Thermodynamics of sequence-specific protein-DNA interactions

The molecular recognition processes in sequence-specific protein-DNA interactions are complex. The only feature common to all sequence-specific protein-DNA structures is a large interaction interface, which displays a high degree of complementarity in terms of shape, polarity and electrostatics. Many molecular mechanisms act in concert to form the specific interface. These include conformational changes in DNA and protein, dehydration of surfaces, reorganization of ion atmospheres, and changes in dynamics. Here we review the current understanding of how different mechanisms contribute to the thermodynamics of the binding equilibrium and the stabilizing effect of the different types of noncovalent interactions found in protein-DNA complexes. The relation to the thermodynamics of small molecule-DNA binding and protein folding is also briefly discussed.     

Prediction of mono- and di-nucleotide-specific DNA-binding sites in proteins using neural networks

Background  

DNA recognition by proteins is one of the most important processes in living systems. Therefore, understanding the recognition process in general, and identifying mutual recognition sites in proteins and DNA in particular, carries great significance. The sequence and structural dependence of DNA-binding sites in proteins has led to the development of successful machine learning methods for their prediction. However, all existing machine learning methods predict DNA-binding sites, irrespective of their target sequence and hence, none of them is helpful in identifying specific protein-DNA contacts. In this work, we formulate the problem of predicting specific DNA-binding sites in terms of contacts between the residue environments of proteins and the identity of a mononucleotide or a dinucleotide step in DNA. The aim of this work is to take a protein sequence or structural features as inputs and predict for each amino acid residue if it binds to DNA at locations identified by one of the four possible mononucleotides or one of the 10 unique dinucleotide steps. Contact predictions are made at various levels of resolution viz. in terms of side chain, backbone and major or minor groove atoms of DNA.     

Are Molecular Alphabets Universal Enabling Factors for the Evolution of Complex Life?

Terrestrial biosystems depend on macromolecules, and this feature is often considered as a likely universal aspect of life. While opinions differ regarding the importance of small-molecule systems in abiogenesis, escalating biological functional demands are linked with increasing complexity in key molecules participating in biosystem operations, and many such requirements cannot be efficiently mediated by relatively small compounds. It has long been recognized that known life is associated with the evolution of two distinct molecular alphabets (nucleic acid and protein), specific sequence combinations of which serve as informational and functional polymers. In contrast, much less detailed focus has been directed towards the potential universal need for molecular alphabets in constituting complex chemically-based life, and the implications of such a requirement. To analyze this, emphasis here is placed on the generalizable replicative and functional characteristics of molecular alphabets and their concatenates. A primary replicative alphabet based on the simplest possible molecular complementarity can potentially enable evolutionary processes to occur, including the encoding of secondarily functional alphabets. Very large uniquely specified (‘non-alphabetic’) molecules cannot feasibly underlie systems capable of the replicative and evolutionary properties which characterize complex biosystems. Transitions in the molecular evolution of alphabets can be related to progressive bridging of barriers which enable higher levels of biosystem organization. It is thus highly probable that molecular alphabets are an obligatory requirement for complex chemically-based life anywhere in the universe. In turn, reference to molecular alphabets should be usefully applied in current definitions of life.     

Reconsidering Darwin’s “Several Powers”

Contemporary textbooks often define evolution in terms of the replication, mutation, and selective retention of DNA sequences, ignoring the contribution of the physical processes involved. In the closing line of The Origin of Species, however, Darwin recognized that natural selection depends on prior more basic living functions, which he merely described as life’s “several powers.” For Darwin these involved the organism’s capacity to maintain itself and to reproduce offspring that preserve its critical functional organization. In modern terms we have come to recognize that this involves the continual generation of complex organic molecules in complex configurations accomplished with the aid of persistent far-from-equilibrium chemical self-organizing and self-assembling processes. But reliable persistence and replication of these processes also requires constantly available constraints and boundary conditions. Organism autonomy further requires that these constraints and co-dependent dynamics are reciprocally produced, each by the other. In this paper I argue that the different constraint-amplifying dynamics of two or more self-organizing processes can be coupled so that they reciprocally generate each other’s critical supportive boundary conditions. This coupling is a higher-order constraint (which can be distributed among components or offloaded onto molecular structures) that effectively constitutes a sign vehicle “interpreted” by the synergistic dynamics of these co-dependent self-organizing process so that they reconstitute this same semiotic-dynamic relationship and its self-reconstituting potential in new substrates. This dynamical co-dependence constitutes Darwin’s “several powers” and is the basis of the biosemiosis that enables evolution.     

