Fingerprint directed scaffold hopping for identification of CCR2 antagonists

Chemokine receptors have evolved as attractive targets for disease conditions which arise due to immunomodulation involving host-defense mechanisms. CCR2, a chemokine receptor, is targeted for diseases like arthritis, multiple sclerosis, vascular disease, obesity, and type 2 diabetes. This study provides a new strategy of a ligand based technique which exploits fingerprint led fragment features in conjunction with structure-guided design for identifying new scaffolds for CCR2. A fragment based mining (FBM) technique was employed on a chemical database to identify novel scaffold hops. The hits were subjected to 3-point pharmacophore fingerprint procedures with Tanimoto similarity metric to compare pharmacophoric fingerprints. The final 66 hits generated by these exercises were predicted by the validated HQSAR model, and the top predicted were suggested as probable scaffolds for CCR2 antagonism. The identified scaffolds were validated through molecular docking studies. The ligands were docked by providing receptor flexibility in the extra cellular domain (1 and 3), N terminal domain, and in the transmembrane (TM1 & TM7) helix region with IFD approach. Some of the scaffolds showed H-bonding potential which was not explored by the data set molecules. All identified scaffolds highlighted a key hydrogen bonding interaction with Thr292 as supported by mutational studies. The observed pi stacking interaction with Tyr188 in data set molecules was also produced by the new scaffolds. Taking the advantage of receptor flexibility the scaffolds explored the hydrophobic binding cleft between helix 1 and 7 occupied by residues Leu44, Leu45, Leu48 and Ile300, Ile303, Ile304, respectively. Two of the identified molecules have promising outcomes and can be considered as novel scaffolds for CCR2 binding.     

Interactions of peptide mimics of hyaluronic acid with the receptor for hyaluronan mediated motility (RHAMM)

Summary Using the hyaluronic acid (HA) binding region of the receptor for hyaluronan-mediated motility (RHAMM) as a model, a molecular perspective for peptide mimicry of the natural ligand was established by comparing the interaction sites of HA and unnatural peptide–ligands to RHAMM. This was accomplished by obtaining a series of octapeptide–ligands through screening experiments that bound to the HA binding domains of RHAMM (amino acids 517–576) and could be displaced by HA. These molecules were computationally docked onto a three-dimensional NMR based model of RHAMM. The NMR model showed that RHAMM(517–576) was a set of three helices, two of which contained the HA binding domains (HABDs) flanking a central groove. The structure was stabilized by hydrophobic interactions from four pairs of Val and Ile side chains extending into the groove. The presence of solvent exposed, positively charged side chains spaced 11Å apart matched the spacing of negative charges on HA. Docking experiments using flexible natural and artificial ligands demonstrated that HA and peptide–mimetics preferentially bound to the second helix that contains HABD-2. Three salt bridges between HA carboxylates and Lys548, Lys553 and Lys560 and two hydrophobic interactions involving Val538 and Val559 were predicted to stabilize the RHAMM-HA complex. The high affinity peptides and HA utilized the same charged residues, with additional contacts to other basic residues. However, hydrophobic contacts do not contribute to affinity for peptide ligand-RHAMM complexes. These results offer insight into how selectivity is achieved in the binding of HA to RHAMM, and how peptide competitors may compete for binding with HA on a single hyaladherin.     

Peptide models XXXI. Conformational properties of hydrophobic residues shaping the core of proteins. An ab initio study of N‐formyl‐L‐valinamide and N‐formyl‐L‐phenylalaninamide

Employing introductory (3‐21G RHF) and medium‐size (6‐311++G** B3LYP) ab initio calculations, complete conformational libraries, containing as many as 27 conformers, have been determined for diamide model systems incorporating the amino acids valine (Val) and phenylalanine (Phe). Conformational and energetic properties of these libraries were analyzed. For example, significant correlation was found between relative energies from 6‐311++G** B3LYP and single‐point B3LYP/6‐311++G**//RHF/3‐21G calculations. Comparison of populations of molecular conformations of hydrophobic aromatic and nonaromatic residues, based on their ab initiorelative energies, with their natural abundance indicates that, at least for the hydrophobic core of proteins, the conformations of Val (Ile, Leu) and Phe (Tyr, Trp) are controlled by the local energetic preferences of the respective amino acids. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 732–751, 2001     

