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Computational drug discovery and design

Overview of attention for book
Cover of 'Computational drug discovery and design'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 A Molecular Dynamics Ensemble-Based Approach for the Mapping of Druggable Binding Sites
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    Chapter 2 Analysis of Protein Binding Sites by Computational Solvent Mapping
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    Chapter 3 Evolutionary Trace for Prediction and Redesign of Protein Functional Sites
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    Chapter 4 Information Entropic Functions for Molecular Descriptor Profiling
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    Chapter 5 Expanding the conformational selection paradigm in protein-ligand docking.
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    Chapter 6 Flexibility Analysis of Biomacromolecules with Application to Computer-Aided Drug Design
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    Chapter 7 On the Use of Molecular Dynamics Receptor Conformations for Virtual Screening
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    Chapter 8 Virtual Ligand Screening Against Comparative Protein Structure Models
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    Chapter 9 AMMOS Software: Method and Application
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    Chapter 10 Rosetta Ligand Docking with Flexible XML Protocols.
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    Chapter 11 Normal Mode-Based Approaches in Receptor Ensemble Docking
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    Chapter 12 Application of Conformational Clustering in Protein–Ligand Docking
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    Chapter 13 How to Benchmark Methods for Structure-Based Virtual Screening of Large Compound Libraries
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    Chapter 14 AGGRESCAN: Method, Application, and Perspectives for Drug Design
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    Chapter 15 ATTRACT and PTOOLS: Open Source Programs for Protein–Protein Docking
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    Chapter 16 Prediction of Interacting Protein Residues Using Sequence and Structure Data
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    Chapter 17 MM-GB/SA Rescoring of Docking Poses
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    Chapter 18 A Case Study of Scoring and Rescoring in Peptide Docking
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    Chapter 19 The Solvated Interaction Energy Method for Scoring Binding Affinities
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    Chapter 20 Linear Interaction Energy: Method and Applications in Drug Design
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    Chapter 21 Computational Drug Discovery and Design
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    Chapter 22 Explicit Treatment of Water Molecules in Data-Driven Protein–Protein Docking: The Solvated HADDOCKing Approach
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    Chapter 23 Protein–Water Interactions in MD Simulations: POPS/POPSCOMP Solvent Accessibility Analysis, Solvation Forces and Hydration Sites
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    Chapter 24 Computing the Thermodynamic Contributions of Interfacial Water
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    Chapter 25 Assignment of Protonation States in Proteins and Ligands: Combining pKa Prediction with Hydrogen Bonding Network Optimization
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    Chapter 26 Computational Drug Discovery and Design
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    Chapter 27 Independent-Trajectory Thermodynamic Integration: A Practical Guide to Protein-Drug Binding Free Energy Calculations Using Distributed Computing
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    Chapter 28 Free Energy Calculations from One-Step Perturbations
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    Chapter 29 Using Metadynamics and Path Collective Variables to Study Ligand Binding and Induced Conformational Transitions
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    Chapter 30 Accelerated Molecular Dynamics in Computational Drug Design
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    Chapter 31 Computational Drug Discovery and Design
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    Chapter 32 Decomposing the Energetic Impact of Drug-Resistant Mutations: The Example of HIV-1 Protease–DRV Binding
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    Chapter 33 Guide to Virtual Screening: Application to the Akt Phosphatase PHLPP.
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    Chapter 34 Molecular-Level Simulation of Pandemic Influenza Glycoproteins
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    Chapter 35 Homology Modeling of Cannabinoid Receptors: Discovery of Cannabinoid Analogues for Therapeutic Use
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    Chapter 36 High-Throughput Virtual Screening Lead to Discovery of Non-Peptidic Inhibitors of West Nile Virus NS3 Protease
Attention for Chapter 24: Computing the Thermodynamic Contributions of Interfacial Water
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
52 Dimensions

Readers on

mendeley
49 Mendeley
citeulike
1 CiteULike
Summary Blogs Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Computing the Thermodynamic Contributions of Interfacial Water
Chapter number 24
Book title
Computational Drug Discovery and Design
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-465-0_24
Pubmed ID
22183549
Book ISBNs
978-1-61779-464-3, 978-1-61779-465-0
Authors

Zheng Li, Themis Lazaridis, Li, Zheng, Lazaridis, Themis

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
India 1 2%
Unknown 47 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 29%
Researcher 12 24%
Student > Doctoral Student 5 10%
Student > Bachelor 4 8%
Professor 3 6%
Other 9 18%
Unknown 2 4%
Readers by discipline Count As %
Chemistry 14 29%
Biochemistry, Genetics and Molecular Biology 7 14%
Computer Science 7 14%
Agricultural and Biological Sciences 5 10%
Mathematics 3 6%
Other 8 16%
Unknown 5 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 July 2019.
All research outputs
#5,815,818
of 23,045,021 outputs
Outputs from Methods in molecular biology
#1,638
of 13,194 outputs
Outputs of similar age
#51,564
of 245,534 outputs
Outputs of similar age from Methods in molecular biology
#108
of 477 outputs
Altmetric has tracked 23,045,021 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 13,194 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 245,534 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 477 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.

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