Conserved Water Molecules Research Articles

The Importance of Structural Water in HDAC8 for Correct Binding Pose Applied for Drug Design of Anticancer Molecules.

Validating the docking procedure and maintaining the structural water molecules at HDAC8 catalytic site. Molecular docking simulations play a significant role in Computer-Aided Drug Design, contributing to the development of new molecules. To ensure the reliability of these simulations, a validation process called "self-docking or re-docking" is employed, focusing on the binding mode of a ligand co-crystallized with the protein of interest. In this study, several molecular docking studies were conducted using five X-ray structures of HDAC8-ligand complexes from the PDB. Ligands initially complexed with HDAC8 were removed and re-docked onto the free protein, revealing a poor reproduction of the expected binding mode. In response to this, we observed that most HDAC8-ligand complexes contained one to two water molecules in the catalytic site, which were crucial for maintaining the cocrystallized ligand. These water molecules enhance the binding mode of the co-crystallized ligand by stabilizing the proteinligand complex through hydrogen bond interactions between ligand and water molecules. Notably, these interactions are lost if water molecules are removed, as is often done in classical docking methodologies. Considering this, molecular docking simulations were repeated, both with and without one or two conserved water molecules near Zn+2 in the catalytic cavity. Simulations indicated that replicating the native binding pose of co-crystallized ligands on free HDAC8 without these water molecules was challenging, showing greater coordinate displacements (RMSD) compared to those including conserved water molecules from crystals. The study highlighted the importance of conserved water molecules within the active site, as their presence significantly influenced the successful reproduction of the ligands' native binding modes. The results suggest an optimal molecular docking procedure for validating methods suitable for filtering new HDAC8 inhibitors for future experimental assays.

Structural and thermodynamic properties of conserved water molecules in Mpro native: A combined approach by MD simulation and Grid Inhomogeneous Solvation Theory.

The new viral strains of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are continuously rising, becoming more virulent, and transmissible. Therefore, the development of new antiviral drugs is essential. Due to its significant role in the viral life cycle of SARS-CoV-2, the main protease (Mpro) enzyme is a leading target for antiviral drug design. The Mpro monomer consists of domain DI, DII, and DI-DII interface. Twenty-one conserved water molecules (W4-W24) are occupied at these domains according to multiple crystal structure analyses. The crystal and MD structures reveal the presence of eight conserved water sites in domain DI, DII and remaining in the DI-DII interface. Grid-based inhomogeneous fluid solvation theory (GIST) was employed on MD structures of Mpro native to predict structural and thermodynamic properties of each conserved water site for focusing to identify the specific conserved water molecules that can easily be displaced by proposed ligands. Finally, MD water W13 is emerged as a promising candidate for water mimic drug design due to its low mean interaction energy, loose binding character with the protein, and its involvement in a water-mediated H-bond with catalytic His41 via the interaction Thr25(OG)---W13---W---His41(NE2). In this context, water occupancy, relative interaction energy, entropy, and topologies of W13 are thermodynamically acceptable for the water displacement method. Therefore, the strategic use of W13's geometrical position in the DI domain may be implemented for drug discovery against COVID disease by designing new ligands with appropriately oriented chemical groups to mimic its structural, electronic, and thermodynamic properties.

Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach.

In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS H2O (MD) methodology, for the identification of conserved water molecules. Our method uses experimental structures of proteins homologous to a query, which are subsequently superimposed upon it. Areas with a particular species present in a similar location among many homologous protein structures are identified using a clustering algorithm. Dense clusters likely represent positions containing species important to the query protein structure or function. We analyze well-characterized apo protein structures and show that the MADE approach can identify clusters corresponding to the expected positions of metal ions in their binding sites. The greatest advantage of our method lies in its generality. It can in principle be applied to any species found in protein records; it is not only limited to metal ions. We additionally demonstrate that the MADE approach can be successfully applied to predict the location of cofactors in computer-modeled structures, e.g., via AlphaFold. We also conduct a careful protein superposition method comparison and find our methodology robust and the results largely independent of the selected protein superposition algorithm. We postulate that with increasing structural data availability, additional applications of the MADE approach will be possible such as non-protein systems, water network identification, protein binding site elaboration, and analysis of binding events, all in a dynamic manner. We have implemented the MADE approach as a plugin for the PyMOL molecular visualization tool. The MADE plugin is available free of charge at https://gitlab.com/Jukic/made_software.

