Mycobacterium tuberculosis causes tuberculosis (TB), which remains a significant health problem worldwide. The rise of multidrug-resistant bacteria has worsened the situation, and current treatments are becoming less effective. InhA, a key enzyme involved in mycolic acid biosynthesis, is a validated therapeutic target in anti-TB therapy. This study aimed to explore the chemical diversity of natural substances from mushrooms against TB. Experimentally validated inhibitors from ChEMBL were retrieved to generate machine learning-based QSAR models combining nine chemical fingerprints and rigorous feature selection. The optimal RF-SVM-RFE model displayed high prediction performance (accuracy = 0.953, ROC_AUC = 0.971) and led virtual screening of mushroom metabolites. Six top-ranked compounds, including Inoscavin A and Schizine A, displayed substantial binding affinities (-11.7 to -10.5 kcal/mol) and stable interaction networks in molecular docking and MD simulations. Explainable AI (SHAP and LIME) showed fundamental structural motifs that drive activity and enhance chemical interpretability. These findings suggest promising natural scaffolds for anti-TB drug development and underscore the importance of AI-driven strategies in accelerating natural product-based therapeutics.

Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) is a crucial post-transcriptional regulator in mRNA localization, stability, and translation. While IGF2BP3 overexpression is widely studied in cancer, recent evidence highlights its role in diabetic retinopathy (DR), a significant cause of blindness. In DR, IGF2BP3 regulates pro-angiogenic and pro-inflammatory factors, such as VEGF, contributing to retinal vascular damage, neovascularization, and inflammation. These effects make IGF2BP3 a potential therapeutic target for DR. Henceforth, in this study, high-throughput virtual screening (HTVS) and molecular dynamics (MD) simulations were implemented to identify potential IGF2BP3 inhibitors, focusing on its KH3 and KH4 RNA-binding domains. The KH4 domain was selected as the optimal target with a higher druggability score. HTVS of the ChemDiv database identified three promising candidates: Y040-1954, C200-9224, and 1761-0723, which showed strong interactions with the GXXG motif within the KH4 domain, critical for RNA binding. Density Functional Theory (DFT) and molecular docking analysis confirmed these candidates' reactivity and binding affinity to IGF2BP3. MD simulations conducted over 200 ns showed that IGF2BP3-inhibitor complexes retained structural stability with consistent hydrogen bonding, particularly involving key residues Ser624, Ser627, and Thr628. These findings suggest that the identified compounds could disrupt IGF2BP3's interaction with m6A-modified RNA, potentially blocking its role in stabilizing pro-angiogenic and pro-inflammatory mRNAs in DR. With experimental validation and optimization, these compounds could significantly advance the treatment landscape for DR, offering hope for better outcomes in this leading cause of blindness.

This research uses density functional theory to examine the structural, electronic, optical, mechanical, thermodynamic, thermoelectric, magnetic, and photovoltaic properties of Sn-based AmSnX (Am = Rb, Cs; X = Cl, Br, I) perovskites. The tolerance factor (0.71-1.04) and the negative cohesive energy confirm the materials' structural and thermodynamic stability. The electronic properties show semiconducting behavior, with energy band gaps of 0.42 eV for RbSnBr3 and 1.02 eV for CsSnCl. The maximum absorption values (7.16 × 10 cm to 8.11 × 10 cm) in the visible region indicate efficient light harvesting for solar cell applications. Mechanical properties suggest mechanical stability and ductility. The Debye temperature (146.08-190.78 K) offers insights into heat capacity and thermal behavior at different temperatures. The Seebeck coefficient at room temperature classifies RbSnBr, RbSnI, and CsSnCl as p-type materials, while RbSnCl, CsSnBr, and CsSnI are n-type. The calculated power conversion efficiencies, from 12.47 % for CsSnI to 29.54 % for CsSnCl, emphasize the novelty of this work, which combines structural, mechanical, electronic, and optical analyses for the first time to thoroughly evaluate the potential of RbSnX and CsSnX perovskites in optoelectronic and energy applications.

