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  • 34 Reads
Development of new computational workflow for the identification of hAQP5 modulators

Aquaporins (AQPs) are membrane channels which facilitate the flow of water and other small molecules, such as glycerol, across biological membranes. They play a crucial role in cell homeostasis and volume regulation, being widely distributed in all organisms. In mammals, there are three subsets of AQPs, divided according to their permeability profiles and sequence homology. Due to its biological importance, deregulation of AQPs activity and/or expression can induce changes in the cell homeostasis, causing health problems and diseases, such as carcinogenesis (1-3). The relationship between AQPs and cancer has been thoroughly studied and, as a result, it was concluded that AQPs are overexpressed in a wide variety of tumors, especially AQP1, AQP3 and AQP5 isoforms. Moreover, the discovery of efficient and selective modulators of human AQPs (hAQPs) has been considered as a potential strategy for cancer treatment/therapy. However, the inhibitors reported thus far exhibit high toxicity and poor selectivity, making them inappropriate to proceed for drug development. (4). Therefore, the main goal of this work, was to develop and apply a new computational workflow to identify hAQP5 modulators from a Sigma-Aldrich database of compounds. This approach combined the use of Molecular Dynamics, Molecular Docking, and MM-PBSA methodologies, allowed for the identification of compounds with high affinity for hAQP5 (5). The five most promising hits were experimentally tested for their inhibitory effect on hAQP5 in an optimized yeast cell model expressing this isoform, by permeability assays using the fluorescence stopped-flow technology. Here, we present and discuss our results, highlighting the limitations of our approach and propose the future methodological perspective that will be pursued to find better and specific hAQP5 inhibitors.

(1) Direito, I., Madeira, A., Brito, M. A., & Soveral, G. (2016). Cellular and Molecular Life Sciences, 73(8), 1623–1640.
(2) Huber, V. J., Tsujita, M., & Nakada, T. (2012). Molecular Aspects of Medicine, 33(5–6), 691–703.
(3) S. Verkman, A., O. Anderson, M., & C. Papadopoulos, M. (2014). Nature Reviews Drug Discovery, 13(4), 259–277.
(4) Abir-Awan, M., Kitchen, P., Salman, M. M., Conner, M. T., Conner, A. C., & Bill, R. M. (2019). International Journal of
Molecular Sciences, 20(7).
(5) Horsefield, R., Nordén, K., Fellert, M., Backmark, A., Törnroth-Horsefield, S., Terwisscha Van Scheltinga, A. C., Kvassman, J.,Kjellbom, P., Johanson, U., & Neutze, R. (2008). Proceedings of the National Academy of Sciences of the United States of America, 105(36), 13327–13332

  • Open access
  • 28 Reads
In silico study of peptidic dendrimers as transfection agents in DNA/RNA vaccines

Peptide dendrimers are compounds related to dendrimers by virtue of their branched and polymeric structure, and to peptides and proteins because only amino acids are present in the dendrimer branches. In the past years peptide dendrimers with two or three amino acids in the branches have been reported to interact with biological molecules and cell membranes leading to good activity as antimicrobial agents, pathogenic biofilm inhibitors and superior vectors for DNA, siRNA and small oligonucleotides [1].

Recently, the use of such structures as vector molecules for mRNA and siRNA vaccines has been explored [2] , which resulted in some promising peptidic dendrimers, namely MH13 and MH18, which are solely constituted by lysines and leucines, and contain two palmitoyl chains or a leucine tetrapeptide as hydrophobic cores, respectively. Furthermore, some mutations in MH18 from L- to D-amino acids, results in improved transfection and delivery efficiencies, as well as improved resistance to proteolytic degradation [2]. Despite these promising results in penetrating the target cells, being resistant to degradation, protecting and delivering their cargo (DNA and RNA), and not triggering a significant cytotoxic or immunogenic reaction, it is remarkable how little we know about the molecular mechanisms of their actions [3].

