An accurate free energy estimator: based on MM/PBSA combined with interaction entropy for protein-ligand binding affinity

Discovery of novel DdlA inhibitors in multidrug-resistant Pseudomonas aeruginosa using virtual screening, molecular docking, and dynamics simulations

Pseudomonas aeruginosa is a gram-negative, opportunistic pathogen that represents a serious risk factor in healthcare services due to its natural resistance mechanisms and the increasing prevalence of multi-drug resistant strains. This study utilized in silico computational approaches to identify the novel inhibitors for D-alanine-D-alanine ligase A (DdlA), an essential enzyme for the bacterial peptidoglycan biosynthesis pathway necessary for cell wall integrity. A structure-based virtual screening of The Medicinal Fungi Secondary Metabolites and Therapeutics (MeFSAT) chemical library was conducted, followed by molecular docking to evaluate the binding affinity of small molecules to the DdlA active site. MSID000191, MSID000200, and MSID000102 were recognized as the leading candidates in the preliminary docking data due to their low binding energy values. These compounds exhibited binding energies markedly superior to the control drug (D-cycloserine), suggesting a substantial potential for inhibiting the DdlA enzyme. Detailed interaction analyses revealed significant salt bridges and hydrogen bonds with active site residues, which enhance the stability of the complex. Density Functional Theory (DFT) analysis and MMPBSA calculations also provided insights into electronic properties and binding free energy, respectively. These findings highlight the potential of these inhibitors as therapeutic candidates and showcase the effectiveness of computational methods in accelerating drug discovery against multidrug-resistant P. aeruginosa. Future research should incorporate more in-silico techniques and experimental validations to confirm these results.

In silico approaches to identify novel anti-diabetic type 2 agents against dipeptidyl peptidase IV from isoxazole derivatives of usnic acid

Diabetes mellitus (DM) is a serious worldwide health issue in the twenty-first century. Additionally, DM, a metabolic endocrine illness that affects the digestion of proteins, carbohydrates, and lipids, has a death rate of 4.9 million individuals globally. This study aims to find anti-diabetic inhibitor for type 2 diabetes (T2D) that inhibits the dipeptidyl peptidase IV (DPP-IV) enzyme using in silico methods. From a range of published literature sources, thirty (30) isoxazole derivatives of UA (IDUA) were selected for this study. To ascertain the possible inhibitory effects of IDUA, ADMET, molecular docking, density functional theory analyses, molecular dynamic simulation and MM/PBSA were conducted. Eleven compounds (1, 2, 3, 4, 7, 13, 18, 21, 22, 24, and 27) were selected from the ADMET study, which were subjected to perform molecular docking against the DPP-IV enzyme of T2D, and findings indicated two compounds (compound 2 and compound 3) showed comparable binding affinity with the reference compound "Linagliptin". In contrast to the reference molecule, which had a binding affinity of - 8.6 kcal/mol against DPP-IV, compound 2 and compound 3 have binding affinities of - 8.1 and - 8.0 kcal/mol, respectively. Furthermore, based on Lipinski's Rule of Five, ELUMO, EHOMO, band energy gap, drug-likeness and DFT-based studies demonstrated druggability and high reactivity for these compounds. In addition, the molecular dynamic (MD) techniques to confirm that docked complexes remained stable and that the binding orientation obtained during docking tests were accurate. These compounds may be investigated in vitro and in vivo for the development of potential DPP-IV of T2D inhibitors.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-025-04287-5.

Enhancing MM/P(G)BSA Methods: Integration of Formulaic Entropy for Improved Binding Free Energy Calculations

Balancing computational efficiency and precision, MM/P(G)BSA methods have been widely employed in the estimation of binding free energies within biological systems. However, the entropy contribution to the binding free energy is often neglected in MM/P(G)BSA calculations, due to the computational cost of conventional methods such as normal mode analysis (NMA). In this work, the entropy effect using a formulaic entropy can be computed from one single structure according to variations in the polar and non-polar solvents accessible surface areas and the count of rotatable bonds in ligands. It was incorporated into MM/P(G)BSA methods to enhance their performance. Extensive benchmarking reveals that the integration of formulaic entropy systematically elevates the performance of both MM/PBSA and MM/GBSA without incurring additional computational expenses. In addition, we found the inclusion of dispersion can deteriorate the correlation performance (Rp) but reduce the root mean square error (RMSE) of both MM/PBSA and MM/GBSA. Notably, MM/PBSA_S, including the formulaic entropy but excluding the dispersion, surpasses all other MM/P(G)BSA methods across a spectrum of datasets. Our investigation furnishes a valuable and practical MM/P(G)BSA method, optimizing binding free energy calculations for a variety of biological systems.

Computer-Aided Design and Pharmacophore-Based Screening of a Diverse Combinatorial Library of Phytoselective Aryloxyacetic Acid Derivatives as HPPD Inhibitors

We investigated the inhibitory potency of aryloxyacetic acid derivatives (AADs) on 4-hydroxyphenylpyruvate dioxygenase (HPPD), a crucial enzyme target for HPPD herbicide development. Developing a wide-ranging approach combining reported structure-activity relationships (SARs with the observed inhibitory potencies of the enzyme Kiexp), our simulations for molecular mechanics Poisson-Boltzmann (MM-PB) complexation quantitative SAR (QSAR) (computed relative Gibbs free energies of the HPPD-AADx complex formation ΔΔGcom), and three-dimensional (3D)-QSAR pharmacophore (PH4) models for screening the chemical subspace of aryloxyacetic acid derivatives (a virtual library of AADs, VL), we come out with a handful of novel AADs with promising predictive HPPD inhibitory potency and confirmed molecular dynamics (MD) conformational stability. The 3D-QSAR model revealed a correlation (pKiexp = a × ΔΔGcom + b) between computed data and observed inhibition ones: pKiexp = -0.0544 × ΔΔGcom + 6.93, R2 = 0.87 for a training set (TS) of 30 AAD (AAD1-30). The subsequent 3D-QSAR pharmacophore (PH4) of HPPD inhibition by AADs confirmed the correlation (pKiexp = 0.863 × pKipre + 7.92, R2 = 0.86) between PH4-predicted pKipre and the observed ones pKiexp. The structural information derived from these models suggested suitable substituents for building a virtual library (VL) of AAD analogues representing a chemical subspace of 79,500 compounds to be PH4-screened in search of more potent inhibitors; the best predicted Kipre of them reached 40 pM. Finally, the good stability of the AtHPPD-AADx complex and the flexibility of the active conformation of the inhibitor for selected top-ranked AAD analogues were checked with the help of molecular dynamics (MD, 200 ns runs). This computational study proposed a set of new predicted potent inhibitors with herbicidal effects.

Identification and Characterization of the Structure and Size of Aβ42 Oligomers Targeting the Receptor FcγRIIb

Kam and colleagues discovered that FcγRIIb can specifically bind to Aβ42 oligomers (AβOs). The N-terminal residues F4 and D7 of Aβ42, as well as the W115 residue in domain D2 of FcγRIIb, are involved in this binding. However, the specificity of the FcγRIIb receptor's binding sites for AβOs and their dependence on different AβO species, including dimers (D/DT), trimers (T/TT), tetramers (Te/TeT), and pentamers (P/PT) during both the primary (P1) and secondary nucleation phases (P2), remains unknown. To address this, we employed molecular dynamics (MD) simulations to investigate the interactions between the extracellular domains D1 and D2 (FDD) of FcγRIIb and AβOs of varying sizes in the two different phases. We discovered that three specific fragments (f1, f2, and f3) of domain D2 in FDD are the primary binding sites for AβO species. Furthermore, among AβOs of the same molecular weight, those from the P2 phase exhibit a stronger binding affinity for FDD than those from the P1 phase. The distinction is ascribed to the stronger dependence on the hydrophobic residues in the β1 and β2 regions for the binding of AβOs in P2 (including TT, TeT, and PT) than that (including D, Te, and P) in the P1 phase. In the P1 phase, these AβOs prefer to achieve binding to FDD through their N-terminal residues; however, by this, we identified that the species observed in Kam's experiment to bind FcγRIIb should probably be the tetrameric AβO (Te) in the P1 phase. Moreover, within both the P1 and P2 phases, we predicted that the trimeric AβO species in either the P1 or P2 phase is the strongest binding ligand for the FcγRIIb receptor. This study provides a comprehensive molecular perspective on the interaction between FcγRIIb and AβO in P2, which is of significant importance for the development of therapeutic strategies targeting Alzheimer's disease (AD) and autoimmune diseases.

Novel carbazole-thiadiazole derivatives as α-amylase and α-glucosidase inhibitors: Design, biological evaluation, and computational insights

Diabetes mellitus remains a global health challenge, demanding innovative therapeutic solutions. Herein, we present the design, synthesis, and pharmacological evaluation of a novel series of carbazole-thiadiazole hybrids targeting key enzymes in carbohydrate metabolism. Among the synthesized compounds, 5l emerged as the most potent inhibitor of α-amylase, with an IC50 value of 0.68 µM-far surpassing the efficacy of the standard drug acarbose (IC50: 5.19 µM). Similarly, 5r exhibited exceptional dual activity against both α-amylase and α-glucosidase, with IC50 values of 1.63 µM and 0.14 µM, respectively, highlighting its dual inhibitory potential. Biological assays demonstrated the compounds' low cytotoxicity on hepatic stellate (LX-2) cells, affirming their safety for therapeutic use. Molecular docking studies provided mechanistic insights into their binding interactions, revealing strong hydrogen bonding and hydrophobic interactions with key active site residues. Density functional theory (DFT) and electrostatic potential (ESP) analyses further elucidated their electronic properties, offering a deeper understanding of their structure-activity relationships. Pharmacokinetic profiling via the BOILED-Egg model confirmed these derivatives' excellent oral bioavailability and drug-likeness. Collectively, these findings establish carbazole-thiadiazole hybrids as promising candidates for next-generation antidiabetic therapies, warranting further investigation in preclinical and clinical settings.

