Simple quantitative tests to validate sampling from thermodynamic ensembles

It is often difficult to quantitatively determine if a new molecular simulation algorithm or software properly implements sampling of the desired thermodynamic ensemble. We present some simple statistical analysis procedures to allow sensitive determination of whether a de- sired thermodynamic ensemble is properly sampled. We demonstrate the utility of these tests for model systems and for molecular dynamics simulations in a range of situations, includ- ing constant volume and constant pressure simulations, and describe an implementation of the tests designed for end users.Comment: 48 pages, 4 figure

Enhanced sampling in molecular dynamics using metadynamics, replica-exchange, and temperature-acceleration

We review a selection of methods for performing enhanced sampling in molecular dynamics simulations. We consider methods based on collective variable biasing and on tempering, and offer both historical and contemporary perspectives. In collective-variable biasing, we first discuss methods stemming from thermodynamic integration that use mean force biasing, including the adaptive biasing force algorithm and temperature acceleration. We then turn to methods that use bias potentials, including umbrella sampling and metadynamics. We next consider parallel tempering and replica-exchange methods. We conclude with a brief presentation of some combination methods. \ua9 2013 by the author; licensee MDPI, Basel, Switzerland

Current and emerging opportunities for molecular simulations in structure-based drug design

An overview of the current capabilities and limitations of molecular simulation of biomolecular complexes in the context of computer-aided drug design is provided. Steady improvements in computer hardware coupled with more refined representations of energetics are leading to a new appreciation of the driving forces of molecular recognition. Molecular simulations are poised to more frequently guide the interpretation of biophysical measurements of biomolecular complexes. Ligand design strategies emerge from detailed analyses of computed structural ensembles. The feasibility of routine applications to ligand optimization problems hinges upon successful extensive large scale validation studies and the development of protocols to intelligently automate computations

Uji komparasi abnormal return, volume trading activity, dan trading frequency sebelum dan sesudah peristiwa pemilu presiden 2014 (studi empiris pada perusahaan lq-45 di bursa efek indonesia)

Penelitian ini adalah penelitian event study yang dilakukan untuk menguji perbedaan abnormal return, volume trading activity, dan trading frequency sebelum dan sesudah peristiwa Pemilu Presiden Indonesia tahun 2014. Objek dalam penelitian ini adalah perusahaan go public yang tergabung dalam Indeks LQ 45 di Bursa Efek Indonesia untuk periode Februari – Agustus 2014. Sampel diambil dengan menggunakan purposive sampling sebanyak 44 perusahaan. Kriteria yang diambil adalah perusahaan tergabung dalam LQ 45 untuk periode Februari-Agustus 2014, saham perusahaan listing dan aktif diperdagangkan 10 hari sebelum dan sesudah Pemilu Presiden, dan perusahaan tidak melakukan aksi korporasi 10 hari sebelum dan sesudah Pemilu Presiden. Teknik analisis data dimulai dengan melakukan uji normalitas menggunakan uji Kolmogorov - Smirnov, transformasi data, dan data outlier. kemudian melakukan uji hipotesis menggunakan uji paired t – test dan Wilcoxon Signed Rank Test untuk membandingkan perbedaan sebelum dan sesudah terjadinya peristiwa Pemilu Presiden Indonesia tahun 2014. Pada pengujian hipotesis menunjukkan bahwa variabel volume trading activity dan trading frequency ditemukan perbedaan yang signifikan sebelum dan sesudah Pemilu Presiden Indonesia tahun 2014. Sedangkan variabel lainnya yaitu abnormal return tidak ditemukan perbedaan yang signifikan sebelum dan sesudah Pemilu Presiden Indonesia tahun 2014

Potency-Enhancing Mutations of Gating Modifier Toxins for the Voltage-Gated Sodium Channel NaV1.7 Can Be Predicted Using Accurate Free-Energy Calculations

Gating modifier toxins (GMTs) isolated from venomous organisms such as Protoxin-II (ProTx-II) and Huwentoxin-IV (HwTx-IV) that inhibit the voltage-gated sodium channel NaV1.7 by binding to its voltage-sensing domain II (VSDII) have been extensively investigated as non-opioid analgesics. However, reliably predicting how a mutation to a GMT will affect its potency for NaV1.7 has been challenging. Here, we hypothesize that structure-based computational methods can be used to predict such changes. We employ free-energy perturbation (FEP), a physics-based simulation method for predicting the relative binding free energy (RBFE) between molecules, and the cryo electron microscopy (cryo-EM) structures of ProTx-II and HwTx-IV bound to VSDII of NaV1.7 to re-predict the relative potencies of forty-seven point mutants of these GMTs for NaV1.7. First, FEP predicted these relative potencies with an overall root mean square error (RMSE) of 1.0 ± 0.1 kcal/mol and an R2 value of 0.66, equivalent to experimental uncertainty and an improvement over the widely used molecular-mechanics/generalized born-surface area (MM-GB/SA) RBFE method that had an RMSE of 3.9 ± 0.8 kcal/mol. Second, inclusion of an explicit membrane model was needed for the GMTs to maintain stable binding poses during the FEP simulations. Third, MM-GB/SA and FEP were used to identify fifteen non-standard tryptophan mutants at ProTx-II[W24] predicted in silico to have a at least a 1 kcal/mol gain in potency. These predicted potency gains are likely due to the displacement of high-energy waters as identified by the WaterMap algorithm for calculating the positions and thermodynamic properties of water molecules in protein binding sites. Our results expand the domain of applicability of FEP and set the stage for its prospective use in biologics drug discovery programs involving GMTs and NaV1.7

Simple Predictive Models of Passive Membrane Permeability Incorporating Size-Dependent Membrane-Water Partition

We investigate the relationship between passive permeability and molecular size, in the context of solubility-diffusion theory, using a diverse compound set with molecular weights ranging from 151 to 828, which have all been characterized in a consistent manner using the RRCK cell monolayer assay. Computationally, each compound was subjected to extensive conformational search and physics-based permeability prediction, and multiple linear regression analyses were subsequently performed to determine, empirically, the relative contributions of hydrophobicity and molecular size to passive permeation in the RRCK assay. Additional analyses of Log <i>D</i> and PAMPA data suggest that these measurements are not size selective, a possible reason for their sometimes weak correlation with cell-based permeability