Cited by 259Computational Drug Discovery MethodsProtein Structure and Dynamicsvaccines and immunoinformatics approaches

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Scoring functions for protein-ligand docking.

Bentham Science Publisher, Bentham Science Publisher·2006·Current Protein & Peptide Science

DOI 10.2174/138920306778559395

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Abstract

Virtual screening by molecular docking has become established as a method for drug lead discovery and optimization. All docking algorithms make use of a scoring function in combination with a method of search. Two theoretical aspects of scoring function performance dominate operational performance. The first is the degree to which a scoring function has a global extremum within the ligand pose landscape at the proper location. The second is the degree to which the magnitude of the function at the extremum is accurate. Presuming adequate search strategies, a scoring function's location performance will dominate behavior with respect to docking accuracy: the degree to which a predicted pose of a ligand matches experimental observation. A scoring function's magnitude performance will dominate behavior with respect to screening utility: enrichment of true ligands over non-ligands. Magnitude estimation also controls pure scoring accuracy: the degree to which bona fide ligands of a particular protein may be correctly ranked. Approaches to the development of scoring functions have varied widely, with a number of functions yielding similarly high levels of performance relating to the location issue. However, even among functions performing equally well on location, widely varying performance is observed on the question of magnitude. In many cases, performance is good enough to yield high enrichments of true ligands versus non-ligands in screening across a wide variety of protein types. Generally, performance is not good enough to correctly rank among true ligands. Strategies for improvement are discussed.

