The Many Roles of Computation in Drug Discovery

  title={The Many Roles of Computation in Drug Discovery},
  author={William L. Jorgensen},
  pages={1813 - 1818}
An overview is given on the diverse uses of computational chemistry in drug discovery. Particular emphasis is placed on virtual screening, de novo design, evaluation of drug-likeness, and advanced methods for determining protein-ligand binding. 

Comparative Modeling of Drug Target Proteins☆

Computational Methods in Medicinal Chemistry : Mechanistic Investigations and Virtual Screening Development

Computational methods have become an integral part of drug development and can help bring new and better drugs to the market faster. The process of predicting the biological activity of large compo

Multivariate design of molecular docking experiments : An investigation of protein-ligand interactions

This paper presents a meta-analyses of the chiral stationary phase of the H2O2/O2 mixture and shows clear patterns of CHB interaction that are consistent with that of a “drug-drug interaction”.

Frontiers in Computational Chemistry for Drug Discovery

Computational methods pervade almost all aspects of drug discovery and have a fundamental role in drug discovery.

Modeling the Interaction Space of Biological Macromolecules: A Proteochemometric Approach : Applications for Drug Discovery and Development

The ability to model and predict interactions of any biological molecule to recognize and predict those of other molecules is key to understanding molecular recognition processes and their applications in medicine.

Current and emerging opportunities for molecular simulations in structure-based drug design

  • J. Michel
  • Biology, Chemistry
    Physical chemistry chemical physics : PCCP
  • 2014
Opportunities are reviewed for state-of-the-art molecular simulations to progress the understanding of the molecular driving forces of protein–ligand association, assist interpretation of biophysical

Computer-aided drug design: lead discovery and optimization.

The generation of initial lead compounds and the subsequent optimization aimed at improving potency and pharmacological properties are the core activities among all.

Virtual screening and new drug discovery

This review will introduce recent advances in virtual screening and its function in new drug discovery, and discuss the research situation of virtual screening in this country.

In silico antitarget screening.

New perspectives in cancer drug development: computational advances with an eye to design.

Recent applications of advanced simulation techniques to difficult challenges in drug discovery, including the characterization of allosteric mechanisms and the identification of cryptic pockets determined by protein motions, are discussed.



A review of protein-small molecule docking methods

An overview of current docking techniques is presented with a description of applications including single docking experiments and the virtual screening of databases.

Prediction of 'drug-likeness'.

A new method for predicting binding affinity in computer-aided drug design.

A new semi-empirical method for calculating free energies of binding from molecular dynamics (MD) simulations is presented. It is based on standard thermodynamic cycles and on a linear approximation

Computational approaches to molecular recognition.

Lead discovery using molecular docking.

Prediction of drug solubility from structure.

Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B.

The diversity of both hit lists and their dissimilarity from each other suggest that docking and HTS may be complementary techniques for lead discovery.

SPROUT: Recent developments in the de novo design of molecules

SPROUT is a computer program for constrained structure generation. It is designed to generate molecules for a range of applications in molecular recognition. The program uses a number of

Development and validation of a genetic algorithm for flexible docking.

GOLD (Genetic Optimisation for Ligand Docking) is an automated ligand docking program that uses a genetic algorithm to explore the full range of ligand conformational flexibility with partial flexibility of the protein, and satisfies the fundamental requirement that the ligand must displace loosely bound water on binding.