Investigation into mechanism of orotidine 5′-monophosphate decarboxylase enzyme by MM-PBSA/MM-GBSA and molecular docking

In this work, we studied the binding affinity of orotidine 5′-monophosphate (OMP) and 6-hydroxy-UMP (BMP) for Saccharomyces cerevisiae orotidine 5′-monophosphate decarboxylase (OMPDC) enzyme by using Molecular Mechanics-Poisson–Boltzmann Surface Area (MM-PBSA) and the Molecular Mechanics-Generalised Born Surface Area (MM-GBSA) calculations. In all simulations, Asp91, which is an important residue in the enzyme active site, was considered in both anionic (present in the native form of the enzyme) and neutral states. A series of 10-ns molecular dynamics simulations were performed for the four OMPDC–ligand complexes, two ligand-free enzymes and two free ligands, followed by MM-PBSA/MM-GBSA calculations on the collected snapshots, and molecular docking calculations using the free enzymes and ligands. The results of MM-PBSA/MM-GBSA calculations indicate that all of the OMPDC–ligand complexes form favourable systems in water, which is in agreement with corresponding experimental data. The results of the MM-PBSA and molecular docking methods also showed that OMPDC–BMP complexes, transition state analogue and inhibitor of the OMPDC enzyme have the highest binding affinities. The fact that in the native anionic state BMP shows a higher binding affinity compared with the substrate suggests the contribution of a transition state stabilisation mechanism in the debatable catalytic mechanism of the OMPDC enzyme.     

Exploring the conformational and binding properties of unphosphorylated/phosphorylated monomeric and trimeric Bcl‐2 through docking and molecular dynamics simulations

B‐cell lymphoma (Bcl‐2) is commonly associated with the progression and preservation of cancer and certain lymphomas; therefore, it is considered as a biological target against cancer. Nevertheless, evidence of all its structural binding sites has been hidden because of the lack of a complete Bcl‐2 model, given the presence of a flexible loop domain (FLD), which is responsible for its complex behavior. FLD region has been implicated in phosphorylation, homotrimerization, and heterodimerization associated with Bcl‐2 antiapoptotic function. In this contribution, homology modeling, molecular dynamics (MD) simulations in the microsecond (µs) time‐scale and docking calculations were combined to explore the conformational complexity of unphosphorylated/phosphorylated monomeric and trimeric Bcl‐2 systems. Conformational ensembles generated through MD simulations allowed for identifying the most populated unphosphorylated/phosphorylated monomeric conformations, which were used as starting models to obtain trimeric complexes through protein–protein docking calculations, also submitted to µs MD simulations. Principal component analysis showed that FLD represents the main contributor to total Bcl‐2 mobility, and is affected by phosphorylation and oligomerization. Subsequently, based on the most representative unphosphorylated/phosphorylated monomeric and trimeric Bcl‐2 conformations, docking studies were initiated to identify the ligand binding site of several known Bcl‐2 inhibitors to explain their influence in homo‐complex formation and phosphorylation. Docking studies showed that the different conformational states experienced by FLD, such as phosphorylation and oligomerization, play an essential role in the ability to make homo and hetero‐complexes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 393–413, 2016.     

Molecular dynamics simulation of the induced‐fit binding process of DNA aptamer and L‐argininamide

Aptamers are rare functional nucleic acids with binding affinity to and specificity for target ligands. Recent experiments have lead to the proposal of an induced‐fit binding mechanism for L ‐argininamide (Arm) and its binding aptamer. However, at the molecular level, this mechanism between the aptamer and its coupled ligand is still poorly understood. The present study used explicit solvent molecular dynamics (MD) simulations to examine the critical bases involved in aptamer‐Arm binding and the induced‐fit binding process at atomic resolution. The simulation results revealed that the Watson‐Crick pair (G10‐C16), C9, A12, and C17 bases play important roles in aptamer‐Arm binding, and that binding of Arm results in an aptamer conformation optimized through a general induced‐fit process. In an aqueous solution, the mechanism has the following characteristic stages: (a) adsorption stage, the Arm anchors to the binding site of aptamer with strong electrostatic interaction; (b) binding stage, the Arm fits into the binding site of aptamer by hydrogen‐bond formation; and (c) complex stabilization stage, the hydrogen bonding and electrostatic interactions cooperatively stabilize the complex structure. This study provides dynamics information on the aptamer‐ligand induced‐fit binding mechanism. The critical bases in aptamer‐ligand binding may provide a guideline in aptamer design for molecular recognition engineering.     

