quantitative-structure-activity-relationship-activity-prediction

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

The increasing incidence of HIV-1 drug resistance presents a challenge to the effectiveness of combination antiretroviral therapy, particularly in ...

university of Johannesburg

Two-dimensional TiSe, with YbMnSb and AlSbYb thermoelectric materials, were used to generate heterostructures. The electronic and optical calculations were done using the Materials Studio 2018 modelling software package, employing the Cambridge Serial Total Energy Package code and using the generalised gradient approximation with Perdew-Burke-Ernzerhof exchange-correlation functionals. However, the electronic results obtained revealed a reduction in the calculated band gap and an increase in the slope of the density of state at the Femi level, as well as the energy bands of the generated heterostructures was reported. Partial density of states showed that various orbitals were present in the thermoelectric materials. The thermal transport and electronic properties are compared using the Boltzmann transport theory and Mott derived equations, which were expressed in the maximum attainable figure of merit. A variation in the electric potential of the layers is observed. The dielectric function is found to decrease in both thermoelectric layers generated and far more than the YbMnSb-TiSe layer, which was more negative. The reduction in reflectivity of AlSbYbTiSe layer and elevation of the YbMnSb-TiSe layer is observed. Upon forming heterostructures with TiSe, the conductivity reduced in the high frequency, due to the generated complex multicomponent compounds.

The effects of two-dimensional TiSe on the thermoelectric, electronic and optical response of YbMnSb/AlSbYb heterostructures - A theoretical study.

Timely and accurate diagnosis of Alzheimer's disease (AD) remains a major challenge in the medical arena. β-amyloid (Aβ) imaging techniques such as positron emission tomography and single photon emission computed tomography require the use of an imaging probe. To date, only flutemetamol, florbetaben and florbetapir have been approved for clinical use as imaging probes. Design of imaging probes requires a detailed understanding of disease mechanism(s) and receptor-ligand interaction. In this study, molecular docking, molecular dynamics and binding free energies were used to investigate the multiple binding sites exhibited by β-amyloid fibrils. Protein atomic models 2BEG, 5KK3, 2M4J, 2LMN, 5OQV, 2NAO, 2MVX and 2MXU (protein databank codes) were used to investigate the nature and location of binding sites and binding profiles of selected molecules with known affinities. Although amyloid fibrils are known to have multiple binding sites, we demonstrated that model 2MXU possesses one site which is druggable and can bind with common scaffolds currently being used in the imaging of amyloid fibrils. Models 2NAO, 5KK3 and 2M4J revealed that even though multiple sites may be available in some fibrils, the entire protein may not have a druggable site. Molecular dynamics revealed atomic models 2MXU and 2MVX to be the least flexible among the list. The outcomes of this investigation can be translated to assist in designing novel molecules that can be used for brain imaging in Alzheimer's disease.

Computational investigation of the binding characteristics of β-amyloid fibrils.

Currently, only three molecules, flutemetamol, florbetaben and florbetapir, have been approved for clinical use towards the definitive diagnosis of Alzheimer's disease (AD). Despite the clinically approved drugs' advantages, there still exists a need for new diagnostic molecules with improved properties (physicochemical and pharmacokinetic) in comparison to the current molecules in clinical use and research. In this work, we report a pharmacophore model and a quantitative structure activity relationship (QSAR) model, constructed from a series of 166 amyloid beta diagnostic compounds (targeting Alzheimer's disease) with the purpose of identifying functional groups influencing and predicting bioactivity. Subsequently, pharmacophore based virtual screening and QSAR predictions were used to identify new amyloid beta diagnostic molecules. In addition, docking and molecular dynamics simulations were conducted to explore the type and nature of interactions required for ligands to bind effectively in the binding regions of amyloid beta fibrils (PDB 2MXU). In our findings, the highest-ranked 4 feature pharmacophore model possessed one hydrogen bond acceptor, one hydrophobic feature and two ring features (AHRR). Systematically, the same dataset of molecules used for pharmacophore modelling was used to generate an atom-based 3D QSAR hypothesis to illustrate the activity relationship of amyloid-beta diagnostic molecules. The partial least squares (PLS) 3D QSAR model obtained showed good correlation as indicated by respective statistical parameters, R^2, Q^2 and Pearson values of 0.76, 0.72 and 0.86 respectively. Virtual screening against ZINC15 database and the ChemBridge CNS-Set yielded 7 molecules, 4 of which had satisfactory ADME properties. Docking and molecular dynamics simulations showed that hydrogen bonding, hydrophobic and π-π interactions are crucial towards the binding of ligands (as predicted by our pharmacophore and QSAR models) to amyloid beta fibrils. In conclusion, the findings of this work present a wealth of information that can be useful in future research towards identifying and design of new amyloid diagnostic molecules. The pharmacophore presented here can be used to filter independent databases to identify new structurally related molecules with improved activity whereas the QSAR model can be useful in predicting bioactivities of the predicted hits.

