MPRAP: An accessibility predictor for a-helical transmem-brane proteins that performs well inside and outside the membrane

<p>Abstract</p> <p>Background</p> <p>In water-soluble proteins it is energetically favorable to bury hydrophobic residues and to expose polar and charged residues. In contrast to water soluble proteins, transmembrane proteins face three distinct environments; a hydrophobic lipid environment inside the membrane, a hydrophilic water environment outside the membrane and an interface region rich in phospholipid head-groups. Therefore, it is energetically favorable for transmembrane proteins to expose different types of residues in the different regions.</p> <p>Results</p> <p>Investigations of a set of structurally determined transmembrane proteins showed that the composition of solvent exposed residues differs significantly inside and outside the membrane. In contrast, residues buried within the interior of a protein show a much smaller difference. However, in all regions exposed residues are less conserved than buried residues. Further, we found that current state-of-the-art predictors for surface area are optimized for one of the regions and perform badly in the other regions. To circumvent this limitation we developed a new predictor, MPRAP, that performs well in all regions. In addition, MPRAP performs better on complete membrane proteins than a combination of specialized predictors and acceptably on water-soluble proteins. A web-server of MPRAP is available at <url>http://mprap.cbr.su.se/</url></p> <p>Conclusion</p> <p>By including complete <it>a</it>-helical transmembrane proteins in the training MPRAP is able to predict surface accessibility accurately both inside and outside the membrane. This predictor can aid in the prediction of 3D-structure, and in the identification of erroneous protein structures.</p

Structure-based statistical analysis of transmembrane helices

Recent advances in determination of the high-resolution structure of membrane proteins now enable analysis of the main features of amino acids in transmembrane (TM) segments in comparison with amino acids in water-soluble helices. In this work, we conducted a large-scale analysis of the prevalent locations of amino acids by using a data set of 170 structures of integral membrane proteins obtained from the MPtopo database and 930 structures of water-soluble helical proteins obtained from the protein data bank. Large hydrophobic amino acids (Leu, Val, Ile, and Phe) plus Gly were clearly prevalent in TM helices whereas polar amino acids (Glu, Lys, Asp, Arg, and Gln) were less frequent in this type of helix. The distribution of amino acids along TM helices was also examined. As expected, hydrophobic and slightly polar amino acids are commonly found in the hydrophobic core of the membrane whereas aromatic (Trp and Tyr), Pro, and the hydrophilic amino acids (Asn, His, and Gln) occur more frequently in the interface regions. Charged amino acids are also statistically prevalent outside the hydrophobic core of the membrane, and whereas acidic amino acids are frequently found at both cytoplasmic and extra-cytoplasmic interfaces, basic amino acids cluster at the cytoplasmic interface. These results strongly support the experimentally demonstrated biased distribution of positively charged amino acids (that is, the so-called the positive-inside rule) with structural data

PRIMO: an interactive homology modeling pipeline

The development of automated servers to predict the three-dimensional structure of proteins has seen much progress over the years. These servers make calculations simpler, but largely exclude users from the process. In this study, we present the PRotein Interactive MOdeling (PRIMO) pipeline for homology modeling of protein monomers. The pipeline eases the multi-step modeling process, and reduces the workload required by the user, while still allowing engagement from the user during every step. Default parameters are given for each step, which can either be modified or supplemented with additional external input. PRIMO has been designed for users of varying levels of experience with homology modeling. The pipeline incorporates a user-friendly interface that makes it easy to alter parameters used during modeling

Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques

<p>Abstract</p> <p>Background</p> <p>Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as cancer. Kinase inhibitors have potential for treatment of these diseases. However, current inhibitors interact with a broad variety of kinases and interfere with multiple vital cellular processes, which causes toxic effects. Bioinformatics approaches that can predict inhibitor-kinase interactions from the chemical properties of the inhibitors and the kinase macromolecules might aid in design of more selective therapeutic agents, that show better efficacy and lower toxicity.</p> <p>Results</p> <p>We applied proteochemometric modelling to correlate the properties of 317 wild-type and mutated kinases and 38 inhibitors (12,046 inhibitor-kinase combinations) to the respective combination's interaction dissociation constant (K_d). We compared six approaches for description of protein kinases and several linear and non-linear correlation methods. The best performing models encoded kinase sequences with amino acid physico-chemical z-scale descriptors and used support vector machines or partial least- squares projections to latent structures for the correlations. Modelling performance was estimated by double cross-validation. The best models showed high predictive ability; the squared correlation coefficient for new kinase-inhibitor pairs ranging P²= 0.67-0.73; for new kinases it ranged P²_kin= 0.65-0.70. Models could also separate interacting from non-interacting inhibitor-kinase pairs with high sensitivity and specificity; the areas under the ROC curves ranging AUC = 0.92-0.93. We also investigated the relationship between the number of protein kinases in the dataset and the modelling results. Using only 10% of all data still a valid model was obtained with P²= 0.47, P²_kin= 0.42 and AUC = 0.83.</p> <p>Conclusions</p> <p>Our results strongly support the applicability of proteochemometrics for kinome-wide interaction modelling. Proteochemometrics might be used to speed-up identification and optimization of protein kinase targeted and multi-targeted inhibitors.</p

Tailored Approaches in Drug Development and Diagnostics: From Molecular Design to Biological Model Systems

