gene prediction for protein-coding regions.

Motivation: gene prediction in nonmodel organisms is a difficult task. While many methods have been developed, their average accuracy over long segments of a genome, and especially when assessed over a wide range of species, generally yields results with sensitivity and specificity levels in the low 60% range. A common weakness of most methods is the tendency to learn patterns that are species-specific to varying degrees.

Protein Function Analysis through Machine Learning.

Machine learning (ML) has been an important arsenal in computational biology used to elucidate protein function for decades. With the recent burgeoning of novel ML methods and applications, new ML approaches have been incorporated into many areas of computational biology dealing with protein function. We examine how ML has been integrated into a wide range of computational models to improve prediction accuracy and gain a better understanding of protein function.

Functional Dynamics of Substrate Recognition in TEM Beta-Lactamase.

The beta-lactamase enzyme provides effective resistance to beta-lactam antibiotics due to substrate recognition controlled by point mutations. Recently, extended-spectrum and inhibitor-resistant mutants have become a global health problem. Here, the functional dynamics that control substrate recognition in TEM beta-lactamase are investigated using all-atom molecular dynamics simulations.

Victory Tax: A Holistic Income Tax System.

How can an income tax system be designed to exploit human nature and a free market to create a poverty free society, while balancing budgets without disproportional tax burdens? Such a tax system, with universal character, is deduced from the following guiding principles: (1) a single tax rate applies to all income types and levels; (2) the tax rate adjusts to satisfy budget projections; (3) government transfer only supplements the income of households with self-generated income below the poverty line; (4) deductions for basic living expenses, itemized investments and capital losses are allowed; (5) deductions cannot be applied to government transfer. A general framework emerges with three parameters that determine a minimum allowed tax deduction, a maximum allowed itemized deduction, and a maximum deduction defined by income percentage. An income distribution that mimics the United States, and a series of log-normal distributions are considered to quantitatively compare detailed characteristics of this tax system to progressive and flat tax systems.

JEDi: java essential dynamics inspector - a molecular trajectory analysis toolkit.

Background: Principal component analysis (PCA) is commonly applied to the atomic trajectories of biopolymers to extract essential dynamics that describe biologically relevant motions. Although application of PCA is straightforward, specialized software to facilitate workflows and analysis of molecular dynamics simulation data to fully harness the power of PCA is lacking. The Java Essential Dynamics inspector (JEDi) software is a major upgrade from the previous JED software.

Molecular function recognition by supervised projection pursuit machine learning.

Identifying mechanisms that control molecular function is a significant challenge in pharmaceutical science and molecular engineering. Here, we present a novel projection pursuit recurrent neural network to identify functional mechanisms in the context of iterative supervised machine learning for discovery-based design optimization. Molecular function recognition is achieved by pairing experiments that categorize systems with digital twin molecular dynamics simulations to generate working hypotheses.

Rigidity and flexibility characteristics of DD[E/D]-transposases Mos1 and Sleeping Beauty.

DD[E/D]-transposases catalyze the multistep reaction of cut-and-paste DNA transposition. Structurally, several DD[E/D]-transposases have been characterized, revealing a multi-domain structure with the catalytic domain possessing the RNase H-like structural motif that brings three catalytic residues (D, D, and E or D) into close proximity for the catalysis. However, the dynamic behavior of DD[E/D]-transposases during transposition remains poorly understood.

Statistical Measures to Quantify Similarity between Molecular Dynamics Simulation Trajectories.

Molecular dynamics simulation is commonly employed to explore protein dynamics. Despite the disparate timescales between functional mechanisms and molecular dynamics (MD) trajectories, functional differences are often inferred from differences in conformational ensembles between two proteins in structure-function studies that investigate the effect of mutations. A common measure to quantify differences in dynamics is the root mean square fluctuation (RMSF) about the average position of residues defined by C-atoms.

Decomposing Dynamical Couplings in Mutated scFv Antibody Fragments into Stabilizing and Destabilizing Effects.

