Results of the combined use of the classical force field and the recent quantum chemical PM7 method for docking are presented. Initially the gridless docking of a flexible low molecular weight ligand into the rigid target protein is performed with the energy function calculated in the MMFF94 force field with implicit water solvent in the PCM model. Among several hundred thousand local minima, which are found in the docking procedure, about eight thousand lowest energy minima are chosen and then energies of these minima are recalculated with the recent quantum chemical semiempirical PM7 method. This procedure is applied to 16 test complexes with different proteins and ligands. For almost all test complexes such energy recalculation results in the global energy minimum configuration corresponding to the ligand pose near the native ligand position in the crystalized protein-ligand complex. A significant improvement of the ligand positioning accuracy comparing with MMFF94 energy calculations is demonstrated.

Coagulation factor Xa and factor XIa are proven to be convenient and crucial protein targets for treatment for thrombotic disorders and thereby their inhibitors can serve as effective anticoagulant drugs. In the present work, we focused on the structure–activity relationships of derivatives of pyrrolo[3,2,1-ij]quinolin-2(1H)-one and an evaluation of their activity against factor Xa and factor XIa. For this, docking-guided synthesis of nine compounds based on pyrrolo[3,2,1-ij]quinolin-2(1H)-one was carried out. For the synthesis of new hybrid hydropyrrolo[3,2,1-ij]quinolin-2(1H)-one derivatives, we used convenient structural modification of both the tetrahydro- and dihydroquinoline moiety by varying the substituents at the C^6,8,9 positions. In vitro testing revealed that four derivatives were able to inhibit both coagulation factors and three compounds were selective factor XIa inhibitors. An IC₅₀ value of 3.68 μM for was found for the best factor Xa inhibitor and 2 μM for the best factor XIa inhibitor.

The initial step of the rational drug design pipeline extremely needs an increase in effectiveness. This can be done using molecular modeling: docking and molecular dynamics. Docking programs are popular now due to their simple idea, quickness and ease of use. Nevertheless accuracy of these programs still leaves much to be desired and discovery by chance and experimental screening still play an important role. Docking performs ligand positioning in the target protein and estimates the protein-ligand binding free energy. While in many cases positioning accuracy of docking is satisfactory, the accuracy of binding energy calculations is insufficient to perform the hit-to-lead optimization. The accuracy depends on many approximations which are built into the respective model. We show that all simplifications restricting docking accuracy can be withdrawn and this can be done on the basis of modern supercomputer facilities allowing to perform docking of one ligand using many thousand computing cores. We describe in short the SOL docking program which is used during years for virtual screening of large ligand databases using supercomputer resources of LomonosovMoscow State University. SOL to some extent is organized similarly to popular docking programs and reflects their limitations and advantages. We present our supercomputer docking programs, FLM and SOL-P, developed over the past 5 years for Lomonosov supercomputer of Moscow State University. These programs are free of most important simplifications and their performance shows the road map of the docking accuracy improvement. Some results of their performance for very flexible ligand docking into the rigid protein and docking of flexible ligands into the protein with some moveable protein atoms are presented. The so-called quasi-docking approach combining a force field and quantum chemical methods is described and it is shown that best docking accuracy is reached with the PM7 method and the COSMO solvent model.

In the modern world, complications caused by disorders in the blood coagulation system are found in almost all areas of medicine. Thus, the development of new, more advanced drugs that can prevent pathological conditions without disrupting normal hemostasis is an urgent task. The blood coagulation factor XIIa is one of the most promising therapeutic targets for the development of anticoagulants based on its inhibitors. The initial stage of drug development is directly related to computational methods of searching for a lead compound. In this study, docking followed by quantum chemical calculations was used to search for noncovalent low-molecular-weight factor XIIa inhibitors in a focused library of druglike compounds. As a result of the study, four low-molecular-weight compounds were experimentally confirmed as factor XIIa inhibitors. Selectivity testing revealed that two of the identified factor XIIa inhibitors were selective over the coagulation factors Xa and XIa.

Ab initio quantum molecular dynamics simulation is used to transform a silicon dioxide crystal into silica amorphous states. Two type of amorphous states are obtained from the melts stabilized at temperatures well above the crystal melting point. The first type of amorphous states are obtained from the melts stabilized at comparably low temperatures of \(3000\) and \(4000\) K. These states are characterized by a perfect structure similar to those of the initial crystal and vitreous silica glass without point defects. Completely different amorphous states are obtained from the high temperature melts of \(5000\) and \(6000\) K. Structures of these amorphous states are less regular and contain point defects of silicon dioxide such as over-coordinated fivefold silicon, threefold oxygen atoms and a new silica defect 2-Bridging Oxygen Center. The latter is detected in the model of amorphous silica for the first time and it is formed by two neighbouring \(SiO_{4}\)-tetrahedra with two common oxygen vertexes. The amorphous silica models can be useful for description of amorphous silicon dioxide films obtained by high energy ion-beam deposition process where a fast local melting-quenching process should exist.

Candidates to being inhibitors of the main protease (M${}^{pro}$) of SARS-CoV-2 were selected from the database of Voronezh State University using molecular modeling. The database contained approximately 19,000 compounds represented by more than 41,000 ligand conformers. These ligands were docked into M${}^{pro}$ using the SOL docking program. For one thousand ligands with best values of the SOL score, the protein–ligand binding enthalpy was calculated by the PM7 quantum-chemical method with the COSMO solvent model. Using the SOL score and the calculated protein–ligand binding enthalpies, eighteen compounds were selected for the experiments. Several of these inhibitors suppressed the replication of the coronavirus in cell culture, and we used the best three among them in the search for chemical analogs. Selection among analogs using the same procedure followed by experiments led to identification of seven inhibitors of the SARS-CoV-2 replication in cell culture with EC${}_{50}$ values at the micromolar level. The identified inhibitors belong to three chemical classes. The three inhibitors, 4,4-dimethyldithioquinoline derivatives, inhibit SARS-CoV-2 replication in Vero E6 cell culture just as effectively as the best published non-covalent inhibitors, and show low cytotoxicity. These results open up a possibility to develop antiviral drugs against the SARS-CoV-2 coronavirus.