Exploring the pH- and Ligand-Dependent Flap Dynamics of Malarial Plasmepsin II

Malaria remains a global health threatover 400,000 deaths occurred in 2019. Plasmepsins are promising targets of antimalarial therapeutics; however, no inhibitors have reached the clinic. To fuel the progress, a detailed understanding of the pH- and ligand-dependent conformational dynamics of plasmepsins is needed. Here we present the continuous constant pH molecular dynamics study of the prototypical plasmepsin II and its complexed form with a substrate analogue. The simulations revealed that the catalytic dyads D34 and D214 are highly coupled in the apo protein and that the pepstatin binding enhances the difference in proton affinity, making D34 the general base and D214 the general acid. The simulations showed that the flap adopts an open state regardless of pH; however, upon pepstatin binding the flap can close or open depending on the protonation state of D214. These and other data are discussed and compared with the off-targets human cathepsin D and renin. This study lays the groundwork for a systematic investigation of pH- and ligand-modulated dynamics of the entire family of plasmepsins to help design more potent and selective inhibitors

pH-Dependent Population Shift Regulates BACE1 Activity and Inhibition

BACE1, a major therapeutic target for treatment of Alzheimer’s disease, functions within a narrow pH range. Despite tremendous effort and progress in the development of BACE1 inhibitors, details of the underlying pH-dependent regulatory mechanism remain unclear. Here we elucidate the pH-dependent conformational mechanism that regulates BACE1 activity using continuous constant-pH molecular dynamics (MD). The simulations reveal that BACE1 mainly occupies three conformational states and that the relative populations of the states shift according to pH. At intermediate pH, when the catalytic dyad is monoprotonated, a binding-competent state is highly populated, while at low and high pH a Tyr-inhibited state is dominant. Our data provide strong evidence supporting conformational selection as a major mechanism for substrate and peptide-inhibitor binding. These new insights, while consistent with experiment, greatly extend the knowledge of BACE1 and have implications for further optimization of inhibitors and understanding potential side effects of targeting BACE1. Finally, the work highlights the importance of properly modeling protonation states in MD simulations

Conformational Activation of a Transmembrane Proton Channel from Constant pH Molecular Dynamics

Proton-coupled transmembrane proteins play important roles in human health and diseases; however, detailed mechanisms are often elusive. Experimentally resolving proton positions and structural details is challenging, and conventional molecular dynamics simulations are performed with preassigned and fixed protonation states. To address this challenge, here we illustrate the use of the state-of-the-art continuous constant pH molecular dynamics (CpHMD) to directly describe the activation of the M2 channel of influenza virus, for which abundant experimental data are available. Starting from the closed crystal structure, simulation reveals a pH-dependent conformational switch to an activated state that resembles the open crystal structure. Importantly, simulation affords the free energy of channel opening coupled to the titration of a histidine tetrad, thereby providing a thermodynamic mechanism for M2 activation, that is consistent with NMR data and resolves the controversy with crystal structures obtained at different pH values. This work illustrates the utility of CpHMD in offering previously unattainable conformational details and thermodynamic information for proton-coupled transmembrane channels and transporters

How Electrostatic Coupling Enables Conformational Plasticity in a Tyrosine Kinase

Protein kinases are important cellular signaling molecules involved in cancer and a multitude of other diseases. It is well-known that inactive kinases display a remarkable conformational plasticity; however, the molecular mechanisms remain poorly understood. Conformational heterogeneity presents an opportunity but also a challenge in kinase drug discovery. The ability to predictively model various conformational states could accelerate selective inhibitor design. Here we performed a proton-coupled molecular dynamics study to explore the conformational landscape of a c-Src kinase. Starting from a completely inactive structure, the simulations captured all major types of conformational states without the use of a target structure, mutation, or bias. The simulations allowed us to test the experimental hypotheses regarding the mechanism of DFG flip, its coupling to the αC-helix movement, and the formation of regulatory spine. Perhaps the most significant finding is how key titratable residues, such as DFG-Asp, αC-Glu, and HRD-Asp, change protonation states dependent on the DFG, αC, and activation loop conformations. Our data offer direct evidence to support a long-standing hypothesis that protonation of Asp favors the DFG-out state and explain why DFG flip is also possible in simulations with deprotonated Asp. The simulations also revealed intermediate states, among which a unique DFG-out/α-C state formed as DFG-Asp is moved into a back pocket forming a salt bridge with catalytic Lys, which can be tested in selective inhibitor design. Our finding of how proton coupling enables the remarkable conformational plasticity may shift the paradigm of computational studies of kinases which assume fixed protonation states. Understanding proton-coupled conformational dynamics may hold a key to further innovation in kinase drug discovery

