Quantitative correlation of spectroscopic signatures with ligand–protein interactions in anti-cancer drug Afinitor: an integrated experimental–computational study

P Venkata Ramana; Rashmirekha Ram; Prasadarao Bobbili; Y Rama Krishna; Rabinarayan Panda; Shouri Dominic; Pratap Kumar Dakua; Siddharth Kumar

doi:10.1038/s41598-026-56242-w

. 2026 Jul 23;16:23078. doi: 10.1038/s41598-026-56242-w

Quantitative correlation of spectroscopic signatures with ligand–protein interactions in anti-cancer drug Afinitor: an integrated experimental–computational study

P Venkata Ramana ^1,^✉, Rashmirekha Ram ², Prasadarao Bobbili ³, Y Rama Krishna ¹, Rabinarayan Panda ⁴, Shouri Dominic ⁵, Pratap Kumar Dakua ⁶, Siddharth Kumar ^7,^✉

PMCID: PMC13396367 PMID: 42493535

Abstract

A detailed molecular-level understanding of anticancer drugs is essential for improving therapeutic efficacy and guiding rational drug design. Everolimus (Afinitor), a clinically important inhibitor of the mammalian target of rapamycin (mTOR) pathway, is widely used in cancer therapy; however, a quantitatively grounded relationship between its spectroscopic characteristics and ligand–protein interactions remains insufficiently explored. In this study, an integrated experimental–computational approach was employed, combining FT-IR spectroscopy, UV–Vis spectroscopy, and molecular docking simulations. Spectroscopic analyses were used to characterise functional groups and electronic structure, while docking simulations were performed to investigate interactions with FK506 binding protein (FKBP12) and the FKBP–rapamycin binding (FRB) domain. FT-IR analysis revealed a high density of oxygen-containing functional groups, including hydroxyl and carbonyl moieties, with vibrational frequencies indicative of a strongly polarised electronic environment. Molecular docking demonstrated favourable binding affinities with FKBP12 (− 9.7 and − 9.6 kcal·mol⁻¹) and the FRB domain (− 8.5 and − 6.6 kcal·mol⁻¹). Detailed interaction analysis showed that these functional groups correspond to specific interacting atoms (e.g., O66, O67, O63, and O36), forming quantifiable hydrogen bonds (1.7–2.9 Å) and electrostatic interactions (~ 4.37 Å) with key residues such as TYR82, THR85, and GLU54. The UV–Vis absorption maximum at 278 nm corresponds to a HOMO–LUMO energy gap of 4.46 eV, indicating moderate electronic polarizability that supports charge redistribution during binding. The study establishes a quantitative and mechanistically grounded structure–spectra–interaction relationship, demonstrating that spectroscopic observables encode the local electronic environment governing ligand–protein interaction propensity. Binding affinity is shown to arise from a cooperative network of multiple non-covalent interactions enabled by the spatial distribution of functional groups. This integrated framework provides predictive insight into drug–protein interactions and offers a robust foundation for the rational design and optimisation of mTOR-targeting therapeutics.

Keywords: FT-IR and UV–Vis, Afinitor, Immunosuppressant FK506, FKBP-Rapamycin binding domain, Molecular docking

Subject terms: Cancer, Chemistry, Computational biology and bioinformatics, Drug discovery

Introduction

Cancer remains one of the most significant global health challenges, accounting for millions of deaths each year and placing an increasing burden on healthcare systems worldwide. According to recent global cancer statistics, the incidence of cancer continues to rise due to population growth, ageing, and lifestyle-related risk factors. These trends highlight the urgent need for improved therapeutic strategies and a deeper molecular understanding of anticancer drugs currently used in clinical practice¹. In this context, investigations aimed at elucidating the structural and molecular interactions of established anticancer agents can contribute valuable insights for optimising drug performance and guiding the development of next-generation therapeutics. Among the various targeted anticancer therapies, inhibitors of the mammalian target of rapamycin (mTOR) signalling pathway have emerged as important therapeutic agents for the treatment of several malignancies. The mTOR pathway plays a central role in regulating cell growth, proliferation, metabolism, and survival. Dysregulation of this signalling pathway is commonly associated with the progression of various cancers, including renal cell carcinoma, breast cancer, and neuroendocrine tumours. Consequently, pharmacological inhibition of mTOR has become an important strategy in targeted cancer therapy.

Everolimus, commercially known as Afinitor, is a derivative of the macrolide compound sirolimus and functions as a potent inhibitor of the mTOR signalling pathway. The drug exerts its therapeutic effect through interaction with FK506 binding protein-12 (FKBP12), forming a complex that subsequently inhibits the activity of mTOR. This inhibition prevents the progression of cells from the G1 phase to the S phase of the cell cycle, thereby suppressing cellular proliferation. Owing to its mechanism of action, Everolimus has been widely used in the treatment of several malignancies and in the prevention of organ transplant rejection². Understanding the molecular interactions between anticancer drugs and their target proteins is crucial for improving therapeutic efficacy and minimising adverse effects. In recent years, in-silico computational techniques have become powerful tools in modern drug discovery and molecular pharmacology. Among these techniques, molecular docking simulations are widely employed to predict ligand–protein binding modes, estimate binding affinities, and identify key residues involved in molecular recognition. These computational approaches complement experimental techniques by providing atom-level insights into interaction mechanisms that are often difficult to observe directly through experimental methods alone.

In parallel with computational approaches, spectroscopic techniques play an essential role in characterising the structural and electronic properties of pharmaceutical compounds. Vibrational spectroscopic methods such as Fourier transform infrared (FT-IR) spectroscopy provide valuable information regarding the functional groups and molecular bonding present within a compound. Similarly, UV–Vis spectroscopy offers insight into electronic transitions and molecular orbital interactions, enabling estimation of important parameters such as energy gaps between frontier molecular orbitals. Together, these spectroscopic techniques contribute to a detailed understanding of the physicochemical properties of drug molecules.

Although the pharmacological activity and molecular structure of Everolimus are well established, studies that integrate spectroscopic characterisation with molecular docking-based interaction analysis of FKBP-associated targets remain relatively limited. Most previous investigations have focused primarily on pharmacological mechanisms or computational screening of potential inhibitors. However, the relationship between spectroscopically identified functional groups of the drug molecule and their specific roles in protein-binding interactions has received comparatively less attention. Establishing such correlations may provide additional insights into the molecular determinants governing drug–target recognition³.

In this context, the present study aims to provide an integrated experimental–computational investigation of the anticancer drug Afinitor (Everolimus) by combining FT-IR spectroscopy, UV–Vis spectroscopy, and molecular docking simulations. The spectroscopic analysis enables identification of characteristic functional groups and electronic transitions associated with the molecular structure of the drug, while the molecular docking analysis explores the interaction mechanisms between Everolimus and two biologically relevant targets, namely FKBP12 and the FKBP–rapamycin binding (FRB) domain. By correlating spectroscopic features with docking-derived interaction patterns, this study seeks to provide additional molecular-level insight into the structural features that govern ligand–protein interactions in the mTOR signalling pathway.

