The crystal and molecular structure of 9-methylphenanthro[4,3-a]dibenzothiophene

The crystal structure of 9-methylphenanthro[4,3-a]dibenzothiophene, C₂₅H₁₆S, M_r = 348.47, has been determined. Monoclinic, P2₁/c, a = 11.364(3), b, = 14.257(3), c = 11.575(2)Å, β = 116.26(2)°, V = 1681.9(7)ų, Z = 4, D_x = 1.38 g/cc, MoKα radiation λ = .71069 Å, F(000) = 728, T = 163K, R = .0458 for 2330 reflections. The structure compares favorably with that of hexahelicene and methylated derivatives. The thiophene moiety increases the helical core radius and decreases the pitch with respect to hexahelicene and its derivatives.     

A hybrid optimization technique coupling an evolutionary and a local search algorithm

Evolutionary algorithms are robust and powerful global optimization techniques for solving large-scale problems that have many local optima. However, they require high CPU times, and they are very poor in terms of convergence performance. On the other hand, local search algorithms can converge in a few iterations but lack a global perspective. The combination of global and local search procedures should offer the advantages of both optimization methods while offsetting their disadvantages. This paper proposes a new hybrid optimization technique that merges a genetic algorithm with a local search strategy based on the interior point method. The efficiency of this hybrid approach is demonstrated by solving a constrained multi-objective mathematical test-case.     

Stabilizing the monodromy of an open book decomposition

We prove that any mapping class on a compact oriented surface with non-empty boundary can be made pseudo-Anosov and right-veering after a sequence of positive stabilizations.      

Reconstructing compositions

We consider the problem of reconstructing compositions of an integer from their subcompositions, which was raised by Raykova (albeit disguised as a question about layered permutations). We show that every composition w of n?3k+1 can be reconstructed from its set of k-deletions, i.e., the set of all compositions of n-k contained in w. As there are compositions of 3k with the same set of k-deletions, this result is best possible.     

Synthesis of nucleoside derivatives via heterocyclocondensation reactions

A new synthesis of nucleoside analogues has been developed. The cyclocondensation of a glycosylated diazadiene or thiazadiene, with acyl chlorides or α-halogenoketones, respectively, resulted in good yields and excellent regioselectivities. We report an efficient method for the production of glucosyl pyrimidinones and glucosylamino thiazoles.     

Rapid and accurate estimation of protein–ligand relative binding affinities using site-identification by ligand competitive saturation

Predicting relative protein–ligand binding affinities is a central pillar of lead optimization efforts in structure-based drug design. The site identification by ligand competitive saturation (SILCS) methodology is based on functional group affinity patterns in the form of free energy maps that may be used to compute protein–ligand binding poses and affinities. Presented are results obtained from the SILCS methodology for a set of eight target proteins as reported originally in Wang et al. (J. Am. Chem. Soc., 2015, 137, 2695–2703) using free energy perturbation (FEP) methods in conjunction with enhanced sampling and cycle closure corrections. These eight targets have been subsequently studied by many other authors to compare the efficacy of their method while comparing with the outcomes of Wang et al. In this work, we present results for a total of 407 ligands on the eight targets and include specific analysis on the subset of 199 ligands considered previously. Using the SILCS methodology we can achieve an average accuracy of up to 77% and 74% when considering the eight targets with their 199 and 407 ligands, respectively, for rank-ordering ligand affinities as calculated by the percent correct metric. This accuracy increases to 82% and 80%, respectively, when the SILCS atomic free energy contributions are optimized using a Bayesian Markov-chain Monte Carlo approach. We also report other metrics including Pearson''s correlation coefficient, Pearlman''s predictive index, mean unsigned error, and root mean square error for both sets of ligands. The results obtained for the 199 ligands are compared with the outcomes of Wang et al. and other published works. Overall, the SILCS methodology yields similar or better-quality predictions without a priori need for known ligand orientations in terms of the different metrics when compared to current FEP approaches with significant computational savings while additionally offering quantitative estimates of individual atomic contributions to binding free energies. These results further validate the SILCS methodology as an accurate, computationally efficient tool to support lead optimization and drug discovery.

Predicting relative protein–ligand binding affinities is a central pillar of lead optimization efforts in structure-based drug design.