Approaches to increase the efficiency in developing drugs and diagnostics tools, including new drug delivery and diagnostic technologies, are needed for improved diagnosis and treatment of major diseases and health problems such as cancer, inflammatory diseases, chronic wounds, and antibiotic resistance. Development within several areas of research ranging from computational sciences, material sciences, bioengineering to biomedical sciences and bioimaging is needed to realize innovative drug development and diagnostic (DDD) approaches. Here, an overview of recent progresses within key areas that can provide customizable solutions to improve processes and the approaches taken within DDD is provided. Due to the broadness of the area, unfortunately all relevant aspects such as pharmacokinetics of bioactive molecules and delivery systems cannot be covered. Tailored approaches within (i) bioinformatics and computer-aided drug design, (ii) nanotechnology, (iii) novel materials and technologies for drug delivery and diagnostic systems, and (iv) disease models to predict safety and efficacy of medicines under development are focused on. Current developments and challenges ahead are discussed. The broad scope reflects the multidisciplinary nature of the field of DDD and aims to highlight the convergence of biological, pharmaceutical, and medical disciplines needed to meet the societal challenges of the 21st century

Development of New Bacteria-Reducing Surfaces

In recent years, antibacterial surfaces have been a subject of increased interest. Especiallyinteresting are non-leaching, contact-active surfaces that physically disrupts the bacterialcell using immobilised cationic polymers. Thus the risks of bacterial resistance and discharge of hazardous biocides is minimised. The assembly of such surfaces is elaborate andusually involves organic solvents. Here, polyelectrolyte multilayers (PEM) are proposed as an effective surface modification method, with an overall goal of producing antibacterial cellulose fibres. The PEM process is based on physical adsorption of oppositely charged polymers in aqueous solutions. Multilayers were formed with the bactericidal polymer polyvinylamine (PVAm) and polyacrylic acid. PVAm compounds with hydrophobic modificationswere applied as well, as they possess increased antibacterial activity in solution. In this work, the multilayer formation was studied on model surfaces of silicone oxide and glass in order to obtain fundamental knowledge of the polymer system. QCM-D and reflectometry, which detect total mass including bound water and polymer mass only, respectively, were used to analyse the layer formation. Salt-concentrations were varied at 1, 10 or 100 mM NaCl. A stepwise multilayer formation with exponential-like polymer adsorption but with decreasing water content for each layer was seen at all salt concentrations.A higher salt concentration resulted in an increased adsorbed mass. No significant differences in adsorption between the modified and unmodified PVAm could be detected. AFM imaging applied to multilayers having nine layers showed large surface aggregates under high salt conditions for the C6-modified PVAm. Dynamic light scattering showed that the polymer occurred as single molecules in solution; hence it was concluded that theaggregation is surface-associated. The multilayers were then tested for bacterial growth inhibition. The relative bacterial inhibition was time-dependent, as the surface was saturated with bacteria over time. After two hours, a maximal inhibition of 99 % could be observed for the multilayers. After eight hours, a moderate inhibition of less than 40 % was detected. Using multilayers affected the results positively compared to single layers. After three layers, though, no further reductionwas seen. Viability staining of the surface-adhered bacteria revealed that the adhered bacteria had intact membranes. Therefore, the microbiological properties of the multilayers can at this point be described more as growth-inhibiting by bacterial adhesion effectsthan as biocidal. However, this work has shown the importance of combining surface characterisation and microbial testing to understand the bacteria-surface interaction.Biointeractive fibre

On the effects of structure and function on protein evolution

Many proteins can be described as working machines that make sure that everything functions in the cell. Their specific molecular functions are largely dependent on their three-dimensional structures, which in turn are mainly predetermined by their linear sequences of amino acid residues. Therefore, there is a relation between the sequence, structure and function of a protein, in which knowledge about the structure is crucial for understanding the functions. The structure is generally difficult to determine experimentally, but should in principle be possible to predict from the sequence by computational methods. The instructions of how to build the linear proteins sequences are copied during cell division and are passed on to successive generations. Although the copying process is a very efficient and accurate system, it does not function correctly on every occasion. Sometimes errors, or mutations can result from the process. These mutations gradually accumulate over time, so that the sequences and thereby also the structures and functions of proteins evolve overtime. This thesis is based on four papers concerning the relationship between function, structure and sequence and how it changes during the evolution of proteins. Paper I shows that the structural change is linearly related to sequence change and that structures are 3 to 10 times more conserved than sequences. In Paper II and Paper III we investigated non-helical structures and polar residues, respectively, positioned in the nonpolar membrane core environment of α-helical membrane proteins. Both types were found to be evolutionary conserved and functionally important. Paper IV includes the development of a method to predict the residues in α-helical membrane proteins that after folding become exposed to the solvent environment.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript

On the effects of structure and function on protein evolution

Many proteins can be described as working machines that make sure that everything functions in the cell. Their specific molecular functions are largely dependent on their three-dimensional structures, which in turn are mainly predetermined by their linear sequences of amino acid residues. Therefore, there is a relation between the sequence, structure and function of a protein, in which knowledge about the structure is crucial for understanding the functions. The structure is generally difficult to determine experimentally, but should in principle be possible to predict from the sequence by computational methods. The instructions of how to build the linear proteins sequences are copied during cell division and are passed on to successive generations. Although the copying process is a very efficient and accurate system, it does not function correctly on every occasion. Sometimes errors, or mutations can result from the process. These mutations gradually accumulate over time, so that the sequences and thereby also the structures and functions of proteins evolve overtime. This thesis is based on four papers concerning the relationship between function, structure and sequence and how it changes during the evolution of proteins. Paper I shows that the structural change is linearly related to sequence change and that structures are 3 to 10 times more conserved than sequences. In Paper II and Paper III we investigated non-helical structures and polar residues, respectively, positioned in the nonpolar membrane core environment of α-helical membrane proteins. Both types were found to be evolutionary conserved and functionally important. Paper IV includes the development of a method to predict the residues in α-helical membrane proteins that after folding become exposed to the solvent environment.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript