Comparative analysis of nucleotide translocation through protein nanopores using steered molecular dynamics and an adaptive biasing force

Exploring ssDNA translocation through α-hemolysin using coarse-grained steered molecular dynamics

Protein nanopores have proven to be effective for single-molecule studies, particularly for single-stranded DNA (ssDNA) translocation. Previous experiments demonstrated their ability to distinguish differences in purine and pyrimidine bases and in the orientation of the ssDNA molecule inside nanopores. Unfortunately, the microscopic details of ssDNA translocation over experimental time scales, which are not accessible through all-atom molecular dynamics (MD), have yet to be examined. However, coarse-grained (CG) MD simulations enable systems to be simulated over longer characteristic times closer to experiments than all-atom MD. This paper studies ssDNA translocation through α-hemolysin nanopores exploiting steered MD using the MARTINI CG force field. The impacts of the sequence length, orientation inside the nanopore and DNA charges on translocation dynamics as well as the conformational dynamics of ssDNA during the translocation are explored. Our results highlight the efficacy of CG molecular dynamics in capturing the experimental properties of ssDNA translocation, including a wide distribution in translocation times per base. In particular, the phosphate charges of the DNA molecule are crucial in the translocation dynamics and impact the translocation rate. Additionally, the influence of the ssDNA molecule orientation on the translocation rate is explained by the conformational differences of ssDNA inside the nanopore during its translocation. Our study emphasizes the significance of obtaining sufficient statistics via CG MD, which can elucidate the great variety of translocation processes.

Selectivity and Ranking of Tight-Binding JAK-STAT Inhibitors Using Markovian Milestoning with Voronoi Tessellations

Janus kinases (JAK), a group of proteins in the nonreceptor tyrosine kinase (NRTKs) family, play a crucial role in growth, survival, and angiogenesis. They are activated by cytokines through the Janus kinase-signal transducer and activator of a transcription (JAK-STAT) signaling pathway. JAK-STAT signaling pathways have significant roles in the regulation of cell division, apoptosis, and immunity. Identification of the V617F mutation in the Janus homology 2 (JH2) domain of JAK2 leading to myeloproliferative disorders has stimulated great interest in the drug discovery community to develop JAK2-specific inhibitors. However, such inhibitors should be selective toward JAK2 over other JAKs and display an extended residence time. Recently, novel JAK2/STAT5 axis inhibitors (N-(1H-pyrazol-3-yl)pyrimidin-2-amino derivatives) have displayed extended residence times (hours or longer) on target and adequate selectivity excluding JAK3. To facilitate a deeper understanding of the kinase-inhibitor interactions and advance the development of such inhibitors, we utilize a multiscale Markovian milestoning with Voronoi tessellations (MMVT) approach within the Simulation-Enabled Estimation of Kinetic Rates v.2 (SEEKR2) program to rank order these inhibitors based on their kinetic properties and further explain the selectivity of JAK2 inhibitors over JAK3. Our approach investigates the kinetic and thermodynamic properties of JAK-inhibitor complexes in a user-friendly, fast, efficient, and accurate manner compared to other brute force and hybrid-enhanced sampling approaches.

Large Scale Study of Ligand-Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the "enhanced sampling" method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

Principles of Small-Molecule Transport through Synthetic Nanopores

Synthetic nanopores made from DNA replicate the key biological processes of transporting molecular cargo across lipid bilayers. Understanding transport across the confined lumen of the nanopores is of fundamental interest and of relevance to their rational design for biotechnological applications. Here we reveal the transport principles of organic molecules through DNA nanopores by synergistically combining experiments and computer simulations. Using a highly parallel nanostructured platform, we synchronously measure the kinetic flux across hundreds of individual pores to obtain rate constants. The single-channel transport kinetics are close to the theoretical maximum, while selectivity is determined by the interplay of cargo charge and size, the pores' sterics and electrostatics, and the composition of the surrounding lipid bilayer. The narrow distribution of transport rates implies a high structural homogeneity of DNA nanopores. The molecular passageway through the nanopore is elucidated via coarse-grained constant-velocity steered molecular dynamics simulations. The ensemble simulations pinpoint with high resolution and statistical validity the selectivity filter within the channel lumen and determine the energetic factors governing transport. Our findings on these synthetic pores' structure-function relationship will serve to guide their rational engineering to tailor transport selectivity for cell biological research, sensing, and drug delivery.

Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets

A fundamental problem in thermodynamics is the recovery of macroscopic equilibrated interaction energies from experimentally measured single-molecular interactions. The Jarzynski equality forms a theoretical basis in recovering the free energy difference between two states from exponentially averaged work performed to switch the states. In practice, the exponentially averaged work value is estimated as the mean of finite samples. Numerical simulations have shown that samples having thousands of measurements are not large enough for the mean to converge when the fluctuation of external work is above 4 k_BT, which is easily observable in biomolecular interactions. We report the first example of a statistical gamma work distribution applied to single molecule pulling experiments. The Gibbs free energy of surface adsorption can be accurately evaluated even for a small sample size. The values obtained are comparable to those derived from multi-parametric surface plasmon resonance measurements and molecular dynamics simulations.

Measuring interaction energies from experimentally measured single-molecular interactions is challenging. Here, the authors report a gamma work distribution applied to single molecule pulling events for estimating peptide absorption free energy.

Increased Dissociation of Adamantanamines in Influenza A M2 S31N with Partial Block by Rimantadine

The ubiquitous mutation from serine (WT) to asparagine at residue 31 (S31N) in the influenza A M2 channel renders it insensitive to amantadine (AMT) and rimantadine (RMT) block, but it is unknown whether the inhibition results from weak binding or incomplete block. Two-electrode voltage clamp (TEVC) of transfected Xenopus oocytes revealed that the M2 S31N channel is essentially fully blocked by AMT at 10 mM, demonstrating that, albeit weak, AMT binding in a channel results in complete block of its proton current. In contrast, RMT achieves only a modest degree of block in the M2 S31N channel at 1 mM, with very little increase in block at 10 mM, indicating that the RMT binding site in the channel saturates with only modest block. From exponential curve fits to families of proton current wash-in and wash-out traces, the association rate constant (k₁) is somewhat decreased for both AMT and RMT in the S31N, but the dissociation rate constant (k₂) is dramatically increased compared with WT. The potentials of mean force (PMF) from adaptive biasing force (ABF) molecular dynamics simulations predict that rate constants should be exquisitely sensitive to the charge state of the His37 selectivity filter of M2. With one exception out of eight cases, predictions from the simulations with one and three charged side chains bracket the experimental rate constants, as expected for the acidic bath used in the TEVC assay. From simulations, the weak binding can be accounted for by changes in the potentials of mean force, but the partial block by RMT remains unexplained.

Ensemble-Based Steered Molecular Dynamics Predicts Relative Residence Time of A2A Receptor Binders

Drug-target residence time, the length of time for which a small molecule stays bound to its receptor target, has increasingly become a key property for optimization in drug discovery programs. However, its in silico prediction has proven difficult. Here we describe a method, using atomistic ensemble-based steered molecular dynamics (SMD), to observe the dissociation of ligands from their target G protein-coupled receptor in a time scale suitable for drug discovery. These dissociation simulations accurately, precisely, and reproducibly identify ligand-residue interactions and quantify the change in ligand energy values for both protein and water. The method has been applied to 17 ligands of the A_2A adenosine receptor, all with published experimental kinetic binding data. The residues that interact with the ligand as it dissociates are known experimentally to have an effect on binding affinities and residence times. There is a good correlation ( R² = 0.79) between the computationally calculated change in water-ligand interaction energy and experimentally determined residence time. Our results indicate that ensemble-based SMD is a rapid, novel, and accurate semi-empirical method for the determination of drug-target relative residence time.

