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European Journal of Medicinal Chemistry xxx (2014) 1e3

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European Journal of Medicinal Chemistry

journal homepage: http: / /www.elsevier .com/locate/ejmech

Editorial

Molecular dynamics: New advances in drug discovery

1. Preface

Over the past years, a myriad of new biologically active mole-cules have been synthesized or isolated from natural sources. But,in the last decade, despite the intense research efforts devoted tothe discovery of new effective drugs, out of 10,000 new drug candi-dates proposed per year only one has been selected for clinicaltreatments. Why medicinal chemistry makes such lowprogression?

Plainly, there is a crying need to findways to design (and screen)an increasingly large number of promising drug candidates at thelowest possible cost. Moreover, the entire drug discovery processhas to be streamlined in such a way that compounds that passthe screening move quickly along the development pipeline. Themajority of the significant successes in the medicinal chemistryarea have been mostly achieved after the discovery of novel targetse e.g. metabolic pathways and enzymes. But now it is fair to statethat, while chemists have been successful in providing new medi-cines that have significantly improved our capacity to treat somediseases (e.g. the discovery of protease inhibitors for the treatmentof virus infections including HIV and kinase inhibitors used in thetherapy of several tumors to mention a few), we are still far awayfrom being able to tackle new challenging targets, such as amyloidaggregation and proteineprotein interaction as well [1]. The mostrelevant progresses have been made in the investigation of 3Dstructures of ligandereceptor complexes by NMR or X-rays crystal-lography. Both these two experimental techniques provide apowerful tool to scrutinize the binding of a biologically active sub-stance to its target. Drugetarget interactions can thus be investi-gated with high precision and displayed in three dimensions e akey preliminary step for the development of new active molecules.However X-rays crystallography provides only “frozen” proteinstructures and NMR methods may not be applied to largebiomacromolecules.

Computational chemistry has effectively complemented theseexperimental techniques providing a valuable contribution in thefield of drug discovery [1]. The term “virtual screening” was usedfor the first time in the late 90s. It describes the use of in silicomethods for the identification of new molecules with potentialemployment in therapy. Since those early attempts, many softwaretools have been developed and applied for the discovery of newlead compounds [2e8]. Nevertheless, although a large number ofvirtual screeningmethods have proved to be successful in many cir-cumstances [9] their real potential in driving a particular drug dis-covery project to the market has been questioned. It would seemthat the major success of virtual screening methods so far hasbeen the identification/elimination of the mass of inactive mole-cules for a certain target rather than the selection of active drug

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Please cite this article in press as: D. Milardi, M. Pappalardo, Molecular dyinal Chemistry (2014), http://dx.doi.org/10.1016/j.ejmech.2014.10.078

candidates [8]. Moreover, the development of virtual screeningsoftware with higher accuracy and reliability has been stagnatingin the last years, also probably because many academic groupshave focused on the application of virtual screening in the indus-trial R & D. Significant advances in virtual screening campaignsare expected to occur only after that a deeper understanding ofthe motions that regulate protein folding and/or ligandetarget dy-namics has been reached. Automated docking has made muchprogress in obtaining reliable ligand poses but the scoring functionsused to rank the different binding modes are still rather coarse[10e12]. Flexible binding modes, the role of water molecules andprotonation states should lie at the root of a new thinking of theuse of computational chemistry in drug design where a dynamicdescription of the ligandetarget complexes has to replace the tradi-tional e static e vision of the investigated systems. Molecular dy-namics (MD) simulations, due to the impetuous advances incomputing power and in simulation models, have recently evolvedinto a potent tool for investigating the dynamics and the structuresof biomolecular complexes [13]. MD simulations treat biomoleculesand solvation water as particles interacting one another through aclassical potential energy function named “forcefield”. Integrationof Newton's law of motions versus time provides information, atan atomistic level, of the conformational transitions of the investi-gated system. Of course, this wealth of information needs to beinterpreted and complemented, if possible, by experiments. Wellestablished experimental approaches are certainly available butoffer a limited degree of characterization of the mechanical proper-ties within large databases of targetedrugs complexes at a reason-able cost. On the other hand the analytical capabilities ofcomputational methods are evolving rapidly in their ability to accu-rately define the subtle and concerted structural dynamics thatcomprise targetedrug assemblies. Towards this goal, the challengeof this special issue is to bring together a collection of differentcomputational investigations required to link molecular mecha-nisms with cellular pathways and potential drug development.