Significance of the study

The present work provides an integrated spectroscopic and computational analysis of Everolimus by correlating vibrational and electronic spectral features with ligand–protein interaction patterns obtained from molecular docking simulations. Such a combined experimental–computational approach offers deeper insight into the structural determinants governing the interaction of Everolimus with FKBP-associated protein targets. This framework may contribute to improved understanding of anticancer drug interactions and support future structure-guided optimisation of mTOR-targeting therapeutics.

Mechanism of action of Afinitor

Afinitor binds to FKBP-12, and it suppresses mTOR activity by inhibiting the activation of the (FKBP-12) immunophilin FK Binding Protein-12 in the cells. Inhibition of mTOR suppresses T cell activation and proliferation triggered by antigens and cytokines. When given to kidney and heart transplant patients, Afinitor lowers the risk of acute and chronic rejection⁴. In comparison to other immunosuppressants, this one has less nephrotoxicity. In addition to its immunosuppressive effects, Afinitor is a macrolide immunosuppressant that works in synergy with ciclosporin and inhibits vascular and bronchial smooth muscle cell proliferation⁵. In comparison to sirolimus, Afinitor has a superior pharmacokinetic profile since it is a hydroxyethyl derivative of sirolimus. Afinitor has greater bioavailability and a shorter half-life than sirolimus⁶. The Molecular formula of Afinitor is C53H83NO14_, 958.24 Da (Dalton), which is the Molecular mass, with a total of 151 atoms, and the structure is depicted in Fig. 1 and Fig. 2.

Fig. 1 — 2D Structural schematic representation of Afinitor.

Fig. 2 — 3D structural representation of the atomic view of Afinitor.

To fight different kinds of cancer, Afinitor was recently created as an antineoplastic agent. RCC and hormone receptor-positive breast cancer that has spread are also examples of this may all benefit from this drug when used in conjunction with patients with subependymal large cell astrocytomas treated with Exemestane, all of which are linked with tuberous sclerosis⁷. Many authorities have now authorised cancer patients who have had Afinitor for different kinds of cancer⁸. This medication comes with an unknown level of risk for side effects. Afinitor-induced cardiotoxicity was studied as an antineoplastic factor in patients who received the particular medication, and any potential antiatherogenic effects of systemic administration of the drug were evaluated^9,10. Everolimus, the main ingredient in Afinitor, may have certain unwanted side effects in addition to its necessary ones. Even though not all of these negative consequences are possible, if they develop, one should seek medical attention immediately to prevent more issues¹¹.

Materials and methods

Experimental details

Afinitor was kindly provided by Cipla Laboratories. It is employed in the measurement of the spectrum. The spectra of Perkin Elmer The Afinitor are recorded using two FTIR-ATR spectrophotometers with a resolution of less than 1 cm^-1 in the 4000–450 cm^-1 range¹². “A summary of the observed vibrational frequencies is provided in Table 1. The FT-IR spectra obtained through experimental analysis are presented in Figs. 3a and 3b. UV–visible absorption spectra were recorded using a PerkinElmer Lambda 35 UV/Vis DRS/DTS spectrophotometer in ethanol, covering a wavelength range of 190 to 1100 nm¹³. Figure 4 depicts the UV–Vis spectra of Afinitor.

Table 1.

Frequency, corresponding absorption, transmission (%), and functional group assignment of Afinitor.

S.No	Wavenumber (cm^-1)	Absorption	Transmission (%)	Functional group
1	3449	0.0337	92.54	υOH
2	3375	0.0401	91.18	υOH
3	3354	0.0414	90.91	υOH
4	3350	0.0414	90.9	υCH
5	3285	0.0487	89.4	υCH₃ss
6	2977	0.0193	95.66	υCH₃is
7	2955	0.0204	95.41	υCHmeln
8	2915	0.0252	94.35	υCHmeln
9	2902	0.0284	93.68	υCH₃os
10	2877	0.028	93.75	υCHmeln
11	2782	0.0177	96	υCHmeln
12	2698	0.0162	96.34	υCH
13	2653	0.0164	96.3	υCH
14	1654	0.0303	93.25	υC = O
15	1648	0.0297	93.38	υC = O
16	1578	0.0165	96.28	υC-O
17	1560	0.0158	96.44	υCC, βHCH
18	1475	0.0246	94.5	υCC, βCH
19	1449	0.0332	92.65	βCH₃ib, βCH₃ir
20	1419	0.0483	89.48	βCH₃ob, βCH₃or
21	1388	0.0298	93.37	βCH₂Rocking
22	1361	0.0345	92.36	υCC
23	1341	0.0386	91.49	βCH₂Twisting
24	1308	0.0382	91.58	βCH₂Scissoring
25	1288	0.0364	91.96	βNCH₂
26	1282	0.0364	91.96	βCH₂Rocking
27	1266	0.0347	92.31	υCN
28	1252	0.0419	90.81	βCOH
29	1225	0.0299	93.34	υCN
30	1210	0.0289	93.56	υCC ring
31	1191	0.0288	93.57	Ring bending
32	1159	0.0568	87.74	βCH₂Twisting
33	1115	0.0828	82.65	βCH₃ir
34	1095	0.102	79.07	υCC ring
35	1082	0.0801	83.16	βCH₃or
36	1068	0.138	72.78	υCC ring
37	1044	0.127	74.65	υCC
38	1033	0.1387	72.66	υCO
39	1018	0.1135	76.99	υCC ring
40	988	0.1088	77.83	υCC
41	948	0.0468	89.79	υCC ring
42	915	0.0327	92.74	Ring trigonal d
43	892	0.0582	87.46	ωCH
44	877	0.0537	88.37	βCH₂Wagging
45	833	0.0304	93.23	ωCH
46	811	0.0269	93.98	ωCH
47	808	0.027	93.98	τ Ring trigonal d
48	769	0.0602	87.06	ωCH
49	734	0.0551	88.09	Ring asym d
50	701	0.0601	87.08	Ring sym d
51	657	0.076	83.95	Ring torsion
52	631	0.0689	85.34	ωCCN
53	597	0.0912	81.07	ωCC
54	581	0.0886	81.55	τCCOH
55	552	0.0996	79.51	βOCO
56	536	0.0956	80.25	ωCC
57	518	0.0911	81.08	τCCOH
58	475	0.0869	81.86	βCCO
59	462	0.0897	81.34	τ Ring asym d

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“υ: Stretching, β: In-plane bending, ω: Out-of-plane bending, τ: Torsion, meln: Methylene, ss: symmetric stretching, is: in-plane stretching, os: out-of-plane stretching, ir: in-plane rocking or: Out-of-plane rocking, ib: in-plane bending, ob: Out-of-plane bending d: deformation sym d: Symmetric deformation, asym d: asymmetric deformation”.

