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The proteins structure can be mainly classified into four classes: all-α, all-β, α/β, and α + β protein according to their chain fold topologies. For the purpose of predicting the protein structural class, a new predicting algorithm, in which the increment of diversity combines with Quadratic Discriminant analysis, is presented to study and predict protein structural class. On the basis of the concept of the pseudo amino acid composition (Chou, Proteins: Struct Funct Genet 2001, 43, 246; Erratum: Proteins Struct Funct Genet 2001, 44, 60), 400 dipeptide components and 20 amino acid composition are, respectively, selected as parameters of diversity source. Total of 204 nonhomologous proteins constructed by Chou (Chou, Biochem Biophys Res Commun 1999, 264, 216) are used for training and testing the predictive model. The predicted results by using the pseudo amino acids approach as proposed in this paper can remarkably improve the success rates, and hence the current method may play a complementary role to other existing methods for predicting protein structural classification. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 [ABSTRACT FROM AUTHOR]

The Molecular Fractionation with Conjugate Caps (MFCC) method is a popular fragmentation method for the quantum-chemical treatment of proteins. However, it does not account for interactions between the amino acid fragments, such as intramolecular hydrogen bonding. Here, we present a combination of the MFCC fragmentation scheme with a second-order many-body expansion (MBE) that consistently accounts for all fragment--fragment, fragment--cap, and cap--cap interactions, while retaining the overall simplicity of the MFCC scheme with its chemically meaningful fragments. We show that with the resulting MFCC-MBE(2) scheme, the errors in the total energies of selected polypeptides and proteins can be reduced by up to one order of magnitude and relative energies of different protein conformers can be predicted accurately. [ABSTRACT FROM AUTHOR]

We illustrate solving the protein alignment problem exactly using the algorithm VESPA (very efficient search for protein alignment). We have compared our result with the approximate solution obtained with BLAST (basic local alignment search tool) software, which is currently the most widely used for searching for protein alignment. We have selected human and mouse proteins having around 170 amino acids for comparison. The exact solution has found 78 pairs of amino acids, to which one should add 17 individual amino acid alignments giving a total of 95 aligned amino acids. BLAST has identified 64 aligned amino acids which involve pairs of more than two adjacent amino acids. However, the difference between the two outputs is not as large as it may appear, because a number of amino acids that are adjacent have been reported by BLAST as single amino acids. So if one counts all amino acids, whether isolated (single) or in a group of two and more amino acids, then the count for BLAST is 89 and for VESPA is 95, a difference of only six. [ABSTRACT FROM AUTHOR]

A novel approach to the problem of protein alignments is described, which in comparison with existing approaches is visibly more efficient. This approach is based on superposition of amino acid adjacency matrices of a pair of proteins, which have been modified to record the sequential order of amino acids. As a result, one obtains simultaneously all segments of the two proteins which are shifted relative to one another by one or more positions in either directions, without need of a prior exhaustive search for an alignment that included unproductive directions and unknown displacement steps. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2012 [ABSTRACT FROM AUTHOR]

Computation of the thermodynamic consequences of protein mutations holds great promise in protein biophysics and design. Alchemical free energy methods can give improved estimates of mutational free energies, and are already widely used in calculations of relative and absolute binding free energies in small molecule design problems. In principle, alchemical methods can address any amino acid mutation with an appropriate alchemical pathway, but identifying a strategy that produces such a path for proline and glycine mutations is an ongoing challenge. Most current strategies perturb only side chain atoms, while proline and glycine mutations also alter the backbone parameters and backbone ring topology. Some strategies also perturb backbone parameters and enable glycine mutations. This work presents a strategy that enables both proline and glycine mutations and comprises two key elements: a dual backbone with restraints and scaling of bonded terms, facilitating backbone parameter changes, and a soft bond in the proline ring, enabling ring topology changes in proline mutations. These elements also have utility for core hopping and macrocycle studies in computer‐aided drug design. This new strategy shows slight improvements over an alternative side chain perturbation strategy for a set T4 lysozyme mutations lacking proline and glycine, and yields good agreement with experiment for a set of T4 lysozyme proline and glycine mutations not previously studied. To our knowledge this is the first report comparing alchemical predictions of proline mutations with experiment. With this strategy in hand, alchemical methods now have access to the full palette of amino acid mutations. [ABSTRACT FROM AUTHOR]