Structure‐guided screening of chemical database to identify NS3‐NS2B inhibitors for effective therapeutic application in dengue infection

Dengue infection is the most common arthropod‐borne disease caused by dengue viruses, predominantly affecting millions of human beings annually. To find out promising chemical entities for therapeutic application in Dengue, in the current research, a multi‐step virtual screening effort was conceived to screen out the entire “screening library” of the Asinex database. Initially, through “Lipinski rule of five” filtration criterion almost 0.6 million compounds were collected and docked with NS3‐NS2B protein. Thereby, the chemical space was reduced to about 3500 compounds through the analysis of binding affinity obtained from molecular docking study in AutoDock Vina. Further, the “Virtual Screening Workflow” (VSW) utility of Schrödinger suite was used, which follows a stepwise multiple docking programs such as ‐ high‐throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) docking, and in postprocessing analysis the MM‐GBSA based free binding energy calculation. Finally, five potent molecules were proposed as potential inhibitors for the dengue NS3‐NS2B protein based on the investigation of molecular interactions map and protein‐ligand fingerprint analyses. Different pharmacokinetics and drug‐likeness parameters were also checked, which favour the potentiality of selected molecules for being drug‐like candidates. The molecular dynamics (MD) simulation analyses of protein‐ligand complexes were explained that NS3‐NS2B bound with proposed molecules quite stable in dynamic states as observed from the root means square deviation (RMSD) and root means square fluctuation (RMSF) parameters. The binding free energy was calculated using MM‐GBSA method from the MD simulation trajectories revealed that all proposed molecules possess such a strong binding affinity towards the dengue NS3‐NS2B protein. Therefore, proposed molecules may be potential chemical components for effective inhibition of dengue NS3‐NS2B protein subjected to experimental validation.     

N-(thiazol-2-yl)-2-thiophene carboxamide derivatives as Abl inhibitors identified by a pharmacophore-based database screening of commercially available compounds

Suggestions derived from a previous ligand-based ligand design approach and docking calculations aimed at finding compound with affinity toward Abl and molecular scaffolds previously untested as Abl inhibitors, led to the identification of commercially available N-(thiazol-2-yl)-2-thiophene carboxamide derivatives with affinity in a cell-free assay up to low nanomolar concentrations, significantly enhanced with respect to that of their parent compounds previously reported. In particular, among compounds of the Asinex database, molecular docking simulations guided the choice of high-affinity ligands, predicting their binding mode and their interaction pattern with the Abl catalytic binding site. Moreover, affinity of the new compounds was also rationalized in terms of their interactions with the enzyme.     

Predicting binding modes of reversible peptide‐based inhibitors of falcipain‐2 consistent with structure–activity relationships

Falcipain‐2 (FP‐2) is a major hemoglobinase of Plasmodium falciparum, considered an important drug target for the development of antimalarials. A previous study reported a novel series of 20 reversible peptide‐based inhibitors of FP‐2. However, the lack of tridimensional structures of the complexes hinders further optimization strategies to enhance the inhibitory activity of the compounds. Here we report the prediction of the binding modes of the aforementioned inhibitors to FP‐2. A computational approach combining previous knowledge on the determinants of binding to the enzyme, docking, and postdocking refinement steps, is employed. The latter steps comprise molecular dynamics simulations and free energy calculations. Remarkably, this approach leads to the identification of near‐native ligand conformations when applied to a validation set of protein‐ligand structures. Overall, we proposed substrate‐like binding modes of the studied compounds fulfilling the structural requirements for FP‐2 binding and yielding free energy values that correlated well with the experimental data. Proteins 2017; 85:1666–1683. © 2017 Wiley Periodicals, Inc.     

An application of CIFAP for predicting the binding affinity of Chk1 inhibitors derived from 2‐aminothiazole‐4‐carboxamide