GPCR oligomerization across classes: A2AR-mediated regulation of mGlu5R activation

The adenosine A2A receptor (A2AR), a class A GPCR, is a known player in neurological diseases, including Parkinson's disease and Alzheimer's disease, and is also implicated in SARS-CoV-2 infection. Recent studies have revealed its oligomerization with metabotropic glutamate receptor type 5 (mGlu5R), a class C G protein coupled receptor (GPCR) that exists in the homodimeric form. Simultaneous activation of both receptors synergistically enhances mGlu5R-mediated effects in the hippocampus. Despite their importance, the molecular mechanisms governing these interactions remain unclear. In this study, we used molecular modelling techniques, including molecular docking, extensive molecular dynamics (MD) simulations, and detailed analysis, to elucidate the interactions between mGlu5R and A2AR in the inactive and active states. Our findings provide molecular-level insights into the permissive role of A2AR in mGlu5R activation, demonstrating that the inactive A2AR interface within the oligomer blocks the mGlu5R transmembrane helix 6 (TM6), which is crucial for activation. Upon A2AR activation, the oligomer interface undergoes conformational rearrangement, exposing mGlu5R-TM6 and allowing for mGlu5R activation. Furthermore, we identified a pivotal role of the mGlu5R-TM4:A2AR-TM4 interface in facilitating mGlu5R activation. These results highlight the intricate architecture of the mGlu5R:A2AR oligomer, advancing our understanding of GPCR oligomerization and its regulatory mechanisms on receptor activity.

Allosteric site engagement and cooperativity mechanism by PHI1 for BRAFV600E kinase inhibition

With the ability to reveal allosteric sites, Ponatinib and Ponatinib Hybrid Inhibitor 1 (PHI1) are novel inhibitors of BRAF, a potent oncogene that activates the MAPK pathway. PHI1 also exhibits unique positive cooperativity, with enhanced inhibition on the other monomer when one monomer of the BRAFV600E dimer bound to an inhibitor. The abovementioned properties lack rigorous theoretical verification, so this study compared the interaction mechanisms of four inhibitor types and explored the source of the cooperativity of PHI1 via various computational methods. Results revealed that residues on the αC-helix formed hydrogen bonds with inhibitors, shifting the position of the αC-helix. PHI1 induced binding pocket contraction through contact with allosteric sites. Entropy contributions were considerably weakened when both BRAFV600E monomers were occupied, thereby increasing the binding ability of PHI1, indicating that entropy contributions were the main source of PHI1 cooperativity. The change in overall motion intensity tightened the binding pocket, increasing the binding abilities of hotspot residues, including Arg575 and Leu567. Moreover, three key hydrogen bonds formed between PHI1 and BRAFV600E in the dimer system were conducive to the binding. The insights derived from this study are expected to advance the development of inhibitors targeting BRAFV600E kinase.

Exploring the effect of L-theanine synergised with EGCG on starch digestibility in ultrasonic field from different perspectives

With the increasing prevalence of diabetes, the search for natural compounds with potential anti-hyperglycemic effects has become a key focus in food and nutrition research. L-theanine (THE) and epigallocatechin gallate (EGCG) from tea are gaining attention due to their antioxidant and metabolic regulation properties. Although they have been shown to have an effect on glucose metabolism, their synergistic effect on starch digestive properties and the mechanism remain unclear. Here, we explored that THE and EGCG synergistically regulated starch digestive properties in ultrasound treatment through two different perspectives. At specific THE/EGCG ratios (THE/EGCG1:1), maize starch granules exhibited significant aggregation and densification. THE promoted the ordered arrangement of starch molecular chains through hydrogen bonding, and the polyphenolic structure of EGCG further stabilised this ordered structure, thus enhancing the crystallinity and short-range ordering of starch. It meant that THE and EGCG further reduced starch digestibility by synergistically modulating the multi-scale structure of starch. In addition, THE and EGCG exhibited significant synergistic inhibition of α-amylase activity (1.6 mM THE and 0.05 mg/mL EGCG). The multi-spectral results showed that the addition of THE and EGCG enhanced the conformational change of the enzyme, leading to the change of the secondary structure, and the synergistic effect might originate from the multiple interactions of THE and EGCG with different amino acid residues in the digestive enzyme (e.g., THR-163, GLN-63, ASP-197, etc), which strengthened the inhibition, and the molecular dynamics simulations further supported the findings. This work promotes the further development and utilisation of endogenous substances in tea and provides some references for the development of food ingredients with potential hypoglycaemic functions.

Next-Generation Carbazole-Linked 1,2,4-Triazole-Thione Derivatives: Strategic Design, Synthesis, Molecular Docking, and Evaluation of Antidiabetic Potential

Currently, available therapies for diabetes cannot achieve normal sugar values in a high percentage of treated patients. This work synthesized a series of carbazole-triazole-thione derivatives, and their potential antidiabetic activity was investigated against the key diabetic enzymes α-amylase and glycosidase. Normal human hepatic stellate cells (LX-2) were employed to assess their cytotoxicity and safety, followed by in vivo testing to investigate the hypoglycemic effect of the most promising agent. As a result, a set of 18 carbazole-1,2,4-triazole-thione derivatives were synthesized. Seven structures demonstrated potential inhibitory activity against α-amylase enzyme, with IC50 lower than 6.4 μM. Among them, compounds C5f, C5o, and C5r exhibited the highest potency, with IC50 values of 0.56, 0.53, and 0.97 μM, respectively, compared to the well-known α-amylase inhibitor acarbose, which has an IC50 value of 5.31 μM. Exploring the inhibition potency of these series against α-glucosidase enzyme revealed that C5f and C5r compounds act as moderate inhibitors, with IC50 values of 11.03 and 13.76 μM, respectively. Moreover, at 100 μM concentration, most of the evaluated compounds showed negligible cytotoxic effect against LX-2 cell lines, particularly compounds C5o and C5s, that demonstrated lower cytotoxic activity by 3-fold compared to the positive control 5-Flururicle (cell viability 13.45%). Thus, the C5f compound was selected for in vivo evaluation, and after administering five doses of this compound (10 mg/kg) to group III of mice, a significant reduction in glucose concentration was observed, bringing it down from 290.54 to 216.15 mg/dL, in comparison with the control group which did not show a reduction in blood glucose level. These observed in vitro and in vivo results were upheld by performing a set of chemoinformatic studies that elucidated the binding interactions of the most active derivatives within the enzyme's active site and highlighted the critical roles of both the 1,2,4-triazole-3-thione and carbazole scaffolds in these interactions. Finally, the drug-likeness profiles of our carbazole-triazole-thione derivatives suggest their potential as candidates for further in vivo studies and clinical trials.

From Implicit to Explicit: An Interaction-Reorganization Approach to Molecular Solvation Energy

Accurate calculation of solvation energies has long fascinated researchers, but complex interactions within bulk water molecules pose significant challenges. Currently, molecular solvation energy calculations are mostly based on implicit solvent approximations in which the solvent molecules are treated as continuum dielectric media. However, the implicit solvent approach is not ideal because it lacks certain real solvation effects, such as that of the first solvation shell, etc. Here, we propose an explicit solvent approach, interaction-reorganization solvation (IRS) method, for molecular solvation energy calculations. The IRS approach achieves predictive accuracy comparable to that of the widely recognized solvation model based on the density (SMD) method and is significantly more accurate than that of the Poisson-Boltzmann/generalized Born surface area (PB/GBSA) methods. This is demonstrated in both the correlation coefficient and the mean absolute error (MAE) with respect to the experimental data. The IRS method is based on molecular dynamics simulation in explicit solvent and does not need to solve Poisson-Boltzmann or Schrödinger equations. On the other hand, the accuracy of the IRS method does depend on the accuracy of the molecular force field used in MD simulations. We expect that the IRS method will be very useful for the solvation energy calculations of molecules.

Enhancing plant-based cheese formulation through molecular docking and dynamic simulation of tocopherol and retinol complexes with zein, soy and almond proteins via SVM-machine learning integration

The current study addresses the growing demand for sustainable plant-based cheese alternatives by employing molecular docking and deep learning algorithms to optimize protein-ligand interactions. Focusing on key proteins (zein, soy, and almond protein) along with tocopherol and retinol, the goal was to improve texture, nutritional value, and flavor characteristics via dynamic simulations. The findings demonstrated that the docking analysis presented high accuracy in predicting conformational changes. Flexible docking algorithms provided insights into dynamic interactions, while analysis of energetics revealed variations in binding strengths. Tocopherol exhibited stronger affinity (-5.8Kcal/mol) to zein compared to retinol (-4.1Kcal/mol). Molecular dynamics simulations offered comprehensive insights into stability and behavior over time. The integration of machine learning algorithms improved the classification and the prediction accuracy, achieving a rate of 71.59%. This study underscores the significance of molecular understanding in driving innovation in the plant-based cheese industry, facilitating the development of sustainable alternatives to traditional dairy products.

