Free Energy Landscape Calculations Research Articles

Identification of Peregrin inhibitors-modulators by harnessing the computational prowess of molecular simulation and machine learning algorithms

Peregrin is marked as a potential drug target due to its pivotal role in the epigenetic maintenance of cellular metabolism. It is counted among those of the bromodomain-containing protein family. The protein binds to the acetylated lysine of N-terminus histone proteins of the nucleosomes. This bound form neutralizes the otherwise positively charged histone and, thus, crucially impacts the DNA replication mechanism. In several diseases like cancer, bone loss, and leukemia, this peregrin binding impacts the genes’ overexpression. Hence, the present study, computational screening of the bromodomain-specific inhibitors from a library of 5430 compounds retrieved from the ChemDiv database. Two different scoring functions based molecular docking studies have been employed for molecular interaction analysis. Followed by an artificial intelligence-based absolute binding affinity prediction has been confirmed through KDeep, which follows a machine learning step to obtain a precise binding energy score for the set of best compounds in the screening process. The resultant compounds were then screened for pharmacokinetics and drug-likeliness properties. Using molecular dynamics (MD) simulation analysis, the dynamic behavior of the four suggested compounds and Peregrin has been investigated for a 100 ns period. Identified compounds are found to be sufficiently effective in holding their strong interaction affinity toward Peregrin for an adequate time span, and structural integrity is also found to be comparable with the standard compound considered in the study. Mostly, all four potent compounds (K788-9421, S357-0084, S357-0893, S357-0915) are hydrophobic and evaluated for thermodynamics property analysis using MM-GBSA and free energy landscape (FEL) calculations. However, among all, K788-9421 shows comparatively better and energetically most favorable interactions with peregrin. Overall, study findings can lead to further research in developing next-generation broad-spectrum Peregrin inhibitors-modulators; they need extensive experimental validation for considering the compounds for clinical-trial application for being an excellent drug-candidate entity against Peregrin protein.

Design and evaluation of piperidine carboxamide derivatives as potent ALK inhibitors through 3D-QSAR modeling, artificial neural network and computational analysis

Tumor stands as one of the principal contributors to global mortality. As research into tumor treatments advances, tumor inhibitors emerge as pivotal milestones in tumor therapy. Among these inhibitors, Anaplastic Lymphoma Kinase (ALK), a receptor tyrosine kinase, is critical owing to its close association with tumor cell proliferation and growth, which renders it a critical therapeutic target. This work systematically explores the relationship between the chemical structures of 36 piperidine carboxamide derivatives and their efficacy in inhibiting Karpas-299 tumor cell activity by employing a rigorous 3D-QSAR modeling approach. A robust Topomer CoMFA model was generated and was meticulously validated through ANN neural network analysis (q2 = 0.597, r2 = 0.939, F = 84.401, N = 4, SEE = 0.268). Based on the model, 60 new compounds with desirable inhibitory activities were successfully designed. Combined with Lipinski’s rule and ADMET criteria alongside molecular docking and dynamics simulations, a lead compound with high inhibitory activity and good drug-likeness was selected. Further computational analyses, encompassing free energy landscape and binding free energy calculations, provided compelling evidence of the stable binding conformation of the lead compound and the superior affinity with the target protein at the active site, underscoring its potential therapeutic utility. In summary, this investigation offers valuable insights and methodological guidance for advancing tumor therapy and underscores the promise of piperidine carboxamide derivatives as prospective ALK inhibitors.

Antiviral actions of natural compounds against dengue virus RNA dependent RNA polymerase: insights from molecular dynamics and Gibbs free energy landscape

Dengue fever, a major global health challenge, affects nearly half the world’s population and lacks effective treatments or vaccines. Addressing this, our study focused on natural compounds that potentially inhibit the dengue virus’s RNA-dependent RNA polymerase (RdRp), a crucial target in the viral replication cycle. Utilizing the MTiOpenScreen webserver, we screened 1226 natural compounds from the NP-lib database. This screening identified four promising compounds ZINC000059779788, ZINC0000044404209, ZINC0000253504517 and ZINC0000253499146), each demonstrating high negative binding energies between −10.4 and −9.9 kcal/mol, indicative of strong potential as RdRp inhibitors. These compounds underwent rigorous validation through re-docking and a detailed 100 ns molecular dynamics (MD) simulation. This analysis affirmed the dynamic stability of the protein-ligand complexes, a critical factor in the effectiveness of potential drug candidates. Additionally, we conducted essential dynamics and free energy landscape calculations to understand the structural transitions in the RdRp protein upon ligand binding, providing valuable insights into the mechanism of inhibition. Our findings present these natural molecules as promising therapeutic agents against the dengue virus. By targeting the allosteric site of RdRp, these compounds offer a novel approach to hinder the viral replication process. This research significantly contributes to the search for effective anti-dengue treatments, positioning natural compounds as potential key players in dengue virus control strategies. Communicated by Ramaswamy H. Sarma

