Energy penalties enhance flexible receptor docking in a model cavity

Protein flexibility remains a major challenge in library docking because of difficulties in sampling conformational ensembles with accurate probabilities. Here, we use the model cavity site of T4 lysozyme L99A to test flexible receptor docking with energy penalties from molecular dynamics (MD) simulations. Crystallography with larger and smaller ligands indicates that this cavity can adopt three major conformations: open, intermediate, and closed. Since smaller ligands typically bind better to the cavity site, we anticipate an energy penalty for the cavity opening. To estimate its magnitude, we calculate conformational preferences from MD simulations. We find that including a penalty term is essential for retrospective ligand enrichment; otherwise, high-energy states dominate the docking. We then prospectively docked a library of over 900,000 compounds for new molecules binding to each conformational state. Absent a penalty term, the open conformation dominated the docking results; inclusion of this term led to a balanced sampling of ligands against each state. High ranked molecules were experimentally tested by Tm upshift and X-ray crystallography. From 33 selected molecules, we identified 18 ligands and determined 13 crystal structures. Most interesting were those bound to the open cavity, where the buried site opens to bulk solvent. Here, highly unusual ligands for this cavity had been predicted, including large ligands with polar tails; these were confirmed both by binding and by crystallography. In docking, incorporating protein flexibility with thermodynamic weightings may thus access new ligand chemotypes. The MD approach to accessing and, crucially, weighting such alternative states may find general applicability.

Energy Penalties Enhance Flexible Receptor Docking in a Model Cavity

Protein flexibility remains a major challenge in library docking due to difficulties in sampling conformational ensembles with accurate probabilities. Here we use the model cavity site of T4 Lysozyme L99A to test flexible receptor docking with energy penalties from molecular dynamics (MD) simulations. Crystallography with larger and smaller ligands indicates that this cavity can adopt three major conformations, open, intermediate, and closed. Since smaller ligands typically bind better to the cavity site, we anticipate an energy penalty for cavity opening. To estimate its magnitude, we calculate conformational preferences from MD simulations. We find that including a penalty term is essential for retrospective ligand enrichment, otherwise high-energy states dominate the docking. We then prospectively docked a library of over 900,000 compounds for new molecules binding to each conformational state. Absent a penalty term, the open conformation dominated the docking results; inclusion of this term led to a balanced sampling of ligands against each state. High ranked molecules were experimentally tested by Tm-upshift and X-ray crystallography. From 33 selected molecules, we identified 18 new ligands and determined 13 crystal structures. Most interesting were those bound to the open cavity, where the buried site opens to bulk solvent. Here, highly unusual ligands for this cavity had been predicted, including large ligands with polar tails; these were confirmed both by binding and by crystallography. In docking, incorporating protein flexibility with thermodynamic weightings may thus access new ligand chemotypes. The MD approach to accessing and, crucially, weighting such alternative states may find general applicability.

Perspectives on High-Throughput Ligand/Protein Docking With Martini MD Simulations

Molecular docking is central to rational drug design. Current docking techniques suffer, however, from limitations in protein flexibility and solvation models and by the use of simplified scoring functions. All-atom molecular dynamics simulations, on the other hand, feature a realistic representation of protein flexibility and solvent, but require knowledge of the binding site. Recently we showed that coarse-grained molecular dynamics simulations, based on the most recent version of the Martini force field, can be used to predict protein/ligand binding sites and pathways, without requiring any a priori information, and offer a level of accuracy approaching all-atom simulations. Given the excellent computational efficiency of Martini, this opens the way to high-throughput drug screening based on dynamic docking pipelines. In this opinion article, we sketch the roadmap to achieve this goal.

Patterns in Protein Flexibility: A Comparison of NMR “Ensembles”, MD Trajectories, and Crystallographic B-Factors

Proteins are molecular machines requiring flexibility to function. Crystallographic B-factors and Molecular Dynamics (MD) simulations both provide insights into protein flexibility on an atomic scale. Nuclear Magnetic Resonance (NMR) lacks a universally accepted analog of the B-factor. However, a lack of convergence in atomic coordinates in an NMR-based structure calculation also suggests atomic mobility. This paper describes a pattern in the coordinate uncertainties of backbone heavy atoms in NMR-derived structural “ensembles” first noted in the development of FindCore2 (previously called Expanded FindCore: DA Snyder, J Grullon, YJ Huang, R Tejero, GT Montelione, Proteins: Structure, Function, and Bioinformatics 82 (S2), 219–230) and demonstrates that this pattern exists in coordinate variances across MD trajectories but not in crystallographic B-factors. This either suggests that MD trajectories and NMR “ensembles” capture motional behavior of peptide bond units not captured by B-factors or indicates a deficiency common to force fields used in both NMR and MD calculations.

D614G substitution at the hinge region enhances the stability of trimeric SARS-CoV-2 spike protein

Background Spike protein is a key player in the SARS-CoV-2 infection by mediating primary contact between the virus and host cell surface. In the current COVID-19 pandemic, a variant of SARS-CoV-2 having D614G substitution in the spike protein has become dominant world-wide. Initial characterization of the virus shows that the G614 variant is more infectious and has higher fitness than the ancestral (D614) variant. In this study, we analyzed the significance of the D614G substitution on the protein flexibility, inter-residue interaction energies and thermostability of the spike protein trimer. Results Using Gaussian network model-based normal mode analysis, we demonstrate that D614G substitution occurs at hinge region that facilitates domain-domain motions between receptor binding domain and S2 region of the spike protein. Further, in-silico mutagenesis and inter-residue energy calculations reveal that contacts involving D614 are energetically frustrated whereas contacts involving G614 are energetically favourable implying the substitution strengthens intra- as well as inter-protomers association. Upon glycine substitution, free energy difference (ΔΔG) is -2.6 kcal/mol for closed and − 2.0 kcal/mol for 1-RBD up conformation i.e., thermodynamic stability has increased. When we perform reverse mutation in the structures of spike protein having G614 substitution, we observe that the free energy difference is 6.6 kcal/mol and 6.3 kcal/mol for closed and 1-RBD up conformations respectively indicating lowered thermodynamic stability. Together, these observations suggest that D614G substitution could modulate the flexibility of spike protein and confer enhanced thermodynamic stability. Conclusion Our results on protein flexibility and energetic basis of enhanced stability hint that G614 likely increases the availability of functional form of spike trimer thereby associated to increased infectivity.

Enrichments of Ensemble Docking Strategy Based on the Bayesian Model

MotivationChallenges remained in structure-based drug discovery which include protein flexibility in binding site. Thus, concerning the flexibility of proteins, docking into an ensemble of rigid conformations (ensemble docking) have been proposed with incorporation into protein flexibility with expects that it could provide higher enrichments than rigid single receptor. Here we have developed the ensemble docking strategy by using Bayesian Model algorithms, and this method is validated by three proteins: BTK, JAK and PARP. The Bayesian Model was used to integrate independent docking runs of an ensemble of rigid crystal structures and MD simulations. ResultsThe structure of MD simulations outperforms the crystal structures in separating inhibitors from decoys in BTK and PARP. Further, the results demonstrated that the ensemble docking strategy has better performance than rigid single conformation.

Protein Flexibility Reduces Solvent-Mediated Friction Barriers of Ligand Binding to a Hydrophobic Surface Patch

Solvent fluctuations have been explored in detail for idealized and rigid hydrophobic model systems, but so far it has remained unclear how internal protein motions and their coupling to the...