Target identification by structure-based computational approaches: Recent advances and perspectives.

Area of Science:

• Computational chemistry and drug discovery
• Bioinformatics and cheminformatics

Background:

• Traditional experimental methods for identifying drug targets can be time-consuming and resource-intensive.
• Computational techniques are increasingly vital in early-stage drug discovery for efficient target identification.
• In silico screening offers a promising alternative or complement to wet-lab approaches.

Purpose of the Study:

• To provide an overview of computational target identification techniques.
• To highlight recent advancements in structure-based computational approaches for target identification.
• To focus on Inverse Virtual Screening (IVS) and its applications in drug discovery.

Main Methods:

• Review of established target identification techniques.
• Detailed examination of structure-based computational methods.
• Analysis of Inverse Virtual Screening (IVS) methodologies and case studies.
• Exploration of computational approaches integrated with other techniques.

Main Results:

• Computational techniques, particularly in silico screening, are gaining prominence in drug discovery's target identification phase.
• Structure-based computational approaches, including IVS, show significant potential for identifying biological targets.
• IVS has demonstrated utility in recent drug discovery applications.

Conclusions:

• Computational methods, especially IVS, are crucial for accelerating early-stage drug discovery.
• Structure-based computational approaches offer efficient strategies for target identification.
• Future research should explore the synergistic use of IVS with other computational and experimental methods.