In this work, we will present our preliminary findings regarding the pH-dependent conformational space of MH18 and its variants composed of a different number (and position) of D-amino acids. We will present a specific protocol to build our dendrimers without bias, coupled to a robust initialization/equilibration scheme that prepares the peptidic dendrimers to be used in our state-of-the-art CpHMD simulations. We will present the pH titration behavior and perform several conformational characterizations, including the radius of gyration and the root mean square deviation (RMSD). These results are pivotal to help us choose the next steps of the project, where the interactions with lipid membranes and DNA/RNA are planned, to help experimentalists interpret their data, and to design new and improved peptidic dendrimers.

  1. Reymond J-L, Bergmann M, Darbe T. ChemInform Abstract: Glycopeptide Dendrimers as Pseudomonas aeruginosa Biofilm Inhibitors. ChemInform. 2013. p. no–no. doi:10.1002/chin.201335206
  2. Heitz M, Javor S, Darbre T, Reymond J-L. Stereoselective pH Responsive Peptide Dendrimers for siRNA Transfection. Bioconjug Chem. 2019;30: 2165–2182.
  3. Filipe LCS, Campos SRR, Machuqueiro M, Darbre T, Baptista AM. Structuring Peptide Dendrimers through pH Modulation and Substrate Binding. J Phys Chem B. 2016;120: 10138–10152.
  • Open access
  • 12 Reads
Identification of membrane PAINS via an optimized computational protocol

Membrane Pan-Assay INterference compoundS (PAINS) are a subcategory of molecules that interact with
lipid membranes in a nonspecific way and alter their physicochemical properties [1]. A prompt detection
of these compounds in the drug discovery process is therefore crucial, as it avoids wasting precious time
and resources chasing after false leads. Here we present an optimized umbrella sampling/molecular
dynamics-based computational protocol to identify compounds with varying degrees of membrane PAINS
behavior. We observed that the method was extremely susceptible to fluctuations in membrane
thickness, which we were able to alleviate by changing the US-reference position from the membrane
center to the closest interacting monolayer. The computational performance was further improved by
adjusting the number, strength, and position of the umbrellas. The membrane permeability coefficients
calculated using the inhomogeneous solubility diffusion model were able to accurately assess the
membrane PAINS character of both curcumin and resveratrol [2] but indicated a possible misclassification
of notophagin in a previous work [3].
Acknowledgements: FCT to projects PTDC/BIA-BFS/28419/2017 (B. L. Victor) UIDB/04046/2020−UIDP/04046/2020
[1] Baell, J.B. et al. (2010) JMC 53(7):2719
[2] Ingólfsson, H.I. et al. (2014) ACSCB 9(8):1788
[3] Jesus, A.R. et al. (2017) JMC 60(2), 568-579

  • Open access
  • 3 Reads
Design of Indoloisoquinoline derivatives as potential inhibitors of the interaction between c-MYC:G4 and helicase

Guanine-rich DNA or RNA sequences may form a noncanonical higher-order structure called G-quadruplexes (G4). The structural features of G4 have been described to promote genomic instability in DNA replication, modulate transcription and translation, and have been found with high prevalence in promoter regions of many cancer-related genes such as c-MYC (1). G4s are transient structures that can be unfolded by helicases, a protein family that binds and remodel nucleic acid structures and nucleic acid-protein complexes. Some helicases, such as DHX36, prefer binding and unwinding G4 nucleic acid structures (2). In previous reports, G4 structure stabilization by small organic molecules has shown promising results as an anticancer drug target (1,3). However, many difficulties related to lipophilicity and specificity towards different G4s have been found. To overcome these obstacles, in this project, we propose to design, synthesize and evaluate indoloisoquinoline (IDQ) derivatives as potential inhibitors of the c-MYC:G4-DHX36 interaction, taking advantage of the recently resolved crystallographic structure of DHX36 helicase in complex with this G4 (2). The IDQ core was combined with a library of purchasable fragments to create a final library of compound derivatives, which was then used in a molecular docking screening campaign targeting the c-MYC:G4 structure in complex with DHX36 (5). Different scoring functions from different molecular docking softwares (4-6) were used to derive a final consensus scoring (7), and consequently identify a subset of IDQ fragment substituents shown to be prevalent in the lowest binding affinity docking solutions with c-MYC:G4. These results will now guide the synthesis of the most promising ligands, which selectivity and stabilization will afterwards be validated with several in vitro assays. The obtained results will guide additional structure-activity in silico calculations, to allow the optimization of the most promising inhibitors.


