Improving virtual screening results with MM/GBSA and MM/PBSA rescoring

Identification of novel chemical scaffolds against kinase domain of cancer causing human epidermal growth factor receptor 2: a systemic chemoinformatic approach

The Human epidermal growth factor receptor 2 (HER2) is expressed in high magnitude in several cancers. Designing new drug molecules that target kinase domain of the HER2 enzyme might provide an appealing platform. Considering this, herein, a multi-phase bioinformatic approach is applied to screen diverse natural and chemical scaffolds to identify compounds that fit best at the kinase domain of HER2. By doing so, three compounds; LAS_51187157, LAC_51217113, LAC_51390233 were pointed with docking score of -11.4 kcal/mol, -11.3 kcal/mol and -11.2 kcal/mol, respectively. In molecular dynamic simulation, the complexes behaved in a stable dynamic with no major local/global structural variations. The intermolecular binding free energies were further estimated that concluded LAC_51390233 complex was the most stable and has less entropy energy. The good docked affinity of LAC_51390233 with HER2 was confirmed by WaterSwap absolute binding free energy. The entropy energy demonstrated that LAC_51390233 has less freedom energy compared to others. Similarly, all three compounds revealed very favorable druglike properties and pharmacokinetics. All the selected three compounds were also non-carcinogenic, non-immunotoxicity, non-mutagenicity, and non-cytotoxic. In a nutshell, the compounds are interesting scaffolds and might be subjected to extensive experimental testing to reveal their real biological potency.Communicated by Ramaswamy H. Sarma.

Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation

GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibitors. In this study, multiclass classification-based QSAR models were developed using diverse machine learning algorithms. These models were built from curated compounds with experimentally derived GRK5 inhibitory activity. Additionally, a pharmacophore model was constructed using active compounds from the dataset. Among the models, the SVM-based approach proved most effective and was initially used to screen DrugBank compounds within the applicability domain. Compounds showing significant GRK5 inhibitory potential underwent evaluation for key pharmacophoric features. Prospective compounds were subjected to molecular docking to assess binding affinity towards GRK5's key active site amino acid residues. Stability at the binding site was analyzed through 200 ns molecular dynamics simulations. MM-GBSA analysis quantified individual free energy components contributing to the total binding energy with respect to binding site residues. Metadynamics analysis, including PCA, FEL, and PDF, provided crucial insights into conformational changes of both apo and holo forms of GRK5 at defined energy states. The study identifies DB02844 (S-Adenosyl-1,8-Diamino-3-Thiooctane) and DB13155 (Esculin) as promising GRK5 inhibitors, warranting further in vitro and in vivo validation studies.

Understanding the impact of binding free energy and kinetics calculations in modern drug discovery

INTRODUCTION

For rational drug design, it is crucial to understand the receptor-drug binding processes and mechanisms. A new era for the use of computer simulations in predicting drug-receptor interactions at an atomic level has begun with remarkable advances in supercomputing and methodological breakthroughs.

AREAS COVERED

End-point free energy calculation methods such as Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) or Molecular-Mechanics/Generalized Born Surface Area (MM/GBSA), free energy perturbation (FEP), and thermodynamic integration (TI) are commonly used for binding free energy calculations in drug discovery. In addition, kinetic dissociation and association rate constants (k off and k on ) play critical roles in the function of drugs. Nowadays, Molecular Dynamics (MD) and enhanced sampling simulations are increasingly being used in drug discovery. Here, the authors provide a review of the computational techniques used in drug binding free energy and kinetics calculations.

EXPERT OPINION

The applications of computational methods in drug discovery and design are expanding, thanks to improved predictions of the binding free energy and kinetic rates of drug molecules. Recent microsecond-timescale enhanced sampling simulations have made it possible to accurately capture repetitive ligand binding and dissociation, facilitating more efficient and accurate calculations of ligand binding free energy and kinetics.

In Silico Search for Drug Candidates Targeting the PAX8-PPARγ Fusion Protein in Thyroid Cancer

The PAX8/PPARγ rearrangement, producing the PAX8-PPARγ fusion protein (PPFP), is thought to play an essential role in the oncogenesis of thyroid follicular tumors. To identify PPFP-targeted drug candidates and establish an early standard of care for thyroid tumors, we performed ensemble-docking-based compound screening. Specifically, we investigated the pocket structure that should be adopted to search for a promising ligand compound for the PPFP; the position of the ligand-binding pocket on the PPARγ side of the PPFP is similar to that of PPARγ; however, the shape is slightly different between them due to environmental factors. We developed a method for selecting a PPFP structure with a relevant pocket and high prediction accuracy for ligand binding. This method was validated using PPARγ, whose structure and activity values are known for many compounds. Then, we performed docking calculations to the PPFP for 97 drug or drug-like compounds registered in the DrugBank database with a thiazolidine backbone, which is one of the characteristics of ligands that bind well to PPARγ. Furthermore, the binding affinities of promising ligand candidates were estimated more reliably using the molecular mechanics Poisson-Boltzmann surface area method. Thus, we propose promising drug candidates for the PPFP with a thiazolidine backbone.

Identification of TBK1 inhibitors against breast cancer using a computational approach supported by machine learning

Introduction: The cytosolic Ser/Thr kinase TBK1 is of utmost importance in facilitating signals that facilitate tumor migration and growth. TBK1-related signaling plays important role in tumor progression, and there is need to work on new methods and workflows to identify new molecules for potential treatments for TBK1-affecting oncologies such as breast cancer. Methods: Here, we propose the machine learning assisted computational drug discovery approach to identify TBK1 inhibitors. Through our computational ML-integrated approach, we identified four novel inhibitors that could be used as new hit molecules for TBK1 inhibition. Results and Discussion: All these four molecules displayed solvent based free energy values of -48.78, -47.56, -46.78 and -45.47 Kcal/mol and glide docking score of -10.4, -9.84, -10.03, -10.06 Kcal/mol respectively. The molecules displayed highly stable RMSD plots, hydrogen bond patterns and MMPBSA score close to or higher than BX795 molecule. In future, all these compounds can be further refined or validated by in vitro as well as in vivo activity. Also, we have found two novel groups that have the potential to be utilized in a fragment-based design strategy for the discovery and development of novel inhibitors targeting TBK1. Our method for identifying small molecule inhibitors can be used to make fundamental advances in drug design methods for the TBK1 protein which will further help to reduce breast cancer incidence.