Genomics and early cellular evolution. The origin of the DNA world.

The sequencing of several genomes from each of the three domains of life (Archaea, Bacteria and Eukarya) has provided a huge amount of data that can be used to gain insight about early cellular evolution. Some features of the universal tree of life based on rRNA polygenies have been confirmed, such as the division of the cellular living world into three domains. The monophyly of each domain is supported by comparative genomics. However, the hyperthermophilic nature of the 'last universal common ancestor' (LUCA) is not confirmed. Comparative genomics has revealed that gene transfers have been (and still are) very frequent in genome evolution. Nevertheless, a core of informational genes appears more resistant to transfer, testifying for a close relationship between archaeal and eukaryal informational processes. This observation can be explained either by a common unique history between Archaea and Eukarya or by an atypical evolution of these systems in Bacteria. At the moment, comparative genomics still does not allow to choose between a simple LUCA, possibly with an RNA genome, or a complex LUCA, with a DNA genome and informational mechanisms similar to those of Archaea and Eukarya. Further comparative studies on informational mechanisms in the three domains should help to resolve this critical question. The role of viruses in the origin and evolution of DNA genomes also appears an area worth of active investigations. I suggest here that DNA and DNA replication mechanisms appeared first in the virus world before being transferred into cellular organisms.     

Probability rule for chiral recognition

Molecular Chirality is of central interest in biological studies because enantiomeric compounds, while indistinguishable by most inanimate systems, show profoundly different properties in biochemical environments. Enantioselective separation methods, based on the differential recognition of two optical isomers by a chiral selector, have been amply documented. Also, great effort has been directed towards a theoretical understanding of the fundamental mechanisms underlying the chiral recognition process. Here we report a comprehensive data examination of enantio separation measurements for over 72000 chiral selector-select and pairs from the chiral selection compendium CHIRBASE. The distribution of alpha = k'(D)/k'(L) values was found to follow a power law, equivalent to an exponential decay for chiral differential free energies. This observation is experimentally relevant in terms of the number of different individual or combinatorial selectors that need to be screened in order to observe alpha values higher than a preset minimum. A string model for enantiorecognition (SMED) formalism is proposed to account for this observation on the basis of an extended Ogston three-point interaction model. Partially overlapping molecular interaction domains are analyzed in terms of a string complementarity model for ligand-receptor complementarity. The results suggest that chiral selection statistics may be interpreted in terms of more general concepts related to biomolecular recognition.     

Molecular mechanisms for the recognition of damaged DNA regions by peptides and proteins

DNA damages can lead to drastic perturbations of living cell cycle (e.g., in carcinogenesis) by inducing mutations in the genetic information. Therefore DNA repair processes play an important role during cell life by eliminating DNA damages before mutation fixation. Different repair processes are briefly presented in this review. Two probes were used to provide information on the mechanisms involved in the specific recognition of damaged DNA by proteins and enzymes of the DNA repair machinery. It will be shown that a simple tripeptide Lys-Trp-Lys is able to mimic two repair systems, namely, the photosensitized splitting of pyrimidine dimers and the cleavage of phosphodiester bonds at apurinic sites.     

Sequence-dependent dynamics in duplex DNA

The submicrosecond bending dynamics of duplex DNA were measured at a single site, using a site-specific electron paramagnetic resonance active spin probe. The observed dynamics are interpreted in terms of the mean squared amplitude of bending relative to the end-to-end vector defined by the weakly bending rod model. The bending dynamics monitored at the single site varied when the length and position of a repeated AT sequence, distant from the spin probe, were changed. As the distance between the probe and the AT sequence was increased, the mean squared amplitude of bending seen by the probe due to that sequence decreased. A model for the sequence-dependent internal flexural motion of duplex DNA, which casts the mean squared bending amplitudes in terms of sequence-dependent bending parameters, has been developed. The best fit of the data to the model occurs when the (AT)(n) basepairs are assumed to be 20% more flexible than the average of the basepairs within the control sequence. These findings provide a quantitative basis for interpreting the kinetics of biological processes that depend on duplex DNA flexibility, such as protein recognition and chromatin packaging.     