Pharmaceutical pollutants such as Diclofenac and Naproxen are emerging environmental contaminants due to their persistence and potential biological hazards. In this study, pristine and functionalized Kekulene nanorings (KNRs) were theoretically explored as novel adsorbents using density functional theory (DFT). Various functional groups (-COOH, -NO, -NO, -N, -O, -S) were introduced to modulate the interaction with drug molecules. Adsorption energy (E) calculations confirmed spontaneous physisorption across all systems, with values ranging from -2.473 to -0.441 eV. Notably, the KNR-NO-N system in aqueous phase exhibited the lowest E (-0.441 eV) and shortest recovery time (τ = 2.864 × 10 s), making it the most promising candidate for rapid desorption and recyclability. Non-covalent interaction (NCI) analysis revealed that van der Waals forces and weak electrostatic interactions dominate the adsorption mechanism. Natural Bond Orbital (NBO) analysis of the oxygen atom (O6) confirmed variable charge transfer behaviour, reflecting the influence of surface functionalization. HOMO-LUMO analysis showed frontier orbital localization patterns that shifted upon functionalization, especially in Naproxen complexes, indicating enhanced electronic interactions. Compared to benchmark materials such as PTX@rGO and FPV@GN, KNR-based adsorbents demonstrated competitive or superior tunability and desorption potential. These results suggest that functionalized KNRs-particularly KNR-NO-N-are promising candidates for efficient, reversible pharmaceutical pollutant capture in both gas and aqueous environments.

Histone deacetylase 3 (HDAC3) is a key epigenetic regulator implicated in breast cancer progression and represents a promising therapeutic target. Here, we investigated 14 HDAC3-ligand complexes using molecular dynamics (MD) simulations and binding free energy calculations (MM/GBSA) to identify the determinants of inhibitor binding. Key residues consistently engaged across ligands included Gly132, His134-135, Phe144, Asp170, His172, Phe200, Asp259, Leu266, Gly296, Tyr298, and the catalytic Zn ion. Among the compounds, domatinostat and entinostat exhibited the strongest affinities (ΔGbind ≈ -70 kcal/mol), in reasonable agreement with experimental data (r = 0.60). Both ligands also showed small Highest Occupied Molecular Orbital-Lowest Unoccupied Molecular Orbital (HOMO-LUMO) gaps, high softness, and elevated electrophilicity indices, providing chemical cues for the design of next-generation HDAC3 inhibitors. Notably, ligand binding stabilized regions surrounding Phe200 and Asn370, restricting the conformational flexibility required for enzymatic activation. This supports an allosteric inhibition mechanism in which ligands lock HDAC3 into inactive conformations. Collectively, these findings offer mechanistic insights into HDAC3 regulation and highlight structural hot spots for the rational design of selective inhibitors with potential applications in targeted breast cancer therapy.

Atomic packing is an important metric for characterizing protein structures, as it significantly influences various features including the stability, the rate of evolution and the functional roles of proteins. Packing in protein structures is a measure of the overall proximity between the proteins' atoms and it can vary notably among different structures. However, even single domain proteins do not exhibit uniform packing throughout their structure. Protein cores in the interior tend to be more tightly packed compared to the protein surface and the presence of cavities and voids can disrupt that internal tight packing too. Many different methods have been used to measure the quality of packing in proteins, identify factors that influence it, and their possible implications. In this work, we examine atomic density distributions derived from 21,255 non-redundant protein structures and show that statistically significant differences between those distributions are present. The biomolecular assembly unit was chosen as a representative for these structures. Addition of hydrogen atoms and solvation was also performed to emulate a faithful representation of the structures in vitro. Several protein structures deviate significantly and systematically from the average packing behavior. Hierarchical clustering indicated that there are groups of structures with similar atomic density distributions. Search for common features and patterns in these clusters showed that some of them include proteins with characteristic structures such as coiled-coils and cytochromes. Certain classification families such as hydrolases and transferases have also a preference to appear more frequently in dense and loosely-packed clusters respectively. Regarding factors influencing packing, our results support knowledge that larger structures have a smaller range in their density values, but tend to be more loosely packed, compared to smaller proteins. We also used indicators, like crystallographic water molecules abundance and B-factors as estimates of the stability of the structures to reveal its relationship with packing.

