Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the “second secret of life.” The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets

Computational structure‐based drug design: Predicting target flexibility

The role of molecular modeling in drug design has experienced a significant revamp in the last decade. The increase in computational resources and molecular models, along with software developments, is finally introducing a competitive advantage in early phases of drug discovery. Medium and small companies with strong focus on computational chemistry are being created, some of them having introduced important leads in drug design pipelines. An important source for this success is the extraordinary development of faster and more efficient techniques for describing flexibility in three‐dimensional structural molecular modeling. At different levels, from docking techniques to atomistic molecular dynamics, conformational sampling between receptor and drug results in improved predictions, such as screening enrichment, discovery of transient cavities, etc. In this review article we perform an extensive analysis of these modeling techniques, dividing them into high and low throughput, and emphasizing in their application to drug design studies. We finalize the review with a section describing our Monte Carlo method, PELE, recently highlighted as an outstanding advance in an international blind competition and industrial benchmarks.We acknowledge the BSC-CRG-IRB Joint Research Program in Computational Biology. This work was supported by a grant from the Spanish Government CTQ2016-79138-R.J.I. acknowledges support from SVP-2014-068797, awarded by the Spanish Government.Peer ReviewedPostprint (author's final draft

Studies on Proteolysis Targeting Chimeras: platform technology for targeted protein degradation in drug discovery

Proteolysis Targeting Chimeras (PROTACs) represent an innovative approach to chemical intervention into biology, with attractive therapeutic potential. In contrast to protein inhibition, PROTACs trigger targeted protein degradation inside cells via hijacking the ubiquitinproteasome machinery. PROTACs are bifunctional compounds composed by two small molecules connected by a linker; one molecule binds to a protein of interest and the other one binds to an E3 ubiquitin ligase. The ligases most commonly recruited are the von Hippel- Lindau (VHL) protein complex CRL2VHL and the cereblon (CRBN) complex CRL4CRBN. To date, different classes of target proteins have been successfully degraded, including epigenetic targets such as bromodomain-containing proteins BRD2, BRD3, and BRD4, BRD9, TRIM24, SIRT2, PCAF/GNC5, protein kinases, nuclear receptors and E3 ubiquitin ligases to selfdegrade. The work described in this thesis is divided into two parts: the first part is about the research activity carried out at the University of Dundee, under the supervision of Professor Alessio Ciulli, while a second part involves the work done at the Department of Chemical Core Technologies, within Nerviano Medical Sciences (Milan), under the supervision of Doctor Eduard Felder. The aim of the project carried out in Ciulli Lab was to investigate PROTAC-mediated degradation of BRD7 and BRD9 proteins, subunits of the human SWI/SNF chromatin remodelling complexes. These subunits have gained interest as therapeutic target especially in hematopoietic cancers, for example supporting growth of acute myeloid leukemia (AML) cells. Despite inhibitors able to disrupt the interaction of the BRD7/9 bromodomains are known, their cellular activity has remained limited as other non-bromodomain functions of the target remain unaffected. PROTAC molecules able to induce BRD9 degradation would more profoundly impact on BRD7 and BRD9 function and therefore could be used as chemical tools to better understand its role in BAF complex and in oncogenesis. Following analysis of the available co-crystal structures of the individual target and ligase proteins with their respective ligands, a library of degraders has been designed and synthesised, involving convergent synthetic strategies to conjugate a diverse range of scaffolds and linkers. All compounds were tested in vitro against different cancer cell lines and immunoblotting was carried out to assess the target degradation profile. VZ185 was found as a highly selective, potent and rapid dual BRD7/BRD9 degrader, with slight preference for BRD9 over BRD7. Degradation was demonstrated to be dependent upon proteasomal activity, cullin neddylation and VHL binding. The second section of the thesis reports the design, synthesis and biological characterization of PROTACs targeting protein kinases, carried out at NMS for one-year stage. With the future prospect of extending the development of PROTAC to other targets, it was planned to study a literature example, in order to confirm the proof of concept. Amongst those available, we chose DAS-6-2-2-6-CRBN, based on a potent tyrosine kinase inhibitor and a CRBN ligand that induce degradation of c-ABL and BCR-ABL. Furthermore, we decided to extend the development of degraders focusing on how target ligand and linker composition affect efficacy and selectivity. The biological evaluation of the synthetized compounds was performed by the Department of Biology of NMS throughout in vitro treatments of cancer cell lines and immunoblotting