Unveiling MurE ligase potential inhibitors for treating multi-drug resistant Acinetobacter baumannii

Acinetobacter baumannii is an opportunistic pathogen with ability to cause serious infection such as bacteremia, ventilator associated pneumonia, and wound infections. As strains of A. baumannii are resistant to almost all clinically used antibiotics and with the emergence of carbapenems resistant phenotypes warrants the search for novel antibiotics. Considering this, herein, a series of computer aided drug designing approach was utilized to search novel chemical scaffolds that bind stronger to MurE ligase enzyme of A. baumannii, which is involved peptidoglycan synthesis. The work identified LAS_22461675, LAS_34000090 and LAS_51177972 compounds as promising binding molecules with MurE enzyme having binding energy score of -10.5 kcal/mol, -9.3 kcal/mol and -8.6 kcal/mol, respectively. The compounds were found to achieve docked inside the MurE substrate binding pocket and established close distance chemical interactions. The interaction energies were dominated by van der Waals and less contributions were seen from hydrogen bonding energy. The dynamic simulation assay predicted the complexes stable with no major global and local changes noticed. The docked stability was also validated by MM/PBSA and MM/GBSA binding free energy methods. The net MM/GBSA binding free energy of LAS_22461675 complex, LAS_34000090 complex and LAS_51177972 complex is -26.25 kcal/mol, -27.23 kcal/mol and -29.64 kcal/mol, respectively. Similarly in case of MM-PBSA, the net energy value was in following order; LAS_22461675 complex (-27.67 kcal/mol), LAS_34000090 complex (-29.94 kcal/mol) and LAS_51177972 complex (-27.32 kcal/mol). The AMBER entropy and WaterSwap methods also confirmed stable complexes formation. Further, molecular features of the compounds were determined that predicted compounds to have good druglike properties and pharmacokinetic favorable. The study concluded the compounds to good candidates to be tested by in vivo and in vitro experimental assays.Communicated by Ramaswamy H. Sarma.

Elucidation of protein-ligand interactions by multiple trajectory analysis methods

The identification of interaction between protein and ligand including binding positions and strength plays a critical role in drug discovery. Molecular docking and molecular dynamics (MD) techniques have been widely applied to predict binding positions and binding affinity. However, there are few works that describe the systematic exploration of the MD trajectory evolution in this context, potentially leaving out important information. To address the problem, we build a framework, Moira (molecular dynamics trajectory analysis), which enables automating the whole process ranging from docking, MD simulations and various analyses as well as visualizations. We utilized Moira to analyze 400 MD simulations in terms of their geometric features (root mean square deviation and protein-ligand interaction profiler) and energetics (molecular mechanics Poisson-Boltzmann surface area) for these trajectories. Finally, we demonstrate the performance of different analysis techniques in distinguishing native poses among four poses.

Harnessing Brazilian biodiversity database: identification of flavonoids as potential inhibitors of SARS-CoV-2 main protease using computational approaches and all-atom molecular dynamics simulation

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is the etiological agent responsible for the global outbreak of COVID-19 (Coronavirus Disease 2019). The main protease of SARS-CoV-2, Mpro, is a key enzyme that plays a vital role in mediating viral replication and transcription. In this study, a comprehensive computational approach was employed to investigate the binding affinity, selectivity, and stability of natural product candidates as potential new antivirals acting on the viral polyprotein processing mediated by SARS-CoV-2 Mpro. A library of 288 flavonoids extracted from Brazilian biodiversity was screened to select potential Mpro inhibitors. An initial filter based on Lipinski's rule of five was applied, and 204 compounds that did not violate any of the Lipinski rules were selected. The compounds were then docked into the active site of Mpro using the GOLD program, and the poses were subsequently re-scored using MM-GBSA (Molecular Mechanics Generalized Born Surface Area) binding free energy calculations performed by AmberTools23. The top five flavonoids with the best MM-GBSA binding free energy values were selected for analysis of their interactions with the active site residues of the protein. Next, we conducted a toxicity and drug-likeness analysis, and non-toxic compounds were subjected to molecular dynamics simulation and free energy calculation using the MM-PBSA (Molecular Mechanics Poisson-Boltzmann Surface Area) method. It was observed that the five selected flavonoids had lower MM-GBSA binding free energy with Mpro than the co-crystal ligand. Furthermore, these compounds also formed hydrogen bonds with two important residues, Cys145 and Glu166, in the active site of Mpro. Two compounds that passed the drug-likeness filter showed stable conformations during the molecular dynamics simulations. Among these, NuBBE_867 exhibited the best MM-PBSA binding free energy value compared to the crystallographic inhibitor. Therefore, this study suggests that NuBBE_867 could be a potential inhibitor against the main protease of SARS-CoV-2 and may be further examined to confirm our results.

Discovery of new antiviral agents through artificial intelligence: In vitro and in vivo results

In this research, we employed a deep reinforcement learning (RL)-based molecule design platform to generate a diverse set of compounds targeting the neuraminidase (NA) of influenza A and B viruses. A total of 60,291 compounds were generated, of which 86.5 % displayed superior physicochemical properties compared to oseltamivir. After narrowing down the selection through computational filters, nine compounds with non-sialic acid-like structures were selected for in vitro experiments. We identified two compounds, DS-22-inf-009 and DS-22-inf-021 that effectively inhibited the NAs of both influenza A and B viruses (IAV and IBV), including H275Y mutant strains at low micromolar concentrations. Molecular dynamics simulations revealed a similar pattern of interaction with amino acid residues as oseltamivir. In cell-based assays, DS-22-inf-009 and DS-22-inf-021 inhibited IAV and IBV in a dose-dependent manner with EC50 values ranging from 0.29 μM to 2.31 μM. Furthermore, animal experiments showed that both DS-22-inf-009 and DS-22-inf-021 exerted antiviral activity in mice, conferring 65 % and 85 % protection from IAV (H1N1 pdm09), and 65 % and 100 % protection from IBV (Yamagata lineage), respectively. Thus, these findings demonstrate the potential of RL to generate compounds with promising antiviral properties.