Unraveling the Behavior of Intrinsically Disordered Protein c-Myc: A Study Utilizing Gaussian-Accelerated Molecular Dynamics.

The protein c-Myc is a transcription factor that remains largely intrinsically disordered and is known to be involved in various biological processes and is overexpressed in various cancers, making it an attractive drug target. However, intrinsically disordered proteins such as c-Myc do not show funnel-like basins in their free-energy landscapes; this makes their druggability a challenge. For the first time, we propose a heterodimer model of c-Myc/Max in full length in this work. We used Gaussian-accelerated molecular dynamics (GaMD) simulations to explore the behavior of c-Myc and its various regions, including the transactivation domain (TAD) and the basic helix-loop-helix-leucine-zipper (bHLH-Zipper) motif in three different conformational states: (a) monomeric c-Myc, (b) c-Myc when bound to its partner protein, Max, and (c) when Max was removed after binding. We analyzed the GaMD trajectories using root-mean-square deviation (RMSD), radius of gyration, root-mean-square fluctuation, and free-energy landscape (FEL) calculations to elaborate the behaviors of these regions. The results showed that the monomeric c-Myc structure showed a higher RMSD fluctuation as compared with the c-Myc/Max heterodimer in the bHLH-Zipper motif. This indicated that the bHLH-Zipper motif of c-Myc is more stable when it is bound to Max. The TAD region in both monomeric and Max-bound states showed similar plasticity in terms of RMSD. We also conducted residue decomposition calculations and showed that the c-Myc and Max interaction could be driven mainly by electrostatic interactions and the residues Arg299, Ile403, and Leu420 seemed to play important roles in the interaction. Our work provides insights into the behavior of c-Myc and its regions that could support the development of drugs that target c-Myc and other intrinsically disordered proteins.

Assembling Biocompatible Polymers on Gold Nanoparticles: Toward a Rational Design of Particle Shape by Molecular Dynamics.

Gold nanoparticles (AuNPs) have received great attention in a number of fields ranging from the energy sector to biomedical applications. As far as the latter is concerned, due to rapid renal clearance and a short lifetime in blood, AuNPs are often encapsulated in a poly(lactic-co-glycolic acid) (PLGA) matrix owing to its biocompatibility and biodegradability. A better understanding of the PLGA polymers on the AuNP surface is crucial to improve and optimize the above encapsulation process. In this study, we combine a number of computational approaches to explore the adsorption mechanisms of PLGA oligomers on a Au crystalline NP and to rationalize the PLGA coating process toward a more efficient design of the NP shape. Atomistic simulations supported by a recently developed unsupervised machine learning scheme show the temporal evolution and behavior of PLGA clusterization by tuning the oligomer concentration in aqueous solutions. Then, a detailed surface coverage analysis coupled with free energy landscape calculations sheds light on the anisotropic nature of PLGA adsorption onto the AuNP. Our results prove that the NP shape and topology may address and privilege specific sites of adsorption, such as the Au {1 1 1} crystal planes in selected NP samples. The modeling-based investigation suggested in this article offers a solid platform to guide the design of coated NPs.

Ab initio metadynamics determination of temperature-dependent free-energy landscape in ultrasmall silver clusters.

Ab initio metadynamics enables the extraction of free-energy landscapes having the accuracy of first-principles electronic structure methods. We introduce an interface between the PLUMED code that computes free-energy landscapes and enhanced-sampling algorithms and the Atomic Simulation Environment (ASE) module, which includes several ab initio electronic structure codes. The interface is validated with a Lennard-Jones cluster free-energy landscape calculation by averaging multiple short metadynamics trajectories. We use this interface and analysis to estimate the free-energy landscape of Ag5 and Ag6 clusters at 10, 100, and 300K with the radius of gyration and coordination number as collective variables, finding at most tens of meV in error. Relative free-energy differences between the planar and non-planar isomers of both clusters decrease with temperature in agreement with previously proposed stabilization of non-planar isomers. Interestingly, we find that Ag6 is the smallest silver cluster where entropic effects at room temperature boost the non-planar isomer probability to a competing state. The new ASE-PLUMED interface enables simulating nanosystem electronic properties under more realistic temperature-dependent conditions.