Heptazethrene derivatives have garnered significant interest due to their potential applications in photovoltaics and optics. Building on previous studies that explored the structure-property relationship for photovoltaic applications, this research delves into a detailed analysis of infrared spectral examination, electron density difference, and non-covalent interactions. Directly linking optical absorption profiles, oscillator strength, and excited state data, such as dipole moment and transition energy, with linear and nonlinear optical polarizability, it is observed that heptazethrene derivatives exhibit desirable average diradical characteristics. These characteristics enhance the linear polarizability by 30-50 % and the nonlinear polarizability by 6-12 times compared to the reference. This investigation positions heptazethrene derivatives as promising materials to enhance optical and photonic technologies in optoelectronic devices.

Ketosteroid isomerase (KSI), a highly conserved enzyme in the β-ketoacyl metabolic pathway, exhibits temperature-dependent functional adaptations across species. In this study, we investigated the temperature sensitivity of mesophilic KSI from Pseudomonas putida using molecular dynamics simulations. Since KSI functions as a dimer, we simulated both monomeric and dimeric forms at its optimal catalytic temperature (303 K) and at an elevated, non-optimal temperature (338 K) to evaluate how temperature and dimerization affect activation. We focused on the dynamics of three catalytically important residues-Y16, D40, and D103-where Y16 is located on the mobile α1-helix not involved in the dimer interface, D40 lies at the edge of the dimer interface, and D103 resides at the center of the core β-sheet structure that remains static in both monomeric and dimeric states. In the monomeric form at 303 K, the Y16-D40, Y16-D103, and D40-D103 pairs exhibit broader and longer separation distances than the optimal range for catalysis. Dimerization stabilizes D40, resulting in a narrower D40-D103 separation that falls within the catalytically competent range. The relatively unchanged mobility of Y16 upon dimerization suggests that Y16 undergoes an induced-fit adjustment upon substrate binding. At 338 K, although dimerization partially corrects the D40-D103 geometry, the increased conformational flexibility of Y16 indicates a reduced likelihood of achieving the substrate-induced active-site reorganization. Together, our results demonstrate that dimerization is essential for achieving the geometric organization required for catalytic activity and that elevated temperature disrupts this coordination, rendering KSI inactive.

This theoretical study investigates the properties of T-GeNRs using tight-binding formalism, Green's function, and the Kubo formula. Our research examines the temperature dependence of thermodynamic functions under varying external parameters, including electric bias and magnetic fields and chemical potential. The application of bias voltage induces a band gap, the magnetic field enhances the density of states (DOS) and the chemical potential modulates the charge carrier concentration, leading to distinct modifications in the electrical and thermal properties across different temperature ranges. The electrical property analysis reveals that the unperturbed structure exhibits metallic behavior. This feature remains unchanged under magnetic field, with increasing field strength leading to significant enhancing DOS spectrum intensity. In contrast, the introduction of voltage bias induces a metal-to-semiconductor transition, with the band gap size being directly correlated to the bias strength. The thermodynamic properties, including electrical and thermal conductivity, Magnetic susceptibility and the Lorenz number, demonstrate distinct responses to external fields, while bias voltage reduces these properties, the magnetic field enhances them. A particularly notable feature in the temperature dependence of thermodynamic functions is emergence a zero-intensity region attributed to the energy gap formation. The occurrence of this zero-intensity temperature region is closely related to field strength, increasing with bias voltage and decreasing with the magnetic field. To optimize thermodynamic performance in the selected structures, the simultaneous application of voltage bias and a magnetic field can be employed, making T-GeNRs promising candidates for nanoelectronic and thermophotonic applications.