1. FCT to projects PTDC/BIA-BFS/28419/2017 (B. L. Victor)
2. UIDB/04046/2020−UIDP/04046/2020 (BioISI) and UIDP/04138/2020 (iMed).

1. Paulo A. et. al. (2017) Third Edition. Vols. 5–8, Comprehensive Medicinal Chemistry III. Elsevier; 308–340 p. 2. Chen, M. C., et al. (2018). Nature, 558(7710), 465–483. 3. Cadoni E, et al. (2021). Pharmaceuticals. 14(7) 669. 4. Trott, O., Olson, A. J. (2009). Journal of Computational Chemistry, NA-NA. 5. Eberhardt, J., Santos-Martins, D., Tillack, A. F., & Forli, S. (2021). Journal of Chemical Information and Modeling, 61(8), 3891–3898. 6. Koebel MR, et al.. (2016) J Cheminform. May 18;8:27. 7. Ochoa, R. et al., (2021) Journal of Molecular Graphics and Modelling, Volume 109, 108023.

  • Open access
  • 34 Reads
Computational Screening and Design of G-quadruplex Ligands Targeting c-MYC in Breast Cancer

G-quadruplexes (G4) are four-stranded nucleic acid secondary structures formed by guanine-rich sequences of DNA or RNA. It has been shown that G4s are involved in relevant biological functions of normal mammalian cells, but more importantly, in cancer cells. Several studies reported that G4 is prevalent in telomeres and promotor regions of several oncogenes like c-MYC, which has a key role in several cellular regulatory processes, cancer development, and progression[1].
G4 formed in the promoter region of c-MYC may constitute an anticancer drug target by inhibiting the DNA transcription via the block of DNA polymerase and binding of transcription factors. Interestingly, G4 in the c-MYC promoter is reported to be unwounded by the helicase DHX36, a protein of the eukaryotic DEAH/RHA family that recognizes specifically G4s and promotes the regulation of DNA transcription[1,2]. Therefore, we will take advantage of the identified biological relevance of G4, together with the recent published crystallographic structure of DHX36 helicase with the c-MYC G4, to develop an in silico approach to identify inhibitors of this DNAG4-helicase interaction, with the objective to promote an anti-proliferative activity and downregulation of this oncogene expression[2,3]. In this communication, we report a molecular docking workflow that considers different scoring functions coupled to a consensus analysis approach to identify the most promising indoloisoquinoline (IDQ) derivatives capable to bind to c-MYC G4. From an initial library of 1104 ligands, we were able to identify a small group of fragment substituents with a high prevalence in the compounds with higher binding affinities to the c-MYC G4. These results will guide the chemical synthesis of a small subset of IDQ derivatives, and consequent in vitro validation. The obtained results will then afterward be used in subsequent in silico structure/activity studies to assure the optimization of the most promising c-MYC G4-helicase interaction inhibitors.

  • Open access
  • 2 Reads
A novel US-CpHMD protocol to study the protonation-dependent mechanism of the ATP/ADP carrier.

Electrostatic interactions are key participants in biomolecular processes, being the main driving force of molecular interactions [1]. However, describing these forces accurately is quite challenging using both experimental and computational methods. We propose a new computational protocol combining Umbrella Sampling with Constant-pH Molecular Dynamics [2] to overcome the time-scale limitations of conventional MD simulations and to allow protonation changes of all molecules in our simulations. Such protocol was employed to study the transport of two highly negatively charged molecules (ATP and ADP) through the ATP/ADP carrier (AAC), where electrostatic interactions have previously been shown to be very important [3]. Until now, these complete transport processes have not been studied thoroughly and with the correct description of pH. Therefore, our US-CpHMD simulations can bring an unprecedented realism to these complex processes by capturing both conformational and protonation changes occurring during transport.