Ligand-based pharmacophore modelling and virtual screening for the identification of amyloid-beta diagnostic molecules.

Segmented polyurethanes show extraordinary physicochemical properties, mainly owing to the nature and the chemistry of the hard segment domains. There are yet many inexplicable physiochemical properties of MDI-BDO-based hard polyurethane segments such as the geometry, cis-trans isomerism, electronic structure, chemical reactivity, the inter-hard-segment interactions, and the photo-response. In the present study, it was attempted to develop and validate a model system that would facilitate further research on the structural and chemical properties of the MDI-BDO hard segments. It was found that the trans isomer of urethane bond is more stable than the cis isomer, and it is argued here that thermal transformation from trans to cis not possible due to the high rotational energy barrier. The differences between the calculated IR spectra of the cis and trans isomers are proposed as a powerful differentiation tool. The calculated Fukui indices show that cis and trans isomers are different in their chemical reactivity. The findings of the present study suggest intermolecular and intramolecular pi-stacking and highly plausible two significant types of hydrogen bond types between hard segments. In the present study, a model system for MDI-BDO hard segment was developed and successfully validated via computational experiments. Further calculations done with the new model provided an indispensable understanding of the structure, cis-trans isomerism, reactivity, and intermolecular interactions of the MDI-BDO hard segments. The proposed model can be further improved in the future by incorporating suitable soft segments. In summary, the model system developed and validated in the present study has provided new opportunities to understand and further study the structural and chemical features of the hard segments of the MDI-BDO-based polyurethane.

Computational development and validation of a representative MDI-BDO-based polyurethane hard segment model.

A group of bioactive compounds known as triterpenoids, which are often found in plant materials, have been tested to possess nutritional and pharmaceutical activity. These plant components are referred to as nutraceuticals, and are used as therapeutic agents. In this study, we explore the interactions of betulinic acid (BA), oleanolic acid (OA), ursolic acid (UA), and maslinic acid (MA) against FadA5. Studies have identified FadA5, a trifunctional enzyme-like thiolase, as a target towards Mycobacterium tuberculosis inhibition. The investigation involves molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) applications. Analyses of the four pentacyclic triterpenoids binding to FadA5 showed appreciable bioactivity against FadA5. The application of two or more theoretical models to unravel ligand-enzyme binding energies can pave the way for accurate binding affinity prediction and validation.

Exploring the bioactivity of pentacyclic triterpenoids as potential antimycobacterial nutraceutics: Insights through comparative biomolecular modelling.

Corrigendum to "Exploring the bioactivity of pentacyclic triterpenoids as potential antimycobacterial nutraceutics: Insights through comparative biomolecular modelling" [J. Mol. Graph. Model. 105 (2021) 107900-107908/JMGM-D-20-00515R1].