Investigation of protein‐ligand interactions obtained from experiments has a crucial part in the design of newly discovered and effective drugs. Analyzing the data extracted from known interactions could help scientists to predict the binding affinities of promising ligands before conducting experiments. The objective of this study is to advance the CIFAP (compressed images for affinity prediction) method, which is relevant to a protein‐ligand model, identifying 2D electrostatic potential images by separating the binding site of protein‐ligand complexes and using the images for predicting the computational affinity information represented by pIC₅₀ values. The CIFAP method has 2 phases, namely, data modeling and prediction. In data modeling phase, the separated 3D structure of the binding pocket with the ligand inside is fitted into an electrostatic potential grid box, which is then compressed through 3 orthogonal directions into three 2D images for each protein‐ligand complex. Sequential floating forward selection technique is performed for acquiring prediction patterns from the images. In the prediction phase, support vector regression (SVR) and partial least squares regression are used for testing the quality of the CIFAP method for predicting the binding affinity of 45 CHK1 inhibitors derived from 2‐aminothiazole‐4‐carboxamide. The results show that the CIFAP method using both support vector regression and partial least squares regression is very effective for predicting the binding affinities of CHK1‐ligand complexes with low‐error values and high correlation. As a future work, the results could be improved by working on the pose of the ligands inside the grid.     

New molecular scaffolds for the design of Mycobacterium tuberculosis type II dehydroquinase inhibitors identified using ligand and receptor based virtual screening

Using ligand and receptor based virtual screening approaches we have identified potential virtual screening hits targeting type II dehydroquinase from Mycobacterium tuberculosis, an effective and validated anti-mycobacterial target. Initially, we applied a virtual screening workflow based on a combination of 2D structural fingerprints, 3D pharmacophore and molecular docking to identify compounds that rigidly match specific aspects of ligand bioactive conformation. Subsequently, the resulting compounds were ranked and prioritized using receptor interaction fingerprint based scoring and quantitative structure activity relationship model developed using already known actives. The virtual screening hits prioritized belong to several classes of molecular scaffolds with several available substitution positions that could allow chemical modification to enhance binding affinity. Finally, identified hits may be useful to a medicinal chemist or combinatorial chemist to pick up the new molecular starting points for medicinal chemistry optimization for the design of novel type II dehydroquinase inhibitors.     

Virtual screening of small molecules databases for discovery of novel PARP-1 inhibitors: combination of in silico and in vitro studies

Poly(ADP-ribose) polymerase-1 (PARP-1) enzyme has critical roles in DNA replication repair and recombination. Thus, PARP-1 inhibitors play an important role in the cancer therapy. In the current study, we have performed combination of in silico and in vitro studies in order to discover novel inhibitors against PARP-1 target. Structure-based virtual screening was carried out for an available small molecules database. A total of 257,951 ligands from Otava database were screened at the binding pocket of PARP-1 using high-throughput virtual screening techniques. Filtered structures based on predicted binding energy results were then used in more sophisticated molecular docking simulations (i.e. Glide/standard precision, Glide/XP, induced fit docking – IFD, and quantum mechanics polarized ligand docking – QPLD). Potential high binding affinity compounds that are predicted by molecular simulations were then tested by in vitro methods. Computationally proposed compounds as PARP-1 inhibitors (Otava Compound Codes: 7111620047 and 7119980926) were confirmed by in vitro studies. In vitro results showed that compounds 7111620047 and 7119980926 have IC₅₀ values of 0.56 and 63 μM against PARP-1 target, respectively. The molecular mechanism analysis, free energy perturbation calculations using long multiple molecular dynamics simulations for the discovered compounds which showed high binding affinity against PARP-1 enzyme, as well as structure-based pharmacophore development (E-pharmacophore) studies were also studied.     

Computational analysis of BACE1-ligand complex crystal structures and linear discriminant analysis for identification of BACE1 inhibitors with anti P-glycoprotein binding property

More than 100 years of research on Alzheimer’s disease didn’t yield a potential cure for this dreadful disease. Poor Blood Brain Barrier (BBB) permeability and P-glycoprotein binding of BACE1 inhibitors are the major causes for the failure of these molecules during clinical trials. The design of BACE1 inhibitors with a balance of sufficient affinity to the binding site and little or no interaction with P-glycoproteins is indispensable. Identification and understanding of protein–ligand interactions are essential for ligand optimization process. Structure-based drug design (SBDD) efforts led to a steady accumulation of BACE1-ligand crystal complexes in the PDB. This study focuses on analyses of 153 BACE1-ligand complexes for the direct contacts (hydrogen bonds and weak interactions) observed between protein and ligand and indirect contacts (water-mediated hydrogen bonds), observed in BACE1-ligand complex crystal structures. Intraligand hydrogen bonds were analyzed, with focus on ligand P-glycoprotein efflux. The interactions are dissected specific to subsites in the active site and discussed. The observed protein-ligand and intraligand interactions were used to develop the linear discriminant model for the identification of BACE1 inhibitors with less or no P-glycoprotein binding property. Excellent statistical results and model’s ability to correctly predict a new data-set with an accuracy of 92% is achieved. The results are retrospectively analyzed to give input for the design of potential BACE1 inhibitors.     