Fig. 3 — (a) Absorption FT-IR spectrum of Afinitor, (b) Absorption FT-IR spectrum of Afinitor.

Fig. 4 — Absorption UV–Vis spectrum of Afinitor.

Molecular Docking Methodology

Molecular docking simulations were performed to investigate the interaction mechanisms between Afinitor (Everolimus) and two biologically relevant targets associated with mTOR signalling, namely the FK506 binding protein (FKBP12) and the FKBP–rapamycin binding (FRB) domain. The three-dimensional structures of the target proteins were retrieved from the Protein Data Bank (PDB) with accession codes 1FKL and 1AUE, respectively. These structures were selected based on their high crystallographic resolution, availability of ligand-bound conformations, and relevance to the biological mechanism of mTOR inhibition.

Prior to docking, protein preparation was performed using BIOVIA Discovery Studio Visualizer. All crystallographic water molecules and co-crystallised ligands not involved in the binding interaction were removed to avoid interference during docking. Polar hydrogen atoms were added to the protein structures, and Kollman charges were assigned. The prepared protein structures were then saved in the PDBQT format required for docking calculations.

The ligand structure of Afinitor (Everolimus) was obtained from the PubChem database and subsequently optimised using molecular modelling tools within Discovery Studio. Hydrogen atoms were added, and the ligand geometry was energy-minimised to obtain a stable conformational state before docking. The optimised ligand was then converted into the PDBQT format for compatibility with the docking software.

Molecular docking simulations were carried out using AutoDock Tools 1.5.6, which employs the Lamarckian Genetic Algorithm (LGA) to explore possible ligand conformations within the receptor binding pocket. In the docking protocol, the protein structure was treated as rigid while the ligand was considered flexible, allowing rotational freedom around its torsional bonds to identify the most favourable binding orientation.

The docking grid box was defined around the active site of the receptor protein to ensure that the search space covered the relevant binding pocket. The grid centre coordinates used for the docking calculations were x = 3.199382, y = 12.129956, and z = 13.313500, while the grid box dimensions were set to 20 Å × 20 Å × 20 Å along the x, y, and z axes, respectively. These parameters ensured sufficient coverage of the binding cavity while maintaining computational efficiency.

The docking calculations were performed using the Lamarckian Genetic Algorithm with standard parameters, including multiple docking runs to explore various ligand conformations. The resulting docking poses were ranked according to their predicted binding free energies. The conformation with the lowest binding energy and favourable interaction profile was considered the most stable binding mode.

To evaluate the reliability of the docking protocol, a re-docking validation procedure was performed. In this approach, the co-crystallised ligand present in the original PDB structure was removed and subsequently re-docked into the same binding site. The predicted pose was then compared with the experimentally determined crystal structure using the root mean square deviation (RMSD) metric. An RMSD value below 2.0 Å was obtained, confirming the reliability and accuracy of the docking procedure used in this study.

The resulting ligand–protein complexes were analysed using BIOVIA Discovery Studio Visualizer, which enabled visualisation of hydrogen bonds, electrostatic interactions, hydrophobic contacts, and π–π stacking interactions between Afinitor and the amino acid residues of the target proteins. Both two-dimensional and three-dimensional interaction diagrams were generated to better understand the molecular interactions responsible for binding stability.

The docking results, including binding affinities, RMSD values, and interaction patterns, were further analysed to identify key residues involved in stabilising the ligand–protein complex. These interactions provide insight into the molecular basis of Afinitor’s inhibitory activity against mTOR-associated proteins.

Results and discussion

FT-IR Spectrum analysis of Afinitor

Standard investigations of Afinitor’s FT-IR spectra present that the anti-cancer medication is organised into various functional groups. The Afinitor’s OH stretching groups correspond to its FT-IR frequencies of 3449, 3375, and 3354 cm^-1, which have been displayed to have a significant absorption zone¹⁴. The cancer medication’s FT-IR spectra show the stretching groups of CH as bands 3350, 2698, and 2653 cm^-1 in the infrared spectrum. The CH3os stretching mode was given a frequency of 2902 cm^-1, the CH3ss (Symmetric Stretching) stretching mode a wavenumber band of 3285 cm^-1, and the CH3is stretching mode a wavenumber band of 2977 cm^-1 ¹⁵. The bands 2955, 2915, 2877, and 2782 cm^-1 in Afinitor’s infrared spectra are characterised as the "CHmeln stretching vibrational modes."¹⁶. In Afinitor’s infrared spectrum, the C = O mode, one C-O mode, and the two C = O stretching modes are assigned frequency bands of 1578 and 1654, 1648 cm^-1, respectively¹⁷. In Afinitor’s FT-IR spectrum, the VC–C vibration is observed at 1361 cm⁻1, while the bending of βCH and βHCH is identified at 1560 cm⁻1 and 1475 cm⁻1, respectively¹⁸. When examining the infrared spectra of the cancer agent in question, the modes of in-plane bending, CH3ib and CH3ir, were assigned to 1449 cm^-1. Additionally, the 1419 cm^-1 found in Afinitor’s "FT-IR spectra" was attributed to βCH3ob and βCH3or, respectively¹⁹. Afinitor’s CH2 rocking modes may be explained by the 1388 and 1282 cm^-1 wavenumber bands in the molecule’s infrared spectra. In the IR spectrum, it was found that the bands with frequencies 1341 and 1159 cm^-1 were CH2Twisting modes. In the infrared spectrum, the βCH2, or CH2Scissoring, has been found at a wavenumber of 1308 cm^-1 ²⁰. The βNCH2 was given a wavenumber area of 1288 cm^-1, which is consistent with Afinitor’s FT-IR spectrum. Specifically, the βCOH has a wavenumber of 1252 cm^-1, whereas the C-N stretching modes have wavenumbers of 1266 and 1225 cm^-1. According to Afinitor’s peak assimilation, the anti-cancer drug’s νC-C was associated with the bands of 1210, 1095, 1068, 1018, and 948 cm^-1 in "the IR spectrum," while Afinitor’s νC-C was linked to the ranges of 1044 and 988 cm^-1 ²¹. The findings indicate that the wavenumbers 915, 734, 701, and 657 cm^-1 correspond to the ring trigonal deformation, symmetric, asymmetric deformations, and torsion modes. The out-of-plane bending modes (ω) of Afinitor have been identified as the ωCH in the frequency regions 892, 833, and 769 cm^-1 of the “IR spectrum” βCH2 wagging may be attributed to the frequency of 877 cm^-1, whereas the Ring Trigonal deformation was attributed to the frequency of 808 cm^-1²². Two ωCCs, severally, with wavenumbers of 597 cm^-1 and 536 cm^-1 ²³. Afinitor’s FT-IR spectra, which are ascribed to ωCCN, have a frequency of 631 cm^-1 ⁴⁷. According to Afinitor’s IR spectrum, the drug’s torsions τCCOH belong to wavenumbers 581 and 518 cm^-1. Afinitor’s infrared spectra showed in-plane bending and torsion modes at frequencies of 552, 475, and 462 cm^-1. These modes were found to match the βOCO, βCCO, and ring-bending torsion modes of the cancer drug’s molecule²⁴.