Structural Reorganization Mechanism of the Aβ42 Fibril Mediated by N-Substituted Oligopyrrolamide ADH-353

The inhibition of amyloid-β (Aβ) fibrillation and clearance of Aβ aggregates have emerged as a potential pharmacological strategy to alleviate Aβ aggregate-induced neurotoxicity in Alzheimer's disease (AD). Maity et al. shortlisted ADH-353 from a small library of positively charged N-substituted oligopyrrolamides for its notable ability to inhibit Aβ fibrillation, disintegrate intracellular cytotoxic Aβ oligomers, and alleviate Aβ-induced cytotoxicity in the SH-SY5Y and N2a cells. However, the molecular mechanism through which ADH-353 interacts with the Aβ42 fibrils, leading to their disruption and subsequent clearance, remains unclear. Thus, a detailed molecular mechanism underlying the disruption of neurotoxic Aβ42 fibrils (PDB ID 2NAO) by ADH-353 has been illuminated in this work using molecular dynamics simulations. Interestingly, conformational snapshots during simulation depicted the shortening and disappearance of β-strands and the emergence of a helix conformation, indicating a loss of the well-organized β-sheet-rich structure of the disease-relevant Aβ42 fibril on the incorporation of ADH-353. ADH-353 binds strongly to the Aβ42 fibril (ΔGbinding= -142.91 ± 1.61 kcal/mol) with a notable contribution from the electrostatic interactions between positively charged N-propylamine side chains of ADH-353 with the glutamic (Glu3, Glu11, and Glu22) and aspartic (Asp7 and Asp23) acid residues of the Aβ42 fibril. This aligns well with heteronuclear single quantum coherence NMR studies, which depict that the binding of ADH-353 with the Aβ peptide is driven by electrostatic and hydrophobic contacts. Furthermore, a noteworthy decrease in the binding affinity of Aβ42 fibril chains on the incorporation of ADH-353 indicates the weakening of interchain interactions leading to the disruption of the double-horseshoe conformation of the Aβ42 fibril. The illumination of key interactions responsible for the destabilization of the Aβ42 fibril by ADH-353 in this work will greatly aid in designing new chemical scaffolds with enhanced efficacy for the clearance of Aβ aggregates in AD.

Molecular Insights into the Binding and Conformational Changes of Hepcidin25 Blood Peptide with 4-Aminoantipyrine and Their Sorption Mechanism by Carboxylic-Functionalized Multiwalled Carbon Nanotubes: A Comprehensive Spectral Analysis and Molecular Dynamics Simulation Study

In this work, the main purpose is to analyze and understand the mechanism and thermodynamic interactions of carboxylic acid-functionalized multiwalled carbon nanotubes (cf-MWCNTs) and 4-aminoantipyrine (AAP) with human hepcidine25 (Hep25) using multispectroscopic and molecular docking modeling methods, binding free energy calculations, and molecular dynamics (MD) simulations under physiological conditions. AAP belongs to a class of persistent environmental contaminants, and its residue is a potential hazard to human health, exhibiting a high binding affinity with blood peptides. Hepcidin is a 25-residue peptide hormone with four disulfide bonds that regulates the iron balance in vertebrates and contributes to host immunity as a cysteine-rich antimicrobial peptide. Due to their diverse properties and pollutant absorption capabilities, CNTs demonstrate important biological effects in biological applications, particularly in the noncovalent interactions with blood peptides. A comprehensive molecular dynamics simulation integrated with molecular docking methodologies was employed to explore the binding free energy between AAP and Hep25, identify binding sites, elucidate thermodynamic characteristics, and evaluate the binding forces governing their interaction. The investigation delved into elucidating the precise binding site of AAP within the Hep25 protein and thoroughly analyzed the impact of AAP on the microenvironment and conformational dynamics of Hep25. The circular dichroism (CD) experimental results highlight a reduction in β-sheet composition following the introduction of AAP and cf-MWCNT. In addition, outcomes from fluorescence spectroscopy demonstrate that both cf-MWCNT and AAP significantly attenuated Hep-25 fluorescence via a static quenching mechanism. According to the MD simulations, the presence of AAP induces changes in the secondary structure of Hep25 and enhances its hydrophobicity. Additionally, our findings demonstrated that alongside the alteration in protein structure and functionality induced by contaminants, cf-MWCNTs possess the capability to mitigate the contaminant-induced effects on Hep25 activity while preserving the overarching structural integrity of Hep25. Based on the distance and RDF data, we found that during the simulation the presence of the cf-MWCNT causes the AAP to move away from the Hep25, and as a result fewer and weaker interactions of the AAP with the Hep25 will be observed. Likewise, free energy calculations indicate that the binding of Hep25 to AAP and cf-MWCNT involves electrostatic, π-cationic, and π-π stacking interactions. The research findings offer invaluable insights into the intricate influence of pollutants and carbon nanotubes on protein functionality within the circulatory system and their toxicity in vivo for prospective investigations.

Pharmacological mechanism of quercetin in the treatment of colorectal cancer by network pharmacology and molecular simulation

Colorectal cancer is a serious threat to people's life due to its high incidence and high mortality. Quercetin can effectively treat colorectal carcinoma (CRC), but its exact mechanism of action is still unclear. Then quercetin-related target genes were obtained from Swiss Target Prediction database and Similarity Ensemble Approach (SEA) database, and CRC-related target genes were obtained from GeneCards database, respectively. Common target genes were obtained by FunRich software. String software was used to construct a protein-protein interaction (PPI) network. R package was used for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking, molecular dynamics (MD) simulation and post-dynamics simulation were used to explore the binding stability of quercetin to key targets. In total, 103 and 141 target information of quercetin were obtained from the Swiss Target Prediction database and SEA database, respectively. 1,649 CRC-related genes were obtained from GeneCards database. FunRich software was used to draw venny map and obtain 36 intersection targets of quercetin and CRC. String software was used to construct the PPI network. The core genes were AKT1, EGFR, MMP9, KDR, MET and PTK2. There were 532 items related to biological processes, 14 items related to cellular components, and 43 items related to molecular functions among the key target GO enrichment items. KEGG enrichment pathways of key targets involved cancer pathways, PI3K-Akt signal pathway, etc. The results of molecular docking, MD simulation and post-dynamics simulation showed they had a good affinity and formed a stable effect. So quercetin may play an important role in the treatment of CRC by acting on AKT1, EGFR, MMP9, KDR, MET and PTK2 to affect the development of CRC.Communicated by Ramaswamy H. Sarma.

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.

Computational investigation on the binding modes of PET polymer to PETase

Poly(ethylene terephthalate) (PET) has been widely utilized in daily life, but its non-degradability has induced severe environmental and health problems. Recently, PETase, which has been isolated from bacterium Ideonella sakaiensisis, was reported to have the highest PET degradation activity and specificity under room temperature, but no crystal structure for PET in complex with PETase has been reported. To provide deep insight into the binding mode of PET polymer on PETase and the binding interactions, we employed molecular docking and molecular dynamics simulations to study the substrate binding at the atomic level. Different PET oligomers have been studied with chain lengths varying from 2 to 8. In addition, the binding energies and hot-spot residues were analyzed to gain better insights into the binding mechanism by MM/GBSA approach. The PET oligomers adopt stable and reactive conformations in a shallow cleft on a flat surface of PETase. The binding cleft can only accommodate four moieties, and others beyond the region will be stabilized by the π-stacking interactions with Trp156 at the terephthalic acid terminal. Our studies provide a clear picture of how the binding mode of PET polymer and its interactions with PETase change with the chain length. Those studies would provide useful information for the rational design of catalytically more efficient PETase variants toward plastic degradation.Communicated by Ramaswamy H. Sarma.

Analytic and In Silico Methods to Understand the Interactions between Dinotefuran and Haemoglobin

This work lies in the growing concern over the potential impacts of pesticides on human health and the environment. Pesticides are extensively used to protect crops and control pests, but their interaction with essential biomolecules like haemoglobin (Hb) remains poorly understood. Spectrofluorometric, electrochemical, and in silico investigations have been chosen as potential methods to delve into this issue, as they offer valuable insights into the molecular-level interactions between pesticides and haemoglobin. The research aims to address the gaps in knowledge and contribute to developing safer and more sustainable pesticide practices. The interaction was studied by spectroscopic techniques (UV-Visible & Fluorescence), in silico studies (molecular docking & molecular dynamics simulations) and electrochemical techniques (cyclic voltammetry and tafel). The studies showed effective binding of dinotefuran with the Hb which will cause toxicity to human. The formation of a stable molecular complex between ofloxacin and Haemoglobin was shown via molecular docking and the binding energy was found to be -5.37 kcal/mol. Further, molecular dynamics simulations provide an insight for the stability of the complex (Hb-dinotefuran) for a span of 250 ns with a binding free energy of -53.627 kJ/mol. Further, cyclic voltammetry and tafel studies show the interaction of dinotefuran with Hb effectively.

