入侵杂草化感作用的细胞自动机模拟研究

细胞自动机模型(Cellular Automata Model,简称CA模型)是一种能够表现系统复杂行为的模拟方法,适于研究植物群落时空动态过程.本文利用CA模型,模拟具有化感作用的外来种入侵原有物种所构成植被的过程.模型由产生化感物质的外来种和两个对化感物质敏感性不同的本地种组合成不同类型的群落,利用化感物质作用下受体物种生物活性响应模型及种子扩散负指数分布模型,模拟外来杂草和本地种分布格局的时空动态变化.结果表明,外来种可成功地完全入侵由两个对化感物质敏感的本地种构成的群落空间,但对于由对化感物质敏感的一个本地种及对化感物质具有抗性的另一个本地种构成的群落,外来种只能够与本地种共存.     

3D-QSAR studies of checkpoint kinase 1 inhibitors based on molecular docking and CoMFA

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of substituted 1,4-dihydroindeno[1,2-c]pyrazoles inhibitors, using molecular docking and comparative molecular field analysis (CoMFA). The docking results from GOLD 3.0.1 provide a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA model was built with cross-validated q ² value of 0.534 and non-cross-validated partial least-squares analysis with the optimum components of six showed a conventional r ² value of 0.911. The predictive ability of this model was validated by the testing set with a conventional r ² value of 0.812. Based on the docking and CoMFA, we have identified some key features of the 1,4-dihydroindeno[1,2-c]pyrazoles derivatives that are responsible for checkpoint kinase 1 inhibitory activity. The analyses may be used to design more potent 1,4-dihydroindeno[1,2-c]pyrazoles derivatives and predict their activity prior to synthesis.     

Integrated computational approaches to screen gene expression data to determine key genes and therapeutic targets for type-2 diabetes mellitus

There is a rapid rise in cases of Type-2-diabetes mellitus (T2DM) globally, irrespective of the geography, ethnicity or any other variable factors. The molecular mechanisms that could cause the condition of T2DM need to be more thoroughly analysed to understand the clinical manifestations and to derive better therapeutic regimes. Tools in bioinformatics are used to trace out key gene elements and to identify the key causative gene elements and their possible therapeutic agents. Microarray datasets were retrieved from the Gene expression omnibus database and studied using R to derive different expressed gene (DEG) elements. With the comparison of the expressed genes with disease specific genes in DisGeNET, the final annotated genes were taken for analysis. Gene Ontology studies, Protein–protein interaction (PPI), Co-expression analysis, Gene-drug interactions were performed to scale down the hub genes and to identify the novelty across the genes analysed so far. In vivo and invitro analysis of key genes and the trace of interaction pathway is crucial to better understand the unique outcomes from the novel genes, forming the basis to understand the pathway that ends up causing T2DM. Afterwards, docking was executed enabling recognition of interacting residues involved in inhibition. The complex CCL5-265 and CD8A-40585 thus docked showed best results as is evident from its PCA analysis and MMGBSA calculation. There is now scope for deriving candidate drugs that could possibly detect personalized therapies for T2DM.     

Hydrogen bond analysis of confined water in mesoporous silica using the reactive force field

ABSTRACT

The structural and dynamical properties of water confined in nanoporous silica with a pore diameter of 2.7?nm were investigated by performing large-scale molecular dynamics simulations using the reactive force field. The radial distribution function and diffusion coefficient of water were calculated, and the values at the centre of the pore agreed well with experimental values for real water. In addition, the pore was divided into thin coaxial layers, and the average number of hydrogen bonds, hydrogen bond lifetime and hydrogen bond strength were calculated as a function of the radial distance from the pore central axis. The analysis showed that hydrogen bonds involving silanol (Si–OH) have a longer lifetime, although the average number of hydrogen bonds per atom does not change from that at the pore centre. The longer lifetime, as well as smaller diffusion coefficient, of these hydrogen bonds is attributed to their greater strength.     

