Evaluating the use of absolute binding free energy in the fragment optimization process.

Key to the fragment optimization process is the need to accurately capture the changes in affinity that are associated with a given set of chemical modifications. Due to the weakly binding nature of fragments, this has proven to be a challenging task, despite recent advancements in leveraging experimental and computational methods. In this work, we evaluate the use of Absolute Binding Free Energy (ABFE) calculations in guiding fragment optimization decisions, retrospectively calculating binding free energies for 59 ligands across 4 fragment elaboration campaigns. We first demonstrate that ABFEs can be used to accurately rank fragment-sized binders with an overall Spearman’s r of 0.89 and a Kendall τ of 0.67, although often deviating from experiment in absolute free energy values with an RMSE of 2.75 kcal/mol. We then also show that in several cases, retrospective fragment optimization decisions can be supported by the ABFE calculations. Cases that were not supported were often limited by large uncertainties in the free energy estimates, however generally the right direction in ΔΔG is still observed. Comparing against cheaper endpoint methods, namely Nwat-MM/GBSA, we find that ABFEs offer better outcomes in ranking binders, improving correlation metrics, although a similar confidence in retrospective synthetic decisions is achieved. Our results indicate that ABFE calculations are currently at the level of accuracy that can be usefully employed to gauge which fragment elaborations are likely to offer the best gains in affinity.

Binding free energies for the SAMPL8 CB8 “Drugs of Abuse” challenge from umbrella sampling combined with Hamiltonian replica exchange

Umbrella sampling along a one-dimensional order parameter in combination with Hamiltonian replica exchange was employed to calculate the binding free energy of five guest molecules with known affinity to cucurbit[8]uril. A simple empirical approach correcting for the overestimation of the affinity by the GAFF force field was proposed and subsequently applied to the seven guest molecules of the “Drugs of Abuse” SAMPL8 challenge. Compared to the uncorrected binding free energies, the systematic error decreased but quantitative agreement with experiment was only reached for a few compounds. From a retrospective analysis a weak point of the correction term was identified.

Metabolomic Analysis of Skin Malodor-Associated Compounds and Structure-based Prediction of Acetolactate Synthase Selective Sulfonylurea Inhibitors

Bromhidrosis is characterized as a chronic condition related to malodor from the skin. The underlying etiology is from bacterial decompositions of glandular secretion products. However, specific pathways and metabolites for the disease are yet to be investigated. Here, twenty-eight metabolites, including fifteen major sweat constituents and thirteen compounds emitted from malodor-producing skin bacteria, were subjected to the metabometric analysis using Metaboanalyst. Different pathways in the butanoate metabolism revealed that acetolactate synthase (ALS) in skin Staphylococcus epidermidis (S. epidermidis) bacteria are catalyzing pyruvate to several malodor compounds like diacetyl. In the docking studies of the sulfonylurea-ALS interaction, five selected sulfonylureas, which originally were developed for the treatment of diabetes mellitus type 2, showed different binding free energies (ΔG) from chlorimuron ethyl - a well-known ALS sulfonylurea inhibitor. Amongst five sulfonylureas, gliquidone and glisoxepide were found to have free energy differences that were lower than or equal to chlorimuron ethyl, revealing their high affinities to ALS. In the future, further investigations of gliquidone and glisoxepide against ALS in skin bacteria would be crucial in repurposing these two sulfonylureas as new anti-bromhidrosis drugs.

Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility

The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat myriad diseases. In this work we examine the computation of alchemical relative binding free energies with an eye to assessing reproducibility across popular molecular dynamics packages and free energy estimators. The focus of this work is on 54 ligand transformations from a diverse set of protein targets: MCL1, PTP1B, TYK2, CDK2 and thrombin. These targets are studied with three popular molecular dynamics packages: OpenMM, NAMD2 and NAMD3. Trajectories collected with these packages are used to compare relative binding free energies calculated with thermodynamic integration and free energy perturbation methods. The resulting binding free energies show good agreement between molecular dynamics packages with an average mean unsigned error between packages of 0.5 $kcal/mol$ The correlation between packages is very good with the lowest Spearman's, Pearson's and Kendall's tau correlation coefficient between two packages being 0.91, 0.89 and 0.74 respectively. Agreement between thermodynamic integration and free energy perturbation is shown to be very good when using ensemble averaging.