Electron absorption spectra

The UV–Vis absorption spectra of Afinitor were obtained using a PerkinElmer LAMBDA 35 UV/Vis DRS spectrophotometer, operating within a wavelength range of 190–1100 nm and a spectral bandwidth of 0.5 to 4 nm. As shown in Fig. 4, Afinitor’s UV–Vis spectrum was obtained.” In molecular orbital theory, the primary absorption band of a compound is attributed to the promotion of an electron from the highest energy orbital containing electrons (HOMO) to the lowest energy orbital that remains vacant (LUMO). These transitions account for the optical absorption properties observed in a molecule²⁵. An excited state is produced when electrons in the molecule shift from the HOMO to the LUMO in response to light absorption. Certain wavelengths in "the absorption spectrum" correlate to the energy required for this transformation²⁶. One important determinant of a molecule’s electrical structure is the “HOMO–LUMO gap”. When the gap is smaller, the molecule is more susceptible to lower-energy radiation as electronic transitions need less energy²⁷. The energy needed for internal charge transfer between the molecule’s electron-donating and electron-accepting groups can be observed by the HOMO–LUMO gap in conjugated compounds. The creation of organic materials for optoelectronic devices is based on this principle. The equation provides the energy-wavelength relationship in quantum mechanics.

The energy E in electron-volts (eV) can be obtained from Eq. (2), where the wavelength λ is given in nanometers (nm). This calculation incorporates the fundamental constants: (Speed of light in freespace) c = 3 × 10⁸ m/s, (Planck’s constant) h = 6.625 10^–34 Js, and conversion factor (6.242 × 10¹⁸ eV = 1 Joule) have been entered.

Electron redistribution among these orbitals plays a decisive role in defining the electronic properties of the molecule, a factor of significant relevance to various technological applications. The calculated energy gap associated with this electronic transition is 4.4601 eV, while the corresponding absorption maximum, depicted in Fig. 4, is observed at a wavelength of 278 nm²⁸.

Molecular docking analysis

Molecular docking simulations were performed to investigate the interaction of Afinitor with two key mTOR-associated targets, FK506 binding protein (FKBP12; PDB ID: 1FKL) and the FKBP–rapamycin binding (FRB) domain (PDB ID: 1AUE). The docking results revealed energetically favourable binding conformations with high binding affinities, indicating strong ligand–protein interactions. The best docking poses exhibited binding affinities of − 9.7 and − 9.6 kcal·mol⁻¹ for FKBP12, and − 8.5 and − 6.6 kcal·mol⁻¹ for the FRB domain, indicating a stronger interaction preference for FKBP12.

Predicting two molecules’ binding affinities and preferences with precision is one of the trickiest elements of docking. Using docking algorithms that assess the binding affinities at different receptor binding sites in different ligand poses yields the optimal docking solutions. After determining the best kind of binding (in this case, solely proteins) between a ligand and its macromolecular partner, the best docking solution is chosen from a range of sites. Consequently, a vast array of distinct positions for the ligand in a range of patterns and orientations (or poses) must be created inside the protein’s binding site. The current study used molecular docking with the FKBP-Rapamycin Binding Domain and the FK506 binding protein^29,30. The Protein Data Bank (RCSB) provided the structural database for the target proteins 1FKL and 1AUE, respectively³¹ (Figs. 5, 6, 7).

Fig. 5 — (**a, b**) Hydrogen Bond and Ramachandran plot of Afinitor docking interaction.

Fig. 6 — (a) 2D layout of Afinitor docking interaction in pose -1, (b) 3D layout of Afinitor docking interaction in pose -1, (c) 3D surface layout of Afinitor docking interaction in pose -1.

Fig. 7 — (a) 2D layout of Afinitor docking interaction in pose -2, (b) 3D layout of Afinitor docking interaction in pose -2, (c) 3D surface layout of Afinitor docking interaction in pose -2.

The structural quality of the target proteins was validated using Ramachandran plot analysis, confirming that the majority of residues lie within allowed regions, indicating reliable protein conformations for docking studies (Figs. 5a, 5b and 8a, 8b). All residues are accessible within the permitted range, as the graphs show. The 1FKL and 1AUE target proteins were used in Afinitor molecular docking studies utilising the Discovery Studios software AutoDock Tools 1.5.6 and BIOVIA^32–35. The ligand–target associations were observed in two distinct conformational orientations, exhibiting binding free energies of –9.7 and –9.6 kcal·mol⁻1 for one protein, and –8.5 and –6.6 kcal·mol⁻1 for the other. These interaction conformations are illustrated in Figs. 6(a–c), 7(a–c), 9(a–c), and 10(a–c) for the respective target proteins.

Fig. 8 — (a), (b): Hydrogen Bond and Ramachandran plot of Afinitor docking interaction with FKBP-Rapamycin Binding Domain.

Fig. 9 — (a) 2D layout of Afinitor docking interaction in pose -1 with FKBP-Rapamycin Binding Domain Green: Hydrogen Bond, Saffron: Electrostatic, Pink: Pi –Pi Stacked, Pale pink: Alkyl (b): 3D layout of Afinitor docking interaction in pose -1 with FKBP-Rapamycin Binding Domain (c) 3D surface layout of Afinitor docking interaction in pose -1 with FKBP-Rapamycin Binding Domain.

Fig. 10 — (a) 2D layout of Afinitor docking interaction in pose -2 with FKBP-Rapamycin Binding Domain, (b) 3D layout of Afinitor docking interaction in pose -2 with FKBP-Rapamycin Binding Domain, (c) 3D surface layout of Afinitor docking interaction in pose -2 with FKBP-Rapamycin Binding Domain.

The binding affinity values obtained for Everolimus (− 9.7 and − 9.6 kcal·mol⁻1) are comparable to those of previously reported mTOR inhibitors such as sirolimus and temsirolimus. These results suggest that Everolimus exhibits strong interaction with FKBP12, consistent with its known pharmacological activity.

Comprehensive details regarding the spatial orientation and docking coordinates of the ligand–protein complexes are compiled in Tables 2, 3, 4, 5, encompassing RMSD values and the spectrum of intermolecular contacts, including atom-specific and epitope-level interactions. Owing to its comparatively low binding free energy, the molecule demonstrates strong potential as an anti-hypercoagulant agent and engages in the formation of a stable non-covalent interaction with Rotamase (FKBP12–Rapamycin), an immunophilin-associated immunosuppressive complex¹⁷. Oxygen atoms formed the greatest number of associations with the target in the Afinitor docking simulations with the FK506 binding protein (PDB ID: 1FKL). Three hydrogen (conventional) bonds are formed between the element O66 and 1FKL(A:ALA84:HN), 1FKL(A:THR85:HN), and 1FKL(A:THR85:HG1). A hydrogen (conventional) bond is formed between the atoms O67 and O63 with 1FKL (A: TYR82:HH and A: THR85:HG1, respectively)^45,46.

