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The principles behind the computation of protein-ligand binding free energies by Monte Carlo integration are described in detail. The simulation provides gas-phase binding free energies that can be converted to aqueous energies by solvation corrections. The direct integration simulation has several characteristics beneficial to free-energy calculations. One is that the number of parameters that must be set for the simulation is small and can be determined objectively, making the outcome more deterministic, with respect to choice of input conditions, as compared to perturbation methods. Second, the simulation is free from assumptions about the starting pose or nature of the binding site. A final benefit is that binding free energies are a direct outcome of the simulation, and little processing is required to determine them. The well-studied T4 lysozyme experimental free energy data and crystal structures were used to evaluate the method.
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Using Monte Carlo simulations, we investigate the structural characteristics of an interacting hard sphere system with shifted charge to elucidate the effect of the non-centrosymmetric interaction on its phase behavior. Two different phase transitions are identified for this model system. Upon increasing the volume fraction, an abrupt liquid-to-crystal transition first occurs at a significantly lower volume fraction in comparison to that of the centro-charged system. This is due to the stronger effective inter-particle repulsion caused by the additional charge anisotropy. Moreover, within the crystal state at higher volume fraction, the system further undergoes a continuous disorder-to-order transition with respect to the charge orientation. Detailed analyses in this work disclose the nature of these transitions, and orientation fluctuation may cause non-centrosymmetric unit cells. The dependence of crystal formation and orientational ordering on temperature was also examined. These findings indicate that the non-centrosymmetric interaction in this work results in additional freedoms to fine-tune the phase diagram and increase the functionalities of materials. Moreover, these model studies are essential to advance our future understanding regarding the fundamental physiochemical properties of novel Janus colloidal particles and protein crystallization conditions.
We describe a Monte Carlo procedure which allows sampling of the disjoint configuration spaces associated with crystalline and fluid phases, within a single simulation. The method utilises biased sampling techniques to enhance the probabilities of gateway states (in each phase) which are such that a global switch (to the other phase) can be implemented. Equilibrium freezing-point parameters can be determined directly; statistical uncertainties prescribed transparently; and finite-size effects quantified systematically. The method is potentially quite general; we apply it to the freezing of hard spheres.
In this paper we consider the problem of RNA folding with pseudoknots. We use a graphical representation in which the secondary structures are described by planar diagrams. Pseudoknots are identified as non-planar diagrams. We analyze the non-planar topologies of RNA structures and propose a classification of RNA pseudoknots according to the minimal genus of the surface on which the RNA structure can be embedded. This classification provides a simple and natural way to tackle the problem of RNA folding prediction in presence of pseudoknots. Based on that approach, we describe a Monte Carlo algorithm for the prediction of pseudoknots in an RNA molecule.
Some of the most arduous and error-prone aspects of precision resummed calculations are related to the partonic hard process, having nothing to do with the resummation. In particular, interfacing to parton-distribution functions, combining various channels, and performing the phase space integration can be limiting factors in completing calculations. Conveniently, however, most of these tasks are already automated in many Monte Carlo programs, such as MadGraph, Alpgen or Sherpa. In this paper, we show how such programs can be used to produce distributions of partonic kinematics with associated color structures representing the hard factor in a resummed distribution. These distributions can then be used to weight convolutions of jet, soft and beam functions producing a complete resummed calculation. In fact, only around 1000 unweighted events are necessary to produce precise distributions. A number of examples and checks are provided, including $e^+e^-$ two- and four-jet event shapes, $n$-jettiness and jet-mass related observables at hadron colliders. Attached code can be used to modify MadGraph to export the relevant leading-order hard functions and color structures for arbitrary processes.
We report results of both Diffusion Quantum Monte Carlo(DMC) method and Reptation Quantum Monte Carlo(RMC) method on the potential energy curve of the helium dimer. We show that it is possible to obtain a highly accurate description of the helium dimer. An improved stochastic reconfiguration technique is employed to optimize the many-body wave function, which is the starting point for highly accurate simulations based on the Diffusion Quantum Monte Carlo(DMC) and Reptation Quantum Monte Carlo (RMC) methods. We find that the results of these methods are in excellent agreement with the best theoretical results at short range, especially recently developed Reptation Quantum Monte Carlo(RMC) method, yield practically accurate results with reduced statistical error, which gives very excellent agreement across the whole potential. For the equilibrium internuclear distance of 5.6 bohr, the calculated electronic energy with Reptation Quantum Monte Carlo(RMC) method is 5.807483599$pm$0.000000015 hartrees and the corresponding well depth is -11.003$pm$0.005 K.
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