A Fourier Transformation Based Method to Mine Peptide Space for Antimicrobial Activity

Background Naturally occurring antimicrobial peptides are currently being explored as potential candidate peptide drugs. Since antimicrobial peptides are part of the innate immune system of every living organism, it is possible to discover new candidate peptides using the available genomic and proteomic data. High throughput computational techniques could also be used to virtually scan the entire peptide space for discovering out new candidate antimicrobial peptides. Result We have identified a unique indexing method based on biologically distinct characteristic features of known antimicrobial peptides. Analysis of the entries in the antimicrobial peptide databases, based on our indexing method, using Fourier transformation technique revealed a distinct peak in their power spectrum. We have developed a method to mine the genomic and proteomic data, for the presence of peptides with potential antimicrobial activity, by looking for this distinct peak. We also used the Euclidean metric to rank the potential antimicrobial peptides activity. We have parallelized our method so that virtually any given protein space could be data mined, in search of antimicrobial peptides. Conclusion The results show that the Fourier transform based method with the property based coding strategy could be used to scan the peptide space for discovering new potential antimicrobial peptides

Designing algorithms to aid discovery by chemical robots

Recently, automated robotic systems have become very efficient, thanks to improved coupling between sensor systems and algorithms, of which the latter have been gaining significance thanks to the increase in computing power over the past few decades. However, intelligent automated chemistry platforms for discovery orientated tasks need to be able to cope with the unknown, which is a profoundly hard problem. In this Outlook, we describe how recent advances in the design and application of algorithms, coupled with the increased amount of chemical data available, and automation and control systems may allow more productive chemical research and the development of chemical robots able to target discovery. This is shown through examples of workflow and data processing with automation and control, and through the use of both well-used and cutting-edge algorithms illustrated using recent studies in chemistry. Finally, several algorithms are presented in relation to chemical robots and chemical intelligence for knowledge discovery

Molecular simulations of potential agents and targets of Alzheimer’s disease

The World Alzheimer Report statedin 2016 that approximately 46.8 million people were living with dementia and this figure is expected to triple by 2050. Alzheimer’s Disease was discovered to be a precursor to dementia in 1976 and since then efforts to understand Alzheimer’s have been prioritized. To date, there are very few effective forms of treatment for Alzheimer’s, many are known to offer only mild calming of the symptoms and have side effects such as diarrhea, nausea, loss of appetite and sleep disturbances. This has been due to lack of understanding on how Alzheimer’s is caused. With the two main hallmarks of the disease now being more understood it has opened the doorway into the discovery of new treatments for this disease. This study focuses on the hallmark involving the aggregation of the β-amyloid protein to form plaques surrounding the neurons of the brain. Copper, Zinc and Iron have also been found in high concentrations in and surrounding these plaques. This study focused on the screening of the South African Natural Compound database (SANCDB) to discover hits that have potential destabilizing action against the Beta-amyloid aggregate. If one of these compounds could prove to have destabilizing action on the aggregate it could open the doorway to new potential forms of treatment. Over 700 SANCDB compounds were docked, and the top hits were taken to molecular dynamics to further study the interactions of the compounds and the aggregate. However, the hits identified had strong binding to the aggregate causing it to become stable instead of the desired effect of destabilizing the structure. This information, however, does not rule out the possibility of these compounds preventing the formation of the aggregates. Further, interactions of copper with β-amyloid and copper were determined by solubilizing the aggregate and introducing copper ions in a dynamics simulation. Possible interactions between copper and the methionine residues were visualised

Structure based drug design for the discovery of promising inhibitors of human Bcl-2 and Streptococcus dysgalactiae LytR proteins

