FOLD-RATE: prediction of protein folding rates from amino acid sequence

We have developed a web server, FOLD-RATE, for predicting the folding rates of proteins from their amino acid sequences. The relationship between amino acid properties and protein folding rates has been systematically analyzed and a statistical method based on linear regression technique has been proposed for predicting the folding rate of proteins. We found that the classification of proteins into different structural classes shows an excellent correlation between amino acid properties and folding rates of two and three-state proteins. Consequently, different regression equations have been developed for proteins belonging to all-α, all-β and mixed class. We observed an excellent agreement between predicted and experimentally observed folding rates of proteins; the correlation coefficients are, 0.99, 0.97 and 0.90, respectively, for all-α, all-β and mixed class proteins. The prediction server is freely available at

design of selective peptide antibiotics by using the sequence moment concept

New antibiotics against multidrug-resistant bacteria are urgently needed, but rapid acquisition of resistance limits their usefulness. Endogenous antimicrobial peptides (AMPs) with moderate selectivity, but multimodal mechanism of action, have remained effective against bacteria for millions of years. Their therapeutic application, however, requires optimizing the balance between antibacterial activity and selectivity, so that rational design methods for increasing selectivity are highly desirable. We have created training (n=36) and testing (n=37) sets from frog-derived AMPs with determined therapeutic index (TI). The 'sequence moments' concept then enabled us to find a one-parameter linear model resulting in a good correlation between measured and predicted TI (r2=0.83 and 0.64 for each set, respectively). The concept was then used in the AMP-Designer algorithm to propose primary structures for highly selective AMPs against Gram-negative bacteria. Testing the activity of one such peptide produced a TI>200 as compared to the best AMP in the data-base, with TI=125

A mixture of physicochemical and evolutionary–based feature extraction approaches for protein fold recognition

Griffith Sciences, Griffith School of EngineeringFull Tex

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences

<p>Abstract</p> <p>Background</p> <p>Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences.</p> <p>Results</p> <p>The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes.</p> <p>Conclusions</p> <p>The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at <url>http://biomine.ece.ualberta.ca/MODAS/</url>.</p

Computational and Experimental Approaches to Reveal the Effects of Single Nucleotide Polymorphisms with Respect to Disease Diagnostics

DNA mutations are the cause of many human diseases and they are the reason for natural differences among individuals by affecting the structure, function, interactions, and other properties of DNA and expressed proteins. The ability to predict whether a given mutation is disease-causing or harmless is of great importance for the early detection of patients with a high risk of developing a particular disease and would pave the way for personalized medicine and diagnostics. Here we review existing methods and techniques to study and predict the effects of DNA mutations from three different perspectives: in silico, in vitro and in vivo. It is emphasized that the problem is complicated and successful detection of a pathogenic mutation frequently requires a combination of several methods and a knowledge of the biological phenomena associated with the corresponding macromolecules

Dizajn i testiranje adepantina – novih peptidnih antibiotika

As an important part of the innate immune system of all organisms, antimicrobial peptides, are considered as a possible solution for fighting bacteria resistant to standard antibiotics.Crucial characteristic of peptide antibiotic, as drug candidate is its high selectivity, parameterized as the ratio of concentration causing 50% haemolysis (HC50) against erythrocytes and the minimal inhibitory concentration (MIC) against the reference bacterium Escherichia coli. Using the “Designer” algorithm adepantins were designed - highly selective artificial glycine and lysine rich peptides in predominant α helical conformation, having less than 50% homology of primary sequence to any known sequence of antimicrobial peptides. The algoritham used our database of anuran antimicrobial peptides with known selectivity index. Structure and activity of adepantins were experimentally and computationally tested in their monomeric, dimeric and fluorescently labelled form. Experimental investigations performed on different bacteria strains showed high selectivity of adepantins for Gram-negative bacteria ( MIC = 0.5 - 4 μM ), especially E. coli. In membrane permeabilization measurements, different membrane models were used and adepantins showed rapid permeabilization of both membranes of E. coli. These tests provided insight in their mode of action. All monomeric adepantins have exceptionally low haemolytic activity, while dimers expressed certain toxicity against host cells. It is proven that adepantins bind efficiently to the cell surface of the host cell membranes without subsequent membrane damage. Gathered results confirmed that adepantins are indeed highly selective artificial peptide antibiotics.Kao važan dio urođenog imunološkog sustava svih živih bića, antimikrobni peptidi, smatraju se možebitnim riješenjem u brobi protiv bakterija otpornih na standardne antibiotike. Važna osobina dobrog kandidata za budući lijek njegova je selektivnost, koja se određuje kao omjer koncentracije pri kojoj se opaža 50%-tna hemolitična aktivnost prema eritrocitima i minimalne inhibitorne koncentracije pri kojoj se opaža 100%-tna inhibicija rasta bakterije Escherichije coli. Algoritmom „Designer“ dizajnirani su adepantini–veoma selektivni umjetni peptid i u konformaciji α uzvojnice, bogati glicinom i lizinom, a sličnost njihovih sekvenci s poznatim antimikrobnim peptidima manja je od 50%. Algoritam je koristio našu bazu podataka antimikrobnih peptida iz anura s poznatim indeksom selektivnosti. Eksperimentalnim i računalnim metodama istražene su strukture i aktivnosti monomera, dimera i fluorescentno označenih oblika adepantina. Eksperimentalna istraživanja provedena na različitim sojevima bakterija pokazala su visoku selektivnost adepantina prema Gram-negativnim bakterijama ( MIC = 0.5 - 4 μM ), naročito prema E. coli. U mjerenju propusnosti membrana rabljeni su različiti modeli membrana, a pokazalo se da adepantini vrlo brzo povećavaju propusnost obje membrane E. coli. Time je dobiven uvid u mehanizme djelovanja adepantina. Svi monomeri adepantina imaju izrazito malu hemolitičnost prema eritrocitima, dok su dimeri pokazali određenu toksičnost prema ljudskim stanicama. Dokazano je da se adepantini vežu na staničnu površinu ljudskih stanica bez popratnog oštećenja membrane. Prikupljeni rezultati potvrdili su adepantine kao jako selektivne umjetne peptidne antibiotike