Acquired immunodeficiency syndrome (AIDS), one of the deadliest global diseases, is caused by the Human Immunodeficiency Virus (HIV). To date, there are no known conventional drugs that can cure HIV/AIDS, and this has prompted continuous scientific efforts in the search for novel and potent anti-HIV therapies. In this study, molecular dynamics simulation (MDS) and computational techniques were employed to investigate the inhibitory potential of bioactive compounds from selected South African indigenous plants against HIV-1 subtype C protease (HIVpro). Of the eight compounds (CMG, MA, UA, CA, BA, UAA, OAA and OA) evaluated, only six (CMG (-9.9 kcal/mol), MA (-9.3 kcal/mol), CA (-9.0 kcal/mol), BA (-8.3 kcal/mol), UAA (-8.5 kcal/mol), and OA (-8.6 kcal/mol)) showed favourable activities against HIVpro and binding landscapes like the reference FDA-approved drugs, Lopinavir (LPV) and Darunavir (DRV), with CMG and MA having the highest binding affinities. Using the structural analysis (root-mean-square deviation (RMSD), fluctuation (RMSF), and radius of gyration (RoG) of the bound complexes with HIVpro after 350 ns, structural evidence was observed, indicating that the six compounds are potential lead candidates for inhibiting HIVpro. This finding was further corroborated by the structural analysis of the enzyme-ligand complexe systems, where structural mechanisms of stability, flexibility, and compactness of the study metabolites were established following binding with HIVpro. Furthermore, the ligand interaction plots revealed that the metabolites interacted hydrophobically with the active site amino residues, with identification of other key residues implicated in HIVpro inhibition for drug design. Overall, this is the first computational report on the anti-HIV-1 activities of CMG and MA, with efforts on their in vitro and in vivo evaluations underway. Judging by the binding affinity, the degree of stability, and compactness of the lead metabolites (CMG, MA, CA, BA, OA, and UAA), they could be concomitantly explored with conventional HIVpro inhibitors in enhancing their therapeutic activities against the HIV-1 serotype.

Molecular Dynamics Study on Selected Bioactive Phytochemicals as Potential Inhibitors of HIV-1 Subtype C Protease.

Mycobacterial pathogens present a significant challenge to disease control efforts globally due to their inherent resistance to multiple antibiotics. The rise of drug-resistant strains of Mycobacterium tuberculosis has prompted an urgent need for innovative therapeutic solutions. One promising way to discover new tuberculosis drugs is by utilizing natural products from the vast biochemical space. Multidisciplinary methods can used to harness the bioactivity of these natural products. This study aimed to evaluate the antimycobacterial efficacy of functional crude extracts from bacteria isolated from gold mine tailings in South Africa. Bacterial strains were identified using 16S rRNA sequencing. The crude extracts obtained from the bacteria were tested against Mycobacterium tuberculosis H37Rv, Mycobacterium smegmatis mc155, and Mycobacterium aurum A+. Untargeted HPLC-qTOF and molecular networking were used to identify the functional constituents present in extracts that exhibited inhibitory activity. A virtual screening workflow (VSW) was used to filter compounds that were strong binders to Mycobacterium tuberculosis Pks13 and PknG. The ligands returned from the VSW were subjected to optimization using density functional theory (DFT) at M06-2X/6-311++ (d,p) level of theory and basis set implemented in Gaussian16 Rev.C01. The optimized ligands were re-docked against Mycobacterium tuberculosis Pks13 and PknG. Molecular dynamics simulation and molecular mechanics generalized born surface area were used to evaluate the stability of the protein-ligand complexes formed by the identified hits. The hit that showed promising binding characteristics was virtually modified through multiple synthetic routes using reaction-driven enumeration. Three bacterial isolates showed significant activity against the two strains of Mycobacterium, while only two, Bacillus subtilis and Bacillus licheniformis, exhibited activity against both Mycobacterium tuberculosis H37Rv, Mycobacterium smegmatis mc155, and Mycobacterium aurum A+. The tentatively identified compounds from the bacterial crude extracts belonged to various classes of natural compounds associated with antimicrobial activity. Two compounds, cyclo-(L-Pro-4-OH-L-Leu) and vazabitide A, showed strong binding against PknG and Pks13, with pre-MD MM-GBSA values of - 42.8 kcal/mol and - 47.6 kcal/mol, respectively. The DFT-optimized compounds exhibited the same docking scores as the ligands optimized using the OPSL-4 force field. After modifying vazabitide A, its affinity to the Pks13 binding site increased to - 85.8 kcal/mol, as revealed by the post-MD MM-GBSA analysis. This study highlights the potential of bacteria isolates from gold mine tailings as a source of new scaffolds for designing and optimizing anti-Mycobacterium agents. These agents synthesized in-silico can be further tested in-vitro to evaluate their efficacy.

Molecular docking, molecular dynamics simulations and binding free energy studies of interactions between Mycobacterium tuberculosis Pks13, PknG and bioactive constituents of extremophilic bacteria.

