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Coarse‐grained normal mode analyses of protein dynamics rely on the idea that the geometry of a protein structure contains enough information for computing its fluctuations around its equilibrium conformation. This geometry is captured in the form of an elastic network (EN), namely a network of edges between its residues. The normal modes of a protein are then identified with the normal modes of its EN. Different approaches have been proposed to construct ENs, focusing on the choice of the edges that they are comprised of, and on their parameterizations by the force constants associated with those edges. Here we propose new tools to guide choices on these two facets of EN. We study first different geometric models for ENs. We compare cutoff‐based ENs, whose edges have lengths that are smaller than a cutoff distance, with Delaunay‐based ENs and find that the latter provide better representations of the geometry of protein structures. We then derive an analytical method for the parameterization of the EN such that its dynamics leads to atomic fluctuations that agree with experimental B‐factors. To limit overfitting, we attach a parameter referred to as flexibility constant to each atom instead of to each edge in the EN. The parameterization is expressed as a non‐linear optimization problem whose parameters describe both rigid‐body and internal motions. We show that this parameterization leads to improved ENs, whose dynamics mimic MD simulations better than ENs with uniform force constants, and reduces the number of normal modes needed to reproduce functional conformational changes. [ABSTRACT FROM AUTHOR]

Determining the flexibility of structured biomolecules is important for understanding their biological functions. One quantitative measurement of flexibility is the atomic Debye‐Waller factor or temperature B‐factor. Most existing studies are limited to temperature B‐factors of proteins and their prediction. Only one method attempted to predict temperature B‐factors of ribosomal RNA. Here, we developed and compared machine‐learning techniques in prediction of temperature B‐factors of RNAs. The best model based on Support Vector Machines yields Pearson's correction coefficient at 0.51 for fivefold cross validation and 0.50 for the independent test. Analysis of the performance indicates that the model has the best performance on rRNAs, tRNAs, and protein‐bound RNAs, for long chains in particular. The server is available at http://sparks-lab.org/server/RNAflex. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

