The ability to predictively model various conformational states could accelerate selectivity inhibitor design. We present, to our best knowledge, the first predictive computational study that captured the four major types of kinase conformations starting from a single crystal structure without employing a target structure, mutation, or bias. Our data revealed, for the first time, how protonation state changes of key residues facilitate the conformational transitions, providing a direct support and explanation for a long-standing hypothesis regarding the protonation-dependent DFG flip. Our simulations also uncovered intermediate states, among which a unique inactive state, which can be tested in selective inhibitor design.
We present a computational tool to assess the nucleophilicities of lysines and cysteines to accelerate covalent drug design. The tool enabled us to discover that kinases in a rare inactive conformation can be covalently targeted at catalytic lysines. A new strategy for designing highly selective, lysine-targeted covalent kinase inhibitors was proposed to address the emergent drug resistance issue facing the cysteine-targeted strategy and help usher in the next generation covalent kinase inhibitor design.
Designing dynamic, stimuli-responsive, reconfigurable materials has growing interest in academia and industry. We report a computational study that provided novel, atomically-detailed physical insights for a pH-responsive, reconfigurable system. pKa gradients are known to be integral to protein structures and functions; our work presents the first theoretical demonstration of a pKa gradient for a highly dynamical polysaccharide system and how it allows a persistent but erasable gradient in the structural and mechanical properties of the hydrogel.
The role of water in protein-ligand has been intensely studied in recent years; however, how ligand protonation state change perturbs water has not been investigated. Here we use two homologues aspartyl proteases to illustrate how modeling protein-ligand binding while allowing ligand titration can further advance our understanding of the role of water in modulating the inhibitor selectivity for a particular target.
Nature is efficient; why would it require two protons if one is enough to do the job? This commentary article discusses a recent computational work in the context of our current understanding of how proton translocation mediates the active transport of drugs and substrates across the biological membrane.
We report the CPU implementation of the CpHMD method based on the GBNeck2 generalized Born (GB) implicit-solvent model in the pmemd engine of the Amber molecular dynamics package. Benchmark data based on 11 proteins are discussed. The related software is disseminated through Amber18.
Despite the importance, prediction of catalytic proton donors and nucleophiles has remained an unsolved problem. Here we tested three types of state-of-the-art computational methods to predict the pKa’s of buried and coupled carboxyl dyads in enzymes. We asked the question what makes a residue proton donor vs. nucleophile. Our study revealed a surprisingly simple trend, which is not apparent from crystal structures, empirical or traditional pKa calculations.
pH plays an important role in protein dynamics, stability, and folding; however, detailed mechanisms remain poorly understood. We carried out the first explicit-solvent protein folding simulation in a pH-dependent manner. Remarkably, the data revealed an unfolding intermediate bearing the signature of a dry molten globule, which is currently hypothesized as a universal intermediate in protein folding.
Top-down fabrication methods lack the capabilities to generate complex matrix architectures observed in biology. Here we show that temporally varying electric signals can cue a self-assembling polysaccharide to controllably form a hydrogel with complex internal patterns.
AcrB is the inner-membrane transporter of the AcrAB-TolC efflux complex in E. coli which confers resistance to antibiotics. Crystal structures have revealed three distinct states in the drug transport cycle; however, detailed mechanism remains unknown. Our study offered convincing support for the 1:1 drug:proton stoichiometry by depicting how proton release triggers the conformational transition, in agreement with the crystal structure.
Many pharmaceutical targets, such as aspartyl proteases and kinases, exhibit pH-dependent dynamics and functions. Accurate prediction of their binding free energies is challenging, and current computational studies neglect the effects of pH and changes in protonation states. We demonstrated a new protocol to improve the predictive power of current binding free energy calculations. The allosteric mechanism discovered here could lead to exciting opportunities in drug design.
Aminopolysaccharides can form complex structures with the properties highly dependent on environmental conditions; however, molecular details are not understood. We found that, contrary to common belief, chitosan chains have a high intrinsic flexibility and salt increases the flexibility by shifting the population from extended to bent glycosidic backbone conformation.
Targeting the aspartyl protease BACE1 with small-molecule inhibitors offers a promising route for treatment of Alzheimer's disease. However, developing inhibitors that can selectively target BACE1 in favor of other proteases, especially cathepsin D, has presented significant challenges. We reported the first computational study that characterizes the conformational dynamics of capthesin D and how it binds a BACE1 small-molecule inhibitor.
Proton-coupled transmembrane proteins play important roles in human health and diseases. We performed the first computer simulation that 1) directly describes the proton-coupled conformational activation of a transmembrane channel with fully atomic detail; 2) accurately determines the stepwise acid-base constants of a transmembrane channel; 3) provides the proton-coupled free energy of channel activation. The presented methodologies and major findings are generalizable for studies of proton-coupled channels and transporters.
Development of a pH stat to control solution pH in biomolecular simulations remains a outstanding goal. In recent years, the constant pH molecular dynamics methods have emerged; however, the accuracy and generality have been hampered by the use of implicit-solvent models or truncation-based electrostatic schemes. We reported the first implementation of the all-atom PME-based continuous constant pH method and benchmark results on a set of commonly used proteins.
NhaA is the principal sodium-proton antiporter in E. Coli., essential for cellular sodium and pH homeostasis. Abundant experimental and computational studies as well as two high-resolution crystal structures have been published; however, the pH-regulated mechanism at the molecular-level remains elusive. We reported the first computational study that offers an atomically-detailed view of the pH-dependent activation and key conformational events in the sodium-proton exchange cycle of NhaA.
Targeting the aspartyl protease BACE1 with small-molecule inhibitors offers a promising route for treatment of Alzheimer's disease. However, the intricate pH dependence of BACE1 function and inhibitor efficacy has posed major challenges. We reported the first simulation that uncovers the atomic details of pH-dependent binding of two drug candidates for BACE1. Our work demonstrated the drastic contrast in affinity of the two inhibitors is due to the subtle differences in the protonation behavior of the protein-inhibitor complex.