In Silico Evaluation of the Thr58-Associated Conserved Water with KRAS Switch-II Pocket Binders.

The KRAS switch-II pocket (SII-P) has proven to be one of the most successful tools for targeting KRAS with small molecules to date. This has been demonstrated with several KRAS(G12C)-targeting covalent inhibitors, already resulting in two FDA-approved drugs. Several earlier-stage compounds have also been reported to engage KRAS SII-P with other position 12 mutants, including G12D, G12S, and G12R. A highly conserved water molecule exists in the KRAS SII-P, linking Thr58 of switch-II and Gly10 of β1 sheet. This conserved water is also present in the cocrystal structures of most of the disclosed small-molecule inhibitors but is only displaced by a handful of SII-P binders. Here, we evaluated the conserved water molecule energetics by the WaterMap for the SII-P binders with publicly disclosed structures and studied the water behavior in the presence of selected inhibitors by microsecond timescale molecular dynamics (MD) simulations using two water models (total simulation time of 120 μs). Our data revealed the high-energy nature of this hydration site when coexisting with an SII-P binder and that there is a preference for a single isolated hydration site in this location within the most advanced compounds. Furthermore, water displacement was only achieved with a few disclosed compounds and was suboptimal, as for instance a cyanomethyl group as a water displacer appears to introduce repulsion with the native conformation of Thr58. These results suggested that this conserved water should be considered more central when designing new inhibitors, especially in the design of noncovalent inhibitors targeting the SII-P.

Insight into the Role of Active Site Protonation States and Water Molecules in the Catalytic Inhibition of DPP4 by Vildagliptin.

Vildagliptin (VIL) is an antidiabetic drug that inhibits dipeptidyl peptidase-4 (DPP4) through a covalent mechanism. The molecular bases for this inhibitory process have been addressed experimentally and computationally. Nevertheless, relevant issues remain unknown such as the roles of active site protonation states and conserved water molecules nearby the catalytic center. In this work, molecular dynamics simulations were applied to examine the structures of 12 noncovalent VIL-DPP4 complexes encompassing all possible protonation states of three noncatalytic residues (His126, Asp663, Asp709) that were inconclusively predicted by different computational tools. A catalytically competent complex structure was only achieved in the system with His126 in its ε-form and nonconventional neutral states for Asp663/Asp709. This complex suggested the involvement of one water molecule in the catalytic process of His740/Ser630 activation, which was confirmed by QM/MM simulations. Our findings support the suitability of a novel water-mediated mechanism in which His740/Ser630 activation occurs concertedly with the nucleophilic attack on VIL and the imidate protonation by Tyr547. Then, the restoration of His740/ Tyr547 protonation states occurs via a two-water hydrogen bonding network in a low-barrier process, thus describing the final step of the catalytic cycle for the first time. Additionally, two hydrolytic mechanisms were proposed based on the hydrogen bonding networks formed by water molecules and the catalytic residues along the inhibitory mechanism. These findings are valuable to unveil the molecular features of the covalent inhibition of DPP4 by VIL and support the future development of novel derivatives with improved structural or mechanistic profiles.

Structural insight to human Retinoid X receptor alpha-Thyroid hormone receptor beta heterodimer by molecular modelling and MD-simulation studies: role of conserved water molecules

The Retinoid X receptor alpha–Thyroid hormone receptor beta (RXRα-THRβ) heterodimer plays an important role in physiological function of humans specially in the growth and development. Extensive MD-simulation studies on the aquated complexes of modelled RXRα-THRβ heterodimer with DNA-duplex have indicated the role of some conserved/semiconserved water molecules in the complexation process in presence or absence of Triiodothyronine (T3) and 9-cis retinoic acid (9CR) in the respective Ligand Binding Domain (LBD) domain. Among the seventeen conserved/semi-conserved water molecules, the W1-W4 water centers have been observed to mediate the interaction between the residues of A-chain (DBD of RXR) to consensus sequence (C-chain) of DNA. The W5-W8 water centers involve in recognition of the residues of B-chain (DBD of THR) to C-chain of DNA. The W9-W13 centers have connected the different residues of B-chain (THR) to D-chain of DNA through H-bonds, whereas W14-W17 water molecules were involved in the interaction of A-chain′s (RXR) residues to D-chain of DNA. In our previous study with homodimeric THRβ from Rattus norvegicus we have identified fifteen conserved water molecules at the DNA-DBD interface. Moreover, the conformational flexibility of Met313 (in the LBD of THR) from open to close form in presence or absence of T3 molecule in the holo and Apo-protein may provide a plausible rational on the possible role of that residue to acts as gate which could restrict the solvent molecules to enter into the hydrophobic T3-binding pocket of LBD during the absence of ligand molecule and thus could help the stabilization of that domain in THRβ structure. Communicated by Ramaswamy H. Sarma