Molecular insights into the binding selectivity of a synthetic ligand DAAG to Fc fragment of IgG

Affinity chromatography with synthetic ligands has been focused as the potential alternative to protein A‐based chromatography for antibody capture because of its comparable selectivity and efficiency. Better understanding on the molecular interactions between synthetic ligand and antibody is crucial for improving and designing novel ligands. In this work, the molecular interaction mechanism between Fc fragment of IgG and a synthetic ligand (DAAG) was studied with molecular docking and dynamics simulation. The docking results on the consensus binding site (CBS) indicated that DAAG could bind to the CBS with the favorable orientation like a tripod for the top‐ranked binding complexes. The ligand‐Fc fragment complexes were then tested by molecular dynamics simulation at neutral condition (pH 7.0) for 10 ns. The results indicated that the binding of DAAG on the CBS of Fc fragment was achieved by the multimodal interactions, combining the hydrophobic interaction, electrostatic interaction, hydrogen bond, and so on. It was also found that multiple secondary interactions endowed DAAG with an excellent selectivity to Fc fragment. In addition, molecular dynamics simulation conducted at acidic condition (pH 3.0) showed that the departure of DAAG ligand from the surface of Fc fragment was the result of reduced interaction energies. The binding modes between DAAG and CBS not only shed light on the molecular mechanisms of DAAG for antibody purification but also provide useful information for the improvement of ligand design. Copyright © 2014 John Wiley & Sons, Ltd.     

Homology modeling and atomic level binding study of Leishmania MAPK with inhibitors

The current therapy for leishmaniasis is not sufficient and it has two severe drawbacks, host-toxicity and drug resistance. The substantial knowledge of parasite biology is not yet translating into novel drugs for leishmaniasis. Based on this observation, a 3D structural model of Leishmania mitogen-activated protein kinase (MAPK) homologue has been developed, for the first time, by homology modeling and molecular dynamics simulation techniques. The model provided clear insight in its structure features, i.e. ATP binding pocket, phosphorylation lip, and common docking site. Sequence-structure homology recognition identified Leishmania CRK3 (LCRK3) as a distant member of the MAPK superfamily. Multiple sequence alignment and 3D structure model provided the putative ATP binding pocket of Leishmania with respect to human ERK2 and LCRK3. This analysis was helpful in identifying the binding sites and molecular function of the Leishmania specific MAPK homologue. Molecular docking study was performed on this 3D structural model, using different classes of competitive ATP inhibitors of LCRK3, to check whether they exhibit affinity and could be identified as Leishmania MAPK specific inhibitors. It is well known that MAP kinases are extracellular signal regulated kinases ERK1 and ERK2, which are components of the Ras-MAPK signal transduction pathway which is complexed with HDAC4 protein, and their inhibition is of significant therapeutic interest in cancer biology. In order to understand the mechanism of action, docking of indirubin class of molecules to the active site of histone deacetylase 4 (HDAC4) protein is performed, and the binding affinity of the protein-ligand interaction was computed. The new structural insights obtained from this study are all consistent with the available experimental data, suggesting that the homology model of the Leishmania MAPK and its ligand interaction modes are reasonable. Further the comparative molecular electrostatic potential and cavity depth analysis of Leishmania MAPK and human ERK2 suggested several important differences in its ATP binding pocket. Such differences could be exploited in the future for designing Leishmania specific MAPK inhibitors.     

Zinc(II)cyclen-peptide conjugates interacting with the weak effector binding state of Ras

Zinc(II)cyclen-peptide hybrid compounds and bis-zinc(II)cyclen complexes are prepared as potential binders of the guanine nucleotide binding protein Ras, an important molecular switch in cellular signal transduction. The design of the compounds is based on the previous observation that zinc(II)cyclen complexes could serve as lead compounds for inhibitors of Ras-effector interaction and thus be able to interrupt Ras induced signal transduction. Zinc(II)cyclen selectively stabilizes conformational state 1 of active Ras, a conformational state with drastically decreased affinity to effector proteins like Raf-kinase. To achieve higher binding affinities of such Ras-Raf interaction inhibitors, zinc(II)cyclen conjugates with short peptides, derived from the sequence of the Ras-activator SOS, were prepared by solid phase synthesis protocols. Dinuclear bis-zinc(II)cyclen complexes were obtained from alkyne-azide cycloaddition reactions. NMR investigations of the prepared compounds revealed that the peptide conjugates do not lead to an increase in Ras binding affinity of the metal complex-peptide conjugates. The dinuclear zinc complexes lead to an immediate precipitation of the protein prohibiting spectroscopic investigations of their binding.     

