Due to the high parallelism and recognition ability of the biomolecules in biochemical reactions, biomolecular computing behaves great advantage in solving combinatorial optimization problems. Biomolecular computing has been successfully applied in computing NP complete problems such as Hamiltonion path problem, maximal clique problem and SAT problems in Boolean calculation, etc. This paper presents a review of fundamental ideas, computing methods, applications and advances in biomolecular computing. Furthermore, the developmental trend of biomolecular computing is described.

As an important heuristic optimization algorithm, genetic algorithm (GA) has been widely applied in computer-aided drug design (CADD). In this paper, the basic concept and mechanism of GA were introduced. More-over, combining the research work in authors' group, the applications of GA in quantitative structure-activity relation-ship, conformational analysis, pharmacophore modeling, molecular docking and virtual combinatorial chemistry, were re-viewed.

In recent years, the methods of calculating free energies based on the combination of molecular dynamics simulations and continuum solvation models have drawn more and more attention, in which MM/PBSA is the most repre-sentational one. In MM/PBSA, the sum of molecular mechanical energies of the molecules is calculated from molecular mechanics (MM); the polar solvation energy in continuum solvent is usually computed using a finite-difference Poisson-Boltzmann (PB) model; and the nonpolar solvation energy is often obtained from the solvent-accessible surface area (SA). In this paper, the progress and application of MM/PBSA, as well as some research works in our group, are intro-duced.

Macromolecules including surfactants can aggregate to form micelles with various shapes in solution, and this character makes it widely used in the applications of industrial and living fields. It is significant to study the charac-ters of aggregation of surfactants, especially for the study of aggregation of amphiphilic macromolecules in life sciences and for biomineralization or biomimetic synthesis. In this paper, the progress in computer simulation of macromolecules self-assembling is summarized from the thermodynamic and molecular dynamic point of view.

Extractive distillation is an important and useful technique for separating close boiling and azeotropic liquid mixtures. The selection of appropriate solvents for extractive distillation is the key to improve the production capacity and reduce the energy consumption. Computer-aided molecular design (CAMD) is on the basis of property estimate method , generating a set of solvent molecular structures with desirable properties and screening the candidate molecules. There are three main CAMD approaches : generation-and-test , mathematical optimization , and combinatorial optimizations. The generation-and-test usually implements heuristics or knowledge-based methods to combat combinatorial explosion of group combinations , can't guarantee the quality of the results. The mathematical optimization approach ,which includes MINLP (mixed-integer nonlinear programming) and MILP (mixed-integer linear programming) problems ,has been applied to the nonlinear or linear structure-property correlations , but exact expression of the structure-property correlations may be very difficult or even impossible. Thus , the third approach , combinatorial optimization such as genetic algorithm(GA) and simulated annealing (SA) , is implemented in CAMD and can easily handle combinatorial complexity of the molecular design. In this paper , the principle of three approaches is depicted , and a comparison among three approaches is made. Furthermore , the major encounter problems in the industrialization of the selection of solvents are also discussed.

Multidimensional quantitative structure-activity relationship (MD QSAR) has been successfully applied as a crucial technique for computeraided drug design (CADD) in various fields. Based on plentiful literatures, different strategies and various methodologies of MD QSAR are systematically summarized by combining with research works in authors'  laboratory. Recent progress of MD QSAR in CADD is reviewed.

With simple introduction of the history of micro fluidic chip, the mathematically modeling and solving for electrophoresis processes on microchip, including governing equations of electrical field, flow field, concentration distribution and mass transport are reviewed. Furthermore, the progress on computer assisted design of channel networks on electrophoresis microchip, concerning sampling and separation channel, is discussed.

The quantum chemical theoretic and experimental studies on the configuration, state of aggregation and carbocyanine molecular structure domino effect of its properties are introduced in this paper. The advances of study in the carbocyanine molecular quantum chemical calculation are reviewed. The progress direction of the carbocyanine molecular quantum chemical calculation is summed up.