Insights into phenylalanine derivatives recognition of VLA-4 integrin: from a pharmacophoric study to 3D-QSAR and molecular docking analyses

The very late antigen-4 (VLA-4), also known as integrin alpha4beta1, is expressed on monocytes, T- and B-lympohocytes, basophils, and eosinophils and is involved in the massive recruitment of granulocytes in different pathological conditions such as multiple sclerosis and asthma. VLA-4 interacts with its endogenous ligand VCAM-1 during chronic inflammation, and blockade of VLA-4 /VCAM-1 interaction is a potential target for immunosuppression. Two classes of VLA-4 antagonists have so far been reported: beta-amino acid derivatives containing a diaryl urea moiety (BIO-1211) and phenylalanine derivatives (TR-14035). With the aim of clarifying the structural basis responsible for VLA-4 recognition by phenylalanine derivatives, we developed a combined computational study on a set of 128 antagonists available through the literature. Our computational approach is composed of three parts. (i) A VCAM-1 based pharmacophore was constructed with a restricted number of phenylalanine derivatives to identify the region of the protein that resembles synthetic antagonists. The pharmacophore was instrumental in constructing an alignment of a set of 128 compounds. This alignment was exploited to build a pseudoreceptor model with the RECEPTOR program. (ii) 3D-QSAR analysis was carried out on the computed electrostatic and steric interaction energies with the pseudoreceptor surface. The 3D-QSAR analysis yielded a predictive model able to explain much of the variance of the 128 antagonists. (iii) A homology modeling study of the headpiece of VLA-4 based on the crystal structure of alphavbeta3 was performed. Docking experiments of TR-14035 into the binding site of VLA-4 aided the interpretation of the 3D-QSAR model. The obtained results will be fruitful for the design of new potent and selective antagonists of VLA-4.     

Fabrication of nanofibers with uniform morphology by self-assembly of designed peptides

Fabrication of controlled peptide nanofibers with homogeneous morphology has been demonstrated. Amphiphilic beta-sheet peptides were designed as sequences of Pro-Lys-X(1)-Lys-X(2)-X(2)-Glu-X(1)-Glu-Pro. X(1) and X(2) were hydrophobic residues selected from Phe, Ile, Val, or Tyr. The peptide FI (X(1)=Phe; X(2)=Ile) self-assemble into straight fibers with 80-120 nm widths and clear edges, as examined by transmission electron microscopy (TEM) and atomic force microscopy (AFM). The fiber formation is performed in a hierarchical manner: beta-sheet peptides form a protofibril, the protofibrils assemble side-by-side to form a ribbon, and the ribbons then coil in a left-handed fashion to make up a straight fiber. These type of fibers are formed from peptides possessing hydrophobic aromatic Phe residue(s). Furthermore, a peptide with Ala residues at both N and C termini does not form fibers (100 nm scale) with clear edges; this causes random aggregation of small pieces of fibers instead. Thus, the combination of unique amphiphilic sequences and terminal Pro residues determine the fiber morphology.     

