopenalex-snapshot
An Integrated Computational Approach to the Phenomenon of Potent and Selective Inhibition of Aurora Kinases B and C by a Series of 7-Substituted Indirubins
inferred← citeshttps://doi.org/10.1111/cbdd.12877openalex-snapshot
Clarifying binding difference of ATP and ADP to extracellular signal‐regulated kinase 2 by using molecular dynamics simulations
inferred← citeshttps://doi.org/10.1111/j.1747-0285.2012.01396.xopenalex-snapshot
Generation of Receptor Structural Ensembles for Virtual Screening Using Binding Site Shape Analysis and Clustering
inferred← citeshttps://doi.org/10.1134/s1068162010040023openalex-snapshot
Molecular docking: The role of noncovalent interactions in the formation of protein-nucleotide and protein-peptide complexes
inferred← citeshttps://doi.org/10.1146/annurev.biophys.36.040306.132550openalex-snapshot
Calculation of Protein-Ligand Binding Affinities
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1000528openalex-snapshot
High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations
inferred← citeshttps://doi.org/10.2174/978160805142711101010099openalex-snapshot
Receptor Flexibility in Ligand Docking and Virtual Screening
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