Drug research has evolved significantly in the last decades toward the concept of the rational design of drugs. The capability to study molecular interactions at the atomic level and to rationalize this knowledge to construct and improve drug candidates provided the premises of structure-based drug design (SBDD). This approach allied to the computational methods available nowadays yields the opportunity to expedite the intricate process of drug discovery. In the present thesis, the SBDD approach was implemented to study promising candidate inhibitors of the human Bcl-2 and the Streptococcus dysgalactiae LytR proteins. Half of the cancers in humans are estimated to be related with overexpression of Bcl-2 protein. This macromolecule is responsible for the inhibition of the apoptotic process, which is pivotal for the elimination of abnormal cells. When Bcl-2 is overexpressed, these abnormal cells don’t respond to death stimuli, either endogenous or exogenous, such as chemotherapeutic, and become immortal. Promising 4H-chromene and indole derivatives were studied regarding their potential to inhibit Bcl-2. Molecular docking studies revealed sub-micromolar binding of the 4Hchromene activemethine and the indole derivatives in the binding groove essential for Bcl-2 biological function. Biophysical characterization did not demonstrate significant evidence of binding between Bcl-2 and the compounds under study, probably due to their small network of interactions with the binding pocket residues. The structure determination process of the proteinligand complexes achieved preliminary co-crystallization conditions that require further optimization. Numerous infectious diseases are associated to the bacterial biofilm phenotype, which consists of agglomerates of cells enclosed in a self-produced matrix. Biofilms confer bacteria improved resistance to the host’s innate immune system and to conventional antibiotics. LytR belongs to the LCP family of proteins, which are thought to be responsible for the attachment of anionic polymers to the peptidoglycan, protecting the Gram-positive bacteria from phagocytosis and lysis. Previous virtual screening studies yielded ellagic acid and fisetin has promising inhibitors of LytR, displaying anti-biofilm activity. Molecular docking revealed binding of these compounds in the hypothetical active site of LytR, with micromolar affinities, and specific interactions with crucial protein residues for catalysis. Biophysical techniques failed to provide evidence of protein-ligand interactions, although this may be related to the possible co-purification with a lipidic substrate, which has been reported before. Mass spectrometry or structural determination, through X-ray crystallography or NMR, should be pivotal to establish evidence of this molecule’s accommodation in the binding pocket

Computational Protein-Ligand Modelling of the Enzymes DNA gyrase and IcaB

Computational modelling of proteins and their interactions with small molecule ligands is a growing field of research. Such studies provide an understanding of how protein structure relates to mechanism and function as well as informing drug discovery and design. This thesis had two main aspects: computational modelling of ciprofloxacin derivatives binding to DNA gyrase and homology modelling of the protein IcaB based on sequence alignment with a related protein, PgaB. The inhibitory activity of synthetic ciprofloxacin derivatives (with various linkage to citrate groups) was experimentally assessed by gel electrophoresis to examine the effect on DNA gyrase binding to a target DNA strand. Overall, the derivative which possessed the greatest inhibition compared to the unmodified ciprofloxacin was the c-gly-ciprofloxacin derivative, which had a 2 atom linker between the ciprofloxacin and citrate groups. This correlated with the change in interactions seen between ciprofloxacin derivatives as computationally modelled by molecular mechanics methods. The second aspect of the thesis was to generate a model of the protein IcaB to test the hypothesis that it is a deactylase of poly-N-acetyl-glucosamine (PNAG) during maturation of the poly-glycan in the extracellular matrix responsible for biofilm generation for bacteria. An initial review of deacetylase enzyme structures identified the conserved features required for activity. A homologous protein, Pga,B was then used as a template to generate a homology model of IcaB. The model maintained the orientation and positioning of the metal-binding and catalytic residues critical for proper deacetylase function. However, the PNAG binding groove, believed to be involved in the transport of the PNAG to the active site of PgaB, was not properly replicated in the IcaB model. Further modelling would require improved characterization of the binding groove of IcaB

Estudios computacionales de mecanismos moleculares de la inmunidad innata

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Farmacia, leída el 20-12-2022Antimicrobial Resistance (AMR) is a worldwide health emergency. ESKAPE pathogens include the most relevant AMR bacterial families. In particular, Gram-negative bacteria stand out due to their cell envelope complexity, which exhibits strong resistance to antimicrobials. A key element for AMR is the chemical structure of bacterial lipopolysaccharide (LPS), and the phospholipid composition of the membrane, inflecting the membrane permeability to antibiotics. We have applied coarse-grained molecular dynamics simulations to capture the role of the phospholipid composition and lipid A structure in the membrane properties and morphology of ESKAPE Gram-negative bacterial vesicles. Moreover, the reported antimicrobial peptides Cecropin B1, JB95, and PTCDA1-kf were used to unveil their implications for membrane disruption. This study opens a promising starting point for understanding the molecular keys of bacterial membranes and promoting the discovery of new antimicrobials to overcome AMR...La resistencia a los antimicrobianos (AMR) es una emergencia sanitaria mundial. Los patógenos ESKAPE incluyen las familias bacterianas más resistentes a antibióticos y son altamente virulentas. En particular, las bacterias Gram negativas destacan por la complejidad de su pared celular, que presenta una fuerte resistencia frente a los antibióticos. Un elemento clave para la AMR es la estructura química del lipopolisacárido bacteriano (LPS) y la composición de los fosfolípidos de la membrana bacteriana, que influyen en su permeabilidad a los antibióticos. Se han empleado simulaciones de dinámica molecular de grano grueso para captar el papel de la composición de los fosfolípidos y la estructura del LPS en las propiedades y morfología de modelos de vesículas bacterianas Gram negativas ESKAPE. Además, se han empleado los péptidos antimicrobianos Cecropin B1, JB95 y PTCDA1-kf para desvelar su mecanismo disrupción de la membrana bacteriana. Este estudio abre un prometedor punto de partida para comprender las claves moleculares de la resistencia en membranas bacterianas y acelerar el descubrimiento de nuevos antibióticos para hacer frente a la AMR...Fac. de FarmaciaTRUEunpu

