Skip to main content
eScholarship
Open Access Publications from the University of California

Scholarly Works (7 results)

  • Thesis
  • Peer Reviewed
UC Riverside Electronic Theses and Dissertations (2022)

Drugs with desired kinetic properties have better efficacy. Non-covalent small molecule drugs can bind/unbind from their targets, which normally are macro biomolecules. Experimental methods can measure kinetics parameters at ensemble level, but they are unable to track the exact drug binding/unbinding pathways or explain whether drugs show different kinetic behaviors from different pathways. Investigation of ligand binding/unbinding pathways can deepen our understanding of ligand-protein molecular recognition. In this work, possible pathways of ligands-protein were sampled and post-analysis were conducted to investigate ligand binding kinetics (residence time), free energy landscape of ligand unbinding, and key factors that affect binding kinetics.

We are the first utilizing unbiased molecular dynamics to sample a pair of ligands, ritonavir and xk263, unbinding from HIV protease comprehensively, and classify the unbinding pathways based on the contacts between ligand-protein regions during dissociation. I identify key residues that form hydrogen bond with ligands that results in a meta-stable state for ligand-protein complex. Four distal mutation sites were observed forming interactions with ligands during unbinding, which explains why distal mutations in HIV protease affect drug binding affinity. Molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) was performed to calculate free energy landscape during ligands dissociation. HIV protease backbone conformations during ligands binding/unbinding were compared based on root-mean-square deviation (RMSD). High similarity of protein conformation during ritonavir binding/unbinding suggests that ritonavir follows conformation-selection mechanism during dissociation. In the contrast, low similarity of protein conformation during xk263 binding/unbinding suggests that xk263 follows induced-fit mechanism during dissociation.

Reconstruction of real free energy landscape of ritonavir-HIV protease dissociation was performed using Binding Kinetic Toolkit (BKiT) package. First two principal components (PC) of alpha carbon of protein along with heavy atoms in ritonavir were used as reaction coordinates to guide dissociation path on PC space. Energy barriers on free energy landscape under different unbinding pathways were explained by the molecular recognition of ritonavir-HIV protease. Furthermore, free energy landscape using ligand RMSD were computed, giving a much more accurate binding free energy and residence time approximation but in the lack of detailed ligand-protein interactions.