Protein:Ligand binding free energies: A stringent test for computational protein design

A computational protein design method is extended to allow Monte Carlo simulations where two ligands are titrated into a protein binding pocket, yielding binding free energy differences. These provide a stringent test of the physical model, including the energy surface and sidechain rotamer definition. As a test, we consider tyrosyl‐tRNA synthetase (TyrRS), which has been extensively redesigned experimentally. We consider its specificity for its substrate l ‐tyrosine (l ‐Tyr), compared to the analogs d ‐Tyr, p‐acetyl‐, and p‐azido‐phenylalanine (ac‐Phe, az‐Phe). We simulate l ‐ and d ‐Tyr binding to TyrRS and six mutants, and compare the structures and binding free energies to a more rigorous “MD/GBSA” procedure: molecular dynamics with explicit solvent for structures and a Generalized Born + Surface Area model for binding free energies. Next, we consider l ‐Tyr, ac‐ and az‐Phe binding to six other TyrRS variants. The titration results are sensitive to the precise rotamer definition, which involves a short energy minimization for each sidechain pair to help relax bad contacts induced by the discrete rotamer set. However, when designed mutant structures are rescored with a standard GBSA energy model, results agree well with the more rigorous MD/GBSA. As a third test, we redesign three amino acid positions in the substrate coordination sphere, with either l ‐Tyr or d ‐Tyr as the ligand. For two, we obtain good agreement with experiment, recovering the wildtype residue when l ‐Tyr is the ligand and a d ‐Tyr specific mutant when d ‐Tyr is the ligand. For the third, we recover His with either ligand, instead of wildtype Gln. © 2015 Wiley Periodicals, Inc.     

Structure–activity relationships of cannabinoids: A joint CoMFA and pseudoreceptor modelling study

A cannabinoid pseudoreceptor model for the CB1-receptor has been constructed for 31 cannabinoids using the molecular modelling software YAK. Additionally, two CoMFA studies were performed on these ligands, the first of which was conducted prior to the building of the pseudoreceptor. Its pharmacophore is identical with the initial superposition of ligands used for pseudoreceptor construction. In contrast, the ligand alignment for the second CoMFA study was taken directly from the final cannabinoid pseudoreceptor model. This altered alignment gives markedly improved cross-validated r² values as compared to those obtained from the original alignment with values of 0.79 and 0.63, respectively, for five components. However, the pharmacophore alignment has the better predictive ability. Both the CoMFA and pseudoreceptor methods predict the free energy of binding of test ligands well.     

Exploring the structural requirements in multiple chemical scaffolds for the selective inhibition of Plasmodium falciparum calcium-dependent protein kinase-1 (PfCDPK-1) by 3D-pharmacophore modelling,and docking studies

Current research on antimalarial protein kinases has provided an opportunity to design kinase-based antimalarial drugs. We have developed a common feature-based pharmacophore model from a set of multiple chemical scaffolds including derivatives of 3,6-imidazopyridazines, pyrazolo[2,3-d]pyrimidines and imidazo[1,5-a]pyrazines, in order to incorporate the maximum structural diversity information in the model for the Plasmodium falciparum calcium-dependent protein kinase-1 (PfCDPK-1) target. The best pharmacophore model (Hypo-1) with the essential features of two hydrogen bond donors (HBD), one hydrophobic aromatic (HYAr) and one ring aromatic (RA) showed the classification accuracies of 86.27%, 78.43% and 100.00% in labelling the training and test set (test set-1 and test set-2) compounds into more active and less active classes. In order to identify the crucial interaction between multiple scaffold ligands and the target protein, we first developed the homology model using a template structure of P. bergheii (PbCDPK1; PDB ID: 3Q5I), and thereafter performed the docking studies. The residues such as Lys85, Phe147, Tyr148, Leu198, Val211, and Asp212 were found to be the most important interacting residues for possessing PfCDPK-1 inhibitory activity.     

Homology modeling and 3D–QSAR study of benzhydrylpiperazine δ opioid receptor agonists

