title: Overview of computational methods employed in early-stage drug discovery.
abstract: BACKGROUND
  The understanding of biomolecular interactions ultimately depends on knowledge about the structural and dynamic details of the interacting system. Rational structure-based drug design implements computational methodology in this rationale.
  
  
  CONCLUSIONS
  Together with increasing throughput of structural biology, molecular modeling has progressively contributed to rational drug design and elucidation of nontoxic and patient-tailored interventions, helping to make drug development more cost-efficient. But in this challenging time for the pharmaceutical industry, the successful discovery of novel therapeutics should rely on integration of computational modeling with experimentation when it comes to ligand-binding energetics, system flexibility and genetic diversity/heterogeneity of the target. Moreover, it appears that many drugs--even those for which specific receptors have been identified--intercalate in biological membranes, which could also become the actual target.
  
  
  CONCLUSIONS
  Understanding the drug-target and drug-unwanted-target interactions at the atomic level is fundamental in the initial phases of the drug development process. Molecular dynamics simulations and complementary computational methods are already contributing in this endeavor for the soluble pharmacological targets and show an increasing importance in the understanding of membrane-ligand interactions.
authors.affiliation: Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway.
authors.forename: Age Aleksander
authors.initials: AA
authors.lastname: Skjevik
authors.forename: Knut
authors.initials: K
authors.lastname: Teigen
authors.forename: Aurora
authors.initials: A
authors.lastname: Martinez
mesh_terms: D020650:Combinatorial Chemistry Techniques; D055808:Drug Discovery / Q000191:economics / Q000379:methods; D057166:High-Throughput Screening Assays; D056004:Molecular Dynamics Simulation; D021281:Quantitative Structure-Activity Relationship; D013816:Thermodynamics