CAVER Analyst 1.0: graphic tool for interactive visualization and analysis of tunnels and channels in protein structures

ABSTRACT Summary: The transport of ligands, ions or solvent molecules into proteins with buried binding sites or through the membrane is enabled by protein tunnels and channels. CAVER Analyst is a software tool for calculation, analysis and real-time visualization of access tunnels and channels in static and dynamic protein structures. It provides an intuitive graphic user interface for setting up the calculation and interactive exploration of identified tunnels/channels and their characteristics. Availability and Implementation: CAVER Analyst is a multi-platform software written in JAVA. Binaries and documentation are freely available for non-commercial use at http://www.caver.cz

Regulating effect of β-ketoacyl synthase domain of fatty acid synthase on fatty acyl chain length in de novo fatty acid synthesis

Fatty acid synthase (FAS) is a multifunctional homodimeric protein, and is the key enzyme required for the anabolic conversion of dietary carbohydrates to fatty acids. FAS synthesizes long-chain fatty acids from three substrates: acetyl-CoA as a primer, malonyl-CoA as a 2 carbon donor, and NADPH for reduction. The entire reaction is composed of numerous sequential steps, each catalyzed by a specific functional domain of the enzyme. FAS comprises seven different functional domains, among which the β-ketoacyl synthase (KS) domain carries out the key condensation reaction to elongate the length of fatty acid chain. Acyl tail length controlled fatty acid synthesis in eukaryotes is a classic example of how a chain building multienzyme works. Different hypotheses have been put forward to explain how those sub-units of FAS are orchestrated to produce fatty acids with proper molecular weight. In the present study, molecular dynamics simulation based binding free energy calculation and access tunnels analysis showed that the C16 acyl tail fatty acid, the major product of FAS, fits to the active site on KS domain better than any other substrates. These simulations supported a new hypothesis about the mechanism of fatty acid production ratio: the geometric shape of active site on KS domain might play a determinate role

Geometric algorithms for cavity detection on protein surfaces

Macromolecular structures such as proteins heavily empower cellular processes or functions. These biological functions result from interactions between proteins and peptides, catalytic substrates, nucleotides or even human-made chemicals. Thus, several interactions can be distinguished: protein-ligand, protein-protein, protein-DNA, and so on. Furthermore, those interactions only happen under chemical- and shapecomplementarity conditions, and usually take place in regions known as binding sites. Typically, a protein consists of four structural levels. The primary structure of a protein is made up of its amino acid sequences (or chains). Its secondary structure essentially comprises -helices and -sheets, which are sub-sequences (or sub-domains) of amino acids of the primary structure. Its tertiary structure results from the composition of sub-domains into domains, which represent the geometric shape of the protein. Finally, the quaternary structure of a protein results from the aggregate of two or more tertiary structures, usually known as a protein complex. This thesis fits in the scope of structure-based drug design and protein docking. Specifically, one addresses the fundamental problem of detecting and identifying protein cavities, which are often seen as tentative binding sites for ligands in protein-ligand interactions. In general, cavity prediction algorithms split into three main categories: energy-based, geometry-based, and evolution-based. Evolutionary methods build upon evolutionary sequence conservation estimates; that is, these methods allow us to detect functional sites through the computation of the evolutionary conservation of the positions of amino acids in proteins. Energy-based methods build upon the computation of interaction energies between protein and ligand atoms. In turn, geometry-based algorithms build upon the analysis of the geometric shape of the protein (i.e., its tertiary structure) to identify cavities. This thesis focuses on geometric methods. We introduce here three new geometric-based algorithms for protein cavity detection. The main contribution of this thesis lies in the use of computer graphics techniques in the analysis and recognition of cavities in proteins, much in the spirit of molecular graphics and modeling. As seen further ahead, these techniques include field-of-view (FoV), voxel ray casting, back-face culling, shape diameter functions, Morse theory, and critical points. The leading idea is to come up with protein shape segmentation, much like we commonly do in mesh segmentation in computer graphics. In practice, protein cavity algorithms are nothing more than segmentation algorithms designed for proteins.Estruturas macromoleculares tais como as proteínas potencializam processos ou funções celulares. Estas funções resultam das interações entre proteínas e peptídeos, substratos catalíticos, nucleótideos, ou até mesmo substâncias químicas produzidas pelo homem. Assim, há vários tipos de interacções: proteína-ligante, proteína-proteína, proteína-DNA e assim por diante. Além disso, estas interações geralmente ocorrem em regiões conhecidas como locais de ligação (binding sites, do inglês) e só acontecem sob condições de complementaridade química e de forma. É também importante referir que uma proteína pode ser estruturada em quatro níveis. A estrutura primária que consiste em sequências de aminoácidos (ou cadeias), a estrutura secundária que compreende essencialmente por hélices e folhas , que são subsequências (ou subdomínios) dos aminoácidos da estrutura primária, a estrutura terciária que resulta da composição de subdomínios em domínios, que por sua vez representa a forma geométrica da proteína, e por fim a estrutura quaternária que é o resultado da agregação de duas ou mais estruturas terciárias. Este último nível estrutural é frequentemente conhecido por um complexo proteico. Esta tese enquadra-se no âmbito da conceção de fármacos baseados em estrutura e no acoplamento de proteínas. Mais especificamente, aborda-se o problema fundamental da deteção e identificação de cavidades que são frequentemente vistos como possíveis locais de ligação (putative binding sites, do inglês) para os seus ligantes (ligands, do inglês). De forma geral, os algoritmos de identificação de cavidades dividem-se em três categorias principais: baseados em energia, geometria ou evolução. Os métodos evolutivos baseiam-se em estimativas de conservação das sequências evolucionárias. Isto é, estes métodos permitem detectar locais funcionais através do cálculo da conservação evolutiva das posições dos aminoácidos das proteínas. Em relação aos métodos baseados em energia estes baseiam-se no cálculo das energias de interação entre átomos da proteína e do ligante. Por fim, os algoritmos geométricos baseiam-se na análise da forma geométrica da proteína para identificar cavidades. Esta tese foca-se nos métodos geométricos. Apresentamos nesta tese três novos algoritmos geométricos para detecção de cavidades em proteínas. A principal contribuição desta tese está no uso de técnicas de computação gráfica na análise e reconhecimento de cavidades em proteínas, muito no espírito da modelação e visualização molecular. Como pode ser visto mais à frente, estas técnicas incluem o field-of-view (FoV), voxel ray casting, back-face culling, funções de diâmetro de forma, a teoria de Morse, e os pontos críticos. A ideia principal é segmentar a proteína, à semelhança do que acontece na segmentação de malhas em computação gráfica. Na prática, os algoritmos de detecção de cavidades não são nada mais que algoritmos de segmentação de proteínas

