Analysis and Modeling Tools for Protein Data

Lasergene Protein is a robust set of tools for protein sequence analysis, macromolecular visualization, and protein structure prediction and analysis. The foundation of Lasergene Protein is Protean 3D, which is used to explore macromolecular structure, motion, and function. Lasergene Protein can be used with our Nova Applications, for protein structure prediction and modeling.

Sequence and Structure Analysis Protein Modeling Benchmarks

Protein Sequence and Structure Analysis

Lasergene Protein includes Protean 3D, our application for protein sequence and protein structure analysis. Using the integrated views within the software, you can view macromolecular sequence, structure and prediction methods simultaneously. Sequences and structures can be annotated and exported to PDF, bitmap and PowerPoint formats.

Protein Sequence Analysis

Import protein structure or sequence files from GenBank and PDB

Analyze biophysical properties such as amphilicity, charge density, disorder, flexibility, hydropathy, and stability
Access to multiple methods for secondary structure prediction
Calculate surface probability and predict probable transmembrane regions
Perform amino acid composition analysis for selections or full proteins
Create and manage features and annotations
Translate or batch translate DNA sequences in SeqBuilder Pro

Export to PDF, bitmap and PowerPoint formats

Protein Structural Analysis

Import protein structure or sequence files
Download PDB files directly from the Protein Data Bank or import multi-model PDB files to view conformational changes.
Utilize integrated protein sequence analysis tools to highlight regions of interest on the protein structure
Introduce a sequence mutation and see the impact on the protein structure
Change the rendering, orientation and lighting on a structure
Browse and search over 300 animated and annotated macromolecular conformational changes calculated by the Yale Morph Server
Export movie files from protein structures and animations

Epitope Prediction

Predict B-cell epitopes and antigenic regions based on protein sequence data
Compare epitope predictions to other characteristics, such as surface probability
Create molecular and solvent accessible surfaces around your structure and view predicted epitopes relative to the protein surface
View confidence scores for predicted antigenic regions

Change appearance of predicted epitopes on the sequence and structure for optimized visualization

White Paper: B Cell Epitope Prediction

Precise Predictions of Linear B Cell Epitopes in Protean 3D

Structural Alignment

Align entire macromolecular structures or selected regions
Identify regions of similarity between two or more structures, independent of sequence similarity
View RMSD values for aligned regions
Visualize aligned structures in the Structure View

Export images of aligned structures

Molecular Motion Visualization

Browse and search over 300 animated and annotated macromolecular conformational changes calculated by the Yale Morph Server
Access to detailed information for each animation model, including links to molecule information in the PDB, CATH, and GO databases
Effortlessly slow and pause animation to interrogate protein models
Compare selected animations by overlaying models

Export molecular motion animations as QuickTime movies, AVI format, or animated GIF

SNP to Structure Analysis

Combine genomic sequencing and SNP analysis results with structure files from the PDB to model point mutations on the protein structure and assess the effect on protein stability.

Model SNPs of interest in Protean 3D and view the mutated amino acid side chains along the backbone
Use DFIRE energy calculations to predict whether the mutation is stabilizing or destabilizing to the protein structure
Apply solvent-accessible surfaces to further explore potential impact of mutation on protein stability and function
Analyze secondary structure characteristics to interrogate mutation’s effect on protein flexibility, amphiphilicity, charge density, hydropathy, and more

Note: The use of this workflow requires assembly with the Homo sapiens – Ensembl w/PDB genome template package.

Poster: SNP to Structure Workflow

Software for In Silico 3-D Protein Structure Predictions from DNA Sequence Variation Data

Protein Modeling

Our protein modeling tools generate highly accurate structural models of both proteins and protein-protein complexes that are unattainable through standard modeling methodologies. Our Nova Applications for protein structure prediction, antibody modeling, and protein-protein docking are available as optional, cloud-based applications when you purchase Lasergene Protein. We always include five Nova predictions when you buy, so that you can try our protein modeling capabilities for free. And our protein design tools are included free of charge with each academic, government and non-profit license.

Protein Structure Prediction with NovaFold

Predict accurate, 3D atomic models of proteins, using a combination of threading and ab initio protein structure prediction technologies
View protein models in the integrated Protean 3D views
Analyze protein prediction results using a variety of statistics, including TM-score, RMSD, C-score, and more
Predict protein-ligand binding sites and protein function

Align similar experimental structures with predicted NovaFold models

White Paper: NovaFold Accuracy

Accuracy of NovaFold Protein Folding Predictions

Access NovaFold on the Cloud

Antibody Modeling with NovaFold Antibody

Generate models of antibodies and antibody fragments (Fv, Fab, VH, sdAb)
Provide sequences for the light chain, the heavy chain, or both
Search a library of antibody frameworks, or provide custom templates
Automated annotation of CDR loops
View prediction results in Protean 3D for further structure analysis and rendering, and to export publication-quality graphics

Use with NovaDock to predict the structure and binding of antibody-antigen complexes

Access NovaFold Antibody on the Cloud

Protein Design

Scan for “hot-spots” using alanine and serine scanning to locate residues that are important for protein fold stability.
Create specific variants and see how they impact changes in energy.
Utilize the protein design tools in Protean 3D in combination with the virtual cloning and primer design capabilities in SeqBuilder Pro when performing PCR site-directed mutagenesis to see the structural impact of a mutation before designing your primers.

Case Study: Structure-Guided Molecular Cloning

DNASTAR Lasergene: Bridging the Gap Between Protein Sequence & Structure

Protein Docking with NovaDock

Predict protein docking interactions for two binding partners in NovaDock, which utilizes SwarmDock, one of the top three algorithms validated in the CAPRI blind docking experiment
Provide your ligand and receptor sequence files, and propose specific residue contacts between the binding partners, if desired
Evaluate energy score, cluster size, and number of ligand contacts for each model in a summarized view, and adjust the filtering scheme as desired

Open any model as a new structure document for further exploration and to export custom images for publication

Access NovaDock on the Cloud

NovaFold Protein Structure Prediction Runtimes

*NovaFold runtimes plotted by sequence length and colored by TM-score

NovaFold Benchmarks

DNASTAR NovaFold was evaluated by recreating the CASP11 competition, in which participants attempted to predict the structures for a given set of target sequences whose structures were previously unknown. In this benchmark test, NovaFold created predictions for these same target sequences which were then evaluated and scored based on the same metrics used in the CASP11 experiment.

A normalized measure of similarity between superimposed protein structures weighs close atom pairs between structures greater than more distant atom pairs. The range varies from 0 to 1, with a higher score indicating a better structural match.

Additional Notes:

NovaFold versions 12.3 and higher support sequences up to 2,000 residues in length.

To accurately simulate the conditions of the original competition, the benchmark was run using a library composed only of templates available prior to the end date of the CASP11 contest. In addition, targets leaked during the competition were removed from the benchmark library.

This benchmark test utilized the Cloud-based version of NovaFold and evaluated structure prediction only, not binding or function prediction.

Related Workflows

Molecular Biology

Genomics and Transcriptomics