Nanomedicine has transformed cancer therapy by introducing and developing nanocarriers to enhance drug delivery. Herein, we have executed a computational investigation of the efficiency of two anti-breast cancer drugs viz. Exemestane (EXE) and Ruxolitinib (RUX) are delivered through armchair CNT (10,10). The encapsulation process of drugs in CNTs has been investigated through an analysis of various structural and electrical parameters viz. atom centered density matrix(ADMP), adsorption energy, electrostatic potential map(ESPM), molecular orbital(MO) analysis, natural bond orbital (NBO) analysis, non-covalent index (NCI) plot, and projected density of state (PDOS). The higher adsorption value of RUX -72.42 kcal/mol(-3.14 eV) with CNT and CNT-EXE -63.29 kcal/mol(-2.75 eV) indicates a stronger binding affinity of RUX and EXE. The electronic properties of the CNT were examined and compared before and after the adsorption process.Study of several thermodynamic parameters revealed that the whole encapsulation process is exothermic and spontaneous in nature. The stabilizing interaction of drugs and CNT has been established and validated from ADMP molecular dynamics simulation and NCI analysis was performed through the encapsulation procedure of the drugs within CNT at room temperature. The best docking score showed the CNT with EXE (-7.6 kcal/mol) followed by CNT with RUX (-7.5 kcal/mol), higher than the studied drugs i.e. EXE (-7.3 kcal/mol) and RUX (-7.2 kcal/mol). The docking score indicates that the inclusion complex has a better interaction and pave the way for unlimited opportunities for the delivery vehicle of CNT for the studied drugs within the biological systems.

The design and development of efficient and responsive drug carriers always remain a challenge in targeted cancer treatment, where the traditional nanocarriers suffer the drawbacks of limited stability, a lack of selectivity, and slow release of the drug. In this perspective, the oxygenated triaryl methyl (oxTAM) nanocarrier is known for its tunability, and redox activity offers a promising alternative. In the present work, we hypothesize that the oxTAM carrier can function as an efficient and effective drug carrier for selected anticancer drugs like Fludarabine (Flu) and Cytarabine (Cyt) due to its ability to make stable noncovalent interactions and release of drugs in acidic conditions. The potential application of oxTAM as drug carrier is explored by using ωB97XD/6-31+G(d,p) functional. The interaction in energy analysis (E) and interacting distances (E) reveal that oxTAM shows excellent interaction for Flu (-1.77 eV, 1.92 Å) drug. Non-covalent interaction index (NCI) indicates the existence of van der Waals interaction and hydrogen bonding (O-H bond) between the interacting moieties. The results of dipole moment and quantum chemical descriptors show the high reactivities of oxTAM for Flu and Cyt drugs. Electronic analysis including natural bond orbital (NBO) charge transfer demonstrates the higher response of Flu drug towards oxTAM. In addition, the reduced adsorption stability upon protonation in an acidic environment can quickly release drug molecules from the carrier. Short recovery time indicates easy drug delivery at the targeted site. From all these results, we concluded that oxTAM can be a potential candidate for further experimental exploration in drug delivery systems.

The rapidly growing number of protein structures in the Protein Data Bank (PDB) offers opportunities to derive biological insights from proteins with common features. Taking advantage of this "big data" resource, we developed an automated open-source Python script designated "Vanalyzer" that performs statistical analysis on vanadate-binding sites across the PDB. Vanalyzer evaluates the structural properties of proteins containing vanadium-based oxyanions by comparing binding interfaces and geometries across a diverse array of proteins. Additionally, it allows a focused analysis on specific enzyme classes, facilitating direct comparisons between them. The newly developed tool will contribute to the understanding of vanadate recognition within protein binding sites and will serve as a valuable, up-to-date resource for analyzing both current and newly submitted vanadate structures in the PDB.