The binding affinity of a series of benzhydrylpiperazine δ opioid receptor agonists were pooled and evaluated by using 3D-QSAR and homology modeling/molecular docking methods. Ligand-based CoMFA and CoMSIA 3D-QSAR analyses with 46 compounds were performed on benzhydrylpiperazine analogues by taking the most active compound BW373U86 as the template. The models were generated successfully with q² value of 0.508 and r² value of 0.964 for CoMFA, and q² value of 0.530 and r² value of 0.927 for CoMSIA. The predictive capabilities of the two models were validated on the test set with R²_pred value of 0.720 and 0.814, respectively. The CoMSIA model appeared to work better in this case. A homology model of active form of δ opioid receptor was established by Swiss-Model using a reported crystal structure of active μ opioid receptor as a template, and was further optimized using nanosecond scale molecular dynamics simulation. The most active compound BW373U86 was docked to the active site of δ opioid receptor and the lowest energy binding pose was then used to identify binding residues such as s Gln105, Lys108, Leu125, Asp128, Tyr129, Leu200, Met132, Met199, Lys214, Trp274, Ile277, Ile304 and Tyr308. The docking and 3D-QSAR results showed that hydrogen bond and hydrophobic interactions played major roles in ligand-receptor interactions. Our results highlight that an approach combining structure-based homology modeling/molecular docking and ligand-based 3D-QSAR methods could be useful in designing of new opioid receptor agonists.     

Calculation of relative binding affinities of fructose 1,6-bisphosphatase mutants with adenosine monophosphate using free energy perturbation method

The free energy perturbation (FEP) methodology is the most accurate means of estimating relative binding affinities between inhibitors and protein variants. In this article, the importance of hydrophobic and hydrophilic residues to the binding of adenosine monophosphate (AMP) to the fructose 1,6-bisphosphatase (FBPase), a target enzyme for type-II diabetes, was examined by FEP method. Five mutations were made to the FBPase enzyme with AMP inhibitor bound: 113Tyr --> 113Phe, 31Thr --> 31Ala, 31Thr --> 31Ser, 177Met --> 177Ala, and 30Leu --> 30Phe. These mutations test the strength of hydrogen bonds and van der Waals interactions between the ligand and enzyme. The calculated relative free energies indicated that: 113Tyr and 31Thr play an important role, each via two hydrogen bonds affecting the binding affinity of inhibitor AMP to FBPase, and any changes in these hydrogen bonds due to mutations on the protein will have significant effect on the binding affinity of AMP to FBPase, consistent to experimental results. Also, the free energy calculations clearly show that the hydrophilic interactions are more important than the hydrophobic interactions of the binding pocket of FBPase.     

Improving the quality of 3D-QSAR by using flexible-ligand receptor models

To address the problems associated with molecular conformations and alignments in the 3D-QSAR studies, we have developed the Flexible Ligand - Atomic Receptor Model (FLARM) 2.0 method. The FLARM 2.0 method has three unique features as compared to other pseudoreceptor model methods: (1) the training ligands are flexibly optimized inside the receptors to achieve minimal docking energies; (2) the receptor atoms are spatially moveable in the process of genetic evolving in order to avoid improper initial receptor shapes; and (3) void receptor sites are specially favored in order to obtain open receptor models that allow large gaps. Advantages of an open model include less noise information, a smaller risk of overfitting, and ease of locating the key interaction sites. The latter two features, inherited from the previous FLARM 1.0 method, can improve the predictive ability of the 3D-QSAR models, while the first feature is newly implemented to relieve the uncertainty caused by improper conformation and alignment. Three FLARM 2.0 case studies were performed, and the results show that FLARM 2.0 models are highly predictive and robust. FLARM 2.0 pseudoreceptor models can correspond well with the pharmacophore models and/or the binding sites of the real protein receptors.     

Structure-activity study of intact porcine motilin

Biologically important sites on intact porcine motilin (pMTL) were explored using its partial peptides. The partial peptides were synthesized using Fmoc (9-fluorenylmethyloxycarbonyl) solid phase methodology, and tested for the binding activity to motilin receptor and the smooth muscle contractile activity. The results were as follows: important residues for the contractile activity were found to be Phe1, Ile4, and Tyr7, and an open space existed beyond the N-terminus between motilin and its receptor. On the model of interaction between motilin and motilin receptor evolved from these results, the three points of interaction, due to Phe1, Ile4, and Tyr7, and the presence of an open space were expected. The motilin agonist and antagonist, designed on this model, will help the inquiry into motilin associated diseases.     