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New Wine in an Old Bottle: Utilizing Chemical Genetics to Dissect Apical Hook Development
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Investigation of the Potential Antidiabetic Effect of Zygophyllum Sp. by Studying the Interaction of its Chemical Compounds with Alpha-Amylase and DPP-4 Enzymes using a Molecular Docking Approach
Arbi, B., Bouchentouf, S., & El‐Shazly, M. (2023) · Current Enzyme Inhibition · doi:10.2174/1573408019666230202092954 · Cited by 5
Artificial intelligence approaches for anti-addiction drug discovery
董, C. 晨. D., Jiang, J. H., Hayes, N., Su, Z., & Wei, G. (2025) · Digital Discovery · doi:10.1039/d5dd00032g · Cited by 4
Ligand B‐Factor Index: A Metric for Prioritizing Protein‐Ligand Complexes in Docking
Halip, L., Neanu, C., & Avram, S. I. (2025) · Molecular Informatics · doi:10.1002/minf.70010 · Cited by 4
Structural characterization of human CRTh2: a combined homology modeling, molecular docking and 3D-QSAR-based in silico approach
Babu, S., Nagarajan, S. K., Lee, S. H., & Madhavan, T. (2016) · Medicinal Chemistry Research · doi:10.1007/s00044-016-1516-z · Cited by 4
“The docking algorithm uses the idealized active site called the protomol (Jain, 2006).”
Design and Synthesis of Angiotensin Converting Enzyme (ACE) Inhibitors: Analysis of the Role of Tetrazole Ring Appended to Biphenyl Moiety
Bayannavar, P. K., Kamble, R. R., Joshi, S. D., Nesaragi, A. R., Shaikh, S. K. J., Sudha, B. S., Dodamani, S., & Hoolageri, S. R. (2022) · ChemistrySelect · doi:10.1002/slct.202103336 · Cited by 4
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Moon, D. (2024) · Biomolecules · doi:10.3390/biom14121572 · Cited by 5
Enhancing Metaheuristic-based Virtual Screening Methods on Massively Parallel and Heterogeneous Systems
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“In general, VS methods optimize scoring functions , which are mathematical models used to predict the strength of the non-covalent interaction between two molecules after docking [17].”
Method
Biomolecular Talks—Part 1: A Theoretical Revisit on Molecular Modeling and Docking Approaches
Ramaswamy, A., Balasubramanian, S., & Rajagopalan, M. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822312-3.00015-1 · Cited by 4
Bioinformatics and Computational Biology
Ali, M. A., Zahoor, A., Niaz, Z., Jabran, M., Anas, M., Shafique, I., Ahmad, H. M., Usama, M., & Abbas, A. (2024) · Springer eBooks · doi:10.1007/978-981-97-0814-7_10 · Cited by 4
POSE SCALING: GEOMETRICAL ASSESSMENT OF LIGAND BINDING POSES
Zhong, S., & MacKerell, A. D. (2008) · Journal of Theoretical and Computational Chemistry · doi:10.1142/s0219633608004155 · Cited by 4
A COMPUTATIONAL STUDY OF CIPROFLOXACIN METABOLITES AND SOME NATURAL COMPOUNDS AGAINST RESISTANT METHICILLIN STAPHYLOCOCCUS AUREUS (MRSA)
MOURAD, T., & Alahmad, S. (2022) · International Journal of Pharmacy and Pharmaceutical Sciences · doi:10.22159/ijpps.2022v14i8.44560 · Cited by 4
Combined Deep Learning and Molecular Docking Simulations Approach Identifies Potentially Effective FDA Approved Drugs for Repurposing Against SARS-CoV-2Preprint
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ComparePD : Improving protein– DNA complex model comparison with hydrogen bond energy‐based metrics
Malik, F., & Guo, J. (2023) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.26493 · Cited by 3
Structure‐Based Approaches for the Prediction of Alzheimer's Disease Inhibitors: Comparative Interactions Analysis, Pharmacophore Modeling and Molecular Dynamics Simulations
Zerroug, E., Belaıdı, S., Chtita, S., Tuffaha, G. O., Qais, F. A., Kciuk, M., Dubey, A., & Taha, M. O. (2024) · ChemistrySelect · doi:10.1002/slct.202303307 · Cited by 3
Local functional descriptors for surface comparison based binding prediction
Cipriano, G., Phillips, N. G., & Gleicher, M. L. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-314 · Cited by 3
“While there is evidence that detailed physical computations are not essential for the kinds of applications our approach targets [56], we have chosen to use standard methods in our initial experiments.”
Method
Increasing Molecular Dynamics Simulations Throughput by Virtualizing Remote GPUs with rCUDA
Prades, J., Reaño, C., Silla, F., Imbernón, B., Pérez‐Sánchez, H., & Cecilia, J. M. (2018) · International Conference on Parallel Processing Workshops (ICPPW) · doi:10.1145/3229710.3229734 · Cited by 3
“In general, VS methods optimize scoring functions , which are mathematical models used to predict the strength of the non-covalent interaction between two molecules after docking [8].”
Method
The design of TOPK inhibitors using structure-based pharmacophore modeling and molecular docking based on an MD-refined homology model
Fakhouri, L. I., & Al‐Shar’i, N. A. (2022) · Molecular Diversity · doi:10.1007/s11030-021-10361-w · Cited by 3
Insilico, network pharmacology and neural network studies on Sida acuta Burm f.- based phytochemicals targeting NADH-ubiquinone oxidoreductase
Oyebamiji, A. K., Akintelu, S. A., Ebenezer, O., et al. (2025) · Discover Pharmaceutical Sciences · doi:10.1007/s44395-025-00002-8 · Cited by 3
“More so, the use of computational approaches such as density functional theory, molecular modeling method and quantitative structure activity relationship have been reported by several scientists to be effective methods of observing various activities in any complexes [19, 20].”
Recent Advancements in Computing Reliable Binding Free Energies in Drug Discovery Projects
Murugan, N. A., Poongavanam, V., & Priyakumar, U. D. (2019) · Challenges and advances in computational chemistry and physics · doi:10.1007/978-3-030-05282-9_7 · Cited by 3

Authors: Bentham Science Publisher, B. S. P.
Venue: Current Protein & Peptide Science
Publisher: Bentham Science Publishers Ltd.
Published: 2006-10-01
Volume: 7
Issue: 5
Pages: 407-420
ISSN: 1389-2037 (ISSN-L)
DOI: 10.2174/138920306778559395
OpenAlex: W1512801428
Cited by: 258
References: 0
Citations by year: 2026: 4 · 2025: 8 · 2024: 11 · 2023: 21 · 2022: 32 · 2021: 16 · 2020: 15 · 2019: 16 · 2018: 12 · 2017: 12 · 2016: 14 · 2015: 8 · 2014: 6 · 2013: 6 · 2012: 13
FWCI: 12.94
Type: journal article
Language: en
Open access: closed
Locations: Current Protein and Peptide Science (publishedVersion)
PubMed (publishedVersion)
Funders: National Institutes of Health
National Institute of General Medical Sciences (GM070781, R01GM070481)
Topics: Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
Keywords: protein-ligand docking, scoring functions, virtual screening, docking accuracy, enrichment, ligand ranking, lead compound identification
MeSH terms: Animals, Drug Evaluation, Preclinical, Ligands, Models, Chemical, Protein Binding, Proteins, Research Design

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Scoring functions for protein-ligand docking.

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