Quantum Mechanical-Cluster Approach to Solve the Bioisosteric Replacement Problem in Drug Design.

Bioisosteres are molecules that differ in substituents but still have very similar shapes. Bioisosteric replacements are ubiquitous in modern drug design, where they are used to alter metabolism, change bioavailability, or modify activity of the lead compound. Prediction of relative affinities of bioisosteres with computational methods is a long-standing task; however, the very shape closeness makes bioisosteric substitutions almost intractable for computational methods, which use standard force fields.

The role of human in the loop: lessons from D3R challenge 4.

The rapid development of new machine learning techniques led to significant progress in the area of computer-aided drug design. However, despite the enormous predictive power of new methods, they lack explainability and are often used as black boxes. The most important decisions in drug discovery are still made by human experts who rely on intuitions and simplified representation of the field.

Quantifying Possible Routes for SpnF-Catalyzed Formal Diels-Alder Cycloaddition.

The Diels-Alder reaction is a cornerstone of modern organic synthesis. Despite this, it remains essentially inaccessible to biosynthetic approaches. Only a few natural enzymes catalyze even a formal [4 + 2] cycloaddition, and it remains uncertain if any of them proceed via the Diels-Alder mechanism.

An explicit account of solvation is essential for modeling Suzuki-Miyaura coupling in protic solvents.

We compared explicit and implicit solvation approaches in modeling the free energy profile of the final step of Suzuki-Miyaura coupling. Both approaches produced similar ΔG(≠) in all the studied solvents (benzene, toluene, DMF, ethanol, and water). Solvation free energies of individual reaction components reasonably correlated for explicit and implicit models in aprotic solvents (RMSE = 30-50 kJ mol(-1), R(2) > 0.

2,3-Dihydroxy-quinoxaline induces ATPase activity of Herpes Simplex Virus thymidine kinase.

2,3-Dihydroxy-quinoxaline, a small molecule that promotes ATPase catalytic activity of Herpes Simplex Virus thymidine kinase (HSV-TK), was identified by virtual screening. This compound competitively inhibited HSV-TK catalyzed phosphorylation of acyclovir with Ki=250 μM (95% CI: 106-405 μM) and dose-dependently increased the rate of the ATP hydrolysis with KM=112 μM (95% CI: 28-195 μM). The kinetic scheme consistent with this experimental data is proposed.

Alchemical FEP Calculations of Ligand Conformer Focusing in Explicit Solvent.

Slow rotational degrees of freedom in ligands can make alchemical FEP simulations unreliable due to inadequate sampling. We addressed this problem by introducing a FEP-based protocol of ligand conformer focusing in explicit solvent. Our method involves FEP transformations between conformers using equilibrium dihedral angle as a reaction coordinate and provides the cost of "focusing" on one specific conformational state that binds to a protein.

Molecular modeling of different substrate-binding modes and their role in penicillin acylase catalysis.

Molecular modeling was addressed to understand different substrate-binding modes and clarify the role of two positively charged residues of the penicillin G acylase active site - βR263 and αR145 - in binding of negatively charged substrates. Although the electrostatic contribution to productive substrate binding was dominated by βR263 rather than αR145, it was found that productive binding was not the only possible mode of substrate placement in the active site. Two extra binding modes - nonproductive and preproductive - were located by means of molecular docking and dynamics with binding affinities comparable with the productive one.

Lead Finder docking and virtual screening evaluation with Astex and DUD test sets.

Lead Finder is a molecular docking software. Sampling uses an original implementation of the genetic algorithm that involves a number of additional optimization procedures. Lead Finder's scoring functions employ a set of semi-empiric molecular mechanics functionals that have been parameterized independently for docking, binding energy predictions and rank-ordering for virtual screening.

Hit clustering can improve virtual fragment screening: CDK2 and PARP1 case studies.

Virtual fragment screening could be a promising alternative to existing experimental screening techniques. However, reliable methods of in silico fragment screening are yet to be established and validated. In order to develop such an approach we first checked how successful the existing molecular docking methods can be in predicting fragment binding affinities and poses.

TSAR, a new graph-theoretical approach to computational modeling of protein side-chain flexibility: modeling of ionization properties of proteins.

A new graph-theoretical approach called thermodynamic sampling of amino acid residues (TSAR) has been elaborated to explicitly account for the protein side chain flexibility in modeling conformation-dependent protein properties. In TSAR, a protein is viewed as a graph whose nodes correspond to structurally independent groups and whose edges connect the interacting groups. Each node has its set of states describing conformation and ionization of the group, and each edge is assigned an array of pairwise interaction potentials between the adjacent groups.

CSAR scoring challenge reveals the need for new concepts in estimating protein-ligand binding affinity.

The dG prediction accuracy by the Lead Finder docking software on the CSAR test set was characterized by R(2)=0.62 and rmsd=1.93 kcal/mol, and the method of preparation of the full-atom structures of the test set did not significantly affect the resulting accuracy of predictions.

Improving performance of docking-based virtual screening by structural filtration.

In the current study an innovative method of structural filtration of docked ligand poses is introduced and applied to improve the virtual screening results. The structural filter is defined by a protein-specific set of interactions that are a) structurally conserved in available structures of a particular protein with its bound ligands, and b) that can be viewed as playing the crucial role in protein-ligand binding. The concept was evaluated on a set of 10 diverse proteins, for which the corresponding structural filters were developed and applied to the results of virtual screening obtained with the Lead Finder software.

Developing novel approaches to improve binding energy estimation and virtual screening: a PARP case study.

Poly-(ADP-ribose)-polymerase (PARP) is a promising anti-cancer target as it plays a crucial role in the cellular reparation and survival mechanisms. However, the development of a robust and cost effective experimental technique to screen PARP inhibitors is still a scientific challenge owing to the difficulties in quantitative detection of the enzyme activity. In this work we demonstrate that the computational chemistry tools including molecular docking and scoring can perform on par with the experimental studies in assessing binding constants and in the recovery of active compounds in virtual screening.

Lead finder: an approach to improve accuracy of protein-ligand docking, binding energy estimation, and virtual screening.

An innovative molecular docking algorithm and three specialized high accuracy scoring functions are introduced in the Lead Finder docking software. Lead Finder's algorithm for ligand docking combines the classical genetic algorithm with various local optimization procedures and resourceful exploitation of the knowledge generated during docking process. Lead Finder's scoring functions are based on a molecular mechanics functional which explicitly accounts for different types of energy contributions scaled with empiric coefficients to produce three scoring functions tailored for (a) accurate binding energy predictions; (b) correct energy-ranking of docked ligand poses; and (c) correct rank-ordering of active and inactive compounds in virtual screening experiments.