Rapid, Accurate, Ranking of Protein-Ligand Binding Affinities with VM2, the Second-Generation Mining Minima Method.

The structure-based technologies most widely used to rank the affinities of candidate small molecule drugs for proteins range from faster but less reliable docking methods to slower but more accurate explicit solvent free energy methods. In recent years, we have advanced another technology, which is called mining minima because it "mines" out the main contributions to the chemical potentials of the free and bound molecular species by identifying and characterizing their main local energy minima. The present study provides systematic benchmarks of the accuracy and computational speed of mining minima, as implemented in the VeraChem Mining Minima Generation 2 (VM2) code, across two well-regarded protein-ligand benchmark data sets, for which there are already benchmark data for docking, free energy, and other computational methods.

Capture of activated dioxygen intermediates at the copper-active site of a lytic polysaccharide monooxygenase.

Metalloproteins perform a diverse array of redox-related reactions facilitated by the increased chemical functionality afforded by their metallocofactors. Lytic polysaccharide monooxygenases (LPMOs) are a class of copper-dependent enzymes that are responsible for the breakdown of recalcitrant polysaccharides oxidative cleavage at the glycosidic bond. The activated copper-oxygen intermediates and their mechanism of formation remains to be established.

Computation of host-guest binding free energies with a new quantum mechanics based mining minima algorithm.

A new method called QM-VM2 is presented that efficiently combines statistical mechanics with quantum mechanical (QM) energy potentials in order to calculate noncovalent binding free energies of host-guest systems. QM-VM2 efficiently couples the use of semi-empirical QM (SEQM) energies and geometry optimizations with an underlying molecular mechanics (MM) based conformational search, to find low SEQM energy minima, and allows for processing of these minima at higher levels of ab initio QM theory. A progressive geometry optimization scheme is introduced as a means to increase conformational sampling efficiency.

Modeling Protein-Ligand Binding by Mining Minima.

We present the first application of the mining minima algorithm to protein-small molecule binding. This end-point approach use an empirical force field and implicit solvent models, treats the protein binding-site as fully flexible and estimates free energies as sums over local energy wells. The calculations are found to yield encouraging agreement with experiment for three sets of HIV-1protease inhibitors and a set of phosphodiesterase 10a inhibitors.

Solvent-induced frequency shifts: configuration interaction singles combined with the effective fragment potential method.

The simplest variational method for treating electronic excited states, configuration interaction with single excitations (CIS), has been interfaced with the effective fragment potential (EFP) method to provide an effective and computationally efficient approach for studying the qualitative effects of solvents on the electronic spectra of molecules. Three different approaches for interfacing a non-self-consistent field (SCF) excited-state quantum mechanics (QM) method and the EFP method are discussed. The most sophisticated and complex approach (termed fully self consistent) calculates the excited-state electron density with fully self-consistent accounting for the polarization (induction) energy of effective fragments.

Proteomic analysis identifies oxidative stress induction by adaphostin.

Purpose: Activities distinct from inhibition of Bcr/abl have led to adaphostin (NSC 680410) being described as "a drug in search of a mechanism." In this study, proteomic analysis of adaphostin-treated myeloid leukemia cell lines was used to further elucidate a mechanism of action.

Experimental Design: HL60 and K562 cells treated with adaphostin for 6, 12, or 24 h were analyzed using two-dimensional PAGE.

Determinants of the relative reduction potentials of type-1 copper sites in proteins.

The relative Cu(2+)/Cu(+) reduction potentials of six type-1 copper sites (cucumber stellacyanin, P. aeruginosa azurin, poplar plastocyanin, C. cinereus laccase, T.