Conformational fluctuations within scFv antibodies are characterized by a novel perturbation-response decomposition of molecular dynamics trajectories. Both perturbation and response profiles are stratified into stabilizing and destabilizing conditions. The linker between the VH and VL domains exhibits the dominant dynamical response by being coupled to nearly the entire protein, responding to both stabilizing and destabilizing perturbations.

JED: a Java Essential Dynamics Program for comparative analysis of protein trajectories.

Background: Essential Dynamics (ED) is a common application of principal component analysis (PCA) to extract biologically relevant motions from atomic trajectories of proteins. Covariance and correlation based PCA are two common approaches to determine PCA modes (eigenvectors) and their eigenvalues. Protein dynamics can be characterized in terms of Cartesian coordinates or internal distance pairs.

Mutations in Antibody Fragments Modulate Allosteric Response Via Hydrogen-Bond Network Fluctuations.

A mechanical perturbation method that locally restricts conformational entropy along the protein backbone is used to identify putative allosteric sites in a series of antibody fragments. The method is based on a distance constraint model that integrates mechanical and thermodynamic viewpoints of protein structure wherein mechanical clamps that mimic substrate or cosolute binding are introduced. Across a set of six single chain-Fv fragments of the anti-lymphotoxin-β receptor antibody, statistically significant responses are obtained by averaging over 10 representative structures sampled from a molecular dynamics simulation.

Novel Ricin Subunit Antigens With Enhanced Capacity to Elicit Toxin-Neutralizing Antibody Responses in Mice.

RiVax is a candidate ricin toxin subunit vaccine antigen that has proven to be safe in human phase I clinical trials. In this study, we introduced double and triple cavity-filling point mutations into the RiVax antigen with the expectation that stability-enhancing modifications would have a beneficial effect on overall immunogenicity of the recombinant proteins. We demonstrate that 2 RiVax triple mutant derivatives, RB (V81L/C171L/V204I) and RC (V81I/C171L/V204I), when adsorbed to aluminum salts adjuvant and tested in a mouse prime-boost-boost regimen were 5- to 10-fold more effective than RiVax at eliciting toxin-neutralizing serum IgG antibody titers.

Dynamics and thermodynamic properties of CXCL7 chemokine.

Chemokines form a family of signaling proteins mainly responsible for directing the traffic of leukocytes, where their biological activity can be modulated by their oligomerization state. We characterize the dynamics and thermodynamic stability of monomer and homodimer structures of CXCL7, one of the most abundant platelet chemokines, using experimental methods that include circular dichroism (CD) and nuclear magnetic resonance (NMR) spectroscopy, and computational methods that include the anisotropic network model (ANM), molecular dynamics (MD) simulations and the distance constraint model (DCM). A consistent picture emerges for the effects of dimerization and Cys5-Cys31 and Cys7-Cys47 disulfide bonds formation.

Rigidity Emerges during Antibody Evolution in Three Distinct Antibody Systems: Evidence from QSFR Analysis of Fab Fragments.

The effects of somatic mutations that transform polyspecific germline (GL) antibodies to affinity mature (AM) antibodies with monospecificity are compared among three GL-AM Fab pairs. In particular, changes in conformational flexibility are assessed using a Distance Constraint Model (DCM). We have previously established that the DCM can be robustly applied across a series of antibody fragments (VL to Fab), and subsequently, the DCM was combined with molecular dynamics (MD) simulations to similarly characterize five thermostabilizing scFv mutants.

A virtual pebble game to ensemble average graph rigidity.

Background: The body-bar Pebble Game (PG) algorithm is commonly used to calculate network rigidity properties in proteins and polymeric materials. To account for fluctuating interactions such as hydrogen bonds, an ensemble of constraint topologies are sampled, and average network properties are obtained by averaging PG characterizations. At a simpler level of sophistication, Maxwell constraint counting (MCC) provides a rigorous lower bound for the number of internal degrees of freedom (DOF) within a body-bar network, and it is commonly employed to test if a molecular structure is globally under-constrained or over-constrained.

Redistribution of flexibility in stabilizing antibody fragment mutants follows Le Châtelier's principle.

Le Châtelier's principle is the cornerstone of our understanding of chemical equilibria. When a system at equilibrium undergoes a change in concentration or thermodynamic state (i.e.

