Steered Molecular Dynamics Research Articles

Molecular dynamics investigation of ivermectin bound to importin alpha/beta heterodimer

ABSTRACT Ivermectin (D1), an FDA-approved drug, is mainly used as an inhibitor for the treatment of parasitic infections. This drug was drawn attention due to its effectiveness in COVID-19 treatment. In this work, we investigated how ivermectin and its analogues are interacted with Impα/β1 heterodimer by molecular docking, steered molecular dynamics (SMD), classical molecular dynamics (MD), and MM/PBSA binding free energy analysis. Docking results showed that ivermectin dimer showed the highest binding affinity of −12.2 kcal/mol compared to its monomer. In SMD, the highest acceleration of 600 pm/ps2 is noticed for D1-Impα/β1 complex in the distance from 18.27 to 18.36 Å. The pulling force of 1745.86 pN is also detected for D1-Impα/β1. To validate the docking and SMD results, 100 ns molecular dynamics (MD) simulation is performed on the D1-Impα/β1 complex. The average RMSD value indicates a good structural stability of the complex despite some significant changes at the beginning. It is noted that most of the residues are stable over the simulation time with an average RMSF value of less than 2.65 Å. The MM/PBSA free energy of ivermectin also shows strong and spontaneous binding with the Impα/β1.

Evaluation of transport mechanism of ascorbic acid through cyclic peptide-based nanotubes: A molecular dynamics study

Cyclic peptide nanotubes (CPNTs) are potential candidates for drug delivery, separation and recovery technologies, as well as self-assembling nanomaterials. In this study, we investigated the L-ascorbic acid transport behaviour through two CPNTs using computational studies, including quantum calculations, molecular docking and steered molecular dynamics (SMD) simulations. Two cyclic peptide nanotubes 8 × [L-Gln-(D-Leu-L-Trp) 4-D-Leu-] (QLWL) and 8 × [(D-Ala-L-Ala) 5] (AA), embedded in a fully hydrated membrane composed of DPPC/POPC/POPS/cholesterol, were considered. Our findings from SMD simulations revealed that ascorbic acid moves differently in AA nanotube compared to QLWL nanotube. The analysis of the number of hydrogen bonds shows that the hydrogen atoms of ascorbic acid hydroxyl groups form more hydrogen bonds compared to oxygen atoms with water molecules and the CPNTs. This result was supported using the calculations of radial distribution functions of various atoms of the ascorbic acid near the oxygen atom of water molecules and carbonyl groups of the CPNTs during the transport pathway in the lumen of each CPNTs. Entropy calculations show that the configurational entropy of ascorbic acid in the transport pathway is not monotonous, and it changes due to variable behaviour when the molecule moves throughout CPNTs. The interactions that the nanotubes form with their environment play an important role in the binding energy of ascorbic acid with each of the peptide ring that the binding energy value is significant for each of the peptide rings with ascorbic acid. These informations can be useful to future applications and studies in the field of nanoscience and nanotechnology, such as drug delivery and nanosensors.

Application of in vitro PAMPA technique and in silico computational methods for blood-brain barrier permeability prediction of novel CNS drug candidates

Permeability assessment of small molecules through the blood-brain barrier (BBB) plays a significant role in the development of effective central nervous system (CNS) drug candidates. Since in vivo methods for BBB permeability estimation require a lot of time and resources, in silico and in vitro approaches are becoming increasingly popular nowadays for faster and more economical predictions in early phases of drug discovery. In this work, through application of in vitro parallel artificial membrane permeability assay (PAMPA-BBB) and in silico computational methods we aimed to examine the passive permeability of eighteen compounds, which affect serotonin and dopamine levels in the CNS. The data set was consisted of novel six human dopamine transporter (hDAT) substrates that were previously identified as the most promising lead compounds for further optimisation to achieve neuroprotective effect, twelve approved CNS drugs, and their related compounds. Firstly, PAMPA methods was used to experimentally determine effective BBB permeability (Pe) for all studied compounds and obtained results were further submitted for quantitative structure permeability relationship (QSPR) analysis. QSPR models were built by using three different statistical methods: stepwise multiple linear regression (MLR), partial least square (PLS), and support-vector machine (SVM), while their predictive capability was tested through internal and external validation. Obtained statistical parameters (MLR- R2pred=-0.10; PLS- R2pred=0.64, r2m=0.69, r/2m=0.44; SVM- R2pred=0.57, r2m=0.72, r/2m=0.55) indicated that the SVM model is superior over others. The most important molecular descriptors (H0p and SolvEMt_3D) were identified and used to propose structural modifications of the examined compounds in order to improve their BBB permeability. Moreover, steered molecular dynamics (SMD) simulation was employed to comprehensively investigate the permeability pathway of compounds through a lipid bilayer. Taken together, the created QSPR model could be used as a reliable and fast pre-screening tool for BBB permeability prediction of structurally related CNS compounds, while performed MD simulations provide a good foundation for future in silico examination.

