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We have used high resolution AFM based dynamic force spectroscopy to investigate peptide-lipid membrane interactions by measuring the detachment (last-rupture) force distribution, P(F), and the corresponding force dependent rupture rate, k(F), for two different peptides and lipid bilayers. The measured quantities, which differed considerably for different peptides, lipid-membranes, AFM tips (prepared under identical conditions), and retraction speeds of the AFM cantilever, could not be described in terms of the standard theory, according to which detachment occurs along a single pathway, corresponding to a diffusive escape process across a free energy barrier. In particular, the prominent retraction speed dependence of k(F) was a clear indication that peptide-lipid membrane dissociation occurs stochastically along several detachment pathways. Thereby, we have formulated a general theoretical approach for describing P(F) and k(F), by assuming that peptide detachment from lipid membranes occurs, with certain probability, along a few dominant diffusive pathways. This new method was validated through a consistent interpretation of the experimental data. Furthermore, we have found that for moderate retraction speeds at intermediate force values, k(F) exhibits catch-bond behavior (i.e. decreasing detachment rate with increasing force). According to the proposed model this behavior is due to the stochastic mixing of individual detachment pathways which do not convert or cross during rupture. To our knowledge, such catch-bond mechanism has not been proposed and demonstrated before for a peptide-lipid interaction.

In recent years \textit{in silico} protein structure prediction reached a level where a variety of servers can generate large pools of near-native structures. However, the identification and further refinement of the best structures from the pool of decoys remain problematic. To address these issues, we have developed a selective refinement protocol (SRP), and a molecular dynamics (MD) simulation based ranking method (MDR). In SRP the refinement of structures is accomplished by using the relax mode of the Rosetta software package, subject to specific constraints determined by the type and complexity of the target. The final best models are selected with MDR by testing their relative stability against gradual heating during all atom MD simulations. We have implemented the selective refinement protocol and the MDR method in Mufold-MD, our fully automated protein structure prediction server. Mufold-MD was one of the top servers in the CASP10 competition.

Organs are in high demand. Tissue engineering and regenerative medicine might be the answer to this challenge of the 21st century. Towards this goal our objective is to optimize the conditions for cells to self assemble into functional structures, such as tissues and eventually organoids. To facilitate self-assembly we employ the technology of bioprinting. To maintain the extended cellular assemblies, they need to be vascularized. Thus we first concentrate on the fabrication of blood vessels. We prepare convenient bioink particles, multicellular units composed of the relevant cell types and we deposit them into a geometry, consistent with the shape of the vessels. Self-assembly and the maturation of the construct takes place post-printing in special-purpose bioreactors by the fusion of the bioink units and the rearrangement of the cells within them. The time to achieve near physiological biomechanical properties has so far been found by trial and error. We have developed an experimental-theoretical-computational framework to optimize the postprinting maturation process, in particular the fusion of the bioink units. This paper focuses on the experimental component of this formalism, in particular on the fusion of spherical and cylindrical bioink units. The connection between experiments and computer simulations are guided by theory. Here we report the results of extended fusion experiments and on their comparison with predictions of the theory. The excellent agreement we find, on one hand, provides a verification of the theoretical component of the formalism, and, on the other hand, the input for the computational component of the formalism. Specifically, our experiments, together with the theory, allow the calibration of the basic simulation parameters, which in turn allows to fully implement the computational component of the formalism to optimize the fabrication of blood vessels through the bioprinting process.

Retinoic acid receptor (RAR) is a ligand-dependent transcription factor that regulates the expression of genes involved in cell growth, differentiation, and development. Binding of the retinoic acid hormone to RAR is accompanied by conformational changes in the protein which induce transactivation or transrepression of the target genes. In this paper we present a study of the hormone binding/unbinding process in order to clarify the role of some of the amino acid contacts and identify possible pathways of the all-trans retinoic acid binding/unbinding to/from human retinoic acid receptor (hRAR)-g. Three possible pathways were explored using steered molecular dynamics simulations. Unbinding was induced on a time scale of 1 ns by applying external forces to the hormone. The simulations suggest that the hormone may employ one pathway for binding and an alternative "back door" pathway for unbinding., Comment: 10 pages, PDF file