Table 2.

Molecular docking investigation data of Pose-1 of Afinitor with FK506 binding protein (PDB ID: 1FKL).

S.No			From	To	Bond distance(Å)
1	Electrostatic	Attractive Charge	Afinitor ( O36) + ve	1FKL(A:GLU54:OE2) -ve	4.37
2	H-Bond	Conventional	1FKL (A:TYR82:HH)	Afinitor (O67)	1.72
3	H-Bond	Conventional	1FKL(A: ALA84:HN)	Afinitor (O66)	2.51
4	H-Bond	Conventional	1FKL(A:THR85:HN)	Afinitor (O66)	1.93
5	H-Bond	Conventional	1FKL(A: THR85:HG1)	Afinitor (O63)	2.88
6	H-Bond	Conventional	1FKL(A:THR85:HG1)	Afinitor (O66)	1.99
7	H-Bond	Carbon	1FKL(A:GLU54:CA)	Afinitor (O37)	3.55
8	H-Bond	Carbon	1FKL(A:GLU54:CA)	Afinitor (O39)	3.68
9	H-Bond	Pi-Donor	Afinitor (O40)	1FKL(A:HIS87)	3.17
10	H-Bond	Pi-Donor	Afinitor (O11)	1FKL(A:HIS87)	3.71

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H-Bond: Hydrogen Bond, Please refer to Fig. 1 and Fig. 2 for numbering of atoms.

(Binding Energy -9.7 kcal/mol, RMSD l.b = 0.00 Å, RMSD u.b = 0.00 Å).

Table 3.

Molecular docking investigation data of Pose-2 of Afinitor with FK506 binding protein (PDB ID: 1FKL).

S.No	Category	Bond Type	From	To	Bond distance(Å)
1	Electrostatic	Attractive Charge	Afinitor ( O36) + ve	1FKL(A:GLU54:OE2) -ve	4.72
2	H-Bond	Conventional	1FKL (A:TYR82:HH)	Afinitor (O67)	2.07
3	H-Bond	Conventional	1FKL(A: ALA84:HN)	Afinitor (O66)	2.49
4	H-Bond	Conventional	1FKL(A:THR85:HN)	Afinitor (O66)	2.10
5	H-Bond	Conventional	1FKL(A: THR85:HG1)	Afinitor (O63)	2.90
6	H-Bond	Conventional	1FKL(A:THR85:HG1)	Afinitor (O66)	2.11
7	H-Bond	Carbon	Afinitor (O37)	1FKL (A: TYR82: O)	3.11
8	H-Bond	Carbon	1FKL(A:HIS87:CD2)	Afinitor (O41)	3.34
9	H-Bond	Pi-Donor	Afinitor (O67)	1FKL(A:HIS87)	2.90
10	H-Bond	Pi-Donor	Afinitor (O41)	1FKL(A:TYR82)	3.98

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H-Bond: Hydrogen Bond, Please refer to Fig. 1 and Fig. 2 for numbering of atoms.

(Binding Energy -9.6 kcal/mol, rmsd l.b = 0.97 Å, rmsd u.b = 1.18 Å).

Table 4.

Molecular docking investigation data of Pose-1 of Afinitor with FKBP-Rapamycin Binding Domain (PDB ID: 1AUE).

S.No			From	To	Bond distance(Å)
1	Electrostatic	Attractive Charge	Afinitor ( N4) + ve	1AUE (A:GLU2060:OE2) –ve	4.78
2	H-Bond	Conventional	Afinitor (H134)	1AUE (A:GLU2060:OE2)	2.09
3	H-Bond	Conventional	Afinitor (H134)	Afinitor (O39)	2.48
4	H-Bond	Conventional	Afinitor (H149)	1AUE (A:GLU2060:OE2)	2.63
5	H-Bond	Conventional	Afinitor (H145)	Afinitor (O66)	2.08
6	H-Bond	Conventional	Afinitor (H150)	Afinitor (O41)	1.63

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H-Bond: Hydrogen Bond, Please refer to Fig. 1 and Fig. 2 for numbering of atoms.

(Binding Energy -8.5 kcal/mol, RMSD l.b = 0.00 Å, RMSD u.b = 0.00 Å).

Table 5.

Molecular docking investigation data of Pose-2 of Afinitor with FKBP-Rapamycin Binding Domain (PDB ID: 1AUE).

S.No			From	To	Bond distance(Å)
1	H-Bond	Conventional	1AUE (A:ARG2087:HE)	Afinitor (O11)	2.52
2	H-Bond	Conventional	1AUE (A:ARG2087:HE)	Afinitor (O61)	2.27
3	H-Bond	Conventional	Afinitor (H54)	IAUE(A:GLU2053:OE2)	2.10
4	H-Bond	Conventional	Afinitor (H152)	1AUE (A:GLU2053:OE2)	2.66
5	H-Bond	Conventional	Afinitor (H152)	Afinitor (O68)	2.53
6	H-Bond	Conventional	Afinitor (H152)	Afinitor (O63)	2.13
7	H-Bond	Carbon	Afinitor (H153)	Afinitor (O41)	1.70

Open in a new tab

H-Bond: Hydrogen Bond, Please refer to Fig. 1 and Fig. 2 for numbering of atoms.

(Binding Energy -6.6 kcal/mol, RMSD l.b = 1.98 Å, RMSD u.b = 2.90 Å).

The target FK506 binding protein (PDB ID: 1FKL) has atoms O37 and O39 that form hydrogen (carbon) bonds with 1FKL (A:GLU54:CA) and 1FKL (A:GLU54:CA), respectively. The persistence of the ligand–receptor interaction is largely dictated by the formation of specific non-covalent forces, wherein hydrogen atoms engage with negatively polarised regions of the receptor’s molecular architecture. O36 and 1FKL (A:GLU54:OE2) establish an electrostatic connection through interactions between the ligand’s electron-rich pi-system and the receptor’s anions. One hydrogen (Pi-Donor) bond is formed by the atom O40⁴⁸. Pi-Donor interactions help stabilise the hydrogen bond with 1FKL(A:HIS87) by interacting between the ligand’s pi-electron cloud and the receptor’s sigma electron cloud. One hydrogen (Pi-Donor) bond is formed by the atom O11. Pi-donor interactions help stabilise the hydrogen bond with 1FKL(A:HIS87) of the target FK506 binding protein (PDB ID: 1FKL) in pose-1 by interacting between the ligand’s pi-electron cloud and the receptor’s sigma electron cloud²⁶.