Theoretical Study of Dissociation Process of Plastocyanins by PaCS-MD Simulation

We present a procedure of calculation of free energy landscape of two proteins by using parallel cascade molecular dynamics (PaCS-MD) and multiple independent umbrella sampling (MIUS). The free energy landscape of two plastocyanins for association/dissociation process is investigate by using the present method. We find that binding free energy is around 1 kcal/mol and that the barrier energy at around the middle range between the equilibrium point and the dissociation state becomes about 1 kcal/mol from the association process. The present results suggest that the energy barrier may arise from hydrogen bonds between two plastocyanins. We also find that the effective interaction between two plastocyanins already vanishes at the distance of 2 Å from equilibrium state. The equilibrium point of the complex around 27.9 Å is a good agreement with the experimental result 27.8 Å

Force-Correction Analysis Method for Derivation of Multidimensional Free-Energy Landscapes from Adaptively Biased Replica Simulations.

A methodology is proposed for the calculation of multidimensional free-energy landscapes of molecular systems, based on analysis of multiple molecular dynamics trajectories wherein adaptive biases have been applied to enhance the sampling of different collective variables. In this approach, which we refer to as the Force-Correction Analysis Method (FCAM), local averages of the total and biasing forces are evaluated post hoc, and the latter are subtracted from the former to obtain unbiased estimates of the mean force across collective-variable space. Multidimensional free-energy surfaces and minimum free-energy pathways are then derived by integrating the mean-force landscape with a kinetic Monte Carlo algorithm. To evaluate the proposed method, a series of numerical tests and comparisons with existing approaches were carried out for small molecules, peptides, and proteins, based on all-atom trajectories generated with standard, concurrent, and replica-exchange metadynamics in collective-variable spaces ranging from one to six dimensional. The tests confirm the correctness of the FCAM formulation and demonstrate that calculated mean forces and free energies converge rapidly and accurately, outperforming other methods used to unbias this kind of simulation data.

Computational study of non-conductive selectivity filter conformations and C-type inactivation in a voltage-dependent potassium channel.

C-type inactivation is a time-dependent process of great physiological significance that is observed in a large class of K+ channels. Experimental and computational studies of the pH-activated KcsA channel show that the functional C-type inactivated state, for this channel, is associated with a structural constriction of the selectivity filter at the level of the central glycine residue in the signature sequence, TTV(G)YGD. The structural constriction is allosterically promoted by the wide opening of the intracellular activation gate. However, whether this is a universal mechanism for C-type inactivation has not been established with certainty because similar constricted structures have not been observed for other K+ channels. Seeking to ascertain the general plausibility of the constricted filter conformation, molecular dynamics simulations of a homology model of the pore domain of the voltage-gated potassium channel Shaker were performed. Simulations performed with an open intracellular gate spontaneously resulted in a stable constricted-like filter conformation, providing a plausible nonconductive state responsible for C-type inactivation in the Shaker channel. While there are broad similarities with the constricted structure of KcsA, the hypothetical constricted-like conformation of Shaker also displays some subtle differences. Interestingly, those are recapitulated by the Shaker-like E71V KcsA mutant, suggesting that the residue at this position along the pore helix plays a pivotal role in determining the C-type inactivation behavior. Free energy landscape calculations show that the conductive-to-constricted transition in Shaker is allosterically controlled by the degree of opening of the intracellular activation gate, as observed with the KcsA channel. The behavior of the classic inactivating W434F Shaker mutant is also characterized from a 10-μs MD simulation, revealing that the selectivity filter spontaneously adopts a nonconductive conformation that is constricted at the level of the second glycine in the signature sequence, TTVGY(G)D.