H-NS uses an autoinhibitory conformational switch for environment-controlled gene silencing

As an environment-dependent pleiotropic gene regulator in Gram-negative bacteria, the H-NS protein is crucial for adaptation and toxicity control of human pathogens such as Salmonella, Vibrio cholerae or enterohaemorrhagic Escherichia coli. Changes in temperature affect the capacity of H-NS to form multimers that condense DNA and restrict gene expression. However, the molecular mechanism through which H-NS senses temperature and other physiochemical parameters remains unclear and controversial. Combining structural, biophysical and computational analyses, we show that human body temperature promotes unfolding of the central dimerization domain, breaking up H-NS multimers. This unfolding event enables an autoinhibitory compact H-NS conformation that blocks DNA binding. Our integrative approach provides the molecular basis for H-NS-mediated environment-sensing and may open new avenues for the control of pathogenic multi-drug resistant bacteria.

Molecular Dynamics Simulations of Conformational Conversions in Transformer Proteins

A relatively recently discovered class of proteins known as transformer proteins undergo large-scale conformational conversions that change their supersecondary structure. These structural transformations lead to different configurations that perform different functions. We describe computational methods using molecular dynamics simulations that allow the determination of the specific amino acids that facilitate the conformational transformations. These investigations provide guidance on the location and type of amino acid mutations that can either enhance or inhibit the structural transitions that allow transformer proteins to perform multiple functions.

Assessment of Conformational State Transitions of Class B GPCRs Using Molecular Dynamics

Class B G protein-coupled receptors (GPCRs) comprise a family of 15 peptide-binding members, which are crucial targets for endocrine, metabolic, and stress-related disorders. While their protein structures and dynamics remain largely unclear, computer modeling and simulations represent a promising means to help solve such puzzles. Herein, we present a basic introduction to the methodology of molecular dynamics (MD) simulations and two analytical methods to assess the conformational ensembles and transitions of Class B GPCRs, using our recent studies of the human pituitary adenylate cyclase activating polypeptide (PAC₁) receptor as an example. From long MD simulations, conformational ensembles with different roles in ligand binding and receptor activation are sampled to establish four states identified as either "open" or "closed" for the PAC₁ receptor. Next, the dynamical network can be applied to analyze the simulations and identify key features within each conformational ensemble, which help distinguish the ligand-bound states of the PAC₁ receptor from the ligand-free one. Further, the Markov State Model has emerged as a key approach to construct the transition network and connect the GPCR ensembles, providing detailed information for the transition pathways and kinetics. For the ligand-free PAC₁ receptor, the transitions within the closed states are near 10-30 times faster than the open-closed transitions, which is likely related to the activation mechanism of the receptor. Overall, long MD simulations and analyses are useful to assess conformational transitions for the Class B GPCRs and to gain mechanistic insight, which is difficult to obtain using other methods.

Theoretical rationalisation of the photophysics of a TICT excited state of cinnamoyl–coumarin derivatives in homogeneous and biological membrane models

Analysis of the potential energy barriers and structural dynamics of a new TICT-probe for monitoring biological environments.

Computational Studies of Molecular Permeation through Connexin26 Channels

A signal property of connexin channels is the ability to mediate selective diffusive movement of molecules through plasma membrane(s), but the energetics and determinants of molecular movement through these channels have yet to be understood. Different connexin channels have distinct molecular selectivities that cannot be explained simply on the basis of size or charge of the permeants. To gain insight into the forces and interactions that underlie selective molecular permeation, we investigated the energetics of two uncharged derivatized sugars, one permeable and one impermeable, through a validated connexin26 (Cx26) channel structural model, using molecular dynamics and associated analytic tools. The system is a Cx26 channel equilibrated in explicit membrane/solvent, shown by Brownian dynamics to reproduce key conductance characteristics of the native channel. The results are consistent with the known difference in permeability to each molecule. The energetic barriers extend through most of the pore length, rather than being highly localized as in ion-specific channels. There is little evidence for binding within the pore. Force decomposition reveals how, for each tested molecule, interactions with water and the Cx26 protein vary over the length of the pore and reveals a significant contribution from hydrogen bonding and interaction with K(+). The flexibility of the pore width varies along its length, and the tested molecules have differential effects on pore width as they pass through. Potential sites of interaction within the pore are defined for each molecule. The results suggest that for the tested molecules, differences in hydrogen bonding and entropic factors arising from permeant flexibility substantially contribute to the energetics of permeation. This work highlights factors involved in selective molecular permeation that differ from those that define selectivity among atomic ions.

