Significance: Density functionals with Hartree–Fock exchange have been widely used for a wide range of chemical applications, but the nonlocal character of exchange makes long-range exchange computationally expensive for solid-state calculations with periodic boundary conditions, and full exchange is nonphysical for condensed-phase systems. Here, we present a screened-exchange (SX) density functional, M06-SX, that is especially designed to have good accuracy for both solid-state physics and chemical applications with less computational cost than full Hartree–Fock exchange. The M06-SX functional gives accuracy comparable to functionals with full Hartree–Fock exchange for predicting chemical properties of molecules, while also being practical with good accuracy for plane wave calculations on band gaps and lattice constants of solids.

Kohn–Sham density functional theory is widely used in chemistry, but no functional can accurately predict the whole range of chemical properties, although recent progress by some doubly hybrid functionals comes close. Here, we optimized a singly hybrid functional called CF22D with higher across-the-board accuracy for chemistry than most of the existing non-doubly hybrid functionals by using a flexible functional form that combines a global hybrid meta-nonseparable gradient approximation that depends on density and occupied orbitals with a damped dispersion term that depends on geometry. We optimized this energy functional by using a large database and performance-triggered iterative supervised training. We combined several databases to create a very large, combined database whose use demonstrated the good performance of CF22D on barrier heights, isomerization energies, thermochemistry, noncovalent interactions, radical and nonradical chemistry, small and large systems, simple and complex systems and transition-metal chemistry.

Optimal therapeutic strategies for liver cancer patients remain challenging due to the high recurrence rate after surgical resection and chemotherapy resistance. Emerging evidence has shown that epigenetic factor SIRT7 is involved in various aspects of cancer biology, while inactive SIRT7 reverses human cancer phenotype and suppresses tumor growth. In the present study, we predicted the SIRT7 structure by using the fold recognition (or threading) method and performed structure-based virtual screening to develop specific SIRT7 inhibitor by docking 939319 structurally diverse compounds with SIRT proteins. Compounds with high affinities to SIRT7 but low affinities to other SIRT proteins were chosen as candidates of specific SIRT7 inhibitor. Our leading compounds 2800Z and 40569Z showed strong interaction with SIRT7 protein, and specifically inhibited SIRT7 deacetylation activity in vitro. Our docking results also revealed that ARG-120, TRP-126, and HIS-187 were critical sites responsible for interaction of SIRT7 with small molecules. Mutations in the aforementioned sites significantly abolished interaction and inhibitory effects of compounds to SIRT7. In addition, in vivo data indicated that compounds 2800Z and 40569Z were able to induce apoptosis and increase chemosensitivity to sorafenib in human liver cancer. Our findings demonstrated targeting SIRT7 may offer novel therapeutic options for cancer management, and the value of compounds 2800Z and 40569Z as chemical probes for the study of SIRT7 biological functions as well as starting leads for the development of new therapeutic options against liver cancer.