Accelerated Protein Folding Using Greedy-Proximal A.

The protein folding problem has been studied in the field of molecular biophysics and biochemistry for many years. Even small changes in folding patterns may lead to serious diseases such as Alzheimer's or Parkinson's where proteins are folded either too quickly or too slowly. Molecular dynamics (MD) is one of the tools used to understand how proteins fold into native conformations. While it captures sequences of conformations that lead over time to the folded state, limitations in simulation timescales remain problematic. Although many approaches have been suggested to speed up the simulation process using rapid changes in temperature or pressure, we propose a rational approach, Greedy-proximal A* (GPA*), derived from path finding algorithms to explore the supposed shortest path folding pathway from the unfolded to a given folded conformation. We introduce several new protein structure comparison metrics based on the contact map distance to help mitigate the challenges faced by "standard" metrics. We test our approach on proteins which represent the two main types of secondary structure: (a) the Trp-cage miniprotein construct TC5b (1L2Y) which is a short, fast-folding protein that represents an α-helical secondary structure formed because of a locked tryptophan in the middle, (b) the immunoglobulin binding domain of the streptococcal protein G (1GB1), containing an α-helix and several ß-sheets, and (c) the chicken villin subdomain HP-35, N68H protein (1YRF)-one of the fastest folding proteins which forms three α-helices. We compare our algorithm to replica-exchange MD and steered MD methods which represent the main algorithms used for accelerating folding proteins with MD. We find that GPA* not only reduces the computational time needed to obtain the folded conformation without adding artificial energy bias but also makes it possible to generate trajectories which contain minimal motions needed for the folding transition.

A data-driven approach to modeling the tripartite structure of multidrug resistance efflux pumps.

Many bacterial pathogens are becoming increasingly resistant to antibiotic treatments, and a detailed understanding of the molecular basis of antibiotic resistance is critical for the development of next-generation approaches for combating bacterial infections. Studies focusing on pathogens have revealed the profile of resistance in these organisms to be due primarily to the presence of multidrug resistance efflux pumps: tripartite protein complexes which span the periplasm bridging the inner and outer membranes of Gram-negative bacteria. An atomic-level resolution tripartite structure remains imperative to advancing our understanding of the molecular mechanisms of pump function using both theoretical and experimental approaches. We develop a fast and consistent method for constructing tripartite structures which leverages existing data-driven models and provide molecular modeling approaches for constructing tripartite structures of multidrug resistance efflux pumps. Our modeling studies reveal that conformational changes in the inner membrane component responsible for drug translocation have limited impact on the conformations of the other pump components, and that two distinct models derived from conflicting experimental data are both consistent with all currently available measurements. Additionally, we investigate putative drug translocation pathways via geometric simulations based on the available crystal structures of the inner membrane pump component, AcrB, bound to two drugs which occupy distinct binding sites: doxorubicin and linezolid. These simulations suggest that smaller drugs may enter the pump through a channel from the cytoplasmic leaflet of the inner membrane, while both smaller and larger drug molecules may enter through a vestibule accessible from the periplasm.

Dynamic electrophoretic fingerprinting of the HIV-1 envelope glycoprotein.

BACKGROUND: Interactions between the HIV-1 envelope glycoprotein (Env) and its primary receptor CD4 are influenced by the physiological setting in which these events take place. In this study, we explored the surface chemistry of HIV-1 Env constructs at a range of pH and salinities relevant to mucosal and systemic compartments through electrophoretic mobility (EM) measurements. Sexual transmission events provide a more acidic environment for HIV-1 compared to dissemination and spread of infection occurring in blood or lymph node. We hypothesize functional, trimeric Env behaves differently than monomeric forms. RESULTS: The dynamic electrophoretic fingerprint of trimeric gp140 revealed a change in EM from strongly negative to strongly positive as pH increased from that of the lower female genital tract (pHx) to that of the blood (pHy). Similar findings were observed using a trimeric influenza Haemagglutinin (HA) glycoprotein, indicating that this may be a general attribute of trimeric viral envelope glycoproteins. These findings were supported by computationally modeling the surface charge of various gp120 and HA crystal structures. To identify the behavior of the infectious agent and its target cells, EM measurements were made on purified whole HIV-1 virions and primary T-lymphocytes. Viral particles had a largely negative surface charge, and lacked the regions of positivity near neutral pH that were observed with trimeric Env. T cells changed their surface chemistry as a function of activation state, becoming more negative over a wider range of pH after activation. Soluble recombinant CD4 (sCD4) was found to be positively charged under a wide range of conditions. Binding studies between sCD4 and gp140 show that the affinity of CD4-gp140 interactions depends on pH. CONCLUSIONS: Taken together, these findings allow a more complete model of the electrochemical forces involved in HIV-1 Env functionality. These results indicate that the influence of the localized environment on the interactions of HIV with target cells are more pronounced than previously appreciated. There is differential chemistry of trimeric, but not monomeric, Env under conditions which mimic the mucosa compared to those found systemically. This should be taken into consideration during design of immunogens which targets virus at mucosal portals of entry.

