An Antibody-Drug Conjugate for Multiple Myeloma Prepared by Multi-Arm Linkers

First-line treatment of multiple myeloma, a prevalent blood cancer lacking a cure, using anti-CD38 daratumumab antibody and lenalidomide is often inadequate due to relapse and severe side effects. To enhance drug safety and efficacy, an antibody-drug conjugate, TE-1146, comprising six lenalidomide drug molecules site-specifically conjugated to a reconfigured daratumumab to deliver cytotoxic lenalidomide to tumor cells is developed. TE-1146 is prepared using the HighDAR platform, which employs i) a maleimide-containing "multi-arm linker" to conjugate multiple drug molecules creating a drug bundle, and ii) a designed peptide with a Zn2+-binding cysteine at the C-termini of a reconfigured daratumumab for site-specific drug bundle conjugation. It is shown that TE-1146 remains intact and effectively enters CD38-expressing tumor cells, releasing lenalidomide, leading to enhanced cell-killing effects compared to lenalidomide/daratumumab alone or their combination. This reveals the remarkable potency of lenalidomide once internalized by myeloma cells. TE-1146 precisely delivers lenalidomide to target CD38-overexpressing tumor cells. In contrast, lenalidomide without daratumumab cannot easily enter cells, whereas daratumumab without lenalidomide relies on Fc-dependent effector functions to kill tumor cells.

Experimental and Computational Insight into the Mechanism of NO Binding to Ferric Microperoxidase. The Likely Role of Tautomerization to Account for the pH Dependence

According to the current paradigm, the metal-hydroxo bond in a six-coordinate porphyrin complex is believed to be significantly less reactive in ligand substitution than the analogous metal-aqua bond, due to a much higher strength of the former bond. Here, we report kinetic studies for nitric oxide (NO) binding to a heme-protein model, acetylated microperoxidase-11 (AcMP-11), that challenge this paradigm. In the studied pH range 7.4-12.6, ferric AcMP-11 exists in three acid-base forms, assigned in the literature as [(AcMP-11)Fe^III(H₂O)(HisH)] (1), [(AcMP-11)Fe^III(OH)(HisH)] (2), and [(AcMP-11)Fe^III(OH)(His^-)] (3). From the pH dependence of the second-order rate constant for NO binding (k_on), we determined individual rate constants characterizing forms 1-3, revealing only a ca. 10-fold decrease in the NO binding rate on going from 1 (k_on⁽¹⁾ = 3.8 × 10⁶ M^-1 s^-1) to 2 (k_on⁽²⁾ = 4.0 × 10⁵ M^-1 s^-1) and the inertness of 3. These findings lead to the abandonment of the dissociatively activated mechanism, in which the reaction rate can be directly correlated with the Fe-OH bond energy, as the mechanistic explanation for the process with regard to 2. The reactivity of 2 is accounted for through the existence of a tautomeric equilibrium between the major [(AcMP-11)Fe^III(OH)(HisH)] (2a) and minor [(AcMP-11)Fe^III(H₂O)(His^-)] (2b) species, of which the second one is assigned as the NO binding target due to its labile Fe-OH₂ bond. The proposed mechanism is further substantiated by quantum-chemical calculations, which confirmed both the significant labilization of the Fe-OH₂ bond in the [(AcMP-11)Fe^III(H₂O)(His^-)] tautomer and the feasibility of the tautomer formation, especially after introducing empirical corrections to the computed relative acidities of the H₂O and HisH ligands based on the experimental pK_a values. It is shown that the "effective lability" of the axial ligand (OH^-/H₂O) in 2 may be comparable to the lability of the H₂O ligand in 1.

Automatically Constructed Neural Network Potentials for Molecular Dynamics Simulation of Zinc Proteins

The development of accurate and efficient potential energy functions for the molecular dynamics simulation of metalloproteins has long been a great challenge for the theoretical chemistry community. An artificial neural network provides the possibility to develop potential energy functions with both the efficiency of the classical force fields and the accuracy of the quantum chemical methods. In this work, neural network potentials were automatically constructed by using the ESOINN-DP method for typical zinc proteins. For the four most common zinc coordination modes in proteins, the potential energy, atomic forces, and atomic charges predicted by neural network models show great agreement with quantum mechanics calculations and the neural network potential can maintain the coordination geometry correctly. In addition, MD simulation and energy optimization with the neural network potential can be readily used for structural refinement. The neural network potential is not limited by the function form and complex parameterization process, and important quantum effects such as polarization and charge transfer can be accurately considered. The algorithm proposed in this work can also be directly applied to proteins containing other metal ions.