Conserved Water Networks Identification for Drug Design Using Density Clustering Approaches on Positional and Orientational Data.

This work describes the development and testing of a method for the identification and classification of conserved water molecules and their networks from molecular dynamics (MD) simulations. The conserved waters in the active sites of proteins influence protein-ligand binding. Recently, several groups have argued that a water network formed from conserved waters can be used to interpret the thermodynamic signature of the binding site. We implemented a novel methodology in which we apply the complex approach to categorize water molecules extracted from the MD simulation trajectories using clustering approaches. The main advantage of our methodology as compared to current state of the art approaches is the inclusion of the information on the orientation of hydrogen atoms to further inform the clustering algorithm and to classify the conserved waters into different subtypes depending on how strongly certain orientations are preferred. This information is vital for assessing the stability of water networks. The newly developed approach is described in detail as well as validated against known results from the scientific literature including comparisons with the experimental data on thermolysin, thrombin, and Haemophilus influenzae virulence protein SiaP as well as with the previous computational results on thermolysin. We observed excellent agreement with the literature and were also able to provide additional insights into the orientations of the conserved water molecules, highlighting the key interactions which stabilize them. The source code of our approach, as well as the utility tools used for visualization, are freely available on GitHub.

Predicting Conserved Water Molecules in Binding Sites of Proteins Using Machine Learning Methods and Combining Features.

Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it is difficult to identify the conserved water molecules (CWMs) from free water molecules (FWMs) directly as CWMs are normally deeply embedded in proteins and form strong hydrogen bonds with surrounding polar groups. To circumvent this difficulty, in this work, the abundance of spatial structure information and physicochemical properties of water molecules in proteins inspires us to adopt machine learning methods for identifying the CWMs. Therefore, in this study, a machine learning framework to identify the CWMs in the binding sites of the proteins was presented. First, by analyzing water molecules' physicochemical properties and spatial structure information, six features (i.e., atom density, hydrophilicity, hydrophobicity, solvent-accessible surface area, temperature B-factors, and mobility) were extracted. Those features were further analyzed and combined to reach a higher CWM identification rate. As a result, an optimal feature combination was determined. Based on this optimal combination, seven different machine learning models (including support vector machine (SVM), K-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), discriminant analysis (DA), naïve Bayes (NB), and ensemble learning (EL)) were evaluated for their abilities in identifying two categories of water molecules, i.e., CWMs and FWMs. It showed that the EL model was the desired prediction model due to its comprehensive advantages. Furthermore, the presented methodology was validated through a case study of crystal 3skh and extensively compared with Dowser++. The prediction performance showed that the optimal feature combination and the desired EL model in our method could achieve satisfactory prediction accuracy in identifying CWMs from FWMs in the proteins' binding sites.

Identification and structural analysis of a selective tropomyosin receptor kinase C (TRKC) inhibitor

Tropomyosin receptor kinases (TRKs) are a family of TRKA, TRKB and TRKC isoforms. It has been widely reported that TRKs are implicated in a variety of tumors with several Pan-TRK inhibitors currently being used or evaluated in clinical treatment. However, off-target adverse events frequently occur in the clinical use of Pan-TRK inhibitors, which result in poor patient compliance, even drug discontinuation. Although a subtype-selectivity TRK inhibitor may avert the potential off-target adverse events and can act as a more powerful tool compound in the biochemical studies on TRKs, the high sequence similarities of TRKs hinder the development of subtype-selectivity TRK inhibitors. For example, no selective TRKC inhibitor has been reported. Herein, a selective TRKC inhibitor (L13) was disclosed, with potent TRKC inhibitory activity and 107.5-/34.9-fold selectivity over TRKA/B (IC50 TRKA/B/C = 1400 nM, 454 nM, 13 nM, respectively). Extensive molecular dynamics simulations illustrated that key interactions of L13 with the residues and diversely conserved water molecules in the ribose regions of different TRKs may be the structural basis of selectivity. This will provide inspiring insights into the development of subtype-selectivity TRK inhibitors. Moreover, L13 could serve as a tool compound to investigate the distinct biological functions of TRKC and a starting point for further research on drugs specifically targeting TRKC.