An Asymmetric C-Type Inactivated Structure of HERG Channel and Its Binding to Chemically Diverse Drugs

The fast C-type inactivation displayed by the voltage-activated potassium channel hERG plays a critical role in the repolarization of cardiac cells, and malfunction caused by non-specific binding of drugs or naturally occurring missense mutations affecting inactivation can lead to pathologies. From a pharmacological standpoint, the C-type inactivated state of hERG could bind a large set of chemically diverse drugs. Therefore, understanding the structural basis of C-type inactivation in hERG could help screening compounds for their impact on hERG activity, an indispensable step for drug development. In present study, long-timescale molecular dynamics simulation, free energy landscape calculations, and electrophysiological experiments are combined to address the structural and functional impacts of several disease-associated mutations. Our data suggest that C-type inactivation in hERG is associated with an asymmetrical constricted-like conformation of the selectivity filter, identifying F627 side-chain and the hydrogen bond between Y616 and N627 are key determinants. The energetics of inactivation in hERG, Shaker, and KcsA shows that the C-type inactivation rate depends on the degree of opening of the intracellular gate via the filter-gate allosteric coupling, providing a molecular explanation of the fast inactivation in hERG channel. After the selectivity filter constricts asymmetrically, it is observed that the key residue in the binding site, Y652 in all four subunits, shows high structural flexibility. The snapshots were clustered based on the conformational similarity of Y652, and typical conformations were selected to perform ensemble docking with multiple chemically diverse drugs. The docking results show there are different C-type inactivated conformations more favorable for drugs binding compared with the first experimental conductive structure, demonstrating that the high flexibility of Y652 after constriction is the structural basis for the binding of chemically diverse drug to the hERG channel.

Identification of FDA approved drugs and nucleoside analogues as potential SARS-CoV-2 A1pp domain inhibitor: An in silico study

Coronaviruses are known to infect respiratory tract and intestine. These viruses possess highly conserved viral macro domain A1pp having adenosine diphosphate (ADP)-ribose binding and phosphatase activity sites. A1pp inhibits adenosine diphosphate (ADP)-ribosylation in the host and promotes viral infection and pathogenesis. We performed in silico screening of FDA approved drugs and nucleoside analogue library against the recently reported crystal structure of SARS-CoV-2 A1pp domain. Docking scores and interaction profile analyses exhibited strong binding affinity of eleven FDA approved drugs and five nucleoside analogues NA1 (−13.84), nadide (−13.65), citicholine (−13.54), NA2 (−12.42), and NA3 (−12.27). The lead compound NA1 exhibited significant hydrogen bonding and hydrophobic interaction at the natural substrate binding site. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface (SASA), hydrogen bond formation, principle component analysis, and free energy landscape calculations for NA1 bound protein displayed stable complex formation in 100 ns molecular dynamics simulation, compared to unbound macro domain and natural substrate adenosine-5-diphosphoribose bound macro domain that served as a positive control. The molecular mechanics Poisson–Boltzmann surface area analysis of NA1 demonstrated binding free energy of −175.978 ± 0.401 kJ/mol in comparison to natural substrate which had binding free energy of −133.403 ± 14.103 kJ/mol. In silico analysis by modelling tool ADMET and prediction of biological activity of these compounds further validated them as putative therapeutic molecules against SARS-CoV-2. Taken together, this study offers NA1 as a lead SARS-CoV-2 A1pp domain inhibitor for future testing and development as therapeutics against human coronavirus.

Identification of potential natural inhibitors of SARS-CoV2 main protease by molecular docking and simulation studies

Coronaviruses are contagious pathogens primarily responsible for respiratory and intestinal infections. Research efforts to develop antiviral agents against coronavirus demonstrated the main protease (Mpro) protein may represent effective drug target. X-ray crystallographic structure of the SARS-CoV2 Mpro protein demonstrated the significance of Glu166, Cys141, and His41 residues involved in protein dimerization and its catalytic function. We performed in silico screening of compounds from Curcuma longa L. (Zingiberaceae family) against Mpro protein inhibition. Employing a combination of molecular docking, scoring functions, and molecular dynamics simulations, 267 compounds were screened by docking on Mpro crystallographic structure. Docking score and interaction profile analysis exhibited strong binding on the Mpro catalytic domain with compounds C1 (1E,6E)-1,2,6,7-tetrahydroxy-1,7-bis(4-hydroxy-3-methoxyphenyl)hepta-1,6-diene-3,5-dione) and C2 (4Z,6E)‐1,5‐dihydroxy‐1,7‐bis(4‐hydroxyphenyl)hepta‐4,6‐dien‐3‐one as lead agents. Compound C1 and C2 showed minimum binding score (–9.08 and –8.07 kcal/mole) against Mpro protein in comparison to shikonin and lopinavir (≈ −5.4 kcal/mole) a standard Mpro inhibitor. Furthermore, principal component analysis, free energy landscape and protein-ligand energy calculation studies revealed that these two compounds strongly bind to the catalytic core of the Mpro protein with higher efficacy than lopinavir, a standard antiretroviral of the protease inhibitor class. Taken together, this structure based optimization has provided lead on two natural Mpro inhibitors for further testing and development as therapeutics against human coronavirus. Communicated by Ramaswamy H. Sarma

