Entropic analysis reveals a connection between the recurrence of cancer and chemotherapy.

In this study, we proposed an entropic analysis to overcome limitations of conventional statistical methods to analyze clinical data for cancer patients who experienced relapse of tumors following chemotherapy. We have applied this entropic method to reveal potential mechanisms that lead to a relapse of Wilms' tumor in pediatric patients. Results indicate ß-tubulin isotype III up-regulation is likely the primary cause of the relapse.

A unified approach to computational drug discovery.

It has been reported that a slowdown in the development of new medical therapies is affecting clinical outcomes. The FDA has thus initiated the Critical Path Initiative project investigating better approaches. We review the current strategies in drug discovery and focus on the advantages of the maximum entropy method being introduced in this area. The maximum entropy principle is derived from statistical thermodynamics and has been demonstrated to be an inductive inference tool. We propose a unified method to drug discovery that hinges on robust information processing using entropic inductive inference. Increasingly, applications of maximum entropy in drug discovery employ this unified approach and demonstrate the usefulness of the concept in the area of pharmaceutical sciences.

Mathematical and computational modeling in biology at multiple scales.

A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.

Homology and molecular dynamics models of toll-like receptor 7 protein and its dimerization.

Toll-like receptor protein 7 is a transmembrane protein playing a crucial role in the signaling pathways involved in innate immunity. Its crystal structure is not yet available, but there are several proteins possessing domains of sufficiently high homology, which enabled us to build a model of the toll-like receptor protein 7 monomer and gain insights into dimer formation. To obtain a reliable structure prediction, we subjected this model to equilibration using molecular dynamics simulations. Furthermore, the equilibrated monomer structure was used to construct models of dimerization and to predict binding sites for small ligands. Docking studies were performed for some of the known toll-like receptor protein 7 ligands. We determined that a new homology model generated by the LOOPP server provides a good alternative to a previously reported model. Our docking results indicate that the addition of either imiquimod or 1V209 to a toll-like receptor protein 7 dimer changes an unfavorable interaction into a favorable one. We found that eight small molecules docked to two pockets in toll-like receptor protein 7 bind to both pockets at pH 7 and at pH 5.5. This work provides a realistic model that could be used for drug discovery aimed at finding toll-like receptor protein 7 dimerization activators, with potential clinical applications to a host of diseases, including cancer.

A computationally designed DNA aptamer template with specific binding to phosphatidylserine.

The phospholipid phosphatidylserine (PS) is an early marker exploited for detecting apoptosis (PS externalization in the cell membrane bilayer) and one factor that is associated with increased amyloid plaque deposition in transmissible spongiform encephalopathies (TSEs). PS can therefore be considered as a promising target for diagnosis or treatment of diseases. Aptamers (short nucleic acid sequences) are a particularly attractive class of materials among those currently considered for targeting PS. Here we applied an entropy based seed-and-grow strategy to design a DNA aptamer template to bind specifically to PS. The binding properties of designed aptamers were investigated computationally and experimentally. The studies identify the sequence, 5'-AAAGAC-3', as the preferred template for further modifications and studies toward its practical implementations.

Chemotherapy drugs form ion pores in membranes due to physical interactions with lipids.

We demonstrate the effects on membrane of the tubulin-binding chemotherapy drugs: thiocolchicoside and taxol. Electrophysiology recordings across lipid membranes in aqueous phases containing drugs were used to investigate the drug effects on membrane conductance. Molecular dynamics simulation of the chemotherapy drug-lipid complexes was used to elucidate the mechanism at an atomistic level. Both drugs are observed to induce stable ion-flowing pores across membranes. Discrete pore current-time plots exhibit triangular conductance events in contrast to rectangular ones found for ion channels. Molecular dynamics simulations indicate that drugs and lipids experience electrostatic and van der Waals interactions for short periods of time when found within each other's proximity. The energies from these two interactions are found to be similar to the energies derived theoretically using the screened Coulomb and the van der Waals interactions between peptides and lipids due to mainly their charge properties while forming peptide-induced ion channels in lipid bilayers. Experimental and in silico studies together suggest that the chemotherapy drugs induce ion pores inside lipid membranes due to drug-lipid physical interactions. The findings reveal cytotoxic effects of drugs on the cell membrane, which may aid in novel drug development for treatment of cancer and other diseases.

Modeling the yew tree tubulin and a comparison of its interaction with paclitaxel to human tubulin.

PURPOSE: To explore possible ways in which yew tree tubulin is naturally resistant to paclitaxel. While the yew produces a potent cytotoxin, paclitaxel, it is immune to paclitaxel's cytotoxic action. METHODS: Tubulin sequence data for plant species were obtained from Alberta 1000 Plants Initiative. Sequences were assembled with Trinity de novo assembly program and tubulin identified. Homology modeling using MODELLER software was done to generate structures for yew tubulin. Molecular dynamics simulations and molecular mechanics Poisson-Boltzmann calculations were performed with the Amber package to determine binding affinity of paclitaxel to yew tubulin. ClustalW2 program and PHYLIP package were used to perform phylogenetic analysis on plant tubulin sequences. RESULTS: We specifically analyzed several important regions in tubulin structure: the high-affinity paclitaxel binding site, as well as the intermediate binding site and microtubule nanopores. Our analysis indicates that the high-affinity binding site contains several substitutions compared to human tubulin, all of which reduce the binding energy of paclitaxel. CONCLUSIONS: The yew has achieved a significant reduction of paclitaxel's affinity for its tubulin by utilizing several specific residue changes in the binding pocket for paclitaxel.