Discovering potential drug leads has played a key role in the drug development. As a new method or technology for drug discovery, virtual screening via molecular docking has been developed as a practical tool complemented with high throughput empirical screening, and is now a widespread drug lead identification method in the pharmaceutical industry. In this review, we will introduce recent advances in discovering drug leads via docking, synthesis and bioassay focused on our laboratory work.

Finding a theoretical calculation method to obtain the accurate solvation free energy and pKa value so as to verify or complement the experimental data has long been an important aspect for many theoretical chemists. In this review, an overview of quantum chemistry computation research achievements concerning solvation free energy and pK_a value of organic compounds in aqueous or organic mediums with the PCM solvation model in the recent few years is presented. The accuracy and characteristics of different computational methods are also discussed.

Hydrogen is the most promising energy carrier in future and hydrogen storage technology is the key problem for hydrogen application. With the development of computational materials science, density functional theory(DFT) and first principles quantum mechanical calculations have been effectively utilized to study the performance of existing hydrogen storage materials and explore new light hydrogen storage materials. The theoretical and experimental studies on metal-carbon-based hydrogen storage materials in recent years are reviewed in this paper, including metal-decorated carbon nanotubes，C₆₀ and transition-metal-ethylene complexes, and so on. The future of metal-carbon-based hydrogen storage materials is also anticipated.

Contents
1 Introduction
2 Metal decorated carbon-nanotubes and C₆₀ hydrogen storage materials
2.1 Progress on experimental research
2.2 Progress on theoretical research
3 Transition-metal-ethylene complexes hydrogen storage
3.1 Progress on experimental research
3.2 Progress on theoretical research
4 Outlook

Protein kinases regulate signal transduction pathways in cell by phosphorylating the protein kinase substrate, and they are important targets in drug design. Protein kinase A (PKA) is the first kinase that was obtained X-ray structure of its catalytic domain, and is regarded as prototype for protein kinase superfamily. The progress in computational chemistry study of protein kinase A has been reviewed, including the molecular dynamics simulation study of PKA holoenzyme and its C subunit and R subunit in aqueous solution, phosphoryl transfer mechanism, the binding free energy predicting and flexible docking of C subunit with its inhibitor balanol. Various computational approaches are applied to this system, including molecular dynamics simulation, dock, homology modeling, QM/MM.

Contents
1 Introduction
2 Molecular dynamics simulation study on PKA
2.1 Molecular dynamics simulation study on C subunit
2.2 Modeling of the complex of C subunit and R subunit
2.3 Molecular dynamics simulation study on R subunit
3 Phosphoryl transfer mechanism
4 Balanol
4.1 Prediction of binding free energy
4.2 Flexible protein-flexible ligand docking
4.3 Mechanism of high selectivity of balanol analogue BD2
4.4 Functional role of structure water molecules in the recognition of C subunit and BD2
5 Conclusion and outlook

Cyclodextrins have played an important role in the development of supramolecular chemistry. They have been extensively studied both experimentally and theoretically due to their special physical and chemical properties. In this paper, the progress in the theoretical calculations of the cyclodextrin chemistry over the past decade is reviewed. In particular, some recent applications of molecular dynamics simulations and free-energy calculations in the investigation of the recognition and assembly behavior of cyclodextrins are emphasized. In addition, the theoretical research trends of cyclodextrins are discussed.

Contents
1 Introduction
2 Computational methods
2.1 Quantum mechanics (QM)
2.2 Molecular mechanics/molecular dynamics (MM/MD)
2.3 Docking
2.4 Quantitative structure–activity relationship (QSAR)
3 Applications of molecular modeling to the study of cyclodextrins
3.1 Structural features of cyclodextrins
3.2 Hydration of cyclodextrins
3.3 Molecular recognition by cyclodextrins
3.4 Molecular self-assembly of cyclodextrins
4 Conclusion and outlook

We briefly reviewed the recent advances in computational actinide chemistry during the past ten years. They cover two issues: the geometrical and electronic structures, and reactions. The former addresses the An—O and M—An (M is another metal atom including An) bonds in the actinide molecular systems, and the latter the hydration and ligand exchange, the disproportionation, the oxidation, the reduction of uranyl, hydroamination, and the photolysis of uranium azide.