Lactoferrin's role in modulating NF-κB pathway to alleviate diabetes-associated inflammation: A novel in-silico study

Lactoferrin (LF), a multifunctional glycoprotein found in mammalian milk and various exocrine secretions, plays a pivotal role in modulating various responses. Lactoferrin plays a significant role in type-2 diabetes by improving hepatic insulin resistance and pancreatic dysfunction however, the exact mechanism for this improvement is not thoroughly elucidated. To this date, there are no evidence that attributes the direct interaction of lactoferrin with components of NF-κB pathway. Considering this precedent, the current study aimed to investigate the interaction of LF with key components of NF-κB pathway using molecular docking and simulation approaches. Results indicated that LF has shown highly stable interactions with IL-1β, IL-6, IκBα and NF-κB, and relatively weaker interactions with IKK and TNF-α. All four trajectories, including root mean square of deviations (RMSD), root mean square of fluctuation (RMSF), hydrogen bond interactions, and radius of gyration (RoG), confirmed the stable interactions of LF with NF-κB pathway components. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis further supports their stable interactions. To the best of our knowledge, this is the first study to provide convincing evidence that LF can interact with all six major components of the NF-κB pathway. This study provides pioneering in-silico evidence that lactoferrin (LF) can interact with all six major components of the NF-κB pathway, demonstrating highly stable interactions with IL-1β, IL-6, IκBα, and NF-κB, and relatively weaker interactions with IKK and TNF-α. These findings suggest that LF and its peptides have significant potential for both preventive and therapeutic applications by targeting the NF-κB pathway to inhibit inflammation, thereby improving insulin sensitivity and aiding in the management of diabetes.

Insight into the Binding Interaction between PEDCs and hERRγ Utilizing Molecular Docking and Molecular Dynamics Simulations

Phenolic environmental endocrine-disrupting chemicals (PEDCs) are persistent EDCs that are widely found in food packaging materials and environmental media and seriously threaten human health and ecological security. Human estrogen-related receptor γ (hERRγ) has been proposed as a mediator for the low-dose effects of many environmental PEDCs; however, the atomic-level descriptions of dynamical structural features and interactions of hERRγ and PEDCs are still unclarified. Herein, how three PEDCs, 4-(1-methylpropyl)phenol (4-sec-butylphenol), 5,6,7,8-tetrahydro-2-naphthol (tetrahydro-2-napthol), and 2,2-bis(4-hydroxy-3,5-dimethoxyphenyl)propane (BP(2,2)(Me)), interact with hERRγ to produce its estrogenic disruption effects was studied. Molecular docking and multiple molecular dynamics (MD) simulations were first conducted to distinguish the detailed interaction pattern of hERRγ with PEDCs. These binding structures revealed that residues around Leu271, Leu309, Leu345, and Phe435 are important when binding with PEDCs. Furthermore, the binding energies of PEDCs with hERRγ were also characterized using the molecular mechanics/Poisson Boltzmann surface area (MM-PBSA) and solvated interaction energy (SIE) methods, and the results showed that the interactions of CH-π, π-π, and hydrogen bonds are the major contributors for hERRγ binding to these three PEDCs. What is striking is that the methoxide groups of BP(2,2)(Me), as hydrophobic groups, can help to reduce the binding energy of PEDCs binding with hERRγ. These results provide important guidance for further understanding the influence of PEDCs on human health problems.

Specific interaction from different Aβ42 peptide fragments to α7nAChR-A study of molecular dynamics simulation

CONTEXT

Existing researches confirmed that β amyloid (Aβ) has a high affinity for the α7 nicotinic acetylcholine receptor (α7nAChR), associating closely to Alzheimer's disease. The majority of related studies focused on the experimental reports on the neuroprotective role of Aβ fragment (Aβx), however, with a lack of investigation into the most suitable binding region and mechanism of action between Aβ fragment and α7nAChR. In the study, we employed four Aβ1-42 fragments Aβx, Aβ1-16, Aβ10-16, Aβ12-28, and Aβ30-42, of which the first three were confirmed to play neuroprotective roles upon directly binding, to interact with α7nAChR.

METHODS

The protein-ligand docking server of CABS-DOCK was employed to obtain the α7nAChR-Aβx complexes. Only the top α7nAChR-Aβx complexes were used to perform all-atom GROMACS dynamics simulation in combination with Charmm36 force field, by which α7nAChR-Aβx interactions' dynamic behavior and specific locations of these different Aβx fragments were identified. MM-PBSA calculations were also done to estimate the binding free energies and the different contributions from the residues in the Aβx. Two distinct results for the first three and fourth Aβx fragments in binding site, strength, key residue, and orientation, account for why the fourth fails to play a neuroprotective role at the molecular level.

Exploring transmembrane allostery in the MexB: DB08385 variant as a promising inhibitor-like candidate against Pseudomonas aeruginosa antibiotic resistance: a computational study

Pseudomonas aeruginosa, a formidable pathogen renowned for its antimicrobial resistance, poses a significant threat to immunocompromised individuals. In this regard, the MexAB-OprM efflux pump acts as a pivotal line of defense by extruding antimicrobials from bacterial cells. The inner membrane homotrimeric protein MexB captures antibiotics and translocates them into the outer membrane OprM channel protein connected through the MexA adaptor protein. Despite extensive efforts, competitive inhibitors targeting the tight (T) protomer of the MexB protein have not received FDA approval for medical use. Over the past few years, allosteric inhibitors have become popular as alternatives to the classical competitive inhibitor-based approach because of their higher specificity, lower dosage, and reduced toxicological effects. Hence, in this study, we unveiled the existence of a transmembrane allosteric binding pocket of MexB inspired by the recent discovery of an important allosteric inhibitor, BDM88855, for the homolog AcrB protein. While repurposing BDM88855 proved ineffective in controlling the MexB loose (L) protomer, our investigation identified a promising alternative: a chlorine-containing variant of DB08385 (2-Cl DB08385 or Variant 1). Molecular dynamics simulations, including binding free energy estimation coupled with heterogeneous dielectric implicit membrane model (implicit-membrane MM/PBSA), interaction entropy (IE) analysis and potential of mean force (PMF) calculation, demonstrated Variant 1's superior binding affinity to the transmembrane pocket, displaying the highest energy barrier in the ligand unbinding process. To elucidate the allosteric crosstalk between the transmembrane and porter domain of MexB, we employed the 'eigenvector centrality' measure in the linear mutual information obtained from the protein correlation network. Notably, this study confirmed the presence of an allosteric transmembrane site in the MexB L protomer. In addition to this, Variant 1 emerged as a potent regulator of allosteric crosstalk, inducing an 'O-L intermediate state' in the MexB L protomer. This induced state might hold the potential to diminish substrate intake into the access pocket, leading to the ineffective efflux of antibiotics.

Synthesis of R-GABA Derivatives via Pd(II) Catalyzed Enantioselective C(sp3)-H Arylation and Virtual Validation with GABAB1 Receptor for Potential leads

GABA (γ-amino butyric acid) analogues like baclofen, tolibut, phenibut, etc., are well-known GABAB1 inhibitors and pharmaceutically important drugs. However, there is a huge demand for more chiral GABA aryl analogues with promising pharmacological actions. Here, we demonstrate the chiral ligand acetyl-protected amino quinoline (APAQ) mediated enantioselective synthesis of GABAB1 inhibitor drug scaffolds from easily accessible GABA via Pd-catalyzed C(sp3)-H activation. The synthetic methodology shows moderate to good yields, up to 74% of ee. We have successfully demonstrated the deprotection and removal of the directing group to synthesize R-tolibut in 86% yield. Further, we employed computation to probe the binding of R-GABA analogues to the extracellular domain of the human GABAB1 receptor. Our Rosetta-based molecular docking calculations show better binding for four R-enantiomers of GABA analogues than R-baclofen and R-phenibut. In addition, we employed GROMACS MD simulations and MMPB(GB)SA calculations to identify per-residue contribution to binding free energy. Our computational results suggest analogues (3R)-4-amino-3-(3,4-dimethylphenyl) butanoic acid, (3R)-4-amino-3-(3-fluorophenyl) butanoic acid, (3R)-3-(4-acetylphenyl)-4-aminobutanoic acid, (3R)-4-amino-3-(4-methoxyphenyl) butanoic acid, and (3R)-4-amino-3-phenylbutanoic acid are potential leads which could be synthesized from our methodology reported here.

