Classification of Current Scoring Functions

Liu, Jie; Wang, Renxiao

doi:10.1021/ci500731a

Cited by 248 publications

(219 citation statements)

References 103 publications

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“…Scoring is used to evaluate and rank the target–ligand complexes predicted by docking algorithms. Scoring functions are used in SBDD for scoring and evaluating protein–ligand interactions [100–101]. The scoring function used by docking algorithms is a crucial part of the algorithm.…”

Section: Reviewmentioning

confidence: 99%

Computational methods in drug discovery

Leelananda

Lindert

2016

Beilstein J. Org. Chem.

470

309

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The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

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Section: Reviewmentioning

confidence: 99%

Computational methods in drug discovery

Leelananda

Lindert

2016

Beilstein J. Org. Chem.

470

309

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“…Accurately scoring the binding and ranking of docked compounds is a crucial step in virtual screening. Frequently used scoring functions, as reported in several papers (Huang et al 2010;Cheng et al 2012;Lavecchia and Di Giovanni 2013;Liu and Wang 2015), are divided into three categories: (a) Force fieldbased functions calculate binding affinity derived from physical atomic contacts in the target-ligand complex. Both solvation and entropy terms can also be evaluated.…”

Section: Docking and Scoringmentioning

confidence: 99%

Role of computer-aided drug design in modern drug discovery

Macalino¹,

Gosu²,

Hong³

et al. 2015

Arch. Pharm. Res.

544

316

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Drug discovery utilizes chemical biology and computational drug design approaches for the efficient identification and optimization of lead compounds. Chemical biology is mostly involved in the elucidation of the biological function of a target and the mechanism of action of a chemical modulator. On the other hand, computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the determination of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are critical for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with experimental routines, has a powerful impact on rational drug design. In this article, we give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.

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“…An additional electrostatic term can be added to reflect these contributions. Since hydrogen bonds are also calculated in the electrostatic term, one must also be careful of not over-counting its contributions [153,154]. …”

Section: Challenges In Automated Protein Designmentioning

confidence: 99%

Recent advances in automated protein design and its future challenges

Setiawan

Brender

Zhang

2018

Expert Opinion on Drug Discovery

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Introduction Protein function is determined by protein structure which is in turn determined by the corresponding protein sequence. If the rules that cause a protein to adopt a particular structure are understood, it should be possible to refine or even redefine the function of a protein by working backwards from the desired structure to the sequence. Automated protein design attempts to calculate the effects of mutations computationally with the goal of more radical or complex transformations than are accessible by experimental techniques. Areas covered The authors give a brief overview of the recent methodological advances in computer-aided protein design, showing how methodological choices affect final design and how automated protein design can be used to address problems considered beyond traditional protein engineering, including the creation of novel protein scaffolds for drug development. Also, the authors address specifically the future challenges in the development of automated protein design. Expert opinion Automated protein design holds potential as a protein engineering technique, particularly in cases where screening by combinatorial mutagenesis is problematic. Considering solubility and immunogenicity issues, automated protein design is initially more likely to make an impact as a research tool for exploring basic biology in drug discovery than in the design of protein biologics.

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Classification of Current Scoring Functions

Cited by 248 publications

References 103 publications

Computational methods in drug discovery

Computational methods in drug discovery

Role of computer-aided drug design in modern drug discovery

Recent advances in automated protein design and its future challenges

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