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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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Journal ArticleDOI

Virtual Screening Algorithms in Drug Discovery: A Review Focused on Machine and Deep Learning Methods

TL;DR: Virtual screening (VS) as discussed by the authors is an in-silico approach based on computer simulation that can select organic molecules toward the therapeutic targets of interest, based on the structure of ligands, receptors, or fragments.
Journal ArticleDOI

A Variational Ansatz for Taylorized Imaginary Time Evolution

TL;DR: In this article , a variational ansatz for noisy quantum computers to calculate the ground state with the help of imaginary time evolution is proposed. But the authors admit that the complexity of strongly correlated molecular systems limits the performance of classical algorithms, and they admit that quantum computation has the potential to be a game changer in the field of molecular simulations.
Journal ArticleDOI

Microbiological Aspects of Unique, Rare, and Unusual Fatty Acids Derived from Natural Amides and Their Pharmacological Profile

TL;DR: In this article , the pharmacological profile of unique, rare, and unusual fatty acids derived from natural amides is considered, which demonstrated strong antifungal, antibacterial, antiviral, antineoplastic, anti-inflammatory activities.
References
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Journal ArticleDOI

AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

TL;DR: AutoDock Vina achieves an approximately two orders of magnitude speed‐up compared with the molecular docking software previously developed in the lab, while also significantly improving the accuracy of the binding mode predictions, judging by tests on the training set used in AutoDock 4 development.

疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

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TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
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CHARMM: A program for macromolecular energy, minimization, and dynamics calculations

TL;DR: The CHARMM (Chemistry at Harvard Macromolecular Mechanics) as discussed by the authors is a computer program that uses empirical energy functions to model macromolescular systems, and it can read or model build structures, energy minimize them by first- or second-derivative techniques, perform a normal mode or molecular dynamics simulation, and analyze the structural, equilibrium, and dynamic properties determined in these calculations.
Journal ArticleDOI

Scalable molecular dynamics with NAMD

TL;DR: NAMD as discussed by the authors is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems that scales to hundreds of processors on high-end parallel platforms, as well as tens of processors in low-cost commodity clusters, and also runs on individual desktop and laptop computers.
Journal ArticleDOI

Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

TL;DR: Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described in this article, where the rule of 5 is used to predict poor absorption or permeability when there are more than 5 H-bond donors, 10 Hbond acceptors, and the calculated Log P (CLogP) is greater than 5 (or MlogP > 415).
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