Deciphering Campylobacter jejuni DsbA1 protein dynamics in the presence of anti-virulent compounds: a multi-pronged computer-aided approach

The current study aims to evaluate Asinex library compounds against Campylobacter jejuni DsbA1 protein, a thiol disulfide oxidoreductase enzyme that plays a major role in the oxidative folding of bacterial virulence proteins, making it a promising anti-viral drug target. By employing several techniques of computer-aided drug design, BDC25697459, BDD33601083, and BDC30129064 were identified with binding energy scores of -8.8 kcal/mol, -8.8 kcal/mol, and -8.3 kcal/mol, respectively. However, the control molecule, tetraethylene glycol, exhibited a binding energy score of -7.0 kcal/mol. The control, BDD33601083, and BDC30129064 were unveiled to bind the same co-crystallized binding site (pocket 1), while BDC25697459 interacted with a new binding pocket (pocket 2) adjacent to the control binding region. The molecular dynamics simulation showed that complexes exhibit stable dynamics without significant global or residue-level fluctuations. The average RMSD values were in the range of 2.07 Å-2.45 Å. Similarly, mean RMSF was recorded between 1.30 and 1.42 Å. The C. jejuni DsbA1 was also observed as compact in the presence of the compounds, showing a mean RoG value in the range of 16.42 Å-16.55 Å. In terms of MM/PBSA binding energy, the BDC30129064 complex was ranked top with -44.88 ± 4.14 kcal/mol, whereas the positive control molecule exhibited -22.22 ± 3.33 kcal/mol. From a pharmacokinetic perspective, the compounds are suitable candidates for clinical trial investigation. Preliminary computational analysis of these virtual hits indicates that these compounds have a low potential for ADME and toxicity-associated liabilities. In summary, the compounds displayed a high affinity for the C. jejuni DsbA1 protein, indicating potential efficacy that requires further investigation.Communicated by Ramaswamy H. Sarma.

Exploration of human pancreatic alpha-amylase inhibitors from Physalis peruviana for the treatment of type 2 diabetes

Type 2 Diabetes (T2D), a chronic metabolic disorder characterized by persistent hyperglycemia, accounts for ∼90% of all types of diabetes. Pancreatic α-amylase is a potential drug target for preventing postprandial hyperglycemia and inhibiting T2D in humans. Although many synthetic drugs have been identified against pancreatic α-amylase, however, reported several side effects, and plant-derived natural products are less explored against T2D. This study tested 34 flavonoids derived from the plant Physalis peruviana against the human pancreatic α-amylase (HPA) using in silico computational approaches such as molecular docking and molecular dynamics simulation approaches. Schrödinger, a drug discovery package with modules applicable for molecular docking, protein-ligand interaction analysis, molecular dynamics, post-dynamics simulation, and binding free energy calculation, was employed for all computational studies. Four flavonoids, namely, Chlorogenic acid, Withaperuvin F, Withaperuvin H, and Rutin, were picked based on their docking score ranging between -7.03 kcal/mol and -11.35 kcal/mol compared to the docking score -7.3 kcal/mol of reference ligand, i.e. Myricetin. The molecular dynamics analysis suggested that all flavonoids showed considerable stability within the protein's catalytic pocket, except chlorogenic acid, which showed high deviation during the last 15 ns. However, the interactions observed in initial docking and extracted from the simulation trajectory involved > 90% identical residues, indicating the affinity and stability of the docked flavonoids with the protein. Therefore, all four compounds identified in this study are proposed as promising antidiabetic candidates and should be further considered for their in vitro and in vivo validation.Communicated by Ramaswamy H. Sarma.

Design of new chemical entities targeting both native and H275Y mutant influenza a virus by deep reinforcement learning

Influenza virus remains a major public health challenge due to its high morbidity and mortality and seasonal surge. Although antiviral drugs against the influenza virus are widely used as a first-line defense, the virus undergoes rapid genetic changes, resulting in the emergence of drug-resistant strains. Thus, new antiviral drugs that can outwit resistant strains are of significant importance. Herein, we used deep reinforcement learning (RL) algorithm to design new chemical entities (NCEs) that are able to bind to the native and H275Y mutant (oseltamivir-resistant) neuraminidases (NAs) of influenza A virus with better binding energy than oseltamivir. We generated more than 66211 NCEs, which were prioritized based on the filtering rules, structural alerts, and synthetic accessibility. Then, 18 NCEs with better MM/PBSA scores than oseltamivir were further analyzed in molecular dynamics (MD) simulations conducted for 100 ns. The MD experiments showed that 8 NCEs formed very stable complexes with the binding pocket of both native and H275Y mutant NAs of H1N1. Furthermore, most NCEs demonstrated much better binding affinity to group 2 (N2, N3, and N9) and influenza B virus NAs than oseltamivir. Although all 8 NCEs have non-sialic acid-like structures, they showed a similar binding mode as oseltamivir, indicating that it is possible to find new scaffolds with better binding and antiviral properties than sialic acid-like inhibitors. In conclusion, we have designed potential compounds as antiviral candidates for further synthesis and testing against wild and mutant influenza virus.Communicated by Ramaswamy H. Sarma.

Vaccinomics to design a multi-epitope-based vaccine against monkeypox virus using surface-associated proteins