In our work, the potential of mean force (PMF) profiles of our US-CpHMD simulations at pH 7 show a clear selectivity in the import of ADP, compared to ATP, while in the export, no selectivity was observed. We also observed that, in the import process, AAC was able to sequester both substrates at longer distances and transiently protonate them while crossing the cavity. These features were not observed in the export process and may be an important advantage to counteract the unfavorable mitochondrial membrane potential. Finally, we observed a substrate-induced disruption of the matrix salt-bridge network, which can promote the conformational transition (from the C- to the M-state) required to complete the import process. This work unraveled several important structural features where the complex electrostatic interactions were pivotal to interpret the protein function and illustrated the potentiality of applying the US-CpHMD protocol to other transport processes involving membrane proteins.

  1. Zhang Z, Witham S, Alexov E. On the role of electrostatics in protein–protein interactions. Phys Biol. 2011;8: 035001.
  2. Santos HAF, Vila-Viçosa D, Teixeira VH, Baptista AM, Machuqueiro M. Constant-pH MD Simulations of DMPA/DMPC Lipid Bilayers. J Chem Theory Comput. 2015;11: 5973–5979.
  3. Bidon-Chanal A, Krammer E-M, Blot D, Pebay-Peyroula E, Chipot C, Ravaud S, et al. How Do Membrane Transporters Sense pH? The Case of the Mitochondrial ADP–ATP Carrier. J Phys Chem Lett. 2013;4: 3787–3791.
  • Open access
  • 33 Reads
An US-CpHMD protocol to calculate pH-dependent membrane permeability coefficients of antitumor drugs

Many antitumor drugs cross the lipid membrane by passive diffusion to enter tumor cells. In the case of Lewis Base drugs, which are charged in water (pKa values are generally between 8 and 9), a transient deprotonation is required to cross the lipid bilayer [1,2]. Since the Tumor MicroEnvironment (TME) is slightly more acidic than normal cells, it has been proposed that this increased acidity can significantly decrease the antitumor efficiency of these Lewis Bases by impairing the transient deprotonation process [1].

To quantify the impact of the TME in the membrane permeability of some chemotherapeutics, we propose a new protocol based on Constant-pH Molecular Dynamics [2] coupled with an Umbrella Sampling scheme (US-CpHMD) and applied it to two well-known drugs, sunitinib and nintedanib, interacting with a POPC lipid bilayer. The membrane permeability coefficients were calculated using the inhomogeneous-solubility diffusion model (ISDM) [3]. The calculations were performed at different pH values, namely 7.5 to mimic a healthy cell, 6.0 to model the TME acidity, and 4.5 to capture the strong acidity of the lysosomes lumen. The latter can provide some insights on the lysosomal sequestration phenomenon, which has been proposed as a drug resistance mechanism [1]. We have calculated the impact of acidity in the bioavailability of both sunitinib and nintedanib, which helped us design a new compound as a proof of concept that is able to circumvent these limitations.

  1. Assaraf YG, Brozovic A, Gonçalves AC, Jurkovicova D, Linē A, Machuqueiro M, et al. The multi-factorial nature of clinical multidrug resistance in cancer. Drug Resist Updat. 2019;46: 100645.
  2. Stark M, Silva TFD, Levin G, Machuqueiro M, Assaraf YG. The Lysosomotropic Activity of Hydrophobic Weak Base Drugs is Mediated via Their Intercalation into the Lysosomal Membrane. Cells. 2020;9. doi:10.3390/cells9051082
  3. de Faria CF, Moreira T, Lopes P, Costa H, Krewall JR, Barton CM, et al. Designing new antitubercular isoniazid derivatives with improved reactivity and membrane trafficking abilities. Biomed Pharmacother. 2021;144: 112362.
  • Open access
  • 61 Reads
Partial purification and characterization by fluorimetry and spectrophotometry of buffalo lactoferrin