Entropic fragment-based approach to aptamer design.

Aptamers are short RNA/DNA sequences that are identified through the process of systematic evolution of ligands by exponential enrichment and that bind to diverse biomolecular targets. Aptamers have strong and specific binding through molecular recognition and are promising tools in studying molecular biology. They are recognized as having potential therapeutic and diagnostic clinical applications. The success of the systematic evolution of ligands by exponential enrichment process requires that the RNA/DNA pools used in the process have a sufficient level of sequence diversity and structural complexity. While the systematic evolution of ligands by exponential enrichment technology is well developed, it remains a challenge in the efficient identification of correct aptamers. In this article, we propose a novel information-driven approach to a theoretical design of aptamer templates based solely on the knowledge regarding the biomolecular target structures. We have investigated both theoretically and experimentally the applicability of the proposed approach by considering two specific targets: the serum protein thrombin and the cell membrane phospholipid phosphatidylserine. Both of these case studies support our method and indicate a promising advancement in theoretical aptamer design. In unfavorable cases where the designed sequences show weak binding affinity, these template sequences can be still modified to enhance their affinities without going through the systematic evolution of ligands by exponential enrichment process.

From laws of inference to protein folding dynamics.

Protein folding dynamics is one of major issues constantly investigated in the study of protein functions. The molecular dynamic (MD) simulation with the replica exchange method (REM) is a common theoretical approach considered. Yet a trade-off in applying the REM is that the dynamics toward the native configuration in the simulations seems lost. In this work, we show that given REM-MD simulation results, protein folding dynamics can be directly derived from laws of inference. The applicability of the resulting approach, the entropic folding dynamics, is illustrated by investigating a well-studied Trp-cage peptide. Our results are qualitatively comparable with those from other studies. The current studies suggest that the incorporation of laws of inference and physics brings in a comprehensive perspective on exploring the protein folding dynamics.

Quantitative analysis of the effect of tubulin isotype expression on sensitivity of cancer cell lines to a set of novel colchicine derivatives.

BACKGROUND: A maximum entropy approach is proposed to predict the cytotoxic effects of a panel of colchicine derivatives in several human cancer cell lines. Data was obtained from cytotoxicity assays performed with 21 drug molecules from the same family of colchicine compounds and correlate these results with independent tubulin isoform expression measurements for several cancer cell lines. The maximum entropy method is then used in conjunction with computed relative binding energy values for each of the drug molecules against tubulin isotypes to which these compounds bind with different affinities. RESULTS: We have found by using our analysis that alphabetaI and alphabetaIII tubulin isoforms are the most important isoforms in establishing predictive response of cancer cell sensitivity to colchicine derivatives. However, since alphabetaI tubulin is widely distributed in the human body, targeting it would lead to severe adverse side effects. Consequently, we have identified tubulin isotype alphabetaIII as the most important molecular target for inhibition of microtubule polymerization and hence cancer cell cytotoxicity. Tubulin isotypes alphabetaI and alphabetaII are concluded to be secondary targets. CONCLUSIONS: The benefit of being able to correlate expression levels of specific tubulin isotypes and the resultant cell death effect is that it will enable us to better understand the origin of drug resistance and hence design optimal structures for the elimination of cancer cells. The conclusion of the study described herein identifies tubulin isotype alphabetaIII as a target for optimized chemotherapy drug design.

Integrity of H1 helix in prion protein revealed by molecular dynamic simulations to be especially vulnerable to changes in the relative orientation of H1 and its S1 flank.

In the template-assistance model, normal prion protein (PrPC), the pathogenic cause of prion diseases such as Creutzfeldt-Jakob in human, bovine spongiform encephalopathy in cow, and scrapie in sheep, converts to infectious prion (PrPSc) through an autocatalytic process triggered by a transient interaction between PrPC and PrPSc. Conventional studies suggest the S1-H1-S2 region in PrPC to be the template of S1-S2 beta-sheet in PrPSc, and the conformational conversion of PrPC into PrPSc may involve an unfolding of H1 in PrPC and its refolding into the beta-sheet in PrPSc. Here we conduct a series of simulation experiments to test the idea of transient interaction of the template-assistance model. We find that the integrity of H1 in PrPC is vulnerable to a transient interaction that alters the native dihedral angles at residue Asn(143), which connects the S1 flank to H1, but not to interactions that alter the internal structure of the S1 flank, nor to those that alter the relative orientation between H1 and the S2 flank.