sesA: A Program for the Analytic Computation of Solvent-Excluded Surface Areas.

The surface area of a molecule, an inherent geometric property of its structure, plays important roles in its solvation and functioning. Here we present an accurate and robust program, sesA, for the analytic computation of solvent-excluded surface (SES) areas. The accuracy and robustness are achieved through the analytic computations of all the solvent-accessible surface (SAS) regions for a surface atom and probe-probe intersections.

Protein secondary structure assignment using pc-polyline and convolutional neural network.

Motivation: The assignment of protein secondary structure elements (SSEs) underpins structural analysis and prediction. The backbone of a protein could be adequately represented using a pc-polyline that passes through the centers of its peptide planes. One salient feature of pc-polyline representation is that the secondary structure of a protein becomes recognizable in a matrix whose elements are the pairwise distances between two peptide plane centers.

The characterization of pc-polylines representing protein backbones.

The backbone of a protein is typically represented as either a C -polyline, a three-dimensional (3D) polyline that passes through the C atoms, or a tuple of ϕ,ψ pairs while its fold is usually assigned using the 3D topological arrangement of the secondary structure elements (SSEs). It is tricky to obtain the SSE composition for a protein from the C -polyline representation while its 3D SSE arrangement is not apparent in the two-dimensional (2D) ϕ,ψ representation. In this article, we first represent the backbone of a protein as a pc-polyline that passes through the centers of its peptide planes.

Evaluation of Low Pressure and Vapor Heat as a Phytosanitary Treatment For Chlorophorus annularis (Coleoptera: Cerambycidae) in Postharvest Bamboo Poles.

The bamboo longhorned beetle, Chlorophorus annularis (Fabricius), distributed widely in Asian countries attacking live or postharvest bamboo, is a concern to the international trade of bamboo materials. With the phase out of methyl bromide for quarantine and preshipment use, a reliable, safe, and environmentally friendly phytosanitary treatment is needed as an alternative. In this study, the thermotolerance of C.

Comparison of Populations of Ceratitis capitata (Diptera: Tephritidae) from Three Continents for Susceptibility to Cold Phytosanitary Treatment and Implications for Generic Cold Treatments.

The Mediterranean fruit fly, Ceratitis capitata (Wiedemann) (Diptera: Tephritidae), is arguably the most significant and studied quarantine pest of fresh fruits. There is well over a century of research observations on its response to cold, first as it pertains to shipment of fruits using cold temperatures to preserve fruit quality and how that may aid the survival and distribution of the pest, and then the use of colder temperatures to kill the pest in fruit shipments. Cold tolerance at 1.

A New Secondary Structure Assignment Algorithm Using Cα Backbone Fragments.

The assignment of secondary structure elements in proteins is a key step in the analysis of their structures and functions. We have developed an algorithm, SACF (secondary structure assignment based on Cα fragments), for secondary structure element (SSE) assignment based on the alignment of Cα backbone fragments with central poses derived by clustering known SSE fragments. The assignment algorithm consists of three steps: First, the outlier fragments on known SSEs are detected.

Amino Acids in Nine Ligand-Prefer Ramachandran Regions.

Several secondary structures, such as π-helix and left-handed helix, have been frequently identified at protein ligand-binding sites. A secondary structure is considered to be constrained to a specific region of dihedral angles. However, a comprehensive analysis of the correlation between main chain dihedral angles and ligand-binding sites has not been performed.

An Algorithm for Protein Helix Assignment Using Helix Geometry.

Helices are one of the most common and were among the earliest recognized secondary structure elements in proteins. The assignment of helices in a protein underlies the analysis of its structure and function. Though the mathematical expression for a helical curve is simple, no previous assignment programs have used a genuine helical curve as a model for helix assignment.

An Accurate Model for Biomolecular Helices and Its Application to Helix Visualization.

Helices are the most abundant secondary structural elements in proteins and the structural forms assumed by double stranded DNAs (dsDNA). Though the mathematical expression for a helical curve is simple, none of the previous models for the biomolecular helices in either proteins or DNAs use a genuine helical curve, likely because of the complexity of fitting backbone atoms to helical curves. In this paper we model a helix as a series of different but all bona fide helical curves; each one best fits the coordinates of four consecutive backbone Cα atoms for a protein or P atoms for a DNA molecule.

A geometric clustering algorithm with applications to structural data.

An important feature of structural data, especially those from structural determination and protein-ligand docking programs, is that their distribution could be mostly uniform. Traditional clustering algorithms developed specifically for nonuniformly distributed data may not be adequate for their classification. Here we present a geometric partitional algorithm that could be applied to both uniformly and nonuniformly distributed data.

Highly selective aza-nitrile inhibitors for cathepsin K, structural optimization and molecular modeling.

As a new type of cathepsin K inhibitor, azadipeptide nitriles have the characteristics of proteolytic stability and excellent inhibitory activity, but they exhibit barely any satisfactory selectivity. Great efforts have focused on improving their selectivity toward cathepsin K. In this sequential study, we report the further structural optimization, synthesis, molecular modeling, and in vitro enzymatic assays of a new series of potent and selective inhibitors of cathepsin K without the P2-P3 amide linker.

A compound-based computational approach for the accurate determination of hot spots.

