Mohamed Elrefaiy

Computational Chemist & Scientific Software Developer

Theoretical chemist and open-source software developer with over seven years of multidisciplinary experience in drug design, quantum chemistry, and biophysics.

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Latest Updates

A timeline of my recent publications, software releases, and milestones.

July 5, 2025

Package Release: Neural Finance v1.0

Neural Finance is a research-oriented deep learning framework for predictive modeling of financial time series. The framework integrates Long Short-Term Memory (LSTM) neural networks with technical indicators and sentiment analysis pipelines, enabling comprehensive temporal modeling of asset prices. It aims to address non-stationary characteristics of financial data, multi-scale temporal dependencies, and the integration of qualitative sentiment information, providing a platform for rigorous scientific experimentation and evaluation.

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July 1, 2025

Alprotein-Alpha v1.2 Release

Alprotein is a powerful, modern Python package for calculating site energies and electronic properties of pigment-protein complexes using the Charge Density Coupling (CDC) method. Built with a focus on accuracy, usability, and extensibility, it provides both programmatic APIs and an intuitive graphical interface for computational biophysics research.

Available upon request →

Core Expertise

Computational Biophysics & Molecular Modeling

Advanced pipelines for modeling excitation energy transfer in pigment-protein complexes, integrating quantum chemical methods with large-scale structural analysis.

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Drug Discovery & Design

Comprehensive in silico workflows for lead identification and optimization using ensemble docking, molecular scoring, and rational inhibitor design.

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Scientific Software Development

End-to-end experience building scientific software, running HPC simulations, managing cloud deployments, and developing modern full-stack web applications for research interfaces.

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Research Focus Areas

Computational Drug Design

CADD approaches for therapeutic compound discovery and optimization

Comprehensive drug discovery pipeline including virtual screening, molecular dynamics simulations, and bioinspired design for therapeutic compounds.

Key Techniques:

Virtual ScreeningEnsemble DockingMD SimulationsMM/PBSAForce Field ParameterizationStructure-Activity Analysis

Key Results:

Successfully designed 10 lankacidin derivatives with improved antitumor activity and validated binding modes through 50 ns MD simulations

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Structure-Based Modeling of Photosynthetic Light Harvesting

Physics-based Hamiltonian construction for light-harvesting complexes

Development of structure-based Hamiltonians where site energies are calculated from protein environment interactions, moving beyond random parameter fitting to provide mechanistic insight into photosynthetic function.

Key Techniques:

MCCE/CDC PipelineElectrostatic ModelsDFT/TDDFT ValidationSite Energy CalculationsProtonation State AnalysisQM/MM Methods

Key Results:

First-ever construction of structure-based Hamiltonians for CP26 and CP24 complexes with the MCCE/CDC pipeline, achieving QM-comparable accuracy in spectral predictions

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Interested in Collaboration?

I'm always excited to discuss potential research collaborations, joint projects, or consulting opportunities in computational chemistry and drug discovery.

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