The pursuit of high-performance nonlinear optical (NLO) materials remains central to advancing optical communication, photonic circuitry, and laser-based technologies. In this study, we theoretically designed and evaluated a new class of alkali metal-doped diazadioxa[8]circulene complexes, denoted as M@C8 (M = Li, Na, K), using density functional theory. Metal doping induces profound structural and electronic reorganization, with interaction energies ranging from -0.25 to -11.21 kcal mol, affirming both favorable metal binding and thermodynamic stability. Remarkably, these modifications lead to dramatic enhancements in NLO performance. The pristine C8 molecule exhibits a negligible static first hyperpolarizability (β) of just 0.03 au; however, upon doping, β surges to an exceptional 470074.83 au for 3-Li@C8, an increase of nearly 1.57 × 10-fold. Under dynamic conditions (λ = 1064 nm), the first-order hyperpolarizability β(-ω, ω, 0) reaches 104948.80 au for 3-Na@C8, while the hyper-Rayleigh scattering hyperpolarizability (β) peaks at 2837379.65 au for 5-K@C8, showcasing outstanding frequency-dependent NLO activity. Complementary UV-Vis analysis reveals pronounced redshifts in absorption (from 199.39 nm for C8 to 773.60 nm for 6-K@C8), indicating enhanced π-electron delocalization and efficient intramolecular charge transfer. Taken together, these findings position M@C8 complexes as compelling molecular platforms for next-generation NLO materials with exceptional static and dynamic optical responses.

First-principles calculations based on the density functional theory (DFT) are employed to study the structural, electronic, magnetic, optical, and thermal properties of new Zr based half- Heusler compounds with α, β and γ phases. The most stable state is predicted as ferromagnetic α-phase. Electronic structure predicted the half metallic property and indirect band gap nature of the compounds. The magnetic moment around 1μ obeys the Slater-Pauling rule. The spin polarization at the Fermi level is 100 % which also supports the half metallic behavior. The high Curie temperature values 342.7 K, 1082.7 K and 835.3 K of these half-Heusler alloys make them strong ferromagnets. The high value of dielectric function leads to better polarization, stability and energy storage. The dielectric constant values of ZrFeAs, ZrFeSb and ZrFeBi are found to be 19.4, 18.6 and 18.1 respectively. The absence of negative frequency modes in phonon dispersion curve suggests that these alloys are dynamically stable. The zero-point energy values of ZrFeAs, ZrFeSb and ZrFeBi are 8.4 kJ/mol, 8.06 kJ/mol and 6.79 kJ/mol respectively.

This work investigates theoretically the activation and directing effects in a fluorinated allenic system, 1-(5,5-difluoropenta-3,4-dienyl)benzene (FPB), during a Cu-catalyzed cycloaddition reaction with phenyl nitrile oxide (NO). The FPB…Cu interactions were studied and it was found coordination of Cu ion to the central carbon atom of the allenic system and a cation-π interaction in the most stable complex. Four potential possible reaction paths were considered between FPB and NO and the computational results corroborated the experimental findings, indicating that the formation of CA-2 is favored in uncatalyzed reaction, whereas CA-3 formation is preferred in catalyzed one. The calculated energy difference between the most stable and unstable TS is about 32 kJ/mol for the uncatalyzed system, a value that increases to 192 kJ/mol under catalysis. Furthermore, the computed activation Gibbs free energy for TS-2 (the most favorable transition state in uncatalyzed reaction) is 101.03 kJ/mol and that for TS-3-cat (the most favorable TS in catalyzed reaction) is 92.02 kJ/mol. Consequently, the catalyst is shown to be effective not only in decreasing the activation barrier but also in controlling the regioselectivity of the reaction by increasing the difference between the energy surfaces of TSs. The regioselectivity was rationalized through Natural Bond Orbital NBO (based on E values resulted from E perturbation theory) and Independent Gradient Model based on Hirshfeld partition (IGMH) analyses. Finally, application of the Electron Localization Function (ELF) analysis revealed the molecular mechanism to be a two-stage one-step mechanism in both cases.

