The (S−1,S) inventory model and its counterparts in queueing theory

We explore the relationship between the ($S?1,S$) inventory model and three well-known queueing models: the Erlang loss system, the machine-repair model and a two-node Jackson network. Exploiting this relationship allows us to obtain key performance measures of the ($S?1,S$) model, like the so-called virtual outdating time, the number of items on the shelf in steady state, the long-run rate of unsatisfied demands and the distribution of the empty shelf period.     

Similar,or dissimilar,that is the question. How different are methods for comparison of compounds similarity?

Comparison of compounds similarity is one of the main strategies of virtual screening protocols. Both similarity and dissimilarity concepts are of great importance during the search for new active compounds. Similarity is important due to the assumption that underlies the process of searching for new drug candidates: structurally similar compounds should induce similar biological response. On the other hand, we are also interested in dissimilarity, as we usually aim to find structurally novel ligands. In the study, we compared several approaches of evaluating compound similarity. Various representations and metrics were applied and we indicated the rate of variation of the results that can occur when shifting from one strategy to another. We compared both general similarity of datasets using different approaches, as well as examined the changes in the set of nearest neighbors when changing one compound representation into another, and the influence of representation/metric settings on the clustering outcome. We hope that the study will be of great help during the preparation of virtual screening experiments, stressing the need for careful selection of the way, the compound similarity is assessed. The differences in the results that can be obtained via the application of particular strategy can significantly influence the outcome of comparison studies; therefore, its settings should be carefully selected beforerunning the comparison.     

Understanding Molecular Dynamics with Stochastic Processes via Real or Virtual Dynamics

Molecular dynamics with the stochastic process provides a convenient way to compute structural and thermodynamic properties of chemical, biological, and materials systems. It is demonstrated that the virtual dynamics case that we proposed for the Langevin equation[J. Chem. Phys. 147 , 184104 (2017)] in principle exists in other types of stochastic thermostats as well. The recommended "middle" scheme[J. Chem. Phys. 147 , 034109 (2017)] of the Andersen thermostat is investigated as an example. As shown by both analytic and numerical results, while the real and virtual dynamics cases approach the same plateau of the characteristic correlation time in the high collision frequency limit, the accuracy and efficiency of sampling are relatively insensitive to the value of the collision frequency in a broad range. After we compare the behaviors of the Andersen thermostat to those of Langevin dynamics, a heuristic schematic representation is proposed for understanding efficient stochastic thermostatting processes with molecular dynamics.     

Virtual screening of B-Raf kinase inhibitors: A combination of pharmacophore modelling,molecular docking, 3D-QSAR model and binding free energy calculation studies

B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG_bind) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines. In the result, five hit compounds show good biological activities (IC₅₀ < 50 μM). The present method of virtual screening can be applied to find structurally diverse inhibitors, and the obtained five structurally diverse compounds are expected to develop novel BRIs.     

Discovery of potential inhibitor against human acetylcholinesterase: a molecular docking and molecular dynamics investigation

Alzheimer’s disease (AD) is a progressive neurodegenerative disease of central nervous system among elderly people. Human acetylcholinesterase (hAChE), an important enzyme in neuronal signaling, is responsible for the degradation of acetylcholine which in turn prevents the post synaptic signal transmissions. hAChE has been an attractive target of drug discovery for the search of therapeutics against AD. In the recent past hAChE has become hot target for the investigation of new potential therapeutics. We performed virtual screening of entire database against hAChE. Further, the extra precision molecular docking was carried out to refine the docking results and the best complex was passed for molecular dynamics simulations in order of understanding the hAChE dynamics and its behavior in complex with the ligand which corroborate the outcomes of virtual screening. This also provides binding free energy data that establishes the ligands efficiency for inhibiting hAChE. The computational findings discussed in this paper provide initial information of inhibitory effects of ligand, (drugbank entry DB00983), over hAChE.     