Contents
1 Introduction
2 Treatment of relativistic effects
3 Computational Models
3.1 Density functional theory
3.2 Wavefunction based ab initio methods
4 Applications in actinide chemistry
4.1 The role of 5f orbitals
4.2 Geometry and electronic structure
4.3 Reactions
5 Conclusion and outlook
6 Acknowledgement

 

We review and update selected contributions to computational chemistry made since the late 1950s. Introductory remarks are given to place our work in the context of contemporary science. We start with a classical benchmark, the H₂ wave-function constructed with a new one-particle representation, the Chemical spin-Orbitals, which replaces the traditional Atomic and Molecular spin-Orbitals. Computations from diatomic to small polyatomic molecules, obtained with the Hartree-Fock-Heitler-London (HF-HL) model, are compared to those obtained from the traditional Hartree-Fock (HF) and Heitler-London (HL) methods; we conclude that the hierarchy of solutions within the HF-HL approach represents a general and reasonable choice for computational quantum chemistry. Further, we show that a wave function constructed with Chemical spin-Orbitals is equivalent to a wave-function obtained with the HF-HL model. These simulations are complemented with a critical analysis on the correlation energy, and on Wigner and Coulomb Hole functionals. The above studies follow the early Hartree-Fock period (1960-1970) characterised by pioneering computations on atomic and molecular systems, including basis set optimisation, atomic energy tabulation at the Hartree-Fock and post Hartree-Fock level, and potential energy surface computations obtained with the super-molecular approach. However, to deal with large molecular systems and to explicitly consider temperature and time, we must turn to statistical methods; we recall simulations using Monte Carlo, Molecular Dynamics, and Langevin dynamics, first at equilibrium, then for open systems at non-equilibrium. A concatenation of these models constitutes to the Global Simulation approach, discussed in detail. The above work requires both computer hardware and application codes in different areas of computational chemistry. We recall the quantum chemical atomic and molecular codes and the statistical mechanics codes written, documented and freely distributed for the last half century. Further, we recall our pioneering efforts in the early 1980s in computer architecture, with the design and assembly of a parallel supercomputer extensively used to perform the first parallel applications in computational chemistry. Contents 1 Introduction: Where we are? 2 From quantum mechanics to early quantum chemistry 3 The helium atom and the hydrogen molecule 4 Ψ_CO: The chemical orbital wave-function 5 Comparison of molecular computations: from the HF and HL to the HF-HL methods 6 The wave functions from HF-HL and from chemical spin-orbitals models 7 Density functional approximations, DFA, a pragmatic approach to obtain correlation energy corrections 8 Variations on Wigner’s proposal 9 The Coulomb hole approximation in atoms and molecules 10 Decomposition of the correlation energy 11 From atoms to molecules (1950—1965) 12 Basis set for atoms and molecules 13 Energy surfaces for interacting molecules 14 From quantum mechanics of small molecules to larger systems: energetic predictions with inclusion of time, temperature and solvent 15 From molecular dynamics to micro-dynamics 16 Parallel computer architecture 17 Global simulations 18 Conclusions

Molecular simulation is an effective method to study microstructure, thermodynamics and dynamic properties of ionic liquids from the molecule interaction.While quantum chemistry calculations can be used to study structure, properties and catalysis mechanism of ionic liquids theoretically at the molecular and electronic level.In this paper, the recent progress of molecular simulation applied in ionic liquids was reviewed; the studiees of different ionic liquids using molecular dynamic simulation and quantum chemistry calculations to obtain the structural properties, spectral properties (infrared spectrum,Raman spectrum) and reaction mechanisms of ionic liquids are mainly introduced.It aims to provide some theoretical advises for the research of structure-property relationship,interaction of ion pair,catalytic acivity sity,reaction pathway,activation energy, vibrational frequencies and design of ionic liquids.