Introduction: Lactoferrin (Lf) is a iron ligating glycoprotein with a molecular mass of approximately 80 kDa, present in mammalian whey, belonging to the transferrin family. Lf can be found in various mucous secretions, such as tears, saliva, gastrointestinal fluids, urine and seminal fluid, as well as in secondary neutrophil granules, being released in places where there is an inflammatory response. Lf is a multifunctional protein possessing functions such as antibacterial, antiviral, antifungal, anti-inflammatory and immunomodulatory activities. This study aimed to purify, characterizing buffalo milk lactoferrin by monitoring the purification by spectroscopic techniques as well as investigating the interaction of protein with antibiotic amoxicillin. Materials and Methods: The processing of the buffalo milk began with the separation of fat by centrifugation. The skimmed milk was acidified with HCl 0.1 M up to pH 4.6, obtaining acidified whey and the sour serum was neutralized with NaOH 0.1 M until pH 6.8 and then centrifuged. The supernatant was submitted to saline precipitation profiles of 0-20%, 20-40%, 40-60% and 60-80% saturation of (NH4)2SO4. Fluorimetric analyses of salt fractions were performed under excitation length conditions at 290 nm and emission wavelengths between 300-550 nm. Spectrophotometric studies were carried out with additions of 100 μL of saline fraction 40-60% (0.421 mg/mL), 100 μL of purified lactoferrin (0.421 mg/mL) and 100 μL amoxicillin (2.5x10-6 mol. L-1). Uv-vis absorption spectra were recorded from 190 to 450 nm. Results and Discussion: The saline profile of the precipitate was resuspended 40-60% showed the spectrum of fluorescence extinction characteristic of lactoferrin (peak at 332 nm). The 40-60% precipitate was resuspended and submitted to liquid chromatography in a Sephacryl S-100 gel column. Fractions 12 to 16 showed the fluorescence extinction spectrum characteristic of lactoferrin. SDS-PAGE 8%, using commercial lactoferrin (SIGMA) as standard, showed the presence of two protein bands in the standard range. The UV-vis spectrum of maximum absorption showed that the interaction between lactoferrin and amoxicillin play an important role, with the decrease and displacement to the red peak on the UV-vis absorption spectrum when compared with that of lactoferrin partially purified with lactoferrin in the presence of the amoxicillin. Conclusions: Buffalo lactoferrin was partially purify by liquid chromatography in a Sephacryl s-100 resin and SDS-PAGE 8%, using commercial lactoferrin (SIGMA) as standard, showed two protein bands in the standard range. Partially purified buffalo lactoferrin exhibited a UV-vis absorption spectrum with two peaks; the first strong peak centered at absorption maximum in the region 220 to 230 nm is characteristic of the peptide structure and the second peak absorption maximum in the region from 270 to 280 nm due to conjugate double bonds in tyrosine and tryptophan residues. On assays of partial purified Lf incubated with amoxicillin was observed observe a redshift shift from 222.50 nm to 225 nm followed by the hypochromic effect on the UV-vis spectrum of maximum absorption of lactoferrin. The UV-visible absorption spectra studies showed that amoxicillin when coupled with lactoferrin induced alterations in the protein structure.

  • Open access
  • 25 Reads
Extension of the stochastic CpHMD method to the CHARMM36m force field
, , , ,

Constant-pH Molecular Dynamics (CpHMD) methods are nowadays essential to describe pH and the pH effects on the conformational space of biological systems [1]. The stochastic CpHMD method [2] has shown excellent performance over the years [1–3]. Until recently, our implementation of this method only supported the GROMOS 54A7, a force field compatible with the Generalized Reaction-Field (GRF) formalism to treat long-range electrostatic interactions, hence allowing for non-neutral systems [3]. Despite GROMOS popularity, one of the most used force fields is CHARMM36m, which is all-atom and particularly suited for protein, nucleic acids, and lipids simulations [4]. However, it uses mainly PME to treat the long-range electrostatics, which requires a system charge neutralization, a major limitation in its CpHMD implementation [3].

