Is there a future for computational chemistry in drug research?

J Comput Aided Mol Des (2012) 26:8790 DOI 10.1007/s10822-011-9493-2

PERSPECTIVE

Is there a future for computational chemistry in drug research?

Gerald M. Maggiora

Received: 25 October 2011 / Accepted: 8 November 2011 / Published online: 19 November 2011 Springer Science+Business Media B.V. 2011

Abstract Improvements in computational chemistry methods have had a growing impact on drug research. But will incremental improvements be sufcient to ensure this continues? Almost all existing efforts to discover new drugs depend on the classic one target, one drug paradigm, although the situation is changing slowly. A new paradigm that focuses on a more systems biology approach and takes account of the reality that most drugs exhibit some level of polypharmacology is beginning to emerge. This will bring about dramatic changes that can signicantly inuence the role that computational methods play in future drug research. But these changes require that current methods be augmented with those from bioinformatics and engineering if the eld is to have a signicant impact on future drug research.

Keywords Computational chemistry Biological

reductionism Emergent properties Systems biology

Polypharmacology Drug design

Since computational chemistry touches numerous areas of chemistry and biology, the road ahead has many branches. Here we will follow the branch corresponding to chemical biology and drug research, since work in these areas is routinely published in the Journal of Computer-Aided Molecular Design. The key issue is in what direction this branch should be heading. To address this, it is rst

necessary to provide some background on the current state of research in computational chemistry, biology, and drug research.

Computational chemistry and its close companion chemical informatics have made substantial progress over the past several decades, driven in large measure by an explosive growth in the speed and affordability of computer power. This has enabled the handling of massive datasets containing several million molecules and their associated biological and physico-chemical properties. Mathematical models for computing many of these properties have improved signicantly. Considerable progress has also been made in quantum and molecular mechanical computations of structure and properties. Computed structures now rival experimentally determined ones for many organic molecules and even some biomacromolecules. And a number of properties difcult or impossible to measure experimentally can now be obtained with improved accuracy.

In addition to the...