Mechanistic insights into the inhibition of prostate specific antigen by beta-lactam class compounds

Prostate Specific Antigen (PSA) is a biomarker used in the diagnosis of prostate cancer and to monitor therapeutic response. However, its precise role in prostate carcinogenesis and metastasis remains largely unknown. A number of studies arguing in the favor of an active role of PSA in prostate cancer development and progression have implicated this serine protease in the release and activation of growth factors such as insulin-like growth factor 1 (IGF1) through cleavage of insulin like growth factor binding protein 3 and Transforming Growth Factor beta (TGF-beta) through cleavage of Latent TGF-beta. In contrast, other studies suggest that PSA activity might hinder tumor development and progression. In light of these contradictory findings, efficient inhibitors of PSA are needed for exploring its biological role in tumor development and metastasis. Towards the goal of developing potent inhibitors of PSA, we have explored the molecular mechanism of a series of beta-lactam based compounds on binding to PSA using activity assays, matrix assisted laser desorption ionization with a time-of-flight mass spectrometry, and GOLD docking methodology. The mass spectrometry experiments and the activity assays confirmed the time-dependent and covalent nature of beta-lactam binding. To gain insights on the reaction intermediates at the molecular level, we docked beta-lactam inhibitors to a homology modeled PSA using the GOLD docking program in noncovalent and covalent binding modes. The docking studies elucidated the molecular details of the early noncovalent Michaelis complex, the acyl-enzyme covalent complex, and the nature of conformational reorganization required for the long term stability of the covalent complex. Additionally, the molecular basis for the effect of stereochemistry of the lactam ring on the inhibitory potency was elucidated through docking of beta-lactam enantiomers. As a validation of our docking methodology, two novel enantiomers were synthesized and evaluated for their inhibitory potency using fluorogenic substrate based activity assays. Additionally, cis enantiomers of eight beta-lactam compounds reported in a previous study were docked and their GOLD scores and binding modes were analyzed in order to assess the general applicability of our docking results. The close agreement of our docking results with the experimental data validates the mechanistic insights revealed through the docking studies and paves the way for the design and development of potent and specific inhibitors of PSA.     

Insights on Na+ binding and conformational dynamics in multidrug and toxic compound extrusion transporter NorM

MATE (multidrug and toxic compound extrusion) transporter proteins mediate metabolite transport in plants and multidrug resistance in bacteria and mammals. MATE transporter NorM from Vibrio cholerae is an antiporter that is driven by Na+ gradient to extrude the substrates. To understand the molecular mechanism of Na+‐substrate exchange, molecular dynamics simulation was performed to study conformational changes of both wild‐type and mutant NorM with and without cation bindings. Our results show that NorM is able to bind two Na⁺ ions simultaneously, one to each of the carboxylic groups of E255 and D371 in the binding pocket. Furthermore, this di‐Na⁺ binding state is likely more efficient for conformational changes of NorM_VC toward the inward‐facing conformation than single‐Na⁺ binding state. The observation of two Na⁺ binding sites of NorM_VC is consistent with the previous study that two sites for ion binding (denoted as Na1/Na2 sites) are found in the transporter LeuT and BetP, another two secondary transporters. Taken together, our findings shed light on the structure rearrangements of NorM on Na⁺ binding and enrich our knowledge of the transport mechanism of secondary transporters. Proteins 2014; 82:240–249. © 2013 Wiley Periodicals, Inc.     