Within this issue, H. Zhao and A. Caflisch, present several exam-ples of in silico discoveries of tyrosine kinase inhibitors and bromo-domain antagonists whose binding modes were predicted byautomated docking and further corroborated by MD simulations.Final validation by X-ray crystallography of the outcome of compu-tational data offers compelling evidence of the quality and reli-ability of these state-of-art molecular simulations.

M. Persico, L. Petrella, N. Orteca, A. Di Dato, M. Mariani, M.Andreoli, M. De Donato, G. Scambia, E. Novellino, C. Ferlini and C.Fattorusso have investigated, by using computational and biologicalstudies, the interactions of guanylate-binding protein 1 (GBP1)with Proviral Integration of Moloney virus kinase (PIM1). GBP1 isa GTP-binding protein and an important component of the innate

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Editorial / European Journal of Medicinal Chemistry xxx (2014) 1e32

immune response because it mediates cellular responses to inter-feron gamma in infection and inflammation. Not surprisingly,over-expression of GBP1 is associated with different types of tu-mors. GBP1 and PIM1 interact at a molar ratio 1:1 and it is knownthat this proteineprotein interaction initiates a signaling cascadethat induces resistance to common chemotherapeutics such aspaclitaxel. It turned out that GTP decreases the formation of theGBP1:PIM1 complex through an allosteric mechanism, paving theway to the identification of new compounds able to revert resis-tance to paclitaxel.

G. Palermo, U. Rothlisberger, A. Cavalli and M. De Vivo reviewhow computational studies based on classical molecular dynamics,full quantum mechanics, and hybrid QM/MM methods have shedlight on the binding and biological activity of some substratesand inhibitors of the Fatty Acid Amide Hydrolase (FAAH). FAAHplays an important role in the regulation of the endocannabinoidsystem and its inhibition is a promising strategy to cure a varietyof diseases including pain, and inflammation. The authors discusshow computations have been helpful for building structureeactiv-ity relationships of FAAH inhibitors.

One of the hallmarks of Alzheimer's disease (AD) is the aggrega-tion of the amyloid b (Ab) peptide. P. Derreumaux, B. Tarus, P. H.Nguyen, O. Berthoumieu, P. Faller and A. J. Doig, have employedreplica exchange molecular dynamics to simulate the self-assembly of the amyloid b (Ab) peptide in the presence of 1,4-naphthoquinon-2-yl-L-tryptophan (NQTrp), a small molecule witha known capacity to inhibit amyloid aggregation. The authorsshow that the population of b-hairpin is reduced by a factor of 1.5and the population of a-helix in the region 17e24 is increased bya factor of two upon NQTrp binding to Ab. The results of this studypoint to these two evidences as key factors to reduce the patho-genic formation of peptide dimers and may suggest routes to thedesign of novel amyloid inhibitors with improved potency.

M. Cronin, M. J. Coolbaugh, D. Nellis, J. Zhu, D. W. Wood, R. Nus-sinov and Ma Buyong have combined computations and experi-ments to examine the impact of the V67L mutation on thestability and conformational dynamics of theMycobacterium tuber-culosis RecA (Mtu recA) mini-intein splicing domain. Inteins cata-lyze the ligation of flanking host exteins while excisingthemselves. Inteins may have interesting applications in drugdesign, as they are capable of undergoing selective activation of aprotein, drug, or drug encapsulation in a viral coat. However, it isstill a challenge to tightly control intein function within mamma-lian cells. The authors evidence that the V67L mutation stabilizesthe global structure and that cooperative dynamics of all intein re-gions appear more important for intein function than high stability.These studies suggest that quenching the structural dynamics ofinteins through engineered allosteric interactions may deactivatetheir splicing.

J. O. S. Giacoppo, D. T. Mancini, A. P. Guimaraes, A. S. Gonclaves,E. F. F. da Cunha, T. C. C. França, A. S. Gonçalves, and T. C. Ramalhohave applied a mix of Molecular Dynamics, Docking calculationand experimental methods to predict new therapies against Bacil-lus anthracis (BaDHFR). The relevance of this study is quite evidentin order to prevent health issue in case of biological war. In partic-ular they proposed new molecules with potential activities againstBaDHFR.

