The design of compounds with desirable properties - The anti-HIV case study.

Efficacy and safety are among the most desirable characteristics of an ideal drug. The tremendous increase in computing power and the entry of artificial intelligence into the field of computational drug design are accelerating the process of identifying, developing, and optimizing potential drugs. Here, we present novel approach to design new molecules with desired properties.

Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking.

Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low.

Complementarity principle in terms of electron density for the study of EGFR complexes.

The complementarity principle is a well-established concept in the field of chemistry and biology. This concept is widely studied as the lock-and-key relationship between two structures, such as enzyme and ligand interactions. These interactions are based on the overlap of electron clouds between two structures.

Can natural products stop the SARS-CoV-2 virus? A docking and molecular dynamics study of a natural product database.

The SARS-CoV-2 3CLpro is one of the primary targets for designing new and repurposing known drugs. A virtual screening of molecules from the Natural Product Atlas was performed, followed by molecular dynamics simulations of the most potent inhibitor bound to two conformations of the protease and into two binding sites. Eight molecules with appropriate ADMET properties are suggested as potential inhibitors.

Computational insights into the binding mode of curcumin analogues against EP300 HAT domain as potent acetyltransferase inhibitors.

Acetylation plays a key role in maintaining and balancing cellular regulation and homeostasis. Acetyltransferases are an important class of enzymes which mediate this acetylation process. EP300 is a type 3 major lysine (K) acetyl transferase, and its aberrant activity is implicated in many human diseases.

Electron density analysis of CDK complexes using the AlteQ method.

A principle of complementarity is a well-established concept in chemistry and biology. This concept is based on the overlap of electron clouds of the molecules in question. In this article, one such approach (an in-house developed quantum free-orbital AlteQ method) was used to evaluate the complementarity of 51 CDK-ligand complexes.

Novel radial distribution function approach in the study of point mutations: the HIV-1 protease case study.

Mutations are one of the engines of evolution. Under constant stress pressure, mutations can lead to the emergence of unwanted, drug-resistant entities. The radial distribution function weighted by the number of valence shell electrons is used to design quantitative structure-activity relationship (QSAR) model relating descriptors with the inhibition constant for a series of wild-type HIV-1 protease inhibitor complexes.

Performance of radial distribution function-based descriptors in the chemoinformatic studies of HIV-1 protease.

This letter investigates the role of radial distribution function-based descriptors for design of new drugs. The multiple linear regression models for HIV-1 protease and its complexes with a series of inhibitors were constructed. A detailed analysis of major atomic contributions to the radial distribution function descriptor weighted by the number of valence shell electrons identified residues Arg8, Asp29 and residues of the catalytic triad as crucial for the correlation with the inhibition constant, together with residues Asp30 and Ile50, whose mutations are known to cause an emergence of drug resistant variants.

The Influence of Hydrogen Atoms on the Performance of Radial Distribution Function-Based Descriptors in the Chemoinformatic Studies of HIV-1 Protease Complexes with Inhibitors.

Aims: The aim of this letter is to explore the influence of adding hydrogen atoms to the crystallographic structures of HIV-1 protease complexes with a series of inhibitors on the performance of radial distribution function based descriptors recently introduced in chemoinformatic studies.

Background: Quite recently the successful application of molecular descriptors based on a radial distribution function to correlate it with biologically interesting properties of a ligand - enzyme complex was demonstrated. Except its predictive power, the analysis of atoms with dominant contributions to the RDFs can be used to identify relevant atoms and interactions.

Nonparametric chemical descriptors for the calculation of ligand-biopolymer affinities with machine-learning scoring functions.

The computational prediction of ligand-biopolymer affinities is a crucial endeavor in modern drug discovery and one that still poses major challenges. The choice of the appropriate computational method often reveals itself as a trade-off between accuracy and speed, with mathematical devices referred to as scoring functions being the fastest. Among the many shortcomings of scoring functions there is the lack of universal applicability to every molecular system.

Topological Analysis of Electron Density in Large Biomolecular Systems.

Background: A great step toward describing the structure of the molecular electron was made in the era of quantum chemical methods. Methods play a very important role in the prediction of molecular properties and in the description of the reactivity of compounds, which cannot be overestimated. There are many works, books, and articles on quantum methods, their applications, and comparisons.

Grid-based Continual Analysis of Molecular Interior for Drug Discovery, QSAR and QSPR.

Background: In 1979, R.D.Cramer and M.

An approximation of the Cioslowski–Mixon bond order indexes using the AlteQ approach.

Fast and reliable prediction of bond orders in organic systems based upon experimentally measured quantities can be performed using electron density features at bond critical points (J Am Chem Soc 105:5061–5068, 1983; J Phys Org Chem 16:133–141, 2003; Acta Cryst B 61:418–428, 2005; Acta Cryst B 63:142–150, 2007). These features are outcomes of low-temperature high-resolution X-ray diffraction experiments. However, a time-consuming procedure of gaining these quantities makes the prediction limited.

Technique for energy decomposition in the study of "receptor-ligand" complexes.

A new methodology to describe the interactions in "receptor-ligand" complexes is presented. The methodology is based on a combination of the 3D/4D QSAR BiS/MC and CoCon algorithms. The first algorithm performs the restricted docking of compounds to receptor pockets.

A new paradigm for pattern recognition of drugs.

A new paradigm is suggested for pattern recognition of drugs. The approach is based on the combined application of the 4D/3D quantitative structure-activity relationship (QSAR) algorithms BiS and ConGO. The first algorithm, BiS/MC (multiconformational), is used for the search for the conformers interacting with a receptor.