Molecular docking towards drug discovery

Fueled by advances in molecular structure determination, tools for structure-based drug design are proliferating rapidly. Lead discovery through searching of ligand databases with molecular docking techniques represents an attractive alternative to high-throughput random screening. The size of commercial databases imposes severe computational constraints on molecular docking, compromising the level of calculational detail permitted for each putative ligand. We describe alternative philosophies for docking which effectively address this challenge. With respect to the dynamic aspects of molecular recognition, these strategies lie along a spectrum of models bounded by the Lock-and-Key and Induced-Fit theories for ligand binding. We explore the potential of a rigid model in exploiting species specificity and of a tolerant model in predicting absolute ligand binding affinity. Current molecular docking methods are limited primarily by their ability to rank docked complexes; we therefore place particular emphasis on this aspect of the problem throughout our validation of docking strategies.     

Nucleotide analogs and molecular modeling studies reveal key interactions involved in substrate recognition by the yeast RNA triphosphatase

RNA triphosphatases (RTPases) are involved in the addition of the distinctive cap structure found at the 5′ ends of eukaryotic mRNAs. Fungi, protozoa and some DNA viruses possess an RTPase that belongs to the triphosphate tunnel metalloenzyme family of enzymes that can also hydrolyze nucleoside triphosphates. Previous crystallization studies revealed that the phosphohydrolase catalytic core is located in a hydrophilic tunnel composed of antiparallel β-strands. However, all past efforts to obtain structural information on the interaction between RTPases and their substrates were unsuccessful. In the present study, we used computational molecular docking to model the binding of a nucleotide substrate into the yeast RTPase active site. In order to confirm the docking model and to gain additional insights into the molecular determinants involved in substrate recognition, we also evaluated both the phosphohydrolysis and the inhibitory potential of an important number of nucleotide analogs. Our study highlights the importance of specific amino acids for the binding of the sugar, base and triphosphate moieties of the nucleotide substrate, and reveals both the structural flexibility and complexity of the active site. These data illustrate the functional features required for the interaction of an RTPase with a ligand and pave the way to the use of nucleotide analogs as potential inhibitors of RTPases of pathogenic importance.     

The molecular basis of urokinase inhibition: from the nonempirical analysis of intermolecular interactions to the prediction of binding affinity

Urokinase-type plasminogen activator (uPA) is a trypsin-like serine protease that plays a crucial role in angiogenesis process. In addition to its physiological role in healthy organisms, angiogenesis is extremely important in cancer growth and metastasis, resulting in numerous attempts to understand its control and to develop new approaches to anticancer therapy. The α-aminoalkylphosphonate diphenyl esters are well known as highly efficient serine protease inhibitors. However, their mode of binding has not been verified experimentally in details. For a group of average and potent phosphonic inhibitors of urokinase, flexible docking calculations were performed to gain an insight into the active site interactions responsible for observed enzyme inhibition. The docking results are consistent with the previously suggested mode of inhibitors binding. Subsequently, rigorous ab initio study of binding energy was carried out, followed by its decomposition according to the variation–perturbation procedure to reveal stabilization energy constituents with clear physical meaning. Availability of the experimental inhibitory activities and comparison with theoretical binding energy allows for the validation of theoretical models of inhibition, as well as estimation of the possible potential for binding affinity prediction. Since the docking results accompanied by molecular mechanics optimization suggested that several crucial active site contacts were too short, the optimal distances corresponding to the minimum ab initio interaction energy were also evaluated. Despite the deficiencies of force field-optimized enzyme-inhibitor structures, satisfactory agreement with experimental inhibitory activity was obtained for the electrostatic interaction energy, suggesting its possible application in the binding affinity prediction. Figure The comparison of an arrangement of inhibitors within uPA active. Amino acid residues form S1 pocket that binds the variable part of inhibitor molecules     

Different combinations of atomic interactions predict protein‐small molecule and protein‐DNA/RNA affinities with similar accuracy