Identification of Selective Novel Hits against Plasmodium falciparum Prolyl tRNA Synthetase Active Site and a Predicted Allosteric Site Using in silico Approaches.

Recently, there has been increased interest in aminoacyl tRNA synthetases (aaRSs) as potential malarial drug targets. These enzymes play a key role in protein translation by the addition of amino acids to their cognate tRNA. The aaRSs are present in all Plasmodium life cycle stages, and thus present an attractive malarial drug target. Prolyl tRNA synthetase is a class II aaRS that functions in charging tRNA with proline. Various inhibitors against Plasmodium falciparum ProRS (PfProRS) active site have been designed. However, none have gone through clinical trials as they have been found to be highly toxic to human cells. Recently, a possible allosteric site was reported in PfProRS with two possible allosteric modulators: glyburide and TCMDC-124506. In this study, we sought to identify novel selective inhibitors targeting PfProRS active site and possible novel allosteric modulators of this enzyme. To achieve this, virtual screening of South African natural compounds against PfProRS and the human homologue was carried out using AutoDock Vina. The modulation of protein motions by ligand binding was studied by molecular dynamics (MD) using the GROningen MAchine for Chemical Simulations (GROMACS) tool. To further analyse the protein global motions and energetic changes upon ligand binding, principal component analysis (PCA), and free energy landscape (FEL) calculations were performed. Further, to understand the effect of ligand binding on the protein communication, dynamic residue network (DRN) analysis of the MD trajectories was carried out using the MD-TASK tool. A total of ten potential natural hit compounds were identified with strong binding energy scores. Binding of ligands to the protein caused observable global and residue level changes. Dynamic residue network calculations showed increase in betweenness centrality (BC) metric of residues at the allosteric site implying these residues are important in protein communication. A loop region at the catalytic domain between residues 300 and 350 and the anticodon binding domain showed significant contributions to both PC1 and PC2. Large motions were observed at a loop in the Z-domain between residues 697 and 710 which was also in agreement with RMSF calculations that showed increase in flexibility of residues in this region. Residues in this loop region are implicated in ATP binding and thus a change in dynamics may affect ATP binding affinity. Free energy landscape (FEL) calculations showed that the holo protein (protein-ADN complex) and PfProRS-SANC184 complexes were stable, as shown by the low energy with very few intermediates and hardly distinguishable low energy barriers. In addition, FEL results agreed with backbone RMSD distribution plots where stable complexes showed a normal RMSD distribution while unstable complexes had multimodal RMSD distribution. The betweenness centrality metric showed a loss of functional importance of key ATP binding site residues upon allosteric ligand binding. The deep basins in average L observed at the allosteric region imply that there is high accessibility of residues at this region. To further analyse BC and average L metrics data, we calculated the ΔBC and ΔL values by taking each value in the holo protein BC or L matrix less the corresponding value in the ligand-bound complex BC or L matrix. Interestingly, in allosteric complexes, residues located in a loop region implicated in ATP binding had negative ΔL values while in orthosteric complexes these residues had positive ΔL values. An increase in contact frequency between residues Ser263, Thr267, Tyr285, and Leu707 at the allosteric site and residues Thr397, Pro398, Thr402, and Gln395 at the ATP binding TXE loop was observed. In summary, this study identified five potential orthosteric inhibitors and five allosteric modulators against PfProRS. Allosteric modulators changed ATP binding site dynamics, as shown by RMSF, PCA, and DRN calculations. Changes in dynamics of the ATP binding site and increased contact frequency between residues at the proposed allosteric site and the ATP binding site may explain how allosteric modulators distort the ATP binding site and thus might inhibit PfProRS. The scaffolds of the identified hits in the study can be used as a starting point for antimalarial inhibitor development with low human cytotoxicity.

