Transition state structure invariance to model system size and calculation levels: a QM/MM study of the carboxylation step catalyzed by Rubisco

The present study elucidates structural features related to the molecular mechanism in the carboxylation step of the reaction catalyzed by Rubisco. Starting from the initial X-ray Protein Data Bank structure of a Rubisco monomer, the reactive subsystem in vacuo is subjected to quantum chemical semiempirical and ab initio studies, while the effects of the protein environments are included by means of a hybrid quantum mechanical/molecular mechanical (QM/MM) approach. The QM/MM is used to characterize the transition structure for carboxylation inside the protein. The calculations were made with the AM1/CHARMM/GRACE scheme. Comparisons between the in vacuo and in situ transition structures show remarkable invariance with respect to geometric parameters, index and transition vector amplitudes. The transition state couples the carbon dioxide attack to the C2 center of the substrate in its dienol form with a simultaneous intramolecular hydrogen transfer from the C2 atom to the hydroxyl group linked to the C3 center. This study suggests that carboxylation may be simultaneously coupled to the activation of the C3 center in the enzyme. Received: 24 March 1998 / Accepted: 3 September 1998 / Published online: 10 December 1998     

Transition-state structures for describing the enzyme-catalyzed mechanisms of rubisco

The carboxylation and oxygenation processes of a model substrate, 3,4-dihydroxy-2-pentanone, have been theoreticaly characterized as a set of steps, mimicking the corresponding reactions of D-ribulose-1,5-bisphosphate catalyzed by rubisco. A theoretical characterization is carried out of transition-state structures and possible molecular intermediates represented as saddle points of index 1 and minimum energy structures, respectively. The quantum chemical characterization, at the HF/3-21G calculation level, of these stationary points is used to rationalize and to discuss both catalyzed sequences. The reported set of these stationary points maps out most experimental aspects of the reaction pathways for the real system. Received: 24 March 1998 / Accepted: 3 September 1998 / Published online: 10 December 1998     

Heteronuclear diatomic transition-metal cluster ions in the gas phase: Reactivity and thermochemistry of AgFe+

The gas-phase chemistry of AgFe⁺ was studied by using Fourier transform ion cyclotron resonance mass spectrometry. AgFe⁺ is unreactive with alkanes but reacts with cyclic and linear (C4–C8) alkenes. The primary reactions are dominated by dehydrogenation and condensation. In addition, cluster splitting is observed in the reaction of AgFe⁺ with benzene. Secondary reactions generally involve cluster splitting with the loss of Ag, although AgFeC₅H ₆ ⁺ is observed to dehydrogenate cyclopentene to yield AgFeC₁₀H ₁₂ ⁺ . Ion-molecule reactions, collision-induced dissociation, and photodissociation experiments were used to determine the bond energiesD°(Fe⁺–Ag)=53±7 kcal/mol andD°(Ag⁺–Fe)=46±7 kcal/mol. These values in turn were used to calculateH _f (AgFe⁺)=296±7 kcal/mol andIP(AgFe)=6.5±0.3 eV. Related chemical and physical properties of CuFe⁺ are presented for comparison.     

Virtual Screening with Gnina 1.0

Virtual screening—predicting which compounds within a specified compound library bind to a target molecule, typically a protein—is a fundamental task in the field of drug discovery. Doing virtual screening well provides tangible practical benefits, including reduced drug development costs, faster time to therapeutic viability, and fewer unforeseen side effects. As with most applied computational tasks, the algorithms currently used to perform virtual screening feature inherent tradeoffs between speed and accuracy. Furthermore, even theoretically rigorous, computationally intensive methods may fail to account for important effects relevant to whether a given compound will ultimately be usable as a drug. Here we investigate the virtual screening performance of the recently released Gnina molecular docking software, which uses deep convolutional networks to score protein-ligand structures. We find, on average, that Gnina outperforms conventional empirical scoring. The default scoring in Gnina outperforms the empirical AutoDock Vina scoring function on 89 of the 117 targets of the DUD-E and LIT-PCBA virtual screening benchmarks with a median 1% early enrichment factor that is more than twice that of Vina. However, we also find that issues of bias linger in these sets, even when not used directly to train models, and this bias obfuscates to what extent machine learning models are achieving their performance through a sophisticated interpretation of molecular interactions versus fitting to non-informative simplistic property distributions.     

The Moving-Frame Method for the Iterated-Integrals Signature: Orthogonal Invariants

Geometric, robust-to-noise features of curves in Euclidean space are of great interest for various applications such as machine learning and image analysis. We apply Fels–Olver’s moving-frame method (for geometric features) paired with the log-signature transform (for robust features) to construct a set of integral invariants under rigid motions for curves in \({\mathbb {R}}^d\) from the iterated-integrals signature. In particular, we show that one can algorithmically construct a set of invariants that characterize the equivalence class of the truncated iterated-integrals signature under orthogonal transformations, which yields a characterization of a curve in \({\mathbb {R}}^d\) under rigid motions (and tree-like extensions) and an explicit method to compare curves up to these transformations.

     

X-ray studies on phospholipid bilayers. VI. Comparative hydration effects on oriented films

Oriented films of three diacylphosphatidylethanolamines containing 12, 14 and 16 methylene groups in their hydrocarbon chains and one 14 carbon chain lecithin were studied by X-ray fiber diffraction. Their molecular conformations, packing arrangement, crystallographic and physico-chemical parameters as a function of hydration were determined. Basically the four phospholipids exhibit a common bilayer structure. However, they also present some interesting differences which might be relevant to their biological functions.