Role(s) of Acetylation in human pathogen Helicobacter pylori

Helicobacter pyloris (H.pylori) a Gram‐negative bacterium whose infection of the human stomach triggers a chronic gastritis that can evolve into a series of severe pathologies such as gastroduodenal ulcers and cancer. H.pylori infects more than 50% of world population. Its amazing diversity and variability are major contributors to this success by allowing the emegence of new alleles. The bacterium lacks SOS response, DNA mismatch repair system, has a huge repertoire of restriction‐modification systems and is highly competent. These characteristics compelled us to investigate its all‐possible regulatory system (s). Acetylation‐a post‐translational modification has been proven to be a major regulatory machinery in prokaryotic physiology Acetylome analysis of different strains of H. pylori showed the presence of prominent and strain specific protein acetylation. Mass‐spectrometry based analysis showed that acetylated proteins participate in diverse biological processes such as metabolic pathways, transcription, translation, cell signalling and motility. In addition, acetylome analysis showed that two Cag pathogenicity island proteins. Cag 7, Cag 14, UvrD helicase involved in nucleotide excision repair, DNA methyltransferase‐ HPyAVIA, and DprA‐ involved in Natural Transformation process were acetylated. HP0935, a putative N‐acetyltransferase belonging to the GNAT superfamily was identified as possible protein acetyltransferase. It was observed that HP0935 acetylates L‐amino acids such as arginine and methionine at Nα amino group and lysine at both Nα and Nε amino group. Mutational and pH analysis of HP0935 suggest that a possible catalytic mechanism involves deprotonation of amino group of substrates by conserved water molecule followed by nucleophilic attack of deprotonated amino group on Ac‐CoA. Furthermore, Tyr127 act as a general acid that protonates the leaving thiolate anion of Coenzyme A. It was observed that ATPase and helicase activity of HPUvrD was regulated by both enzymatic (HP0935) and non‐enzymatic (Ac‐CoA) acetylation while the methyltransferase activity of M. HPyAVIA was enhanced only by enzymatic (HP0935) acetylation. These observations suggest acetylation of several key proteins plays a role in pathogenesis and in Natural transformation of H. pylori.

Structural insights into the substrate-binding site of main protease for the structure-based COVID-19 drug discovery.

An attractive drug target to combat COVID-19 is the main protease (Mpro ) because of its key role in the viral life cycle by processing the polyproteins translated from the viral RNA. Studying the crystal structures of the protease is important to enhance our understanding of its mechanism of action at the atomic-level resolution, and consequently may provide crucial structural insights for structure-based drug discovery. In the current study, we report a comparative structural analysis of the Mpro substrate binding site for both apo and holo forms to identify key interacting residues and conserved water molecules during the ligand-binding process. It is shown that in addition to the catalytic dyad residues (His41 and Cys145), the oxyanion hole residues (Asn142-Ser144) and residues His164-Glu166 form essential parts of the substrate-binding pocket of the protease in the binding process. Furthermore, we address the issue of the substrate-binding pocket flexibility and show that two adjacent loops in the Mpro structures (residues Thr45-Met49 and Arg188-Ala191) with high flexibility can regulate the binding cavity' accessibility for different ligand sizes. Moreover, we discuss in detail the various structural and functional roles of several important conserved and mobile water molecules within and around the binding site in the proper enzymatic function of Mpro . We also present a new docking protocol in the framework of the ensemble docking strategy. The performance of the docking protocol has been evaluated in predicting ligand binding pose and affinity ranking for two popular docking programs; AutoDock4 and AutoDock Vina. Our docking results suggest that the top-ranked poses of the most populated clusters obtained by AutoDock Vina are the most important representative docking runs that show a very good performance in estimating experimental binding poses and affinity ranking.

Identification of a Catalytic Nucleophile-Activating Network in the endo-α-N-Acetylgalactosaminidase of Family GH101.