Tungsten Oxide Nanodots Exhibit Mild Interactions with WW and SH3 Modular Protein Domains.

Tungsten oxide nanodot (WO3–x) is an active photothermal nanomaterial that has recently been discovered as a promising candidate for tumor theranostics and treatments. However, its potential cytotoxicity remains elusive and needs to be evaluated to assess its biosafety risks. Herein, we investigate the interactions between WO3–x and two ubiquitous protein domains involved in protein–protein interactions, namely, WW and SH3 domains, using atomistic molecular dynamics simulations. Our results show that WO3–x interacts only weakly with the key residues at the putative proline-rich motif (PRM) ligand-binding site of both domains. More importantly, our free energy landscape calculations reveal that the binding strength between WO3–x and WW/SH3 is weaker than that of the native PRM ligand with WW/SH3, implying that WO3–x has a limited inhibitory effect over PRM on both the WW and SH3 domains. These findings suggest that the cytotoxic effects of WO3–x on the key modular protein domains could be very mild, which provides new insights for the future potential biomedical applications of this nanomaterial.

Molecular Determinants of C-type Inactivation for the hERG Channel and Its Disease-associated Mutants

C-type inactivation is a time-dependent process observed in many K+ channels whereby prolonged activation by an external stimulus leads to a reduction in ionic conduction. The extremely fast C-type inactivation of the voltage-gated potassium channel hERG plays a critical role in the repolarization of cardiac cells, with malfunction having a direct impact on human health. For instance, a number of mutations in hERG have been identified to cause various forms of Long/Short QT Syndromes. Yet, understanding at the molecular level is limited, as the conformational change underlying C-type inactivation in the hERG channel has remained elusive. Molecular dynamics simulations show that the fast C-type inactivation in hERG is associated with an asymmetrical constricted-like conformation of the selectivity filter. Furthermore, molecular dynamics free energy landscape calculations reveal the molecular basis for the functional behavior for several disease-associated or functionally documented mutations, i.e., N628D, S631A, F627Y, S620T, and G628C/S631C. The high correlation between the functional data and the calculated free energy landscapes strongly supports the conclusions drawn from the simulations. The simulations point to several key residue-residue contacts responsible for the structural and functional impact of these mutations. The broader significance of one of these key contacts is then confirmed in protein sequence coevolution analysis based on a large number of sequences, supporting the notion that the features underlying C-type inactivation in hERG are universally conserved within the potassium channels family.

Insights Into the Resistance Mechanisms of Inhibitors to FLT3 F691L Mutation via an Integrated Computational Approach.

Research has shown that FMS-like tyrosine kinase 3 (FLT3) may be a vital drug target for acute myeloid leukemia (AML). However, even though the clinically relevant F691L gatekeeper mutation conferred resistance to current FLT3 drug quizartinib, PLX3397 remained unaffected. In this study, the protein–ligand interactions between FLT3 kinase domain (wild-type or F691L) and quizartinib or PLX3397 were compared via an integrated computational approach. The classical molecular dynamics (MD) simulations in conjunction with dynamic cross-correlation (DCC) analysis, solvent-accessible surface area (SASA), and free energy calculations indicated that the resistant mutation may induce the conformational change of αC-helix and A-loop of the FLT3 protein. The major variations were controlled by the electrostatic interaction and SASA, which were allosterically regulated by residues Glu-661 and Asp-829. When FLT3-F691L was bound to quizartinib, a large conformational change was observed via combination of accelerated MD simulations (aMDs), principal component analysis (PCA), and free energy landscape (FEL) calculations. The umbrella sampling (US) simulations were applied to investigate the dissociation processes of the quizartinib or PLX3397 from FLT3-WT and FLT3-F691L. The calculated results suggested that PLX3397 had similar dissociation processes from both FLT3-WT and FLT3-F691L, but quizartinib dissociated more easily from FLT3-F691L than from FLT3-WT. Thus, reduced residence time was responsible for the FLT3-F691L resistance to inhibitors. These findings indicated that both the conformational changes of αC-helix and A-loop and the drug residence time should be considered in the design of drugs so that rational decisions can be made to overcome resistance to FLT3-F691L.

Unfolding Dynamics of Ubiquitin from Constant Force MD Simulation: Entropy-Enthalpy Interplay Shapes the Free-Energy Landscape.