Evaluating mAbs binding abilities to Omicron subvariant RBDs: implications for selecting effective mAb therapies

The ongoing evolution of the Omicron lineage of SARS-CoV-2 has led to the emergence of subvariants that pose challenges to antibody neutralization. Understanding the binding dynamics between the receptor-binding domains (RBD) of these subvariants spike and monoclonal antibodies (mAbs) is pivotal for elucidating the mechanisms of immune escape and for advancing the development of therapeutic antibodies. This study focused on the RBD regions of Omicron subvariants BA.2, BA.5, BF.7, and XBB.1.5, employing molecular dynamics simulations to unravel their binding mechanisms with a panel of six mAbs, and subsequently analyzing the origins of immune escape from energetic and structural perspectives. Our results indicated that the antibody LY-COV1404 maintained binding affinities across all studied systems, suggesting the resilience of certain antibodies against variant-induced immune escape, as seen with the mAb 1D1-Fab. The newly identified mAb 002-S21F2 showed a similar efficacy profile to LY-COV1404, though with a slightly reduced binding to BF.7. In parallel, mAb REGN-10933 emerged as a potential therapeutic candidate against BF.7 and XBB.1.5, reflecting the importance of identifying variant-specific antibody interactions, akin to the binding optimization observed in BA.4/5 and XBB.1.5. And key residues that facilitate RBD-mAb binding were identified (T345, L441, K444, V445, and T500), alongside residues that hinder protein-protein interactions (D420, L455, K440, and S446). Particularly noteworthy was the inhibited binding of V445 and R509 with mAbs in the presence of mAb 002-S21F2, suggesting a mechanism for immune escape, especially through the reduction of V445 hydrophobicity. These findings enhance our comprehension of the binding interactions between mAbs and RBDs, contributing to the understanding of immune escape mechanisms. They also lay the groundwork for the design and optimization of antiviral drugs and have significant implications for the development of treatments against current and future coronaviruses.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

In silico investigation of falcipain-2 inhibition by hybrid benzimidazole-thiosemicarbazone antiplasmodial agents: A molecular docking, molecular dynamics simulation, and kinetics study

The emergence of artemisinin-resistant variants of Plasmodium falciparum necessitates the urgent search for novel antimalarial drugs. In this regard, an in silico study to screen antimalarial drug candidates from a series of benzimidazole-thiosemicarbazone hybrid molecules with interesting antiplasmodial properties and explore their falcipain-2 (FP2) inhibitory potentials has been undertaken herein. FP2 is a key cysteine protease that degrades hemoglobin in Plasmodium falciparum and is an important biomolecular target in the development of antimalarial drugs. Pharmacokinetic properties, ADMET profiles, MM/GBSA-based binding free energies, reaction mechanisms, and associated barrier heights have been investigated. DFT, molecular dynamics simulation, molecular docking, and ONIOM methods were used. From the results obtained, four 4N-substituted derivatives of the hybrid molecule (E)-2-(1-(5-chloro-1H-benzo[d]imidazol-2-yl)ethylidene)hydrazine-1-carbothioamide (1A) denoted 1B, 1C, 1D, and 1E are drug-like and promising inhibitors of FP2, exhibiting remarkably small inhibitory constants (5.94 × 10-14 - 2.59 × 10-04 n M) and favorable binding free energies (-30.32 to -17.17 kcal/mol). Moreover, the ONIOM results have revealed that 1B and possibly 1C and 1D may act as covalent inhibitors of FP2. The rate-determining step of the thermodynamically favorable covalent binding mechanism occurs across a surmountable barrier height of 24.18 kcal/mol in water and 28.42 kcal/mol in diethyl ether. Our findings are useful for further experimental investigations on the antimalarial activities of the hybrid molecules studied.

Discovery of Tetrazolamide-benzimidazol-2-ones as Novel 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors

4-Hydroxyphenylpyruvate dioxygenase (HPPD, EC 1.13.11.27) is one of the most valuable herbicide targets due to its unique biological functions. In search of HPPD inhibitors with promising biological performance, we designed and synthesized a series of novel tetrazolamide-benzimidazol-2-ones using a structure-based drug design strategy. Among the synthesized compounds, 1-(2-chlorobenzyl)-3-methyl-N-(1-methyl-1H-tetrazol-5-yl)-2-oxo-2,3-dihydro-1H-benzo[d]imidazole-4-carboxamide, 25, IC50 = 10 nM, was identified to be the most outstanding HPPD inhibitor, which showed more than 36-fold increased Arabidopsis thaliana HPPD (AtHPPD) inhibition potency than mesotrione (IC50 = 363 nM). Our AtHPPD-25 complex indicated that one nitrogen atom on the tetrazole ring and the oxygen atom on the amide group formed a classical bidentate chelation interaction with the metal ion, the benzimidazol-2-one ring created a tight π-π stacking interaction with Phe381 and Phe424, and some hydrophobic interactions were also found between the ortho-Cl-benzyl group and surrounding residues. Compound 32 showed more than 80% inhibition against all four tested weeds at 150 g ai/ha by the postemergence application. Our results indicated that the tetrazolamide-benzimidazol-2-one scaffold may be a new lead structure for herbicide discovery.

A hierarchical approach towards identification of novel inhibitors against L, D-transpeptidase YcbB as an anti-bacterial therapeutic target

The bacterial cell wall, being a vital component for cell viability, is regarded as a promising drug target. The L, D-Transpeptidase YcbB enzyme has been implicated for a significant role in cell wall polymers cross linking during typhoid toxin release, β-lactam resistance and outer membrane defect rescue. These observations have been recorded in different bacterial pathogens such as Salmonella Typhimurium, Citrobacter rodentium, and Salmonella typhi. In this work, we have shown structure based virtual screening of diverse natural and synthetic drug libraries against the enzyme and revealed three compounds as LAS_32135590, LAS_34036730 and LAS-51380924. These compounds showed highly stable energies and the findings are very competitive with the control molecule ((1RG or (4 R,5S)-3-({(3S,5S)-5-[(3-carboxyphenyl)carbamoyl]pyrrolidin-3-yl}sulfanyl)-5-[(1S,2R)-1-formyl-2-hydroxypropyl]-4-methyl-4,5-dihydro-1H-pyrrole-2-carboxylic acid or ertapenem)) used. Compared to control (which has binding energy score of -11.63 kcal/mol), the compounds showed better binding energy. The binding energy score of LAS_32135590, LAS_34036730 and LAS-51380924 is -12.63 kcal/mol, -12.22 kcal/mol and -12.10 kcal/mol, respectively. Further, the docked snapshot of the lead compounds and control were investigated for stability under time dependent dynamics environment. All the three leads complex and control system showed significant equilibrium (mean RMSD < 3 Å) both in term of intermolecular docked conformation and binding interactions network. Further validation on the complex's stability was acquired from the end-state MMPB/GBSA analysis that observed greater contribution from van der Waals forces and electrostatic energy while less contribution was noticed from solvation part. The compounds were also showed good drug-likeness and are non-toxic and non-mutagenic. In short, the compounds can be used in experimental testing's and might be subjected to structure modification to get better results.

Exploring protein-ligand binding affinity prediction with electron density-based geometric deep learning

Rational structure-based drug design relies on accurate predictions of protein-ligand binding affinity from structural molecular information. Although deep learning-based methods for predicting binding affinity have shown promise in computational drug design, certain approaches have faced criticism for their potential to inadequately capture the fundamental physical interactions between ligands and their macromolecular targets or for being susceptible to dataset biases. Herein, we propose to include bond-critical points based on the electron density of a protein-ligand complex as a fundamental physical representation of protein-ligand interactions. Employing a geometric deep learning model, we explore the usefulness of these bond-critical points to predict absolute binding affinities of protein-ligand complexes, benchmark model performance against existing methods, and provide a critical analysis of this new approach. The models achieved root-mean-squared errors of 1.4-1.8 log units on the PDBbind dataset, and 1.0-1.7 log units on the PDE10A dataset, not indicating significant advantages over benchmark methods, and thus rendering the utility of electron density for deep learning models context-dependent. The relationship between intermolecular electron density and corresponding binding affinity was analyzed, and Pearson correlation coefficients r > 0.7 were obtained for several macromolecular targets.

Investigating the complexation propensity of self-assembling dipeptides with the anticancer peptide-drug Bortezomib: a computational study

The investigation of potential self-assembled peptides as carriers for the delivery of anticancer drug Bortezomib is the topic of the present study. The self-assembly of Bortezomib in water is examined using all-atom molecular dynamics simulations and corresponding experimental results from FESEM experiments. In addition, a series of dipeptides with a similar chemical formula to Bortezomib with hydrogel-forming ability are being investigated for their propensity to bind to the drug molecule. Dipeptides are divided into two classes, the protected FF (Fmoc-FF and Z-FF) and the LF-based (Cyclo-LF and LF) ones. The thermodynamic stability of the complexes formed in an aqueous environment, as well as key morphological features of the nanoassemblies are investigated at the molecular level. Binding enthalpy between Bortezomib and dipeptides follows the increasing order: LF < Cyclo-LF < Fmoc-FF < Z-FF under both van der Waals and electrostatic contributions. Protected FF dipeptides have a higher affinity for the drug molecule, which will favor its entrapment, giving them an edge over the LF based dipeptides. By evaluating the various measures, regarding both the binding between the two components and the eventual ability of controlled drug release, we conclude that the protected FF class is a more suitable candidate for drug release of Bortezomib, whereas among its two members, Fmoc-FF appears to be more promising. The selection of the optimal candidates based on the present computational study will be a stepping stone for future detailed experimental studies involving the encapsulation and controlled release of Bortezomib both in vitro and in vivo.