Mechanism of the Temperature-Dependent Self-Assembly and Polymorphism of Chitin

Chitin is the second most abundant natural biopolymer. Its crystalline structures have been extensively studied. However, the mechanism of chitin’s self-assembly is unknown. Here, we applied all-atom molecular dynamics to study chitin’s self-assembly process at different temperatures. Strikingly, at 278 K, an amorphous aggregate was formed, whereas at 300 K single-sheet and at 323 K both single-sheet and multisheet nanofibril regions were formed. The nanofibrils contain antiparallel, parallel, or mixed orientation chains, with antiparallel being slightly preferred, recapitulating chitin’s polymorphism observed in nature. The inverse temperature dependence is consistent with a recent experiment conducted in the aqueous KOH/urea solution. The analysis suggested that the multisheet nanofibrils are assembled by stacking the single nanofibril sheets, which are formed through two types of pathways in which hydrophobic collapse either precedes or is concomitant with the increasing number of interchain hydrogen bonds and solvent expulsion. Furthermore, the antiparallel and parallel chains are mediated by different interchain hydrogen bonds. The analysis also suggested that the inverse temperature dependence may be attributed to the hydrophobic effect reminiscent of the low critical solution temperature phase behavior. The present study provides a rich, atomic-level view of chitin’s polymorphic self-assembly process, paving the way for the rational design of chitin-derived novel materials

Generalized Born Based Continuous Constant pH Molecular Dynamics in Amber: Implementation, Benchmarking and Analysis

Solution pH plays an important role in structure and dynamics of biomolecular systems; however, pH effects cannot be accurately accounted for in conventional molecular dynamics simulations based on fixed protonation states. Continuous constant pH molecular dynamics (CpHMD) based on the λ-dynamics framework calculates protonation states on the fly during dynamical simulation at a specified pH condition. Here we report the CPU-based implementation of the CpHMD method based on the GBNeck2 generalized Born (GB) implicit-solvent model in the <i>pmemd</i> engine of the Amber molecular dynamics package. The performance of the method was tested using pH replica-exchange titration simulations of Asp, Glu and His side chains in 4 miniproteins and 7 enzymes with experimentally known p<i>K</i>_a’s, some of which are significantly shifted from the model values. The added computational cost due to CpHMD titration ranges from 11 to 33% for the data set and scales roughly linearly as the ratio between the titrable sites and number of solute atoms. Comparison of the experimental and calculated p<i>K</i>_a’s using 2 ns per replica sampling yielded a mean unsigned error of 0.70, a root-mean-squared error of 0.91, and a linear correlation coefficient of 0.79. Though this level of accuracy is similar to the GBSW-based CpHMD in CHARMM, in contrast to the latter, the current implementation was able to reproduce the experimental orders of the p<i>K</i>_a’s of the coupled carboxylic dyads. We quantified the sampling errors, which revealed that prolonged simulation is needed to converge p<i>K</i>_a’s of several titratable groups involved in salt-bridge-like interactions or deeply buried in the protein interior. Our benchmark data demonstrate that GBNeck2-CpHMD is an attractive tool for protein p<i>K</i>_a predictions