A plethora of both experimental and computational methods have been proposed in the past 20 years for the identification of hot spots at a protein-protein interface. The experimental determination of a protein-protein complex followed by alanine scanning mutagenesis, though able to determine hot spots with much precision, is expensive and has no guarantee of success while the accuracy of the current computational methods for hot-spot identification remains low. Here, we present a novel structure-based computational approach that accurately determines hot spots through docking into a set of proteins homologous to only one of the two interacting partners of a compound capable of disrupting the protein-protein interaction (PPI).

Highly selective azadipeptide nitrile inhibitors for cathepsin K: design, synthesis and activity assays.

We have developed a series of azadipeptide nitriles with different P3 groups. A triaryl meta-phenyl derivative, compound 13, was not only a potent inhibitor for cathepsin K (K(i) = 0.0031 nM), but also highly selective over both cathepsins B and S (~1000-fold).

High-resolution protein structure determination starting with a global fold calculated from exact solutions to the RDC equations.

We present a novel structure determination approach that exploits the global orientational restraints from RDCs to resolve ambiguous NOE assignments. Unlike traditional approaches that bootstrap the initial fold from ambiguous NOE assignments, we start by using RDCs to compute accurate secondary structure element (SSE) backbones at the beginning of structure calculation. Our structure determination package, called RDC-PANDA: (RDC-based SSE PAcking with NOEs for Structure Determination and NOE Assignment), consists of three modules: (1) RDC-EXACT: ; (2) PACKER: ; and (3) HANA: (HAusdorff-based NOE Assignment).

A data-driven, systematic search algorithm for structure determination of denatured or disordered proteins.

Traditional algorithms for the structure determination of native proteins by solution nuclear magnetic resonance (NMR) spectroscopy require a large number of experimental restraints. These algorithms formulate the structure determination problem as the computation of a structure or a set of similar structures that best fit the restraints. However, for both laboratory-denatured and natively-disordered proteins, the number of restraints measured by the current NMR techniques is well below that required by traditional algorithms.

A polynomial-time algorithm for de novo protein backbone structure determination from nuclear magnetic resonance data.

We describe an efficient algorithm for protein backbone structure determination from solution Nuclear Magnetic Resonance (NMR) data. A key feature of our algorithm is that it finds the conformation and orientation of secondary structure elements as well as the global fold in polynomial time. This is the first polynomial-time algorithm for de novo high-resolution biomacromolecular structure determination using experimentally recorded data from either NMR spectroscopy or X-ray crystallography.

Analysis of a systematic search-based algorithm for determining protein backbone structure from a minimum number of residual dipolar couplings.

We have developed an ab initio algorithm for determining a protein backbone structure using global orientational restraints on internuclear vectors derived from residual dipolar couplings (RDCs) measured in one or two different aligning media by solution nuclear magnetic resonance (NMR) spectroscopy [14, 15]. Specifically, the conformation and global orientations of individual secondary structure elements are computed, independently, by an exact solution, systematic search-based minimization algorithm using only 2 RDCs per residue. The systematic search is built upon a quartic equation for computing, exactly and in constant time, the directions of an internuclear vector from RDCs, and linear or quadratic equations for computing the sines and cosines of backbone dihedral (phi, psi) angles from two vectors in consecutive peptide planes.

An algebraic geometry approach to protein structure determination from NMR data.

Our paper describes the first provably-efficient algorithm for determining protein structures de novo, solely from experimental data. We show how the global nature of a certain kind of NMR data provides quantifiable complexity-theoretic benefits, allowing us to classify our algorithm as running in polynomial time. While our algorithm uses NMR data as input, it is the first polynomial-time algorithm to compute high-resolution structures de novo using any experimentally-recorded data, from either NMR spectroscopy or X-Ray crystallography.

An efficient and accurate algorithm for assigning nuclear overhauser effect restraints using a rotamer library ensemble and residual dipolar couplings.

Nuclear Overhauser effect (NOE) distance restraints are the main experimental data from protein nuclear magnetic resonance (NMR) spectroscopy for computing a complete three dimensional solution structure including sidechain conformations. In general, NOE restraints must be assigned before they can be used in a structure determination program. NOE assignment is very time-consuming to do manually, challenging to fully automate, and has become a key bottleneck for high-throughput NMR structure determination.

A polynomial-time nuclear vector replacement algorithm for automated NMR resonance assignments.

High-throughput NMR structural biology can play an important role in structural genomics. We report an automated procedure for high-throughput NMR resonance assignment for a protein of known structure, or of a homologous structure. These assignments are a prerequisite for probing protein-protein interactions, protein-ligand binding, and dynamics by NMR.

Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a systematic search algorithm for determining protein backbone structure.

We have derived a quartic equation for computing the direction of an internuclear vector from residual dipolar couplings (RDCs) measured in two aligning media, and two simple trigonometric equations for computing the backbone (phi,psi) angles from two backbone vectors in consecutive peptide planes. These equations make it possible to compute, exactly and in constant time, the backbone (phi,psi) angles for a residue from RDCs in two media on any single backbone vector type. Building upon these exact solutions we have designed a novel algorithm for determining a protein backbone substructure consisting of alpha-helices and beta-sheets.