Molecular Modelling Dissertation Titles
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Molecular Modelling Dissertation Titles

Info: 1557 words(1 pages) Molecular Modelling Dissertation Titles Published: 11th December 2025 in Molecular Modelling Dissertation Titles

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Introduction

Molecular modelling is a pivotal technique in today’s chemistry and drug discovery as it allows the prior prediction of molecular behaviour, structural properties and biological activity in an experimental manner. The combination of improvements in computational chemistry, quantum mechanics, AI-based prediction tools, and molecular simulations has accelerated the process of developing new drug candidates, functional materials, and metal complexes. Still, the challenges have not been completely overcome; there is a lack of experimental validation for numerous computationally designed molecules, a huge problem in obtaining single-crystal data for full structural confirmation and the unavailability of standard frameworks that securely link computational predictions with empirical evidence, which are among the problems faced. The titles of the dissertations below address these major issues in molecular modelling, focusing on structural validation without crystallography, computational drug design, and the integration of computational and experimental workflows.

Molecular Modelling Dissertation Titles

1: Temporal and Biological Determinants of Transcriptomic Points of Departure: A Multi-Scale Framework for Toxicogenomics

Transcriptomic Points of Departure (tPODs) are to be one of the most innovative tools in Toxicogenomics and toxicological risk assessment, and hence, their reliability still needs a comprehensive understanding of biological bases. In a review by O’Brien et al. (2025) published in Toxicological Sciences argue that the most serious issues in this respect are, firstly, the time point of sampling, secondly, the temporal stability of transcriptomic responses, thirdly, tissue representativeness and finally, the choice of cell type. According to the authors, these problems affect the reproducibility and interpretation of tPOD-based assessments because there is no agreement on the best timing of exposure, the changes in tPOD values over time, or the tissues and cell types that most certainly convey the toxicological mechanisms. They suggest that a more robust scientific argument is needed for the determination of sentinel tissue validity and the minimum biological systems required for meaningful tPOD derivation; otherwise, the adoption of tPODs in regulatory frameworks will be confined due to worries about consistency, mechanistic accuracy, and inter-study comparability.

Problem Statement:
Still today, there is no single, standards-based view on how the biological context, which refers to the time, tissue, and cellular diversity, influences the transcriptomic biomarkers. Consequently, the current tPOD studies have a risk of producing unstable or misleading estimates, which limits their utility in the regulatory domain.

Research Gap:
In the literature, there does not exist a comprehensive model that has undergone empirical validation and is capable of integrating biological timing, temporal tPOD stability, and tissue/cell selection criteria. Currently, no framework determines the best sampling windows or explains when a particular tissue or cell type can be relied upon to represent systemic toxicity.

Research question:
What is the impact of sampling time, tissue specificity, and temporal stability on the accuracy, reproducibility, and mechanistic interpretation of transcriptomic Points of Departure?

Outcome:
This thesis is expected to deliver a cross-scale biological model along with certified procedures for the selection of time-points, the prioritisation of tissues, and the assessment of temporal consistency, thus allowing the derivation of tPODs for regulatory decisions that are more robust and biologically grounded.

Reference:

O’Brien, J., Mitchell, C., Auerbach, S., Doonan, L., Ewald, J., Everett, L., … Costa, E. (2025). Bioinformatic workflows for deriving transcriptomic points of departure: current status, data gaps, and research priorities. Toxicological Sciences, 203(2), 147–159.

2. Advancing Reporting Standards for Transcriptomic Toxicology: A Unified Regulatory Framework in tPOD Studies

The transcriptomic Points of Departure (tPODs) are becoming recognised as powerful means in the ecosystem of transcriptomic toxicology and risk assessment, but still, the associated biological aspects do not influence the reliability of these measures, so much so that they are still poorly understood. A review of O’Brien et al. (2025), in a publication issued at the same time in Toxicological Sciences, points to significant shortcomings in the areas of sampling time, temporal stability, tissue representativeness, and cell-type selection. Thus, these sources of uncertainty impact the regulatory decisions based on tPODs as to their reproducibility and interpretation. The review authors call for detailed research studies to determine, among other things, the best time for exposure, the validity of the sentinel tissue, and the minimum number of tissues or cell types that give rise to biologically meaningful and consistent tPOD outcomes; moreover, such studies should take the chemical, species, and assay system differences into account.

Problem Statement:
Regulatory toxicology is still in a position where it has to rely on very vague biological criteria when it comes to the selection of the sampling windows, tissues, and temporal evaluation strategies needed for the derivation of transcriptomic Points of Departure (tPODs). This lack of biologically grounded criteria further reduces confidence in tPOD results being consistent, reproducible, and interpretable; thus, regulators often find themselves in doubt whether the transcriptomic responses seen are really toxic effects of significance.