Identification of new pentapeptides as potential inhibitors of amyloid-β42 aggregation using virtual screening and molecular dynamics simulations

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease mainly characterized by extracellular accumulation of amyloid-β (Aβ) peptide. Previous studies reported pentapeptide RIIGL as an effective inhibitor of Aβ aggregation and neurotoxicity induced by Aβ aggregates. In this work, a library of 912 pentapeptides based on RIIGL has been designed and assessed for their efficacy to inhibit Aβ42 aggregation using computational techniques. The top hit pentapeptides revealed by molecular docking were further assessed for their binding affinity with Aβ42 monomer using MM-PBSA (molecular mechanics Poisson-Boltzmann surface area) method. The MM-PBSA analysis identified RLAPV, RVVPI, and RIAPA, which bind to Aβ42 monomer with a higher binding affinity -55.80, -46.32, and -44.26 kcal/mol, respectively, as compared to RIIGL (ΔGbinding = -41.29 kcal/mol). The residue-wise binding free energy predicted hydrophobic contacts between Aβ42 monomer and pentapeptides. The secondary structure analysis of the conformational ensembles generated by molecular dynamics (MD) depicted remarkably enhanced sampling of helical and no β-sheet conformations in Aβ42 monomer on the incorporation of RVVPI and RIAPA. Notably, RVVPI and RIAPA destabilized the D23-K28 salt bridge in Aβ42 monomer, which plays a crucial role in Aβ42 oligomer stability and fibril formation. The MD simulations highlighted that the incorporation of proline and arginine in pentapeptides contributed to their strong binding with Aβ42 monomer. Furthermore, RVVPI and RIAPA prevented conformational conversion of Aβ42 monomer to aggregation-prone structures, which, in turn, resulted in a lower aggregation tendency of Aβ42 monomer.

Systemic computational investigation to identify potential inhibitors against cancer by targeting P21-activated kinase 4 and D(CGATCG)

Cancer accounts for more than 10 million deaths in the year 2020. Development of drugs that specifically target cancer signaling pathways and proteins attain significant importance in the recent past. The p21-activated kinase 4 enzyme, which plays diverse functions in cancer and is reported in elevated expression makes this enzyme an attractive anti-cancer drug target. Similarly, cancer cells' DNA could also serve as a good platform for anti-cancer drug development. Herein, a robust in silico framework is designed to virtually screen multiple drug libraries from diverse sources to identify potential binders of the mentioned cancer targets. The virtual screening process identified three compounds (BAS_01059603, ASN_10027856, and ASN_06916672) as best docked molecules with a binding energy score of ≤ -10 kcal/mol for p21-activated kinase 4 and ≤ -6 kcal/mol for D(CGATCG). In the docking analysis, the filtered compounds revealed stable binding to the same site to which controls bind in X-ray structures. The binding interactions of the compounds with receptors are dominated by van der Waals interactions. The average root mean square deviation (rmsd) value for p21-activated kinase 4 systems is noticed at ∼2 Å, while for D(CGATCG), the average rmsd is 2.7 Å. The MMGB/PBSA interpreted ASN_12674021 to show strong intermolecular binding energy compared to the other two systems and control in both receptors. Moreover, the entropy energy contribution is less than the mean binding energy. In short, the compounds are showing promising binding to the biomolecules and therefore must be evaluated for anti-cancer activity in experimental studies.Communicated by Ramaswamy H. Sarma.

DFT, ADME studies and evaluation of the binding with HSA and MAO-B inhibitory potential of protoberberine alkaloids from Guatteria friesiana: theoretical insights of promising candidates for the treatment of Parkinson's disease

CONTEXT

Parkinson's disease is a chronic neurodegenerative condition that has no cure, characterized by the progressive degeneration of specific brain cells responsible for producing dopamine, a crucial neurotransmitter for controlling movement and muscle coordination. Parkinson's disease is estimated to affect around 1% of the world's population over the age of 60, but it can be diagnosed at younger ages. One of the treatment strategies for Parkinson's disease involves the use of drugs that aim to increase dopamine levels or simulate the action of dopamine in the brain. A class of commonly prescribed drugs are the so-called monoamine oxidase B (MAO-B) inhibitors due to the fact that this enzyme is responsible for metabolizing dopamine, thus reducing its levels in the brain. Studies have shown that berberine-derived alkaloids have the ability to selectively inhibit MAO-B activity, resulting in increased dopamine availability in the brain. In this context, berberine derivatives 13-hydroxy-discretinine and 7,8-dihydro-8-hydroxypalmatine, isolated from Guatteria friesiana, were evaluated via density functional theory followed by ADME studies, docking and molecular dynamic simulations with MAO-B, aiming to evaluate their anti-Parkinson potential, which have not been reported yet. Docking simulations with HSA were carried out aiming to evaluate the transport of these molecules through the circulatory system.

METHODS

The 3D structures of the berberine-derived alkaloids were modeled via the DFT approach at B3LYP-D3(BJ)/6-311 + + G(2df, 2pd) theory level using Gaussian 09 software. Solvation free energies were determined through Truhlar's solvation model. MEP and ALIE maps were generated with Multiwfn software. Autodock Vina software was used for molecular docking simulations and analysis of the interactions in the binding sites. The 3D structure of MAO-B was obtained from the Protein Data Bank website under PDB code 2V5Z. For the interaction of studied alkaloids with human serum albumin (HSA) drug sites, 3D structures with PDB codes 2BXD, 2BXG, and 4L9K were used. Molecular dynamics simulations were carried out using GROMACS 2019.4 software, with the GROMOS 53A6 force field at 100 ns simulation time. The estimation of the ligand's binding free energies was obtained via molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method.

Identification and characterization of the conformation and size of amyloid-β (42) oligomers targeting the receptor LilrB2

Experimental observations revealed that the amyloid-β 42 oligomer (AβO) can directly bind to the LilrB2 D1D2(LDD) receptor with nanomolar-affinity, leading to changes in synaptic plasticity and cognitive deficits. However, the dependence of neurotoxicity on the morphology, size, and aggregation stage (SP1, SP2) of AβO, as well as the specific molecular mechanism of AβO-LDD interaction, remain uncertain. To address these uncertainties, we investigated the interaction between the LDD neuroreceptor and AβO with different Aβ42 species (nontoxic species, toxic species, and protofibril) and sizes. Our results showed that the LDD selectively binds AβO species rather than the Aβ42 monomer, accommodating various Aβ42 dimers and trimers as well as SP2 AβO, in a specific pose in the pocket of the LDD receptor (region I). Additionally, protofibrils with exposed β1/β2 regions can also bind to region I of the LDD receptor, as observed experimentally (Cao, et al., Nat. Chem., 2018, 10, 1213; and Aim et al., Nat. Commun., 2021, 12, 3451). More extensively, we identified two additional regions of the LDD receptor, regions II and III, suitable for binding to larger AβO species at the SP1 with different molecular weights and conformations, accounting for the stronger binding strength obtained experimentally. We suggest that the two regions are more competitive than region I in causing toxicity by AβO binding. The detailed and systematic characterization for the complexes generated between the LDD receptor and various AβO species, including the protofibril, offers deep insight into the dependence of neurotoxicity on the AβO size and conformation at the molecular level, and provides novel and specific targets for drug design of Alzheimer's disease.

Binding characteristics of pyrrole-scaffold hepatitis B virus capsid inhibitors and identification of novel potent compounds

Hepatitis B virus (HBV) capsid assembly modulators (CAMs) are currently being evaluated in clinical trials as potential curative therapies for HBV. This study used in silico computational modeling to provide insights into the binding characteristics between the HBV core protein and two pyrrole-scaffold inhibitors, JNJ-6379 and GLP-26, both in the CAM-Normal (CAM-N) series. Molecular dynamics simulations showed that the pyrrole inhibitors displayed similar general binding-interaction patterns to NVR 3-778, another CAM-N, with hydrophobic interactions serving as the major driving force. However, consistent with their higher potency, the pyrrole inhibitors exhibited stronger nonpolar interactions with key residues in a solvent-accessible region as compared to NVR 3-778. This feature was facilitated by distinct hydrogen bond interactions of the pyrrole scaffold inhibitors with the residue 140 in chain B of the HBV core protein (L140B). Based on these findings, novel CAM-N compounds were designed to mimic the interaction with L140B residue while maximizing nonpolar interactions in the solvent-accessible region. Several 1H-pyrrole-2-carbonyl substituted pyrrolidine-based compounds with various hydrophobic side chains were synthesized and evaluated. Through analyses of the structure-activity and structure-druggability relations of a series of compounds, CU15 emerged as the most promising lead CAM-N compound, exhibiting sub-nanomolar potency and good pharmacokinetic profiles. Overall, the study demonstrated a practical approach to leverage computational methods for understanding key target binding features for rationale-based design, and for guiding the identification of novel compounds.

Identification and dynamics of novel scaffolds against Enterococcus faecium serine hydroxymethyltransferase enzyme: a potential target for antibiotics development

Serine hydroxymethyltransferase enzyme is a significant player in purine, thymidylate, and L-serine biosynthesis and has been tagged as a potential target for cancer, viruses, and parasites. However, this enzyme as an anti-bacterial druggable target has not been explored much. Herein, in this work, different computational chemistry and biophysics techniques were applied to identify potential computational predicted inhibitory molecules against Enterococcus faecium serine hydroxymethyltransferase enzyme. By structure based virtual screening process of ASINEX antibacterial library against the enzyme two main compounds: Top-1_BDC_21204033 and Top-2_BDC_20700155 were reported as best binding molecules. The Top-1_BDC_21204033 and Top-2_BDC_20700155 binding energy value is -9.3 and -8.9 kcal/mol, respectively. The control molecule binding energy score is -6.55 kcal/mol. The mean RMSD of Top-1-BDC_21204033, Top-2-BDC_20700155 and control is 3.7 Å (maximum 5.03 Å), 1.7 Å (maximum 3.05 Å), and 3.84 Å (maximum of 6.7 Å), respectively. During the simulation time, the intermolecular docked conformation and interactions were seen stable despite of few small jumps by the compounds/control, responsible for high RMSD in some frames. The MM/GBSA and MM/PBSA binding free energy of lead Top-2-BDC_20700155 complex is -79.52 and -82.63 kcal/mol, respectively. This complex was seen as the most stable compared to the control. Furthermore, the lead molecules and control showed good druglikeness and pharmacokinetics profile. The lead molecules were non-toxic and non-mutagenic. In short, the compounds are promising in terms of binding to the serine hydroxymethyltransferase enzyme and need to be subjected to experimental studies.Communicated by Ramaswamy H. Sarma.