Bifidobacterium longum endo-α-N-acetylgalactosaminidase (GH101), EngBF, is highly specific toward the mucin Core 1 glycan, Galβ1-3GalNAc. Apart from the side chains involved in the retaining mechanism of EngBF, Asp-682 is important for the activity. In the crystal structures of both EngBF and EngSP (from Streptococcus pneumoniae), we identified a conserved water molecule in proximity to Asp-682 and the homologue residue in EngSP. The water molecule also coordinates the catalytic nucleophile and three other residues conserved in GH101 enzymes; in EngBF, these residues are His-685, His-718, and Asn-720. With casein-glycomacropeptide as the substrate, the importance of Asp-682 was confirmed by the lack of a detectable activity for the D682N enzyme. The enzyme variants, H685A, H718A, H685Q, and H718Q, all displayed only a modestly reduction in kcat of up to 15 fold for the H718A variant. However, the double-substituted variants, H685A/H718A and H685Q/H718Q, had a greatly reduced kcat value by about 200 fold compared to that of wild-type EngBF. With the synthetic substrate, Galβ(1-3)GalNAcα1-para-nitrophenol, kcat of the double-substituted variants was only up to 30-fold reduced and was found to increase with pH. Compared to the pre-steady-state kinetics of wild-type EngBF, a burst of about the size of the enzyme concentration was absent with the double-substituted EngBF variants, indicating that the nucleophilic attack had become at least as slow as the hydrolysis of the enzyme intermediate. Together, the results indicate that not only Asp-682 but also the entire conserved network of His-685, His-718, and what we suggest is a catalytic water molecule is important in the activation of the catalytic nucleophile.

Sweet Drugs for Bad Bugs: A Glycomimetic Strategy against the DC-SIGN-Mediated Dissemination of SARS-CoV-2.

The C-type lectin receptor DC-SIGN is a pattern recognition receptor expressed on macrophages and dendritic cells. It has been identified as a promiscuous entry receptor for many pathogens, including epidemic and pandemic viruses such as SARS-CoV-2, Ebola virus, and HIV-1. In the context of the recent SARS-CoV-2 pandemic, DC-SIGN-mediated virus dissemination and stimulation of innate immune responses has been implicated as a potential factor in the development of severe COVID-19. Inhibition of virus binding to DC-SIGN, thus, represents an attractive host-directed strategy to attenuate overshooting innate immune responses and prevent the progression of the disease. In this study, we report on the discovery of a new class of potent glycomimetic DC-SIGN antagonists from a focused library of triazole-based mannose analogues. Structure-based optimization of an initial screening hit yielded a glycomimetic ligand with a more than 100-fold improved binding affinity compared to methyl α-d-mannopyranoside. Analysis of binding thermodynamics revealed an enthalpy-driven improvement of binding affinity that was enabled by hydrophobic interactions with a loop region adjacent to the binding site and displacement of a conserved water molecule. The identified ligand was employed for the synthesis of multivalent glycopolymers that were able to inhibit SARS-CoV-2 spike glycoprotein binding to DC-SIGN-expressing cells, as well as DC-SIGN-mediated trans-infection of ACE2+ cells by SARS-CoV-2 spike protein-expressing viruses, in nanomolar concentrations. The identified glycomimetic ligands reported here open promising perspectives for the development of highly potent and fully selective DC-SIGN-targeted therapeutics for a broad spectrum of viral infections.

Revealing Escherichia coli type II l-asparaginase active site flexible loop in its open, ligand-free conformation

Since 1993, when the structure of Escherichia coli type II l-asparaginase (EcAII) in complex with l-aspartate was firstly reported, many structures of the wild type and mutated enzyme have been deposited in the Protein Data Bank. None of them report the full structure of the monomer in its ligand-free, open conformation, mainly because of the high dynamic and flexibility of the active site flexible loop. Here we report for the first time the structure of EcAII wild type in its open conformation comprising, for at least one protomer, clear electron density for the active site flexible loop (PDB ID: 6YZI). The structural element is highly mobile and it is transposed onto the rigid part of the active site upon substrate binding to allow completion of the enzyme catalytic center, thanks to key residues that serve as hinges and anchoring points. In the substrate binding pocket, several highly conserved water molecules are coordinated by residues involved in substrate binding, comprising two water molecules very likely involved in the enzyme catalytic process. We also describe, by molecular dynamics simulations, how the transposition of the loop, besides providing the proximity of residues needed for catalysis, causes a general stabilization of the protein.