Dizajn i testiranje adepantina – novih peptidnih antibiotika

As an important part of the innate immune system of all organisms, antimicrobial peptides, are considered as a possible solution for fighting bacteria resistant to standard antibiotics.Crucial characteristic of peptide antibiotic, as drug candidate is its high selectivity, parameterized as the ratio of concentration causing 50% haemolysis (HC50) against erythrocytes and the minimal inhibitory concentration (MIC) against the reference bacterium Escherichia coli. Using the “Designer” algorithm adepantins were designed - highly selective artificial glycine and lysine rich peptides in predominant α helical conformation, having less than 50% homology of primary sequence to any known sequence of antimicrobial peptides. The algoritham used our database of anuran antimicrobial peptides with known selectivity index. Structure and activity of adepantins were experimentally and computationally tested in their monomeric, dimeric and fluorescently labelled form. Experimental investigations performed on different bacteria strains showed high selectivity of adepantins for Gram-negative bacteria ( MIC = 0.5 - 4 μM ), especially E. coli. In membrane permeabilization measurements, different membrane models were used and adepantins showed rapid permeabilization of both membranes of E. coli. These tests provided insight in their mode of action. All monomeric adepantins have exceptionally low haemolytic activity, while dimers expressed certain toxicity against host cells. It is proven that adepantins bind efficiently to the cell surface of the host cell membranes without subsequent membrane damage. Gathered results confirmed that adepantins are indeed highly selective artificial peptide antibiotics.Kao važan dio urođenog imunološkog sustava svih živih bića, antimikrobni peptidi, smatraju se možebitnim riješenjem u brobi protiv bakterija otpornih na standardne antibiotike. Važna osobina dobrog kandidata za budući lijek njegova je selektivnost, koja se određuje kao omjer koncentracije pri kojoj se opaža 50%-tna hemolitična aktivnost prema eritrocitima i minimalne inhibitorne koncentracije pri kojoj se opaža 100%-tna inhibicija rasta bakterije Escherichije coli. Algoritmom „Designer“ dizajnirani su adepantini–veoma selektivni umjetni peptid i u konformaciji α uzvojnice, bogati glicinom i lizinom, a sličnost njihovih sekvenci s poznatim antimikrobnim peptidima manja je od 50%. Algoritam je koristio našu bazu podataka antimikrobnih peptida iz anura s poznatim indeksom selektivnosti. Eksperimentalnim i računalnim metodama istražene su strukture i aktivnosti monomera, dimera i fluorescentno označenih oblika adepantina. Eksperimentalna istraživanja provedena na različitim sojevima bakterija pokazala su visoku selektivnost adepantina prema Gram-negativnim bakterijama ( MIC = 0.5 - 4 μM ), naročito prema E. coli. U mjerenju propusnosti membrana rabljeni su različiti modeli membrana, a pokazalo se da adepantini vrlo brzo povećavaju propusnost obje membrane E. coli. Time je dobiven uvid u mehanizme djelovanja adepantina. Svi monomeri adepantina imaju izrazito malu hemolitičnost prema eritrocitima, dok su dimeri pokazali određenu toksičnost prema ljudskim stanicama. Dokazano je da se adepantini vežu na staničnu površinu ljudskih stanica bez popratnog oštećenja membrane. Prikupljeni rezultati potvrdili su adepantine kao jako selektivne umjetne peptidne antibiotike

Molecular Science for Drug Development and Biomedicine

With the avalanche of biological sequences generated in the postgenomic age, molecular science is facing an unprecedented challenge, i.e., how to timely utilize the huge amount of data to benefit human beings. Stimulated by such a challenge, a rapid development has taken place in molecular science, particularly in the areas associated with drug development and biomedicine, both experimental and theoretical. The current thematic issue was launched with the focus on the topic of “Molecular Science for Drug Development and Biomedicine”, in hopes to further stimulate more useful techniques and findings from various approaches of molecular science for drug development and biomedicine