In silico design and identification of new peptides for mitigating hIAPP aggregation in type 2 diabetes

The aberrant misfolding and self-aggregation of human islet amyloid polypeptide (hIAPP or amylin) into cytotoxic aggregates are implicated in the pathogenesis of type 2 diabetes (T2D). Among various inhibitors, short peptides derived from the amyloidogenic regions of hIAPP have been employed as hIAPP aggregation inhibitors due to their low immunogenicity, biocompatibility, and high chemical diversity. Recently, hIAPP fragment HSSNN18-22 was identified as an amyloidogenic sequence and displayed higher antiproliferative activity to RIN-5F cells. Various hIAPP aggregation inhibitors have been designed by chemical modifications of the highly amyloidogenic sequence (NFGAIL) of hIAPP. In this work, a library of pentapeptides based on fragment HSSNN18-22 was designed and assessed for their efficacy in blocking hIAPP aggregation using an integrated computational screening approach. The binding free energy calculations by molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method identified HSSQN and HSSNQ that bind to hIAPP monomer with a binding affinity of -21.25 ± 4.90 and -19.73 ± 3.10 kcal/mol, respectively, which is notably higher as compared to HSSNN (-11.90 ± 4.12 kcal/mol). The sampling of the non aggregation-prone helical conformation was notably increased from 23.5 ± 3.0 in the hIAPP monomer to 38.1 ± 3.6, and 33.8 ± 3.0% on the incorporation of HSSQN, and HSSNQ, respectively, which indicate reduced aggregation propensity of hIAPP monomer. The pentapeptides, HSSQN and HSSNQ, identified as hIAPP aggregation inhibitors in this work can be further conjugated with various metal chelating peptides to yield more efficacious and clinically relevant multifunctional modulators for targeting various pathological hallmarks of T2D.

Origin of stronger binding of ionic pair (IP) inhibitor to Aβ42 than the equimolar neutral counterparts: synergy mechanism of IP in disrupting Aβ42 protofibril and inhibiting Aβ42 aggregation under two pH conditions

Fibrous aggregates of beta-amyloid (Aβ) is a hallmark of Alzheimer's disease (AD). Several major strategies of drugs or inhibitors, including neutral molecules, positive or negative ions, and dual-inhibitor, are used to inhibit the misfolding or aggregation of Aβ42, among which a kind of dual-inhibitor composed of a pair of positive and negative ions is emerging as the most powerful candidate. This knowledge lacks the origin of the strong inhibitory effect and synergy mechanisms blocking the development and application of such inhibitors. To this end, we employed 1 : 1 ionic pairs (IP) of oppositely charged benzothiazole molecules (+)BAM1-EG6 (Pos) and (-)BAM1-EG6 (Neg) as well as equimolar neutral BAM1-EG6 (Neu) counterpart at two pH conditions (5.5 and 7.0) to bind Aβ42 targets, Aβ42 monomer (AβM), soluble pentamer (AβP), and pentameric protofibril (AβF) models, respectively, corresponding to the products of three toxic Aβ42 development pathways, lag, exponential and fibrillation phases. Simulated results illustrated the details of the inhibitory mechanisms of IP and Neu for the AβY (Y = M, P, or F) in the three different phases, characterizing the roles of Pos and Neg of IP as well as their charged, hydrophobic groups and linker playing in the synergistic interaction, and elucidated a previously unknown molecular mechanism governing the IP-Aβ42 interaction. Most importantly, we first revealed the origin of the stronger binding of IP inhibitors to Aβ42 than that of the equimolar neutral counterparts, observing a perplexing phenomenon that the physiological condition (pH = 7.0) than the acidic one (pH = 5.5) is more favorable to the enhancement of IP binding, and finally disclosed that solvation is responsible to the enhancement because at pH 7.0, AβP and AβF act as anionic membranes, where solvation plays a critical role in the chemoelectromechanics. The result not only provides a new dimension in dual-inhibitor/drug design and development but also a new perspective for uncovering charged protein disaggregation under IP-like inhibitors.

Insights into the Binding Profile of Anti-chlorpyrifos Recombinant Antibodies: From Computational Simulation to Immunoassay Validation

A novel virtual screening strategy was proposed for the profiling and discovery of active variable regions (VRs) that encode hapten-specific recombinant antibodies (rAbs). Chlorpyrifos, a hazardous organophosphorus pesticide, was selected as the target. First, a VR model-14G4 from anti-chlorpyrifos hybridoma was built via homology modeling. Its binding pattern toward seven organophosphorus analogues was assessed through virtual screening by performing molecular docking. Based on energy scoring, visual examination, and molecular interaction analysis, chlorpyrifos-methyl was also inferred as the high-affinity target for model-14G4 and was then confirmed via a non-competitive surface plasmon resonance (SPR) assay. Subsequently, we attempted to discover hapten-specific VRs by creating a collection of VR models for anonymous testing. Chlorpyrifos and model-14G4 were employed as the known hit and active VRs, respectively. After molecular docking, a novel anti-chlorpyrifos VR (model-1) was identified due to its satisfactory energy scoring and a similar binding pattern to the reference model-14G4. Expressed by HEK293(F) mammalian cells, the newly prepared full-length rAb-model-1 and rAb-14G4 exhibited high sensitivities for detecting chlorpyrifos by the indirect competitive enzyme-linked immunosorbent assay (ic-ELISA), with IC₅₀ of 3.01 ng/mL and 42.82 ng/mL, respectively. They recognized chlorpyrifos-methyl with a cross-reactivity (CR) of 2.5-17.3%. Moreover, the binding properties of rAb-model-1 for recognizing chlorpyrifos and chlorpyrifos-methyl were confirmed via a non-competitive microscale thermophoresis (MST) method. Thus, the experimental results showed good agreement with computational outputs on antibody profiling. Furthermore, the recognition diversity of rAb-model-1 for chlorpyrifos and chlorpyrifos-methyl was studied via molecular dynamics simulation. Overall, the proposed study provides a versatile and economical strategy for antibody characterization and promotes the in vitro production of rAbs for pesticide monitoring.

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.

Unveiling How Hydroxytyrosol Destabilizes α-Syn Oligomers Using Molecular Simulations

The etiology of Parkinson's disease (PD) is mainly linked to the α-synuclein (α-Syn) fibrillogenesis. Hydroxytyrosol (HT), also known as 3,4-dihydroxyphenylethanol, is a naturally occurring polyphenol, found in extra virgin olive oil, and has been shown to have cardioprotective, anticancer, antiobesity, and antidiabetic properties. HT has neuroprotective benefits in neurodegenerative diseases and lessens the severity of PD by reducing the aggregation of α-Syn and destabilizing the preformed toxic α-Syn oligomers. However, the molecular mechanism by which HT destabilizes α-Syn oligomers and alleviates the accompanying cytotoxicity remains unexplored. The impact of HT on the α-Syn oligomer structure and its potential binding mechanism was examined in this work by employing molecular dynamics (MD) simulations. The secondary structure analysis depicted that HT significantly reduces the β-sheet and concomitantly increases the coil content of α-Syn trimer. Visualization of representative conformations from the clustering analysis depicted the hydrogen bond interactions of the hydroxyl groups in HT with the N-terminal and nonamyloid-β component (NAC) region residues of α-Syn trimer, which, in turn, leads to the weakening of interchain interactions in α-Syn trimer and resulted in the disruption of the α-Syn oligomer. The binding free energy calculations depict that HT binds favorably to α-Syn trimer (ΔG_binding = -23.25 ± 7.86 kcal/mol) and a notable reduction in the interchain binding affinity of α-Syn trimer on the incorporation of HT, which, in turn, highlights its potential to disrupt α-Syn oligomers. The current research provided mechanistic insights into the destabilization of α-Syn trimer by HT, which, in turn, will provide new clues for developing therapeutics against PD.

Disulfiram reduces the severity of mouse acute pancreatitis by inhibiting RIPK1-dependent acinar cell necrosis

Acute pancreatitis (AP) is a frequent abdominal inflammatory disease. Despite the high morbidity and mortality, the management of AP remains unsatisfactory. Disulfiram (DSF) is an FDA-proved drug with potential therapeutic effects on inflammatory diseases. In this study, we aim to investigate the effect of DSF on pancreatic acinar cell necrosis, and to explore the underlying mechanisms. Cell necrosis was induced by sodium taurocholate or caerulein, AP mice model was induced by nine hourly injections of caerulein. Network pharmacology, molecular docking, and molecular dynamics simulation were used to explore the potential targets of DSF in protecting against cell necrosis. The results indicated that DSF significantly inhibited acinar cell necrosis as evidenced by a decreased ratio of necrotic cells in the pancreas. Network pharmacology, molecular docking, and molecular dynamics simulation identified RIPK1 as a potent target of DSF in protecting against acinar cell necrosis. qRT-PCR analysis revealed that DSF decreased the mRNA levels of RIPK1 in freshly isolated pancreatic acinar cells and the pancreas of AP mice. Western blot showed that DSF treatment decreased the expressions of RIPK1 and MLKL proteins. Moreover, DSF inhibited NF-κB activation in acini. It also decreased the protein expression of TLR4 and the formation of neutrophils extracellular traps (NETs) induced by damage-associated molecular patterns released by necrotic acinar cells. Collectively, DSF could ameliorate the severity of mouse acute pancreatitis by inhibiting RIPK-dependent acinar cell necrosis and the following formation of NETs.