Molecular dynamics simulations are carried out to investigate the binding of the estrogen receptor, a member of the nuclear hormone receptor family, to specific and non-specific DNA. Two systems have been simulated, each based on the crystallographic structure of a complex of a dimer of the estrogen receptor DNA binding domain with DNA. One structure includes the dimer and a consensus segment of DNA, ds(CCAGGTCACAGTGACCTGG); the other structure includes the dimer and a nonconsensus segment of DNA, ds(CCAGAACACAGTGACCTGG). The simulations involve an atomic model of the protein-DNA complex, counterions, and a sphere of explicit water with a radius of 45 A. The molecular dynamics package NAMD was used to obtain 100 ps of dynamics for each system with complete long-range electrostatic interactions. Analysis of the simulations revealed differences in the protein-DNA interactions for consensus and nonconsensus sequences, a bending and unwinding of the DNA, a slight rearrangement of several amino acid side chains, and inclusion of water molecules at the protein-DNA interface region. Our results indicate that binding specificity and stability is conferred by a network of direct and water mediated protein-DNA hydrogen bonds. For the consensus sequence, the network involves three water molecules, residues Glu-25, Lys-28, Lys-32, Arg-33, and bases of the DNA. The binding differs for the nonconsensus DNA sequence in which case the fluctuating network of hydrogen bonds allows water molecules to enter the protein-DNA interface. We conclude that water plays a role in furnishing DNA binding specificity to nuclear hormone receptors.

Molecular dynamics simulations have been employed to determine the optimal conformation of an estrogen receptor DNA binding domain dimer bound to a consensus response element, ds(AGGTCACAGTGACCT), and to a nonconsensus response element, ds(AGAACACAGTGACCT). The structures simulated were derived from a crystallographic structure and solvated by a sphere (45-A radius) of explicit water and counterions. Long-range electrostatic interactions were accounted for during 100-ps simulations by means of a fast multipole expansion algorithm combined with a multiple time-step scheme in the molecular dynamics package NAMD. The simulations demonstrate that the dimer induces a bent and underwound (10.7 bp/turn) conformation in the DNA. The bending reflects the dyad symmetry of the receptor dimer and can be described as an S-shaped curve in the helical axis of DNA when projected onto a plane. A similar bent and underwound conformation is observed for nucleosomal DNA near the nucleosome's dyad axis that reflects the symmetry of the histone octamer. We propose that when a receptor dimer binds to a nucleosome, the most favorable dimer-DNA and histone-DNA interactions are achieved if the respective symmetry axes are aligned. Such positioning of a receptor dimer over the dyad of nucleosome B in the mouse mammary tumor virus promoter is in agreement with experiment.

The mechanosensitive channel of large conductance (MscL) in prokaryotes plays a crucial role in exocytosis as well as in the response to osmotic downshock. The channel can be gated by tension in the membrane bilayer. The determination of functionally important residues in MscL, patch-clamp studies of pressure-conductance relationships, and the recently elucidated crystal structure of MscL from Mycobacterium tuberculosis have guided the search for the mechanism of MscL gating. Here, we present a molecular dynamics study of the MscL protein embedded in a fully hydrated POPC bilayer. Simulations totaling 3ns in length were carried out under conditions of constant temperature and pressure using periodic boundary conditions and full electrostatics. The protein remained in the closed state corresponding to the crystal structure, as evidenced by its impermeability to water. Analysis of equilibrium fluctuations showed that the protein was least mobile in the narrowest part of the channel. The gating process was investigated through simulations of the bare protein under conditions of constant surface tension. Under a range of conditions, the transmembrane helices flattened as the pore widened. Implications for the gating mechanism in light of these and experimental results are discussed.

Previous studies have shown that under certain conditions living tissues and multicellular aggregates behave as highly visco-elastic liquids. Tissue liquidity, brought about by cellular adhesion and motility, forms the basis of the newly developed bioprinting technology, which is used to design and build 3D tissue constructs by employing computer-controlled layer-by-layer deposition of bioink (submillimeter size cell aggregate) droplets onto biopaper (biocompatible gel). In order to describe and predict the self-assembly process of bioprinted multicellular constructs we have developed a computer simulation method referred to as cellular particle dynamics (CPD). In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined directly by recording the trajectories of all CPs through integration of their equations of motion. The cellular level CP model parameters are related to the experimentally measurable tissue level biophysical quantities (e.g., surface tension, viscosity and shear modulus) by comparing the results from selected benchmark experiments (e.g., compression and fusion of spherical cell aggregates) with those from the corresponding CPD simulations. Here we apply the CPD method to describe and predict in silico the post-bioprinting time evolution of the formation of tubular multicellular structures (which resemble primitive blood vessels). Our CPD simulations take substantially less time and effort than the corresponding experiments and, most importantly, provide results in good agreement with the experimental ones.Work supported by the National Science Foundation [FIBR-0526854]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Individual atoms and lipid molecules in biologically relevant phospholipid bilayers have an extremely rich dynamics that extend on a wide range of time and length scales. Computer modeling and simulations can be used effectively both to investigate the dynamics of such complex systems and to interpret the results from a variety of experimental techniques employed to probe such systems. Here we present an all-atom molecular dynamics (MD) simulation, combined with theoretical modeling, to investigate the dynamics of selected lipid atoms and lipid molecules in a hydrated diyristoyl-phosphatidylcholine (DMPC) lipid bilayer. From the analysis of a 0.1 microsecond MD trajectory we find that the time evolution of the mean square displacement (MSD) of lipid atoms and molecules exhibits three well separated dynamical regions: (1) for short times (t < 10 fs) the motion is ballistic with a quadratic in time MSD; (2) for intermediate times (10 ps