As the world grapples with the relentless challenges posed by diseases like malaria, the advent of sophisticated computational tools has emerged as a beacon of hope in the quest for effective treatments. In this study we delve into the strategies behind computational tools encompassing virtual screening, molecular docking, artificial intelligence (AI), and machine learning (ML). We assess their effectiveness and contribution to the progress of malaria treatment. The convergence of these computational strategies, coupled with the ever-increasing power of computing systems, has ushered in a new era of drug discovery, holding immense promise for the eradication of malaria. SCIENTIFIC CONTRIBUTION: Computational tools remain pivotal in drug design and development. They provide a platform for researchers to explore various treatment options and save both time and money in the drug development pipeline. It is imperative to assess computational techniques and monitor their effectiveness in disease control. In this study we examine renown computational tools that have been employed in the battle against malaria, the benefits and challenges these tools have presented, and the potential they hold in the future eradication of the disease.

Leveraging computational tools to combat malaria: assessment and development of new therapeutics.

N-(2-hydroxyl) propyl-3-trimethyl ammonium chitosan chloride (HTCC), a quaternized chitosan derivative, has been shown to exhibit a broad spectrum of antimicrobial activity, especially against bacteria and enveloped viruses. Despite this, molecular docking studies showing its atomic-level mechanisms against these microorganisms are scarce. Here, for the first time, we employed molecular docking analyses to investigate the potential antibacterial activity of HTCC against  and its antiviral activity against human immunodeficiency virus 1 (HIV-1). According to the findings, HTCC exhibited promising antibacterial activity with high binding affinities; however, it had limited antiviral activity. To validate these theoretical outcomes, experimental studies were conducted. Different derivatives of HTCC were synthesized and characterized using NMR, XRD, FTIR, and DLS. The in vitro assays validated the potent antibacterial efficacy of HTCC against , whereas the antiviral studies did not show good antiviral activity. However, our research also revealed a promising avenue for further exploration of the antimicrobial activity of HTCC nanoparticles (NPs), since, thus far, no studies have been conducted to show the antiviral activity of HTCC NPs against HIV-1. The nanosized HTCC exhibited superior antiviral performance compared to the parent polymers, with complete (100%) inhibition of HIV-1 viral activity at the highest tested concentration (0.33 mg/mL).

Dual Antimicrobial Activity of HTCC and Its Nanoparticles: A Synergistic Approach for Antibacterial and Antiviral Applications Through Combined In Silico and In Vitro Studies.

The COVID-19 pandemic, caused by SARS-CoV-2, has underscored the urgent need for effective antiviral therapies, particularly against vaccine-resistant variants. This study investigates natural xanthone derivatives as potential inhibitors of the ACE2 receptor, a critical entry point for the virus. We computationally evaluated 91 xanthone compounds derived from Swertia chirayita, identifying two promising candidates: 8-O-[β-D-Xylopyranosyl-(1→6)-β-D-glucopyranosyl]-1,7-dihydroxy-3-methoxy xanthone (XAN71) and 8-O-[β-D-Xylopyranosyl-(1→6)-β-D-glucopyranosyl]-1-hydroxy-3,7-dimethoxy-xanthone (XAN72). Molecular docking and dynamics simulations (MDDS) were performed to assess their binding energy and stability within the ACE2 active site, comparing them to the reference inhibitor MLN-4067. The top six compounds were selected based on their docking performance, followed by Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) calculations to quantify binding affinities. Additionally, molecular electrostatic potential (MEP) analysis was conducted to visualize electron density regions relevant to binding interactions. Our results demonstrate that XAN71 and XAN72 exhibit superior binding affinities of -70.97 and - 69.85 kcal/mol, respectively, outperforming MLN-4067 (-61.33 kcal/mol). MD simulations revealed stable interactions with key ACE2 residues, primarily through hydrogen bonds and hydrophobic contacts. The Molecular Electrostatic Potential(MEP) analysis further elucidated critical electron density regions that enhance binding stability. This study establishes XAN71 and XAN72 as viable candidates for ACE2 inhibition, providing a structural basis for their development as natural xanthone-based therapeutics against SARS-CoV-2. These findings highlight the potential of targeting ACE2 with natural compounds to combat COVID-19, particularly in light of emerging viral variants.

In silico exploration of natural xanthone derivatives as potential inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication and cellular entry.

