An N log N approximation based on the natural organization of biomolecules for speeding up the computation of long range interactions

Presented here is a method, the hierarchical charge partitioning (HCP) approximation, for speeding up computation of pairwise electrostatic interactions in biomolecular systems. The approximation is based on multiple levels of natural partitioning of biomolecular structures into a hierarchical set of its constituent structural components. The charge distribution in each component is systematically approximated by a small number of point charges, which, for the highest level component, are much fewer than the number of atoms in the component. For short distances from the point of interest, the HCP uses the full set of atomic charges available. For long‐distance interactions, the approximate charge distributions with smaller sets of charges are used instead. For a structure consisting of N charges, the computational cost of computing the pairwise interactions via the HCP scales as O(N log N), under assumptions about the structural organization of biomolecular structures generally consistent with reality. A proof‐of‐concept implementation of the HCP shows that for large structures it can lead to speed‐up factors of up to several orders of magnitude relative to the exact pairwise O(N²) all‐atom computation used as a reference. For structures with more than 2000–3000 atoms the relative accuracy of the HCP (relative root‐mean‐square force error per atom), approaches the accuracy of the particle mesh Ewald (PME) method with parameter settings typical for biomolecular simulations. When averaged over a set of 600 representative biomolecular structures, the relative accuracies of the two methods are roughly equal. The HCP is also significantly more accurate than the spherical cutoff method. The HCP has been implemented in the freely available nucleic acids builder (NAB) molecular dynamics (MD) package in Amber tools. A 10 ns simulation of a small protein indicates that the HCP based MD simulation is stable, and that it can be faster than the spherical cutoff method. A critical benefit of the HCP approximation is that it is algorithmically very simple, and unlike the PME, the HCP is straightforward to use with implicit solvent models. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Dynamic response of beams on generalised elastic foundations

Dynamic responses of beams on generalised elastic foundations is studied using the method of Initial parameters. The foundation model proposed by Vlasov and Leontev is modified by incorporating in the analysis the horizontal displacements in the elastic foundation thus making it more general and physically close to the actual situation. Results are compared with those reported by Rades, using Pasternak's foundation model and Winkler's model. The insufficiency of the Winkler's model in the study of dynamic responses (mainly the bending moments) is emphasized. Solutions presented are quite general for application to beams on generalised elastic foundations subjected to arbitrary external dynamic loads and (or) moments.     

Enhanced Production of Laccase from Coriolus versicolor NCIM 996 by Nutrient Optimization Using Response Surface Methodology

Plackett and Burman design criterion and central composite design were applied successfully for enhanced production of laccase by Coriolus versicolor NCIM 996 for the first time. Plackett and Burman design criterion was applied to screen the significance of ten nutrients on laccase production by C. versicolor NCIM 996. Out of the ten nutrients tested, starch, yeast extract, MnSO(4), MgSO(4) x 7H(2)O, and phenol were found to have significant effect on laccase production. A central composite design was applied to determine the optimum concentrations of the significant variables obtained from Plackett-Burman design. The optimized medium composition for production of laccase was (g/l): starch, 30.0; yeast extract, 4.53; MnSO(4), 0.002; MgSO(4) x 7H(2)O, 0.755; and phenol, 0.026, and the optimum laccase production was 6,590.26 (U/l), which was 7.6 times greater than the control.     

Computational Analysis Reveals Monomethylated Triazolopyrimidine as a Novel Inhibitor of SARS-CoV-2 RNA-Dependent RNA Polymerase (RdRp)

The human population is still facing appalling conditions due to several outbreaks of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) virus. The absence of specific drugs, appropriate vaccines for mutants, and knowledge of potential therapeutic agents makes this situation more difficult. Several 1, 2, 4-triazolo [1, 5-a] pyrimidine (TP)-derivative compounds were comprehensively studied for antiviral activities against RNA polymerase of HIV, HCV, and influenza viruses, and showed immense pharmacological interest. Therefore, TP-derivative compounds can be repurposed against the RNA-dependent RNA polymerase (RdRp) protein of SARS-CoV-2. In this study, a meta-analysis was performed to ensure the genomic variability and stability of the SARS-CoV-2 RdRp protein. The molecular docking of natural and synthetic TP compounds to RdRp and molecular dynamic (MD) simulations were performed to analyse the dynamic behaviour of TP compounds at the active site of the RdRp protein. TP compounds were also docked against other non-structural proteins (NSP1, NSP2, NSP3, NSP5, NSP8, NSP13, and NSP15) of SARS-CoV-2. Furthermore, the inhibition potential of TP compounds was compared with Remdesivir and Favipiravir drugs as a positive control. Additionally, TP compounds were analysed for inhibitory activity against SARS-CoV RdRp protein. This study demonstrates that TP analogues (monomethylated triazolopyrimidine and essramycin) represent potential lead molecules for designing an effective inhibitor to control viral replication. Furthermore, in vitro and in vivo studies will strengthen the use of these inhibitors as suitable drug candidates against SARS-CoV-2.