Biophysics in drug discovery : impact, challenges and opportunities

Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound-target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems

In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs

Rational drug design implies usage of molecular modeling techniques such as pharmacophore modeling, molecular dynamics, virtual screening, and molecular docking to explain the activity of biomolecules, define molecular determinants for interaction with the drug target, and design more efficient drug candidates. Kinases play an essential role in cell function and therefore are extensively studied targets in drug design and discovery. Kinase inhibitors are clinically very important and widely used antineoplastic drugs. In this review, computational methods used in rational drug design of kinase inhibitors are discussed and compared, considering some representative case studies

Janus Kinases in Leukemia

Simple Summary Janus kinase/signal transducers and activators of transcription (JAK/STAT) pathway is a crucial cell signaling pathway that drives the development, differentiation, and function of immune cells and has an important role in blood cell formation. Mutations targeting this pathway can lead to overproduction of these cell types, giving rise to various hematological diseases. This review summarizes pathogenic JAK/STAT activation mechanisms and links known mutations and translocations to different leukemia. In addition, the review discusses the current therapeutic approaches used to inhibit constitutive, cytokine-independent activation of the pathway and the prospects of developing more specific potent JAK inhibitors. Janus kinases (JAKs) transduce signals from dozens of extracellular cytokines and function as critical regulators of cell growth, differentiation, gene expression, and immune responses. Deregulation of JAK/STAT signaling is a central component in several human diseases including various types of leukemia and other malignancies and autoimmune diseases. Different types of leukemia harbor genomic aberrations in all four JAKs (JAK1, JAK2, JAK3, and TYK2), most of which are activating somatic mutations and less frequently translocations resulting in constitutively active JAK fusion proteins. JAKs have become important therapeutic targets and currently, six JAK inhibitors have been approved by the FDA for the treatment of both autoimmune diseases and hematological malignancies. However, the efficacy of the current drugs is not optimal and the full potential of JAK modulators in leukemia is yet to be harnessed. This review discusses the deregulation of JAK-STAT signaling that underlie the pathogenesis of leukemia, i.e., mutations and other mechanisms causing hyperactive cytokine signaling, as well as JAK inhibitors used in clinic and under clinical development.Peer reviewe

4,6-Diphenyl-pyridines/pyrimidines and pyrazolo[3,4-d]pyrimidines: promising scaffolds as antiviral, anticancer and theranostic agents.

Nitrogen-based heterocyclic molecules received increasing attention in biological and chemical sciences, becoming a significant moiety in drug design. In this thesis, the research work has been focused on the design and the synthesis of novel derivatives based on the 4,6-diphenyl-pyridine/pyrimidine and pyrazolo[3,4-d]pyrimidine scaffolds as key pharmacophores for their antiviral and anticancer activities, respectively. The first part deals with the design and synthesis of a set of small molecules able to interfere with the Influenza (flu) RNA-dependent RNA Polymerase (RdRp) functions, exploiting the protein-protein interactions (PPIs) approach. An introduction of influenza disease and its pathogens is provided, focusing on the replicative mechanism of the influenza viruses and on the structural and functional information of the flu RdRp. The PPIs of the three polymerase subunits PA, PB1 and PB2, are reported and the inhibitors targeting the heterodimer PA-PB1 are introduced. Finally, the rational design and synthesis of new hybrid compounds bearing the 4,6-diphenyl-pyridine/pyrimidine cores are described togheter with the biological evaluation and molecular modeling studies. The second part of the dissertation focuses on the pyrazolo[3,4-d]pyrimidine compounds, on which both a lead optimization study and a theranostic design have been performed. The pyrazolo[3,4-d]pyrimidines have shown a promising activity both in in vitro and in in vivo as protein kinase inhibitors. The lead optimization study has been performed with the aim of obtaining a new class of derivatives as potent Src kinase inhibitors. The rational design, synthesis and biological analysis of the novel compounds are discussed. A further part of the project is dedicated to the design and development of potential theranostic prodrugs of two promising in-house pyrazolo[3,4-d]pyrimidines, SI306 and SI113. These prodrugs have been synthesized as potential agents for the diagnosis and the treatment of glioblastoma multiforme (GBM). The state of the art on theranostic applications of drugs, whose use is continually increasing, is also described