Generative ß-hairpin design using a residue-based physicochemical property landscape.

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the ß-hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of ß hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial ß-hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

Computational Investigation of Substituent Effects on the Fluorescence Wavelengths of Oxyluciferin Analogs.

Oxyluciferin, which is the light emitter for firefly bioluminescence, has been subjected to extensive chemical modifications to tune its emission wavelength and quantum yield. However, the exact mechanisms for various electron-donating and withdrawing groups to perturb the photophysical properties of oxyluciferin analogs are still not fully understood. To elucidate the substituent effects on the fluorescence wavelength of oxyluciferin analogs, we applied the absolutely localized molecular orbitals (ALMO)-based frontier orbital analysis to assess various types of interactions (i.e. permanent electrostatics/exchange repulsion, polarization, occupied-occupied orbital mixing, virtual-virtual orbital mixing, and charge-transfer) between the oxyluciferin and substituent orbitals. We suggested two distinct mechanisms that can lead to red-shifted oxyluciferin emission wavelength, a design objective that can help increase the tissue penetration of bioluminescence emission. Within the first mechanism, an electron-donating group (such as an amino or dimethylamino group) can contribute its highest occupied molecular orbital (HOMO) to an out-of-phase combination with oxyluciferin's HOMO, thus raising the HOMO energy of the substituted analog and narrowing its HOMO-LUMO gap. Alternatively, an electron-withdrawing group (such as a nitro or cyano group) can participate in an in-phase virtual-virtual orbital mixing of fragment LUMOs, thus lowering the LUMO energy of the substituted analog. Such an ALMO-based frontier orbital analysis is expected to lead to intuitive principles for designing analogs of not only the oxyluciferin molecule, but also many other functional dyes.

Molecular Dynamics Reveals Altered Interactions between Belzutifan and HIF-2 with Natural Variant G323E or Proximal Phosphorylation at T324.

In patients with von-Hippel Lindau (VHL) disease, hypoxia-independent accumulation of HIF-2α leads to increased transcriptional activity of HIF-2α:ARNT that drives cancers such as renal cell carcinoma. Belzutifan, a recently FDA-approved drug, is designed to prevent the transcriptional activity of HIF-2α:ARNT, thereby overcoming the consequences of its unnatural accumulation in VHL-dependent cancers. Emerging evidence suggests that the naturally occurring variant G323E located in the HIF-2α drug binding pocket prevents inhibitory activity of belzutifan analogs, though the mechanism of inhibition remains unclear. Interestingly, proximal phosphorylation at neighboring T324, previously shown to regulate HIF-2 protein interactions, has also been proposed to affect HIF-2 drug binding. Here, we used molecular dynamics (MD) simulations to understand and compare the molecular-level effects of G323E and phospho-T324 (pT324) on the belzutifan bound-HIF-2α:ARNT complex. We find that both G323E and pT324 increase structural flexibility within the drug binding site and reduce the apparent binding affinity for belzutifan. Whereas the effects of G323E are concentrated in the binding pocket Fα helix within the HIF-2α PAS-B domain, pT324 decreased the belzutifan binding affinity and stabilized the HIF-2 heterodimer through an alternate mechanism involving polar interactions between the HIF-2α PAS-B and PAS-A domains. Further analysis via ensemble machine learning uncovered important and distinct interchain residue interactions modified by G323E and pT324. These findings reveal a molecular mechanism of G323E-induced drug resistance and suggest that pT324 may also affect the efficacy of HIF-2 drug binding interactions via allosteric effects.

Visualization of Electron Density Changes Along Chemical Reaction Pathways.

We propose a simple procedure for visualizing the electron density changes (EDC) during a chemical reaction, which is based on a mapping of rectangular grid points for a stationary structure into (distorted) positions around atoms of another stationary structure. Specifically, during a small step along the minimum energy pathway (MEP), the displacement of each grid point is obtained as a linear combination of the motion of all atoms, with the contribution from each atom scaled by the corresponding Hirshfeld weight. For several reactions (identity SN2, Claisen rearrangement, Diels-Alder reaction, [3+2] cycloaddition, and phenylethyl mercaptan attack on pericosine A), our EDC plots showed an expected reduction of electron densities around severed bonds (or those with the bond-order lowered), with the opposite observed for newly-formed or enhanced chemical bonds. The EDC plots were also shown for copper triflate catalyzed N2O fragmentation, where the N-O bond weakening initially occurred on a singlet surface, but continued on a triplet surface after reaching the minimum-energy crossing point (MECP) between the two potential energy surfaces.