Metal Affinity/Selectivity of Monophosphate-Containing Signaling/Lipid Molecules

Monophosphate, an essential component of nucleic acids, as well as cell membranes and signaling molecules, is often bound to metal cations. Despite the biological importance of monophosphate-containing cell-signaling or lipid molecules, their propensity to bind the two most abundant cellular dications, Mg²⁺ and Ca²⁺, in a particular mode (inner/outer shell, mono/bidentate) is not well understood. Whether they prefer binding to Mg²⁺ than to Ca²⁺ and if they can outcompete the carboxylates of excitatory Asp/Glu and inhibitory gamma-aminobutyric acid (GABA) neurotransmitters in binding to Mg²⁺/Ca²⁺ remain unclear. To address these questions, we modeled cyclic adenosine/guanosine monophosphate (cAMP/cGMP), nucleoside 2',3'-cyclic phosphate, phosphatidylinositol (PI), phosphatidylserine (PS), and phosphatidylethanolamine (PEA) and determined their most stable metal-binding modes, including those of Asp/Glu and GABA, as well as their selectivity for Mg²⁺/Ca²⁺ using density functional theory combined with the polarizable continuum model. The results obtained, which are consistent with the available experimental findings, reveal that the structurally and functionally diverse monophosphate-containing ligands studied prefer monodentate coordination of Mg²⁺ because of the greater strain encountered upon bidentate coordination, whereas the larger Ca²⁺ imposes less strain upon bidentate binding and has reduced/no preference for monodentate coordination. We further show that in a low-dielectric environment, negatively charged monophosphate-containing ligands favor the better charge-accepting dication, that is, Mg²⁺ rather than Ca²⁺. By promoting Mg²⁺ over Ca²⁺ binding, signaling monophosphates (cAMP/cGMP) do not entrap cellular Ca²⁺ and interfere with signal transduction processes employing Ca²⁺ as a second messenger. In regions with high glutamate cytoplasmic concentration, glutamate may sequester Mg²⁺ bound to isolated five-/six-membered ring phosphates, PI, or neutral PEA, but not anionic phospholipids constituting the inner leaflet of the cell membrane.

How enzymes harness highly unfavorable proton transfer reactions

Acid-base reactions that are exceedingly unfavorable under standard conditions can be catalytically important at enzyme active sites. For example, in triose phosphate isomerase, a glutamate side chain (nominal pK_a ≈ 4 in solution) can in fact deprotonate a CH group that is vicinal to a carbonyl (pK_a ≈ 18 in solution). This is true because of three distinct interactions: (a) ground state pK_a shifts due to environment polarity and electrostatics; (b) dramatic increases in effective molarity due to optimization of proximity and orientation; and (c) transition state pK_a shifts due to binding interactions and the formation of strong low barrier hydrogen bonds. In this report, we review the literature showing that the sum of these three effects supplies more than enough free energy to push forward proton transfer reactions that under standard conditions are exceedingly nonspontaneous and slow.

Accurate and rapid prediction of pKa of transition metal complexes: semiempirical quantum chemistry with a data-augmented approach

Data-augmented high-throughput QM approach to compute pK_a of transition metal hydride complexes with hDFT accuracy and low cost.

How the Local Environment of Functional Sites Regulates Protein Function

Proteins form complex biological machineries whose functions in the cell are highly regulated at both the cellular and molecular levels. Cellular regulation of protein functions involves differential gene expressions, post-translation modifications, and signaling cascades. Molecular regulation, on the other hand, involves tuning an optimal local protein environment for the functional site. Precisely how a protein achieves such an optimal environment around a given functional site is not well understood. Herein, by surveying the literature, we first summarize the various reported strategies used by certain proteins to ensure their correct functioning. We then formulate three key physicochemical factors for regulating a protein's functional site, namely, (i) its immediate interactions, (ii) its solvent accessibility, and (iii) its conformational flexibility. We illustrate how these factors are applied to regulate the functions of free/metal-bound Cys and Zn sites in proteins.

Factors governing when a metal-bound water is deprotonated in proteins

We evaluate the extent to which the pK_w depends on the type, number, and metal-binding mode of the first-shell ligands, the metal–ligand bond distances, first-shell⋯second-shell H-bonding interactions, and the protein environment.