Ab Initio Protein Structure Prediction Using Evolutionary Approach: A Survey

Protein Structure Prediction (PSP) problem is to determine the three-dimensional structure of a protein only from its primary structure. Misfolding of a protein causes human diseases. Thus, the knowledge of the structure and functionality of proteins, combined with the prediction of their structure is a complex problem and a challenge for the area of computational biology. The metaheuristic optimization algorithms are naturally applicable to support in solving NP-hard problems.These algorithms are bio-inspired, since they were designed based on procedures found in nature, such as the successful evolutionary behavior of natural systems. In this paper, we present a survey on methods to approach the \textit{ab initio} protein structure prediction based on evolutionary computing algorithms, considering both single and multi-objective optimization. An overview of the works is presented, with some details about which characteristics of the problem are considered, as well as specific points of the algorithms used. A comparison between the approaches is presented and some directions of the research field are pointed out

Divergence, Recombination and Retention of Functionality During Protein Evolution

We have only a vague idea of precisely how protein sequences evolve in the context of protein structure and function. This is primarily because structural and functional contexts are not easily predictable from the primary sequence, and evaluating patterns of evolution at individual residue positions is also difficult. As a result of increasing biodiversity in genomics studies, progress is being made in detecting context-dependent variation in substitution processes, but it remains unclear exactly what context-dependent patterns we should be looking for. To address this, we have been simulating protein evolution in the context of structure and function using lattice models of proteins and ligands (or substrates). These simulations include thermodynamic features of protein stability and population dynamics. We refer to this approach as \u27ab initio evolution\u27 to emphasise the fact that the equilibrium details of fitness distributions arise from the physical principles of the system and not from any preconceived notions or arbitrary mathematical distributions. Here, we present results on the retention of functionality in homologous recombinants following population divergence. A central result is that protein structure characteristics can strongly influence recombinant functionality. Exceptional structures with many sequence options evolve quickly and tend to retain functionality--even in highly diverged recombinants. By contrast, the more common structures with fewer sequence options evolve more slowly, but the fitness of recombinants drops off rapidly as homologous proteins diverge. These results have implications for understanding viral evolution, speciation and directed evolutionary experiments. Our analysis of the divergence process can also guide improved methods for accurately approximating folding probabilities in more complex but realistic systems

The molecular basis of central element assembly within the synaptonemal complex during meiosis

PhD ThesisIn the first meiotic division, homologous chromosomes must pair, synapsis, exchange genetic material through crossing over, and then segregate to allow haploid germ cell production. This challenging process is triggered by double-strand break (DSB) induction, which activates repair machinery to generate recombination intermediates between homologues. These physical tethers guide synaptonemal complex (SC) assembly; a supramolecular lattice producing continuous synapsis between homologues. The SC provides the necessary three-dimensional structure for recombination intermediate resolution, including crossover formation, therefore is essential for meiotic division and thereby fertility. The underlying mammalian SC lattice is provided through self-assembly of SYCP1. However, a further five central element (CE) proteins are essential for full SC structure and function in vivo. A direct biochemical interaction was identified between human SYCP1 and CE protein SYCE3, revealing the sole physical link between SYCP1 and the CE. Light and Xray scattering experiments elucidated conformational re-modelling upon interacting, with SYCE3 modifying the SYCP1 lattice to achieve its regular incorporation. SYCE3 further interacts with, and thereby recruits, other CE proteins thus acting as a molecular glue for SC maturation. The CE SYCE2-TEX12 complex is recruited via SYCE3 binding, and undergoes fibrous assembly to achieve SC elongation. Through identification of two mutants that separately block SYCE2-TEX12 4:4 complex formation and its fibrous assembly, coupled with detailed biophysical analysis and two X-ray crystal structures, a structural model is proposed for the SYCE2-TEX12 complex and the mechanism of fibrous assembly. Analysis of mammalian SC assembly in vivo is severely hampered by the lack of a genetically tractable system. Whilst SC structure is conserved in yeast, protein constituents show no overt sequence similarity; thus, structural studies of the yeast SC were initiated to understand the underlying conservation. Yeast CE proteins, Ecm11-Gmc2, form a constitutive 2:2 complex with a structural model presented based upon solution scattering studies

A molecular model for the role of SYCP3 in meiotic chromosome organisation.