Contents
1 Introduction
2 Molecular simulation of ionic liquids
3 Quantum chemical calculation of ionic liquids
3.1 Structural properties
3.2 Spectral properties
3.3 Reaction mechanism
4 Perspective

Biological apatite is the main inorganic mineral component of animal and human bone and tooth enamel, moreover apatite mineral composition and structure affect on the bone and tooth enamel mechanical strength and physiological behavior. The structure of hydroxyapatite (HAP) has proved more difficult to resolve, two different hydroxyl arrangements may occur in HAP resulting in hexagonal and monoclinic structures. Extensive isomorphic substitutions may greatly affect the properties of this mineral. In the paper, computational methods are well placed to calculate at the atomic level the geometry and relative energies of the various possible hydroxy groups in apatite, and they have been employed to study the uptake and distribution of small molecule or biomacromolecule in the hydroxyapatite. Application of computer simulation at the atomic level to investigate apatites, especially HAP, is anticipated to provide a deeper understanding of crystal chemistry and interaction with biomacromolecules. These results offer a more comprehensive investigation of bio-apatite and perspective applications.

Contents
1 Introduction
2 Applications of computer simulation to the apatite crystal
3 Applications of computer simulation to the apatite substitution
4 The interaction of apaptite and other molecules or ions
4.1 The interaction of apaptite and water molecules
4.2 The interaction of apaptite and haloid ions
4.3 The interaction of apaptite and citric acid molecules
4.4 The interaction of apaptite and biologic molecules
5 Conclusions and Outlook

Computer-aided rational protein design was demonstrated to be effective in addressing important issues in chemistry and biology. With computer simulation, a structural and functional nitric oxide reductase (NOR) was successfully designed using myoglobin (Mb) as a protein model, which was accomplished at the time with no three dimensional structure available for NOR itself. More importantly, the designed NOR protein model, Fe_BMb, was confirmed by an X-ray structure of native NOR one year later. The progress and rationalities of design of Fe_BMb, I107E Fe_BMb, as well as Fe_BMb(-His), were reviewed herein. The use of molecular simulation to obtain atomic structural information on Mb in a non-native state with bis-Histidine coordination was also highlighted, as the information was otherwise difficult to obtain experimentally. The general application of computer-aided rational protein design will provide deep insight into biological systems.

Contents
1 Introduction
2 Myoglobin: an ideal scaffold for protein molecular design
3 Nitric oxide reductase: both a chance and a challenge for protein molecular design
4 Exploring unknown areas: ongoing of protein molecular design
5 Conclusion and outlook

In modern quantum chemistry, valence bond (VB) theory and molecular orbital (MO) theory are the two general theoretical approaches for chemical bonding. VB theory provides clear interpretation and chemical insights by employing covalent and ionic VB structures explicitly. This review focuses on the methodology development of the current modern classical VB methods in the improvement of computational accuracy and the extension of application areas. Moreover, the further development of modern classical VB methods is briefly prospected. Contents
1 Introduction
2 Ab initio VB methods
2.1 VBSCF
2.2 BOVB
2.3 VBCI
2.4 VBPT2
3 Ab initio VB methods for complicated systems
3.1 VBSCF
3.2 VBSM
3.3 VB/MM
4 Conclusion and perspective

Zinc enzymes play a variety of essential biological roles, and their functions and/or structural organizations are critically dependent on the zinc binding site. However, the zinc coordination shell is so complicated that an accurate and powerful theoretical simulation protocol is highly required in calculation. Herein, we review the recent studies of the selected zinc enzymes by the state-of-the-art combined quantum mechanism/molecular mechanism molecular dynamics (QM/MM MD) simulations in probing the reaction mechanism and revealing the relationship of structure and function. Meanwhile, the accuracy of all the current available pairwise force fields to describe zinc coordination structure is very poor, so the recent development of force fields for zinc enzyme is also presented. By the end of this review, some prospects and suggestions are given for further exploration of zinc enzyme. 1 Significance and challenges of zinc enzymes
1.1 Zinc enzyme
1.2 Challenges of experimental research in zinc enzyme
1.3 Challenges of computational research in zinc enzym
2 Recent advance of computational research in zinc enzyme
2.1 QM/MM study of zinc enzyme
2.2 Force field development for zinc enzyme
3 Outlook