A. P. Guimar~aes, F. R. de Souza, A. A. Oliveira, A. S. Gonçalves, R. B.de Alencastro, T. C. Ramalho, T. C. C. França have constructed a ho-mology model of the enzyme thymidylate kinase fromVariola virus(VarTMPK). Next, they used the antivirals cidofovir and acyclovir asreference compounds to choose eleven compounds as lead to thedrug design of inhibitors for VarTMPK. Docking and molecular dy-namics (MD) studies of the interactions of these compounds insideVarTMPK and human TMPK (HssTMPK) have evidenced that they

Please cite this article in press as: D. Milardi, M. Pappalardo, Molecular dyinal Chemistry (2014), http://dx.doi.org/10.1016/j.ejmech.2014.10.078

compete for the binding region of the substrate and were used topropose the structures of ten new inhibitors for VarTMPK. FurtherMD refinement simulations suggest that nine among ten are poten-tial selective inhibitors of VarTMPK.

U. S. Sudheendra, V. Dhople, A. Datta, R. K. Kar, C. E. Shelburne, A.Bhunia and A. Ramamoorthy have addressed, by an array of compu-tations and experimental techniques, the capacity of Human betadefensin-3 (HbD-3) to interact with zwitterionic or anionic modelmembranes. There is considerable interest in the function of thisprotein due to its antibacterial activity against Gram-positive Staph-ylococcus aureus. The whole of the results have demonstrated theimportance of the positively charged residues at the HbD-3 C-ter-minus in providing selectivity to Gram-negative bacteria.

L. Russo, M. Palmieri, J. V. Caso, G. D'Abrosca, D. Diana, G. Mal-gieri, I. Baglivo, C. Isernia, P. V. Pedone and R. Fattorusso, have char-acterized in silico the prokaryotic Cys2His2 zinc finger motif,included in the DNA binding region (Ros87) of Ros protein fromAgrobacterium tumefaciens. Cys2His2 zinc finger motifs are knownto be the most important structural domains playing a major rolein driving proteineDNA interactions in eukaryotes. The authorsinvestigated ROS87eDNA interactions using a combination of Nu-clear Magnetic Resonance (NMR) and Molecular Dynamics (MD)simulations data. They demonstrated that Ros87eDNA interactioninvolves the first two residues of the first a-helix of ROS87, andseveral residues located in the basic regions of the zinc-finger pro-tein. They have also shown that the introduction of the protein flex-ibility in docking studies is needed to improve, in terms of accuracy,the quality of the obtained models.

S. Decherchi, M. Masetti, I. Vyalov andW. Rocchia have reviewedexisting theories and methods to estimate solvent effects in Molec-ular Dynamics. Solvation plays a fundamental role in many biolog-ical processes and especially in molecular binding. Its preciseestimation is then of critical importance in MD simulations of bio-molecules. In most of the currently adopted models, the solvent isconsidered as a continuum homogenous medium (implicitmodels), while the solute can be represented at the atomic detailand at different levels of theory. The authors highlight that, despitetheir degree of approximation, implicit methods are still widelyemployed due to their convenient trade-off between accuracyand computational costs.

I. Autiero, M. Saviano and E. Langella have investigated, bymeans of a molecular dynamics approach, the structural proper-ties that drive the interaction of the chiral D-Lys-PNA (PeptideNucleic Acid) and the corresponding achiral PNA system withDNA as well as RNA complementary strands. Currently, PNA findsuseful applications in various areas of diagnostics and therapeu-tics including gene induction, for inhibition of translation, andalso as probe to identify specific gene sequences or to recognizeeven a single gene mutation. The results obtained reconcile withexperimental data and suggest that PNA/RNA recognition, ifcompared to DNA, results differently affected by the three D-Lysgroups on the PNA backbone. These evidences suggest whatmodifications should be taken into account for the developmentof new PNA-based molecules able to discriminate between DNAand RNA.