Research gap:

There are no validated guidelines so far in the literature for the optimal sampling times, minimum tissue or cell-type requirements, or the degree of temporal stability expected from tPOD reporting guidelines. Additionally, there is very little evidence on whether some tissues can be trusted to reliably act as proxies (sentinel tissues) or the extent to which temporal dynamics influence biological interpretation. All these missing elements make it very hard to grow a standardised, biologically robust tPOD methodology that would meet the needs of regulatory applications.

Research Question:
What is the impact of the timing of exposure, the selection of tissue/cell types and their temporal dynamics on the reproducibility and biological validity of transcriptomic Points of Departure in toxicological assessments?

Outcome:
The present work will provide the scientific community with an evidence-based biological framework that specifies the best sampling times, points to the most reliable sentinel tissues, and clearly states the temporal restrictions for deriving stable and biologically interpretable tPODs. The results will enhance methodological uniformity and help to gain acceptance for the tPOD-based decision-making in the regulatory processes.

Reference:

O’Brien, J., Mitchell, C., Auerbach, S., Doonan, L., Ewald, J., Everett, L., … Costa, E. (2025). Bioinformatic workflows for deriving transcriptomic points of departure: current status, data gaps, and research priorities. Toxicological Sciences, 203(2), 147–159.

3. Bridging the Structural Determination Gap: Integrating Advanced Crystal-Growth Engineering and Hybrid Computational Methods for Metal (II) Schiff Base Complexes

Transition-metal Schiff base metal complexes are still highly researched and used in catalysis, materials design, and bioinorganic chemistry. Unfortunately, one big problem that often occurs in this field is the failure to produce appropriate single crystals for X-ray diffraction (SC-XRD). One of the main problems that have to do with crystals was discussed in the journal Applied Organometallic Chemistry, where Sogukomerogullari et al. (2025) mentioned that none of the synthesised Ni(II), Cu(II), Zn(II), and Pd(II) Schiff base complexes turned out to be single crystals despite the many attempts to crystallize them. The research presented a combination of NMR, FT-IR, UV–Vis, elemental analysis, molar conductivity, magnetic susceptibility, and DFT calculations to suggest a distorted square planar geometry, but the absence of crystallographic data didn’t allow for complete structural confirmation. This case is an indicator of the need for advanced crystallisation techniques and computational-experimental integration in order to overcome such characterisation bottlenecks.

Problem Statement:
Regardless of the availability of thorough spectroscopic and computational data, the non-availability of single-crystal X-ray structures continues to create ambiguities regarding coordination geometry, bond parameters, and crystal packing. This situation hampers the reproducibility of experiments, limits the analysis of structure–activity relationships, and lowers the confidence in the accurate structural assignments of metal(II) Schiff base complexes.

Research Gap:

There are many studies—including one from 2025 published in Applied Organometallic Chemistry—that provide extensive characterisation, but they still do not have crystallographic confirmation because of the failure of crystal growth. The current literature presents isolated crystallisation techniques but does not provide a systematic, experimentally verified, and computationally assisted framework for resolving structural uncertainties when SC-XRD is not possible.

Research Question:
What combination of advanced crystal growth engineering and hybrid computational methods can effectively offset the nonavailability of single-crystal X-ray diffraction in the structural understanding of metal (II) Schiff base complexes?

Outcome:
The outcome of this PhD research will be the development of a unified framework that includes: Optimised crystallisation methods (microseeding, slow vapour diffusion, temperature gradient, mechanochemical crystallisation), computational crystallography (crystal structure prediction, packing energy profiling), DFT-guided refinement of geometry and coordination modes, cross-validation using spectroscopic fingerprints and thermodynamic descriptors.

Reference:

Sogukomerogullari, H. G., Dede, B., Sahin, D., & Akkoç, S. (2025). Comprehensive Study on Synthesis, Quantum Chemical Calculations, Molecular Modelling Studies, and Cytotoxic Activities of Metal (II) Schiff Base Complexes. Applied Organometallic Chemistry, 39(3), e70034.

4. Developing a Multi-Technique, Computationally Driven Structural Validation Framework for Metal (II) Schiff Base Complexes Lacking Single-Crystal Data

Single-crystal X-ray diffraction (SC-XRD) is the method of choice which performing the definitive molecular and crystal structure determination. But the case of several Schiff base metal complexes remains that they cannot be crystallised and hence require indirect characterisation methods. Such a case was recently demonstrated in a paper published in Applied Organometallic Chemistry from Sogukomerogullari et al. (2025), where they worked on the Ni (II), Cu (II), Zn (II), and Pd (II) complexes. A complete spectroscopic characterisation together with DFT-based modelling was conducted, but the absence of SC-XRD scuppered the accurate measurement of bond lengths, coordination geometries and molecular packing. This problem illustrates the urgent need for a reliable non-crystallographic system of structural validation in coordination chemistry, which is a common issue in the field. Such instances underscore the pressing requirement, rather than simply the use of crystallographic evidence, a frequent problem in coordination chemistry, to rely on alternative validation methods that take computational insights, advanced structure prediction methods, and spectroscopic data into account.