This review starts with the most basic concepts in photochemistry, followed by the introduction of developing process of theoretical methods and the related typical applications, as well as our comments. We pursue a goal that the readers can integrally understand the discipline of computational photochemistry by this review. We also indicated the effect of hardware development and the current difficulties and problems in the computational photochemistry for peer discussion. Contents
1 Introduction
2 Basic concepts in photochemistry
2.1 Potential energy surface
2.2 Vertical and adiabatic excitation energy
2.3 Conical intersection
3 Development of computational methods and typical applications in photochemistry
3.1 Semi-empirical methods
3.2 Single-reference ab initio methods
3.3 Multi-reference ab initio methods
3.4 TDDFT methods
3.5 Some combined or improved methods
3.6 Brief comments on all kinds of methods
4 Effect of the development of hardware on the computational photochemsitry
5 Conclusions and outlook

Carbon can exist in many different forms at different temperatures and pressures. Some allotropes of carbon have been predicted in theory but still have not been found in nature. In this article, we mainly overview a number of three-dimensional (3D) crystalline carbon allotropes, predicted by ab initio calculations. Particular attention will be placed on the carbon foams, which possess porous structures with a large surface area. Carbon foams are mostly composed of graphite segments connected by different types of carbon bonds. We will also review 3D carbon superstructures of low-dimensional allotropes, typically built from carbon fullerenes, nanobuds, nanotubes and graphene nanoribbons, as well as various other 3D crystalline carbon structures. Some of these carbon superstructures are composed of mixed sp-sp² carbon or pure sp² carbon (e.g., H-6, bct-4, C-20, K₄), and some have larger mass density than diamond (C₈, hP3, tl12, tp12), and some can be transformed from graphite at room temperature and high pressure (e.g., M carbon, bct-4 carbon, W carbon, Z carbon). Some of these theoretically predicted carbon allotropes may be synthesized in the laboratory in future.

The studies of gaseous reactive scattering dynamics by quantum wave packet method, especially at product-states resolved level, are reviewed. The current numerical methods for extracting product-states resolved attributives using quantum wave packet method are discussed. This theory now can present detailed and accurate predictions on the dynamics and kinetics of reactions containing three or four atoms. Several typical reactive scattering systems which have been studied using quantum wave packet method at product-states resolved level are briefed. Contents
1 Introduction
2 Brief review of historical development of quantum wave packet method applications in reactive scattering field
3 Theoretical methods of quantum wave packet
3.1 Discrete variable representation
3.2 Construction of initial wave packet and S-matrix extraction
3.3 Popular propagators
4 Theoretical methods for extraction product-states resolved information using quantum wave packet method
4.1 Product Jacobi coordinate based method
4.2 Reactant Jacobi coordinate based method
4.3 Reactant product-decoupling method
5 Typical reactive scattering systems studied by quantum wave packet method at product-states resolved level
5.1 Typical triatomic molecules reactive scattering
5.2 Typical tetraatomic molecules reactive scattering
6 Conclusions and outlook

N-H···OC、C-H···OC、N-H···N and C-H···N hydrogen bonds are the main factors for the formation of protein a-helices and b-sheets and for the formation of the double helices of the deoxyribonucleic acid. These hydrogen bonds also play important roles in the processes of the protein-nucleic acid recognition, in the processes of the protein replication, and in the processes of transcription and expression of genetic information from DNA to protein. Accurate and rapid determination of the strengths of the hydrogen bonds and their dynamic properties in DNA and protein systems is very important for correctly simulating and therefore deeply understanding the mechanism of protein folding processes and the formation mechanism of the double helices of the deoxyribonucleic acid and for designing new biomolecular materials possessing special function. In this review, a dipole-dipole hydrogen bonding model and its applications to the hydrogen-bonded complexes containing peptide amides and/or nucleic acid bases are introduced. Contents
1 Introduction
2 Hydrogen bond model and parameterization
2.1 The dipole-dipole hydrogen bonding model
2.2 Parameterization
3 Applications
3.1 Calculation of the hydrogen bond strengths and hydrogen bonding potential energy curves for amide-amide and amide-water hydrogen-bonded dimers
3.2 Calculation of the total binding energies and potential energy curves for hydrogen-bonded complexes made of peptide amides and nucleic acid bases
3.3 Calculation of the total binding energies and potential energy curves for protein β-sheets
4 Conclusion and outlook

