Assessing Molecular Docking Tools for Relative Biological Activity Prediction: A Case Study of Triazole HIV-1 NNRTIs

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. We combined various neural networks and linear regression algorithms to build models for cytotoxicity and anti-HIV activity based on Continual Molecular Interior analysis (CoMIn) and Cinderella's Shoe (CiS) derived molecular descriptors. After validating the reliability of the models, a genetic algorithm was coupled with the Des-Pot Grid algorithm to generate new molecules from a predefined pool of molecular fragments and predict their bioactivity and cytotoxicity. This combination led to the proposal of 16 hit molecules with high anti-HIV activity and low cytotoxicity. The anti-SARS-CoV-2 activity of the hits was predicted.

Molecular Docking: Challenges, Advances and its Use in Drug Discovery Perspective

Molecular docking is a process through which small molecules are docked into the macromolecular structures for scoring its complementary values at the binding sites. It is a vibrant research area with dynamic utility in structure-based drug-designing, lead optimization, biochemical pathway and for drug designing being the most attractive tools. Two pillars for a successful docking experiment are correct pose and affinity prediction. Each program has its own advantages and drawbacks with respect to their docking accuracy, ranking accuracy and time consumption so a general conclusion cannot be drawn. Moreover, users don't always consider sufficient diversity in their test sets which results in certain programs to outperform others. In this review, the prime focus has been laid on the challenges of docking and troubleshooters in existing programs, underlying algorithmic background of docking, preferences regarding the use of docking programs for best results illustrated with examples, comparison of performance for existing tools and algorithms, state of art in docking, recent trends of diseases and current drug industries, evidence from clinical trials and post-marketing surveillance are discussed. These aspects of the molecular drug designing paradigm are quite controversial and challenging and this review would be an asset to the bioinformatics and drug designing communities.

Marine Bacterial Compounds Evaluated by In Silico Studies as Antipsychotic Drugs Against Schizophrenia

Schizophrenia (SCZ) is one of the brain disorders which affects the thinking and behavioral skills of patients. This disorder comes along with an overproduction of kynurenic acid in the cerebrospinal fluid and the prefrontal cortex of SCZ patients. In this study, marine bacterial compounds were screened for their suitability as antagonists against human kynurenine aminotransferase (hKAT-1) which causes the synthesis of kynurenic acid downstream which ultimately causes the SCZ disorder according to the kynurenic hypothesis of SCZ. The marine actinobacterial compound bonactin shows more promising results than other tested marine compounds such as the histamine H2 blocker famotidine and indole-3-acetic acid (IAC) from docking and in silico toxicological studies carried out here. The obtained results of the Grid-based Ligand Docking with Energetics (Glide) scores of extra-precision (XP) Glide against the target protein hKAT-1 on IAC, famotidine, and bonactin were - 6.581, - 6.500 and - 7.730 kcal/mol where Glide energies were - 29.84, - 28.391, and - 47.565 kcal/mol, respectively. Bonactin is known as an antibacterial and antifungal compound being extracted from a marine Streptomyces sp. Comparing tested compounds against the drug target hKAT-1, bonactin alone showed the best Glide score and Glide energy on the target protein hKAT-1.

Molecular Docking Studies of HIV-1 Resistance to Reverse Transcriptase Inhibitors: Mini-Review

Currently, millions of people are living with human immunodeficiency virus type 1 (HIV-1), which causes acquired immunodeficiency syndrome. However, the spread of the HIV-1 resistance to antiviral agents is the major problem in the antiretroviral therapy and medical management of HIV-infected patients. HIV-1 reverse transcriptase (RT) is one of the key viral targets for HIV-1 inhibition. Therefore, the studies on the combatting the HIV resistance that occurs due to the structural changes in RT, are in great demand. This work aims to provide an overview of the state-of-the-art molecular docking approaches applied to the studies of the HIV-1 resistance, associated with RT structure changes. We have reviewed recent studies using molecular docking with mutant forms of RT. The work discusses the modifications of molecular docking, which have been developed to find the novel molecules active against resistance mutants of RT and/or recombinant strains of HIV-1. The perspectives of the existing algorithms of molecular docking to the studies on molecular mechanisms of resistance and selection of the correct binding poses for the reverse transcriptase inhibitors are discussed.

Importance of protein flexibility in molecular recognition: a case study on Type-I1/2 inhibitors of ALK

Anaplastic lymphoma kinase (ALK) has been regarded as a promising target for the therapy of various cancers.

Diaryl ethers with carboxymethoxyphenacyl motif as potent HIV-1 reverse transcriptase inhibitors with improved solubility

In search of new non-nucleoside reverse transcriptase inhibitors (NNRTIs) with improved solubility, two series of novel diaryl ethers with phenacyl moiety were designed and evaluated for their HIV-1 reverse transcriptase inhibition potentials. All compounds exhibited good to excellent results with IC₅₀ at low micromolar to submicromolar concentrations. Two most active compounds (7e and 7 g) exhibit inhibitory potency comparable or even better than that of nevirapine and rilpivirine. Furthermore, SupT1 and CD4⁺ cell infectivity assays for the most promising (7e) have confirmed its strong antiviral potential while docking studies indicate a novel binding interactions responsible for high activity.