Oxygen atoms formed the greatest number of associations with the target in the Afinitor docking evaluation with the FK506 binding protein (PDB ID: 1FKL). Three hydrogen (conventional) bonds are formed by the element O66 with 1FKL(A:ALA84:HN), 1FKL(A:THR85:HN), and 1FKL(A:THR85:HG1). A hydrogen (conventional) bond is formed between the atoms O67 and O63 with 1FKL (A:TYR82:HH and A: THR85:HG1, respectively). The target FK506 binding protein (PDB ID: 1FKL) has two hydrogen (carbon) bonds: one with atom O37 (A: TYR82: O) and another with atom O41 (A:HIS87:CD2). The formation of hydrogen bonds, involving hydrogen atoms and electronegative sites on the receptor, is crucial for maintaining the structural stability of the ligand–receptor complex. O36 and 1FKL (A:GLU54:OE2) establish an electrostatic connection through interactions between the ligand’s electron-rich pi-system and the receptor’s anions. One hydrogen (Pi-Donor) bond is formed by the atom O67. Pi-Donor interactions help stabilise the hydrogen bond with 1FKL(A:HIS87) by interacting between the ligand’s pi-electron cloud and the receptor’s sigma electron cloud. In pose-2, π-donor interactions—arising from the ligand’s π-electron cloud engaging with the receptor’s σ-electron cloud—contribute to the stabilisation of a hydrogen bond with the HIS87 residue (chain A) of the FK506 binding protein (PDB ID: 1FKL)⁴⁹. The atom O41 forms one hydrogen (Pi-Donor) bond. The binding strength and selectivity of Afinitor toward the FK506 binding protein are primarily influenced by the molecular interactions between them. Understanding these chemical interactions is crucial for the creation of new drugs and for the reasonable modification of existing ligands to improve their ability to target certain disease-causing proteins. The discipline of pharmacology and drug discovery is eventually advanced by these molecular discoveries, which aid in the creation of new medications with improved specificity, potency, and minimal adverse effects³⁵.

The nitrogen N4 atom formed an electrostatic interaction with 1AUE (A:GLU2060:OE2), according to Afinitor’s docking examinations with the target FKBP-Rapamycin Binding Domain (PDB ID: 1AUE). The target’s 1AUE (A: GLU2060:OE2) is formed by the atom H134 in a conventional hydrogen bond, Afinitor O39 in a conventional hydrogen bond, and the target’s 1AUE (PDB ID: 1AUE) in a conventional hydrogen bond. Pose 1 shows that the atoms H145 and H150, respectively, establish typical hydrogen bonds with Afinitor O66 and O41⁵⁰. The stability of the ligand–receptor complex is largely maintained through hydrogen bonding, which involves interactions between the receptor electronegative atoms and hydrogen atoms from the ligand. O11 and O61 atoms establish conventional hydrogen bonds with 1AUE (A:ARG2087:HE) and 1AUE (A:ARG2087:HE), respectively, based on Afinitor’s docking studies with the target FKBP-Rapamycin Binding Domain (PDB ID: 1AUE). The target’s 1AUE (A:GLU2053:OE2) and the H54 atom form an ordinary hydrogen bond (PDB ID: 1AUE). An ordinary hydrogen bond is formed between the atoms H152 and 1AUE (A:GLU2053:OE2). With Afinitor O68 and O63, atom H152 forms two conventional internal hydrogen bonds, and with Afinitor O41 in pose-2, atom H153 forms a conventional internal hydrogen bond. The persistence of the ligand–receptor interaction is largely dictated by the formation of specific non-covalent forces, wherein hydrogen atoms engage with negatively polarised regions of the receptor’s molecular architecture³⁶.

A consolidated overview of the hydrogen-bonding patterns identified within the functional receptor structures is presented in Tables 2, 3, 4, and 5. After binding to FKBP-12, Afinitor suppresses mTOR activity by inhibiting the activation of “the immunophilin FK Binding Protein-12 (FKBP-12)” in the cells. As a result, a pharmacological complex inhibiting mTOR activity is formed. Cells can’t go from the G1 to the S phase because the downstream effectors are less active as a result of this suppression, which causes a growth arrest and eventual cell death. The research on Afinitor’s docking process has been pivotal in pinpointing the specific regions where it interacts with FKBP-12, shedding light on its unique mechanisms within cancerous cells. The combined contribution of hydrogen bonding, electrostatic interactions, and hydrophobic contacts results in a stable ligand–protein complex. The stronger binding affinity observed for FKBP12 compared to the FRB domain suggests preferential interaction, consistent with the known mechanism of Everolimus. Overall, the docking results demonstrate that the interaction of Everolimus with mTOR-associated proteins is governed by a network of complementary non-covalent interactions. These findings provide a structural basis for its inhibitory activity and form the foundation for the mechanistic correlation developed in Section "Quantitative correlation between spectroscopic signatures and ligand–protein interactions".

These findings hold immense promise for advancing drug development. By focusing on precise adjustments within existing anticancer medications, this study provides valuable insights into the regulatory and reciprocating residues involved. These insights carry the potential to minimise unwanted side effects and fine-tune the drug’s functions. These targeted modifications may enhance the drug’s selectivity and its ability to bind to specific targets, ultimately amplifying its efficacy in cancer treatment. These innovative discoveries are paving the way for the development of safer and more potent drugs, presenting patients with improved and customised options for managing complex medical conditions⁵¹.

Functional group analysis of Afinitor

The chemical structure of Afinitor explains the importance of its functional groups. Specific atom configurations inside molecules, known as chemical functional groups, control a molecule’s chemical behaviour. Afinitor’s chemical structure includes a number of significant functional groups that support both its pharmacological activity and its interactions with the body. A macrocyclic lactone ring, or big cyclic ester, is present in Afinitor. The drug’s capacity to attach to its target, mTOR, and suppress its activity depends on this structural motif. For the medication to inhibit the mTOR pathway specifically and effectively, its macrocyclic structure is essential³⁷.

The hydroxy group (–OH)

Afinitor (everolimus) functions as an mTOR inhibitor, and one important part of this process is the hydroxy group (–OH) functional group. Here’s how Afinitor works better because of the hydroxy group. Afinitor’s hydroxy group has the ability to establish hydrogen bonds with a variety of compounds, including bodily proteins and enzymes. In biological systems, hydrogen bonding is an essential intermolecular force. Hydrogen bonding interactions between the hydroxy group and certain amino acid residues in the mTOR protein’s active site may happen in the setting of Afinitor. These interactions boost Afinitor’s potential to bind to mTOR by stabilising the drug-protein complex³⁸. In water and other biological fluids, a molecule’s solubility can be affected by the presence of hydroxy groups in it. The hydroxy groups included in Afinitor have the potential to enhance its solubility, therefore guaranteeing the drug’s efficient administration and distribution throughout the body. For the medication to reach its target areas and have the desired pharmacological effects, it must be sufficiently soluble³⁹. Phase II metabolism, namely glucuronidation, a process wherein the drug and glucuronic acid are conjugated to aid in the drug’s excretion from the body, may incorporate hydroxy groups. The drug’s pharmacokinetics, especially its clearance rate, may be impacted by its metabolism. Determining the drug’s dosage and length of effect requires an understanding of the metabolic pathways involving hydroxy groups⁴⁰. Hydroxy groups are adaptable and may be chemically changed to produce derivatives with various characteristics. By creating analogues or prodrugs, medicinal chemists can make use of Afinitor’s hydroxy group and perhaps improve the drug’s bioavailability, tissue-specific targeting, or effectiveness. Afinitor’s hydroxy group plays a crucial role in its solubility, metabolism, interactions with biological molecules, and potential for chemical modification. All of these elements work together to make Afinitor a successful treatment for a variety of malignancies and other disorders by blocking the mTOR pathway⁴¹.