Single-molecule characterization of Fen1 and Fen1/PCNA complexes acting on flap substrates

Flap endonuclease 1 (Fen1) is a highly conserved structure-specific nuclease that catalyses a specific incision to remove 5′ flaps in double-stranded DNA substrates. Fen1 plays an essential role in key cellular processes, such as DNA replication and repair, and mutations that compromise Fen1 expression levels or activity have severe health implications in humans. The nuclease activity of Fen1 and other FEN family members can be stimulated by processivity clamps such as proliferating cell nuclear antigen (PCNA); however, the exact mechanism of PCNA activation is currently unknown. Here, we have used a combination of ensemble and single-molecule Förster resonance energy transfer together with protein-induced fluorescence enhancement to uncouple and investigate the substrate recognition and catalytic steps of Fen1 and Fen1/PCNA complexes. We propose a model in which upon Fen1 binding, a highly dynamic substrate is bent and locked into an open flap conformation where specific Fen1/DNA interactions can be established. PCNA enhances Fen1 recognition of the DNA substrate by further promoting the open flap conformation in a step that may involve facilitated threading of the 5′ ssDNA flap. Merging our data with existing crystallographic and molecular dynamics simulations we provide a solution-based model for the Fen1/PCNA/DNA ternary complex.     

Necessity of chance: biological roulettes and biodiversity

Chance plays an important role in the dynamics of biodiversity. It is largely responsible for the spontaneous processes leading to biological diversification. The mechanisms behind chance belong to two categories: on the one hand, those outside of biological systems, and thus belonging to their environment, on the other hand, those endogenous to these systems. These last mechanisms are present at all levels of the hierarchical organization of the living world, from genes to ecosystems. We propose calling them 'biological roulettes'. Like roulettes in casinos, they could be deterministic processes functioning in chaotic domains and producing results that look as though they had been generated by random processes. The spontaneous appearance and natural selection of these roulettes have led to living systems potentially adapted to new environmental conditions not encountered before. They may even have permitted some of them to survive major upheavals. Moreover, palaeontological data show that the rate of biological diversification accelerates and that living systems become more and more complex over time. That may also increase their resilience. It can be also the consequence of the appearance and the selection of 'biological roulettes' and of chance they generate. They are at the same time products and engines of the evolution. Without them, life would have disappeared from the Earth a long time ago. Thus, they are of primary importance.     

Otolith microstructure reveals ecological and oceanographic processes important to ecosystem-based management

Information obtained from fish otoliths has been a critical component of fisheries management for decades. The nature of this information has changed over time as management goals and approaches have shifted. The earliest and still most pervasively used data are those of annual age and growth used to calculate the demographic rates of populations in single-species management strategies. Over time, the absence of simple stock-recruitment relationships has focused attention on the youngest stages, where otolith microstructure resolved on a daily basis has become a valuable tool. As management has transitioned to more ecosystem-based approaches, the need to understand ecological and oceanographic processes has been advanced through the analysis of daily otolith microstructure. Recent field examples illustrate how otolith microstructure data have been used to reveal environmental influences on larval growth, traits that lead to higher survivorship, mechanisms of larval transport, dynamics of dispersal and population connectivity, determinants of recruitment magnitude, carry-over processes between life stages, habitat-specific juvenile survival, and identification of natal sources. Daily otolith-derived data collected at an individual level are increasingly combined with data from other disciplines and incorporated into individual-based models, which in turn can form the building blocks of complex models of ecosystem dynamics. A mechanistic understanding of the ecology of young stages is particularly necessary in light of a rapidly changing ocean environment, as we need to be able to predict individual and population responses to perturbations. Otolith microstructure analysis is an important tool in our management arsenal, contributing to a broader understanding of the oceanographic and ecological processes underlying ecosystem dynamics.     