Transmissible spongiform encephalopathies or prion diseasesare characterized by accumulation of an insoluble form of the prionprotein in the brain. Therefore, various studies have been directedtoward the development of therapeutics for preventing the forma-tion of this pathogenic prion isoform. N. S. Pagadala, R. Perez-Pineiro, D. S. Wishart and J. A. Tuszynski have developed andapplied a new predictive 3D quantitative structureeactivity rela-tionship to rationalize the antiprion properties of 2-aminothiazoles.Molecular simulations combined with fluorescence studies haveevidenced that these compounds bind to pocket-D of SHaPrP

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near Trp145 confirming the importance of this site in targetingprion pathogenesis.

In conclusion, computational methods have become a majorfocus in the academic and industrial pharmaceutical research,and the expectations of new effective drugs emerging from themare considerable. But, in many cases determining a priori whetheror not a molecule will exhibit any therapeutical activity is a difficultprocess and as a matter of fact, of all the molecules designed bycomputational methods only a few have the planned biological ac-tivity. For example, we have still a limited control over the off-target activities of most of themolecules that are designed and syn-thesized. It is likely that in the very next future, new computationalalgorithms will routinely assist medicinal chemists in designingtheir own research thus fully realizing the potential of virtualscreening methods. To this aim, this special issue will hopefullyconstitute a reliable source of information for medicinal chemistsand contribute to attract researchers from other disciplines to getinvolved into this fascinating field.

References

[1] T. Hoffmann, R. Metternich, The future of medicinal chemistry, Angew. Chem.Int. Ed. 51 (2012) 8670e8671.

[2] G. Klebe, Virtual ligand screening: strategies, perspectives and limitations,Drug Discov. Today 11 (2006) 580e594.

[3] H. Mauser, W. Guba, Recent developments in de novo design and scaffoldhopping, Curr. Opin. Drug Discov. Devel. 11 (2008) 365e374.

[4] H. Koppen, Virtual screening e what does it give us? Curr. Opin. Drug Discov.Devel. 12 (2009) 397e407.

[5] C.M. Song, S.J. Lim, J.C. Tong, Recent advances in computer-aided drug design,Brief. Bioinform. 10 (2009) 579e591.

Please cite this article in press as: D. Milardi, M. Pappalardo, Molecular dyinal Chemistry (2014), http://dx.doi.org/10.1016/j.ejmech.2014.10.078

[6] W.L. Jorgensen, Efficient drug lead discovery and optimization, AccountsChem. Res. 42 (2009) 724e733.

[7] G. Schneider, O. Clement-Chomienne, L. Hilfiger, P. Schneider, S. Kirsch,H.J. Bohm, W. Neidhart, Virtual screening for bioactive molecules by evolu-tionary de novo design, Angew. Chem. Int. Ed. 39 (2000) 4130e4133.

[8] J. Alvarez, B. Shoichet, Virtual Screening in Drug Discovery, Taylor & Francis,Boca Raton, 2005.

[9] C. McInnes, Virtual screening strategies in drug discovery, Curr. Opin. Chem.Biol. 11 (2007) 494e502.

[10] M. Totrov, R. Abagyan, Flexible ligand docking to multiple receptor conforma-tions: a practical alternative, Curr. Opin. Struct. Biol. 18 (2008) 178e184.

[11] C.A. Sotriffer, P. Sanschagrin, H. Matter, G. Klebe, SFCscore: scoring functionsfor affinity prediction of protein-ligand complexes, Proteins 73 (2008)395e419.

[12] C. B.R., J. Subramanian, S.D. Sharma, Managing protein flexibility in dockingand its applications, Drug Discov. Today 14 (2009) 394e400.

[13] S.A. Adcock, J.A. McCammon, Molecular dynamics: survey of methods forsimulating the activity of proteins, Chem. Rev. 106 (2006) 1589e1615.

Danilo Milardi, Managing Guest Editor*

National Research Council, Institute of Biostructures and Bioimages,Via Paolo Gaifami 18, 95126 Catania, Italy

Matteo Pappalardo, Guest EditorUniversity of Catania, Dipartimento di Scienze Chimiche, Viale Andrea

Doria, 6, 95125 Catania, Italy

* Corresponding author.E-mail address: danilo.milardi@cnr.it (D. Milardi).

Available online xxx

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