Quantifying surface free energy of molecular crystal β-HMX using non-equilibrium molecular dynamics methods

Granular molecular crystals show a large variation in the orientation, length, shape, and cohesive interactions of interfaces when embedded in a polymer matrix. But the determination of the associated excess of free energy is not straightforward, especially due to the entropic contribution which is not negligible for molecular compounds. The surface free energy (SFE) is also important to predict crystal shapes and growth or to prove crucial insights into the mesoscale interfaces in the granular composites often with interfacial defects, voids, and pores. In this paper, we use Molecular Dynamics (MD) and assess and adapt two non-equilibrium methods, namely, non-equilibrium thermodynamic integration (NETI) and modified steered MD (SMD), to determine the SFE of various facets of a high-energy molecular crystal of interest: β-HMX. Starting with defect-free surfaces, both methods agree well with experiment concerning the most stable facets, whose energy is further lowered by a large entropic contribution. For some facets, surface creation (debonding process) and annihilation (bonding process) show fundamentally different paths, henceforth irreversible. Then, we discuss some sources of discrepancy between theoretical and experimental SFE, considering non-reversible dissipative events, surface roughness, and differences between various experimental techniques. These non-equilibrium methods can be applied to a wide range of molecular crystals and to study interface stability in polycrystals or with binding polymers, including the effects of various defects.

Mechanism for the Unfolding of the TOP7 Protein in Steered Molecular Dynamics Simulations as Revealed by Mutual Information Analysis.

We employed mutual information (MI) analysis to detect motions affecting the mechanical resistance of the human-engineered protein Top7. The results are based on the MI analysis of pair contact correlations measured in steered molecular dynamics (SMD) trajectories and their statistical dependence on global unfolding. This study is the first application of the MI analysis to SMD forced unfolding, and we furnish specific SMD recommendations for the utility of parameters and options in the TimeScapes package. The MI analysis provided a global overview of the effect of perturbation on the stability of the protein. We also employed a more conventional trajectory analysis for a detailed description of the mechanical resistance of Top7. Specifically, we investigated 1) the hydropathy of the interactions of structural segments, 2) the H2O concentration near residues relevant for unfolding, and 3) the changing hydrogen bonding patterns and main chain dihedral angles. The results show that the application of MI in the study of protein mechanical resistance can be useful for the engineering of more resistant mutants when combined with conventional analysis. We propose a novel mutation design based on the hydropathy of residues that would stabilize the unfolding region by mimicking its more stable symmetry mate. The proposed design process does not involve the introduction of covalent crosslinks, so it has the potential to preserve the conformational space and unfolding pathway of the protein.

The penetration of human defensin 5 (HD5) through bacterial outer membrane: simulation studies.

Human α-defensin 5 (HD5) is one of cationic antimicrobial peptides which plays a crucial role in an innate immune system in human body. HD5 shows the killing activity against a broad spectrum of pathogenic bacteria by making a pore in a bacterial membrane and penetrating into a cytosol. Nonetheless, its pore-forming mechanisms remain unclear. Thus, in this work, the constant-velocity steered molecular dynamics (SMD) simulation was used to simulate the permeation of a dimeric HD5 into a gram-negative lipopolysaccharide (LPS) membrane model. Arginine-rich HD5 is found to strongly interact with a LPS surface. Upon arrival, arginines on HD5 interact with lipid A head groups (a top part of LPS) and then drag these charged moieties down into a hydrophobic core resulting in the formation of water-filled pore. Although all arginines are found to interact with a membrane, Arg13 and Arg32 appear to play a dominant role in the HD5 adsorption on a gram-negative membrane. Furthermore, one chain of a dimeric HD5 is required for HD5 adhesion. The interactions of arginine-lipid A head groups play a major role in adhering a cationic HD5 on a membrane surface and retarding a HD5 passage in the meantime.

Molecular Mechanism of Ca2+ in the Allosteric Regulation of Human Parathyroid Hormone Receptor-1.