Analyzing the effect of mutations in SARS-CoV2 papain-like protease from Saudi isolates on protein structure and drug-protein binding: Molecular modelling and dynamics studies

The continuous and rapid development of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus remains a health concern especially with the emergence of numerous variants and mutations worldwide. As with other RNA viruses, SARS-CoV-2 has a genetically high mutation rate. These mutations have an impact on the virus characteristics, including transmissibility, antigenicity and development of drug and vaccine resistance. This work was pursued to identify the differences that exist in the papain-like protease (PL^Pro) from 58 Saudi isolates in comparison to the first reported sequence from Wuhan, China and determine their implications on protein structure and the inhibitor binding. PL^pro is a key protease enzyme for the host cells invasion and viral proteolytic cleavage, hence, it emerges as a valuable antiviral therapeutic target. Two mutations were identified including D108G and A249V and shown to increase the molecular flexibility of PL^Pro protein and alter the protein stability, particularly with D108G mutation. The effect of these mutations on the stability and dynamic behavior of PL^Pro structures as well as their effect on the binding of a known inhibitor; GRL0617 were further investigated by molecular docking and dynamic simulation.     

Effect of including genetic progress in milk yield on evaluating the use of sexed semen and other reproduction strategies in a dairy herd

The objective of this study was to explore the importance of including genetic progress in milk yield when evaluating different reproductive strategies in a dairy herd by simulation modeling. The model used in this study was SimHerd V, a dynamic and mechanistic Monte Carlo simulation model of a dairy herd including young stock. A daily increasing trend describing genetic milk yield potential of the sire population was included in the model. The inaccuracy of assuming that replacement heifers have the same (milk yield) potential as the cows present in the herd was hereby dealt with. Improving estrus detection rate from 0.45 to 0.80 increased gross margin (GM) per cow-year by €20 when genetic progress was not included in the model. When genetic progress was included in the model, then the same improvement in estrus detection decreased the GM per cow-year by €7.4. This reduced effect was explained by a lower replacement rate in consequence of the improved estrus detection and thereby a slower genetic progress in the herd. There was a reduced effect of including genetic progress on GM when surplus heifers were sold selectively based on breeding values. Repeated insemination with sexed semen on the superior half of all heifers reduced GM by €8 per cow-year when genetic progress was not included and increased the GM by €16 per cow-year when genetic progress was included in the model. Including genetic progress reduced the losses caused by lower conception and estrus detection rates and had a minimal effect with regard to postponing first insemination. This study has proven that it is important to include genetic progress in decisions on reproduction strategies in a dairy herd.     

Protein aggregation determinants from a simplified model: cooperative folders resist aggregation

Two-chain aggregation simulations using minimalist models of proteins G, L, and mutants were used to investigate the fundamentals of protein aggregation. Mutations were selected to break up repeats of hydrophobic beads in the sequence while maintaining native topology and folding ability. Data are collected under conditions in which all chain types have similar folded populations and after equilibrating the separated chains to minimize competition between folding and aggregation. Folding cooperativity stands out as the best single-chain determinant under these conditions and for these simple models. It can be experimentally measured by the width of the unfolding transition during thermal denaturation and loosely related to population of intermediate-like states during folding. Additional measures of cooperativity and other properties such as radius of gyration fluctuations and patterning of hydrophobic residues are also examined. Initial contact system states with transition-state characteristics can be identified and are more expanded than average initial contact states. Two-chain minimalist model aggregates are considerably less structured than their native states and have minimal domain-swapping features.     

A Monte Carlo method for the simulation of kinetie models

The purpose of this note is to illustrate the feasibility of simulating kinetic systems, such as commonly encountered in photosynthesis research, using the Monte Carlo (MC) method. In this approach, chemical events are considered at the molecular level where they occur randomly and the macroscopic kinetic evolution results from averaging a large number of such events. Their repeated simulation is easily accomplished using digital computing. It is shown that the MC approach is well suited to the capabilities and resources of modern microcomputers. A software package is briefly described and discussed, allowing a simple programming of any kinetic model system and its resolution. The execution is reasonably fast and accurate; it is not subject to such instabilities as found with the conventional analytical approach.Abbreviations MC Monte Carlo - RN random number - PSU photosynthetic unit Dedicated to Prof. L.N.M. Duysens on the occasion of his retirement.