In this work, we present an extension to the stochastic CpHMD to include the CHARMM36m force field. In this preliminary benchmark study, we simulated two well-known proteins - lysozyme and thioredoxin - for which there is a significant amount of experimental data available [5]. These systems were thoroughly studied (pH range 1-12) and the final pKa values were compared between force fields and with the experimental data [5]. Please visit our Poster to see the performance of both force fields, the details on how to circumvent the PME neutralization step, and the code efficiency (ns/day).

1. Vila-Viçosa D, Reis PBPS, Baptista AM, Oostenbrink C, Machuqueiro M. A pH Replica Exchange Scheme in the Stochastic Titration Constant-pH MD Method. J Chem Theory Comput. 2019;15: 3108–3116. doi:10.1021/acs.jctc.9b00030

2. Baptista AM, Teixeira VH, Soares CM. Constant-pH molecular dynamics using stochastic titration. J Chem Phys. 2002;117: 4184–4200. doi:10.1063/1.1497164

3. Silva TFD, Vila-Viçosa D, Reis PBPS, Victor BL, Diem M, Oostenbrink C, et al. The Impact of Using Single Atomistic Long-Range Cutoff Schemes with the GROMOS 54A7 Force Field. J Chem Theory Comput. 2018;14: 5823–5833. doi:10.1021/acs.jctc.8b00758

4. Huang J, Rauscher S, Nawrocki G, Ran T, Feig M, de Groot BL, et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat Methods. 2017;14: 71–73. doi:10.1038/nmeth.4067

5. Pahari S, Sun L, Alexov E. PKAD: a database of experimentally measured pKa values of ionizable groups in proteins. Database. 2019;2019.

  • Open access
  • 68 Reads
The Catalytic Mechanism of the SARS-Cov-2 Main Protease

SARS-CoV-2 Main Protease (Mpro), also known as 3C-like protease, is a key enzyme involved in the replication process of the virus that is causing the COVID-19 pandemic. It is also the most promising antiviral drug target targeting the SARS-CoV-2 virus. In this work [1], the catalytic mechanism of Mpro was studied using the full model of the enzyme and a computational QM/MM methodology [2] with 69/72-atoms included in the QM region treated at DLPNO-CCSD(T)[3][4]/CBS//B3LYP/6-31G(d,p):AMBER level, containing the catalytic important oxyanion-hole residues. The transition state of each step was fully characterized and described together with the related reactants and products. The rate-limiting step of the catalytic process is the hydrolysis of the thioester-enzyme adduct, and the calculated barrier closely agrees with the available kinetic data. Our simulations have disclosed important aspects of the mechanism, namely: (1) the role of the interaction between the P2 residue of the substrate and the catalytic His; (2) the important role of P1’ residue of the substrate in the stabilization of the ion pair intermediate; (3) the critical role of Gly143, Ser144, and Cys145 in the stabilization of the substrate’s oxo group.

The obtained Gibbs free energy profile, together with the full atomistic detail of the structures involved in catalysis, can be helpful for the rational drug design of transition state analogs as new inhibitors targeting the SARS-CoV-2 virus.


[1] H. S. Fernandes, S. F. Sousa, N. M. F. S. A. Cerqueira, Mol. Divers. 2021, DOI 10.1007/s11030-021-10259-7.
[2] H. S. Fernandes, M. J. Ramos, N. M. F. S. A. Cerqueira, J. Comput. Chem. 2018, 39, 1344–1353.
[3] Y. Guo, C. Riplinger, U. Becker, D. G. Liakos, Y. Minenkov, L. Cavallo, F. Neese, J. Chem. Phys. 2018, 148, 011101.
[4] F. Neese, F. Wennmohs, U. Becker, C. Riplinger, J. Chem. Phys. 2020, 152, 224108.


This work was supported by the Applied Molecular Biosciences Unit—UCIBIO (UIDP/04378/2020 and UIDB/04378/2020).