Problem Statement:
If SC-XRD is not an option, there is no universally accepted method for researchers to achieve crystallographic-level certainty in metal complex geometries. Consequently, the situation results in the lack of clarity around such parameters as coordination modes, structural distortions, and bonding environments, which have major impacts on reactivity, stability, and biological behaviour.

Research gap:

Though spectroscopy and DFT give good hints, still, no such combined, multi-technique structural validation framework for metal (II) Schiff base complexes that fail to crystallise exists. The limitations pointed out in the journal Applied Organometallic Chemistry demonstrate the need for a systematic, predictive, and computationally augmented protocol to validate structures by non-crystallographic methods.

Research Question:
What methods and techniques can be employed to create a multi-approach validation framework that is constantly driven by computational means and is reliable enough to decide the structures of metal (II) Schiff base complexes without the support of single-crystal X-ray diffraction?

Outcome:
The offered solution will not only make up for the PhD but will also yield an outstanding validation model that will take advantage of: high-quality spectral deconvolution (NMR, FT-IR, UV–Vis, EPR, XPS), DFT-assisted geometry optimisation and energy computation, AI algorithms for predicting coordination geometry, molecular dynamics calculations for checking structural durability, comparison with the SC-XRD data for determining trust levels.

Reference:

Sogukomerogullari, H. G., Dede, B., Sahin, D., & Akkoç, S. (2025). Comprehensive Study on Synthesis, Quantum Chemical Calculations, Molecular Modelling Studies, and Cytotoxic Activities of Metal (II) Schiff Base Complexes. Applied Organometallic Chemistry, 39(3), e70034.

5. Bridging the Computational–Experimental Divide: Advancing the Synthesis and Biological Validation of Computationally Designed Triazole-Based Xanthine Oxidase Inhibitors

The use of computational methods in drug design has been acknowledged as the most important step that allows early detection of new compounds by screening the substances with the highest therapeutic value before the expensive laboratory stages. The triazole derivatives have recently been considered the most important among the xanthine oxidase inhibitors, with the possibility of being used for the treatment of gout and hyperuricemia. The Zhang et al. (2022) study reports that the new molecular modelling study employed several methods, such as 3D-QSAR, molecular docking, MD simulations, and DFT calculations, to predict the inhibitory activity of novel triazole-based candidates. The research has shown that the designed molecules (more precisely Pred 4 and Pred 5) have good predicted activity and excellent ADMET properties, yet the project was purely computational. This brings up a constant problem in the field of computational drug discovery, whereby no experimental validation is done to back up in silico predictions, or even to demonstrate the biological activity of the compounds.

Problem Statement:
Even though computational methods have the ability to provide exact predictions of binding affinity, pharmacokinetic properties, and toxicity profiles, empirical validation is still a required step in the process. The potential of triazole drug design to be used in the treatment of gout and associated diseases remains uncertain if no synthesis and biological testing are done; thus, the development of drug candidates based on this area cannot be realised.

Research gap:

The computational discovery aspect is mentioned in the molecular modelling study, but it does not go beyond the experimental phases of synthesis, structural confirmation, and XO inhibitory assays. Consequently, the proposed compounds (Pred 4, Pred 5, and so forth) remain as predictions unconfirmed. The chasm is created by the lack of experimental proof that would confirm their biological activity, pharmacokinetic behaviour, and safety, which are exactly the steps required to establish the reliability of QSAR models, docking assessments, and MD-derived predictions.

Research Question:
What will be the procedure to synthesise, characterise, and test biologically the triazole-based XO inhibitors designed by computer to confirm their expected strength and advantages in pharmacokinetics?

Outcome:
The computational–experimental gap will be fully covered by this PhD project in the following ways: The synthesis of the most prioritised predicted inhibitors (e.g., Pred 4 and Pred 5),
 the use of spectroscopic and analytical methods for structural confirmation, the conducting of in vitro XO assays to evaluate inhibitory activity, and the use of experimental and predictive hybrid models for determining ADMET properties.

Reference:

Er-Rajy, M., El Fadili, M., Zarougui, S., Mujwar, S., Aloui, M., Zerrouk, M., … & Elhallaoui, M. (2025). Design and evaluation of novel triazole derivatives as potential anti-gout inhibitors: a comprehensive molecular modeling study. Frontiers in Chemistry, 13, 1518777.

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