Predicting off-targets by computational methods is getting increasing importance in early drug discovery stages.
Efficient connection of the biological components with related literature by computational methods was a useful strategy for deducing the metabolic pathways.
Because of the lack of known conserved characteristics of piRNA sequences (except the occurrence of a uridine base at the first position) and structure (there is no known structure for piRNAs), their identification by computational methods is a difficult task.
Although, the osmoprotectants listed on the resource were reported in the literature as such, the detection of a pathway in a genome by computational methods is not conclusive evidence for its activation or its role in osmoprotection, as biodiversity is incredibly big and many organisms can, under abiotic stress, use some pathways and not others despite the presence of all.
However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed.
In recent years, enormous amounts of interaction data have been generated by various high-throughput experiments thus computational methods are invaluable to analyze these data.
All data regarding geometry and spin state provided by both computational methods were compared with experimental data when available.
Therefore, as tandem MS alone was unable to provide clarity about how protonation sites affect gas-phase structures, structural analysis by IM and computational methods were required.
28, 31 Although the high affinity of ShK and BgK for Kv1.3 channel by experimental and some computational methods was previously reported, 9, 10, 32, 33 these results are barely agreeing in respect to some binding sites that could be useful for the treatment of autoimmune diseases.
Application of the computational methods is illustrated by means of example design problems that are worked in complete detail.