基于结构虚拟筛选发现蛋白质精氨酸甲基转移酶5抑制剂

蛋白质精氨酸甲基转移酶5(PRMT5)是蛋白质甲基转移酶家族(PRMTs)的重要一员,其主要生理功能是催化精氨酸单对称二甲基化。PRMT5的上调发生在不同类型的肿瘤中,并与不良预后密切相关,已被视为肿瘤治疗中的潜在靶点。近年来,已有多种PRMT5抑制剂进入临床试验,但目前尚未有药物获批上市。本研究基于Glide对接的虚拟筛选和生物活性实验,发现化合物8018-1271对PRMT5酶的抑制活性IC₅₀值为13.56±0.86μmol/L,并通过分子动力学揭示其与PRMT5蛋白结构域的相互作用模式。本研究所得化合物8018-1271可作为进一步改造的先导化合物,为新型PRMT5抑制剂的发现提供参考。     

Multiple QSAR and molecular modelling for identification of potent human adenovirus inhibitors

This study has investigated docking-based 2D- and 3D-quantitative structure-activity relationships (QSARs) for a range of 53 hydroxybenzamide analogues as anti- Human adenoviruses (HAdVs). The best 3D-QSAR (Schrodinger, LLC, NY, 2020) and 2D-QSAR models were obtained for the training set and were found to be statistically significant, with cross-validated coefficients (q²) of 0.6775 and 0.7875, and coefficients of determination (r²) of 0.8106 and 0.8122, respectively. Our in-silico docking and virtual screening studies revealed significant higher binding affinity of dataset molecule 34 (-141.444 ​kcal/mol) and hit ZINC01088642 (-114.357 ​kcal/mol) with 4PIE protein than the standard drugs. In in-silico ADME/toxicity studies, molecule 34 and proposed hit ZINC01088642 were found safe with good intestinal absorption, aqueous solubility, medium blood–brain barrier (BBB), no eye corrosion, no skin irritancy, and non-mutagenic profiles. Molecular dynamics analysis showed good stability of complex, hit ZINC01088642 with protein, 4PIE over the simulation period of 20 ns. We believe that further experimental, as well as in-vitro investigation, will shed more lights on the identification of ZINC01088642 as a potential human adenovirus agent.     

In silico virtual screening of potent inhibitor to hamper the interaction between HIV-1 integrase and LEDGF/p75 interaction using E-pharmacophore modeling,molecular docking,and dynamics simulations

The rapid increase of HIV-1 infection throughout the globe has a high demand for a superior drug with lesser side effects. LEDGF/p75, the human Lens Epithelium-Derived Growth Factor is identified as a promising cellular cofactor with integrase in facilitating the viral replication in an early stage by acting as a tethering factor in the pre-integration to the chromatin. Therefore, the present study was designed to identify a potent inhibitor by applying an E-pharmacophore based virtual screening, molecular docking, and dynamics simulation approaches. Finally, ZINC22077550 and ZINC32124441 were best identified potent molecules with the efficient binding affinity, strong hydrogen bonding, and acceptable pharmacological properties to hamper the interaction between integrase and LEDGF/p75. Further, the DFT and MDS studies were also analyzed, and shown a favorable energetic state and dynamic stability then reference compound. In conclusion, we suggest that these findings could be novel therapeutics in the future and may increase the lifespan of individuals suffering from viral infection.     

On the Logical Status of the Virtual Work Law

The law of virtual work (VWL) is probably the first law in the history of mechanics; it is previous to the one on the lever, though not completely distinct from it. Here I will discuss the logical status of VWL, that is whether it is an autonomous principle or a theorem of some sort of mechanics. The problem is complicated by the fact that up to now no universally recognised expression has been accepted for it. From this article the problematical nature of VWL demonstrability is quite clear when the mechanics does not characterise completely the constraints. Italian schools in the XVIII century, even if we do not take Lagrange into consideration, had an important role, both in the development of VWL and in the discussion of its role.     

弹性力学问题的虚边界元-配点法

本文提出虚边界方法,建立了离散化虚边界元-配点法,给出了离散化求系数的积分解析式。本文方法完全避免了边界奇异积分及其复杂耗时的运算,成功地提高了普通边界元法(以下简称边界元法)中边界附近区域内包括边界上解的精度,保留了边界元法的优点并扬弃了其弱点。边界元间接法是本文方法中的一个特例。数值算例表明,程序可靠,节省机时,计算精度较高。