With Lasergene 16, DNASTAR has introduced an all-new protein design tool that enables researchers to identify residues that influence protein fold stability, by introducing specific variants to the wild-type structure or by scanning for hot-spot residues. Protein design simulations take seconds to complete – allowing researchers to perform high-throughput scanning of protein variations to support their downstream analysis and experimentation. Findings from the protein design workflow can also be used to guide PCR based site-directed mutagenesis using the Lasergene Molecular Biology software. By integrating structure and sequence-based analysis, Lasergene users can expect to save days of time on mutagenesis experiments. 

NovaFold, part of Lasergene Protein and powered by the award-winning I-TASSER algorithm for protein structure prediction, now further enhances the quality of its world-leading structure predictions. A new structure-refinement protocol improves bond geometries, removes atomic clashes, and creates energetically minimized structure models. These improvements amount to more accurate structure models...

Lasergene 16 also comes with important usability updates that make it easier than ever for researchers to access the software pipeline they need for their specific sequence assembly and analysis workflows - from cloning and primer design to genome assembly and protein modeling. Additionally, the new release includes improved online search functionality for NCBI’s BLAST and Entrez databases, including enhanced results analysis, more intelligent searches, and advanced filters, allowing them to quickly locate and add relevant sequences to their projects. 

DNASTAR spokesperson, Katie Maxfield, commented, “Lasergene 16 bridges the gap between protein sequence and structure, enabling a deeper understanding of macromolecular structure and function for molecular biologists and structural biologists alike. Additionally, with the significant improvements we’ve made to the I-TASSER implementation within NovaFold, protein structure prediction is now more accurate than ever. We are pleased to introduce these important improvements to our users, and we look forward to continuing to deliver the most accurate results and comprehensive analysis in our software. ” 

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