Influence of Chirality of Crizotinib on Its MTH1 Protein Inhibitory Activity: Insight from Molecular Dynamics Simulations and Binding Free Energy Calculations

As a promising target for the treatment of lung cancer, the MutT Homolog 1 (MTH1) protein can be inhibited by crizotinib. A recent work shows that the inhibitory potency of (S)-crizotinib against MTH1 is about 20 times over that of (R)-crizotinib. But the detailed molecular mechanism remains unclear. In this study, molecular dynamics (MD) simulations and free energy calculations were used to elucidate the mechanism about the effect of chirality of crizotinib on the inhibitory activity against MTH1. The binding free energy of (S)-crizotinib predicted by the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Adaptive biasing force (ABF) methodologies is much lower than that of (R)-crizotinib, which is consistent with the experimental data. The analysis of the individual energy terms suggests that the van der Waals interactions are important for distinguishing the binding of (S)-crizotinib and (R)-crizotinib. The binding free energy decomposition analysis illustrated that residues Tyr7, Phe27, Phe72 and Trp117 were important for the selective binding of (S)-crizotinib to MTH1. The adaptive biasing force (ABF) method was further employed to elucidate the unbinding process of (S)-crizotinib and (R)-crizotinib from the binding pocket of MTH1. ABF simulation results suggest that the reaction coordinates of the (S)-crizotinib from the binding pocket is different from (R)-crizotinib. The results from our study can reveal the details about the effect of chirality on the inhibition activity of crizotinib to MTH1 and provide valuable information for the design of more potent inhibitors.

Journey of poly-nucleotides through OmpF porin

OmpF is an abundant porin in many bacteria which attracts attention as a promising biological nanopore for DNA sequencing. We study the interactions of OmpF with pentameric poly-nucleotides (poly-Ns) in silico. The poly-N molecule is forced to translocate through the lumen of OmpF. Subsequently, the structural and dynamical effects of translocation steps on protein and poly-N molecules are explored in detail. The external loops of OmpF are introduced as the main region for discrimination of poly-Ns based on their organic bases. Structural network analyses of OmpF in the presence or absence of poly-Ns characterize special residues in the structural network of porin. These residues pave the way for engineering OmpF protein. The poly-N-specific pattern of OmpF's local conductance is detected in the current study. Computing the potential of mean force for translocation steps, we define the energetic barrier ahead of poly-N to move through OmpF's lumen. We suggest that fast translocation of the examined poly-N molecules through OmpF seems unattainable by small external driving forces. Our computational results suggest some abilities for OmpF porin like OmpF's potential for being used in poly-N sequencing.

The unbinding studies of vascular endothelial growth factor receptor-2 protein tyrosine kinase type II inhibitors

Vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase has two conformations, active and inactive conformations. Type II inhibitors bind to inactive conformation. It has two possible binding/unbinding paths. To explore the unbinding path of inhibitor 01-435 that was generated by fragment build in the binding pocket of VEGFR-2, molecular dynamics (MD) simulation was performed on the crystal structure of VEGFR-2 in complex with 01-435, then steered molecular dynamics (SMD) simulation was executed on the crystal structure of VEGFR-2 in complex with 01-435. Pull force, van der Waals and electrostatic interaction along the two paths were calculated by using SMD simulation. The SMD simulation results indicate that the more favorable path for inhibitor dissociation is along with the traditional ATP-channel rather than the allosteric-pocket-channel, which is mainly due to the less electrostatic interaction that the ligand suffers during dissociation process along the traditional ATP-channel.