Parathyroid hormone (PTH) is an endogenous ligand that activates the PTH type 1 receptor (PTH1R) signaling. Ca2+, a common second messenger, acts as an allosteric regulator for prolonging the activation of PTH1R. However, a clear picture of the underlying allosteric mechanism is still missing. Herein, extensive molecular dynamics (MD) simulations are performed for PTH1R-PTH complexes with and without Ca2+ ions, allowing us to delineate the molecular details of calcium-induced allostery. Our results indicate that acidic residues in the extracellular loop 1 (ECL1) (D251, E252, E254, and E258-E260) and PTH (E19 and E22) serve as key determinants for local Ca2+-coupling structures and rigidity of ECL1. Moreover, the binding of Ca2+ induces conformational changes of transmembrane domain 6/7 (TM6/7) that are related to PTH1R activation and strengthens the residue-residue communication within PTH and TMD allosterically. Moreover, our results demonstrate that the presence of Ca2+ ions potentiates the interaction between PTH and PTH1R via steered molecular dynamics (SMD) simulations, while the point mutation in the PTH (PTHR25C) weakens the binding of PTH and PTH1R. These results support that Ca2+ ions might further prolong the residence time of PTH on PTH1R and facilitate the positive allostery of PTH1R. Together, the present work provides new insights into the allosteric regulation mechanism of GPCRs induced by ions and related drug design targeting the PTH1R allosteric pathway.

Computational insights into binding mechanism of drugs as potential inhibitors against SARS-CoV-2 targets.

Because of the scale of the novel coronavirus (COVID-19) pandemic and the swift transmission of this highly contagious respiratory virus, repurposing existing drugs has become an urgent treatment approach. The objective of our study is to unravel the binding mechanism of the Food and Drug Administration (FDA)-approved dexamethasone (Dex) and boceprevir (Boc) drugs with selected COVID-19 protein targets SARS-CoV-2 spike protein C-terminal domain (spike-CTD), main protease (Mpro), and interleukin-6 (IL-6). Another objective is to analyze the effects of binding Dex and Boc drugs on the interactions of viral spike protein to human angiotensin-converting enzyme 2 (hACE2). Molecular docking and one-microsecond-long molecular dynamics simulations of each of the six protein–drug complexes along with steered molecular dynamics (SMD) and umbrella sampling (US) methods have revealed the binding mode interactions and the physicochemical stability of the three targeted proteins with two drugs. Results have shown that both drugs bind strongly with the three protein targets through hydrogen bonding and hydrophobic interactions. A major finding from this study is how the binding of the drugs with viral spike protein affects its interactions at the binding interface with hACE2 protein. Simulations of drug-bound spike-CTD with hACE2 show that due to the presence of a drug at the binding interface of spike-CTD, hACE2 is being blocked from making putative interactions with viral protein at such interface. These important findings regarding the binding affinity and stability of the two FDA-approved drugs with the main targets of COVID-19 along with the effect of drugs on hACE2 interactions would contribute to COVID-19 drug discovery and development.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11696-021-01843-0.

Molecular dynamics study on emulsified oil droplets with nonionic surfactants

The stability of heavy crude oil is closely related to the netlike structure formed by the aggregation of asphaltene and resin molecules inside the oil droplets, and the aggregation is too complex to accurately obtain the microstructure of these molecules experimentally. In this paper, molecular dynamics (MD) simulation was performed to investigate the structure of emulsified oil droplets on the molecular level. The simulation results showed: (i) The stacking structure of asphaltene and resin molecules form the netlike structure of the oil droplet, and it is also considered as the main reason of high stability and viscosity of heavy crude oil. (ii) When nonionic surfactants were introduced, some of them can adsorb to the surface of oil droplet and change its hydrophilicity; others can enter the interior of the oil droplets and destroy the stacking structure of asphaltene or resins inside the oil droplet. The decreased viscosity of emulsified heavy oil in the present of surfactants attributed to the increase of hydrophilicity on the oil drop surface and the damage of stacking structure inside the oil drops. (iii) the steered molecular dynamics (SMD) simulation proved that the mechanical properties of emulsified heavy oil droplet become easier to be destroyed with the increase of surfactant concentration, and it indicates that nonionic surfactant is beneficial to promote demulsification and viscosity reduction of crude oil.

Electrostatic Interactions Explain the Higher Binding Affinity of the CR3022 Antibody for SARS-CoV-2 than the 4A8 Antibody.

