Free energy landscape and characteristic forces for the initiation of DNA unzipping

DNA unzipping, the separation of its double helix into single strands, is crucial in modulating a host of genetic processes. Although the large-scale separation of double-stranded DNA has been studied with a variety of theoretical and experimental techniques, the minute details of the very first steps of unzipping are still unclear. Here, we use atomistic molecular dynamics (MD) simulations, coarse-grained simulations and a statistical-mechanical model to study the initiation of DNA unzipping by an external force. The calculation of the potential of mean force profiles for the initial separation of the first few terminal base pairs in a DNA oligomer reveal that forces ranging between 130 and 230 pN are needed to disrupt the first base pair, values of an order of magnitude larger than those needed to disrupt base pairs in partially unzipped DNA. The force peak has an "echo," of approximately 50 pN, at the distance that unzips the second base pair. We show that the high peak needed to initiate unzipping derives from a free energy basin that is distinct from the basins of subsequent base pairs because of entropic contributions and we highlight the microscopic origin of the peak. Our results suggest a new window of exploration for single molecule experiments.Comment: 25 pages, 6 figures , Accepted for publication in Biophysical Journa

Mixed Quantum Mechanical/Molecular Mechanical Molecular Dynamics Simulations of Biological Systems in Ground and Electronically Excited States

The current state of the art of Quantum Mechanical/molecular mechanical (QM/MM) molecular dynamics approaches in ground and electronically excited states and their applications to biological problems is reviewed. For a complete description of quantum phenomena, the quantum nature of both electrons and nuclei has to be taken into account. Most of the current QM/MM applications are based on adiabatic dynamics in the electronic ground state. However, for dynamics in electronically excited states, the coupling between states, which is mediated via the nuclear motion, can be sizable, and nonadiabatic effects have to be taken into account. Configuration Interaction Singles (CIS) is a popular method in QM/MM applications due to its computational expedience that allows for the treatment of several hundred atoms. Since the 1990s, the Modified Neglect of Differential Overlap (MNDO) method has been further extended to a d orbital basis. This MNDO/d extension allows for the treatment of heavier elements. By using feature selection algorithms348 to identify the most appropriate subset of relevant variables that describe a certain phenomenon, the high-dimensionality of QM/MM data can be reduced and used for further analysis with causal inference algorithms to establish unique cause-effect relationships

A Mechanochemical Switch to Control Radical Intermediates

B12-dependent enzymes employ radical species with exceptional prowess to catalyze some of the most chemically challenging, thermodynamically unfavorable reactions. However, dealing with highly reactive intermediates is an extremely demanding task, requiring sophisticated control strategies to prevent unwanted side reactions. Using hybrid quantum mechanical/molecular mechanical simulations, we follow the full catalytic cycle of an AdoB12-dependent enzyme and present the details of a mechanism that utilizes a highly effective mechanochemical switch. When the switch is “off”, the 5′-deoxyadenosyl radical moiety is stabilized by releasing the internal strain of an enzyme-imposed conformation. Turning the switch “on,” the enzyme environment becomes the driving force to impose a distinct conformation of the 5′-deoxyadenosyl radical to avoid deleterious radical transfer. This mechanochemical switch illustrates the elaborate way in which enzymes attain selectivity of extremely chemically challenging reactions

Genetic-Algorithm-Based Optimization of a Peptidic Scaffold for Sequestration and Hydration of CO

Biomimicry is a strategy that makes practical use of evolution to find efficient and sustainable ways to produce chemical compounds or engineer products. Exploring the natural machinery of enzymes for the production of desired compounds is a highly profitable investment, but the design of efficient biomimetic systems remains a considerable challenge. An ideal biomimetic system self-assembles in solution, binds a desired range of substrates and catalyzes reactions with turnover rates similar to the native system. To this end, tailoring catalytic functionality in engineered peptides generally requires site-directed mutagenesis or the insertion of additional amino acids, which entails an intensive search across chemical and sequence space. Here we discuss a novel strategy for the computational design of biomimetic compounds and processes that consists of a) characterization of the wild-type and biomimetic systems; b) identification of key descriptors for optimization; c) an efficient search through sequence and chemical space to tailor the catalytic capabilities of the biomimetic system. Through this proof-of-principle study, we are able to decisively understand and identify whether a given scaffold is useful, appropriate and tailorable for a given, desired task

Directed evolution of the suicide protein O⁶-alkylguanine-DNA alkyltransferase for increased reactivity results in an alkylated protein with exceptional stability

Here we present a biophysical, structural, and computational analysis of the directed evolution of the human DNA repair protein O-6-alkylguanine-DNA alkyltransferase (hAGT) into SNAP-tag, a self-labeling protein tag. Evolution of hAGT led not only to increased protein activity but also to that the reactivity of the suicide enzyme can be influenced by higher stability, especially of the alkylated protein, suggesting stabilizing the product of the irreversible reaction. Whereas wild-type hAGT is rapidly degraded in cells after alkyl transfer, the high stability of benzylated SNAP-tag prevents proteolytic degradation. Our data indicate that the intrinstic stability of a key a helix is an important factor in triggering the unfolding and degradation of wild-type hAGT upon alkyl transfer, providing new insights into the structure-function relationship of the DNA repair protein

Evolution of gene knockout strains of <i>E-coli</i> reveal regulatory architectures governed by metabolism

The function of metabolic genes in the context of regulatory networks is not well understood. Here, the authors investigate the adaptive responses of E. coli after knockout of metabolic genes and highlight the influence of metabolite levels in the evolution of regulatory function