Kinesin is a two-headed, ATP-driven motor protein that moves processively along microtubules in discrete steps of 8 nm, probably by advancing each of its heads alternately in sequence. Molecular details of how the chemical energy stored in ATP is coupled to mechanical displacement remain obscure. To shed light on this question, a force clamp was constructed, based on a feedback-driven optical trap capable of maintaining constant loads on single kinesin motors. The instrument provides unprecedented resolution of molecular motion and permits mechanochemical studies under controlled external loads. Analysis of records of kinesin motion under variable ATP concentrations and loads revealed several new features. First, kinesin stepping appears to be tightly coupled to ATP hydrolysis over a wide range of forces, with a single hydrolysis per 8-nm mechanical advance. Second, the kinesin stall force depends on the ATP concentration. Third, increased loads reduce the maximum velocity as expected, but also raise the apparent Michaelis-Menten constant. The kinesin cycle therefore contains at least one load-dependent transition affecting the rate at which ATP molecules bind and subsequently commit to hydrolysis. It is likely that at least one other load-dependent rate exists, affecting turnover number. Together, these findings will necessitate revisions to our understanding of how kinesin motors function.

Motor proteins such as kinesin, myosin and polymerase convert chemical energy into work through a cycle that involves nucleotide hydrolysis. Kinetic rates in the cycle that depend upon load identify transitions at which structural changes, such as power strokes or diffusive motions, are likely to occur. Here we show, by modelling data obtained with a molecular force clamp, that kinesin mechanochemistry can be characterized by a mechanism in which a load-dependent isomerization follows ATP binding. This model quantitatively accounts for velocity data over a wide range of loads and ATP levels, and indicates that movement may be accomplished through two sequential 4-nm substeps. Similar considerations account for kinesin processivity, which is found to obey a load-dependent Michaelis-Menten relationship.

We describe the design and construction of two different types of multiple-beam optical tweezers, each equipped with nanometer-resolution position detectors. Multiple optical traps can be created either by splitting a laser beam in two parts, based on its polarization, or time-sharing a single beam among several different locations. The advantages and disadvantages of optical tweezers based on either scheme are discussed, along with details of specific implementations. Various ways to detect microscopic movements of an optically trapped object are presented and compared, including designs that are relatively insensitive to absolute location of a trapped particle within the field of view. Two of many possible applications for such instruments are illustrated: the detection of molecular steps by kinesin motor molecules, and determinations of the stiffness of single microtubules.

The ability of atomic interaction parameters generated using the Automated Topology Builder and Repository version 3.0 (ATB3.0) to predict experimental hydration free enthalpies (DG water) and solvation free enthalpies in the apolar solvent hexane (DG hexane) is presented. For a validation set of 685 molecules the average unsigned error (AUE) between DG water values calculated using the ATB3.0 and experiment is 3.9 kJ•mol-1. The slope of the line of best fit is 1.00, the intercept-1.0 kJ•mol-1 and the R 2 0.90. For the more restricted set of 239 molecules used to validate OPLS3 (J. Chem. Theory Comput. 2016, 12, 281-296.) the AUE using the ATB3.0 is just 2.7 kJ•mol-1 and the R 2 0.93. A roadmap for further improvement of the ATB parameters is presented together with a discussion of the challenges of validating force fields against the available experimental data.

We have found strong supporting evidence for the helical structures of single-stranded nucleic acids by stretching individual molecules of polyadenylic acid [poly(A)] and polycytidylic acid [poly(C)]. Analyzing the force versus extension data using a two-state elastic model in which random-coil domains alternate with rigid helical domains allows one to extract the thermodynamic and structural properties. In addition, it also yields moderate to low cooperativity of the helix-coil transition for poly(A) and poly(C), respectively.

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy.

We have investigated the elastic properties of poly(U), homopolymeric single-stranded RNA molecules that lack any base pairing and stacking interactions and conform to a random-coil structure. Using single-molecule stretching experiments we show that the elastic properties are described by a wormlike chain model for polymer elasticity rather than by a freely jointed chain model as is commonly used for single-stranded DNA. At low [Na+], introduction of a scale-dependent persistence length is required to account for electrostatic contributions.

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