Towards comprehensive analysis of protein family quantitative stability-flexibility relationships using homology models.

The Distance Constraint Model (DCM) is a computational modeling scheme that uniquely integrates thermodynamic and mechanical descriptions of protein structure. As such, quantitative stability-flexibility relationships (QSFR) that describe the interrelationships of thermodynamics and mechanics can be quickly computed. Using comparative QSFR analyses, we have previously investigated these relationships across a small number of protein orthologs, ranging from two to a dozen [1, 2].

A case study comparing quantitative stability-flexibility relationships across five metallo-β-lactamases highlighting differences within NDM-1.

The Distance Constraint Model (DCM) is an ensemble-based biophysical model that integrates thermodynamic and mechanical viewpoints of protein structure. The DCM outputs a large number of structural characterizations that collectively allow for Quantified Stability-Flexibility Relationships (QSFR) to be identified and compared across protein families. Using five metallo-β-lactamases (MBLs) as a representative set, we demonstrate how QSFR properties are both conserved and varied across protein families.

Principal component analysis: a method for determining the essential dynamics of proteins.

It has become commonplace to employ principal component analysis to reveal the most important motions in proteins. This method is more commonly known by its acronym, PCA. While most popular molecular dynamics packages inevitably provide PCA tools to analyze protein trajectories, researchers often make inferences of their results without having insight into how to make interpretations, and they are often unaware of limitations and generalizations of such analysis.

Variations within class-A β-lactamase physiochemical properties reflect evolutionary and environmental patterns, but not antibiotic specificity.

The bacterial enzyme β-lactamase hydrolyzes the β-lactam ring of penicillin and chemically related antibiotics, rendering them ineffective. Due to rampant antibiotic overuse, the enzyme is evolving new resistance activities at an alarming rate. Related, the enzyme's global physiochemical properties exhibit various amounts of conservation and variability across the family.

Thermodynamic stability and flexibility characteristics of antibody fragment complexes.

Free energy landscapes, backbone flexibility and residue-residue couplings for being co-rigid or co-flexible are calculated from the minimal Distance Constraint Model (mDCM) on an exploratory dataset consisting of VL, scFv and Fab antibody fragments. Experimental heat capacity curves are reproduced markedly well, and an analysis of quantitative stability/flexibility relationships (QSFR) is applied to a representative VL domain and several complexes in the scFv and Fab forms. Global flexibility in the denatured ensemble typically decreases in the larger complexes due to domain-domain interfaces.

Effect of the Reaction Field on Molecular Forces and Torques Revealed by an Image-Charge Solvation Model.

We recently developed the Image-Charge Solvation Model (ICSM), which is an explicit/implicit hybrid model to accurately account for long-range electrostatic forces in molecular dynamics simulations [Lin et al., J. Chem.

Switch II mutants reveal coupling between the nucleotide- and actin-binding regions in myosin V.

Conserved active-site elements in myosins and other P-loop NTPases play critical roles in nucleotide binding and hydrolysis; however, the mechanisms of allosteric communication among these mechanoenzymes remain unresolved. In this work we introduced the E442A mutation, which abrogates a salt-bridge between switch I and switch II, and the G440A mutation, which abolishes a main-chain hydrogen bond associated with the interaction of switch II with the γ phosphate of ATP, into myosin V. We used fluorescence resonance energy transfer between mant-labeled nucleotides or IAEDANS-labeled actin and FlAsH-labeled myosin V to examine the conformation of the nucleotide- and actin-binding regions, respectively.

Changes in Lysozyme Flexibility upon Mutation Are Frequent, Large and Long-Ranged.

We investigate changes in human c-type lysozyme flexibility upon mutation via a Distance Constraint Model, which gives a statistical mechanical treatment of network rigidity. Specifically, two dynamical metrics are tracked. Changes in flexibility index quantify differences within backbone flexibility, whereas changes in the cooperativity correlation quantify differences within pairwise mechanical couplings.

Calculating ensemble averaged descriptions of protein rigidity without sampling.

Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology.