Workshop—Predicting the Structure of Biological Molecules

This April, in Cambridge (UK), principal investigators from the Mathematical Biology Group of the Medical Research Council's National Institute of Medical Research organized a workshop in structural bioinformatics at the Centre for Mathematical Sciences. Bioinformatics researchers of several nationalities from labs around the country presented and discussed their computational work in biomolecular structure prediction and analysis, and in protein evolution. The meeting was intensive and lively and gave attendees an overview of the healthy state of protein bioinformatics in the UK

Improving your target-template alignment with MODalign

Summary: MODalign is an interactive web-based tool aimed at helping protein structure modelers to inspect and manually modify the alignment between the sequences of a target protein and of its template(s). It interactively computes, displays and, upon modification of the target-template alignment, updates the multiple sequence alignments of the two protein families, their conservation score, secondary structure and solvent accessibility values, and local quality scores of the implied three-dimensional model(s). Although it has been designed to simplify the target-template alignment step in modeling, it is suitable for all cases where a sequence alignment needs to be inspected in the context of other biological information. Availability and implementation: Freely available on the web at http://modorama.biocomputing.it/modalign. Website implemented in HTML and JavaScript with all major browsers supported. Contact: [email protected]

Improving your target-template alignment with MODalign

Summary: MODalign is an interactive web-based tool aimed at helping protein structure modelers to inspect and manually modify the alignment between the sequences of a target protein and of its template(s). It interactively computes, displays and, upon modification of the target-template alignment, updates the multiple sequence alignments of the two protein families, their conservation score, secondary structure and solvent accessibility values, and local quality scores of the implied three-dimensional model(s). Although it has been designed to simplify the target-template alignment step in modeling, it is suitable for all cases where a sequence alignment needs to be inspected in the context of other biological information

Benchmarks for flexible and rigid transcription factor-DNA docking

<p>Abstract</p> <p>Background</p> <p>Structural insight from transcription factor-DNA (TF-DNA) complexes is of paramount importance to our understanding of the affinity and specificity of TF-DNA interaction, and to the development of structure-based prediction of TF binding sites. Yet the majority of the TF-DNA complexes remain unsolved despite the considerable experimental efforts being made. Computational docking represents a promising alternative to bridge the gap. To facilitate the study of TF-DNA docking, carefully designed benchmarks are needed for performance evaluation and identification of the strengths and weaknesses of docking algorithms.</p> <p>Results</p> <p>We constructed two benchmarks for flexible and rigid TF-DNA docking respectively using a unified non-redundant set of 38 test cases. The test cases encompass diverse fold families and are classified into easy and hard groups with respect to the degrees of difficulty in TF-DNA docking. The major parameters used to classify expected docking difficulty in flexible docking are the conformational differences between bound and unbound TFs and the interaction strength between TFs and DNA. For rigid docking in which the starting structure is a bound TF conformation, only interaction strength is considered.</p> <p>Conclusions</p> <p>We believe these benchmarks are important for the development of better interaction potentials and TF-DNA docking algorithms, which bears important implications to structure-based prediction of transcription factor binding sites and drug design.</p

Computational Design To Reduce Conformational Flexibility and Aggregation Rates of an Antibody Fab Fragment

Computationally-guided semi-rational design has significant potential for improving the aggregation kinetics of protein biopharmaceuticals. While improvement in the global conformational stability can stabilise proteins to aggregation under some conditions, previous studies suggest that such an approach is limited because thermal transition temperatures (Tm) and the fraction of protein unfolded (fT) tend to only correlate with aggregation kinetics where the protein is incubated at temperatures approaching the Tm. This is because under these conditions, aggregation from globally unfolded protein becomes dominant. However, under native conditions, the aggregation kinetics are presumed to be dependent on local structural fluctuations or partial unfolding of the native state, that reveal regions of high propensity to form protein-protein interactions that lead to aggregation. In this work, we have targeted the design of stabilising mutations to regions of the A33 Fab surface structure, that were predicted to be more flexible. This Fab already has high global stability, and global unfolding is not the main cause of aggregation under most conditions. Therefore, the aim was to reduce the conformational flexibility and entropy of the native protein at various locations, and thus identify which of those regions has the greatest influence on the aggregation kinetics. Highly dynamic regions of structure were identified through both molecular dynamics simulation, and B-factor analysis of related X-ray crystal structures. The most flexible residues were mutated into more stable variants, as predicted by Rosetta, which evaluates the ΔΔGND for each potential point mutation. Additional destabilising variants were prepared as controls to evaluate the prediction accuracy, and also to assess the general influence of conformational stability on aggregation kinetics. The thermal conformational stability, and aggregation rates of eighteen variants at 65 °C, were each examined at pH 4, 200 mM ionic strength, under which conditions the initial wild-type protein was <5% unfolded. Variants with decreased Tm values led to more rapid aggregation due to an increase in the fraction of protein unfolded under the conditions studied. As expected, no significant improvements were observed in the global conformational stability as measured by Tm. However, six of the twelve stable variants led to an increase in the cooperativity of unfolding, consistent with lower conformational flexibility and entropy in the native ensemble. Three of these had 5-11% lower aggregation rates, and their structural clustering indicated that the local dynamics of the C-terminus of the heavy chain had a role in influencing the aggregation rate

Molecular interactions of ASPP1 and ASPP2 with the p53 protein family and the apoptotic promoters PUMA and Bax

The apoptosis stimulating p53 proteins, ASPP1 and ASPP2, are the first two common activators of the p53 protein family that selectively enable the latter to regulate specific apoptotic target genes, which facilitates yes yet unknown mechanisms for discrimination between cell cycle arrest and apoptosis. To better understand the interplay between ASPP- and p53-family of proteins we investigated the molecular interactions between them using biochemical methods and structure-based homology modelling. The data demonstrate that: (i) the binding of ASPP1 and ASPP2 to p53, p63 and p73 is direct; (ii) the C-termini of ASPP1 and ASPP2 interact with the DNA-binding domains of p53 protein family with dissociation constants, Kd, in the lower micro-molar range; (iii) the stoichiometry of binding is 1:1; (iv) the DNA-binding domains of p53 family members are sufficient for these protein–protein interactions; (v) EMSA titrations revealed that while tri-complex formation between ASPPs, p53 family of proteins and PUMA/Bax is mutually exclusive, ASPP2 (but not ASPP1) formed a complex with PUMA (but not Bax) and displaced p53 and p73. The structure-based homology modelling revealed subtle differences between ASPP2 and ASPP1 and together with the experimental data provide novel mechanistic insights

A Sequence and Structure Based Method to Predict Putative Substrates, Functions and Regulatory Networks of Endo Proteases

BACKGROUND: Proteases play a central role in cellular homeostasis and are responsible for the spatio-temporal regulation of function. Many putative proteases have been recently identified through genomic approaches, leading to a surge in global profiling attempts to characterize their function. Through such efforts and others it has become evident that many proteases play non-traditional roles. Accordingly, the number and the variety of the substrate repertoire of proteases are expected to be much larger than previously assumed. In line with such global profiling attempts, we present here a method for the prediction of natural substrates of endo proteases (human proteases used as an example) by employing short peptide sequences as specificity determinants. METHODOLOGY/PRINCIPAL FINDINGS: Our method incorporates specificity determinants unique to individual enzymes and physiologically relevant dual filters namely, solvent accessible surface area--a parameter dependent on protein three-dimensional structure and subcellular localization. By incorporating such hitherto unused principles in prediction methods, a novel ligand docking strategy to mimic substrate binding at the active site of the enzyme, and GO functions, we identify and perform subjective validation on putative substrates of matriptase and highlight new functions of the enzyme. Using relative solvent accessibility to rank order we show how new protease regulatory networks and enzyme cascades can be created. CONCLUSION: We believe that our physiologically relevant computational approach would be a very useful complementary method in the current day attempts to profile proteases (endo proteases in particular) and their substrates. In addition, by using functional annotations, we have demonstrated how normal and unknown functions of a protease can be envisaged. We have developed a network which can be integrated to create a proteolytic world. This network can in turn be extended to integrate other regulatory networks to build a system wide knowledge of the proteome

Rational design of organophosphorus hydrolase for the degradation and detection of neurotoxic pesticides and chemical warfare agents

It is critical to consider the balance between the catalytic capabilities of an enzyme and the inherent structural stability of the protein when developing enzymes for specific applications. Rational site directed mutagenesis has been used to explore the role of residues 254 and 257 in the global stability and catalytic specificities of organophosphorus hydrolase (OPH, EC 3.1.8.1). Substitution of residues H254 and H257, which are located near the active site, had a marked effect on both the global stability and substrate specificity of the enzyme. For example, the for the double mutation CoTGÃÂ2+ H254R H257L (RL) enzyme variant was 19.6 kcal/mol, 5.7 kcal/mol less than that of the wild type enzyme. At the same time, the altered enzyme was catalytically more effective against VX and VR (Russian VX), as compared to the wild type enzyme. Limited proteolysis verified the importance of residues 254 and 257 for functional stability, evidenced by enhanced resistance to irreversible unfolding associated with thermal denaturation. It has been possible to construct third generation OPH variants, which are more stable than the wild type enzyme, with a 10 ðC increase in the apparent melting temperature (TM app), yet retained desirable catalytic properties. It appeared that aromatic stacking and cation-àinteractions involving near active site residues not only affected activity but significantly contributed to the chemical and thermal stability of OPH. Rational design was used to develop an enzyme with an optimized orientation on a catalytically active biosensor surface. In these studies, lysine side chains located on the surface of OPH were used to create attachment sites to a surface plasmon resonance sensor resulting in an ensemble of enzyme orientations. Some of these orientations could be functionally restrictive if the active site is oriented toward the sensor surface. Substitution of a lysine near the active site resulted in 20% more activity with 53% less enzyme immobilized, thus increasing the specific activity of the decorated surface 2.5 fold