The fundamental processes by which proteins recognize and bind to nucleic acids are critical to understanding cellular function. To explore the factors involved in protein-DNA recognition, we used hydrostatic pressure to perturb the binding of the BamHI endonuclease to cognate DNA, both in experiment and in molecular dynamic simulations. A new technique of high-pressure gel mobility shift analysis was used to test the effects of elevated hydrostatic pressure on the binding of BamHI to its cognate recognition sequence. Upon application of a pressure of 500 bar, the equilibrium dissociation constant of BamHI binding to the cognate site was found to increase nearly 10-fold. A challenge has been to link this type of pure thermodynamic measurement to functional events occurring at the molecular level. Thus, we used molecular dynamic simulations at both ambient and elevated pressures to reveal details of the direct and water-mediated interactions between BamHI and cognate DNA, which allow explanation of the effects of pressure on site-specific protein-DNA binding and complex stability.

Bioprinting is a computer-controlled procedure for building three-dimensional tissue constructs via layer-by-layer delivery of cells and supportive hydrogels. To describe the post-printing self-assembly of multicellular structures, we performed computer simulations that incorporate a basic principle of developmental biology, the differential adhesion hypothesis (DAH). DAH states that cell motility combined with differences in the adhesive properties of different cell types yields tissue conformations with the largest number of strong bonds between cells. Metropolis Monte Carlo (MMC) simulations based on DAH predicted the emergence of long-lived structures (cell sheets, toroidal and tubular constructs) in accord with experiments. The MMC method, however, does not describe time evolution. We propose a kinetic Monte Carlo (KMC) approach, where transition rates are associated with possible rearrangements of cells. The system is represented on a lattice, with sites occupied either by cells or by volume elements of cell culture medium. We associate rates to swapping cells with nearest neighbors of different types (cells or medium). The new approach was tested against experiments on cell sorting within an aggregate composed of two cell types. In quantitative studies, we determined the time evolution of the interfacial area between two fusing spherical cell aggregates experimentally, analytically and by KMC simulations. In the analytic approach, we used continuum hydrodynamics to describe the coalescence of two identical, highly viscous liquid droplets, and obtained good agreement with experiments on smooth muscle cell aggregates. Apart from the early stages of fusion, the KMC method predicted a fusion pattern similar to the experimental one. Comparison with measurements allowed relating KMC transition rates to experimental time scales. Our results indicate that the KMC method can give an accurate account of the time evolution of complex cellular structures, thus it may be a useful tool for tissue engineering applications. Work supported by NSF-056854.

In recent years in silico protein structure prediction reached a level where a variety of servers can generate large pools of near-native structures. However, the identification and further refinement of the best structures from the pool of decoys continue to remain problematic. To address these issues we have developed the MUFOLD-MD server that uses the Rosetta software for structure refinement and a molecular dynamics (MD) based ranking (MDR) method for structure selection. The refinement of the selected structures is done by employing Rosetta's relax mode, subject to certain constraints. MDR selects the best structures by testing their relative stability against gradual heating during all atom MD simulations. The MUFOLD-MD server uses three sequential steps consisting of, i.e., structure: 1) generation, 2) refinement and 3) selection. 1) By using sequence-profile alignment (e.g., PSI-BLAST) and profile-profile alignment (e.g., HHSearch) methods, the query sequence is classified as either “hard” or “easy” target. For hard targets, models are generated using the Rosetta 3.2 software (ab initio method) and then ranked by using their Rosetta energy score. For easy targets, models are generated with the Multi-Dimensional Scaling (MDS) method and then ranked using the OPUS_Ca scoring function. 2) The structures (subject to certain constraints) are refined by employing the “relax” mode of Rosetta 3.2. 3) The MDR method is used to select the top 5 structures as the output of the server. Our MUFOLD-MD server was tested in both CASP8 and CASP9 competitions. Based on the official CAP8 results, MUFOLD-MD was ranked as number one server in the Free Modeling category.

In spite of recent advances, the problem of protein structure prediction from the amino acid sequence remains a challenging one. In general, once a large set of model protein structures is predicted one needs to define selection criteria for identifying the structure that is the closest to the native one. The most common way of discriminating between predicted structures of a given protein is to employ either knowledge or physics based energy functions. Here we present an alternative ranking method of the predicted structures of a protein by testing their stability during gradual heating achieved by all atom molecular dynamics (MD) simulations. In general, the smaller the RMSD of the structure of a protein is (with respect to its native one) the more stable this structure is. Thus, one can rank the quality of these structures by comparing the relative stability of the predicted structures against gradual heating. We refer to this approach as the MD-Ranking (MDR) method. We have successfully tested the MDR method on several sets of proteins. We have also tested the MDR method in the 2008 Critical Assessment of Techniques for Protein Structure Prediction (CASP8) competition as part of our MUFOLD-MD server, which worked as follows: i) it generated 10,000 structures using the ab initio method of the Rosetta software, ii) from these, 64 structures with the lowest Rosetta energy were selected, and iii) re-ranked with the MDR method. The top 5 models, with the best MDR score, were submitted to the CASP8 organizers. Based on the official CAP8 results, MUFOLD-MD was ranked as number one server in the Free Modeling category.Work supported by a grant from NIH [R21/R33-GM078601]. Major computer time was provided by the University of Missouri Bioinformatics Consortium.

Inelastic neutron scattering (INS) experiments, based on latest generation of neutron sources, allow us to gain insight into the complex dynamics of lipid molecules in biologically relevant phospholipid bilayers. However, the proper interpretation of the INS scattering experiments requires theoretical and computational models that correctly capture the main features of lipid dynamics at atomic and molecular levels. To this end, here we use a 0.1 microsecond all-atom molecular dynamics simulation to investigate the dynamics of lipid atoms and molecules in a hydrated diyristoyl-phosphatidycholine (DMPC) lipid bilayer. First, as predicted by theories of polymer dynamics, we identify three well separated dynamic regimes in the mean square displacement of the lipid atoms and molecules: (1) a ballistic regime where the mean square displacement increases as the square of time for t 30 nanoseconds. Next, we show that the cumulant approximation of the self-intermediate scattering function (which is the inverse Fourier transform of the dynamic structure factor measured in INS experiments) is in very good agreement with the simulation results, and allows us to connect the three time scales in the mean square displacement to the interpretation of neutron scattering results. Finally, we focus on the hydrogen atoms (which represent the main source of the incoherent INS signal) in the lipids and draw conclusions about the lipid dynamics by examining the wave-vector dependence of the intermediate scattering function.Computer time was generously provided by the University of Missouri Bioinformatics Consortium.

The structure and dynamics of hydration water at the surface of biomolecules (e.g., proteins and lipids in biological membranes) are fundamental for their stability and functioning. Due to the interactions at the surface of a solvated biological membrane, the dynamics of the hydration waters and that of the membrane molecules are to some degree correlated. In spite of previous efforts, little is known about the time and length scale of these correlations. Here, we report on a 0.1 microsecond all-atom molecular dynamics simulation study aimed at investigating the dynamics of the hydration water at the interface of a dimyristoyl-phosphatidylcholine (DMPC) lipid bilayer. We find that, mainly due to hydrogen bonding with the lipid bilayer, the mean-square displacement of the interfacial water has four well defined dynamical regimes, with characteristic power law (t⊥n) time (t) dependence: (1) ballistic, for t 10 ns, with n=1. The super-diffusive regime (characterized by a self intermediate scattering function with compressed exponential relaxation) of the hydration water molecules has not been observed before, and possibly determines the length and time scales of the correlation between the dynamics of water and lipid membrane. Furthermore, the water-lipid interactions give rise to an average liquid-like structure of the interfacial water molecules on a length scale corresponding to the average lipid-lipid separation, and the relaxation time of this structure is an order of magnitude larger than what is expected from the self motion of the water.Computer time was generously provided by the University of Missouri Bioinformatics Consortium.