SDPMOD: an automated comparative modeling server for small disulfide-bonded proteins.

Area of Science:

• Biochemistry
• Structural Biology
• Drug Discovery

Background:

• Small disulfide-bonded proteins (SDPs) are a promising source for novel therapeutic agents.
• The development of drugs from SDPs necessitates accurate three-dimensional structural information.
• Currently, structural data is available for only a limited number of these important proteins.

Purpose of the Study:

• To address the scarcity of structural information for SDPs.
• To provide a freely accessible automated comparative modeling service for researchers.
• To facilitate drug design and development by enabling protein structure prediction.

Main Methods:

• Development of SDPMOD, a web-based automated comparative modeling service.
• Implementation of manual and semi-automated modes for template selection by expert users.
• Inclusion of target-template alignment editing for advanced customization.
• Integration of PROCHECK for stereochemical quality evaluation of predicted models.

Main Results:

• SDPMOD provides a valuable resource for predicting the structures of SDPs.
• The service offers flexibility for expert users through manual and semi-automated template selection and alignment editing.
• Stereochemical quality of the generated models can be assessed using integrated tools.

Conclusions:

• SDPMOD effectively bridges the gap in structural information for SDPs.
• The service empowers researchers to model protein structures, accelerating drug discovery efforts.
• Freely accessible modeling tools like SDPMOD are crucial for advancing therapeutic development.