A structural understanding of the mechanism by which antibodies bind SARS-CoV-2 at the atomic level is highly desirable as it can tell the development of more effective antibodies to treat Covid-19. Here, we use steered molecular dynamics (SMD) and coarse-grained simulations to estimate the binding affinity of the monoclonal antibodies CR3022 and 4A8 to the SARS-CoV-2 receptor-binding domain (RBD) and SARS-CoV-2 N-terminal domain (NTD). Consistent with experiments, our SMD and coarse-grained simulations both indicate that CR3022 has a higher affinity for SARS-CoV-2 RBD than 4A8 for the NTD, and the coarse-grained simulations indicate the former binds three times stronger to its respective epitope. This finding shows that CR3022 is a candidate for Covid-19 therapy and is likely a better choice than 4A8. Energetic decomposition of the interaction energies between these two complexes reveals that electrostatic interactions explain the difference in the observed binding affinity between the two complexes. This result could lead to a new approach for developing anti-Covid-19 antibodies in which good candidates must contain charged amino acids in the area of contact with the virus.

A Study on the Bending Stiffness of a New DNA Origami Nano-Joint.

The present article aims to investigate the mechanical properties of a new DNA origami nano-joint using the steered molecular dynamics (SMD) simulation. Since the analysis of mechanical properties is of great importance in bending conditions for a nano-joint, the forces are selected to achieve angular changes in the joint by the resultant torque. In this study, the nano-joint is considered as a beam in order to use mechanical equations to extract the mechanical properties of the designed nano-joint. In addition, the bending stiffness of the beam is investigated in different modes of deflection using the Euler-Bernoulli beam theory. The results revealed that the value of bending stiffness increases with increasing deflection, and the changes in the bending stiffness relative to the deflection is linear. The proposed DNA origami nano-joint can be used as a joint in nanorobots and can be effectively applied in nanorobotic systems to move different components.

Heavy metal ion separation from industrial wastewater using stacked graphene Membranes: A molecular dynamics simulation study

In recent years, fluid transport through stacked graphene membranes has gained considerable attention due to its potential applications in water purification and desalination. Here, we are resorting to molecular dynamics (MD) simulations to elucidate the metal ion separation efficiency and mechanism of ion transport in stacked graphene membranes of varying interlayer spacing (d). Our simulation results show that metal ions, including Cd2+, Cu2+, Hg2+, and Pb2+, can permeate through wide membranes (d = 1.0 nm), but metal ion rejection is close to complete for the narrower nanochannels, irrespectively of the metal ion type. The increase of the interlayer spacing positively influences the permeance of the metal ions and water. The impact of the first hydration shell of the metal ions on ion rejection from membranes is significantly high, whereas the impact of the second hydration shell is considerably low. Even if the second hydration radius of the metal ions is greater than the half-width of the channel, the ions can pass through the membranes because of the loosely bonded water molecules in that hydration shell. Moreover, free energy analysis using steered molecular dynamics (SMD) simulation techniques show that free energy profiles of a metal atom in wider channels are almost the same, and free energy for the metal atom within the membrane channels is always higher compared to that for water. The free energy of the metal atom within the narrower channel is noticeably high, and that is the reason for complete ion rejection. To sum up, our results suggest that stacked graphene membranes with an interlayer spacing of 0.8 nm are the best for complete metal ion rejection and considerable permeation of water.

Metadynamics-Based Approaches for Modeling the Hypoxia-Inducible Factor 2α Ligand Binding Process.

Several methods based on enhanced-sampling molecular dynamics have been proposed for studying ligand binding processes. Here, we developed a protocol that combines the advantages of steered molecular dynamics (SMD) and metadynamics. While SMD is proposed for investigating possible unbinding pathways of the ligand and identifying the preferred one, metadynamics, with the path collective variable (PCV) formalism, is suggested to explore the binding processes along the pathway defined on the basis of SMD, by using only two CVs. We applied our approach to the study of binding of two known ligands to the hypoxia-inducible factor 2α, where the buried binding cavity makes simulation of the process a challenging task. Our approach allowed identification of the preferred entrance pathway for each ligand, highlighted the features of the bound and intermediate states in the free-energy surface, and provided a binding affinity scale in agreement with experimental data. Therefore, it seems to be a suitable tool for elucidating ligand binding processes of similar complex systems.

