biovia based 2d interaction maps  (Accelrys)

Journal: bioRxiv

Article Title: Deep Learning Structural Ensembles as Proxies for Protein Flexibility

doi: 10.64898/2026.05.16.725658

Figure Lengend Snippet: Ranksorted mean squared fluctuations (MSF) from NMR method and three deep learning structure prediction methods (AlphaFold3, AlphaFold2 and RosettaFold). A) Projections of ranksorted MSF onto protein structures for 2lah. Blue-White-Red color palette is used for the projections, where blue indicates low flexibility and red indicates high flexibility. B) 2D comparison of the experimental and the computed MSF for 2lah. Black line (with squares) is for the experimental data, blue line (with circles) is for AlphaFold3, orange line (with inverse triangles) is for AlphaFold2 and green line (with stars) is for RosettaFold. C) Cosine similarity of the experimental and the computed MSF for 70 proteins in the NMR dataset. AlphaFold3 bars are blue, AlphaFold2 bars are orange and RosettaFold bars are green. Averages of the cosine similarities over the entire dataset are also provided as horizontal lines for AlphaFold3 (blue dot-dashed line), AlphaFold2 (orange dashed line) and RosettaFold (green dotted line).

Article Snippet: An interactive 2D plot of the MSF is generated with Plotly Python library .

Techniques: Comparison

Journal: bioRxiv

Article Title: Deep Learning Structural Ensembles as Proxies for Protein Flexibility

doi: 10.64898/2026.05.16.725658

Figure Lengend Snippet: Ranksorted mean squared fluctuations (MSF) from dual conformations of X-Ray structures and three deep learning structure prediction methods (AlphaFold3, AlphaFold2 and RosettaFold). A) Projections of the ranksorted MSF onto protein structures for 3fweB and 4hzfA. Blue-White-Red color palette is used for the projections, where blue indicates low flexibility and red indicates high flexibility. B) 2D comparison of the experimental and the computed MSF for 3fweB and 4hzfA. Black line (with squares) is for the experimental data, blue line (with circles) is for AlphaFold3, orange line (with inverse triangles) is for AlphaFold2 and green line (with stars) is for RosettaFold. C) Cosine similarity of the experimental and the computed MSF for 43 proteins in the X-Ray dataset. AlphaFold3 bars are blue, AlphaFold2 bars are orange and RosettaFold bars are green. Averages of the cosine similarities over the entire dataset are also provided as horizontal lines for AlphaFold3 (blue dot-dashed line), AlphaFold2 (orange dashed line) and RosettaFold (green dotted line).

Article Snippet: An interactive 2D plot of the MSF is generated with Plotly Python library .

Techniques: Comparison

Journal: bioRxiv

Article Title: Deep Learning Structural Ensembles as Proxies for Protein Flexibility

doi: 10.64898/2026.05.16.725658

Figure Lengend Snippet: Ranksorted mean squared fluctuations (MSF) from all normal modes of cryo-EM structures and three deep learning structure prediction methods (AlphaFold3, AlphaFold2 and RosettaFold). A) Projections of the ranksorted MSF onto protein structures for 9yin. Blue-White-Red color palette is used for the projections, where blue indicates low flexibility and red indicates high flexibility. B) 2D comparison of the experimental and the computed MSF for 9yin. Black line (with squares) is for the experimental data, blue line (with circles) is for AlphaFold3, orange line (with inverse triangles) is for AlphaFold2 and green line (with stars) is for RosettaFold. C) Cosine similarity of the experimental and the computed MSF for 82 proteins in the cryo-EM dataset. AlphaFold3 bars are blue, AlphaFold2 bars are orange and RosettaFold bars are green. Averages of the cosine similarities over the entire dataset are also provided as horizontal lines for AlphaFold3 (blue dot-dashed line), AlphaFold2 (orange dashed line) and RosettaFold (green dotted line).

Article Snippet: An interactive 2D plot of the MSF is generated with Plotly Python library .

Techniques: Cryo-EM Sample Prep, Comparison

Journal: bioRxiv

Article Title: Deep Learning Structural Ensembles as Proxies for Protein Flexibility

doi: 10.64898/2026.05.16.725658

Figure Lengend Snippet: Ranksorted mean squared fluctuations (MSF) from molecular dynamics (MD) simulations and two deep learning structure prediction methods (AlphaFold3 and AlphaFold2). A) Projections of the ranksorted MSF onto protein structures for 6crk chain G. Blue-White-Red color palette is used for the projections, where blue indicates low flexibility and red indicates high flexibility. B) 2D comparison of the MD and the deep learning MSF for 6crk chain G. Blue (simulation 1), green (simulation 2) and orange (simulation 3) lines (with squares) are for the MD simulation data, black line (with circles) is for AlphaFold3, gray line (with inverse triangles) is for AlphaFold2. C) Cosine similarities of the first set of MD simulations and the deep learning ensemble MSF of 10 proteins in the MD dataset. D) Cosine similarities of the second set of MD simulations and the deep learning ensemble MSF of 10 proteins in the MD dataset. E) Cosine similarities of the third set of MD simulations and the deep learning ensemble MSF 10 proteins in the MD dataset. AlphaFold3 bars are black, AlphaFold2 bars are gray. Averages of the cosine similarities over the entire dataset are also provided as horizontal lines for AlphaFold3 (black dot-dashed line), AlphaFold2 (gray dashed line).

Article Snippet: An interactive 2D plot of the MSF is generated with Plotly Python library .