Mechanisms Underlying Gastrodin Alleviating Vincristine-Induced Peripheral Neuropathic Pain

Gastrodin (GAS) is the main bioactive ingredient of Gastrodia, a famous Chinese herbal medicine widely used as an analgesic, but the underlying analgesic mechanism is still unclear. In this study, we first observed the effects of GAS on the vincristine-induced peripheral neuropathic pain by alleviating the mechanical and thermal hyperalgesia. Further studies showed that GAS could inhibit the current density of NaV1.7 and NaV1.8 channels and accelerate the inactivation process of NaV1.7 and NaV1.8 channel, thereby inhibiting the hyperexcitability of neurons. Additionally, GAS could significantly reduce the over-expression of NaV1.7 and NaV1.8 on DRG neurons from vincristine-treated rats according to the analysis of Western blot and immunofluorescence results. Moreover, based on the molecular docking and molecular dynamic simulation, the binding free energies of the constructed systems were calculated, and the binding sites of GAS on the sodium channels (NaV1.7 and NaV1.8) were preliminarily determined. This study has shown that modulation of NaV1.7 and NaV1.8 sodium channels by GAS contributing to the alleviation of vincristine-induced peripheral neuropathic pain, thus expanding the understanding of complex action of GAS as a neuromodulator.

Identification of Novel Potential Anti-Diabetic Candidates targeting Human Pancreatic ɑ-Amylase and Human ɑ-Glycosidase: An Exhaustive Structure-based Screening

Diabetes is a major health issue that half a billion people affected worldwide. It is a serious, long-term medical condition majorly impacting the lives and well-being of individuals, families, and societies at large. It is amongst the top 10 diseases responsible for the death amongst adults with an expected rise to 10.2% (578 million) by 2030 and 10.9% (700 million) by 2045. The carbohydrates absorbed into the body are hydrolyzed by pancreatic α-amylase and other enzymes, human α-glucosidase. The α-amylase and α-glucosidase are validated therapeutic targets in the treatment of Type II diabetes (T2DM) as they play a vital role in modulating the blood glucose post meal. Herein, we report novel and diverse molecules as potential candidates, with predicted affinity for α-amylase and α-glucosidase. These molecules have been identified via hierarchical multistep docking of small molecules database with the estimated binding free energies. A Glide XP Score cutoff −8.00 kcal/mol was implemented to filter out non potential molecules. Four molecules viz. amb22034702, amb18105639, amb17153304, and amb9760832 have been identified after an exhaustive computational study involving, evaluation of binding interactions and assessment of the pharmacokinetics and toxicity profiles. The in-depth analysis of protein– ligand interactions was performed using a 100ns molecular dynamics (MD) simulation to establish the dynamic stability. Furthermore MM-GBSA based binding free energies were computed for 1000 trajectory snapshots to ascertain the strong binding affinity of these molecules for α-amylase and αglucosidase. The identified molecules can be considered as promising candidates for further drug development through necessary experimental assessments.

Omicron: A heavily mutated SARS-CoV-2 variant exhibits stronger binding to ACE2 and potently escape approved COVID-19 therapeutic antibodies

The new SARS-CoV-2 variant of concern “Omicron” was recently (Nov. 24th. 2021) spotted in South Africa and already spread around the world due to its enhanced transmissibility. The variant became conspicuous as it harbors more than thirty mutations in the spike protein with 15 mutations in the RBD region alone, potentially dampening the potency of therapeutic antibodies and enhancing the ACE2 binding. More worrying, Omicron infections have been reported in individuals who have received vaccines jabs in South Africa and Hong Kong. Here, we investigated the binding strength of Omicron with ACE2 and seven monoclonal antibodies that are either approved by FDA for COVID-19 therapy or undergoing phase III clinical trials. Computational mutagenesis and binding free energies could confirm that Omicron Spike binds ACE2 stronger than prototype SARS-CoV-2. Notably, three substitutions, i.e., T478K, Q493K, and Q498R, significantly contribute to the binding energies and doubled electrostatic potential of the RBDOmic-ACE2 complex. Instead of E484K substitution that helped neutralization escape of Beta, Gamma, and Mu variants, Omicron harbors E484A substitution. Together, T478K, Q493K, Q498R, and E484A substitutions contribute to a significant drop in the electrostatic potential energies between RBDOmic-mAbs, particularly in Etesevimab, Bamlanivimab, and CT-p59. CDR diversification could help regain the neutralization strength of these antibodies; however, we could not conduct this analysis to this end. Conclusively, our findings suggest that Omicron binds ACE2 with greater affinity, enhancing its infectivity and transmissibility. Mutations in the Spike are prudently devised by the virus that enhances the receptor binding and weakens the mAbs binding to escape the immune response.