Interactions of SARS-CoV-2 with inanimate surfaces in built and transportation environments

Understanding the interactions and transmission of pathogens with/via inanimate surfaces common in the built environment and public transport vehicles is critical to promoting sustainable and resilient urban development. Here, molecular dynamics (MD) simulations are used to study the adhesion of SARS-CoV-2 (the causative agent of COVID-19) to some of these surfaces at different temperatures (same for surfaces and ambiance) ranging from −23 to 60 °C. Surfaces simulated are aluminum, copper, copper oxide, polyethylene (PE), and silicon dioxide (SiO2). Steered MD (SMD) simulations are also used to investigate the transfer of the virus from PE and SiO2 when a contaminated surface is touched. The virus shows the lowest and highest adhesions to PE and SiO2, respectively (20 vs 534 eV). Influence of temperature is not found to be noticeable. Using simulated water molecules to represent moisture on the skin, SMD simulations show that water molecules can lift the virus from the PE surface but damage the virus when lifting it from the the SiO2 surface. The results suggest that the PE surface is a more favorable surface to transmit the virus than the other surfaces simulated in this study. The results are compared with those reported in a few experimental studies.

MD Simulations on a Well-Built Docking Model Reveal Fine Mechanical Stability and Force-Dependent Dissociation of Mac-1/GPIbα Complex.

Interaction of leukocyte integrin macrophage-1 antigen (Mac-1) to platelet glycoprotein Ibα (GPIbα) is critical for platelet–leukocyte crosstalk in hemostasis and inflammatory responses to vessel injuries under hemodynamic environments. The mechano-regulation and its molecular basis for binding of Mac-1 to GPIbα remain unclear, mainly coming from the lack of crystal structure of the Mac-1/GPIbα complex. We herein built a Mac-1/GPIbα complex model through a novel computer strategy, which included a flexible molecular docking and system equilibrium followed by a “force-ramp + snapback” molecular dynamics (MD) simulation. With this model, a series of “ramp-clamp” steered molecular dynamics (SMD) simulations were performed to examine the GPIbα–Mac-1 interaction under various loads. The results demonstrated that the complex was mechano-stable for both the high rupture force (>250 pN) at a pulling velocity of 3 Å/ns and the conformational conservation under various constant tensile forces (≤75 pN); a catch-slip bond transition was predicted through the dissociation probability, examined with single molecular AFM measurements, reflected by the interaction energy and the interface H-bond number, and related to the force-induced allostery of the complex; besides the mutation-identified residues D222 and R218, the residues were also dominant in the binding of Mac-1 to GPIbα. This study recommended a valid computer strategy for building a likely wild-type docking model of a complex, provided a novel insight into the mechanical regulation mechanism and its molecular basis for the interaction of Mac-1 with GPIbα, and would be helpful for understanding the platelet–leukocyte interaction in hemostasis and inflammatory responses under mechano-microenvironments.

Antigenic Peptide Loading into Major Histocompatibility Complex Class I Is Driven by the Substrate N-Terminus

Major histocompatibility complex class I (MHC-I), a key element of the acquired immune system, plays essential roles in activating CD8+ T cells by recognizing intracellular antigens derived from pa...

Insight Into Seeded Tau Fibril Growth From Molecular Dynamics Simulation of the Alzheimer's Disease Protofibril Core.

Aggregates of the microtubule associated tau protein are a major constituent of neurofibrillary lesions that define Alzheimer’s disease (AD) pathology. Increasing experimental evidence suggests that the spread of tau neurofibrillary tangles results from a prion-like seeding mechanism in which small oligomeric tau fibrils template the conversion of native, intrinsically disordered, tau proteins into their pathological form. By using atomistic molecular dynamics (MD) simulations, we investigate the stability and dissociation thermodynamics of high-resolution cryo-electron microscopy (cryo-EM) structures of both the AD paired-helical filament (PHF) and straight filament (SF). Non-equilibrium steered MD (SMD) center-of-mass pulling simulations are used to probe the stability of the protofibril structure and identify intermolecular contacts that must be broken before a single tau peptide can dissociate from the protofibril end. Using a combination of exploratory metadynamics and umbrella sampling, we investigate the complete dissociation pathway and compute a free energy profile for the dissociation of a single tau peptide from the fibril end. Different features of the free energy surface between the PHF and SF protofibril result from a different mechanism of tau unfolding. Comparison of wild-type tau PHF and post-translationally modified pSer356 tau shows that phosphorylation at this site changes the dissociation free energy surface of the terminal peptide. These results demonstrate how different protofibril morphologies template the folding of endogenous tau in distinct ways, and how post-translational modification can perturb the folding mechanism.