New biochemical insights into the dynamics of water molecules at the GMP or IMP binding site of human GMPR enzyme: A molecular dynamics study.

Human GMP reductase (hGMPR) enzyme is involved in a cellular metabolic pathway, converting GMP into IMP, and also it is an important target for anti-leukemic agents. Present computational investigations explain dynamical behavior of water molecules during the conformational transition process from GMP to IMP using molecular dynamics simulations. Residues at substrate-binding site of cancerous protein (PDB Id. 2C6Q) are mostly more dynamic in nature than the normal protein (PDB Id. 2BLE). Nineteen conserved water molecules are identified at the GMP/IMP binding site and are classified as (i) conserved stable dynamic and (ii) infrequent dynamic. Water molecules W11, W14, and W16 are classified as conserved stable dynamic due to their immobile character, whereas remaining water molecules (W1, W2, W3, W4, W5, W7, W8, W9, W10, W12, W13, W15, W17, W18, and W19) are infrequent with dynamic nature. Entrance or displacement of these infrequent water molecules at GMP/IMP sites may occur due to forward and backward movement of reference residues involving ligands. Four water molecules of hGMPR-I and nine water molecules of hGMPR-II are observed in repetitive transitions from GMP to IMP pathway, which indicates discrimination between two isoforms of hGMPRs. Water molecules in cancerous protein are more dynamic and unstable compared to normal protein. These water molecules execute rare dynamical events at GMP binding site and could assist in detailed understanding of conformational transitions that influence the hGMPR's biological functionality. The present study should be of interest to the experimental community engaged in leukemia research and drug discovery for CML cancer.

Structural and dynamical heterogeneity of water trapped inside Na+-pumping KR2 rhodopsin in the dark state.

Photoisomerization in the retinal leads to a channel opening in rhodopsins that triggers translocation or pumping of ions/protons. Crystal structures of rhodopsins contain several structurally conserved water molecules. It has been suggested that water plays an active role in facilitating the ion pumping/translocation process by acting as a lubricant in these systems. In this paper, we systematically investigate the localization, structure, dynamics, and energetics of the water molecules along the channel for the resting/dark state of KR2 rhodopsin. By employing several microseconds long atomistic molecular dynamics simulation of this trans-membrane protein system, we demonstrate the presence of five distinct water containing pockets/cavities separated by gateways controlled by protein side-chains. There exists a strong hydrogen bonded network involving these buried water molecules and functionally important key residues. We present evidence of significant structural and dynamical heterogeneity in the water molecules present in these cavities, with very rare exchange between them. The exchange time scale of such buried water with the bulk has an extremely wide range, from tens of nanoseconds to >1.5µs. The translational and rotational dynamics of buried water are found to be strongly dependent on the protein cavity size and local interactions with a classic signature of trapped diffusion and rotational anisotropy.

Molecular modeling and molecular dynamics simulation studies on thyroid hormone receptor from Rattus norvegicus: role of conserved water molecules.

Thyroid hormone receptor (THR) belongs to the nuclear receptor (NR) superfamily that is activated by binding of appropriate ligand molecules (thyroid hormones). These receptors directly bind to specific DNA sequences for gene expression, which is essential for metabolism, homeostasis, and the development of organisms, making it an important drug target. Extensive MD-simulation studies of triiodothyronine (T3) docked modeled rnTHRβ1 structures have indicated the presence of twelve conserved water molecules at the DNA-DBD (DNA binding domain) interface. The W1-W5 water centers have been involved in the recognition between the A-chain of DBD to C-chain of DNA, W6 and W7 mediated the interaction between A-chain of DBD and D-chain of DNA, W8 and W9 recognized the B-chain of DBD and C-chain of DNA, and W9-W12 centers conjugated the residues of B-chain of DBD to D-chain of DNA through hydrogen bonds. The conformation flexibility of Phe272 and Met313 residues in the absence of T3 at the LBD (ligand-binding domain) region have been observed and reported.

Understanding the binding conformation of ceftolozane/tazobactam with Metallo-β-lactamases VIM-5 and IMP-7 of Pseudomonas aeruginosa: A molecular docking and virtual screening process.

