TRIFORCE: Tessellated Semianalytical Solvent Exposed Surface Areas and Derivatives.

We present a new approach to the calculation of solvent-accessible surface areas of molecules with potential application to surface area based methods for determination of solvation free energies. As in traditional analytical and statistical approaches, this new algorithm, called TRIFORCE, reports both component areas and derivatives as a function of the atomic coordinates and radii. Unique to TRIFORCE are the rapid and scalable approaches for the determination of sphere intersection points and numerical estimation of the surface areas, derivatives, and other properties that can be associated with the surface area facets. The algorithm performs a special tessellation and semianalytical integration that uses a precomputed look-up table. This provides a simple way to balance numerical accuracy and memory usage. TRIFORCE calculates derivatives in the same manner, enabling application in force-dependent activities such as molecular geometry minimization. TRIFORCE is available free of charge for academic purposes as both a C++ library, which can be directly interfaced to existing molecular simulation packages, and a web-accessible application.

Chromatin-bound IκBα regulates a subset of polycomb target genes in differentiation and cancer.

IκB proteins are the primary inhibitors of NF-κB. Here, we demonstrate that sumoylated and phosphorylated IκBα accumulates in the nucleus of keratinocytes and interacts with histones H2A and H4 at the regulatory region of HOX and IRX genes. Chromatin-bound IκBα modulates Polycomb recruitment and imparts their competence to be activated by TNFα. Mutations in the Drosophila IκBα gene cactus enhance the homeotic phenotype of Polycomb mutants, which is not counteracted by mutations in dorsal/NF-κB. Oncogenic transformation of keratinocytes results in cytoplasmic IκBα translocation associated with a massive activation of Hox. Accumulation of cytoplasmic IκBα was found in squamous cell carcinoma (SCC) associated with IKK activation and HOX upregulation.

Multiscale molecular dynamics of protein aggregation.

The 60's gave birth to the practical implementation of classical mechanics to unravel the dynamics and energetics of biomolecules. In the 70's the use of generalized force fields and more advanced integrative solutions to the microscopic understanding of nature (like hybrid QM/MM) were introduced. During the 80's, algorithms to obtain free energy values were further developed and in the 90's practical integration schemes of molecular mechanics force fields with other levels of detail (QM on one extreme and advances in implicit solvation on the other) were implemented in widely spread software. In the first decade of the XXIst century a considerable effort has been put in two seemingly discordant models for the simulation of biomolecules. On the one hand, extraordinary advances in computing technologies (both in terms of processor power and of new efficient parallel and distributed computing schemas) have allowed researchers to deal with bigger systems and longer simulations, reaching molecular processes including millions of particles or lying in the microsecond scale. On the other hand, the realization that the relevant answers to many biomolecular problems are not homogeneously distributed through the molecular structure, something already envisioned by the QM/MM pioneers more than three decades ago, has led researchers to find smart ways of putting different emphases on different ranges of the spatial or system time scale. In this context, e.g., molecular aggregation represents a paradigm for multiscalability, as molecular recognition can be understood with simple (semi-)macroscopic terms when the two fragments are far apart, while the atomic interactions need to be considered in full detail upon close distances. In this manuscript the current status of the techniques that use multiple scale representations of biomolecules are reviewed, and the findings are synthesized in a modular schema that can be extensively used when studying aggregation processes. It is shown that a smart alternative to brute force and massive computation of uninteresting regions in the all atom potential energy surface is the consideration of a simplified reference potential, explored thoroughly in the relevant regions, combined with a free energy perturbation approach that transforms this simple representation to a full atom representation.