Techniques: Comparison

Journal: Journal of Computer-Aided Molecular Design

Article Title: Single nucleotide polymorphisms affecting galantamine binding to acetylcholinesterase in Alzheimer’s disease: a structural bioinformatics study

doi: 10.1007/s10822-026-00805-6

Figure Lengend Snippet: Representative 3D ( a , c ) and 2D ( b , d ) interaction maps of GNT bound to wild-type ( a , b ) and His447Gln mutant ( c , d ) AChE after 200 ns MD, generated with BIOVIA Discovery Studio. Protein surface rendering includes explicit hydrogens, and non-covalent contacts are coloured as conventional hydrogen bonds (green), carbon–hydrogen bonds (light green), and alkyl or π-alkyl interactions (purple and pink). Residue labels in these interaction diagrams follow the numbering in the analysed MD coordinate files; deposited PDB numbering is provided in Table for reference

Article Snippet: Fig. 6 Representative 3D ( a , c ) and 2D ( b , d ) interaction maps of GNT bound to wild-type ( a , b ) and His447Gln mutant ( c , d ) AChE after 200 ns MD, generated with BIOVIA Discovery Studio.

Techniques: Mutagenesis, Generated, Residue

Journal: Scientific Reports

Article Title: Thyme and cinnamon essential oils inhibit multidrug resistant Escherichia coli and Klebsiella pneumoniae and alter virulence transcripts

doi: 10.1038/s41598-026-38791-2

Figure Lengend Snippet: Representative docking poses and 2D interaction maps of cinnamaldehyde ( A ), carvacrol ( B ), eugenol ( C ), and thymol ( D ) within the FimH adhesin receptor (PDB: 7QUO). Upper panels show ligands as stick models positioned in the pocket surface; lower panels show 2D interaction maps with labeled contact residues. Visualizations were generated using BIOVIA Discovery Studio.

Article Snippet: Figures , , and presented the molecular docking poses of cinnamaldehyde, carvacrol, eugenol, and thymol in four targets, where each figure showed a 3D binding-pocket view (ligands in stick representation within the cavity surface) alongside 2D residue interaction maps generated in BIOVIA Discovery Studio (BIOVIA_DS2025Client).

Techniques: Labeling, Generated

Journal: Scientific Reports

Article Title: Thyme and cinnamon essential oils inhibit multidrug resistant Escherichia coli and Klebsiella pneumoniae and alter virulence transcripts

doi: 10.1038/s41598-026-38791-2

Figure Lengend Snippet: Representative docking poses and 2D interaction maps of carvacrol ( A ), cinnamaldehyde ( B ), eugenol ( C ), and thymol ( D ) within LuxS (PDB: 5V2W). Upper panels show 3D pocket placement; lower panels show residue-level interaction maps. Visualizations were generated using BIOVIA Discovery Studio.

Article Snippet: Figures , , and presented the molecular docking poses of cinnamaldehyde, carvacrol, eugenol, and thymol in four targets, where each figure showed a 3D binding-pocket view (ligands in stick representation within the cavity surface) alongside 2D residue interaction maps generated in BIOVIA Discovery Studio (BIOVIA_DS2025Client).

Techniques: Residue, Generated

Journal: Scientific Reports

Article Title: Thyme and cinnamon essential oils inhibit multidrug resistant Escherichia coli and Klebsiella pneumoniae and alter virulence transcripts

doi: 10.1038/s41598-026-38791-2

Figure Lengend Snippet: Predicted docking poses of four phytochemicals—carvacrol ( A ), cinnamaldehyde ( B ), eugenol ( C ), and thymol ( D )—within the MrkA pocket (PDB ID: 9HW9). For each ligand, the upper panel shows the 3D binding pose (protein in cartoon with pocket surface; ligand as sticks), and the lower panel shows the corresponding 2D interaction map highlighting nearby residues. Across complexes, ligands occupy a similar predominantly hydrophobic/aromatic region, with recurring contacts including Trp78, Val76/Val109/Val149, Leu108/Leu110, Ile122, Tyr147/Tyr148, and polar-edge residues such as Ser111/Thr112 and Lys131/Lys133.

Article Snippet: Figures , , and presented the molecular docking poses of cinnamaldehyde, carvacrol, eugenol, and thymol in four targets, where each figure showed a 3D binding-pocket view (ligands in stick representation within the cavity surface) alongside 2D residue interaction maps generated in BIOVIA Discovery Studio (BIOVIA_DS2025Client).

Techniques: Binding Assay

Journal: Scientific Reports

Article Title: Thyme and cinnamon essential oils inhibit multidrug resistant Escherichia coli and Klebsiella pneumoniae and alter virulence transcripts

doi: 10.1038/s41598-026-38791-2

Figure Lengend Snippet: Representative docking poses and 2D interaction maps of carvacrol ( A ), cinnamaldehyde ( B ), eugenol ( C ), and thymol ( D ) within OmpA-short (PDB: 9FZC). Upper panels show ligand placement in the predicted pocket; lower panels show residue-level interaction maps. Visualizations were generated using BIOVIA Discovery Studio.

Article Snippet: Figures , , and presented the molecular docking poses of cinnamaldehyde, carvacrol, eugenol, and thymol in four targets, where each figure showed a 3D binding-pocket view (ligands in stick representation within the cavity surface) alongside 2D residue interaction maps generated in BIOVIA Discovery Studio (BIOVIA_DS2025Client).

Techniques: Residue, Generated