Unravelling the destabilization potential of ellagic acid on α-synuclein fibrils using molecular dynamics simulations

The aberrant deposition of α-synuclein (α-Syn) protein into the intracellular neuronal aggregates termed Lewy bodies and Lewy neurites characterizes the devastating neurodegenerative condition known as Parkinson's disease (PD). The disruption of pre-existing disease-relevant α-Syn fibrils is recognized as a viable therapeutic approach for PD. Ellagic acid (EA), a natural polyphenolic compound, is experimentally proven as a potential candidate that prevents or reverses the α-Syn fibrillization process. However, the detailed inhibitory mechanism of EA against the destabilization of α-Syn fibril remains largely unclear. In this work, the influence of EA on α-Syn fibril and its putative binding mechanism were explored using molecular dynamics (MD) simulations. EA interacted primarily with the non-amyloid-β component (NAC) of α-Syn fibril, disrupting its β-sheet content and thereby increasing the coil content. The E46-K80 salt bridge, critical for the stability of Greek-key-like α-Syn fibril, was disrupted in the presence of EA. The binding free energy analysis using the MM-PBSA method demonstrates the favourable binding of EA to α-Syn fibril (ΔG_binding = -34.62 ± 11.33 kcal mol^-1). Interestingly, the binding affinity between chains H and J of the α-Syn fibril was significantly reduced on the incorporation of EA, which highlights the disruptive ability of EA towards α-Syn fibril. The MD simulations provide mechanistic insights into the α-Syn fibril disruption by EA, which gives a valuable direction for the development of potential inhibitors of α-Syn fibrillization and its associated cytotoxicity.

Assessment of Different Parameters on the Accuracy of Computational Alanine Scanning of Protein-Protein Complexes with the Molecular Mechanics/Generalized Born Surface Area Method

Computational alanine scanning with the molecular mechanics generalized Born surface area (MM/GBSA) method constitutes a widely used approach for identifying critical residues at protein-protein interfaces. Despite its popularity, the MM/GBSA method still has certain drawbacks due to its dependence on many factors. Here, we performed a systematical study on the impact of four different parameters, namely, the internal dielectric constant, the generalized Born model, the entropic term, and the inclusion of structural waters on the accuracy of computational alanine scanning calculations with the MM/GBSA method. Our results show that the internal dielectric constant is the most critical parameter for getting accurate predictions. The introduction of entropy and interfacial water molecules decreased the quality of the predictions, while the generalized Born model had little to no effect. Considering the significance of the internal dielectric value, we proposed a methodology based on the energetic predominance of a particular set of amino acids at the protein-protein interface for selecting an appropriate value for this variable. We hope that these results serve as a guideline for future studies of protein-protein complexes using the MM/GBSA method.

Chitinase is a Potent Insecticidal Molecular Target of Camptothecin and Its Derivatives

Camptothecin (CPT) is a prominent molecule in natural product research because of its application prospects in medicine and agriculture. In this study, CPT and its derivatives were discovered to be competitive inhibitors of group II and group h insect chitinases, both of which are key components of insect chitinolytic systems. CPT and 7-ethyl-10-hydroxycamptothecin (SN-38) inhibited group II chitinase from Ostrinia furnacalis (OfChtII) with K_i values of 5.1 and 2.0 μM, respectively. Results from tryptophan fluorescence spectroscopy, molecular docking analysis, and molecular dynamics simulations revealed that both CPT and SN-38 inhibit OfChtII-C1 by interacting with solvent-exposed tryptophan residues in a substrate-binding cleft. CPT exhibited high insecticidal activity toward the orthopteran pest Locusta migratoria, possibly because of the midgut metabolism of CPT, with only moderate activities toward lepidopteran pests. Even though SN-38 exhibited much lower insecticidal activities than CPT, it still showed higher inhibitory activity toward chitinase. This study reports a new molecular target of CPT and provides insights into molecular design of CPT-based insecticides against different kinds of pests.

In silico study of selective inhibition mechanism of S-adenosyl-L-methionine analogs for human DNA methyltransferase 3A

Epigenetic mechanisms leading to transcriptional regulation, including DNA methylation, are frequently dysregulated in diverse cancers. Interfering with aberrant DNA methylation performed by DNA cytosine methyltransferases (DNMTs) is a clinically validated approach. In particular, the selective inhibition of the de novo DNMT3A and DNMT3B enzymes, whose expression is limited to early embryogenesis, adult stem cells, and in cancers, is particularly attractive; such selectivity is likely to attenuate the dose limiting toxicity shown by current, non-selective DNMT inhibitors. We use molecular dynamics (MD) based computational analysis to study known small molecule binders of DNMT3A, then propose reversible, tight binding, and selective inhibitors that exploit the Asn¹¹⁹²/Arg⁶⁸⁸ difference between the maintenance DNMT1 and DNMT3A near the active site. A similar strategy exploiting the presence of a unique active site cysteine Cys⁶⁶⁶ is used to propose DNMT3A-selective irreversible inhibitors. We report our results of relative binding energies of the known and proposed compounds estimated using MM/GBSA and umbrella sampling (US) techniques, and our evaluation of other end-point binding free energy calculation methods for these receptors. These calculations offer insight into the potential for small molecules to selectively target the active site of DNMT3A.

Binding site hotspot map of PI3Kα and mTOR in the presence of selective and dual ATP-competitive inhibitors

The PI3K/Akt/mTOR signaling pathway plays a pivotal role in cellular metabolism, growth and survival. PI3Kα hyperactivation impairs downstream signaling, including mTOR regulation, and are linked to poor prognosis and refractory cancer treatment. To support multi-target drug discovery, we took advantage from existing PI3Kα and mTOR crystallographic structures to map similarities and differences in their ATP-binding pockets in the presence of selective or dual inhibitors. Molecular dynamics and MM/PBSA calculations were employed to study the binding profile and identify the relative contribution of binding site residues. Our analysis showed that while varying parameters of solute and solvent dielectric constant interfered in the absolute binding free energy, it had no effect in the relative per residue contribution. In all complexes, the most important interactions were observed within 3-3.5 Å from inhibitors, responding for ∼75-100% of the total calculated interaction energy. While closest residues are essential for the strength of the binding of all ligands, more distant residues seem to have a larger impact on the binding of the dual inhibitor, as observed for PI3Kα residues Phe934, Lys802 and Asp805 and, mTOR residues Leu2192, Phe2358, Leu2354, Lys2187 and Tyr2225. A detailed description of individual residue contribution in the presence of selective or dual inhibitors is provided as an effort to improve the understanding of molecular mechanisms controlling multi-target inhibition. This work provides key information to support further studies seeking the rational design of potent PI3K/mTOR dual inhibitors for cancer treatment.Communicated by Ramaswamy H. Sarma.

Protein-ligand binding affinity prediction with edge awareness and supervised attention

Accurate prediction of protein-ligand binding affinity is crucial in structure-based drug design but remains some challenges even with recent advances in deep learning: (1) Existing methods neglect the edge information in protein and ligand structure data; (2) current attention mechanisms struggle to capture true binding interactions in the small dataset. Herein, we proposed SEGSA_DTA, a SuperEdge Graph convolution-based and Supervised Attention-based Drug-Target Affinity prediction method, where the super edge graph convolution can comprehensively utilize node and edge information and the multi-supervised attention module can efficiently learn the attention distribution consistent with real protein-ligand interactions. Results on the multiple datasets show that SEGSA_DTA outperforms current state-of-the-art methods. We also applied SEGSA_DTA in repurposing FDA-approved drugs to identify potential coronavirus disease 2019 (COVID-19) treatments. Besides, by using SHapley Additive exPlanations (SHAP), we found that SEGSA_DTA is interpretable and further provides a new quantitative analytical solution for structure-based lead optimization.

Funnel metadynamics and behavioral studies reveal complex effect of D2AAK1 ligand on anxiety-like processes

Anxiety is a troublesome symptom for many patients, especially those suffering from schizophrenia. Its regulation involves serotonin receptors, targeted e.g. by antipsychotics or psychedelics such as LSD. 5-HT_2A receptors are known for an extremely long LSD residence time, enabling minute doses to exert a long-lasting effect. In this work, we explore the changes in anxiety-like processes induced by the previously reported antipsychotic, D2AAK1. In vivo studies revealed that the effect of D2AAK1 on the anxiety is mediated through serotonin 5-HT_1A and 5-HT_2A receptors, and that it is time-dependent (anxiogenic after 30 min, anxiolytic after 60 min) and dose-dependent. The funnel metadynamics simulations suggest complicated ligand-5HT_2AR interactions, involving an allosteric site located under the third extracellular loop, which is a possible explanation of the time-dependency. The binding of D2AAK1 at the allosteric site results in a broader opening of the extracellular receptor entry, possibly altering the binding kinetics of orthosteric ligands.