Docking Methodologies and Recent Advances

Docking, a molecular modelling method, has wide applications in identification and optimization in modern drug discovery. This chapter addresses the recent advances in the docking methodologies like fragment docking, covalent docking, inverse docking, post processing, hybrid techniques, homology modeling etc. and its protocol like searching and scoring functions. Advances in scoring functions for e.g. consensus scoring, quantum mechanics methods, clustering and entropy based methods, fingerprinting, etc. are used to overcome the limitations of the commonly used force-field, empirical and knowledge based scoring functions. It will cover crucial necessities and different algorithms of docking and scoring. Further different aspects like protein flexibility, ligand sampling and flexibility, and the performance of scoring function will be discussed.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Development and in Vitro Evaluation of a Microbicide Gel Formulation for a Novel Non-Nucleoside Reverse Transcriptase Inhibitor Belonging to the N-Dihydroalkyloxybenzyloxopyrimidines (N-DABOs) Family

Preventing HIV transmission by the use of a vaginal microbicide is a topic of considerable interest in the fight against AIDS. Both a potent anti-HIV agent and an efficient formulation are required to develop a successful microbicide. In this regard, molecules able to inhibit the HIV replication before the integration of the viral DNA into the genetic material of the host cells, such as entry inhibitors or reverse transcriptase inhibitors (RTIs), are ideal candidates for prevention purpose. Among RTIs, S- and N-dihydroalkyloxybenzyloxopyrimidines (S-DABOs and N-DABOs) are interesting compounds active at nanomolar concentration against wild type of RT and with a very interesting activity against RT mutations. Herein, novel N-DABOs were synthesized and tested as anti-HIV agents. Furthermore, their mode of binding was studied by molecular modeling. At the same time, a vaginal microbicide gel formulation was developed and tested for one of the most promising candidates.

Studies on the binding sites of IgG2 monoclonal antibodies recognized by terpyridine-based affinity ligands

This investigation has examined the origin of the molecular recognition associated with the interaction of monoclonal IgG2's with terpyridine-based ligands immobilized onto agarose-derived chromatographic adsorbents. Isothermal titration calorimetric (ITC) methods have been employed to acquire thermodynamic data associated with the IgG2-ligand binding. These ITC investigations have documented that different enthalpic and entropic processes are involved depending on the nature of the chemical substituents in the core structure of the terpyridinyl moiety. In addition, molecular docking studies have been carried out with IgG2 structures with the objective to identify possible ligand binding sites and key interacting amino acid residues. These molecular docking experiments with the different terpyridine-based ligands have shown that all of the examined ligands can potentially undergo favorable interactions with a site located within the Fab region of the IgG2. However, another favorable binding site was also identified from the docking poses to exist within the Fc region of the IgG2 for some, but not all, of the ligands studied. These investigations have provided a basis to elucidate the unique binding properties and chromatographic behaviors shown by several substituted terpyridine ligands in their interaction with IgGs of different isotype. Copyright © 2016 John Wiley & Sons, Ltd.

vSDC: a method to improve early recognition in virtual screening when limited experimental resources are available

Background

In drug design, one may be confronted to the problem of finding hits for targets for which no small inhibiting molecules are known and only low-throughput experiments are available (like ITC or NMR studies), two common difficulties encountered in a typical academic setting. Using a virtual screening strategy like docking can alleviate some of the problems and save a considerable amount of time by selecting only top-ranking molecules, but only if the method is very efficient, i.e. when a good proportion of actives are found in the 1–10 % best ranked molecules.

Results

The use of several programs (in our study, Gold, Surflex, FlexX and Glide were considered) shows a divergence of the results, which presents a difficulty in guiding the experiments. To overcome this divergence and increase the yield of the virtual screening, we created the standard deviation consensus (SDC) and variable SDC (vSDC) methods, consisting of the intersection of molecule sets from several virtual screening programs, based on the standard deviations of their ranking distributions.

Conclusions

SDC allowed us to find hits for two new protein targets by testing only 9 and 11 small molecules from a chemical library of circa 15,000 compounds. Furthermore, vSDC, when applied to the 102 proteins of the DUD-E benchmarking database, succeeded in finding more hits than any of the four isolated programs for 13–60 % of the targets. In addition, when only 10 molecules of each of the 102 chemical libraries were considered, vSDC performed better in the number of hits found, with an improvement of 6–24 % over the 10 best-ranked molecules given by the individual docking programs.Graphical abstract

Theoretical studies of energetics and binding isotope effects of binding a triazole-based inhibitor to HIV-1 reverse transcriptase

The ¹⁸O binding isotope effect allows us to distinguish the actual binding site of an inhibitor in HIV-1 reverse transcriptase.