This study provides gas-phase S1 excited-state geometries along with emission and adiabatic energies for methylated/demethylated and ring-locked analogues of protonated Schiff base retinal models comprising system of five conjugated double bonds (PSB5), using second order multiconfiguration perturbation theory (CASPT2). CASPT2 results serve as reference data to assess the performance of CC2 (second-order approximate coupled cluster singles and doubles) and a commonly used CASSCF/CASPT2 protocol, that is, complete active space self-consistent field (CASSCF) geometry optimization followed by CASPT2 energy calculation. We find that the CASSCF methodology fails to locate planar S1 minimum energy structures for four out of five investigated planar models in contrast to CC2 and CASPT2 methods. However, for those which were found: one planar and two twisted minima, there is an excellent agreement between CASSCF and CASPT2 results in terms of geometrical parameters, one-electron properties, as well as emission and adiabatic energies. CC2 performs well for in-plane S1 minima and their spectroscopic and electronic properties. However, this picture deteriorates for twisted minima. As expected, the CC2 description of the S2 electronic state, with strong multireference and significant double excitation character, is very poor, exhibiting errors in transition energies exceeding 1 eV. They may be substantially diminished by recalculating transition energies with CASPT2 method. Our work shows that CASSCF/CASPT2 and CC2 shortcomings may influence gas-phase retinal analogues' excited state description in a dramatic way. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Protein-nucleic acid complexes are important for many cellular processes including the most essential functions such as transcription and translation. For many protein-nucleic acid complexes, flexibility of both macromolecules has been shown to be critical for specificity and/or function. The flexibility-rigidity index (FRI) has been proposed as an accurate and efficient approach for protein flexibility analysis. In this article, we introduce FRI for the flexibility analysis of protein-nucleic acid complexes. We demonstrate that a multiscale strategy, which incorporates multiple kernels to capture various length scales in biomolecular collective motions, is able to significantly improve the state of art in the flexibility analysis of protein-nucleic acid complexes. We take the advantage of the high accuracy and O( N) computational complexity of our multiscale FRI method to investigate the flexibility of ribosomal subunits, which are difficult to analyze by alternative approaches. An anisotropic FRI approach, which involves localized Hessian matrices, is utilized to study the translocation dynamics in an RNA polymerase. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Computational protein design (CPD) aims at predicting new proteins or modifying existing ones. The computational challenge is huge as it requires exploring an enormous sequence and conformation space. The difficulty can be reduced by considering a fixed backbone and a discrete set of sidechain conformations. Another common strategy consists in precalculating a pairwise energy matrix, from which the energy of any sequence/conformation can be quickly obtained. In this work, we examine the pairwise decomposition of protein MMGBSA energy functions from a general theoretical perspective, and an implementation proposed earlier for CPD. It includes a Generalized Born term, whose many-body character is overcome using an effective dielectric environment, and a Surface Area term, for which we present an improved pairwise decomposition. A detailed evaluation of the error introduced by the decomposition on the different energy components is performed. We show that the error remains reasonable, compared to other uncertainties. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Elastic network models (ENM) are based on the idea that the geometry of a protein structure provides enough information for computing its fluctuations around its equilibrium conformation. This geometry is represented as an elastic network (EN) that is, a network of links between residues. A spring is associated with each of these links. The normal modes of the protein are then identified with the normal modes of the corresponding network of springs. Standard approaches for generating ENs rely on a cutoff distance. There is no consensus on how to choose this cutoff. In this work, we propose instead to filter the set of all residue pairs in a protein using the concept of alpha shapes. The main alpha shape we considered is based on the Delaunay triangulation of the Cα positions; we referred to the corresponding EN as EN( ∞). We have shown that heterogeneous anisotropic network models, called αHANMs, that are based on EN( ∞) reproduce experimental B-factors very well, with correlation coefficients above 0.99 and root-mean-square deviations below 0.1 Å2 for a large set of high resolution protein structures. The construction of EN( ∞) is simple to implement and may be used automatically for generating ENs for all types of ENMs. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

We are presenting a theoretical study of the hydrolysis of a β-lactam antibiotic in gas phase and in aqueous solution by means of hybrid quantum mechanics/molecular mechanics potentials. After exploring the potential energy surfaces at semiempirical and density functional theory (DFT) level, potentials of mean force have been computed for the reaction in solution with hybrid PM3/TIP3P calculations and corrections with the B3LYP and M06-2X functionals. Inclusion of the full molecule of the antibiotic, Cefotaxime, in the gas phase molecular model has been demonstrated to be crucial since its carboxylate group can activate a nucleophilic water molecule. Moreover, the flexibility of the substrate implies the existence of a huge number of possible conformers, some of them implying formation of intramolecular hydrogen bond interaction that can determine the energetics of the conformers defining the different states along the reaction profile. The results show PM3 provides results that are in qualitative agreement with DFT calculations. The free energy profiles show a step-wise mechanism that is kinetically determined by the nucleophilic attack of a water molecule activated by the proton transfer to the carboxylate group of the substrate (the first step). However, since the main role of the β-lactamase would be reducing the free energy barrier of the first step, and keeping in mind the barrier obtained from second intermediate to products, population of this second intermediate could be significant and consequently experimentally detected in β-lactamases, as shown in the literature. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

A convenient approach to compute kinetic isotope effects (KIEs) in condensed phase chemical reactions is via path integrals (PIs). Usually, the primitive approximation is used in PI simulations, although such quantum simulations are computationally demanding. The efficiency of PI simulations may be greatly improved, if higher-order Trotter factorizations of the density matrix operator are used. In this study, we use a higher-order PI method, in conjunction with mass-perturbation, to compute heavy-atom KIE in the decarboxylation of orotic acid in explicit sulfolane solvent. The results are in good agreement with experiment and show that the mass-perturbation higher-order Trotter factorization provides a practical approach for computing condensed phase heavy-atom KIE. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2012 [ABSTRACT FROM AUTHOR]