Biomechanical characterization of SARS-CoV-2 spike RBD and human ACE2 protein-protein interaction

The current COVID-19 pandemic has led to a devastating impact across the world. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (the virus causing COVID-19) is known to use the receptor-binding domain (RBD) at viral surface spike (S) protein to interact with the angiotensin-converting enzyme 2 (ACE2) receptor expressed on many human cell types. The RBD-ACE2 interaction is a crucial step to mediate the host cell entry of SARS-CoV-2. Recent studies indicate that the ACE2 interaction with the SARS-CoV-2 S protein has a higher affinity than its binding with the structurally identical S protein of SARS-CoV-1, the virus causing the 2002–2004 SARS outbreak. However, the biophysical mechanism behind such binding affinity difference is unclear. This study utilizes combined single-molecule force spectroscopy and steered molecular dynamics (SMD) simulation approaches to quantify the specific interactions between SARS-CoV-2 or SARS-CoV-1 RBD and ACE2. Depending on the loading rates, the unbinding forces between SARS-CoV-2 RBD and ACE2 range from 70 to 105 pN and are 30–40% higher than those of SARS-CoV-1 RBD and ACE2 under similar loading rates. SMD results indicate that SARS-CoV-2 RBD interacts with the N-linked glycan on Asn90 of ACE2. This interaction is mostly absent in the SARS-CoV-1 RBD-ACE2 complex. During the SMD simulations, the extra RBD-N-glycan interaction contributes to a greater force and prolonged interaction lifetime. The observation is confirmed by our experimental force spectroscopy study. After removing N-linked glycans on ACE2, its mechanical binding strength with SARS-CoV-2 RBD decreases to a similar level of the SARS-CoV-1 RBD-ACE2 interaction. Together, the study uncovers the mechanism behind the difference in ACE2 binding between SARS-CoV-2 and SARS-CoV-1 and could help develop new strategies to block SARS-CoV-2 entry.

Investigating the Effect of a Non-Conservative Mutation (G273D) on Integrin Alpha6-Beta4 Binding Interactions

Integrins are heterodimeric transmembrane receptors which function in cell adhesion and signalling. Mutations on either their alpha or beta subunit result in different debilitating conditions. In particular, a G273D mutation in the Integrin Beta 4 (ITGB4) subunit is known to cause a lethal form of epidermolysis bullosa (EB), a rare disease characterized by very fragile skin and mucosal membranes. To gain a deeper understanding of this disease, this study aimed to elucidate the effects of the G273D mutation on the structure of ITGB4 and its interaction with its partner, Integrin Alpha 6 (ITGA6). In this study, in silico modelling predicted more interfacial contacts, and consequently, stronger binding affinity between ITGA6-ITGB4, than between ITGA6-ITGB4(G273D). The type of ions included in the simulated equilibration medium (i.e. CaCl2 or NaCl) was also observed to affect the binding affinities between the integrin subunits. Steered Molecular Dynamics (SMD) simulations showed significantly longer dissociation times for the CaCl2 equilibrated WT ITGB4 replicates compared to the other setups. Significantly higher pull forces were needed for the dissociation of ITGA6-ITGB4 compared to ITGA6-ITGB4(G273D) when equilibrated with CaCl2. These results corroborate previous findings that Calcium ions are needed to stabilize the binding of the heterodimer albeit in an inactive state. More importantly, these suggest that the G273D mutation disrupts the binding of ITGB4 with ITGA6 even in the presence of calcium ions.

Qualitative Prediction of Ligand Dissociation Kinetics from Focal Adhesion Kinase Using Steered Molecular Dynamics.

Most early-stage drug discovery projects focus on equilibrium binding affinity to the target alongside selectivity and other pharmaceutical properties. Since many approved drugs have nonequilibrium binding characteristics, there has been increasing interest in optimizing binding kinetics early in the drug discovery process. As focal adhesion kinase (FAK) is an important drug target, we examine whether steered molecular dynamics (SMD) can be useful for identifying drug candidates with the desired drug-binding kinetics. In simulating the dissociation of 14 ligands from FAK, we find an empirical power–law relationship between the simulated time needed for ligand unbinding and the experimental rate constant for dissociation, with a strong correlation depending on the SMD force used. To improve predictions, we further develop regression models connecting experimental dissociation rate with various structural and energetic quantities derived from the simulations. These models can be used to predict dissociation rates from FAK for related compounds.