Tuberculosis (TB) is one of the leading causes of mortality worldwide. Although it is considered a curable disease, the emergence of strains resistant to conventional treatments has rendered it a significant public health problem. Therefore, it is necessary to identify new therapeutic targets to combat this disease. The serine/threonine protein kinase A (PknA) has gained relevance due to its essential role in cell wall synthesis and the growth of Mycobacterium tuberculosis (Mtb). In the present study, an integrative molecular modeling approach was developed for the screening of libraries containing 1 581 625 compounds to identify potential PknA inhibitors. Pharmacophore-based virtual screening, followed by molecular docking, steered molecular dynamics, and binding free energy calculations have identified compound CHEMBL552033 as a promising hit compound. In addition, in silico ADME profiling, pharmacophore-based toxicity assessment, and kinase selectivity screening were performed to evaluate overall suitability as a promising hit. Molecular dynamics simulations of the PknA-CHEMBL552033 complex demonstrated the stability of the interaction, and the binding free energy values obtained by MM-GBSA (-49.54 ± 7.08 kcal/mol) and LIE-D method (-7.01 ± 1.26 kcal/mol) emphasize the potential of CHEMBL552033 as a potential inhibitor for the development of novel anti-TB therapies.

Ursolic acid (UA) exhibits anti-inflammatory and anti-tumor properties. Developing a nanodrug delivery system for UA can improve its bioavailability. Transition metal sulfides, owing to their distinctive physicochemical characteristics, have emerged as the predominant two-dimensional nanostructures utilized in the advancement of nanodrug delivery systems in recent years. This study employs first-principles calculations to assess the viability of monolayer PtS as a carrier for UA. The results indicate that monolayer PtS exhibits structural stability as a UA carrier, with an adsorption energy of -3.84 eV. Mulliken charge analysis reveals that UA donates 0.34 |e| to PtS. Additionally, the application of strain induces a redshift in the optical absorption peak of monolayer PtS, thereby enhancing its optical absorption capabilities. Furthermore, monolayer PtS displays favorable temperature-controlled release properties when utilized as a delivery vehicle for Ursolic acid. These results offer theoretical insights that could inform the development of innovative drug carriers and significantly contribute to the treatment of inflammatory bowel disease.

In this work, we explore the pH-responsive stability of the supramolecular host-guest complex formed by the tetracationic cyclophane ExBox and diphenylporphyrin. This study builds upon the supramolecular concept originally introduced for ExBox-porphyrin systems by Stoddart and co-workers [1], providing a theoretical perspective on their pH-dependent behavior. We study how porphyrin protonation modulates geometry, binding interactions, and supramolecular behavior using a methodology that integrates density functional theory (DFT), energy decomposition analysis (EDA), non-covalent interaction (NCI) analysis, and molecular dynamics (MD) simulations. Our findings reveal that π-π stacking and electrostatic forces stabilize the neutral complex, whereas protonation breaks host-guest complementarity, weakening the assembly and allowing partial guest release. This set of methodologies provides a predictive tool for recognizing supramolecular assemblies, highlighting the potential of ExBox as a pH-sensitive sequestering agent and showing how a combined DFT, EDA, NCI, and MD framework can serve as a practical approach to investigate controlled release processes in supramolecular systems.

This study investigates the effects of edge hydrogenation and length changes on the electronic and magnetic properties of armchair PSI (Ψ)-graphene nanoribbons (AΨGNRBs) and zigzag PSI (Ψ)- graphene nanoribbons (ZΨGNRBs) with changing the length and a repetition number from 1 to 10. Density Functional Theory (DFT) and Generalized Gradient Approximation (GGA-1/2) were used for this purpose. The Perdew-Burke-Ernzerhof (PBE) method was used to calculate the exchange-correlation energy. Results demonstrated that hydrogenation of AΨGNRBs causes a band gap of about 0.73 eV with slight changes due to the varied length of the nanoribbon (NRB), but with a constant value of 0.7366 in repetitions from 4 to 10. They are utilized in the fields of optoelectronics, photonics, LEDs, lasers, sensors, and photonic devices. This NRB is a non-magnetic N-type semiconductor. It is used in transistors, and quantum devices that require precise electronic (rather than spintronic) control. However, ZΨGNRBs with changing the length and a repetition number from 1 to 10 are non-magnetic conductors, and edge hydrogenation does not cause a band gap. These nanostructures are compatible with conventional electronic (non-spintronic) devices. The formation energy of hydrogen-passivated AΨGNRBs and ZΨGNRBs is lower than that of the non-passivated counterparts, indicating greater stability of the passivated NRBs. Moreover, the formation energy of AΨGNRBs from 1 to 10 repetitions is lower than that of ZΨGNRBs. This significant reduction in the formation energy indicates greater stability and a more optimal structure of AΨGNRBs compared to ZΨGNRBs. This issue is of critical importance in the design of nanomaterials.

This study employs density functional theory (DFT) with Grimme's D3-BJ dispersion correction to investigate the adsorption of six hazardous industrial gases (HI) including cyanogen chloride (CNCl), formaldehyde (CHO), cyanogen (CN), hydrogen cyanide (HCN), dichloroacetylene (CCl), and phosgene (COCl) on a magnesium-porphyrin nanoring sensor (NRPMg). The interactions are characterized as physical and reversible, with BSSE corrected adsorption energies ranging from -1.90 to -18.36 kcal/mol. Gas adsorption induces a significant band gap increase of approximately 122 %, substantially reducing electrical conductivity, while maintaining adsorption distances of 2.16-3.09 Å consistent with physisorption. The calculated recovery times spanning picoseconds to microseconds indicate rapid adsorption-desorption cycles. Electronic structure analysis through Natural Bond Orbital (NBO) and Frontier Molecular Orbital (FMO) calculations reveals consistent electron transfer from gas molecule HOMOs to the nanoring's LUMO. The presence of four distinct adsorption sites enables saturation-free detection of HI, with demonstrated resilience against atmospheric interference from nitrogen and humidity.

Traditional protein-protein docking algorithms face significant limitations when handling flexible protein systems, particularly where conformational flexibility plays crucial roles in binding specificity. This study developed and validated a Coarse-Grained Cubic Orientation Approach (CG-COA) that systematically samples six cubic orientations combined with coarse-grained molecular dynamics simulations and MM/PBSA free energy calculations. As a local docking approach, CG-COA requires prior knowledge of putative bioactive surfaces and focuses computational resources on biologically relevant binding orientations. The methodology was validated using six protein complexes: four core systems (PDB codes: 2HD5, 1MIM, 3QML, 2MWS) representing diverse binding mechanisms, plus two extreme scenarios (2MZD: intrinsically disordered proteins; 2QCS-1RGS: large conformational changes). Benchmark comparisons against established docking methods (ZDOCK and ClusPro) evaluated relative performance across different system types. Results demonstrated robust performance with overall AUROC of 0.94, achieving F-scores up to 1.00 for well-defined systems. Benchmark analysis revealed system-dependent performance: significant advantages for flexible systems (3QML: 3.7-5.1-fold improvement over rigid-body methods) but inferior performance for rigid interfaces (2HD5: outperformed by conventional approaches). Extreme docking scenarios revealed clear method limitations with poor structural accuracy (RMSDs >13 Å), defining important applicability boundaries. The approach correctly diagnosed inherently flexible systems (2MWS) by not converging to single conformations. CG-COA addresses specific limitations of conventional protein-protein docking methods for systems with moderate conformational flexibility while clearly defining applicability boundaries. The methodology is unsuitable for extensive structural rearrangements or intrinsically disordered regions. The dual capability to identify native binding modes and diagnose flexibility provides valuable guidance for protein interaction studies.