The carbonyl group (C = O)

Afinitor’s (everolimus) carbonyl group (C = O) functional group is important to its mTOR inhibitory mode of action. Here’s how Afinitor works better because of the carbonyl group. Owing to the difference in electronegativity between carbon and oxygen, the group exhibits polarity. This characteristic enables it to participate in hydrogen bonding and other polar interactions with target biomolecules. Afinitor’s carbonyl group engages with specific amino acid residues within the mTOR protein’s active site, thereby enhancing the drug’s target-binding affinity. The neighbouring carbon atom is somewhat positive because the oxygen atom in the carbonyl group is electron-withdrawing. Because of this electron shortage, the carbon atom is more electrophilic and vulnerable to nucleophilic assault. This characteristic may be crucial for processes involving enzymes and other biological molecules in biological systems⁴². The Afinitor molecule is more stable when the carbonyl group is present. Carbonyl groups are generally stable under physiological conditions, ensuring that the drug remains intact and active in the body, allowing it to exert its therapeutic effects. Several metabolic processes can occur in the carbonyl group, including oxidation. Determining the drug’s metabolism, rate of clearance, and duration of action in the body requires an understanding of the metabolic pathways involving the carbonyl group. The carbonyl group can be broken down to produce metabolites, which may differ from the original chemical in terms of pharmacological characteristics⁴³. Medicinal chemists can exploit the chemical reactivity of the carbonyl group to design structural analogues or derivatives of Afinitor. The creation of prodrugs or other formulations with modified pharmacokinetic characteristics, bioavailability, or tissue-specific targeting can result from chemical changes in the carbonyl group. Afinitor’s carbonyl group is necessary for its stability, metabolism, capacity to change chemically, and interactions with biological molecules. All of these elements work together to make Afinitor a successful treatment for a variety of malignancies and other ailments by blocking the mTOR pathway⁴⁴, ⁵².

An important aspect of the present work is the integration of spectroscopic characterisation with molecular docking analysis. The FT-IR spectra identified several oxygen-containing functional groups, including hydroxyl and carbonyl moieties, which are known to participate in hydrogen bonding interactions. Interestingly, the docking simulations revealed that these same oxygen atoms play a dominant role in stabilising the ligand–protein complex through hydrogen bonding with key residues such as TYR82, THR85, and GLU54 of the FKBP12 binding site.

This correlation between spectroscopically identified functional groups and the observed docking interactions provides a structural rationale for the binding behaviour of Afinitor. Such combined spectroscopic–computational analysis offers additional insight into the molecular determinants of binding that may not be evident from docking studies alone.

Quantitative correlation between spectroscopic signatures and ligand–protein interactions

To establish a mechanistically grounded relationship between spectroscopic observables and ligand–protein binding behaviour, the vibrational and electronic properties of Everolimus were quantitatively correlated with docking-derived interaction parameters. The underlying premise is that spectroscopic features encode the local electronic environment of functional groups, which directly governs their interaction propensity within the protein binding pocket.

Vibrational frequency as a descriptor of interaction potential

The FT-IR spectrum of Everolimus reveals prominent vibrational modes associated with hydroxyl (νOH: 3449–3354 cm⁻¹) and carbonyl (νC = O: 1654–1648 cm⁻¹) functional groups. These vibrational frequencies are sensitive to the local electron density and bond polarity, which in turn influence hydrogen-bond donor/acceptor strength.

A reduction in vibrational frequency (red shift) is generally associated with increased bond polarisation and enhanced hydrogen-bonding capability. Accordingly, the observed νOH and νC = O bands indicate the presence of strongly polarised oxygen-containing groups capable of forming stabilising interactions with polar amino acid residues.

This relationship can be expressed conceptually as:

where Inline graphic represents the deviation in vibrational frequency, denotes local electron density, and corresponds to the interaction strength. This establishes vibrational frequency as an indirect descriptor of interaction potential⁵³,⁵⁴.

Atom-resolved correlation between functional groups and binding interactions

A direct correspondence is observed between spectroscopically identified functional groups and atom-level interactions obtained from docking simulations. Oxygen atoms associated with νOH and νC = O modes (e.g., O66, O67, O63, O36) participate in hydrogen bonding and electrostatic interactions with key residues such as TYR82, THR85, and GLU54. The quantitative correspondence between spectroscopic features and interaction parameters is summarised in Table 6.

Table 6.

Quantitative structure–spectra–interaction correlation in Afinitor (Everolimus}.

Functional Group	FT-IR Band (cm⁻¹)	Atom	Residue	Distance (Å)	Interaction Type
–OH	3449–3354	O66	THR85	1.93	H-bond
–OH	3449–3354	O67	TYR82	1.72	H-bond
–OH	3449–3354	O63	THR85	2.88	H-bond
C = O	1654–1648	O36	GLU54	4.37	Electrostatic
C = O	1654–1648	O37/O39	GLU54	3.55–3.68	H-bond (carbon)

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H-Bond: Hydrogen Bond, Please refer to Fig. 1 and Fig. 2 for numbering of atoms.

These results demonstrate that the functional groups identified through FT-IR spectroscopy are not merely structural descriptors but correspond directly to the active interaction sites responsible for binding. The short hydrogen bond distances (1.7–2.9 Å) further confirm the strength and specificity of these interactions ⁵⁵, ⁵⁶.

Cooperative interaction network and binding energetics

The spatial distribution of oxygen-containing functional groups within the macrocyclic framework of Everolimus enables the formation of multiple simultaneous interactions. Rather than a single dominant interaction, binding stability arises from a cooperative network of hydrogen bonds, electrostatic interactions, and π-associated contacts.

The total binding free energy Inline graphic can therefore be interpreted as the cumulative contribution of individual non-covalent interactions:

The observed binding affinities (− 9.7 and − 9.6 kcal·mol⁻¹ for FKBP12) are consistent with such a multi-point stabilisation mechanism, where individually moderate interactions collectively produce a strong overall binding effect⁵⁷, ⁵⁸.

Electronic structure contribution from UV–Vis spectroscopy

The UV–Vis absorption peak at 278 nm corresponds to a HOMO–LUMO energy gap of 4.46 eV, indicating moderate electronic stability combined with sufficient polarizability. This electronic structure facilitates charge redistribution during ligand–protein interaction, enhancing both hydrogen bonding and electrostatic contributions.