In 2022, the ongoing multi-country outbreak of monkeypox virus-now occurring outside Africa, too is a global health concern. Monkeypox is a zoonotic virus, which causes disease mainly in animals, and then it is transferred to humans. Recently, in the monkeypox epidemic, a large number of human cases emerged while the global health community worked to tackle the outbreak and save lives. Herein, a multi-epitope-based vaccine is designed against monkeypox virus using two surface-associated proteins: MPXVgp002 accession number > YP_010377003.1 and MPXVgp008 accession number > YP_010377007.1 proteins. These proteins were utilized for B- and T-cell epitopes prediction. The epitopes were further screened, and the screen filtered KCKDNEYRSR, RSCNTTHNR, and RTRRETGAS with the antigenicity scores of 0.5279, 0.5604, and 0.7628, respectively. Overall, the epitopes can induce immunity in 99.74% population of the world. Further, GPGPG linkers were used for joining the epitopes and EAAAK linker was used for adjuvant attachment. It has a three-dimensional structure modelled for retaining the structural stability. Three pairs of amino acid residues that were able to make disulfide bonds were chosen: Gly1-Ser82, Cys7-Tyr10, and Phe51-Ile55. Molecular docking of vaccine was done with toll-like receptors, viz., 2, 3, 4, and 8 immune cell receptors. The docking results revealed that the vaccine as potential molecule due to its better binding affinity with toll-like receptors 2, 3, 4 and 8. Top complex in docking in with each receptor was selected based on lowest energy scores- -888.7 kcal/mol (TLR-2), -976.3 kcal/mol (TLR-3), -801.9 kcal/mol (TLR-4), and -955.4 kcal/mol (TLR-4)-were subjected to simulation. The docked complexes were evaluated in 500 ns of MD simulation. Throughout the simulation time, no significant deviation occurred. This confirmed that the vaccine as potential vaccine candidate to interact with immune cell receptors. This interaction is important for the immune system activation. In conclusion, the proposed vaccine construct against monkeypox could induce an effective immune response and speed up the vaccine development process. However, the study is completely based on the computational approach, hence, the experimental validation is required.Communicated by Ramaswamy H. Sarma.

Cheminformatics-based discovery of new organoselenium compounds with potential for the treatment of cutaneous and visceral leishmaniasis

Leishmaniasis affects more than 12 million humans globally and a further 1 billion people are at risk in leishmaniasis endemic areas. The lack of a vaccine for leishmaniasis coupled with the limitations of existing anti-leishmanial therapies prompted this study. Cheminformatic techniques are widely used in screening large libraries of compounds, studying protein-ligand interactions, analysing pharmacokinetic properties, and designing new drug molecules with great speed, accuracy, and precision. This study was undertaken to evaluate the anti-leishmanial potential of some organoselenium compounds by quantitative structure-activity relationship (QSAR) modeling, molecular docking, pharmacokinetic analysis, and molecular dynamic (MD) simulation. The built QSAR model was validated (R2train = 0.8646, R2test = 0.8864, Q2 = 0.5773) and the predicted inhibitory activity (pIC50) values of the newly designed compounds were higher than that of the template (Compound 6). The new analogues (6a, 6b, and 6c) showed good binding interactions with the target protein (Pyridoxal kinase, PdxK) while also presenting excellent drug-likeness and pharmacokinetic profiles. The results of density functional theory, MD simulation, and molecular mechanics generalized Born surface area (MM/GBSA) analyses suggest the favourability and stability of protein-ligand interactions of the new analogues with PdxK, comparing favourably well with the reference drug (Pentamidine). Conclusively, the newly designed compounds could be synthesized and tested experimentally as potential anti-leishmanial drug molecules.Communicated by Ramaswamy H. Sarma.

A Theobromine Derivative with Anticancer Properties Targeting VEGFR-2: Semisynthesis, in silico and in vitro Studies

A computer-assisted drug design (CADD) approach was utilized to design a new acetamido-N-(para-fluorophenyl)benzamide) derivative of the naturally occurring alkaloid, theobromine, (T-1-APFPB), following the pharmacophoric features of VEGFR-2 inhibitors. The stability and reactivity of T-1-AFPB were assessed through density functional theory (DFT) calculations. Molecular docking assessments showed T-1-AFPB's potential to bind with and inhibit VEGFR-2. The precise binding of T-1-AFPB against VEGFR-2 with optimal energy was further confirmed through several molecular dynamics (MD) simulations, PLIP, MM-GBSA, and PCA studies. Then, T-1-AFPB (4-(2-(3,7-Dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-1-yl)acetamido)-N-(4-fluorophenyl)benzamide) was semi-synthesized and the in vitro assays showed its potential to inhibit VEGFR-2 with an IC50 value of 69 nM (sorafenib's IC50 was 56 nM) and to inhibit the growth of HepG2 and MCF-7 cancer cell lines with IC50 values of 2.24±0.02 and 3.26±0.02 μM, respectively. Moreover, T-1-AFPB displayed very high selectivity indices against normal Vero cell lines. Furthermore, T-1-AFPB induced early (from 0.72 to 19.12) and late (from 0.13 to 6.37) apoptosis in HepG2 cell lines. In conclusion, the combined computational and experimental approaches demonstrated the efficacy and safety of T-1-APFPB providing it as a promising lead VEGFR-2 inhibitor for further development aiming at cancer therapy.

Lead identification against Mycobacterium tuberculosis using highly enriched active molecules against pantothenate synthetase

The Pantothenate synthetase (PS) from the Mycobacterium tuberculosis (Mtb) holds a crucial role in the survival and robust proliferation of bacteria through its catalysis of coenzyme A and acyl carrier protein synthesis. The present study undertook the PS drug target in complex with a co-crystallized ligand and subjected it to docking and virtual screening approaches. The experimental design encompassed three discrete datasets: an active dataset featuring 136 compounds, an inactive dataset comprising 56 compounds, and a decoys dataset curated from the zinc library, comprising an extensive compilation of approximately 53,000 compounds. The compounds' binding energies were observed to be in the range of -5 to ∼-14 kcal/mol. Additionally, binding energy results were further refined through Enrichment Factor analysis (EF). EF is a new statistical approach which uses the scores obtained from docking-based virtual screening and predicts the precision of the scoring function. Remarkably, the Enrichment Factor (EF) analysis produced exceptionally favorable outcomes, attaining an EF of approximately 49% within the uppermost 1% fraction of the compound distribution. Finally, a total of eight compounds, evenly distributed between the active dataset and the decoys dataset, emerged as potent inhibitors of the Pantothenate synthetase (PS) enzyme. The analysis of inhibition constants and binding energy revealed a notable correlation, with an r-squared value (r2) of 0.912 between the two parameters. Furthermore, the shortlisted compounds were subjected to 100 ns MD simulation to determine their stability and dynamics behavior. The decoy compounds that have been identified, exhibiting properties comparable to the active compounds, are postulated as potential candidates for targeting the Pantothenate synthetase (PS) enzyme to treat Mtb infection. Nevertheless, in the pursuit of a comprehensive investigation, it is advisable to undertake additional experimental validation as a component of the subsequent study.Communicated by Ramaswamy H. Sarma.