A bimodal distribution of two distinct categories of intrinsically disordered structures with separate functions in FG nucleoporins.

Nuclear pore complexes (NPCs) gate the only conduits for nucleocytoplasmic transport in eukaryotes. Their gate is formed by nucleoporins containing large intrinsically disordered domains with multiple phenylalanine-glycine repeats (FG domains). In combination, these are hypothesized to form a structurally and chemically homogeneous network of random coils at the NPC center, which sorts macromolecules by size and hydrophobicity. Instead, we found that FG domains are structurally and chemically heterogeneous. They adopt distinct categories of intrinsically disordered structures in non-random distributions. Some adopt globular, collapsed coil configurations and are characterized by a low charge content. Others are highly charged and adopt more dynamic, extended coil conformations. Interestingly, several FG nucleoporins feature both types of structures in a bimodal distribution along their polypeptide chain. This distribution functionally correlates with the attractive or repulsive character of their interactions with collapsed coil FG domains displaying cohesion toward one another and extended coil FG domains displaying repulsion. Topologically, these bipartite FG domains may resemble sticky molten globules connected to the tip of relaxed or extended coils. Within the NPC, the crowding of FG nucleoporins and the segregation of their disordered structures based on their topology, dimensions, and cohesive character could force the FG domains to form a tubular gate structure or transporter at the NPC center featuring two separate zones of traffic with distinct physicochemical properties.

Validating clustering of molecular dynamics simulations using polymer models.

BACKGROUND: Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. RESULTS: We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. CONCLUSIONS: We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.

The Molecular Basis of pH-Modulated HIV gp120 Binding Revealed.

Decades of research has yet to provide a vaccine for HIV, the virus which causes AIDS. Recent theoretical research has turned attention to mucosa pH levels over systemic pH levels. Previous research in this field developed a computational approach for determining pH sensitivity that indicated higher potential for transmission at mucosa pH levels present during intercourse. The process was extended to incorporate a principal component analysis (PCA)-based machine learning technique for classification of gp120 proteins against a known transmitted variant called Biomolecular Electro-Static Indexing (BESI). The original process has since been extended to the residue level by a process we termed Electrostatic Variance Masking (EVM) and used in conjunction with BESI to determine structural differences present among various subspecies across Clades A1 and C. Results indicate that structures outside of the core selected by EVM may be responsible for binding affinity observed in many other studies and that pH modulation of select substructures indicated by EVM may influence specific regions of the viral envelope protein (Env) involved in protein-protein interactions.

Creation of a Curated Aquatic Toxicology Database: EnviroTox.

Flexible, rapid, and predictive approaches that do not require the use of large numbers of vertebrate test animals are needed because the chemical universe remains largely untested for potential hazards. Development of robust new approach methodologies and nontesting approaches requires the use of existing information via curated, integrated data sets. The ecological threshold of toxicological concern (ecoTTC) represents one such new approach methodology that can predict a conservative de minimis toxicity value for chemicals with little or no information available. For the creation of an ecoTTC tool, a large, diverse environmental data set was developed from multiple sources, with harmonization, characterization, and information quality assessment steps to ensure that the information could be effectively organized and mined. The resulting EnviroTox database contains 91 217 aquatic toxicity records representing 1563 species and 4016 unique Chemical Abstracts Service numbers and is a robust, curated database containing high-quality aquatic toxicity studies that are traceable to the original information source. Chemical-specific information is also linked to each record and includes physico-chemical information, chemical descriptors, and mode of action classifications. Toxicity data are associated with the physico-chemical data, mode of action classifications, and curated taxonomic information for the organisms tested. The EnviroTox platform also includes 3 analysis tools: a predicted-no-effect concentration calculator, an ecoTTC distribution tool, and a chemical toxicity distribution tool. Although the EnviroTox database and tools were originally developed to support ecoTTC analysis and development, they have broader applicability to the field of ecological risk assessment. Environ Toxicol Chem 2019;9999:1-12. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Switch Loop Flexibility Affects Substrate Transport of the AcrB Efflux Pump.

The functionally important switch loop of the trimeric multidrug transporter AcrB separates the access and deep drug binding pockets in every protomer. This loop, comprising 11-amino-acid residues, has been shown to be crucial for substrate transport, as drugs have to travel past the loop to reach the deep binding pocket and from there are transported outside the cell via the connected AcrA and TolC channels. It contains four symmetrically arranged glycine residues suggesting that flexibility is a key feature for pump activity. Upon combinatorial substitution of these glycine residues to proline, functional and structural asymmetry was observed. Proline substitutions on the PC1-proximal side completely abolished transport and reduced backbone flexibility of the switch loop, which adopted a conformation restricting the pathway toward the deep binding pocket. Two phenylalanine residues located adjacent to the substitution sensitive glycine residues play a role in blocking the pathway upon rigidification of the loop, since the removal of the phenyl rings from the rigid loop restores drug transport activity.