Accurate electrostatics necessitates the use of multipole moments centered on nuclei or extra point charges centered away from the nuclei. Here, we follow the former alternative and investigate the convergence behavior of atom-atom electrostatic interactions in the pilot protein crambin. Amino acids are cut out from a Protein Data Bank structure of crambin, as single amino acids, di, or tripeptides, and are then capped with a peptide bond at each side. The atoms in the amino acids are defined through Quantum Chemical Topology (QCT) as finite volume electron density fragments. Atom-atom electrostatic energies are computed by means of a multipole expansion with regular spherical harmonics, up to a total interaction rank of L = ℓA+ ℓB + 1 = 10. The minimum internuclear distance in the convergent region of all the 15 possible types of atom-atom interactions in crambin that were calculated based on single amino acids are close to the values calculated from di and tripeptides. Values obtained at B3LYP/aug-cc-pVTZ and MP2/aug-cc-pVTZ levels are only slightly larger than those calculated at HF/6-31G(d,p) level. This convergence behavior is transferable to the well-known amyloid beta polypeptide Aβ1-42. Moreover, for a selected central atom, the influence of its neighbors on its multipole moments is investigated, and how far away this influence can be ignored is also determined. Finally, the convergence behavior of AMBER becomes closer to that of QCT with increasing internuclear distance. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

NMR chemical shifts (CSs: δNNH, δCα, δCβ, δC′, δHNH, and δHα) were computed for the amino acid backbone conformers (αL, βL, γL, δL, εL, αD, γD, δD, and εD [Perczel et al., J Am Chem Soc 1991, 113, 6256]) modeled by oligoalanine structures. Topological differences of the extended fold were investigated on single β-strands, hairpins with type I and II β-turns, as well as double- and triple-stranded β-sheet models. The so-called 'capping effect' was analyzed: residues at the termini of a homoconformer sequence unit usually have different CSs than the central residues of an adequately long homoconformer model. In heteroconformer sequences capping effect ruins the direct applicability of several chemical shift types (δHNH, δC′, and δNNH) for backbone structure determination of the parent residue. Experimental δHα, δCα, and δCβ values retrieved from protein database are in good agreement with the relevant computed data in the case of the common backbone conformers (αL, βL, γL, and εL), even though neighboring residue effects were not accounted for. Experimental and computed ΔδHα-ΔδCα, ΔδHα-ΔδCβ, and ΔδCα-ΔδCβ maps give qualitatively the same picture, that is, the positions of the backbone conformers relative to each other are very similar. This indicates that the Hα, Cα, and Cβ chemical shifts of alanine depend considerably on the backbone fold of the parent residue also in proteins. We provide tabulated CSs of the chiral amino acids that may predict the various structures of the residues. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011 [ABSTRACT FROM AUTHOR]

A computational model, IMP-TYPE, is proposed for the classification of five types of integral membrane proteins from protein sequence. The proposed model aims not only at providing accurate predictions but most importantly it incorporates interesting and transparent biological patterns. When contrasted with the best-performing existing models, IMP-TYPE reduces the error rates of these methods by 19 and 34% for two out-of-sample tests performed on benchmark datasets. Our empirical evaluations also show that the proposed method provides even bigger improvements, i.e., 29 and 45% error rate reductions, when predictions are performed for sequences that share low (40%) identity with sequences from the training dataset. We also show that IMP-TYPE can be used in a standalone mode, i.e., it duplicates significant majority of correct predictions provided by other leading methods, while providing additional correct predictions which are incorrectly classified by the other methods. Our method computes predictions using a Support Vector Machine classifier that takes feature-based encoded sequence as its input. The input feature set includes hydrophobic AA pairs, which were selected by utilizing a consensus of three feature selection algorithms. The hydrophobic residues that build up the AA pairs used by our method are shown to be associated with the formation of transmembrane helices in a few recent studies concerning integral membrane proteins. Our study also indicates that Met and Phe display a certain degree of hydrophobicity, which may be more crucial than their polarity or aromaticity when they occur in the transmembrane segments. This conclusion is supported by a recent study on potential of mean force for membrane protein folding and a study of scales for membrane propensity of amino acids. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2009 [ABSTRACT FROM AUTHOR]