Identification of potent anti-Candida metabolites produced by the soft coral associated Streptomyces sp. HC14 using chemoinformatics

Candida albicans is the most common pathogen responsible for both spontaneous and recurrent candidiasis. The available treatment of Candida infections has several adverse effects, and the development of new drugs is critical. The current study looked at the synthesis of anti-Candida metabolites by Streptomyces sp. HC14 recovered from a soft coral. Using the Plackett Burman design, the medium composition was formulated to maximize production. Using GC-MS, the compounds have been identified, and a cheminformatics approach has been used to identify the potential source of activity. The compounds that showed high potential for activity were identified as pyrrolo[1,2-a]pyrazine-1,4-dione, hexahydro-3-(phenylmethyl)-3 and di-n-octyl based on their docking score against the cytochrome monooxygenase (CYP51) enzyme in Candida albicans. As a result of their discovery, fewer molecules need to be chemically synthesized, and fermentation optimization maximizes their synthesis, providing a strong foundation for the development of novel anti-Candida albicans agents.

A cheminformatics-biophysics correlate to identify promising lead molecules against matrix metalloproteinase-2 (MMP-2) enzyme: A promising anti-cancer target

Matrix metalloproteinase-2 (MMP-2) is an endopeptidase enzyme that is devoted to extracellular matrix proteins degradation. The enzyme is warranted as promising drugs target for different light threating diseases such as arthritis, cancer and fibrosis. Herein, in this study, three drug molecules: CMNPD8322, CMNPD8320, and CMNPD8318 were filtered as high affinity binding compounds with binding energy score of -9.75 kcal/mol, -9.11 kcal/mol, -9.05 kcal/mol, respectively. The control binding energy score was -9.01 kcal/mol. The compounds docked deeply inside the pocket interacting with S1 pocket residues. The docked complexes dynamics in real time at cellular environment was then done to decipher the stable binding conformation and intermolecular interactions network. The compounds complexes achieved very stable dynamics with root mean square deviation (RMSD) with mean value of around 2-3 Å compared to control complex that showed higher fluctuations of 5 Å. The simulation trajectories frames based binding free energy demonstrated all the compounds-MMP-2 complexes reported highly stable energy, particularly the van der Waals energy dominate the overall net energy. Similarly, the complexes revalidation of WaterSwap based energies also disclosed the complexes highly stable in term docked conformation. Also, the compounds illustrated the compounds favorable pharmacokinetics and were non-toxic and non-mutagenic. Thus, the compounds might be used thorough experimental assays to confirm compounds selective biological potency against MMP-2 enzyme.

A Multi-Enzyme Cascade for Efficient Production of Pyrrolidone from l-Glutamate

Pyrrolidone is a high value-added monomer and an important active drug intermediate. However, the efficient enzymatic synthesis of pyrrolidone remains a challenge. Here, we developed and reconstructed a three-enzyme cascade pathway using Escherichia coli BL21(DE3) for the production of pyrrolidone from l-glutamate (l-Glu). The carnitine-CoA ligase from Escherichia coli (EcCaiC) at a low expression level and with a low activity is regarded as the rate-limiting enzyme. Here, we obtained the best EcCaiCF380M/N430D double mutant with a kcat/Km value 1.5 times higher than that of the wild type via mechanism-based protein engineering. For this, we (i) eliminated the steric hindrance of the loop ring to improve the precatalytic conformation of the adenylation intermediate and (ii) fixed the hinge region to stabilize the closed conformation of the enzyme. Furthermore, ribosome-binding site (RBS) optimization led to an increase in the expression level of EcCaiCF380M/N430D, which was then cloned into the plasmid pET-EcCaiCF380M/N430D-DegoPPK2. Finally, under optimal induction and transformation conditions, 16.62 g/L of pyrrolidone was generated from 30 g/L l-Glu (batch feeding) within 24 h with a molar conversion rate of 95.2% and the highest productivity ever obtained, to our knowledge (0.69 g/L/h). Our findings demonstrate a strategy that is potentially attractive for the industrial production of pyrrolidone. IMPORTANCE This study developed a three-enzyme cascade pathway for the production of pyrrolidone from l-Glu. The catalytic efficiency of carnitine CoA ligase from Escherichia coli (EcCaiC) was improved by mechanism-based protein engineering, and the titer of pyrrolidone was further increased by ribosome-binding site (RBS), induction conditions, and conversion conditions optimization. Finally, we efficiently produced pyrrolidone by one pot in vivo with 95.2% conversion and 0.69 g/L/h productivity. Our study provides a new possibility for the industrial production of enzymatic synthesis of pyrrolidone.

Repurposing of FDA-approved drugs as dual-acting MAO-B and AChE inhibitors against Alzheimer's disease: An in silico and in vitro study

An in silico consensus molecular docking approach and in vitro evaluations were adopted in the present study to explore a dataset of FDA-approved drugs as novel multitarget MAO-B/AChE agents in the treatment of Alzheimer's disease (AD). GOLD 5.3 and Glide were employed in the virtual assessments and consensus superimpositions of the obtained poses were applied to increase the reliability of the docking protocols. Furthermore, the top ranked molecules were subjected to binding free energy calculations using MM/GBSA, Induced fit docking (IFD) simulations, and a literature review. Consequently, the top four multitarget drugs were examined for their in vitro MAO-B and AChE inhibition effects. The consensus molecular docking identified Dolutegravir, Rebamipide, Loracarbef and Diflunisal as potential multitarget drugs. The biological data demonstrated that most of the docking scores were in good correlation with the in vitro experiments, however the theoretical simulations in the active site of MAO-B identified two false-positives - Rebamipide and Diflunisal. Dolutegravir and Loracarbef were accessed as active MAO-B inhibitors, while Dolutegravir, Rebamapide and Diflunisal as potential AChE inhibitors. The antiretroviral agent Dolutegravir exhibited the most potent multitarget activity - 41% inhibition of MAO-B (1 μM) and 68% inhibition of AChE (10 μM). Visualizations of the intermolecular interactions of Dolutegravir in the active sites of MAO-B and AChE revealed the formation of several stable hydrogen bonds. Overall, Dolutegravir was identified as a potential anti-AD drug, however further in vivo evaluations should be considered.

