AIMC Topic: Drug Design

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Comprehensive insights into carbonic anhydrase inhibition: A triad of In vitro, In silico, and In vivo perspectives.

Enzyme and microbial technology
Carbonic anhydrases (CAs) are zinc-dependent metalloenzymes essential for sustaining physiological balance by facilitating the reversible conversion of carbon dioxide to its hydrated form. Their biological significance, coupled with their involvement...

Bioactive structures for inhibitors of polymerase enzyme by artificial intelligence.

Future medicinal chemistry
AIMS: Present new bioactive compounds, created by De novo Drug Design and artificial intelligence (AI), as possible inhibitors of polymerase.

Design and Synthesis of Magnolol Derivatives Using Integrated CNNs and Pharmacophore Approaches for Enhanced Parasiticidal Activity in Aquaculture.

Journal of agricultural and food chemistry
Aquaculture is a rapidly growing sector of global food production, playing a vital role in poverty alleviation, food security, and income generation. However, it faces substantial challenges, particularly due to infections caused by the protozoan , l...

How to think about designing smart antibodies in the age of genAI: integrating biology, technology, and experience.

mAbs
Antibody discovery has been successful in designing and progressing molecules to the clinic and market based on largely empirical methods and human experience. The field is now transitioning from classical monospecific antibodies to innovative smart ...

Transforming molecular cores, substituents, and combinations into structurally diverse compounds using chemical language models.

European journal of medicinal chemistry
Transformer-based chemical language models (CLMs) were derived to generate structurally and topologically diverse embeddings of core structure fragments, substituents, or core/substituent combinations in chemically proper compounds, representing a de...

Virtual reality in drug design: Benefits, applications and industrial perspectives.

Current opinion in structural biology
Virtual reality (VR) is a tool which has transformative potential in domains which involve the visualization of complex 3D data such as structure-based drug design (SBDD), where it offers new ways to visualize and manipulate complex molecular structu...

A Specialized and Enhanced Deep Generation Model for Active Molecular Design Targeting Kinases Guided by Affinity Prediction Models and Reinforcement Learning.

Journal of chemical information and modeling
Kinases are critical regulators in numerous cellular processes, and their dysregulation is linked to various diseases, including cancer. Thus, protein kinases have emerged as major drug targets at present, with approximately a quarter to a third of g...

DiffMC-Gen: A Dual Denoising Diffusion Model for Multi-Conditional Molecular Generation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The precise and efficient design of potential drug molecules with diverse physicochemical properties has long been a critical challenge. In recent years, the emergence of various deep learning-based de novo molecular generation algorithms offered new...

Can Deep Learning Blind Docking Methods be Used to Predict Allosteric Compounds?

Journal of chemical information and modeling
Allosteric compounds offer an alternative mode of inhibition to orthosteric compounds with opportunities for selectivity and noncompetition. Structure-based drug design (SBDD) of allosteric compounds introduces complications compared to their orthost...

Role of eccentricity based topological descriptors to predict anti-HIV drugs attributes with supervised machine learning algorithms.

Computers in biology and medicine
Chemical graphs are mathematical representations of molecular structures, where atoms are represented as vertices, while chemical bonds are depicted as edges of a graph. The chemical graphs are widely used in cheminformatics to analyze molecular prop...