    Cover page: Investigation of Ligand-HIV Protease Dissociation: Pathway, Interactions, Mechanism, and Free Energy Landscape
    • Article
    • Peer Reviewed
    UC Riverside Previously Published Works (2022)
    Understanding non-covalent biomolecular recognition, which includes drug-protein bound states and their binding/unbinding processes, is of fundamental importance in chemistry, biology, and medicine. Fully revealing the factors that govern the binding/unbinding processes can further assist in designing drugs with desired binding kinetics. HIV protease (HIVp) plays an integral role in the HIV life cycle, so it is a prime target for drug therapy. HIVp has flexible flaps, and the binding pocket can be accessible by a ligand via various pathways. Comparing ligand association and dissociation pathways can help elucidate the ligand-protein interactions such as key residues directly involved in the interaction or specific protein conformations that determine the binding of a ligand under certain pathway(s). Here, we investigated the ligand unbinding process for a slow binder, ritonavir, and a fast binder, xk263, by using unbiased all-atom accelerated molecular dynamics (aMD) simulation with a re-seeding approach and an explicit solvent model. Using ritonavir-HIVp and xk263-HIVp ligand-protein systems as cases, we sampled multiple unbinding pathways for each ligand and observed that the two ligands preferred the same unbinding route. However, ritonavir required a greater HIVp motion to dissociate as compared with xk263, which can leave the binding pocket with little conformational change of HIVp. We also observed that ritonavir unbinding pathways involved residues which are associated with drug resistance and are distal from catalytic site. Analyzing HIVp conformations sampled during both ligand-protein binding and unbinding processes revealed significantly more overlapping HIVp conformations for ritonavir-HIVp rather than xk263-HIVp. However, many HIVp conformations are unique in xk263-HIVp unbinding processes. The findings are consistent with previous findings that xk263 prefers an induced-fit model for binding and unbinding, whereas ritonavir favors a conformation selection model. This study deepens our understanding of the dynamic process of ligand unbinding and provides insights into ligand-protein recognition mechanisms and drug discovery.
      Cover page: Ritonavir and xk263 Binding-Unbinding with HIV-1 Protease: Pathways, Energy and Comparison
      • Article
      • Peer Reviewed
      UC Riverside Previously Published Works (2021)
      Kinases catalyze the transfer of the γ-phosphate group from adenosine triphosphate (ATP) to their protein and small-molecule substrates, and this phosphorylation is a crucial element of multiple cell signaling pathways. Herein, we employed isotope-coded ATP acyl-phosphate probes, in conjunction with a multiple-reaction monitoring (MRM)-based targeted proteomic method for proteome-wide identifications of endogenous kinases that can bind to two N6-modified ATP derivatives, N6-methyl-ATP (N6-Me-ATP), and N6-furfuryl-ATP (a.k.a. kinetin triphosphate, KTP). We found that, among the ∼300 quantified kinases, 27 and 18 are candidate kinases that can bind to KTP and N6-Me-ATP, respectively. Additionally, GSK3α and GSK3β are among the kinases that can bind to both ATP analogues. Moreover, the in vitro biochemical assay showed that GSK3β could employ N6-Me-ATP but not KTP as the phosphate group donor to phosphorylate its substrate peptide. Molecular modeling studies provided insights into the differences between N6-Me-ATP and KTP in enabling the GSK3β-mediated phosphorylation. Together, our chemoproteomic approach led to the identification of endogenous kinases that can potentially be targeted by the two ATP analogues. The approach should be generally applicable for assessing endogenous kinases targeted by other ATP and purine analogues.
        Cover page: Proteome-Wide Characterizations of N 6‑Methyl-Adenosine Triphosphate- and N 6‑Furfuryl-Adenosine Triphosphate-Binding Capabilities of Kinases
        • Article
        • Peer Reviewed
        UC Riverside Previously Published Works (2019)
        We introduce a new heterogeneous CPU+GPU-enhanced DFTB approach for the routine and efficient simulation of large chemical and biological systems. Compared to homogeneous computing with conventional CPUs, heterogeneous computing approaches exhibit substantial performance with only a modest increase in power consumption, both of which are essential to upcoming exascale computing initiatives. We show that DFTB-based molecular dynamics is a natural candidate for heterogeneous computing, since the computational bottleneck in these simulations is the diagonalization of the Hamiltonian matrix, which is performed several times during a single molecular dynamics trajectory. To thoroughly test and understand the performance of our heterogeneous CPU+GPU approach, we examine a variety of algorithmic implementations, benchmarks of different hardware configurations, and applications of this methodology on several large chemical and biological systems. Finally, to demonstrate the capability of our implementation, we conclude with a large-scale DFTB MD simulation of explicitly solvated HIV protease (3974 atoms total) as a proof-of-concept example of an extremely large/complex system which, to the best of our knowledge, is the first time that an entire explicitly solvated protein has been treated at a quantum-based MD level of detail.
          Cover page: Heterogeneous CPU+GPU-Enabled Simulations for DFTB Molecular Dynamics of Large Chemical and Biological Systems.
          • Article
          • Peer Reviewed
          UC Riverside Previously Published Works (2022)
          Understanding ligand binding kinetics and thermodynamics, which involves investigating the free, transient, and final complex conformations, is important in fundamental studies and applications for chemical and biomedical systems. Examining the important but transient ligand-protein-bound conformations, in addition to experimentally determined structures, also provides a more accurate estimation for drug efficacy and selectivity. Moreover, obtaining the entire picture of the free energy landscape during ligand binding/unbinding processes is critical in understanding binding mechanisms. Here, we present a Binding Kinetics Toolkit (BKiT) that includes several utilities to analyze trajectories and compute a free energy and kinetics profile. BKiT uses principal component space to generate approximated unbinding or conformational transition coordinates for accurately describing and easily visualizing the molecular motions. We implemented a new partitioning approach to assign indexes along the approximated coordinates that can be used as milestones or microstates. The program can generate input files to run many short classical molecular dynamics simulations and uses milestoning theory to construct the free energy profile and estimate binding residence time. We first validated the method with a host-guest system, aspirin unbinding from β-cyclodextrin, and then applied the protocol to pyrazolourea compounds and cyclin-dependent kinase 8 and cyclin C complexes, a kinase system of pharmacological interest. Overall, our approaches yielded good agreement with published results and suggest ligand design strategies. The computed unbinding free energy landscape also provides a more complete picture of ligand-receptor binding barriers and stable local minima for deepening our understanding of molecular recognition. BKiT is easy to use and has extensible features for future expansion of utilities for postanalysis and calculations.
            Cover page: Binding Kinetics Toolkit for Analyzing Transient Molecular Conformations and Computing Free Energy Landscapes.
            • Article
            • Peer Reviewed
            UC Riverside Previously Published Works (2020)
            We report on a cyclic peptide that inhibits matrix metalloproteinase-2 (MMP2) activation with a low-nM-level potency. This inhibitor specifically binds to the D570-A583 epitope on proMMP2 and interferes with the protein-protein interaction (PPI) between proMMP2 and tissue inhibitor of metalloproteinases-2 (TIMP2), thereby preventing the TIMP2-assisted proMMP2 activation process. We developed this cyclic peptide inhibitor through an epitope-targeted library screening process and validated its binding to proMMP2. Using a human melanoma cell line, we demonstrated the cyclic peptide's ability to modulate cellular MMP2 activities and inhibit cell migration. These results provide the first successful example of targeting the PPI between proMMP2 and TIMP2, confirming the feasibility of an MMP2 inhibition strategy that has been sought after for 2 decades.
              Cover page: Inhibiting Matrix Metalloproteinase-2 Activation by Perturbing Protein-Protein Interactions Using a Cyclic Peptide.
              • Article
              • Peer Reviewed
              UC Riverside Previously Published Works (2024)
              Here, we present the second generation of our bicyclic peptide library (NTB), featuring a stereodiversified structure and a simplified construction strategy. We utilized a tandem ring-opening metathesis and ring-closing metathesis reaction (ROM-RCM) to cyclize the linear peptide library in a single step, representing the first reported instance of this reaction being applied to the preparation of macrocyclic peptides. Moreover, the resulting bicyclic peptide can be easily linearized for MS/MS sequencing with a one-step deallylation process. We employed this library to screen against the E363-R378 epitope of MYC and identified several MYC-targeting bicyclic peptides. Subsequent in vitro cell studies demonstrated that one candidate, NT-B2R, effectively suppressed MYC transcription activities and cell proliferation.
                Cover page: MYC-Targeting Inhibitors Generated from a Stereodiversified Bicyclic Peptide Library.
                Top