Force probe methods are routinely used to study conformational transitions of biomolecules at single-molecule level. In contrast to simple kinetics, some proteins show complex response to mechanical perturbations that is manifested in terms of unusual force-dependent kinetics. Here, we study, via fully atomistic molecular dynamics simulations, constant force-induced unfolding of ubiquitin protein. Our simulations reveal a crossover at an intermediate force (about 400 pN) in the unfolding rate versus force curve. We find by calculation of multidimensional free-energy landscape (FEL) of the protein that the complex unfolding kinetics is intimately related to the force-dependent modifications in the FEL. Pearson correlation coefficient analysis allowed us to identify two appropriate order parameters describing the unfolding transition. The crossover in the rate can be explained in terms of an interplay between entropy and enthalpy with relative importance changing from low force to high force. We rationalize the results by using multidimensional transition-state theory.

Bending Lipid Bilayers: A Closed-Form Collective Variable for Effective Free-Energy Landscapes in Quantitative Biology.

Curvature-related processes are of major importance during protein-membrane interactions. The illusive simplicity of membrane reshaping masks a complex molecular process crucial for a wide range of biological functions like fusion, endo- and exocytosis, cell division, cytokinesis, and autophagy. To date, no functional expression of a reaction coordinate capable of biasing molecular dynamics simulations to produce membrane curvature has been reported. This represents a major drawback given that the adequate identification of proper collective variables to enhance sampling is fundamental for restrained dynamics techniques. In this work, we present a closed-form equation of a collective variable that induces bending in lipid bilayers in a controlled manner, allowing for straightforward calculation of free energy landscapes of important curvature-related events, using standard methods such as umbrella sampling and metadynamics. As a direct application of the collective variable, we calculate the bending free energies of a ternary lipid bilayer in the presence and the absence of a Bin/Amphiphysin/Rvs domain with an N-terminal amphipathic helix (N-BAR), a well-known peripheral membrane protein that induces curvature.

Flexible Choice of Solute in Replica Exchange with Solute Tempering Can Improve Performance of Conformation Search for Small Proteins

Replica exchange with solute tempering (REST) significantly reduces computational cost in comparison with conventional temperature replica exchange molecular dynamics method. We extended the solute selection scheme of this REST, to avoid parameter space trapping problem and associated loss in conformational search efficiencies happen in REST. The new scheme, which we call generalized REST (gREST), accepts energy term based partitioning in addition to the particle based one; the solute region can involve only dihedral energy terms, for example. We applied this gREST to the folding and free energy landscape calculations of Trp-cage small protein system, where only dihedral energy terms were considered as the solute (dihedral-gREST), and compared its efficiency with the most frequently used REST variant, REST2. Using this dihedral-gREST, we successfully found the native state of Trp-cage in comparable timescale as REST2 with almost a half of computational cost. Moreover, the free energy landscape, calculated with multistate Bennett acceptance ratio (MBAR), of REST2 underestimated the stability of unfolded state and the convergence rate of the free energy map was slower than that by dihedral-gREST. In REST2, stable structures including the native one favor states with smaller energy scaling coefficients (lower REST temperature, in other words), which is caused by the disturbance in solute and solvent energy compensations due to the energy scaling coefficients. This trapping in the parameter space eventually resulted in the less accurate free energy map. In contrast, dihedral-gREST did not suffer from such a trapping in the parameter space. This generalized variant of REST, gREST, can further extend the capability of REST scheme and is expected to improve many types of simulations including free energy calculations.

Interplay of fast and slow dynamics in rare transition pathways: The disk-to-slab transition in the 2d Ising model.

Rare transitions between long-lived stable states are often analyzed in terms of free energy landscapes computed as functions of a few collective variables. Here, using transitions between geometric phases as example, we demonstrate that the effective dynamics of a system along these variables are an essential ingredient in the description of rare events and that the static perspective provided by the free energy alone may be misleading. In particular, we investigate the disk-to-slab transition in the two-dimensional Ising model starting with a calculation of a two-dimensional free energy landscape and the distribution of committor probabilities. While at first sight it appears that the committor is incompatible with the free energy, they can be reconciled with each other using a two-dimensional Smoluchowski equation that combines the free energy landscape with state dependent diffusion coefficients. These results illustrate that dynamical information is not only required to calculate rate constants but that neglecting dynamics may also lead to an inaccurate understanding of the mechanism of a given process.