Using the pseudo amino acid (PseAA) composition to represent the sample of a protein can incorporate a considerable amount of sequence pattern information so as to improve the prediction quality for its structural or functional classification. However, how to optimally formulate the PseAA composition is an important problem yet to be solved. In this article the grey modeling approach is introduced that is particularly efficient in coping with complicated systems such as the one consisting of many proteins with different sequence orders and lengths. On the basis of the grey model, four coefficients derived from each of the protein sequences concerned are adopted for its PseAA components. The PseAA composition thus formulated is called the “grey-PseAA” composition that can catch the essence of a protein sequence and better reflect its overall pattern. In our study we have demonstrated that introduction of the grey-PseAA composition can remarkably enhance the success rates in predicting the protein structural class. It is anticipated that the concept of grey-PseAA composition can be also used to predict many other protein attributes, such as subcellular localization, membrane protein type, enzyme functional class, GPCR type, protease type, among many others. © 2008 Wiley Periodicals, Inc. J Comput Chem 2008. [ABSTRACT FROM AUTHOR]

The effect of solvation on the electronic structure of the ubiqutin protein was analyzed using the ab initio fragment molecular orbital (FMO) method. FMO calculations were performed for the protein in vacuo, and the protein was immersed in an explicit solvent shell as thick as 12 Å at the HF or MP2 level by using the 6-31G* basis set. The protein's physical properties examined were the net charge, the dipole moment, the internal energy, and the solvent interaction energy. Comparison of the computational results revealed the following changes in the protein upon solvation. First, the positively charged amino acid residues on the protein surface drew electrons from the solvent, while the negatively charged ones transfer electrons to the solvent. Second, the dipole moment of the protein was enhanced as a result of the polarization. Third, the internal energy of the protein was destabilized, but the destabilization was more than compensated for by the generation of a favorable protein–solvent interaction. Finally, the energetic changes were elicited both by the electron correlation effect of the first solvent shell and by the electrostatic effect of more distant solvent molecules. These findings were consistent with the picture of the solvated protein being a polarizable molecule dissolved in a dielectric media. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 [ABSTRACT FROM AUTHOR]

Alanine scanning mutagenesis of protein–protein interfacial residues can be applied to a wide variety of protein complexes to understand the structural and energetic characteristics of the hot-spots. Binding free energies have been estimated with reasonable accuracy with empirical methods, such as Molecular Mechanics/Poisson-Boltzmann surface area (MM-PBSA), and with more rigorous computational approaches like Free Energy Perturbation (FEP) and Thermodynamic Integration (TI). The main objective of this work is the development of an improved methodological approach, with less computational cost, that predicts accurately differences in binding free energies between the wild-type and alanine mutated complexes (ΔΔGbinding). The method was applied to three complexes, and a mean unsigned error of 0.80 kcal/mol was obtained in a set of 46 mutations. The computational method presented here achieved an overall success rate of 80% and an 82% success rate in residues for which alanine mutation causes an increase in the binding free energy > 2.0 kcal/mol (warm- and hot-spots). This fully atomistic computational methodological approach consists in a computational Molecular Dynamics simulation protocol performed in a continuum medium using the Generalized Born model. A set of three different internal dielectric constants, to mimic the different degree of relaxation of the interface when different types of amino acids are mutated for alanine, have to be used for the proteins, depending on the type of amino acid that is mutated. This method permits a systematic scanning mutagenesis of protein–protein interfaces and it is capable of anticipating the experimental results of mutagenesis, thus guiding new experimental investigations. © 2006 Wiley Periodicals, Inc. J Comput Chem 28: 644–654, 2007 [ABSTRACT FROM AUTHOR]