flowchart TD
			step_Oligonucleotide_Modeling["Oligonucleotide Modeling"]
			style step_Oligonucleotide_Modeling stroke-width:2px    
			step_Structure_Building_and_Preparation("Structure Building and Preparation")
			step_Structure_and_interaction_analysis("Structure and interaction analysis")
			step_Do_you_work_with_oligonucleotides_as_ligands_or_targets{{"Do you work with oligonucleotides as ligands or targets?"}}
			step_Binding_site_identification("Binding site identification")
			step_Virtual_screening_for_nucleic_acid_receptors("Virtual screening for nucleic acid receptors")
			step_Lead_optimization_techniques_for_nucleic_acid_targets("Lead optimization techniques for nucleic acid targets")
			step_Docking_nucleic_acids_to_proteins("Docking nucleic acids to proteins")
			step_Conclusion_and_Next_Steps("Conclusion and Next Steps")
    
			step_Oligonucleotide_Modeling --> step_Structure_Building_and_Preparation
			step_Structure_Building_and_Preparation --> step_Structure_and_interaction_analysis
			step_Structure_and_interaction_analysis --> step_Do_you_work_with_oligonucleotides_as_ligands_or_targets
			step_Do_you_work_with_oligonucleotides_as_ligands_or_targets --> |"as target"| step_Binding_site_identification
			step_Do_you_work_with_oligonucleotides_as_ligands_or_targets --> |"as ligand"| step_Docking_nucleic_acids_to_proteins
			step_Binding_site_identification --> step_Virtual_screening_for_nucleic_acid_receptors
			step_Virtual_screening_for_nucleic_acid_receptors --> step_Lead_optimization_techniques_for_nucleic_acid_targets


			step_Lead_optimization_techniques_for_nucleic_acid_targets --> step_Conclusion_and_Next_Steps
			step_Docking_nucleic_acids_to_proteins --> step_Conclusion_and_Next_Steps

		classDef path_title stroke-width:2px,fill:#12122c,stroke:#12122c
		classDef decision_step stroke-width:2px,fill:#005aaa,stroke:#005aaa
		classDef simple_step stroke-width:2px,fill:#12122c,stroke:#12122c
		class step_Oligonucleotide_Modeling path_title
                class step_Structure_Building_and_Preparation,step_Structure_and_interaction_analysis,step_Binding_site_identification,step_Virtual_screening_for_nucleic_acid_receptors,step_Lead_optimization_techniques_for_nucleic_acid_targets,step_Docking_nucleic_acids_to_proteins,step_Conclusion_and_Next_Steps simple_step
		class step_Do_you_work_with_oligonucleotides_as_ligands_or_targets decision_step

Learning Path: Oligonucleotide Modeling

Nucleic acids have recently become both promising therapeutics and intriguing drug targets. Their flexibility and strongly-charged backbone can push computational approaches made for protein targets to their limits. This learning path provides an overview of Schrödinger tools applicable to nucleic acids.

Accurate Physics-Based Prediction of Binding Affinities of RNA- and DNA-Targeting Ligands The OPLS 4 force field is fully parametrized for nucleic acids (including charges, torsions, and sugar puckering). Also see this publication's supporting information for additional details.

Next step: Structure Building and Preparation

Structure Building and Preparation

Preparing Nucleic Acid Structures
Fix common issues in experimental or predicted structures
MM-GBSA residue scanning for mutating nucleic acids Call the backend from the command line as $SCHRODINGER/run -FROM psp mut_pred.py <jobname>.maegz -dna_muts_file dna_muts.txt -dist 5 -forcefield OPLS4 and visualize the results using the Residue Scanning Viewer panel in Maestro.

Next step: Structure and interaction analysis

Structure and interaction analysis

Understanding and Visualizing Target Flexibility While this tutorial uses a protein target, the methods it shows are also applicable to nucleic acids.
Introduction to All-Atom Molecular Dynamics Simulations with Desmond
While this tutorial uses a protein target, MD setup for nucleic acids works similarly. Adding salt and appropriate counterions is essential for nucleic acids.
Introduction to MD Trajectory Analysis with Desmond
Most standard Trajectory Player analyses work for RNA/DNA.
analyze_trajectory_ppi.py script can be used to analyze interactions for user-specified atom sets. Call as $SCHRODINGER/run analyze_trajectory_ppi.py <md_job>-out.cms <md_job_out>.csv 'nucleic_acids' 'not nucleic_acids'
trajectory_RNA_analysis script calculates all nucleic acid torsions, sugar puckering, phase and amplitude, and base pair interactions. It is currently not included in the Schrödinger software release, however it is available upon request.
Protein Interaction Analysis panel Compatible with interaction studies of nucleic acids with both protein or another nucleic acid.
Multiple Sequence Viewer
Works for standard nucleic acid residues. Non-standard residues are labeled N or X.

Next step: Do you work with nucleic acids as ligands or targets?

Decide: Do you work with nucleic acids as ligands or targets?

Computational strategies for discovering and optimizing RNA- and DNA-targeting molecules
This webinar provides a comprehensive overview of computational solutions for working with nucleic acid targets.

Binding site identification

Analyzing Binding Sites of Nucleic Acids with SiteMap The scoring function in SiteMap has been recalibrated for improved RNA support. See this publication for details.
Exploring Protein Binding Sites with Mixed-Solvent Molecular Dynamics MxMD works for nucleic acids, but has not been extensively validated.

Next step: Virtual screening for nucleic acid receptors

Virtual screening for nucleic acid receptors

The following receptor-based stages of the Schrödinger virtual screening pipeline have been augmented and validated for use on nucleic acid targets. Glide WS uses WaterMap, whose application to DNA/RNA systems is under active development at the moment.

Small Molecule – Oligonucleotide Docking with Glide
Glide contains a variant of its scoring function optimized for RNA receptors.
Enabling in-silico Hit Discovery Workflows Targeting RNA with Small Molecules Publication describing our work on validating virtual screening methods for nucleic acid targets, including the RNA-specific adjustments to SiteMap's and Glide's scoring functions.
Re-scoring Docked Ligands with MM-GBSA While this tutorial uses a protein target as example, Prime MM-GBSA can be applied to nucleic acids. There has been limited validation for the results.
Virtual Screening Learning Path for a general overview of methods usable in VS

Next step: Lead optimization techniques for nucleic acid targets

Lead optimization techniques for nucleic acid targets

Forming RNA – Ligand Interactions with Ligand Designer Pose and property based design of DNA/RNA-binding small molecules.
Accurate Physics-Based Prediction of Binding Affinities of RNA- and DNA-Targeting Ligands Publication containing the results of our retrospective validation of FEP+ on nucleic acid targets.

Next step: Conclusion and Next Steps

Docking nucleic acids to proteins

Docking with PIPER In standard mode, docking nucleic acids with proteins is possible but has limited validation.

Next step: Conclusion and Next Steps

Conclusion and Next Steps

This concludes the overview of Schrödinger tools and workflows which have been validated for use on or with nucleic acid targets. For more in-depth guidance on particular scientific workflows, consult our other learning resources.