Visual analysis of protein-ligand interactions

The analysis of protein-ligand interactions is complex because of the many factors at play. Most current methods for visual analysis provide this information in the form of simple 2D plots, which, besides being quite space hungry, often encode a low number of different properties. In this paper we present a system for compact 2D visualization of molecular simulations. It purposely omits most spatial information and presents physical information associated to single molecular components and their pairwise interactions through a set of 2D InfoVis tools with coordinated views, suitable interaction, and focus+context techniques to analyze large amounts of data. The system provides a wide range of motifs for elements such as protein secondary structures or hydrogen bond networks, and a set of tools for their interactive inspection, both for a single simulation and for comparing two different simulations. As a result, the analysis of protein-ligand interactions of Molecular Simulation trajectories is greatly facilitated.Peer ReviewedPostprint (author's final draft

A Five Residue Insertion Between Codons 28 And 29 Of The Hiv-1 Protease Gene Reduces The Replicative Capacity Of The Virus

HIV-1 protease (PR) is a 99 amino acid protein responsible for cleavage of the viral polyprotein. We have identified a novel clinical isolate, MDR/28, which contains a five residue insertion between codons 28 and 29 of a multi-drug resistant (MDR) PR. This clinical isolate displays reduced viral replicative capacity compared to the wild-type. As opposed to drug-resistance mutations, studies on insertions remain largely underrepresented in the literature, and the consequences of such insertions are largely unknown. To understand the mechanism leading to reduced replicative capacity, three PR models were created and subjected to 40ns molecular dynamics simulations: MDR/28, wild type, and MDR PR. In addition, PR inhibitors (PI) atazanavir (ATV), darunavir (DRV), lopinavir (LPV) and saquinavir (SQV), as well as cleavage peptide CA/p2 were docked to the three models. The MDR/28-PI complexes displayed decreased binding affinity when compared to WT complexes, likely due to an increased active site cavity volume and altered secondary structure at residues local to the insertion mutant. Additionally, in the active site of MDR/28 the predicted binding mode of the CA/p2 peptide did not include contact with the catalytic residues, and migrated from that position, a behavior not seen with any tested PIs or with either of the other PR models. These structural changes produced by the insertion suggest a mechanism for reduced replicative capacity of the mutant virus

From complex data to clear insights: visualizing molecular dynamics trajectories

Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization

Gas channel rerouting in a primordial enzyme: Structural insights of the carbon-monoxide dehydrogenase/acetyl-CoA synthase complex from the acetogen Clostridium autoethanogenum

Clostridium autoethanogenum, the bacterial model for biological conversion of waste gases into biofuels, grows under extreme carbon-monoxide (CO) concentrations. The strictly anaerobic bacterium derives its entire cellular energy and carbon from this poisonous gas, therefore requiring efficient molecular machineries for CO-conversion. Here, we structurally and biochemically characterized the key enzyme of the CO-converting metabolism: the CO-dehydrogenase/Acetyl-CoA synthase (CODH/ACS). We obtained crystal structures of natively isolated complexes from fructose-grown and CO-grown C. autoethanogenum cultures. Both contain the same isoforms and if the overall structure adopts the classic alpha(2)beta(2) architecture, comparable to the model enzyme from Moorella thermoacetica, the ACS binds a different position on the CODH core. The structural characterization of a proteolyzed complex and the conservation of the binding interface in close homologs rejected the possibility of a crystallization artefact. Therefore, the internal CO-channeling system, critical to transfer CO generated at the C-cluster to the ACS active site, drastically differs in the complex from C. autoethanogenum. The 1.9-angstrom structure of the CODH alone provides an accurate picture of the new CO-routes, leading to the ACS core and reaching the surface. Increased gas accessibility would allow the simultaneous CO-oxidation and acetyl-CoA production. Biochemical experiments showed higher flexibility of the ACS subunit from C. autoethanogenum compared to M. thermoacetica, albeit monitoring similar CO-oxidation and formation rates. These results show a reshuffling of internal CO-tunnels during evolution of these Firmicutes, putatively leading to a bidirectional complex that ensure a high flux of CO-conversion toward energy conservation, acting as the main cellular powerplant