Peptide is traditionally recognized as an important kind of biologically active substance, which involves in various physiological processes associated with the growth and development of organism. In recent years, however, since it was found that peptide plays a central role in cell signaling and could be exploited as therapeutic drugs targeting protein-protein interaction networks, researchers have redirected their interest to peptide-related topics. In particular, rapidly increasing efforts have been addressed on the use of computational and theoretical methods to investigate the physicochemical properties and biological implications underlying peptide recognition and interaction with protein. Here, we engage the theme “computational peptidology” to cover the field where the methods, strategies and protocols of computational chemistry and bioinformatics are employed to study peptides and peptide mimics. A systematic discussion is also addressed on the database configuration, function inference, molecular docking, dynamics simulation, structure analysis, design and modification, and systems biology of peptides. Through this perspective, we lay our emphasis on protein-peptide recognition and binding which are the basis of peptide-mediated protein interactions and peptidic drug discovery. We also rise the potential applications of computational peptidology in exploring and designing new peptide-based nanomaterials and biological surfactants. Contents 1 Introduction
2 The branches of computational peptidology
2.1 Peptide database
2.2 Peptide function prediction
2.3 Peptide docking
2.4 Peptide dynamics simulation
2.5 Peptide structure analysis
2.6 Peptide design and modification
2.7 Peptide systems biology
3 Conclusions and outlook

Due to the difference in the property of each block, block copolymers can self-assemble into various nanoscale morphologies spontaneously, including sphere, rod, ring, lamella, vesicle and compound micelle etc. These micelles have potential applications in nanotechnology such as drug delivery, catalysts, electronic information and so on. Recently, the computer simulations are widely used to monitor the process of self-assembly, reveal the mechanism of self-assembly, and illuminate the influence of various control factors on micellar structures, which can provide mentality and theoretical support for the experimental research. This review mainly summarizes the latest progresses in computer simulation of self-assembly of block copolymers in selective solvent, and discussed various effects on the micellar morphologies and the process of self-assembly. Moreover, the future development in this filed is also discussed in this review.

Contents
1 Introduction
2 Self-assembly of AB diblock copolymers in selective solvents
3 Self-assembly of ABA triblock copolymers in selective solvents
3.1 Self-assembly of ABA triblock copolymers in A-selective solvents
3.2 Self-assembly of ABA triblock copolymers in B-selective solvents
4 Self-assembly of ABC triblock copolymers in selective solvents
4.1 Self-assembly of ABC triblock copolymers in A-and C-selective solvents
4.2 Self-assembly of ABC triblock copolymers in C-selective solvents
4.3 Self-assembly of ABC miktoarm star terpolymers in selective solvents
5 Self-assembly of mixtures of copolymers in selective solvents
6 Conclusion and outlook

Au-nanoparticles have volume effect, surface effect, quantum size effect, macroscopic quantum tunneling effect and other excellent properties. In addition, there are some special properties for Au-nanoparticles, such as good stability, antibacterial function, surface absorption, fluorescence effect belt and so on. Quantum chemistry calculation provides a method to investigate the factors that affect the catalytic and reactive activity of gold clusters at the molecular level, such as the gold cluster size, shape, electronic state, active site and structure, etc. The interaction modes of nanoparticles with ligands and solvent can be better simulated by molecular dynamics, which can also give the behavior of thermodynamic and kinetic. Dissipative particle dynamics mesoscopic simulation method is applied to study the self-assembly process of Au-nanoparticles and polymer composite system, which would be an effective scheme to control the self-assembled structure. To clear the dominant factors influencing the complex structure and properties, to explore the complex regulation mechanism, to propose the main control factors, which is good for the further understanding the nature of Au-nanoparticles and polymer composite system. It is also providing a reliably theoretical help for experiments to prepare and optimize the new kinds of composite materials.