In Silico Screening of Semi-Synthesized Compounds as Potential Inhibitors for SARS-CoV-2 Papain-Like Protease: Pharmacophoric Features, Molecular Docking, ADMET, Toxicity and DFT Studies

Papain-like protease is an essential enzyme in the proteolytic processing required for the replication of SARS-CoV-2. Accordingly, such an enzyme is an important target for the development of anti-SARS-CoV-2 agents which may reduce the mortality associated with outbreaks of SARS-CoV-2. A set of 69 semi-synthesized molecules that exhibited the structural features of SARS-CoV-2 papain-like protease inhibitors (PLPI) were docked against the coronavirus papain-like protease (PLpro) enzyme (PDB ID: (4OW0). Docking studies showed that derivatives 34 and 58 were better than the co-crystallized ligand while derivatives 17, 28, 31, 40, 41, 43, 47, 54, and 65 exhibited good binding modes and binding free energies. The pharmacokinetic profiling study was conducted according to the four principles of the Lipinski rules and excluded derivative 31. Furthermore, ADMET and toxicity studies showed that derivatives 28, 34, and 47 have the potential to be drugs and have been demonstrated as safe when assessed via seven toxicity models. Finally, comparing the molecular orbital energies and the molecular electrostatic potential maps of 28, 34, and 47 against the co-crystallized ligand in a DFT study indicated that 28 is the most promising candidate to interact with the target receptor (PLpro).

Pyrrolizine/Indolizine-NSAID Hybrids: Design, Synthesis, Biological Evaluation, and Molecular Docking Studies

In the current study, eight new hybrids of the NSAIDs, ibuprofen and ketoprofen with five pyrrolizine/indolizine derivatives were designed and synthesized. The chemical structures of these hybrids were confirmed by spectral and elemental analyses. The antiproliferative activities of these hybrids (5 μM) was investigated against MCF-7, A549, and HT-29 cancer cell lines using the cell viability assay, MTT assay. The results revealed 4–71% inhibition of the growth of the three cancer cell lines, where 8a,e,f were the most active. In addition, an investigation of the antiproliferative activity of 8a,e,f against MCF-7 cells revealed IC50 values of 7.61, 1.07, and 3.16 μM, respectively. Cell cycle analysis of MCF-7 cells treated with the three hybrids at 5 μM revealed a pro-apoptotic increase in cells at preG1 and cell cycle arrest at the G1 and S phases. In addition, the three hybrids induced early apoptotic events in MCF-7 cells. The results of the molecular docking of the three hybrids into COX-1/2 revealed higher binding free energies than their parent compounds 5a,c and the co-crystallized ligands, ibuprofen and SC-558. The results also indicated higher binding free energies toward COX-2 over COX-1. Moreover, analysis of the binding modes of 8a,e,f into COX-2 revealed partial superposition with the co-crystallized ligand, SC-558 with the formation of essential hydrogen bonds, electrostatic, or hydrophobic interactions with the key amino acid His90 and Arg513. The new hybrids also showed drug-likeness scores in the range of 1.06–2.03 compared to ibuprofen (0.65) and ketoprofen (0.57). These results above indicated that compounds 8a,e,f deserve additional investigation as potential anticancer candidates.

WaterSwap Analysis, a Computation-based Method for the Discovery of Effective and Stable Binding Compounds for Mutant EGFR Inhibition

The epidermal growth factor receptor of the tyrosine kinase family has been largely targeted in mutations associated with non-small cell lung cancer. EGFR inhibitors have been produced that bind allosterically to the C797S mutant EGFR enzyme. Here, the Waterswap tool has been used for the interpretation and visualization of trajectories of mutant EGFR-ligand complexes. Virtual screening of the generated compounds has been carried out along with its molecular docking and ADMET analysis. Out of the generated library of compounds, the top 15 have been selected. Waterswap calculated the binding free energies of the compounds and thermodynamic properties of the enumerated compounds were compared with that of standard EAI045. It was observed that styrylquinoline stabilized better than EAI045. The results show that Waterswap analysis offers a promising new path in the hunt for improved tools for analyzing and visualizing molecular driving forces in protein-ligand complex simulations.