pH-Responsive Self-Assembly of Polysaccharide through a Rugged Energy Landscape

Self-assembling polysaccharides can form complex networks with structures and properties highly dependent on the sequence of triggering cues. Controlling the emergence of such networks provides an opportunity to create soft matter with unique features; however, it requires a detailed understanding of the subtle balance between the attractive and repulsive forces that drives the stimuli-induced self-assembly. Here we employ all-atom molecular dynamics simulations on the order of 100 ns to study the mechanisms of the pH-responsive gelation of the weakly basic aminopolysaccharide chitosan. We find that low pH induces a sharp transition from gel to soluble state, analogous to pH-dependent folding of proteins, while at neutral and high pH self-assembly occurs via a rugged energy landscape, reminiscent of RNA folding. A surprising role of salt is to lubricate the conformational search for the thermodynamically stable states. Although our simulations represent the early events in the self-assembly process of chitosan, which may take seconds or minutes to complete, the atomically detailed insights are consistent with recent experimental observations and provide a basis for understanding how environmental conditions modulate the structure and mechanical properties of the self-assembled polysaccharide systems. The ability to control structure and properties via modification of process conditions will aid in the technological efforts to create complex soft matter with applications ranging from bioelectronics to regenerative medicine

Conformational Dynamics of Two Natively Unfolded Fragment Peptides: Comparison of the AMBER and CHARMM Force Fields

Physics-based force fields are the backbone of molecular dynamics simulations. In recent years, significant progress has been made in the assessment and improvement of commonly used force fields for describing conformational dynamics of folded proteins. However, the accuracy for the unfolded states remains unclear. The latter is however important for detailed studies of protein folding pathways, conformational transitions involving unfolded states, and dynamics of intrinsically disordered proteins. In this work, we compare the three commonly used force fields, AMBER ff99SB-ILDN, CHARMM22/CMAP, and CHARMM36, for modeling the natively unfolded fragment peptides, NTL9(1–22) and NTL9(6–17), using explicit-solvent replica-exchange molecular dynamics simulations. All three simulations show that NTL9(6–17) is completely unstructured, while NTL9(1–22) transiently samples various β-hairpin states, reminiscent of the first β-hairpin in the structure of the intact NTL9 protein. The radius of gyration of the two peptides is force field independent but likely underestimated due to the current deficiency of additive force fields. Compared to the CHARMM force fields, ff99SB-ILDN gives slightly higher β-sheet propensity and more native-like residual structures for NTL9(1–22), which may be attributed to its known β preference. Surprisingly, only two sequence-local pairs of charged residues make appreciable ionic contacts in the simulations of NTL9(1–22), which are sampled slightly more by the CHARMM force fields. Taken together, these data suggest that the current CHARMM and AMBER force fields are globally in agreement in modeling the unfolded states corresponding to β-sheet in the folded structure, while differing in details such as the native-likeness of the residual structures and interactions

Quantum Descriptors for Predicting and Understanding the Structure–Activity Relationships of Michael Acceptor Warheads

Predictive modeling and understanding of chemical warhead reactivities have the potential to accelerate targeted covalent drug discovery. Recently, the carbanion formation free energies as well as other ground-state electronic properties from density functional theory (DFT) calculations have been proposed as predictors of glutathione reactivities of Michael acceptors; however, no clear consensus exists. By profiling the thiol-Michael reactions of a diverse set of singly- and doubly-activated olefins, including several model warheads related to afatinib, here we reexamined the question of whether low-cost electronic properties can be used as predictors of reaction barriers. The electronic properties related to the carbanion intermediate were found to be strong predictors, e.g., the change in the Cβ charge accompanying carbanion formation. The least expensive reactant-only properties, the electrophilicity index, and the Cβ charge also show strong rank correlations, suggesting their utility as quantum descriptors. A second objective of the work is to clarify the effect of the β-dimethylaminomethyl (DMAM) substitution, which is incorporated in the warheads of several FDA-approved covalent drugs. Our data suggest that the β-DMAM substitution is cationic at neutral pH in solution and promotes acrylamide’s intrinsic reactivity by enhancing the charge accumulation at Cα upon carbanion formation. In contrast, the inductive effect of the β-trimethylaminomethyl substitution is diminished due to steric hindrance. Together, these results reconcile the current views of the intrinsic reactivities of acrylamides and contribute to large-scale predictive modeling and an understanding of the structure–activity relationships of Michael acceptors for rational TCI design