Ab initio quantum mechanical study of the binding energies of human estrogen receptor alpha with its ligands: an application of fragment molecular orbital method

We have theoretically examined the relative binding affinities (RBA) of typical ligands, 17beta-estradiol (EST), 17alpha-estradiol (ESTA), genistein (GEN), raloxifene (RAL), 4-hydroxytamoxifen (OHT), tamoxifen (TAM), clomifene (CLO), 4-hydroxyclomifene (OHC), diethylstilbestrol (DES), bisphenol A (BISA), and bisphenol F (BISF), to the alpha-subtype of the human estrogen receptor ligand-binding domain (hERalpha LBD), by calculating their binding energies. The ab initio fragment molecular orbital (FMO) method, which we have recently proposed for the calculations of macromolecules such as proteins, was applied at the HF/STO-3G level. The receptor protein was primarily modeled by 50 amino acid residues surrounding the ligand. The number of atoms in these model complexes is about 850, including hydrogen atoms. For the complexes with EST, RAL, OHT, and DES, the binding energies were calculated again with the entire ERalphaLBD consisting of 241 residues or about 4000 atoms. No significant difference was found in the calculated binding energies between the model and the real protein complexes. This indicates that the binding between the protein and its ligands is well characterized by the model protein with the 50 residues. The calculated binding energies relative to EST were very well correlated with the experimental RBA (the correlation coefficient r=0.837) for the ligands studied in this work. We also found that the charge transfer between ER and ligands is significant on ER-ligand binding. To our knowledge, this is the first achievement of ab initio quantum mechanical calculations of large molecules such as the entire ERalphaLBD protein.     

Exploring the applicability of density functional tight binding to transition metal ions. Parameterization for nickel with the spin-polarized DFTB3 model

In this work, we explore the applicability and limitations of the current third order density functional tight binding (DFTB3) formalism for treating transition metal ions using nickel as an example. To be consistent with recent parameterization of DFTB3 for copper, the parametrization for nickel is conducted in a spin-polarized formulation and with orbital-resolved Hubbard parameters and their charge derivatives. The performance of the current parameter set is evaluated based on structural and energetic properties of a set of nickel-containing compounds that involve biologically relevant ligands. Qualitatively similar to findings in previous studies of copper complexes, the DFTB3 results are more reliable for nickel complexes with neutral ligands than for charged ligands; nevertheless, encouraging agreement is noted in comparison to the reference method, B3LYP/aug-cc-pVTZ, especially for structural properties, including cases that exhibit Jahn–Teller distortions; the structures also compare favorably to available X-ray data in the Cambridge Crystallographic Database for a number of nickel-containing compounds. As to limitations, we find it is necessary to use different d shell Hubbard charge derivatives for Ni(I) and Ni(II), due to the distinct electronic configurations for the nickel ion in the respective complexes, and substantial errors are observed for ligand binding energies, especially for charged ligands, d orbital splitting energies and splitting between singlet and triplet spin states for Ni(II) compounds. These observations highlight that future improvement in intra-d correlation and ligand polarization is required to enable the application of the DFTB3 model to complex transition metal ions. © 2018 Wiley Periodicals, Inc.     

A molecular model of a point mutation (Val297Met) in the serine protease domain of protein C

A heterozygous GTG to ATG (Val297Met) mutation was detected in a patient with inherited protein C deficiency and deep vein thrombosis. Cosegregation of the mutation with protein C deficiency was observed through a family pedigree study. Molecular models of the serine protease domains of wild type and mutant protein C were constructed by standard comparative method. Val 297 was found to be located in the hydrophobic core of the protein. Although the substitution of Met for Val does not greatly alter the hydrophobicity of the protein, it introduces a bulkier side chain, which yields steric hindrance between this residue and adjacent residues, such as Met364, Tyr393, Ile321, Ile323, and Val378. It seems that the Met can not fit into the tight packing into which it is trapped, thereby probably inducing misfolding and/or greater instability of the protein. Such misfolding and/or instability thereby eventually disturbs the catalytic triad, in consistent with the observed type I deficiency state.     

