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Open AccessJournal ArticleDOI

Computational methods in drug discovery.

TLDR
An overview of computational methods used in different facets of drug discovery and highlight some of the recent successes is presented, both structure-based and ligand-based drug discovery methods are discussed.
Abstract
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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Citations
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TL;DR: A wide range of new lead finding and lead optimization opportunities result from novel screening methods by NMR, which are the topic of this review article.
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Kinase inhibitors: the road ahead

TL;DR: An overview of the novel targets, biological processes and disease areas that kinase-targeting small molecules are being developed against, highlight the associated challenges and assess the strategies and technologies that are enabling efficient generation of highly optimized kinase inhibitors are provided.
Journal ArticleDOI

Structure-Based Virtual Screening: From Classical to Artificial Intelligence.

TL;DR: An overview of the challenges involved in the use of CADD to performSBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process are presented.
References
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Journal ArticleDOI

Automated Site Preparation in Physics-Based Rescoring of Receptor Ligand Complexes

TL;DR: This work implements and evaluates an automated procedure for optimizing polar hydrogens in protein‐binding sites in complex with ligands, and tests the utility of this method for identifying nativelike ligand poses using 247 protein‐ligand complexes from an established database of docked decoys.
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A Prospective Virtual Screening Study: Enriching Hit Rates and Designing Focus Libraries To Find Inhibitors of PI3Kδ and PI3Kγ

TL;DR: It is found that docking scoring functions are not capable of providing a reliable relative ranking of a set of compounds, but a prioritization of groups of compounds does emerge, which allows for the chemistry efforts to be quickly focused on the most viable candidates.
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Support vector machine applied in QSAR modelling

TL;DR: There is wide prospect for the application of support vector machine (SVM) into QSAR modeling as well as that using radial basis kernel function in both calibration and prediction.
Journal ArticleDOI

Web services as applications' integration tool: QikProp case study

TL;DR: Because by using the described approach almost any legacy application can be wrapped as a Web service, this form of delivery may be recommended as a global alternative to traditional deployment solutions.
Book Chapter

Application of Artificial Neural Networks in Modern Drug Discovery Chapter – 6 published in Artificial Neural Network for Drug Design, Delivery and Disposition

TL;DR: Artificial neural networks (ANNs) are frequently being used for drug design and the discovery process and mimics the capacity of the human brain in terms of its structure and function.
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