Targeting Toxoplasma gondii ME49 TgAPN2: A Bioinformatics Approach for Antiparasitic Drug Discovery

As fewer therapeutic options are available for treating toxoplasmosis, newer antiparasitic drugs that can block TgAPN2 M1 aminopeptidase are of significant value. Herein, we employed several computer-aided drug-design approaches with the objective of identifying drug molecules from the Asinex library with stable conformation and binding energy scores. By a structure-based virtual screening process, three molecules—LAS_52160953, LAS_51177972, and LAS_52506311—were identified as promising candidates, with binding affinity scores of −8.6 kcal/mol, −8.5 kcal/mol, and −8.3 kcal/mol, respectively. The compounds produced balanced interacting networks of hydrophilic and hydrophobic interactions, vital for holding the compounds at the docked cavity and stable binding conformation. The docked compound complexes with TgAPN2 were further subjected to molecular dynamic simulations that revealed mean RMSD for the LAS_52160953 complex of 1.45 Å), LAS_51177972 complex 1.02 Å, and LAS_52506311 complex 1.087 Å. Another round of binding free energy validation by MM-GBSA/MM-PBSA was done to confirm docking and simulation findings. The analysis predicted average MM-GBSA value of <−36 kcal/mol and <−35 kcal/mol by MM-PBSA. The compounds were further classified as appropriate candidates to be used as drug-like molecules and showed favorable pharmacokinetics. The shortlisted compounds showed promising biological potency against the TgAPN2 enzyme and may be used in experimental validation. They may also serve as parent structures to design novel derivatives with enhanced biological potency.

Discovery of New Quinolone-Based Diarylamides as Potent B-RAFV600E/C-RAF Kinase Inhibitors Endowed with Promising In Vitro Anticancer Activity

The emergence of cancer resistance to targeted therapy represents a significant challenge in cancer treatment. Therefore, identifying new anticancer candidates, particularly those addressing oncogenic mutants, is an urgent medical demand. A campaign of structural modifications has been conducted to further optimize our previously reported 2-anilinoquinoline-diarylamides conjugate VII as a B-RAFV600E/C-RAF inhibitor. Considering the incorporation of a methylene bridge between the terminal phenyl and cyclic diamine, focused quinoline-based arylamides have been tailored, synthesized, and biologically evaluated. Among them, the 5/6-hydroxyquinolines 17b and 18a stood out as the most potent members, with IC₅₀ values of 0.128 µM, 0.114 µM against B-RAF^V600E, and 0.0653 µM, 0.0676 µM against C-RAF. Most importantly, 17b elicited remarkable inhibitory potency against the clinically resistant B-RAF^V600K mutant with an IC₅₀ value of 0.0616 µM. The putative binding mode of 17b and 18a were studied by molecular docking and molecular dynamics (MD). Moreover, the antiproliferative activity of all target compounds has been examined over a panel of NCI-60 human cancer cell lines. In agreement with cell-free assays, the designed compounds exerted superior anticancer impact over the lead quinoline VII against all cell lines at a 10 µM dose. Notably, both 17b and 18b showed highly potent antiproliferative activity against melanoma cell lines with growth percent under -90% (SK-MEL-29, SK-MEL-5, and UACC-62) at a single dose, while 17b maintained potency with GI₅₀ values of 1.60-1.89 µM against melanoma cell lines. Taken together, 17b, a promising B-RAF^V600E/V600K and C-RAF kinase inhibitor, may serve as a valuable candidate in the arsenal of anticancer chemotherapeutics.

Theoretical Studies on Selectivity of HPK1/JAK1 Inhibitors by Molecular Dynamics Simulations and Free Energy Calculations

Hematopoietic progenitor kinase 1 (HPK1) is a negative regulator of T cell receptor, which has been regarded as a potential target for immunotherapy. Yu et al. observed the off-target effect of the high-throughput screening HPK1 kinase inhibitor hits on JAK1 kinase. The off-target effect is usually due to the lack of specificity of the drug, resulting in toxic side effects. Therefore, exploring the mechanisms to selectively inhibit HPK1 is critical for developing effective and safe inhibitors. In this study, two indazole compounds as HPK1 inhibitors with different selectivity towards JAK1 were used to investigate the selectivity mechanism using multiple computational methods, including conventional molecular dynamics simulations, binding free energy calculations and umbrella sampling simulations. The results indicate that the salt bridge between the inhibitor and residue Asp101 of HPK1 favors their selectivity towards HPK1 over JAK1. Information obtained from this study can be used to discover and design more potent and selective HPK1 inhibitors for immunotherapy.

Proteome-Wide Screening of Potential Vaccine Targets against Brucella melitensis

The ongoing antibiotic-resistance crisis is becoming a global problem affecting public health. Urgent efforts are required to design novel therapeutics against pathogenic bacterial species. Brucella melitensis is an etiological agent of brucellosis, which mostly affects sheep and goats but several cases have also been reported in cattle, water buffalo, yaks and dogs. Infected animals also represent the major source of infection for humans. Development of safer and effective vaccines for brucellosis remains a priority to support disease control and eradication in animals and to prevent infection to humans. In this research study, we designed an in-silico multi-epitopes vaccine for B. melitensis using computational approaches. The pathogen core proteome was screened for good vaccine candidates using subtractive proteomics, reverse vaccinology and immunoinformatic tools. In total, 10 proteins: catalase; siderophore ABC transporter substrate-binding protein; pyridoxamine 5'-phosphate oxidase; superoxide dismutase; peptidylprolyl isomerase; superoxide dismutase family protein; septation protein A; hypothetical protein; binding-protein-dependent transport systems inner membrane component; and 4-hydroxy-2-oxoheptanedioate aldolase were selected for epitopes prediction. To induce cellular and antibody base immune responses, the vaccine must comprise both B and T-cells epitopes. The epitopes were next screened for antigenicity, allergic nature and water solubility and the probable antigenic, non-allergic, water-soluble and non-toxic nine epitopes were shortlisted for multi-epitopes vaccine construction. The designed vaccine construct comprises 274 amino acid long sequences having a molecular weight of 28.14 kDa and instability index of 27.62. The vaccine construct was further assessed for binding efficacy with immune cell receptors. Docking results revealed that the designed vaccine had good binding potency with selected immune cell receptors. Furthermore, vaccine-MHC-I, vaccine-MHC-II and vaccine-TLR-4 complexes were opted based on a least-binding energy score of -5.48 kcal/mol, 0.64 kcal/mol and -2.69 kcal/mol. Those selected were then energy refined and subjected to simulation studies to understand dynamic movements of the docked complexes. The docking results were further validated through MMPBSA and MMGBSA analyses. The MMPBSA calculated -235.18 kcal/mol, -206.79 kcal/mol, and -215.73 kcal/mol net binding free energy, while MMGBSA estimated -259.48 kcal/mol, -206.79 kcal/mol and -215.73 kcal/mol for TLR-4, MHC-I and MHC-II complexes, respectively. These findings were validated by water-swap and entropy calculations. Overall, the designed vaccine construct can evoke proper immune responses and the construct could be helpful for experimental researchers in formulation of a protective vaccine against the targeted pathogen for both animal and human use.

