Applications and Limitations of In Silico Models in Drug Discovery

Abstract

Drug discovery in the late twentieth and early twenty-first century has witnessed a myriad of changes that were adopted to predict whether a compound is likely to be successful, or conversely enable identification of molecules with liabilities as early as possible. These changes include integration of in silico strategies for lead design and optimization that perform complementary roles to that of the traditional in vitro and in vivo approaches. The in silico models are facilitated by the availability of large datasets associated with high-throughput screening, bioinformatics algorithms to mine and annotate the data from a target perspective, and chemoinformatics methods to integrate chemistry methods into lead design process. This chapter highlights the applications of some of these methods and their limitations. We hope this serves as an introduction to in silico drug discovery.

The design of high affinity human PD-1 mutants by using molecular dynamics simulations (MD)

“…First, computational approaches need to substitute every 20 residue types for each site and all rotamers of each mutation state should be evaluated by an energy minimization process to coincide with the minimum global energy structure for one single mutation. Therefore, the mutational spaces expand dramatically big to be handled by the current computational cost [ 32 ]. Second, multi-site mutagenesis is briefly a sum of a list of single mutations.…”

Metabolic Screening in Drug Development: In-Vivo to In-Silico

“…Now to test, analyse and predict ADME profile of this huge number of new molecules in short time emergence of computer technology based methods are inevitable. This computer based systems are known as In-Silico methods [5].…”

In Silico Verification and Parallel Reaction Monitoring Prevalidation of Potential Prostate Cancer Biomarkers

“…In silico database searching is becoming an indispensable adjunct to high throughput systems biology, albeit there are limitations to its use [33]. Using the SRM database, we verified that over half (51.1%) of our selected PTPs have been assayed previously using targeted SRM.…”

“…However, a duty cycle of close to 100% in the triple quadrupole instrument with electron multiplier-based detection offers a better sensitivity compared with the sensitivity of the Orbitrap's image current detection [41]. This calls to attention the tradeoff between the high mass accuracy and sensitivity between SRM and PRM experiments [24,33,41], PRMs are generally preferable in the screening mode of targeted proteomics experiments while SRM may be required for precise/absolute quantification of analytes across samples [41]. The stochastic nature of ion selection in a PRM setup may be responsible for occasional poor PTP results as well as the fact that we have used pooled samples.…”