Advances in theory and algorithms for electronic structure calculations must be incorporated into program packages to enable them to become routinely used by the broader chemical community. This work reviews advances made over the past five years or so that constitute the major improvements contained in a new release of the Q-Chem quantum chemistry package, together with illustrative timings and applications. Specific developments discussed include fast methods for density functional theory calculations, linear scaling evaluation of energies, NMR chemical shifts and electric properties, fast auxiliary basis function methods for correlated energies and gradients, equation-of-motion coupled cluster methods for ground and excited states, geminal wavefunctions, embedding methods and techniques for exploring potential energy surfaces.

The design of polymers and oligomers that mimic the complex structures and remarkable biological properties of proteins is an important endeavor with both fundamental and practical implications. Recently, a number of nonnatural peptides with designed sequences have been elaborated to provide biologically active structures; in particular, facially amphiphilic peptides built from ␤-amino acids have been shown to mimic both the structures as well as the biological function of natural antimicrobial peptides such as magainins and cecropins. However, these natural peptides as well as their ␤-peptide analogues are expensive to prepare and difficult to produce on a large scale, limiting their potential use to certain pharmaceutical applications. We therefore have designed a series of facially amphiphilic arylamide polymers that capture the physical and biological properties of this class of antimicrobial peptides, but are easy to prepare from inexpensive monomers. The design process was aided by molecular calculations with density functional theory-computed torsional potentials. This new class of amphiphilic polymers may be applied in situations where inexpensive antimicrobial agents are required.

Cracking the case: Aryl amide oligomers with amphiphilic secondary structure were designed that attack bacteria by lysing their membranes. A variety of groups were appended to the lead compound to adjust its overall charge, hydrophobicity, and hydrophobic moment. An Arg‐containing oligomer (see figure) was found to have good antimicrobial activity and low toxicity towards human erythrocytes.

Topological polar surface area (TPSA), which makes use of functional group contributions based on a large database of structures, is a convenient measure of the polar surface area that avoids the need to calculate ligand 3D structure or to decide which is the relevant biological conformation or conformations. We demonstrate the utility of TPSA in 2D-QSAR for 14 sets of diverse pharmacological activity data. Even though a large pool of reports showing the importance of the classic 2D descriptors such as calculated logP (ClogP) and calculated molar refractivity (CMR) exists in the 2D-QSAR literature, this is the first report to demonstrate the value of TPSA as a relevant descriptor applicable to a large, structurally and pharmacologically diverse set of classes of compounds. We also address the limitations of applicability of this descriptor for 2D-QSAR analysis. We observed a negative correlation of TPSA with activity data for anticancer alkaloids, MT1 and MT2 agonists, MAO-B and tumor necrosis factor-alpha inhibitors and a positive correlation with inhibitory activity data for telomerase, PDE-5, GSK-3, DNA-PK, aromatase, malaria, trypanosomatids and CB2 agonists.

Computational tools are essential in the drug design process, especially in order to take advantage of the increasing numbers of solved X-ray and NMR protein–ligand structures. Nowadays, molecular docking methods are routinely used for prediction of protein–ligand interactions and to aid in selecting potent molecules as a part of virtual screening of large databases. The improvements and advances in computational capacity in the last decade have allowed for further developments in molecular docking algorithms to address more complicated aspects such as protein flexibility. The effects of incorporation of active site water molecules and implicit or explicit solvation of the binding site are other relevant issues to be addressed in the docking procedures. Using the right docking algorithm at the right stage of virtual screening is most important. We report a staged study to address the effects of various aspects of protein flexibility and inclusion of active site water molecules on docking effectiveness to retrieve (and to be able to predict) correct ligand poses and to rank docked ligands in relation to their biological activity, for CHK1, ERK2, LpxC and UPA. We generated multiple conformers for the ligand, and compared different docking algorithms that use a variety of approaches to protein flexibility, including rigid receptor, soft receptor, flexible side chains, induced-fit, and multiple structure algorithms. Docking accuracy varied from 1 to 84%, demonstrating that the choice of method is important.