Structural Analysis, Multi-Conformation Virtual Screening and Molecular Simulation to Identify Potential Inhibitors Targeting pS273R Proteases of African Swine Fever Virus

The African Swine Fever virus (ASFV) causes an infectious viral disease in pigs of all ages. The development of antiviral drugs primarily aimed at inhibition of proteases required for the proteolysis of viral polyproteins. In this study, the conformation of the pS273R protease in physiological states were investigated, virtually screened the multi-protein conformation of pS273R target proteins, combined various molecular docking scoring functions, and identified five potential drugs from the Food and Drug Administration drug library that may inhibit pS273R. Subsequent validation of the dynamic interactions of pS273R with the five putative inhibitors was achieved using molecular dynamics simulations and binding free energy calculations using the molecular mechanics/Poison-Boltzmann (Generalized Born) (MM/PB(GB)SA) surface area. These findings demonstrate that the arm domain and Thr159-Lys167 loop region of pS273R are significantly more flexible compared to the core structural domain, and the Thr159-Lys167 loop region can serve as a "gatekeeper" in the substrate channel. Leucovorin, Carboprost, Protirelin, Flavin Mononucleotide, and Lovastatin Acid all have Gibbs binding free energies with pS273R that were less than -20 Kcal/mol according to the MM/PBSA analyses. In contrast to pS273R in the free energy landscape, the inhibitor and drug complexes of pS273R showed distinct structural group distributions. These five drugs may be used as potential inhibitors of pS273R and may serve as future drug candidates for treating ASFV.

Evaluation of interactions between the hepatitis C virus NS3/4A and sulfonamidobenzamide based molecules using molecular docking, molecular dynamics simulations and binding free energy calculations

The Hepatitis C Virus (HCV) NS3/4A is an attractive target for the treatment of Hepatitis C infection. Herein, we present an investigation of HCV NS3/4A inhibitors based on a sulfonamidobenzamide scaffold. Inhibitor interactions with HCV NS3/4A were explored by molecular docking, molecular dynamics simulations, and MM/PBSA binding free energy calculations. All of the inhibitors adopt similar molecular docking poses in the catalytic site of the protease that are stabilized by hydrogen bond interactions with G137 and the catalytic S139, which are known to be important for potency and binding stability. The quantitative assessments of binding free energies from MM/PBSA correlate well with the experimental results, with a high coefficient of determination, R2 of 0.92. Binding free energy decomposition analyses elucidate the different contributions of Q41, F43, H57, R109, K136, G137, S138, S139, A156, M485, and Q526 in binding different inhibitors. The importance of these sidechain contributions was further confirmed by computational alanine scanning mutagenesis. In addition, the sidechains of K136 and S139 show crucial but distinct contributions to inhibitor binding with HCV NS3/4A. The structural basis of the potency has been elucidated, demonstrating the importance of the R155 sidechain conformation. This extensive exploration of binding energies and interactions between these compounds and HCV NS3/4A at the atomic level should benefit future antiviral drug design.

In Silico Evaluation and In Vitro Determination of Neuroprotective and MAO-B Inhibitory Effects of Pyrrole-Based Hydrazones: A Therapeutic Approach to Parkinson's Disease

Parkinson's disease is a huge burden in modern medicinal practice. A serious drawback of current antiparkinsonian therapy is its symptomatic nature. This directed our investigations in the search for new more potent derivatives, affecting not only the loss of dopaminergic neurons but also the oxidative damage of neuronal cells. Thus in vitro neurotoxicity and neuroprotective analysis on a group of N-pyrrolyl hydrazide-hydrazones were performed. The neurotoxicity of the target derivatives was determined on a subcellular level in isolated rat synaptosomes, mitochondria and microsomes determining their effect on cellular vitality, GSH depletion and MDA production. The neuroprotective effects of the evaluated hydrazones were measured in three models of induced oxidative stress: 6-OHDA, t-BuOOH and Fe²⁺/AA-induced lipid peroxidation. Molecular docking simulations along with in vitro evaluation of MAO-B inhibitory potential of the target molecules were also performed. The results identified the ethyl 5-(4-bromophenyl)-1-(3-hydrazinyl-3-oxopropyl)-2-methyl-1H-pyrrole-3-carboxylate (12) as the most promising compound with the lowest neurotoxicity and highest neuroprotection on all evaluated parameters and inhibiting the hMAOB enzyme by 50%, comparable with the activity of the reference, Selegiline. The compatibility of the in silico and in vitro evaluations is a good prerequisite for these methods to be applied in future assessment of pyrrole-based compounds as anti-Parkinson agents.

Combination of ligand and structure based virtual screening approaches for the discovery of potential PARP1 inhibitors

Poly (ADP-ribose) polymerase 1 (PARP1) has high therapeutic value as biomolecular target for research and development of small molecules with antineoplastic activity, since it is upregulated in many cancers, especially in ovarian and BRCA 1/2 mutated breast cancers. Decades of investigation of PARP inhibitors (PARPi) have led to the approval of several drug compounds, however clinical application of PARPi in cancer therapy is limited due to a number of factors, including low selectivity, weak affinity and undesired side effects. Thus, identification of novel drug-like chemical compounds with alternatives to the known PARPi chemical scaffolds, binding modes and interaction patterns with amino acid residues in the active site is of high therapeutic importance. In this study we applied a combination of ligand- and structure-based virtual screening approaches with the goal of identification of novel potential PARPi.