Applications of nuclear magnetic resonance spectroscopy: from drug discovery to protein structure and dynamics.

The versatility of nuclear magnetic resonance (NMR) spectroscopy is apparent when presented with diverse applications to which it can contribute. Here, NMR is used i) as a screening/ validation tool for a drug discovery program targeting the Phosphatase of Regenerating Liver 3 (PRL3), ii) to characterize the conformational heterogeneity of p53 regulator, Murine Double Minute X (MDMX), and iii) to characterize the solution dynamics of guanosine monophosphate kinase (GMPK). Mounting evidence suggesting roles for PRL3 in oncogenesis and metastasis has catapulted it into prominence as a cancer drug target. Yet, despite significant efforts, there are no PRL3 small molecule inhibitors currently in clinical trials. This work combines screening of an FDA-approved drug panel and the identification of binders by protein-observed NMR. FDA-approved drugs salirasib and candesartan were identified as potent inhibitors in in vitro inhibition and migration assays while a weak inhibitor, olsalazine, was identified by NMR as the first small molecule inhibitor to directly bind PRL3. NMR was also used to validate the binding of additional compounds identified as experimental PRL3 inhibitors. Thienopyridone, a potent experimental inhibitor, did not show direct binding to PRL3 but instead inhibited phosphatase activity via redox mechanism. NMR also revealed that other experimental inhibitors did not engage PRL3. Thus, there remains a need to identify potent PRL3-directed inhibitors. Meanwhile, molecular modeling revealed a putative druggable site that has not been thoroughly explored before. The current study provides some scaffolds such as candesartan and particularly, olsalazine, the only binder identified, that could be the starting point of further drug discovery efforts, as well as a putative site that can be targeted in silico. MDMX, a negative regulator of p53, is another important therapeutic target in cancer, along with the homologous protein, MDM2. Inhibitors that block the MDM2-p53 interaction have been identified and despite similarities in the binding site of these homologous proteins, these inhibitors are ineffective against MDMX. It is hypothesized that the flexibility of MDMX contributes to this significant difference in response to inhibitors, despite comparable affinity to their endogenous target, p53. Examination of available inhibitor-bound structures of MDMX reveal a conserved pharmacophore but the structures adopt distinct conformations away from the binding site. This implies that global motions of the protein might contribute to molecular recognition. The conformational heterogeneity in MDMX was further confirmed by collecting residual dipolar couplings (RDCs). Further investigations on both MDMX and MDM2 are necessary to uncover whether the flexibility of MDMX contributes to the differential binding to inhibitors. Finally, NMR relaxation methods and state-of-the-art high-power Carr-Purcell-Meiboom Gill (CPMG) relaxation dispersion measurements, the first documented application on an enzyme, were used to characterize the solution dynamics of GMPK and the changes in dynamics upon GMP binding. Substrate binding resulted in restricting the amplitudes of motion for backbone amide bonds within the picosecond-nanosecond timescale. Meanwhile, CPMG showed dispersion in both in the absence and presence of GMP, such that substrate binding did not quench dynamics within the microsecond-millisecond timescale. Interestingly, more residues are observed to have dispersion in the bound form, some near the C-terminal of helix 3, which has previously been proposed to be involved in product release. Current studies show that substrate binding affect different timescales of protein motion. Future work shall follow how motions within different timescales are affected as GMPK processes its substrates – such as, for instance, binding of ATP analogs within the ATP binding site or simultaneous occupancy of both substrate binding pockets. This paves the way for a complete picture of the relationship of function and dynamics in the conformational enzymatic cycle of a bi-substrate enzyme using GMPK as a model. The current work illustrates some of the diverse applications of NMR on three unique systems that are also drug targets. Information collected here can be leveraged on future structure and dynamics studies as well as drug discovery efforts targeting any of these proteins