Pseudomonas aeruginosa (P. aeruginosa) is one of the community-acquired and healthcare-associated infections causing organisms. It has become resistant to most of the available antibiotics and is termed multi-drug resistance (MDR). There are a limited number of antibiotics are available to treat such MDR organism causing infections. The ceftolozane/tazobactam is one among the combination drug therapy (CDT) prescribed for the treatment of MDR causing infections. The resistance for the same CDT was observed in the MDR P. aeruginosa harboring VIM-5 and IMP-7 Metallo beta (β)-lactamases (MBLs). To explore the resistance mechanism at the molecular level, docking studies were carried out for antibiotics against VIM-5 and IMP-7 MBLs. The Zn2 metal ions carry out the nucleophile attack on the carbonyl carbon of the β-lactam ring along with conserved water molecules. To find lead compounds against the MBLs, a virtual screening process was carried out. We have employed MODELLER for structure modeling, AutoDock for molecular docking and AutoDock Vina, Molinspiration, PASS prediction & admetSAR in virtual screening. The search of low binding energy ceftolozane analogs against VIM-5 and IMP-7 MBLs has resulted in the ZINC000029060075 and ZINC000009163636 analogs. Similarly, the screening of high binding energy inhibitors against VIM-5 and IMP-7 MBLs has resulted in ZINC000003831503 and ZINC000000897247 tazobactam analogs respectively. The ADMET prediction results in the non-toxicity of the lead compounds. Our study may provide new insights for the scientist who are designing novel drugs against MDR P. aeruginosa causing infections.

Role of water in the determination of protonation states of titratable residues.

Water is the fundamental unit for living being, and its contribution in variety of crucial cellular functions is widely accepted. The presence of water molecules in protein's environment also accounts for structural optimization, in which highly conserved water molecules ensure structural stability of the biomolecule by providing protein-water (solute-solvent) hydrogen-bond interaction networks. Similarly, protonation states and pKa values of individual amino acid residues are also influenced by neighboring water molecules present in the protein's vicinity. In the present study, we have highlighted the role of water molecules in hydrogen-bond optimization, in determining pKa values and protonation states of titratable residues in JH2 domain of JAK2 apo protein. We found that inclusion or exclusion of water molecules while calculating pKa and assigning protonation states to amino acid residues during the molecular system build-up step resulted in slight differences in pKa values of few titratable residues and alternative protonation states of a certain residue. Accordingly, different protonation states of ionizable residues offer differing interaction patterns. Thus, we inferred that the presence of water optimizes the hydrogen-bond interactions by forming direct protein-water interactions and by linking via protein-protein bridging interactions. However, in the absence of water, the interaction pattern is somewhat disrupted. We assume that water molecules could modulate the plausibility of a particular protonation state of titratable residues on the basis of its fit with the local environment, by utilizing some particular hydrogen-bond contacts that would remain unexploited in the absence of water.

AquaPELE: A Monte Carlo-Based Algorithm to Sample the Effects of Buried Water Molecules in Proteins

Water is frequently found inside proteins, carrying out important roles in catalytic reactions or molecular recognition tasks. Therefore, computational models that aim to study protein-ligand interactions usually have to include water effects through explicit or implicit approaches to obtain reliable results. While full explicit models might be too computationally daunting for some applications, implicit models are normally faster but omit some of the most important contributions of water. This is the case of our in-house software, called protein energy landscape exploration (PELE), which uses implicit models to speed up conformational explorations as much as possible; the lack of explicit water sampling, however, limits its model. In this work, we confront this problem with the development of aquaPELE. It is a new algorithm that extends the exploration capabilities while keeping efficiency as it employs a mixed implicit/explicit approach to also take into account the effects of buried water molecules. With an additional Monte Carlo (MC) routine, a set of explicit water molecules is perturbed inside protein cavities and their effects are dynamically adjusted to the current state of the system. As a result, this implementation can be used to predict the principal hydration sites or the rearrangement and displacement of conserved water molecules upon the binding of a ligand. We benchmarked this new tool focusing on estimating ligand binding modes and hydration sites in cavities with important interfacial water molecules, according to crystallographic structures. Results suggest that aquaPELE sets a fast and reliable alternative for molecular recognition studies in systems with a strong water-dependency.