A proteomics-MM/PBSA dual approach for the analysis of SARS-CoV-2 main protease substrate peptide specificity

The main protease M^pro of SARS-CoV-2 is a well-studied major drug target. Additionally, it has been linked to this virus' pathogenicity, possibly through off-target effects. It is also an interesting diagnostic target. To obtain more data on possible substrates as well as to assess the enzyme's primary specificity a two-step approach was introduced. First, Terminal Amine Isobaric Labeling of Substrates (TAILS) was employed to identify novel M^pro cleavage sites in a mouse lung proteome library. In a second step, using a structural homology model, the MM/PBSA variant MM/GBSA (Molecular Mechanics Poisson-Boltzmann/Generalized Born Surface Area) free binding energy calculations were carried out to determine relevant interacting amino acids. As a result, 58 unique cleavage sites were detected, including six that displayed glutamine at the P1 position. Furthermore, modeling results indicated that M^pro has a far higher potential promiscuity towards substrates than expected. The combination of proteomics and MM/PBSA modeling analysis can thus be useful for elucidating the specificity of M^pro, and thus open novel perspectives for the development of future peptidomimetic drugs against COVID-19, as well as diagnostic tools.

A New Insight into Toxicity of Colchicine Analogues by Molecular Docking Analysis Based on Intestinal Tight Junction Protein ZO-1

Colchicine (COL) is a well-known plant alkaloid long used for medical purposes due to the selective anti-inflammatory effect on acute gouty arthritis. It is also a kind of mitosis toxin with strong inhibitory effects of cell division and is therefore being applied to the treatment of various cancers. However, this product shows a variety of adverse effects that are significantly correlated with the dosage and have attracted much attention. For the first time, the present work obtained a new insight into the gastrointestinal toxicity of colchicine analogues by molecular docking analysis, which was based on the 3D structure of intestinal tight junction protein ZO-1 and the ligand library containing dozens of small-molecule compounds with the basic skeleton of COL and its metabolites. The binding energy and mode of protein–ligand interaction were investigated to better understand the structure–toxicity relationships of COL analogues and the mechanism of action as well. Cluster analysis clearly demonstrated the strong correlation between the binding energy and toxicity of ligand molecules. The interaction mode further revealed that the hydrogen bonding (via the C-7 amide or C-9 carbonyl group) and hydrophobic effect (at ring A or C) were both responsible for ZO-1-related gastrointestinal toxicity of COL analogues, while metabolic transformation via phase I and/or phase II reaction would significantly attenuate the gastrointestinal toxicity of colchicine, indicating an effective detoxication pathway through metabolism.

Computational methods and theory for ion channel research

Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.

Design, Synthesis and Anticancer Profile of New 4-(1H-benzo[d]imidazol-1-yl)pyrimidin-2-amine-Linked Sulfonamide Derivatives with V600EBRAF Inhibitory Effect

A new series of 4-(1H-benzo[d]imidazol-1-yl)pyrimidin-2-amine linked sulfonamide derivatives 12a–n was designed and synthesized according to the structure of well-established V600EBRAF inhibitors. The terminal sulfonamide moiety was linked to the pyrimidine ring via either ethylamine or propylamine bridge. The designed series was tested at fixed concentration (1 µM) against V600EBRAF, finding that 12e, 12i and 12l exhibited the strongest inhibitory activity among all target compounds and 12l had the lowest IC₅₀ of 0.49 µM. They were further screened on NCI 60 cancer cell lines to reveal that 12e showed the most significant growth inhibition against multiple cancer cell lines. Therefore, cell cycle analysis of 12e was conducted to investigate the effect on cell cycle progression. Finally, virtual docking studies was performed to gain insights for the plausible binding modes of vemurafenib, 12i, 12e and 12l.

Nitric Oxide Photo-Donor Hybrids of Ciprofloxacin and Norfloxacin: A Shift in Activity from Antimicrobial to Anticancer Agents

The potential anticancer effect of fluoroquinolone antibiotics has been recently unveiled and related to their ability to interfere with DNA topoisomerase II. We herein envisioned the design and synthesis of novel Ciprofloxacin and Norfloxacin nitric oxide (NO) photo-donor hybrids to explore the potential synergistic antitumor effect exerted by the fluoroquinolone scaffold and NO eventually produced upon light irradiation. Anticancer activity, evaluated on a panel of tumor cell lines, showed encouraging results with IC50 values in the low micromolar range. Some compounds displayed intense antiproliferative activity on triple-negative and doxorubicin-resistant breast cancer cell lines, paving the way for their potential use to treat aggressive, refractory and multidrug-resistant breast cancer. No significant additive effect was observed on PC3 and DU145 cells following NO release. Conversely, antimicrobial photodynamic experiments on both Gram-negative and Gram-positive microorganisms displayed a significant killing rate in Staphylococcus aureus, accounting for their potential effectiveness as selective antimicrobial photosensitizers.

Identification of non-classical hCA XII inhibitors using combination of computational approaches for drug design and discovery

Human carbonic anhydrase XII (hCA XII) isozyme is of high therapeutic value as a pharmacological target and biomarker for different types of cancer. The hCA XII is one of the crucial effectors that regulates extracellular and intracellular pH and affects cancer cell proliferation, invasion, growth and metastasis. Despite the fact that interaction features of hCAs inhibitors with the catalytic site of the enzyme are well described, lack in the selectivity of the traditional hCA inhibitors based on the sulfonamide group or related motifs is an urgent issue. Moreover, drugs containing sulfanomides can cause sulfa allergies. Thus, identification of novel non-classical inhibitors of hCA XII is of high priority and is currently the subject of a vast field of study. This study was devoted to the identification of novel potential hCA XII inhibitors using comprehensive set of computational approaches for drug design discovery: generation and validation of structure- and ligand-based pharmacophore models, molecular docking, re-scoring of virtual screening results with MMGBSA, molecular dynamics simulations, etc. As the results of the study several compounds with alternative to classical inhibitors chemical scaffolds, in particular one of coumarins derivative, have been identified and are of high interest as potential non-classical hCA XII inhibitors.