Accomplishments and challenges in literature data mining for biology

We review recent results in literature data mining for biology and discuss the need and the steps for a challenge evaluation for this field. Literature data mining has progressed from simple recognition of terms to extraction of interaction relationships from complex sentences, and has broadened from recognition of protein interactions to a range of problems such as improving homology search, identifying cellular location, and so on. To encourage participation and accelerate progress in this expanding field, we propose creating challenge evaluations, and we describe two specific applications in this context.     

Interaction of human SRY protein with DNA: A molecular dynamics study

Molecular dynamics simulations have been conducted to study the interaction of human sex-determining region Y (hSRY) protein with DNA. For this purpose, simulations of the hSRY high mobility group (HMG) domain (hSRY-HMG) with and without its DNA target site, a DNA octamer, and the DNA octamer alone have been carried out, employing the NMR solution structure of hSRY-HMG–DNA complex as a starting model. Analyses of the simulation results demonstrated that the interaction between hSRY and DNA was hydrophobic, just a few hydrogen bonds and only one water molecule as hydrogen-bonding bridge were observed at the protein–DNA interface. These two hydrophobic cores in the hSRY-HMG domain were the physical basis of hSRY-HMG–DNA specific interaction. They not only maintained the stability of the complex, but also primarily caused the DNA deformation. The salt bridges formed between the positive-charged residues of hSRY and phosphate groups of DNA made the phosphate electroneutral, which was advantageous for the deformation of DNA and the formation of a stable complex. We predicted the structure of hSRY-HMG domain in the free state and found that both hSRY and DNA changed their conformations to achieve greater complementarity of geometries and properties during the binding process; that is, the protein increased the angle between its long and short arms to accommodate the DNA, and the DNA became bent severely to adapt to the protein, although the conformational change of DNA was more severe than that of the hSRY-HMG domain. The sequence specificity and the role of residue Met9 are also discussed. Proteins 31:417–433, 1998. © 1998 Wiley-Liss, Inc.     

What is Life? Defining Life in the Context of Emergent Complexity

Erwin Schrödinger defined life not only as a “self-reproducing” aperiodic crystal of DNA coding for proteins but within the context of living entities increasing their order by dissipating matter/energy gradients to maintain themselves away from equilibirium. Since then most definitions of life have focused on the former. But living cells do more than replicate their DNA. Cells also have membrane barriers across which metabolites must move, via which energy transduction as well as information processing occurs, and within which metabolic transformation occurs. An approach of complex systems dynamics, including nonequilibrium thermodynamics, may provide a more robust approach for defining life than a “naked replicator” at the origin of life. The crucial issue becomes the process of emergence of life from pre-biotic chemistry, concomitant with the emergence of function, information, and semiosis. Living entities can be viewed as bounded, informed autocatalytic cycles feeding off matter/energy gradients, exhibiting agency, capable of growth, reproduction, and evolution. Understanding how life might have emerged should sharpen our definition of what life is.     

Putting the ‘bio’ into bioinformatics

Bioinformatic analyses have grown rapidly in sophistication and efficiency to accommodate the vast increase in available data. One of the major challenges has been to incorporate the growing appreciation of the complexity of molecular evolution into new analytical methods. As the reliance on molecular data in biology and medicine increases, we need to be confident that these methods adequately reflect the underlying processes of genome change. This special issue focuses on the way that patterns and processes of molecular evolution are influenced by features of populations of whole organisms, such as selection pressure, population size and life history. The advantage of this approach to molecular evolution is that it views genomic change not simply as a biochemical or stochastic process, but as the result of a complex series of interactions that shape the kinds of genomic changes that can and do happen.     

Directed evolution of novel polymerases

DNA and RNA polymerases evolved to function in specific environments with specific substrates to propagate genetic information in all living organisms. The commercial availability of these polymerases has revolutionized the biotechnology industry, but for many applications native polymerases are limited by their stability or substrate recognition. Thus, there is great interest in the directed evolution of DNA and RNA polymerases to generate enzymes with novel, desired properties, such as thermal stability, resistance to inhibitors, and altered substrate specificity. Several screening and selection approaches have been developed, both in vivo and in vitro, and have been used to evolve polymerases with a variety of important activities. Both the techniques and the evolved polymerases are reviewed here, along with a comparison of the in vivo and in vitro approaches.