Quantum mechanical studies of residue-specific hydrophobic interactions in p53-MDM2 binding

Quantum chemistry calculations at the levels of MP2/cc-pVDZ and MP2/cc-PVTZ have been carried out to study residue-specific interactions at the hydrophobic p53-MDM2 binding interface. The result of the calculation, based on structures from nanosecond molecular dynamics simulation, revealed that (19)Phe, (22)Leu, and (23)Trp of p53 have the strongest binding interaction with MDM2 followed by (26)Leu and (27)Pro. The specific residues of MDM2 that have dominant binding interactions with p53 are specifically identified to be (51)Lys, (54)Leu, (62)Met, (67)Tyr, (72)Gln, (94)Lys, (96)His, and (100)Tyr. The p53-MDM2 binding interaction is dominated by van der Waals interaction and to a lesser degree by electrostatic interaction. The MP2 results are in generally good agreement with those from the force field calculation while the DFT/B3LYP calculation failed to give attractive interaction energies for certain residue-residue interactions due to the lack of dispersion energy.     

A computational analysis of the binding model of MDM2 with inhibitors

Abstract  

It is a new and promising strategy for anticancer drug design to block the MDM2-p53 interaction using a non-peptide small-molecule inhibitor. We carry out molecular dynamics simulations to study the binding of a set of six non-peptide small-molecule inhibitors with the MDM2. The relative binding free energies calculated using molecular mechanics Poisson–Boltzmann surface area method produce a good correlation with experimentally determined results. The study shows that the van der Waals energies are the largest component of the binding free energy for each complex, which indicates that the affinities of these inhibitors for MDM2 are dominated by shape complementarity. The A-ligands and the B-ligands are the same except for the conformation of 2,2-dimethylbutane group. The quantum mechanics and the binding free energies calculation also show the B-ligands are the more possible conformation of ligands. Detailed binding free energies between inhibitors and individual protein residues are calculated to provide insights into the inhibitor-protein binding model through interpretation of the structural and energetic results from the simulations. The study shows that G1, G2 and G3 group mimic the Phe19, Trp23 and Leu26 residues in p53 and their interactions with MDM2, but the binding model of G4 group differs from the original design strategy to mimic Leu22 residue in p53.     

EGFR和4-苯胺喹唑啉类抑制剂之间相互作用模式的研究

采用分子动力学和MM/PBSA相结合的方法预测了表皮生长因子受体和4-苯胺喹 啉类抑制剂的相互作用模式。在分子动力学采样的基础上,采用MM/PBSA的方法分 别预测了四种可能结合模式下表皮生长因子受体和4-苯胺喹唑啉类抑制剂间的结合 自由能。在MM/PBSA计算中,受体和抑制剂之间的非键相互作用能采用分子力学 (MM)的方法得到;溶剂效应中极性部分对自由能的贡献通过解Possion- Boltzmanne (PB)方程的方法得到;溶液效应中非极性部分对自由能的贡献则通过 分子表面积计算(SA)的方法得到。计算表明,在四种结合模式下,表皮生长因子受 体和4-苯胺喹唑啉类抑制剂之间的结合自由能有较大的差别。在最佳的相互作用模 式中,抑制剂的苯胺部分位于活性口袋的底部,能够与受体残基的非极性侧链产生 很强的范德华和疏水相互作用。抑制剂喹唑啉环上的N(1)原子能够和Met-769上的 NH形成稳定的氢键,而抑制剂上的N(3)原子则和周围的一个水分子形成氢键。同时 ,抑制剂双环上的取代基团也能和活性口袋外部的部分残基形成一定的范德华和疏 水相互作用。最佳结合模式能够很好地解释已有抑制剂结构和活性间的关系。