Contents
1 Introduction
1.1 Au-nanoparticles
1.2 Polymers
2 Computer simulation methods
2.1 Quantum chemistry,QC
2.2 Molecular dynamics,MD
2.3 Brownian dynamics,BD
2.4 Dissipative particle dynamics,DPD
3 Assembly of Au-nanoparticles and polymer composites
3.1 Au-nanoparticles and homopolymer
3.2 Au-nanoparticles and copolymer
4 Conclusion

The development in computer science has brought a great impetus to the advance of human society. However, as the manufacturing process goes to the limit, there is an urgent need to find a new computing system to meet the growing demand for computing. DNA computing has attracted great attention due to its advantages in huge information storage, large scale parallelism and very low energy consumption. Many different models have been established ever since the experimental implementation of solving a 6 vertices Hamilton pathway problem by Adleman in 1994. In this paper, a brief introduction to the basic principles and experimental operations in DNA computing is first given, and the theories in this field are illustrated, including the DNA sequence design, complexity of different models and the proof of universal computing power. Moreover, the models regarded as breakthroughs in the field are summarized. All the models are classified based on the specific means in conducting the experiment, and reviewed according to different classes. More detailed descriptions are further set forth for a classical model in each class. At last, a prospect is made based on our work in this area.
Contents
1 Introduction
2 Principles and experimental operations of DNA computing
2.1 Principles of DNA computing
2.2 Experimental operations of DNA computing
3 Advances in DNA computing related theories
3.1 Principles of DNA sequence design
3.2 Universal computing power of DNA
4 Five kinds of DNA computing models
4.1 Parallel overlap assembly model
4.2 Sticker model
4.3 Splicing model
4.4 DNA Tile self-assembly model
4.5 Biochemistry signal based logic circuits model
5 Conclusion and outlook

Molecular dynamics(MD) simulations with free energy calculations have been widely applied to chemistry, biology and material science. However, within the timescale of conventional MD simulations, ergodic sampling in phase space is limited due to high free-energy barriers. Insufficient sampling may, in turn, lead to poor convergence of the free energy calculations based on conventional MD simulations. Enhanced sampling is a powerful technique to overcome this difficulty, among which importance sampling method is the most representative one. In this paper, the principles and progress of four prevalent importance sampling methods, namely, umbrella sampling(US), metadynamics(MtD), adaptive biasing force(ABF) and temperature accelerated molecular dynamics(TAMD), are described and reviewed. In particular, the recent developments of ABF, such as the extended ABF(eABF) considered as the second generation of ABF, and the extended generalized ABF(egABF) methods designed for high dimensional sampling, are comprehensively summarized. The advantages and disadvantages of US, MtD, TAMD and ABF with their variants are presented and compared. Furthermore, challenges and outlooks for free energy calculation with importance sampling methods are discussed and prospected. Specifically, possible further improvements to current ABF methods, such as combination with accelerated molecular dynamics(aMD) simulations or string methods to enhance sampling efficiency in high-dimensional spaces are put forward.
Contents
1 Introduction
2 Umbrella sampling
3 Metadynamics
4 Adaptive biasing force
4.1 Extended adaptive biasing force
4.2 Extended generalized adaptive biasing force
5 Temperature accelerated molecular dynamics
6 Conclusion and outlook

Hydrocarbons play an important role in industrial productionses. The separation and purification of hydrocarbons is one of the most important industrial processes. The separation of low carbon hydrocarbon gases is extremely difficult since their physicochemical properties are similar. The minor differences are their molecular size and valence state. The traditional separation methods suffer from the high energy consumption and low efficiency. Metal-organic frameworks show superiority in separations due to their unique properties including high specific surface area, high porosity and controllable structure size. Computational simulation has been widely used in the investigations of adsorption and separation of MOFs since it can describe the adsorption and separation process at the microscopic level. This paper reviews the recent advances in computational simulations for the adsorption and separation of low-carbon hydrocarbons by metal-organic frameworks. The difficulties and future developments in the study of adsorption and separation of low carbon hydrocarbons by metal-organic frameworks have also been discussed.