The synaptonemal complex (SC) is an evolutionarily-conserved protein assembly that holds together homologous chromosomes during prophase of the first meiotic division. Whilst essential for meiosis and fertility, the molecular structure of the SC has proved resistant to elucidation. The SC protein SYCP3 has a crucial but poorly understood role in establishing the architecture of the meiotic chromosome. Here we show that human SYCP3 forms a highly-elongated helical tetramer of 20 nm length. N-terminal sequences extending from each end of the rod-like structure bind double-stranded DNA, enabling SYCP3 to link distant sites along the sister chromatid. We further find that SYCP3 self-assembles into regular filamentous structures that resemble the known morphology of the SC lateral element. Together, our data form the basis for a model in which SYCP3 binding and assembly on meiotic chromosomes leads to their organisation into compact structures compatible with recombination and crossover formation. DOI: http://dx.doi.org/10.7554/eLife.02963.00

Computational Design and Study of Structural and Dynamic Nucleic Acid Systems

abstract: DNA and RNA are generally regarded as one of the central molecules in molecular biology. Recent advancements in the field of DNA/RNA nanotechnology witnessed the success of usage of DNA/RNA as programmable molecules to construct nano-objects with predefined shapes and dynamic molecular machines for various functions. From the perspective of structural design with nucleic acid, there are basically two types of assembly method, DNA tile based assembly and DNA origami based assembly, used to construct infinite-sized crystal structures and finite-sized molecular structures. The assembled structure can be used for arrangement of other molecules or nanoparticles with the resolution of nanometers to create new type of materials. The dynamic nucleic acid machine is based on the DNA strand displacement, which allows two nucleic acid strands to hybridize with each other to displace one or more prehybridized strands in the process. Strand displacement reaction has been implemented to construct a variety of dynamic molecular systems, such as molecular computer, oscillators, in vivo devices for gene expression control. This thesis will focus on the computational design of structural and dynamic nucleic acid systems, particularly for new type of DNA structure design and high precision control of gene expression in vivo. Firstly, a new type of fundamental DNA structural motif, the layered-crossover motif, will be introduced. The layered-crossover allow non-parallel alignment of DNA helices with precisely controlled angle. By using the layered-crossover motif, the scaffold can go through the 3D framework DNA origami structures. The properties of precise angle control of the layered-crossover tiles can also be used to assemble 2D and 3D crystals. One the dynamic control part, a de-novo-designed riboregulator is developed that can recognize single nucleotide variation. The riboregulators can also be used to develop paper-based diagnostic devices.Dissertation/ThesisDoctoral Dissertation Chemistry 201

Evolving Cellular Automata Schemes for Protein Folding Modeling Using the Rosetta Atomic Representation

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG [Abstract] Protein folding is the dynamic process by which a protein folds into its final native structure. This is different to the traditional problem of the prediction of the final protein structure, since it requires a modeling of how protein components interact over time to obtain the final folded structure. In this study we test whether a model of the folding process can be obtained exclusively through machine learning. To this end, protein folding is considered as an emergent process and the cellular automata tool is used to model the folding process. A neural cellular automaton is defined, using a connectionist model that acts as a cellular automaton through the protein chain to define the dynamic folding. Differential evolution is used to automatically obtain the optimized neural cellular automata that provide protein folding. We tested the methods with the Rosetta coarse-grained atomic model of protein representation, using different proteins to analyze the modeling of folding and the structure refinement that the modeling can provide, showing the potential advantages that such methods offer, but also difficulties that arise.This study was funded by the Xunta de Galicia and the European Union (European Regional Development Fund - Galicia 2014-2020 Program), with grants CITIC (ED431G 2019/01), GPC ED431B 2019/03 and IN845D-02 (funded by the “Agencia Gallega de Innovación”, co-financed by Feder funds), and by the Spanish Ministry of Science and Innovation (project PID2020-116201GB-I00). Open Access funding provided thanks to the CRUE-CSIC agreement with Springer NatureXunta de Galicia; ED431G 2019/01Xunta de Galicia; ED431B 2019/03Xunta de Galicia; IN845D-0