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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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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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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.
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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

3V: cavity, channel and cleft volume calculator and extractor

TL;DR: The 3V web server can automatically extract and comprehensively analyze all the internal volumes from input RNA and protein structures, and produces volumetric representations, both as images and downloadable files, which can be used for further analysis.
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Protein clefts in molecular recognition and function.

TL;DR: An analysis of how cleft volumes in proteins relate to their molecular interactions and functions is presented, finding that, in single-chain enzymes, the ligand is bound in the largest cleft in over 83% of the proteins.
Journal ArticleDOI

Rosettaligand : Protein-small molecule docking with full side-chain flexibility

TL;DR: A new method for docking small molecules into protein binding sites employing a Monte Carlo minimization procedure in which the rigid body position and orientation of the small molecule and the protein side‐chain conformations are optimized simultaneously is described.
Proceedings ArticleDOI

Millisecond-scale molecular dynamics simulations on Anton

TL;DR: Anton's performance when executing actual MD simulations whose accuracy has been validated against both existing MD software and experimental observations is reported, allowing the observation of aspects of protein dynamics that were previously inaccessible to both computational and experimental study.
Journal ArticleDOI

Comparison of several molecular docking programs: pose prediction and virtual screening accuracy.

TL;DR: Cognate ligand docking to 68 diverse, high-resolution X-ray complexes revealed that ICM, GLIDE, and Surflex generated ligand poses close to the X-rays conformation more often than the other docking programs.
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