Interactions between proteins and other molecules play essential roles in all biological processes. Although it is widely held that a protein's ligand specificity is determined primarily by its three‐dimensional structure, the general principles by which structure determines ligand binding remain poorly understood. Here we use statistical analyses of a large number of protein?ligand complexes with associated binding‐affinity measurements to quantitatively characterize how combinations of atomic interactions contribute to ligand affinity. We find that there are significant differences in how atomic interactions determine ligand affinity for proteins that bind small chemical ligands, those that bind DNA/RNA and those that interact with other proteins. Although protein‐small molecule and protein‐DNA/RNA binding affinities can be accurately predicted from structural data, models predicting one type of interaction perform poorly on the others. Additionally, the particular combinations of atomic interactions required to predict binding affinity differed between small‐molecule and DNA/RNA data sets, consistent with the conclusion that the structural bases determining ligand affinity differ among interaction types. In contrast to what we observed for small‐molecule and DNA/RNA interactions, no statistical models were capable of predicting protein?protein affinity with >60% correlation. We demonstrate the potential usefulness of protein‐DNA/RNA binding prediction as a possible tool for high‐throughput virtual screening to guide laboratory investigations, suggesting that quantitative characterization of diverse molecular interactions may have practical applications as well as fundamentally advancing our understanding of how molecular structure translates into function. Proteins 2015; 83:2100–2114. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.     

Three-dimensional Structure of a Kunitz-type Inhibitor in Complex with an Elastase-like Enzyme

Elastase-like enzymes are involved in important diseases such as acute pancreatitis, chronic inflammatory lung diseases, and cancer. Structural insights into their interaction with specific inhibitors will contribute to the development of novel anti-elastase compounds that resist rapid oxidation and proteolysis. Proteinaceous Kunitz-type inhibitors homologous to the bovine pancreatic trypsin inhibitor (BPTI) provide a suitable scaffold, but the structural aspects of their interaction with elastase-like enzymes have not been elucidated. Here, we increased the selectivity of ShPI-1, a versatile serine protease inhibitor from the sea anemone Stichodactyla helianthus with high biomedical and biotechnological potential, toward elastase-like enzymes by substitution of the P1 residue (Lys¹³) with leucine. The variant (rShPI-1/K13L) exhibits a novel anti-porcine pancreatic elastase (PPE) activity together with a significantly improved inhibition of human neuthrophil elastase and chymotrypsin. The crystal structure of the PPE·rShPI-1/K13L complex determined at 2.0 Å resolution provided the first details of the canonical interaction between a BPTI-Kunitz-type domain and elastase-like enzymes. In addition to the essential impact of the variant P1 residue for complex stability, the interface is improved by increased contributions of the primary and secondary binding loop as compared with similar trypsin and chymotrypsin complexes. A comparison of the interaction network with elastase complexes of canonical inhibitors from the chelonian in family supports a key role of the P3 site in ShPI-1 in directing its selectivity against pancreatic and neutrophil elastases. Our results provide the structural basis for site-specific mutagenesis to further improve the binding affinity and/or direct the selectivity of BPTI-Kunitz-type inhibitors toward elastase-like enzymes.     

Structural studies on ligand–DNA systems: A robust approach in drug design

Molecular docking, molecular mechanics, molecular dynamics and relaxation matrix simulation protocols have been extensively used to generate the structural details of ligand-receptor complexes in order to understand the binding interactions between the two entities. Experimental methods like NMR spectroscopy and X-ray crystallography are known to provide structural information about ligand-receptor complexes. In addition, fluorescence spectroscopy, circular dichroism (CD) spectroscopy and molecular docking have also been utilized to decode the phenomenon of the ligand-DNA interactions, with good correlation between experimental and computational results. The DNA binding affinity was demonstrated by analysing fluorescence spectral data. Structural rigidity of DNA upon ligand binding was identified by CD spectroscopy. Docking is carried out using the DNA-Dock program which results in the binding affinity data along with structural information like interatomic distances and H-bonding, etc. The complete structural analyses of various drug-DNA complexes have afforded results that indicate a specific DNA binding pattern of these ligands. It also exhibited that certain structural features of ligands can make a ligand to be AT- or GC-specific. It was also demonstrated that changing specificity from AT base pairs to GC base pairs further improved the DNA topoisomerase inhibiting activity in certain ligands. Thus, a specific molecular recognition signature encrypted in the structure of ligand can be decoded and can be effectively employed in designing more potent antiviral and antitumour agents.