Thus, the HOMO–LUMO gap provides an additional descriptor linking spectroscopic properties to interaction behaviour, particularly in terms of electronic adaptability within the binding environment.

Integrated structure–spectra–interaction framework

The combined analysis establishes a direct and quantitative structure–spectra–interaction relationship:

Spectroscopy (FT-IR, UV–Vis) → probes electronic structure and functional group polarity
Electronic structure → determines interaction propensity
Docking interactions → realise these propensities as measurable binding geometries and energies

This integrated framework demonstrates that spectroscopic observables can serve as predictive indicators of ligand–protein interaction behaviour, thereby providing a mechanistically grounded bridge between experimental characterisation and computational modelling ⁵⁹, ⁶⁰.

Study limitations

Although the present study provides useful insights into the spectroscopic characteristics and molecular docking interactions of Afinitor, several limitations should be acknowledged. The computational investigation in this work was limited to molecular docking simulations, which provide a static representation of ligand–protein interactions and may not fully capture the dynamic behaviour of the complexes under physiological conditions. Advanced computational techniques such as molecular dynamics simulations and free energy calculations could further validate the stability and energetics of the predicted binding modes. In addition, while FT-IR and UV–Vis spectroscopy provide valuable information regarding the functional groups and electronic transitions of the molecule, the present study does not include complementary experimental techniques such as NMR spectroscopy or biological assays that could provide additional validation of the interaction mechanisms. Future studies incorporating molecular dynamics simulations, experimental binding assays, and structure–activity relationship analyses would further enhance the understanding of Afinitor’s molecular interactions with mTOR-associated targets.

Future research directions

Future research will focus on extending the present spectroscopic and computational investigation of Afinitor toward a deeper understanding of its interaction mechanisms with mTOR-associated targets. In particular, advanced computational approaches such as molecular dynamics simulations and free energy calculations could be employed to evaluate the stability of the predicted ligand–protein complexes under physiological conditions. Additionally, structure–activity relationship studies and rational modification of functional groups identified in the spectroscopic analysis may help in designing improved Everolimus analogues with enhanced binding affinity and reduced adverse effects. Experimental validation through biochemical assays and cellular studies will further clarify the therapeutic potential of these interactions and support the development of optimised mTOR-targeting anticancer agents.

Conclusion

This study presents a comprehensive experimental–computational investigation of the anticancer drug Everolimus (Afinitor) by integrating FT-IR spectroscopy, UV–Vis spectroscopy, and molecular docking simulations to elucidate its ligand–protein interaction mechanisms at a molecular level.

The spectroscopic analysis revealed a high density of oxygen-containing functional groups, particularly hydroxyl and carbonyl moieties, whose vibrational signatures reflect a strongly polarised electronic environment. These spectroscopic features were shown to directly correspond to atom-specific interaction sites identified in docking simulations, where oxygen atoms (e.g., O66, O67, O63, and O36) participate in quantitatively characterised hydrogen bonding (1.7–2.9 Å) and electrostatic interactions (~ 4.37 Å) with key residues such as TYR82, THR85, and GLU54.

Importantly, the present work establishes a quantitative structure–spectra–interaction relationship, demonstrating that vibrational frequencies serve as indirect descriptors of local electron density and interaction propensity. This relationship provides a mechanistic basis for understanding how spectroscopically identified functional groups govern ligand–protein binding behaviour. The observed binding affinities (− 9.7 and − 9.6 kcal·mol⁻¹ for FKBP12) arise from a cooperative network of multiple non-covalent interactions, rather than a single dominant interaction, highlighting the role of multi-point stabilisation in molecular recognition.

Furthermore, the UV–Vis-derived HOMO–LUMO energy gap (4.46 eV) indicates moderate electronic polarizability, facilitating charge redistribution during binding and thereby supporting the observed electrostatic and hydrogen-bonding interactions. This establishes electronic structure as an additional link connecting spectroscopic observables to interaction energetics.

Overall, this study advances beyond conventional docking analyses by introducing a mechanistically grounded and quantitatively supported framework that bridges experimental spectroscopy and computational interaction analysis. The proposed structure–spectra–interaction paradigm demonstrates that spectroscopic measurements can provide predictive insight into ligand–protein binding behaviour, thereby offering a robust foundation for the rational design and optimisation of mTOR-targeting therapeutics.

Author contributions

**P. Venkata Ramana** : Writing—Original Draft, Writing—Review & Editing, Conceptualisation, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Supervision, Project administration, Visualisation. **Rashmirekha Ram:** Formal analysis, investigation, Resources, Supervision, **Prasadarao Bobbili:** Visualisation, Resources, Writing—Review & Editing. **Y. Rama Krishna** : Project administration, Supervision, Validation, Software, **Rabinarayan Panda:** Editing & Supervision, Shouri Domini: Validation, Software, **Pratap Kumar Dakua:** Formal Analysis and Supervision, Writing, **Siddharth Kumar:** Visualisation, Resources, Writing—Review & Editing.

Funding

Open access funding provided by Manipal University Jaipur. The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

Data will be made available on request.

Declarations

Competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

P. Venkata Ramana, Email: venkatphotonics@gmail.com.

Siddharth Kumar, Email: siddharth.kumar@jaipur.manipal.edu.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data will be made available on request.

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PERMALINK

Quantitative correlation of spectroscopic signatures with ligand–protein interactions in anti-cancer drug Afinitor: an integrated experimental–computational study

P Venkata Ramana

Rashmirekha Ram

Prasadarao Bobbili

Y Rama Krishna

Rabinarayan Panda

Shouri Dominic

Pratap Kumar Dakua

Siddharth Kumar

Abstract

Introduction

Significance of the study

Mechanism of action of Afinitor

Fig. 1.

Fig. 2.

Materials and methods

Experimental details

Table 1.

Fig. 3.

Fig. 4.

Molecular Docking Methodology

Results and discussion

FT-IR Spectrum analysis of Afinitor

Electron absorption spectra

Molecular docking analysis

Fig. 5.

Fig. 6.

Fig. 7.

Fig. 8.

Fig. 9.

Fig. 10.

Table 2.

Table 3.

Table 4.

Table 5.

Functional group analysis of Afinitor

The hydroxy group (–OH)

The carbonyl group (C = O)

Quantitative correlation between spectroscopic signatures and ligand–protein interactions

Vibrational frequency as a descriptor of interaction potential

Atom-resolved correlation between functional groups and binding interactions

Table 6.

Cooperative interaction network and binding energetics

Electronic structure contribution from UV–Vis spectroscopy

Integrated structure–spectra–interaction framework

Study limitations

Future research directions

Conclusion

Author contributions

Funding

Data availability

Declarations

Competing interests

Footnotes

Contributor Information

References

Associated Data

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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