Relative Binding Free Energy Calculations Applied to Protein Homology Models.

A significant challenge and potential high-value application of computer-aided drug design is the accurate prediction of protein-ligand binding affinities. Free energy perturbation (FEP) using molecular dynamics (MD) sampling is among the most suitable approaches to achieve accurate binding free energy predictions, due to the rigorous statistical framework of the methodology, correct representation of the energetics, and thorough treatment of the important degrees of freedom in the system (including explicit waters). Recent advances in sampling methods and force fields coupled with vast increases in computational resources have made FEP a viable technology to drive hit-to-lead and lead optimization, allowing for more efficient cycles of medicinal chemistry and the possibility to explore much larger chemical spaces.

Automated Protocol for Large-Scale Modeling of Gene Expression Data.

With the continued rise of phenotypic- and genotypic-based screening projects, computational methods to analyze, process, and ultimately make predictions in this field take on growing importance. Here we show how automated machine learning workflows can produce models that are predictive of differential gene expression as a function of a compound structure using data from A673 cells as a proof of principle. In particular, we present predictive models with an average accuracy of greater than 70% across a highly diverse ∼1000 gene expression profile.

Discovery and Optimization of a Selective Ligand for the Switch/Sucrose Nonfermenting-Related Bromodomains of Polybromo Protein-1 by the Use of Virtual Screening and Hydration Analysis.

Bromodomains (BRDs) are epigenetic interaction domains currently recognized as emerging drug targets for development of anticancer or anti-inflammatory agents. In this study, development of a selective ligand of the fifth BRD of polybromo protein-1 (PB1(5)) related to switch/sucrose nonfermenting (SWI/SNF) chromatin remodeling complexes is presented. A compound collection was evaluated by consensus virtual screening and a hit was identified.

Small molecule-facilitated degradation of ANO1 protein: a new targeting approach for anticancer therapeutics.

ANO1, a calcium-activated chloride channel, is highly expressed and amplified in human cancers and is a critical survival factor in these cancers. The ANO1 inhibitor CaCCinh-A01 decreases proliferation of ANO1-amplified cell lines; however, the mechanism of action remains elusive. We explored the mechanism behind the inhibitory effect of CaCCinh-A01 on cell proliferation using a combined experimental and in silico approach.

Automated ligand- and structure-based protocol for in silico prediction of human serum albumin binding.

Plasma protein binding has a profound impact on the pharmacokinetic and pharmacodynamic properties of many drug candidates and is thus an integral component of drug discovery. Nevertheless, extant methods to examine small-molecule interactions with plasma protein have various limitations, thus creating a need for alternative methods. Herein we present a comprehensive and cross-validated in silico workflow for the prediction of small-molecule binding to Human Serum Albumin (HSA), the most ubiquitous plasma protein.

Accurate Force Field Development for Modeling Conjugated Polymers.

The modeling of the conformational properties of conjugated polymers entails a unique challenge for classical force fields. Conjugation imposes strong constraints upon bond rotation. Planar configurations are favored, but the concomitantly shortened bond lengths result in moieties being brought into closer proximity than usual.

Polarized Raman spectroscopy of oligothiophene crystals to determine unit cell orientation.

Raman spectra were recorded experimentally and calculated theoretically for bithiophene, terthiophene, and quaterthiophene samples as a function of excitation polarization. Distinct spectral signatures were assigned and correlated to the molecular/unit cell orientation as determined by X-ray diffraction. The ability to predict molecular/unit cell orientation within organic crystals using polarized Raman spectroscopy was evaluated by predicting the unit cell orientation in a simulated terthiophene crystal given a random set of simulated polarized Raman spectra.

Continuous Localized Orbital Corrections to Density Functional Theory: B3LYP-CLOC.

Our previous works have demonstrated the ability of our localized orbital correction (LOC) methodology to greatly improve the accuracy of various thermochemical properties at the stationary points of the Density Functional Theory (DFT) reaction coordinate (RC). Herein we extend this methodology from stationary points to the entire RC connecting any stationary points by developing continuous localized orbital corrections (CLOCs). We show that the resultant method, DFT-CLOC, is capable of producing RCs with far greater accuracy than uncorrected DFT and yet requires negligible computational cost beyond the uncorrected DFT calculations.

Localized orbital corrections for the calculation of barrier heights in density functional theory.

This work describes the extension of a previously reported empirical localized orbital correction model for density functional theory (DFT-LOC) for atomization energies, ionization potentials, electron affinities, and reaction enthalpies to the correction of barrier heights for chemical reactions of various types including cycloadditions, cycloreversions, dipolar cycloadditions, S(N)2's, carbon radical reactions, hydrogen radical reactions, sigmatropic shifts, and electrocyclizations. The B3LYP localized orbital correction version of the model (B3LYP-LOC) reduces the number of outliers and overall mean unsigned error (MUE) vs. experiment or ab initio values from 3.

Quantitative DFT modeling of the enantiomeric excess for dioxirane-catalyzed epoxidations.

Herein we report the first fully quantum mechanical study of enantioselectivity for a large data set. We show that transition state modeling at the UB3LYP-DFT/6-31G* level of theory can accurately model enantioselectivity for various dioxirane-catalyzed asymmetric epoxidations. All the synthetically useful high selectivities are successfully "predicted" by this method.

Using a two-step hydride transfer to achieve 1,4-reduction in the catalytic hydrogenation of an acyl pyridinium cation.

The stoichiometric reduction of N-carbophenoxypyridinium tetraphenylborate (6) by CpRu(P-P)H (Cp = eta(5)-cyclopentadienyl; P-P = dppe, 1,2-bis(diphenylphosphino)ethane, or dppf, 1,1'-bis(diphenylphosphino)ferrocene), and Cp*Ru(P-P)H (Cp* = eta(5)-pentamethylcyclopentadienyl; P-P = dppe) gives mixtures of 1,2- and 1,4-dihydropyridines. The stoichiometric reduction of 6 by Cp*Ru(dppf)H (5) gives only the 1,4-dihydropyridine, and 5 catalyzes the exclusive formation of the 1,4-dihydropyridine from 6, H(2), and 2,2,6,6-tetramethylpiperidine. In the stoichiometric reductions, the ratio of 1,4 to 1,2 product increases as the Ru hydrides become better one-electron reductants, suggesting that the 1,4 product arises from a two-step (e(-)/H(*)) hydride transfer.