A combined experimental and computational study on the interaction of nitrogen mustards with DNA

In the present work, we suggest that the role of water in the reaction of nitrogen mustards with DNA is more than what was thought before. Nitrogen mustards become activated when they are hydrated by water.

Searching for novel scaffold of triazole non-nucleoside inhibitors of HIV-1 reverse transcriptase

Azoles are a promising class of the new generation of HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs). From thousands of reported compounds, many possess the same basic structure of an aryl substituted azole ring linked by a thioglycolamide chain with another aromatic ring. In order to find novel extensions for this basic scaffold, we explored the 5-position substitution pattern of triazole NNRTIs using molecular docking followed by the synthesis of selected compounds. We found that heterocyclic substituents in the 5-position of the triazole ring are detrimental to the inhibitory activity of compounds with four-membered thioglycolamide linker and this substitution seems to be viable only for compounds with shorter two-membered linker. Promising compound, N-(4-carboxy-2-chlorophenyl)-2-((4-benzyl-5-methyl-4H-1,2,4-triazol-3-yl)sulfanyl)acetamide, with potent inhibitory activity and acceptable aqueous solubility has been identified in this study that could serve as lead scaffold for the development of novel water-soluble salts of triazole NNRTIs.

De novo mutations in KIF1A cause progressive encephalopathy and brain atrophy

Objective

To determine the cause and course of a novel syndrome with progressive encephalopathy and brain atrophy in children.

Methods

Clinical whole-exome sequencing was performed for global developmental delay and intellectual disability; some patients also had spastic paraparesis and evidence of clinical regression. Six patients were identified with de novo missense mutations in the kinesin gene KIF1A. The predicted functional disruption of these mutations was assessed in silico to compare the calculated conformational flexibility and estimated efficiency of ATP binding to kinesin motor domains of wild-type (WT) versus mutant alleles. Additionally, an in vitro microtubule gliding assay was performed to assess the effects of de novo dominant, inherited recessive, and polymorphic variants on KIF1A motor function.

Results

All six subjects had severe developmental delay, hypotonia, and varying degrees of hyperreflexia and spastic paraparesis. Microcephaly, cortical visual impairment, optic neuropathy, peripheral neuropathy, ataxia, epilepsy, and movement disorders were also observed. All six patients had a degenerative neurologic course with progressive cerebral and cerebellar atrophy seen on sequential magnetic resonance imaging scans. Computational modeling of mutant protein structures when compared to WT kinesin showed substantial differences in conformational flexibility and ATP-binding efficiency. The de novo KIF1A mutants were nonmotile in the microtubule gliding assay.

Interpretation

De novo mutations in KIF1A cause a degenerative neurologic syndrome with brain atrophy. Computational and in vitro assays differentiate the severity of dominant de novo heterozygous versus inherited recessive KIF1A mutations. The profound effect de novo mutations have on axonal transport is likely related to the cause of progressive neurologic impairment in these patients.

Improvements, trends, and new ideas in molecular docking: 2012-2013 in review

Molecular docking is a computational method for predicting the placement of ligands in the binding sites of their receptor(s). In this review, we discuss the methodological developments that occurred in the docking field in 2012 and 2013, with a particular focus on the more difficult aspects of this computational discipline. The main challenges and therefore focal points for developments in docking, covered in this review, are receptor flexibility, solvation, scoring, and virtual screening. We specifically deal with such aspects of molecular docking and its applications as selection criteria for constructing receptor ensembles, target dependence of scoring functions, integration of higher-level theory into scoring, implicit and explicit handling of solvation in the binding process, and comparison and evaluation of docking and scoring methods.

Importance of protein flexibility in ranking inhibitor affinities: modeling the binding mechanisms of piperidine carboxamides as Type I1/2 ALK inhibitors

Anaplastic lymphoma kinase (ALK) has gained increased attention as an attractive therapeutic target for the treatment of various cancers, especially non-small-cell lung cancer (NSCLC).

Anti-HIV drug development through computational methods

Although highly active antiretroviral therapy (HAART) is effective in controlling the progression of AIDS, the emergence of drug-resistant strains increases the difficulty of successful treatment of patients with HIV infection. Increasing numbers of patients are facing the dilemma that comes with the running out of drug combinations for HAART. Computational methods play a key role in anti-HIV drug development. A substantial number of studies have been performed in anti-HIV drug development using various computational methods, such as virtual screening, QSAR, molecular docking, and homology modeling, etc. In this review, we summarize recent advances in the application of computational methods to anti-HIV drug development for five key targets as follows: reverse transcriptase, protease, integrase, CCR5, and CXCR4. We hope that this review will stimulate researchers from multiple disciplines to consider computational methods in the anti-HIV drug development process.