Computational approaches complement traditional in-vitro or in-vivo assays, significantly accelerating the drug discovery process by increasing the probability of identifying promising lead compounds. In this study, the apoptotic compounds were assessed for antimycobacterial activity and immunomodulatory potential in infected THP-1 macrophage cells. The antimycobacterial activity of the apoptotic compounds was evaluated using the minimum inhibitory concentration (MIC) assay. The immunomodulatory potential of the apoptotic compounds was determined on mycobacterial-infected THP-1 and non-infected THP-1 macrophage cells. The potential binding dynamics of the compounds against InhA were predicted using molecular docking, molecular dynamics, and MM-GBSA binding free energies. The in-vitro MIC assay showed that cepharanthine (CEP) had the highest antimycobacterial activity against Mycobacterium smegmatis mc155 and Mycobacterium tuberculosis H37Rv, with MICs of 3.1 and 1.5 µg/mL, respectively, followed by CP-31398 dihydrochloride hydrate (DIH) (MICs = 6.2 and 3.1 µg/mL, respectively), marinopyrrole A (MAR) (MICs = 25 and 12.5 µg/mL, respectively), and nutlin-3a (NUT) (MICs = 50 and 25 µg/mL, respectively). MICs for the rest of the drugs were > 200 µg/mL against both M. smegmatis mc155 and M. tuberculosis H37Rv. Furthermore, the growth of M. smegmatis mc155 in infected THP-1 macrophage cells treated with DIH, CEP, carboxyatractyloside potassium salt (CAR), and NUT was inhibited by the mentioned drugs. Cytokine profiling showed that DIH optimally regulated the secretion of IL-1β and TNF-α which potentially enhanced the clearance of the intracellular pathogen. Molecular dynamics simulations showed that NUT, MAR, 17-(allylamino)-17-demethoxygeldanamycin (17-AAG), and BV02 strongly bind to InhA. However, 17-AAG and BV02 did not show significant activity in-vitro. This study highlights the importance of probing already existing chemical scaffolds as a starting point for discovery of therapeutic agents against M. tuberculosis H37Rv using both pathogen and host directed approaches. The integration of molecular dynamics simulations provides valuable insights into potential scaffold modifications to enhance the affinity.

Article	Year
The effects of two-dimensional TiSe on the thermoelectric, electronic and optical response of YbMnSb/AlSbYb heterostructures - A theoretical study. Journal of molecular graphics & modelling\| PubMed ID: 30388692	2019
Computational investigation of the binding characteristics of β-amyloid fibrils. Biophysical chemistry\| PubMed ID: 31756663	2020
Ligand-based pharmacophore modelling and virtual screening for the identification of amyloid-beta diagnostic molecules. Journal of molecular graphics & modelling\| PubMed ID: 32898834	2020
Computational development and validation of a representative MDI-BDO-based polyurethane hard segment model. Journal of molecular modeling\| PubMed ID: 33432382	2021
Exploring the bioactivity of pentacyclic triterpenoids as potential antimycobacterial nutraceutics: Insights through comparative biomolecular modelling. Journal of molecular graphics & modelling\| PubMed ID: 33780786	2021
Corrigendum to "Exploring the bioactivity of pentacyclic triterpenoids as potential antimycobacterial nutraceutics: Insights through comparative biomolecular modelling" [J. Mol. Graph. Model... Journal of molecular graphics & modelling\| PubMed ID: 34022540	2021
Molecular Dynamics Study on Selected Bioactive Phytochemicals as Potential Inhibitors of HIV-1 Subtype C Protease. Metabolites\| PubMed ID: 36422295	2022
Molecular docking, molecular dynamics simulations and binding free energy studies of interactions between Mycobacterium tuberculosis Pks13, PknG and bioactive constituents of extremophilic b... Scientific reports\| PubMed ID: 38514663	2024
Leveraging computational tools to combat malaria: assessment and development of new therapeutics. Journal of cheminformatics\| PubMed ID: 38698437	2024
Dual Antimicrobial Activity of HTCC and Its Nanoparticles: A Synergistic Approach for Antibacterial and Antiviral Applications Through Combined In Silico and In Vitro Studies. Polymers\| PubMed ID: 39518210	2024
In silico exploration of natural xanthone derivatives as potential inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication and cellular entry. Journal of computer-aided molecular design\| PubMed ID: 39960606	2025
Repurposing of apoptotic inducer drugs against Mycobacterium tuberculosis. Scientific reports\| PubMed ID: 40016256	2025

Krishna K. Govender

Biography

JoVE Journal Publications

Other Publications